Validation and quantification of uncertainty in coupled climate models using network analysis

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

Bracco, Annalisa

We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies.more » At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.« less

Reconstitution de données climatiques pour l’Algérie du Nord : application des réseaux neuronaux

NASA Astrophysics Data System (ADS)

Bouaoune, Djahida; Dahmani-Megrerouche, Malika

2010-11-01

In the present context of climate change and preservation of biodiversity, the appreciation of the vulnerability of the natural ecosystems and their capacity of adaptation appears among the main preoccupations to the world level (GIEC, 2007). This assessment of the ecosystems requires the availability of climatic data, what is often made difficult by the weak density or even the absence of meteorological stations notably, to the level of the mountains zones. In order to study the climate-vegetation relationship in North Algeria, we use an automatic interpolation method, the neural network method, for the reconstitution of climatic data of the sampled sites, (1035 phytoecological samples), from the existing meteorological network (269 stations). This method is characterized by a great suppleness of non-linearity and by its capacity for reconstituting information from partial and not well-defined indications such as the case of data provided from meteorological networks. In order to reconstitution of climatic data, we use the explicate variables, longitude, latitude and altitude, the variables to explain being the rainfall and temperatures. To define the best approach, the network calibration has been activated on climatic parameters taken globally or solely, for the whole of study zone, and by geographical sector. The results of the interpolation are expressed through a climatic parameter cartography, released automatically by the MapInfo software. The reliability results obtained by this method can be appreciated by elaboration of errors maps comparing to reference data.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

Core Curriculum in Preventing and Reducing School Violence and Vandalism. Course 3: School Climate. Participant Guide and Reference Notebook.

ERIC Educational Resources Information Center

Center for Human Services, Washington, DC.

This guide, intended for participants in the third course of the National School Resource Network Core Curriculum, contains an activity/content summary for each module of the course, worksheets, and background materials. The purpose of the course is to introduce a conceptual overview and definition of "school climate" with the goal of effecting…

Changing climates of conflict: A social network experiment in 56 schools.

PubMed

Paluck, Elizabeth Levy; Shepherd, Hana; Aronow, Peter M

2016-01-19

Theories of human behavior suggest that individuals attend to the behavior of certain people in their community to understand what is socially normative and adjust their own behavior in response. An experiment tested these theories by randomizing an anticonflict intervention across 56 schools with 24,191 students. After comprehensively measuring every school's social network, randomly selected seed groups of 20-32 students from randomly selected schools were assigned to an intervention that encouraged their public stance against conflict at school. Compared with control schools, disciplinary reports of student conflict at treatment schools were reduced by 30% over 1 year. The effect was stronger when the seed group contained more "social referent" students who, as network measures reveal, attract more student attention. Network analyses of peer-to-peer influence show that social referents spread perceptions of conflict as less socially normative.

Climate Leadership Literacy as a Component of Climate Literacy

NASA Astrophysics Data System (ADS)

Kothavala, D. L.

2014-12-01

How can the 3rd National Climate Assessment be used to go beyond climate change literacy, to include literacy in climate leadership and its improvement? The National Climate Assessment refers to "no-regrets" strategies (i.e., beneficial despite uncertainty), such as, e.g., energy efficiency, cultivating networks, and growing our adaptive capacity. As we cultivate our capacity as a species to pivot, climate leadership performance and its improvement become legitimate - and essential - realms of research, planning, and practice. However, climate leadership across sectors is not yet well-articulated; and operationalizing literacy expressed as 'what to do' may be viewed as overtly prescriptive by scientists. This talk examines approaches and illustrative examples provided in the Climate Assessment at the scale of cities, states, and firms; along with key findings from the National Academies on communicating science to decision makers; in identifying factors to enhance literacy in climate leadership and performance.

[Relationship between reference values of fibrinogen and geographical factors based on neural network analysis].

PubMed

Li, Meng-Jiao; Ge, Miao; Wang, Cong-Xia; Cen, Min-Yi; Jiang, Ji-Lin; He, Jin-Wei; Lin, Qian-Yi; Liu, Xin

2016-08-20

To analyze the relationship between the reference values of fibrinogen (FIB) in healthy Chinese adults and geographical factors to provide scientific evidences for establishing the uniform standard. The reference values of FIB of 10701 Chinese healthy adults from 103 cities were collected to investigate their relationship with 18 geographical factors including spatial index, terrain index, climate index, and soil index. Geographical factors that significantly correlated with the reference values were selected for constructing the BP neural network model. The spatial distribution map of the reference value of FIB of healthy Chinese adults was fitted by disjunctive kriging interpolation. We used the 5-layer neural network and selected 2000 times of training covering 11 hidden layers to build the simulation rule for simulating the relationship between FIB and geographical environmental factors using the MATLAB software. s The reference value of FIB in healthy Chinese adults was significantly correlated with the latitude, sunshine duration, annual average temperature, annual average relative humidity, annual precipitation, annual range of air temperature, average annual soil gravel content, and soil cation exchange capacity (silt). The artificial neural networks were created to analyze the simulation of the selected indicators of geographical factors. The spatial distribution map of the reference values of FIB in healthy Chinese adults showed a distribution pattern that FIB levels were higher in the South and lower in the North, and higher in the East and lower in the West. When the geographical factors of a certain area are known, the reference values of FIB in healthy Chinese adults can be obtained by establishing the neural network mode or plotting the spatial distribution map.

Explorations Around "Graceful Failure" in Transportation Infrastructure: Lessons Learned By the Infrastructure and Climate Network (ICNet)

NASA Astrophysics Data System (ADS)

Jacobs, J. M.; Thomas, N.; Mo, W.; Kirshen, P. H.; Douglas, E. M.; Daniel, J.; Bell, E.; Friess, L.; Mallick, R.; Kartez, J.; Hayhoe, K.; Croope, S.

2014-12-01

Recent events have demonstrated that the United States' transportation infrastructure is highly vulnerable to extreme weather events which will likely increase in the future. In light of the 60% shortfall of the $900 billion investment needed over the next five years to maintain this aging infrastructure, hardening of all infrastructures is unlikely. Alternative strategies are needed to ensure that critical aspects of the transportation network are maintained during climate extremes. Preliminary concepts around multi-tier service expectations of bridges and roads with reference to network capacity will be presented. Drawing from recent flooding events across the U.S., specific examples for roads/pavement will be used to illustrate impacts, disruptions, and trade-offs between performance during events and subsequent damage. This talk will also address policy and cultural norms within the civil engineering practice that will likely challenge the application of graceful failure pathways during extreme events.

The role of observational reference data for climate downscaling: Insights from the VALUE COST Action

NASA Astrophysics Data System (ADS)

Kotlarski, Sven; Gutiérrez, José M.; Boberg, Fredrik; Bosshard, Thomas; Cardoso, Rita M.; Herrera, Sixto; Maraun, Douglas; Mezghani, Abdelkader; Pagé, Christian; Räty, Olle; Stepanek, Petr; Soares, Pedro M. M.; Szabo, Peter

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research (http://www.value-cost.eu). A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of downscaling methods. Such assessments can be expected to crucially depend on the existence of accurate and reliable observational reference data. In dynamical downscaling, observational data can influence model development itself and, later on, model evaluation, parameter calibration and added value assessment. In empirical-statistical downscaling, observations serve as predictand data and directly influence model calibration with corresponding effects on downscaled climate change projections. We here present a comprehensive assessment of the influence of uncertainties in observational reference data and of scale-related issues on several of the above-mentioned aspects. First, temperature and precipitation characteristics as simulated by a set of reanalysis-driven EURO-CORDEX RCM experiments are validated against three different gridded reference data products, namely (1) the EOBS dataset (2) the recently developed EURO4M-MESAN regional re-analysis, and (3) several national high-resolution and quality-controlled gridded datasets that recently became available. The analysis reveals a considerable influence of the choice of the reference data on the evaluation results, especially for precipitation. It is also illustrated how differences between the reference data sets influence the ranking of RCMs according to a comprehensive set of performance measures.

Representativeness of four precipitation observational networks of China

NASA Astrophysics Data System (ADS)

Ren, Yuyu; Ren, Guoyu

2012-08-01

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm (⩽ 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the BMN because the RCN has a more homogeneous distribution of stations.

International Collaboration in the field of GNSS-Meteorology and Climate Monitoring

NASA Astrophysics Data System (ADS)

Jones, J.; Guerova, G.; Dousa, J.; Bock, O.; Elgered, G.; Vedel, H.; Pottiaux, E.; de Haan, S.; Pacione, R.; Dick, G.; Wang, J.; Gutman, S. I.; Wickert, J.; Rannat, K.; Liu, G.; Braun, J. J.; Shoji, Y.

2012-12-01

International collaboration in the field of GNSS-meteorology and climate monitoring is essential, as severe weather and climate change have no respect for national boundaries. The use of Global Navigation Satellite Systems (GNSS) for meteorological purposes is an established atmospheric observing technique, which can accurately sense water vapour, the most abundant greenhouse gas, accounting for 60-70% of atmospheric warming. Severe weather forecasting is challenging, in part due to the high temporal and spatial variation of atmospheric water vapour. Water vapour is currently under-sampled and obtaining and exploiting more high-quality humidity observations is essential to severe weather forecasting and climate monitoring. A proposed EU COST Action (http://www.cost.eu) will address new and improved capabilities from concurrent developments in both GNSS and atmospheric communities to improve (short-range) weather forecasts and climate projections. For the first time, the synergy of the three GNSS systems, GPS, GLONASS and Galileo, will be used to develop new, advanced tropospheric products, stimulating the full potential exploitation of multi-GNSS water vapour estimates on a wide range of temporal and spatial scales, from real-time severe weather monitoring and forecasting to climate research. The Action will work in close collaboration with the Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN), GNSS Precipitable Water Task Team (TT). GRUAN is a global reference observing network, designed to meet climate requirements and to fill a major void in the current global observing system. GRUAN observations will provide long-term, high-quality data to determine climatic trends and to constrain and validate data from space-based remote sensors. Ground-based GNSS PW was identified as a Priority 1 measurement for GRUAN, and the GNSS-PW TT's goal is to develop explicit guidance on hardware, software and data management practices to obtain GNSS PW measurements of consistent quality at all GRUAN sites. The GRUAN GNSS-PW TT and the proposed COST Action will look to expand the international framework already in place with the European E-GVAP programme to facilitate global collaboration to facilitate knowledge and data exchange.

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Quantifying the value of redundant measurements at GCOS Reference Upper-Air Network sites

DOE PAGES

Madonna, F.; Rosoldi, M.; Güldner, J.; ...

2014-11-19

The potential for measurement redundancy to reduce uncertainty in atmospheric variables has not been investigated comprehensively for climate observations. We evaluated the usefulness of entropy and mutual correlation concepts, as defined in information theory, for quantifying random uncertainty and redundancy in time series of the integrated water vapour (IWV) and water vapour mixing ratio profiles provided by five highly instrumented GRUAN (GCOS, Global Climate Observing System, Reference Upper-Air Network) stations in 2010–2012. Results show that the random uncertainties on the IWV measured with radiosondes, global positioning system, microwave and infrared radiometers, and Raman lidar measurements differed by less than 8%.more » Comparisons of time series of IWV content from ground-based remote sensing instruments with in situ soundings showed that microwave radiometers have the highest redundancy with the IWV time series measured by radiosondes and therefore the highest potential to reduce the random uncertainty of the radiosondes time series. Moreover, the random uncertainty of a time series from one instrument can be reduced by ~ 60% by constraining the measurements with those from another instrument. The best reduction of random uncertainty is achieved by conditioning Raman lidar measurements with microwave radiometer measurements. In conclusion, specific instruments are recommended for atmospheric water vapour measurements at GRUAN sites. This approach can be applied to the study of redundant measurements for other climate variables.« less

Deploying temporary networks for upscaling of sparse network stations

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Kelly, Victoria; Hall, Mark; Palecki, Michael A.; Temimi, Marouane

2016-10-01

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3 km and 9 km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3 km and 9 km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.

Is it feasible to estimate radiosonde biases from interlaced measurements?

NASA Astrophysics Data System (ADS)

Kremser, Stefanie; Tradowsky, Jordis S.; Rust, Henning W.; Bodeker, Greg E.

2018-05-01

Upper-air measurements of essential climate variables (ECVs), such as temperature, are crucial for climate monitoring and climate change detection. Because of the internal variability of the climate system, many decades of measurements are typically required to robustly detect any trend in the climate data record. It is imperative for the records to be temporally homogeneous over many decades to confidently estimate any trend. Historically, records of upper-air measurements were primarily made for short-term weather forecasts and as such are seldom suitable for studying long-term climate change as they lack the required continuity and homogeneity. Recognizing this, the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) has been established to provide reference-quality measurements of climate variables, such as temperature, pressure, and humidity, together with well-characterized and traceable estimates of the measurement uncertainty. To ensure that GRUAN data products are suitable to detect climate change, a scientifically robust instrument replacement strategy must always be adopted whenever there is a change in instrumentation. By fully characterizing any systematic differences between the old and new measurement system a temporally homogeneous data series can be created. One strategy is to operate both the old and new instruments in tandem for some overlap period to characterize any inter-instrument biases. However, this strategy can be prohibitively expensive at measurement sites operated by national weather services or research institutes. An alternative strategy that has been proposed is to alternate between the old and new instruments, so-called interlacing, and then statistically derive the systematic biases between the two instruments. Here we investigate the feasibility of such an approach specifically for radiosondes, i.e. flying the old and new instruments on alternating days. Synthetic data sets are used to explore the applicability of this statistical approach to radiosonde change management.

Is U.S. climatic diversity well represented within the existing federal protection network?

PubMed

Batllori, Enric; Miller, Carol; Parisien, Marc-Andre; Parks, Sean A; Moritz, Max A

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans. The conterminous United States of America (CONUS) has an extensive system of protected areas managed by federal agencies, but a comprehensive assessment of how this network represents CONUS climate is lacking. We present a quantitative classification of the climate space that is independent from the geographic locations to evaluate the climatic representation of the existing protected area network. We use this classification to evaluate the coverage of each agency's jurisdiction and to identify current conservation deficits. Our findings reveal that the existing network poorly represents CONUS climatic diversity. Although rare climates are generally well represented by the network, the most common climates are particularly underrepresented. Overall, 83% of the area of the CONUS corresponds to climates underrepresented by the network. The addition of some currently unprotected federal lands to the network would enhance the coverage of CONUS climates. However, to fully palliate current conservation deficits, large-scale private-land conservation initiatives will be critical.

Evaluating Metrics of Drainage Divide Mobility

NASA Astrophysics Data System (ADS)

Forte, A. M.; Whipple, K. X.; DiBiase, R.; Gasparini, N. M.; Ouimet, W. B.

2016-12-01

Watersheds are the fundamental organizing units in landscapes and thus the controls on drainage divide location and mobility are an essential facet of landscape evolution. Additionally, many common topographic analyses fundamentally assume that river network topology and divide locations are largely static, allowing channel profile form to be interpreted in terms of spatio-temporal patterns of rock uplift rate relative to baselevel, climate, or rock properties. Recently however, it has been suggested that drainage divides are more mobile than previously thought and that divide mobility, and resulting changes in drainage area, can potentially induce changes to fluvial topography comparable to spatio-temporal variation in rock uplift, climate, or rock properties. Ultimately, reliable metrics are needed to diagnose the mobility of divides. One such recently proposed metric is cross-divide contrasts in `chi', a measure of the current topology of the drainage network, but cross-divide contrasts in a number of topographic metrics show promise. Here we use a series of landscape evolution modeling scenarios in which we induce divide mobility under different conditions to test the utility of a suite of plausible topographic metrics of divide mobility and compare these to natural examples. Specifically, we test cross-divide contrasts in mean slope, mean local relief, channel bed elevation at a reference drainage area, and chi. Our results highlight that cross-divide contrasts in chi can only be accurately interpreted in terms of divide mobility when uplift, rock erodibility, climate, and base-level are uniform across both river networks on either side of the divide. This is problematic for application of this metric to natural landscapes as (1) uniformity of all of these parameters is exceedingly unlikely and (2) quantifying the spatial patterns of these parameters is difficult. Consequently, as shown here for both simulated and natural landscapes, simple measures of cross-divide contrasts in mean slope, mean local relief, and channel bed elevation at a reference drainage area are more robust metrics of divide mobility, correctly identifying stable or mobile divides independent of cross-divide differences in rock uplift, climate, erodibility or baselevel.

Targeting climate diversity in conservation planning to build resilience to climate change

USGS Publications Warehouse

Heller, Nicole E.; Kreitler, Jason R.; Ackerly, David; Weiss, Stuart; Recinos, Amanda; Branciforte, Ryan; Flint, Lorraine E.; Flint, Alan L.; Micheli, Elisabeth

2015-01-01

Climate change is raising challenging concerns for systematic conservation planning. Are methods based on the current spatial patterns of biodiversity effective given long-term climate change? Some conservation scientists argue that planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species, which shift in response to climate change. Climate is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We propose conservation networks that capture the full range of climatic diversity in a region will improve the resilience of biotic communities to climate change compared to networks that do not. In this study we used historical and future hydro-climate projections from the high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks we designed to capture the diversity of vegetation types. By focusing on the Conservation Lands Network (CLN) of the San Francisco Bay Area as a real-world case study, we compared the potential resilience of networks by examining two factors: the range of climate space captured, and climatic stability to 18 future climates, reflecting different emission scenarios and global climate models. We found that the climate-based network planned at the sub-regional scale captured a greater range of climate space and showed higher climatic stability than the vegetation and regional based-networks. At the same time, differences among network scenarios are small relative to the variance in climate stability across global climate models. Across different projected futures, topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning improves the likely resilience of biodiversity to climate change. We used these analyses to suggest new conservation priorities for the San Francisco Bay Area.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

NASA Astrophysics Data System (ADS)

Coopersmith, Evan J.; Cosh, Michael H.; Bell, Jesse E.; Boyles, Ryan

2016-12-01

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m3/m3. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m3/m3 when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m3/m3 was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m3/m3 was possible.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

The new WegenerNet climate station network web portal - A gateway to over 10 years of high-resolution precipitation data

NASA Astrophysics Data System (ADS)

Fuchsberger, Jürgen; Kirchengast, Gottfried; Bichler, Christoph; Kabas, Thomas; Lenz, Gunther; Leuprecht, Armin

2017-04-01

The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 153 meteorological stations measuring temperature, humidity, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007. Detailed information is available in the recent description by Kirchengast et al. (2014) and via www.wegcenter.at/wegenernet. As a smaller "sister network" of the WegenerNet Feldbach region, the WegenerNet Johnsbachtal consists of eleven meteorological stations (complemented by one hydrographic station at the Johnsbach creek), measuring temperature, humidity, precipitation, radiation, wind, and other parameters in an alpine setting at altitudes ranging from below 700 m to over 2100 m. Data are available partly since 2007, partly since more recent dates and have a temporal resolution of 10 minutes. The networks are set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of radar and satellite data, study of orography-climate relationships, and many others. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near-real time (data latency less than 1-2 h) for visualization and download via a data portal (www.wegenernet.org). This data portal has been undergoing a complete renewal over the last year, and now serves as a modern gateway to the WegenerNet's more than 10 years of high-resolution data. The poster gives a brief introduction to the WegenerNet design and setup and shows a detailed overview of the new data portal. It also focuses on showing examples for high-resolution precipitation measurements, especially heavy-precipitation and convective events. Reference: Kirchengast, G., T. Kabas, A. Leuprecht, C. Bichler, and H. Truhetz (2014): WegenerNet: A pioneering high-resolution network for monitoring weather and climate. Bull. Amer. Meteor. Soc., 95, 227-242, doi:10.1175/BAMS-D-11-00161.1.

Constructing regional climate networks in the Amazonia during recent drought events.

PubMed

Guo, Heng; Ramos, Antônio M T; Macau, Elbert E N; Zou, Yong; Guan, Shuguang

2017-01-01

Climate networks are powerful approaches to disclose tele-connections in climate systems and to predict severe climate events. Here we construct regional climate networks from precipitation data in the Amazonian region and focus on network properties under the recent drought events in 2005 and 2010. Both the networks of the entire Amazon region and the extreme networks resulted from locations severely affected by drought events suggest that network characteristics show slight difference between the two drought events. Based on network degrees of extreme drought events and that without drought conditions, we identify regions of interest that are correlated to longer expected drought period length. Moreover, we show that the spatial correlation length to the regions of interest decayed much faster in 2010 than in 2005, which is because of the dual roles played by both the Pacific and Atlantic oceans. The results suggest that hub nodes in the regional climate network of Amazonia have fewer long-range connections when more severe drought conditions appeared in 2010 than that in 2005.

Accuracy assessment of NOAA gridded daily reference evapotranspiration for the Texas High Plains

USGS Publications Warehouse

Moorhead, Jerry; Gowda, Prasanna H.; Hobbins, Michael; Senay, Gabriel; Paul, George; Marek, Thomas; Porter, Dana

2015-01-01

The National Oceanic and Atmospheric Administration (NOAA) provides daily reference evapotranspiration (ETref) maps for the contiguous United States using climatic data from North American Land Data Assimilation System (NLDAS). This data provides large-scale spatial representation of ETref, which is essential for regional scale water resources management. Data used in the development of NOAA daily ETref maps are derived from observations over surfaces that are different from short (grass — ETos) or tall (alfalfa — ETrs) reference crops, often in nonagricultural settings, which carries an unknown discrepancy between assumed and actual conditions. In this study, NOAA daily ETos and ETrs maps were evaluated for accuracy, using observed data from the Texas High Plains Evapotranspiration (TXHPET) network. Daily ETos, ETrs and the climatic data (air temperature, wind speed, and solar radiation) used for calculating ETref were extracted from the NOAA maps for TXHPET locations and compared against ground measurements on reference grass surfaces. NOAA ETrefmaps generally overestimated the TXHPET observations (1.4 and 2.2 mm/day ETos and ETrs, respectively), which may be attributed to errors in the NLDAS modeled air temperature and wind speed, to which reference ETref is most sensitive. Therefore, a bias correction to NLDAS modeled air temperature and wind speed data, or adjustment to the resulting NOAA ETref, may be needed to improve the accuracy of NOAA ETref maps.

Changing climates of conflict: A social network experiment in 56 schools

PubMed Central

Paluck, Elizabeth Levy; Shepherd, Hana; Aronow, Peter M.

2016-01-01

Theories of human behavior suggest that individuals attend to the behavior of certain people in their community to understand what is socially normative and adjust their own behavior in response. An experiment tested these theories by randomizing an anticonflict intervention across 56 schools with 24,191 students. After comprehensively measuring every school’s social network, randomly selected seed groups of 20–32 students from randomly selected schools were assigned to an intervention that encouraged their public stance against conflict at school. Compared with control schools, disciplinary reports of student conflict at treatment schools were reduced by 30% over 1 year. The effect was stronger when the seed group contained more “social referent” students who, as network measures reveal, attract more student attention. Network analyses of peer-to-peer influence show that social referents spread perceptions of conflict as less socially normative. PMID:26729884

A strategic outlook for coordination of ground-based measurement networks of atmospheric state variables and atmospheric composition

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Thorne, P.; Braathen, G.; De Maziere, M.; Thompson, A. M.; Kurylo, M. J., III

2016-12-01

There are a number of ground-based global observing networks that collectively aim to make key measurements of atmospheric state variables and atmospheric chemical composition. These networks include, but are not limited to:NDACC: Network for the Detection of Atmospheric Composition Change GUAN: GCOS Upper Air Network GRUAN: GCOS Reference Upper Air Network EARLINET: the European Aerosol Research Lidar Network GAW: Global Atmosphere Watch SHADOZ: Southern Hemisphere ADditional OZonesondes TCCON: Total Carbon Column Observing Network BSRN: Baseline Surface Radiation Network While each network brings unique capabilities to the global observing system, there are many instances where the activities and capabilities of the networks overlap. These commonalities across multiple networks can confound funding agencies when allocating scarce financial resources. Overlaps between networks may also result in some duplication of effort and a resultant sub-optimal use of funding resource for the global observing system. While some degree of overlap is useful for quality assurance, it is essential to identify the degree to which one network can take on a specific responsibility on behalf of all other networks to avoid unnecessary duplication, to identify where expertise in any one network may serve other networks, and to develop a long-term strategy for the evolution of these networks that clarifies to funding agencies where new investment is required. This presentation will briefly summarise the key characteristics of each network listed above, adopt a matrix approach to identify commonalities and, in particular, where there may be a danger of duplication of effort, and where gaps between the networks may be compromising the services that these networks are expected to collectively deliver to the global atmospheric and climate science research communities. The presentation will also examine where sharing of data and tools between networks may result in a more efficient delivery of records of essential climate variables to the global research community. There are aspects of underpinning research that are needed across all of these networks, such as laboratory spectroscopy, that often do not receive the attention they deserve. The presentation will also seek to identify where that underpinning research is lacking.

Transformational leadership and group interaction as climate antecedents: a social network analysis.

PubMed

Zohar, Dov; Tenne-Gazit, Orly

2008-07-01

In order to test the social mechanisms through which organizational climate emerges, this article introduces a model that combines transformational leadership and social interaction as antecedents of climate strength (i.e., the degree of within-unit agreement about climate perceptions). Despite their longstanding status as primary variables, both antecedents have received limited empirical research. The sample consisted of 45 platoons of infantry soldiers from 5 different brigades, using safety climate as the exemplar. Results indicate a partially mediated model between transformational leadership and climate strength, with density of group communication network as the mediating variable. In addition, the results showed independent effects for group centralization of the communication and friendship networks, which exerted incremental effects on climate strength over transformational leadership. Whereas centralization of the communication network was found to be negatively related to climate strength, centralization of the friendship network was positively related to it. Theoretical and practical implications are discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Human Impacts and Climate Change Influence Nestedness and Modularity in Food-Web and Mutualistic Networks.

PubMed

Takemoto, Kazuhiro; Kajihara, Kosuke

2016-01-01

Theoretical studies have indicated that nestedness and modularity-non-random structural patterns of ecological networks-influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.

Landscape Conservation Cooperatives: Creating a Collaborative Conservation Vision in the Face of Climate Change Uncertainty

NASA Astrophysics Data System (ADS)

Athearn, N.; Schlafmann, D.

2015-12-01

The 22 Landscape Conservation Cooperatives (LCCs) form a "network of networks," each defined by the characteristics of its ecoregion and its unique community of conservation managers, practitioners, and scientists. As self-directed partnerships, LCCs are strongly influenced not only by the landscape but by the evolving cultures and values that define the multi-faceted relationships between people and place. LCCs maintain an ecologically connected network across these diverse landscapes by transcending borders and leveraging resources. Natural resource managers are challenged to make decisions in the face of multiple uncertainties, and several partners across the network have recognized that climate change is one important uncertainty that spans boundaries - both across the conservation community and beyond. The impacts of climate change across the LCC Network are likely to be as diverse as the network itself - manifesting as, for example, sea level rise, ocean acidification, loss of sea ice, and shifts in climate patterns and timing - but synergies are being leveraged within and between LCCs and national climate-focused programs to systematically address the needs of the network to support a collaborative conservation vision that addresses multiple landscape-scale stressors in the face of climate uncertainties. This vision is being achieved by leveraging the convening power of the LCCs and collaborating with DOI Climate Science Centers and others. Selected case studies will demonstrate how the network finds strength in its differences, but also reveals powerful collaborative opportunities through integrated science, shared conservation strategies, and strategic approaches for translating targeted science to conservation action. These examples exemplify past successes as well as ongoing efforts as the network continues to bring about effective application of climate science to achieve conservation outcomes across the LCC Network in an uncertain future climate.

Percolation Features on Climate Network under Attacks of El Niño Events

NASA Astrophysics Data System (ADS)

Lu, Z.

2015-12-01

Percolation theory under different attacks is one of the main research areas in complex networks but never be applied to investigate climate network. In this study, for the first time we construct a climate network of surface air temperature field to analyze its percolation features. Here, we regard El Niño event as a kind of naturally attacks generated from Pacific Ocean to attack its upper climate network. We find that El Niño event leads an abrupt percolation phase transition to the climate network which makes it splitting and unstable suddenly. Comparing the results of the climate network under three different forms of attacks, including most connected attack (MA), localized attack (LA) and random attack (RA) respectively, it is found that both MA and LA lead first-order transition and RA leads second-order transition to the climate network. Furthermore, we find that most real attacks consist of all these three forms of attacks. With El Niño event emerging, the ratios of LA and MA increase and dominate the style of attack while RA decreasing. It means the percolation phase transition due to El Niño events is close to first-order transition mostly affected by LA and MA. Our research may help us further understand two questions from perspective of percolation on network: (1) Why not all warming in Pacific Ocean but El Niño events could affect the climate. (2) Why the climate affected by El Niño events changes abruptly.

Increasing Susceptibility of the Global Network of Food Trade to Climate Disturbances

NASA Astrophysics Data System (ADS)

Puma, M. J.; Bose, S.; Chon, S.; Cook, B.

2013-12-01

Globalization of agriculture through trade liberalization has led to a dramatic transformation of the global network of food trade. The many benefits of this globalization include greater and more efficient global agricultural production, reduced variability of regional and global food supplies, and savings in global water resources. However, a potential hidden cost is an increasingly fragile network that is more susceptible to shocks or disruptions. Recent studies suggest that complex systems, like the global food trade network, may have architectural features typically associated with the existence of tipping points and susceptibility to collapse. Here we present evidence that this global agricultural network is increasingly connected, homogeneous, and in a state where network nodes (here countries) can flip between alternate states. We use production and trade data from 1986 to 2009 to identify shifts in national self sufficiency and to quantify changes in connectivity and homogeneity of the wheat, maize and rice trade. We then simulate the possible impacts of climate and crop-disease disruptions, which could potentially trigger a global food crisis through an export-restriction-induced domino effect. Changes in self-sufficiency ratio (SSR) over time for various country groups. The SSR is computed based on production and trade of cereals and starchy roots. (Top row) Time series of SSR for the Group of Eight + Five (G8+5) countries. The '+ Five' refers to the five leading emerging economies in the world. (Bottom row) Boxplots of average SSR over two periods (1986-1990 and 2005-2009) for countries designated as 'Annex I' and 'Least Developed Countries' (LDC) by the United Nations.

Linking Climate Risk, Policy Networks and Adaptation Planning in Public Lands

NASA Astrophysics Data System (ADS)

Lubell, M.; Schwartz, M.; Peters, C.

2014-12-01

Federal public land management agencies in the United States have engaged a variety of planning efforts to address climate adaptation. A major goal of these efforts is to build policy networks that enable land managers to access information and expertise needed for responding to local climate risks. This paper investigates whether the perceived and modeled climate risk faced by different land managers is leading to larger networks or more participating in climate adaptation. In theory, the benefits of climate planning networks are larger when land managers are facing more potential changes. The basic hypothesis is tested with a survey of public land managers from hundreds of local and regional public lands management units in the Southwestern United States, as well as other stakeholders involved with climate adaptation planning. All survey respondents report their perceptions of climate risk along a variety of dimensions, as well as their participation in climate adaptation planning and information sharing networks. For a subset of respondents, we have spatially explicity GIS data about their location, which will be linked with downscaled climate model data. With the focus on climate change, the analysis is a subset of the overall idea of linking social and ecological systems.

The EASTNET Project: Extending the Network of Climate-Sensitive Tree-Ring Chronologies From the Eastern United States for Reconstructing the Spatio-Temporal Characteristics of Climate and Drought Over the Past Millennium

NASA Astrophysics Data System (ADS)

Buckley, B. M.; Cook, E. R.

2002-12-01

Recently, a network of gridded PDSI reconstructions for the contiguous United States was produced, based on the available network of drought-sensitive tree-ring chronologies (Cook et al. 1999). Analyses were constrained to the common period of 1700 - 1979 due to the limitations of the available tree-ring data. While several chronologies from the western U.S. span 1,000 years or more, very few chronologies from the eastern U.S. covered even the past 500 years. The objective of this project, funded by the National Science Foundation's ESH program, is to extend the tree-ring chronology network from the eastern U.S. with chronologies spanning the past 500-1,000 years. This aim is being achieved by sampling in areas that have escaped the effects of development, logging and major disturbance such as fire. The two main target species are Thuja occidentalis (eastern white cedar) and Juniperus virginiana (eastern red cedar). The primary terrain types are on cliffs, rocky outcrops, and other areas that have been difficult to access. We have already developed chronologies from Wisconsin, New Hampshire, Pennsylvania, West Virginia, and Virginia that span from 500 to 1500 years. The temporal depth of these chronologies is being extended through the exploitation of "sub-fossil" wood found at these sites, in the form of standing-dead stems and downed and buried logs. We are also currently pursuing leads in Maine, Vermont, Massachusetts, Connecticut, New York, New Jersey Pennsylvania, Kentucky and North Carolina where old cedar trees have either been reported or where terrain types match criteria developed for this project. In this paper we discuss the current status of the network, and explore the spatio-temporal characteristics of climate and drought across the eastern US for the past 500 years and more. We use our preliminary network to explore the regional expression of climate anomalies such as drought. Our analyses so far demonstrates multicentennial variability suggestive of Medieval Warm Period (MWP) and Little Ice Age (LIA) type signatures from an eastern red cedar chronology from West Virginia that spans the past 1,500 years. This is the oldest chronology so far developed from this project, though we anticipate the development of several more millennial length time-series within the next year. References Cook, E.R., Meko, D.M., Stahle, D.W., and Cleaveland, M.K. 1999. Drought reconstructions for the continental United States. Journal of Climate 12:1145-1162.

Integration of Model-Based Estimation Theory With an Adaptive Finite Volume Method for the Detection of a Moving Gaseous Source via a Mobile Sensor

DTIC Science & Technology

2012-02-29

couples the estimation scheme with the computational scheme, using one to enhance the other. Numerically, this switching changes several of the matrices...2011. 11. M.A. Demetriou, Enforcing and enhancing consensus of spatially distributed filters utilizing mobile sensor networks, Proceedings of the 49th...expected May, 2012. References [1] J. H. Seinfeld and S. N. Pandis, Atmospheric Chemistry and Physics: From Air Pollution to Climate Change. New York

Evaporation from weighing precipitation gauges: impacts on automated gauge measurements and quality assurance methods

NASA Astrophysics Data System (ADS)

Leeper, R. D.; Kochendorfer, J.

2015-06-01

Evaporation from a precipitation gauge can cause errors in the amount of measured precipitation. For automated weighing-bucket gauges, the World Meteorological Organization (WMO) suggests the use of evaporative suppressants and frequent observations to limit these biases. However, the use of evaporation suppressants is not always feasible due to environmental hazards and the added cost of maintenance, transport, and disposal of the gauge additive. In addition, research has suggested that evaporation prior to precipitation may affect precipitation measurements from auto-recording gauges operating at sub-hourly frequencies. For further evaluation, a field campaign was conducted to monitor evaporation and its impacts on the quality of precipitation measurements from gauges used at U.S. Climate Reference Network (USCRN) stations. Two Geonor gauges were collocated, with one gauge using an evaporative suppressant (referred to as Geonor-NonEvap) and the other with no suppressant (referred to as Geonor-Evap) to evaluate evaporative losses and evaporation biases on precipitation measurements. From June to August, evaporative losses from the Geonor-Evap gauge exceeded accumulated precipitation, with an average loss of 0.12 mm h-1. The impact of evaporation on precipitation measurements was sensitive to the choice of calculation method. In general, the pairwise method that utilized a longer time series to smooth out sensor noise was more sensitive to gauge evaporation (-4.6% bias with respect to control) than the weighted-average method that calculated depth change over a smaller window (<+1% bias). These results indicate that while climate and gauge design affect gauge evaporation rates, computational methods also influence the magnitude of evaporation biases on precipitation measurements. This study can be used to advance quality insurance (QA) techniques used in other automated networks to mitigate the impact of evaporation biases on precipitation measurements.

SDCLIREF - A sub-daily gridded reference dataset

NASA Astrophysics Data System (ADS)

Wood, Raul R.; Willkofer, Florian; Schmid, Franz-Josef; Trentini, Fabian; Komischke, Holger; Ludwig, Ralf

2017-04-01

Climate change is expected to impact the intensity and frequency of hydrometeorological extreme events. In order to adequately capture and analyze extreme rainfall events, in particular when assessing flood and flash flood situations, data is required at high spatial and sub-daily resolution which is often not available in sufficient density and over extended time periods. The ClimEx project (Climate Change and Hydrological Extreme Events) addresses the alteration of hydrological extreme events under climate change conditions. In order to differentiate between a clear climate change signal and the limits of natural variability, unique Single-Model Regional Climate Model Ensembles (CRCM5 driven by CanESM2, RCP8.5) were created for a European and North-American domain, each comprising 50 members of 150 years (1951-2100). In combination with the CORDEX-Database, this newly created ClimEx-Ensemble is a one-of-a-kind model dataset to analyze changes of sub-daily extreme events. For the purpose of bias-correcting the regional climate model ensembles as well as for the baseline calibration and validation of hydrological catchment models, a new sub-daily (3h) high-resolution (500m) gridded reference dataset (SDCLIREF) was created for a domain covering the Upper Danube and Main watersheds ( 100.000km2). As the sub-daily observations lack a continuous time series for the reference period 1980-2010, the need for a suitable method to bridge the gap of the discontinuous time series arouse. The Method of Fragments (Sharma and Srikanthan (2006); Westra et al. (2012)) was applied to transform daily observations to sub-daily rainfall events to extend the time series and densify the station network. Prior to applying the Method of Fragments and creating the gridded dataset using rigorous interpolation routines, data collection of observations, operated by several institutions in three countries (Germany, Austria, Switzerland), and the subsequent quality control of the observations was carried out. Among others, the quality control checked for steps, extensive dry seasons, temporal consistency and maximum hourly values. The resulting SDCLIREF dataset provides a robust precipitation reference for hydrometeorological applications in unprecedented high spatio-temporal resolution. References: Sharma, A.; Srikanthan, S. (2006): Continuous Rainfall Simulation: A Nonparametric Alternative. In: 30th Hydrology and Water Resources Symposium 4-7 December 2006, Launceston, Tasmania. Westra, S.; Mehrotra, R.; Sharma, A.; Srikanthan, R. (2012): Continuous rainfall simulation. 1. A regionalized subdaily disaggregation approach. In: Water Resour. Res. 48 (1). DOI: 10.1029/2011WR010489.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network.

PubMed

Batllori, Enric; Parisien, Marc-André; Parks, Sean A; Moritz, Max A; Miller, Carol

2017-08-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform a continent-wide climate change vulnerability assessment whereby we compare the baseline climate of the protected area network in North America (Canada, United States, México-NAM) to the projected end-of-century climate (2071-2100). We estimated the projected pace at which climatic conditions may redistribute across NAM (i.e., climate velocity), and identified future nearest climate analogs to quantify patterns of climate relocation within, among, and outside protected areas. Also, we interpret climatic relocation patterns in terms of associated land-cover types. Our analysis suggests that the conservation capacity of the NAM protection network is likely to be severely compromised by a changing climate. The majority of protected areas (~80%) might be exposed to high rates of climate displacement that could promote important shifts in species abundance or distribution. A small fraction of protected areas (<10%) could be critical for future conservation plans, as they will host climates that represent analogs of conditions currently characterizing almost a fifth of the protected areas across NAM. However, the majority of nearest climatic analogs for protected areas are in nonprotected locations. Therefore, unprotected landscapes could pose additional threats, beyond climate forcing itself, as sensitive biota may have to migrate farther than what is prescribed by the climate velocity to reach a protected area destination. To mitigate future threats to the conservation capacity of the NAM protected area network, conservation plans will need to capitalize on opportunities provided by the existing availability of natural land-cover types outside the current network of NAM protected areas. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Ecological networks are more sensitive to plant than to animal extinction under climate change

PubMed Central

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D. Matthias; Dormann, Carsten F.; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N.; Wiemers, Martin; Hof, Christian

2016-01-01

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks. PMID:28008919

Ecological networks are more sensitive to plant than to animal extinction under climate change.

PubMed

Schleuning, Matthias; Fründ, Jochen; Schweiger, Oliver; Welk, Erik; Albrecht, Jörg; Albrecht, Matthias; Beil, Marion; Benadi, Gita; Blüthgen, Nico; Bruelheide, Helge; Böhning-Gaese, Katrin; Dehling, D Matthias; Dormann, Carsten F; Exeler, Nina; Farwig, Nina; Harpke, Alexander; Hickler, Thomas; Kratochwil, Anselm; Kuhlmann, Michael; Kühn, Ingolf; Michez, Denis; Mudri-Stojnić, Sonja; Plein, Michaela; Rasmont, Pierre; Schwabe, Angelika; Settele, Josef; Vujić, Ante; Weiner, Christiane N; Wiemers, Martin; Hof, Christian

2016-12-23

Impacts of climate change on individual species are increasingly well documented, but we lack understanding of how these effects propagate through ecological communities. Here we combine species distribution models with ecological network analyses to test potential impacts of climate change on >700 plant and animal species in pollination and seed-dispersal networks from central Europe. We discover that animal species that interact with a low diversity of plant species have narrow climatic niches and are most vulnerable to climate change. In contrast, biotic specialization of plants is not related to climatic niche breadth and vulnerability. A simulation model incorporating different scenarios of species coextinction and capacities for partner switches shows that projected plant extinctions under climate change are more likely to trigger animal coextinctions than vice versa. This result demonstrates that impacts of climate change on biodiversity can be amplified via extinction cascades from plants to animals in ecological networks.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Evaluation of Daily Extreme Precipitation Derived From Long-term Global Satellite Quantitative Precipitation Estimates (QPEs)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Nickl, E.; Ferraro, R. R.

2017-12-01

This study evaluates the ability of different satellite-based precipitation products to capture daily precipitation extremes over the entire globe. The satellite products considered are the datasets belonging to the Reference Environmental Data Records (REDRs) program (PERSIANN-CDR, GPCP, CMORPH, AMSU-A,B, Hydrologic bundle). Those products provide long-term global records of daily adjusted Quantitative Precipitation Estimates (QPEs) that range from 20-year (CMORPH-CDR) to 35-year (PERSIANN-CDR, GPCP) record of daily adjusted global precipitation. The AMSU-A,B, Hydro-bundle is an 11-year record of daily rain rate over land and ocean, snow cover and surface temperature over land, and sea ice concentration, cloud liquid water, and total precipitable water over ocean among others. The aim of this work is to evaluate the ability of the different satellite QPE products to capture daily precipitation extremes. This evaluation will also include comparison with in-situ data sets at the daily scale from the Global Historical Climatology Network (GHCN-Daily), the Global Precipitation Climatology Centre (GPCC) gridded full data daily product, and the US Climate Reference Network (USCRN). In addition, while the products mentioned above only provide QPEs, the AMSU-A,B hydro-bundle provides additional hydrological information (precipitable water, cloud liquid water, snow cover, sea ice concentration). We will also present an analysis of those additional variables available from global satellite measurements and their relevance and complementarity in the context of long-term hydrological and climate studies.

Species-free species distribution models describe macroecological properties of protected area networks.

PubMed

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Network Connectedness, Sense of Community, and Risk Perception of Climate Change Professionals in the Pacific Islands Region

NASA Astrophysics Data System (ADS)

Corlew, L. K.; Keener, V. W.; Finucane, M.

2013-12-01

The Pacific Regional Integrated Sciences and Assessments (Pacific RISA) Program conducted social network analysis research of climate change professionals (broadly defined) who are from or work in Hawaii and the U.S.-Affiliated Pacific Islands (USAPI) region. This study is supported by the National Oceanic and Atmospheric Administration (NOAA) and the Pacific Islands Climate Science Center (PICSC) to address an identified need for a resource that quantifies the region's collaborative network of climate change professionals, and that supports the further development of cross-regional and inter-sectoral collaborations for future research and adaptation activities. A survey was distributed to nearly 1,200 people who are from and/or work in climate change related fields in the region. The Part One Survey questions (not confidential) created a preferential attachment network by listing major players in Hawaii and the USAPI, with additional open fields to identify important contacts in the greater professional network. Participants (n=340) identified 975 network contacts and frequency of communications (weekly, monthly, seasonally, yearly, at least once ever). Part Two Survey questions (confidential, n=302) explored climate change risk perceptions, Psychological Sense of Community (PSOC), sense of control over climate change impacts, sense of responsibility to act, policy beliefs and preferences regarding climate change actions, concern and optimism scales about specific impacts, and demographic information. Graphical representations of the professional network are being developed for release in September 2013 as a free online tool to promote and assist collaboration building among climate professionals in the region. The graphs are partitioned according to network 'hubs' (high centrality), participant location, and profession to clearly identify network strengths and opportunities for future collaborations across spatial and professional boundaries. For additional analyses, scores are assigned for participant degree centrality, betweenness centrality, and Eigenvector centrality from the Part One Survey, as well as PSOC, control, responsibility, risk perceptions, concern, optimism, and policy preferences from the Part Two Survey. Statistical interaction analyses explore factors motivating connectedness within the network, as well as climate change research and adaptation needs and priorities of participants.

Paleo-environmental Perspectives on Climate-change Monitoring in the National Parks of the Northern U.S. Rocky Mountains

NASA Astrophysics Data System (ADS)

Gray, S. T.; Graumlich, L. J.; Pederson, G. T.; Fagre, D. B.; Betancourt, J. L.; Norris, J. R.; Jackson, S. T.

2004-12-01

In the face of growing visitation, encroaching development and a changing climate, the United States National Park Service has initiated a nationwide program to inventory and monitor the resources it protects. The foundation for this initiative lies in the development of baseline or reference datasets for physical and biological systems within each park unit. In a series of paleo-proxy studies from the Greater Yellowstone and Glacier National Park regions, we demonstrate that most instrumental and observational records are too short to capture a significant portion of the climatic and ecological variability that might be expected in the parks of the northern U.S. Rockies. Networks of tree-ring based temperature and precipitation reconstructions spanning the last ~1,000 yr demonstrate that the climates of these regions are not stationary. These climates are instead characterized by strong regime-like behavior over decadal to multidecadal timescales. Complimentary studies of past plant-community and landscape dynamics show how such lower-frequency variability can have a profound impact on vital park resources and amenities. In the eastern Yellowstone region, for example, persistent (20-30 yr) wet/cool periods in the 19th and early 20th centuries led to widespread recruitment of woody plants, and the legacy of these recruitment events still persists in the structure of many woodlands and forests. Studies of fossil packrat middens also suggest that at least some recent woody-plant encroachment and densification- a major management concern in the region- is related to plant late-Holocene plant migration dynamics and population processes rather than changing climate and land-use. Though the timing and effects of such events may differ, similar ecological responses to decadal/multidecadal climate variability are seen in the Glacier National Park region. In combination these studies serve to emphasize the need for careful selection of reference periods and baseline conditions used in climate-change monitoring, and this work shows the invaluable role that paleo-environmental archives can play in natural resource management. Overall, a more complete knowledge of long-duration ecological processes and lower-frequency climate variability should influence how we monitor and manage climate-change impacts throughout the northern Rockies.

Towards a Community Environmental Observation Network

NASA Astrophysics Data System (ADS)

Mertl, Stefan; Lettenbichler, Anton

2014-05-01

The Community Environmental Observation Network (CEON) is dedicated to the development of a free sensor network to collect and distribute environmental data (e.g. ground shaking, climate parameters). The data collection will be done with contributions from citizens, research institutions and public authorities like communities or schools. This will lead to a large freely available data base which can be used for public information, research, the arts,..... To start a free sensor network, the most important step is to provide easy access to free data collection and -distribution tools. The initial aims of the project CEON are dedicated to the development of these tools. A high quality data logger based on open hardware and free software is developed and a software suite of already existing free software for near-real time data communication and data distribution over the Internet will be assembled. Foremost, the development focuses on the collection of data related to the deformation of the earth (such as ground shaking, surface displacement of mass movements and glaciers) and the collection of climate data. The extent to other measurements will be considered in the design. The data logger is built using open hardware prototyping platforms like BeagleBone Black and Arduino. Main features of the data logger are: a 24Bit analog-to-digital converter; a GPS module for time reference and positioning; wireless mesh networking using Optimized Link State Routing; near real-time data transmission and communication; and near real-time differential GNSS positioning using the RTKLIB software. The project CEON is supported by the Internet Foundation Austria (IPA) within the NetIdee 2013 call.

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.

Long-term observations of tropospheric particle number size distributions and equivalent black carbon mass concentrations in the German Ultrafine Aerosol Network (GUAN)

NASA Astrophysics Data System (ADS)

Birmili, W.; Weinhold, K.; Merkel, M.; Rasch, F.; Sonntag, A.; Wiedensohler, A.; Bastian, S.; Schladitz, A.; Löschau, G.; Cyrys, J.; Pitz, M.; Gu, J.; Kusch, T.; Flentje, H.; Quass, U.; Kaminski, H.; Kuhlbusch, T. A. J.; Meinhardt, F.; Schwerin, A.; Bath, O.; Ries, L.; Wirtz, K.; Fiebig, M.

2015-11-01

The German Ultrafine Aerosol Network (GUAN) is a cooperative atmospheric observation network, which aims at improving the scientific understanding of aerosol-related effects in the troposphere. The network addresses research questions dedicated to both, climate and health related effects. GUAN's core activity has been the continuous collection of tropospheric particle number size distributions and black carbon mass concentrations at seventeen observation sites in Germany. These sites cover various environmental settings including urban traffic, urban background, rural background, and Alpine mountains. In association with partner projects, GUAN has implemented a high degree of harmonisation of instrumentation, operating procedures, and data evaluation procedures. The quality of the measurement data is assured by laboratory intercomparisons as well as on-site comparisons with reference instruments. This paper describes the measurement sites, instrumentation, quality assurance and data evaluation procedures in the network as well as the EBAS repository, where the data sets can be obtained (doi:10.5072/guan).

Long-term observations of tropospheric particle number size distributions and equivalent black carbon mass concentrations in the German Ultrafine Aerosol Network (GUAN)

NASA Astrophysics Data System (ADS)

Birmili, Wolfram; Weinhold, Kay; Rasch, Fabian; Sonntag, André; Sun, Jia; Merkel, Maik; Wiedensohler, Alfred; Bastian, Susanne; Schladitz, Alexander; Löschau, Gunter; Cyrys, Josef; Pitz, Mike; Gu, Jianwei; Kusch, Thomas; Flentje, Harald; Quass, Ulrich; Kaminski, Heinz; Kuhlbusch, Thomas A. J.; Meinhardt, Frank; Schwerin, Andreas; Bath, Olaf; Ries, Ludwig; Gerwig, Holger; Wirtz, Klaus; Fiebig, Markus

2016-08-01

The German Ultrafine Aerosol Network (GUAN) is a cooperative atmospheric observation network, which aims at improving the scientific understanding of aerosol-related effects in the troposphere. The network addresses research questions dedicated to both climate- and health-related effects. GUAN's core activity has been the continuous collection of tropospheric particle number size distributions and black carbon mass concentrations at 17 observation sites in Germany. These sites cover various environmental settings including urban traffic, urban background, rural background, and Alpine mountains. In association with partner projects, GUAN has implemented a high degree of harmonisation of instrumentation, operating procedures, and data evaluation procedures. The quality of the measurement data is assured by laboratory intercomparisons as well as on-site comparisons with reference instruments. This paper describes the measurement sites, instrumentation, quality assurance, and data evaluation procedures in the network as well as the EBAS repository, where the data sets can be obtained (doi:10.5072/guan).

Extensive validation of CM SAF surface radiation products over Europe.

PubMed

Urraca, Ruben; Gracia-Amillo, Ana M; Koubli, Elena; Huld, Thomas; Trentmann, Jörg; Riihelä, Aku; Lindfors, Anders V; Palmer, Diane; Gottschalg, Ralph; Antonanzas-Torres, Fernando

2017-09-15

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m 2 , whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

A hybrid-domain approach for modeling climate data time series

NASA Astrophysics Data System (ADS)

Wen, Qiuzi H.; Wang, Xiaolan L.; Wong, Augustine

2011-09-01

In order to model climate data time series that often contain periodic variations, trends, and sudden changes in mean (mean shifts, mostly artificial), this study proposes a hybrid-domain (HD) algorithm, which incorporates a time domain test and a newly developed frequency domain test through an iterative procedure that is analogue to the well known backfitting algorithm. A two-phase competition procedure is developed to address the confounding issue between modeling periodic variations and mean shifts. A variety of distinctive features of climate data time series, including trends, periodic variations, mean shifts, and a dependent noise structure, can be modeled in tandem using the HD algorithm. This is particularly important for homogenization of climate data from a low density observing network in which reference series are not available to help preserve climatic trends and long-term periodic variations, preventing them from being mistaken as artificial shifts. The HD algorithm is also powerful in estimating trend and periodicity in a homogeneous data time series (i.e., in the absence of any mean shift). The performance of the HD algorithm (in terms of false alarm rate and hit rate in detecting shifts/cycles, and estimation accuracy) is assessed via a simulation study. Its power is further illustrated through its application to a few climate data time series.

The Climate Literacy and Energy Awareness Network (CLEAN) - Enabling Collective Impact on Climate and Energy Literacy

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Gold, A. U.; Niepold, F., III

2015-12-01

Numerous climate change education efforts exist that aim to enable citizens and society to make informed decisions addressing environmental and societal issues arising from climate change. To extend the reach and impact of these efforts, it is necessary to coordinate them in order to reach a greater collective impact. The Collective Impact model, as described by Kania & Kramer (2011), requires five elements: 1) a common agenda; 2) shared measurement systems; 3) mutually reinforcing activities; 4) continuous communication; and 5) a well-funded backbone support organization. The CLEAN Network, as an example of a rudimentary form of such an organization, engages in continuous communication through weekly teleconferences, an active listserv and other activities to share resources, activities, and ideas that is moving the network to develop common understandings that will likely lead to the development of effective collective impact on increasing climate and energy literacy. A Spring 2013 survey of the CLEAN Network provided insight as to how the CLEAN Network was addressing member needs and identified what other support was needed to increase its collective impact. In addition, community discussions identified the components needed for an effective overarching backbone support organization. A Fall 2015 survey of the CLEAN Network and the broader climate change education community is being conducted to examine 1) how the CLEAN Network make up and needs have evolved and how they compare to the broader community, and 2) to gather further input into the shaping of the elements of collective impact on climate and energy literacy. This presentation will describe the results from the 2015 survey and compare them to the 2013 survey and the community discussions. This will include describing the CLEAN Network's evolving professional make up, engagement of its members network activities, the importance of the network to members; how the findings compare with the broader climate change education community, and how the collective impact can be increased.

Disentangling the driving mechanism of streamflow trends using runoff senstivity to land use and climate change.

NASA Astrophysics Data System (ADS)

Silverman, N. L.; Moore, J. N.; Maneta, M. P.

2014-12-01

The majority of watersheds within the United States have been disturbed by anthropogenic land use change. On top of this, there is strong evidence of (historic and projected) climatic changes that affect earth's hydrologic cycle. Streamflow measurements integrate the effects of land use and climate change on watershed hydrology. Therefore, when temporal trends are present, teasing out the cause is challenging due to the overlying climate and land use signals. In this study, we develop an analytical framework for distinguishing trends in streamflow that are driven by climate change from those that are driven by land use change. This framework is based on the theory that during wetter years runoff is affected more by changes in climate than during drier years. Whereas, the inverse is true for land use change. During wetter years runoff is affected less by land use change than during drier years. This difference can be seen in the quantile regression of the 75th and 25th percentile annual stream flows which represent wetter and drier years, respectively. This creates a defining characteristic in how these two forcing mechanisms manifest within the streamflow record. We empirically test this framework and show that the sensitivity of runoff to climate and land use change is uniquely dependent on the spatiotemporal water and energy limitations of a catchment. Finally we apply the framework using 1,566 watersheds across the contiguous United States. We use gages from the United States Geological Survey (USGS) National Water Information System (NWIS) network. The gages are selected because they have continuous and complete data from the years 1950 to 2009 and represent watersheds which are characterized by a range of disturbances. Our results show that the driving mechanisms of streamflow change across the U.S. are regionally coherent and correspond with land management activities and climate zones. This methodology provides a simple means of classifying watershed to regional scale hydroclimatic change without relying on reference stream gages, complex models, or observational climate networks.

Assessment of Climate Change Adaptation Costs for the U.S. Road Network

EPA Science Inventory

The U.S. road network is one of the nation’s most important capital assets and is vital to the functioning of the U.S. economy. Climate change may represent a risk or an opportunity to this network, as changes in climate stress will affect the resources necessary for both road m...

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

NASA Astrophysics Data System (ADS)

Caillouet, Laurie; Vidal, Jean-Philippe; Sauquet, Eric; Devers, Alexandre; Graff, Benjamin

2017-06-01

The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatio-temporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

Influence of ambient meteorology on the accuracy of radiation measurements: insights from field and laboratory experiments

NASA Astrophysics Data System (ADS)

Oswald, Sandro M.; Pietsch, Helga; Baumgartner, Dietmar J.; Rieder, Harald E.

2016-04-01

A precise knowledge of the surface energy budget, which includes the solar and terrestrial radiation fluxes, is needed to accurately characterize the global energy balance which is largely determining Earth's climate. To this aim national and global monitoring networks for surface radiative fluxes have been established in recent decades. The most prominent among these networks is the so-called Baseline Surface Radiation Network (BSRN) operating under the auspices of the World Climate Research Programme (WCRP) (Ohmura et al., 1998). National monitoring networks such as the Austrian RADiation Monitoring Network (ARAD), which has been established in 2010 by a consortium of the Central Agency of Meteorology and Geodynamics (ZAMG), the University of Graz, the University of Innsbruck, and the University of Natural Resources and Applied Sciences, Vienna (BOKU), orient themselves on BSRN standards (McArthur, 2005). ARAD comprises to date five sites (Wien Hohe Warte, Graz/University, Innsbruck/University, Kanzelhöhe Observatory and Sonnblick (which is also a BSRN site)) and aims to provide long-term monitoring of radiation budget components at highest accuracy and to capture the spatial patterns of radiation climate in Austria (Olefs et al., 2015). Given the accuracy requirement for the local monitoring of radiative fluxes instrument offsets, triggered by meteorological factors and/or instrumentation, pose a major challenge in radiation monitoring. Within this study we investigate effects of ambient meteorology on the accuracy of radiation measurements performed with pyranometers contained in various heating/ventilation systems (HV-systems), all of which used in regular operation within the ARAD network. We focus particularly on instrument offsets observed following precipitation events. To quantify pyranometer responses to precipitation we performed a series of controlled laboratory experiments as well as targeted field campaigns in 2015 and 2016. Our results indicate that precipitation (as simulated by spray-tests or observed under ambient conditions) significantly affects the thermal environment of the instruments and thus their stability. Statistical analyses during nighttime conditions showed that precipitation triggers zero offsets of 4 W/m2 or more, depending on the HV-system and prevailing ambient conditions (i.e., air temperature, wind), indicating a clear exceedance of BSRN targets. References: McArthur L. J. B.: World Climate Research Programme-Baseline Surface Radiation Network (BSRN) - Operations Manual Version 2.1, Experimental Studies Division, Atmospheric Environment Service, Downsview, Ontario, Canada, 2005. Olefs M., Baumgartner D. J., Obleitner F., Bichler C., Foelsche U., Pietsch H., Rieder H. E., Weihs P., Geyer F., Haiden T., Schöner W.: The Austrian radiation monitoring network ARAD - best practice and added value, Atmospheric Measurement Techniques Discussions, 8: 10663-10710, 2015. Ohmura A., Dutton E. G., Forgan B., Frohlich C., Gilgen H., Hegner H., Heimo A., Stephens G. L., König-Langlo G., McArthur B., Müller G., Philipona R., Pinker R., Whitlock C. H., Dehne K., Wild M.: Baseline surface radiation network (bsrn/wcrp): new precision radiometry for climate research, Bulletin of the American Meteorological Society, 79(10): 2115-2136, 1998.

Flow networks for Ocean currents

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkenthin, Nora; Marwan, Norbert; Kurths, Jürgen

2014-05-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e., by its high computational complexity, we here introduce a new, discrete construction of flow-networks, which is then applied to static and dynamic velocity fields. Analyzing the flow-networks of prototypical flows we find that our approach can highlight the zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. We also apply the method to time series data of the Equatorial Pacific Ocean Current and the Gulf Stream ocean current for the changing velocity fields, which could not been done before, and analyse the properties of the dynamical system. Flow-networks can be powerful tools to theoretically understand the step from system's dynamics to network's topology that can be analyzed using network measures and is used for shading light on different climatic phenomena.

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

Climate Prediction for Brazil's Nordeste: Performance of Empirical and Numerical Modeling Methods.

NASA Astrophysics Data System (ADS)

Moura, Antonio Divino; Hastenrath, Stefan

2004-07-01

Comparisons of performance of climate forecast methods require consistency in the predictand and a long common reference period. For Brazil's Nordeste, empirical methods developed at the University of Wisconsin use preseason (October January) rainfall and January indices of the fields of meridional wind component and sea surface temperature (SST) in the tropical Atlantic and the equatorial Pacific as input to stepwise multiple regression and neural networking. These are used to predict the March June rainfall at a network of 27 stations. An experiment at the International Research Institute for Climate Prediction, Columbia University, with a numerical model (ECHAM4.5) used global SST information through February to predict the March June rainfall at three grid points in the Nordeste. The predictands for the empirical and numerical model forecasts are correlated at +0.96, and the period common to the independent portion of record of the empirical prediction and the numerical modeling is 1968 99. Over this period, predicted versus observed rainfall are evaluated in terms of correlation, root-mean-square error, absolute error, and bias. Performance is high for both approaches. Numerical modeling produces a correlation of +0.68, moderate errors, and strong negative bias. For the empirical methods, errors and bias are small, and correlations of +0.73 and +0.82 are reached between predicted and observed rainfall.

Microclimate Exposures of Surface-Based Weather Stations: Implications For The Assessment of Long-Term Temperature Trends.

NASA Astrophysics Data System (ADS)

Davey, Christopher A.; Pielke, Roger A., Sr.

2005-04-01

The U.S. Historical Climate Network is a subset of surface weather observation stations selected from the National Weather Service cooperative station network. The criteria used to select these stations do not sufficiently address station exposure characteristics. In addition, the current metadata available for cooperative network stations generally do not describe site exposure characteristics in sufficient detail. This paper focuses on site exposures with respect to air temperature measurements. A total of 57 stations were photographically surveyed in eastern Colorado, comparing existing exposures to the standards endorsed by the World Meteorological Organization. The exposures of most sites surveyed, including U.S. Historical Climate Network sites, were observed to fall short of these standards. This raises a critical question about the use of many Historical Climate Network sites in the development of long-term climate records and the detection of climate trends. Some of these sites clearly have poor exposures and therefore should be considered for removal from the Historical Climate Network. Candidate replacement sites do exist and should be considered for addition into the network to replace the removed sites. Documentation as performed for this study should be conducted worldwide in order to determine the extent of spatially nonrepresentative exposures and possible temperature biases.

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

Treesearch

Enric Batllori; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz; Carol Miller

2017-01-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform...

Assessment of Bias in the National Mosaic and Multi-Sensor QPE (NMQ/Q2) Reanalysis Radar-Only Estimate

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O. P.; Stevens, S. E.; Seo, D. J.; Zhang, J.; Howard, K.

2014-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor QPE (NMQ/Q2) based on the WSR-88D Next-generation Radar (NEXRAD) network over Continental United States (CONUS) is nearly completed for the period covering from 2001 to 2012. Reanalysis data are available at 1-km and 5-minute resolution. An important step in generating the best possible precipitation data is to assess the bias in the radar-only product. In this work, we use data from a combination of rain gauge networks to assess the bias in the NMQ reanalysis. Rain gauge networks such as the Hydrometeorological Automated Data System (HADS), the Automated Surface Observing Systems (ASOS), the Climate Reference Network (CRN), and the Global Historical Climatology Network Daily (GHCN-D) are combined for use in the assessment. These rain gauge networks vary in spatial density and temporal resolution. The challenge hence is to optimally utilize them to assess the bias at the finest resolution possible. For initial assessment, we propose to subset the CONUS data in climatologically representative domains, and perform bias assessment using information in the Q2 dataset on precipitation type and phase.

Causes and implications of the growing divergence between climate model simulations and observations

NASA Astrophysics Data System (ADS)

Curry, Judith

2014-03-01

For the past 15+ years, there has been no increase in global average surface temperature, which has been referred to as a 'hiatus' in global warming. By contrast, estimates of expected warming in the first several decades of 21st century made by the IPCC AR4 were 0.2C/decade. This talk summarizes the recent CMIP5 climate model simulation results and comparisons with observational data. The most recent climate model simulations used in the AR5 indicate that the warming stagnation since 1998 is no longer consistent with model projections even at the 2% confidence level. Potential causes for the model-observation discrepancies are discussed. A particular focus of the talk is the role of multi-decadal natural internal variability on the climate variability of the 20th and early 21st centuries. The ``stadium wave'' climate signal is described, which propagates across the Northern Hemisphere through a network of ocean, ice, and atmospheric circulation regimes that self-organize into a collective tempo. The stadium wave hypothesis provides a plausible explanation for the hiatus in warming and helps explain why climate models did not predict this hiatus. Further, the new hypothesis suggests how long the hiatus might last. Implications of the hiatus are discussed in context of climate model sensitivity to CO2 forcing and attribution of the warming that was observed in the last quarter of the 20th century.

"Time-dependent flow-networks"

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkentin, Nora; Lopez, Cristobal; Hernandez-Garcia, Emilio; Marwan, Norbert; Kurths, Jürgen

2015-04-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply information or heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e. high computational complexity and fixed variety of the flows in the underlying system, we introduce a new, method of flow-networks for changing in time velocity fields including external forcing in the system, noise and temperature-decay. Method of the flow-network construction can be divided into several steps: first we obtain the linear recursive equation for the temperature time-series. Then we compute the correlation matrix for time-series averaging the tensor product over all realizations of the noise, which we interpret as a weighted adjacency matrix of the flow-network and analyze using network measures. We apply the method to different types of moving flows with geographical relevance such as meandering flow. Analyzing the flow-networks using network measures we find that our approach can highlight zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. Flow-networks can be powerful tool to understand the connection between system's dynamics and network's topology analyzed using network measures in order to shed light on different climatic phenomena.

Analysis of Swedish Forest Owners' Information and Knowledge-Sharing Networks for Decision-Making: Insights for Climate Change Communication and Adaptation.

PubMed

André, Karin; Baird, Julia; Gerger Swartling, Åsa; Vulturius, Gregor; Plummer, Ryan

2017-06-01

To further the understanding of climate change adaptation processes, more attention needs to be paid to the various contextual factors that shape whether and how climate-related knowledge and information is received and acted upon by actors involved. This study sets out to examine the characteristics of forest owners' in Sweden, the information and knowledge-sharing networks they draw upon for decision-making, and their perceptions of climate risks, their forests' resilience, the need for adaptation, and perceived adaptive capacity. By applying the concept of ego-network analysis, the empirical data was generated by a quantitative survey distributed to 3000 private forest owners' in Sweden in 2014 with a response rate of 31%. The results show that there is a positive correlation, even though it is generally weak, between forest owner climate perceptions and (i) network features, i.e. network size and heterogeneity, and (ii) presence of certain alter groups (i.e. network members or actors). Results indicate that forest owners' social networks currently serve only a minimal function of sharing knowledge of climate change and adaptation. Moreover, considering the fairly infrequent contact between respondents and alter groups, the timing of knowledge sharing is important. In conclusion we suggest those actors that forest owners' most frequently communicate with, especially forestry experts providing advisory services (e.g. forest owner associations, companies, and authorities) have a clear role to communicate both the risks of climate change and opportunities for adaptation. Peers are valuable in connecting information about climate risks and adaptation to the actual forest property.

Analysis of Swedish Forest Owners' Information and Knowledge-Sharing Networks for Decision-Making: Insights for Climate Change Communication and Adaptation

NASA Astrophysics Data System (ADS)

André, Karin; Baird, Julia; Gerger Swartling, Åsa; Vulturius, Gregor; Plummer, Ryan

2017-06-01

To further the understanding of climate change adaptation processes, more attention needs to be paid to the various contextual factors that shape whether and how climate-related knowledge and information is received and acted upon by actors involved. This study sets out to examine the characteristics of forest owners' in Sweden, the information and knowledge-sharing networks they draw upon for decision-making, and their perceptions of climate risks, their forests' resilience, the need for adaptation, and perceived adaptive capacity. By applying the concept of ego-network analysis, the empirical data was generated by a quantitative survey distributed to 3000 private forest owners' in Sweden in 2014 with a response rate of 31%. The results show that there is a positive correlation, even though it is generally weak, between forest owner climate perceptions and (i) network features, i.e. network size and heterogeneity, and (ii) presence of certain alter groups (i.e. network members or actors). Results indicate that forest owners' social networks currently serve only a minimal function of sharing knowledge of climate change and adaptation. Moreover, considering the fairly infrequent contact between respondents and alter groups, the timing of knowledge sharing is important. In conclusion we suggest those actors that forest owners' most frequently communicate with, especially forestry experts providing advisory services (e.g. forest owner associations, companies, and authorities) have a clear role to communicate both the risks of climate change and opportunities for adaptation. Peers are valuable in connecting information about climate risks and adaptation to the actual forest property.

Mapping of interconnection of climate risks

NASA Astrophysics Data System (ADS)

Yokohata, Tokuta; Tanaka, Katsumasa; Nishina, Kazuya; Takanashi, Kiyoshi; Emori, Seita; Kiguchi, Masashi; Iseri, Yoshihiko; Honda, Yasushi; Okada, Masashi; Masaki, Yoshimitsu; Yamamoto, Akitomo; Shigemitsu, Masahito; Yoshimori, Masakazu; Sueyoshi, Tetsuo; Iwase, Kenta; Hanasaki, Naota; Ito, Akihiko; Sakurai, Gen; Iizumi, Toshichika; Oki, Taikan

2015-04-01

Anthropogenic climate change possibly causes various impacts on human society and ecosystem. Here, we call possible damages or benefits caused by the future climate change as "climate risks". Many climate risks are closely interconnected with each other by direct cause-effect relationship. In this study, the major climate risks are comprehensively summarized based on the survey of studies in the literature using IPCC AR5 etc, and their cause-effect relationship are visualized by a "network diagram". This research is conducted by the collaboration between the experts of various fields, such as water, energy, agriculture, health, society, and eco-system under the project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). First, the climate risks are classified into 9 categories (water, energy, food, health, disaster, industry, society, ecosystem, and tipping elements). Second, researchers of these fields in our project survey the research articles, and pick up items of climate risks, and possible cause-effect relationship between the risk items. A long list of the climate risks is summarized into ~130, and that of possible cause-effect relationship between the risk items is summarized into ~300, because the network diagram would be illegible if the number of the risk items and cause-effect relationship is too large. Here, we only consider the risks that could occur if climate mitigation policies are not conducted. Finally, the chain of climate risks is visualized by creating a "network diagram" based on a network graph theory (Fruchtman & Reingold algorithm). Through the analysis of network diagram, we find that climate risks at various sectors are closely related. For example, the decrease in the precipitation under the global climate change possibly causes the decrease in river runoff and the decrease in soil moisture, which causes the changes in crop production. The changes in crop production can have an impact on society by changing the food price or food supply. Changes in river runoff can also make an impact on the hydropower efficiency. Comprehensive pictures of climate risks and their interconnections are clearly shown in a straightforward manner by the network diagram. We will have a discussion how our results can be helpful for our society to recognize the climate risk.

Visualization of the chains of risks under global climate change

NASA Astrophysics Data System (ADS)

Yokohata, T.; Nishina, K.; Takahashi, K.; Kiguchi, M.; Iseri, Y.; Sueyoshi, T.; Yoshimori, M.; Iwase, K.; Yamamoto, A.; Shigemitsu, M.; Honda, Y.; Hanasaki, N.; Masaki, Y.; Ito, A.; Iizumi, T.; Sakurai, G.; Okada, M.; Emori, S.; Oki, T.

2014-12-01

Anthropogenic climate change possibly causes various impacts on human society and ecosystem. Here, we call possible damages or benefits caused by the future climate change as "climate risks". Many climate risks are closely interconnected with each other by direct cause-effect relationship. In this study, the major climate risks are comprehensively summarized based on the survey of studies in the literature using IPCC AR5 etc, and their cause-effect relationship are visualized by a "network diagram". This research is conducted by the collaboration between the experts of various fields, such as water, energy, agriculture, health, society, and eco-system under the project called ICA-RUS (Integrated Climate Assessment - Risks, Uncertainties and Society). First, the climate risks are classified into 9 categories (water, energy, food, health, disaster, industry, society, ecosystem, and tipping elements). Second, researchers of these fields in our project survey the research articles, and pick up items of climate risks, and possible cause-effect relationship between the risk items. A long list of the climate risks is summarized into ~130, and that of possible cause-effect relationship between the risk items is summarized into ~300, because the network diagram would be illegible if the number of the risk items and cause-effect relationship is too large. Here, we only consider the risks that could occur if climate mitigation policies are not conducted. Finally, the chain of climate risks is visualized by creating a "network diagram" based on a network graph theory (Fruchtman & Reingold algorithm). Through the analysis of network diagram, we find that climate risks at various sectors are closely related. For example, the decrease in the precipitation under the global climate change possibly causes the decrease in river runoff and the decrease in soil moisture, which causes the changes in crop production. The changes in crop production can have an impact on society by changing the food price or food supply. Changes in river runoff can also make an impact on the hydropower efficiency. Comprehensive pictures of climate risks and their interconnections are clearly shown in a straightforward manner by the network diagram. We will have a discussion how our results can be helpful for our society to recognize the climate risk.

Energy loss, range, and bremsstrahlung yield for 10-keV to 100-MeV electrons in various elements and chemical compounds

NASA Astrophysics Data System (ADS)

Pages, Lucien; Bertel, Evelyne; Joffre, Henri; Sklavenitis, Laodamas

2012-12-01

Even though the United States lacks a national climate policy, significant action has occurred at the local and regional levels. Some of the most aggressive climate change policies have occurred at the state and local levels and in interagency cooperation on specific management issues. While there is a long history of partnerships in dealing with a wide variety of policy issues, the uncertainty and the political debate surrounding climate change has generated new challenges to establishing effective policy networks. This paper investigates the formation of climate policy networks in the State of Nevada. It presents a methodology based on social network analysis for assessing the structure and function of local policy networks across a range of substantive climate impacted resources (water, landscape management, conservation, forestry and others). It draws from an emerging literature on federalism and climate policy, public sector innovation, and institutional analysis in socio-ecological systems. Comparisons across different policy issue networks in the state are used to highlight the influence of network structure, connectivity, bridging across vertical and horizontal organizational units, organizational diversity, and flows between organizational nodes.

Robustness of plant-insect herbivore interaction networks to climate change in a fragmented temperate forest landscape.

PubMed

Bähner, K W; Zweig, K A; Leal, I R; Wirth, R

2017-10-01

Forest fragmentation and climate change are among the most severe and pervasive forms of human impact. Yet, their combined effects on plant-insect herbivore interaction networks, essential components of forest ecosystems with respect to biodiversity and functioning, are still poorly investigated, particularly in temperate forests. We addressed this issue by analysing plant-insect herbivore networks (PIHNs) from understories of three managed beech forest habitats: small forest fragments (2.2-145 ha), forest edges and forest interior areas within three continuous control forests (1050-5600 ha) in an old hyper-fragmented forest landscape in SW Germany. We assessed the impact of forest fragmentation, particularly edge effects, on PIHNs and the resulting differences in robustness against climate change by habitat-wise comparison of network topology and biologically realistic extinction cascades of networks following scores of vulnerability to climate change for the food plant species involved. Both the topological network metrics (complexity, nestedness, trophic niche redundancy) and robustness to climate change strongly increased in forest edges and fragments as opposed to the managed forest interior. The nature of the changes indicates that human impacts modify network structure mainly via host plant availability to insect herbivores. Improved robustness of PIHNs in forest edges/small fragments to climate-driven extinction cascades was attributable to an overall higher thermotolerance across plant communities, along with positive effects of network structure. The impoverishment of PIHNs in managed forest interiors and the suggested loss of insect diversity from climate-induced co-extinction highlight the need for further research efforts focusing on adequate silvicultural and conservation approaches.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.

Amplification or suppression: Social networks and the climate change-migration association in rural Mexico.

PubMed

Nawrotzki, Raphael J; Riosmena, Fernando; Hunter, Lori M; Runfola, Daniel M

2015-11-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks - the ties connecting an origin and destination - may operate as "migration corridors" with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying , social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

The MedCLIVAR Network

NASA Astrophysics Data System (ADS)

Lionello, Piero; Medclivar sg, The

2013-04-01

The MedCLIVAR initiative was first proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 with the support of funding agencies from 12 countries. Since then, MedCLIVAR has served as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. Presently, the network continues dealing with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. Its present activities include the publication of a newsletter, the organization of the next MedCLIVAR conference in 2014 and the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region.

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

Humans reclaimed lands in NorthEastern Italy and artificial drainage networks: effects of 30 years of Agricultural Surface Water Management

NASA Astrophysics Data System (ADS)

Sofia, Giulia; Pizzulli, Federica; Tarolli, Paolo

2017-04-01

Agriculture and land-use management has changed drastically in Italy since the end of the Second World War, driven by local but also European agricultural policies. As a result of these changes in farming practices and land use, many drainage networks have changed producing a greater exposure to flooding with a broad range of impacts on society, also because of climate inputs coupling with the human drivers. This study focuses on two main points: which kind of land use and farming changes have been observed in the most recent years ( 30 years)? How do these changes interact with climate and soil conditions? An open challenge to understand how these changes influence the watershed response, is, in fact, to understand if rainfall characteristics and climate have a synergistic effect, if their interaction matters, or to understand what element has the greatest influence on the watershed response connected to agricultural changes. The work is based on a simple model of water infiltration due to soil properties, and a connected evaluation of the distributed surface water storage offered by artificial drainage networks in a study area in Veneto (north-eastern Italy). The analysis shows that economic changes control the development of agro-industrial landscapes, with effects on the hydrological response. However, these changes deeply interact with antecedent soil conditions and climate characteristics. Intense and irregular rainfall events and events with a high recurrence should be expected to be the most critical. The presented outcomes highlight the importance of understanding how agricultural practices can be the driver of or can be used to avoid, or at least mitigate, flooding. The proposed methods can be valuable tools in evaluating the costs and benefits of the management of water in agriculture to inform better policy decision-making. References Sofia G, Tarolli P. 2017. Hydrological Response to 30 years of Agricultural Surface Water Management. Land 6 (1): 3 DOI: 10.3390/land6010003 Sofia G, Roder G, Dalla Fontana G, Tarolli P. 2017. Flood dynamics in urbanised landscapes: 100 years of climate and humans' interaction. Scientific Reports 7, 40527 DOI: 10.1038/srep40527

The Relative Importance of Random Error and Observation Frequency in Detecting Trends in Upper Tropospheric Water Vapor

NASA Technical Reports Server (NTRS)

Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

2011-01-01

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

The relative importance of random error and observation frequency in detecting trends in upper tropospheric water vapor

NASA Astrophysics Data System (ADS)

Whiteman, David N.; Vermeesch, Kevin C.; Oman, Luke D.; Weatherhead, Elizabeth C.

2011-11-01

Recent published work assessed the amount of time to detect trends in atmospheric water vapor over the coming century. We address the same question and conclude that under the most optimistic scenarios and assuming perfect data (i.e., observations with no measurement uncertainty) the time to detect trends will be at least 12 years at approximately 200 hPa in the upper troposphere. Our times to detect trends are therefore shorter than those recently reported and this difference is affected by data sources used, method of processing the data, geographic location and pressure level in the atmosphere where the analyses were performed. We then consider the question of how instrumental uncertainty plays into the assessment of time to detect trends. We conclude that due to the high natural variability in atmospheric water vapor, the amount of time to detect trends in the upper troposphere is relatively insensitive to instrumental random uncertainty and that it is much more important to increase the frequency of measurement than to decrease the random error in the measurement. This is put in the context of international networks such as the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) and the Network for the Detection of Atmospheric Composition Change (NDACC) that are tasked with developing time series of climate quality water vapor data.

Vertical separation of the atmospheric aerosol components by using poliphon retrieval in polarized micro pulse lidar (P-MPL) measurements: case studies of specific climate-relevant aerosol types

NASA Astrophysics Data System (ADS)

Córdoba-Jabonero, Carmen; Sicard, Michaël; Ansmann, Albert; Águila, Ana del; Baars, Holger

2018-04-01

POLIPHON (POlarization-LIdar PHOtometer Networking) retrieval consists in the vertical separation of two/three particle components in aerosol mixtures, highlighting their relative contributions in terms of the optical properties and mass concentrations. This method is based on the specific particle linear depolarization ratio given for different types of aerosols, and is applied to the new polarized Micro-Pulse Lidar (P-MPL). Case studies of specific climate-relevant aerosols (dust particles, fire smoke, and pollen aerosols, including a clean case as reference) observed over Barcelona (Spain) are presented in order to evaluate firstly the potential of P-MPLs measurements in combination with POLIPHON for retrieving the vertical separation of those particle components forming aerosol mixtures and their properties.

Impact of SMOS soil moisture data assimilation on NCEP-GFS forecasts

NASA Astrophysics Data System (ADS)

Zhan, X.; Zheng, W.; Meng, J.; Dong, J.; Ek, M.

2012-04-01

Soil moisture is one of the few critical land surface state variables that have long memory to impact the exchanges of water, energy and carbon between the land surface and atmosphere. Accurate information about soil moisture status is thus required for numerical weather, seasonal climate and hydrological forecast as well as for agricultural production forecasts, water management and many other water related economic or social activities. Since the successful launch of ESA's soil moisture ocean salinity (SMOS) mission in November 2009, about 2 years of soil moisture retrievals has been collected. SMOS is believed to be the currently best satellite sensors for soil moisture remote sensing. Therefore, it becomes interesting to examine how the collected SMOS soil moisture data are compared with other satellite-sensed soil moisture retrievals (such as NASA's Advanced Microwave Scanning Radiometer -AMSR-E and EUMETSAT's Advanced Scatterometer - ASCAT)), in situ soil moisture measurements, and how these data sets impact numerical weather prediction models such as the Global Forecast System of NOAA-NCEP. This study implements the Ensemble Kalman filter in GFS to assimilate the AMSR-E, ASCAT and SMOS soil moisture observations after a quantitative assessment of their error rate based on in situ measurements from ground networks around contiguous United States. in situ soil moisture measurements from ground networks (such as USDA Soil Climate Analysis network - SCAN and NOAA's U.S. Climate Reference Network -USCRN) are used to evaluate the GFS soil moisture simulations (analysis). The benefits and uncertainties of assimilating the satellite data products in GFS are examined by comparing the GFS forecasts of surface temperature and rainfall with and without the assimilations. From these examinations, the advantages of SMOS soil moisture data products over other satellite soil moisture data sets will be evaluated. The next step toward operationally assimilating soil moisture and other land observations into GFS will also be discussed.

Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

2016-04-01

We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

Fragility of estimated spatial temperature patterns in climate field reconstructions of the Common Era

NASA Astrophysics Data System (ADS)

Wang, J.; Emile-Geay, J.; Vaccaro, A.; Guillot, D.; Rajaratnam, B.

2013-12-01

Climate field reconstructions (CFRs) of the Common Era can provide insight into dynamical causes of low-frequency climate variability. For instance, the Mann et al. [2009] study found that the reconstructed sea-surface temperature difference between the Medieval Climate Anomaly and the Little Ice Age (hereinafter MCA - LIA) is marked by a La-Niña like pattern over the tropical Pacific, and proposed dynamical explanations for this observation. In this talk, we assess the robustness of such spatial patterns. First we examine the impact of the CFR methodology. Starting with the network of Mann et al. [2008] (hereinafter M08), we perform temperature reconstruction using four different CFR techniques: RegEM-TTLS [Schneider, 2001], the Mann et al. [2009] implementation of RegEM-TTLS (hereinafter M09), Canonical Correlation Analysis [Smerdon et al., 2010, CCA] and GraphEM [Guillot et al., in revision]. We find that results are greatly method-dependent even with identical inputs. While the M09 reconstruction displays a La Niña-like pattern over the tropical Pacific for MCA - LIA, CCA gives a neutral pattern, RegEM-TTLS and GraphEM both display El Niño-like pattern but show different amplitudes. Next we assess a given CFR technique's sensitivity to the selection of inputs. Proxies are selected based on the statistical significance of their correlations with HadCRUT3v annual temperature. A multiple hypothesis test [Ventura et al., 2004] is conducted to preclude spurious correlations. This choice has a large impact on resulting CFRs. In particular, whether the correlation is calculated between local or regional temperature-proxy pairs determines the number of significant records included in the proxy network. This in turn greatly affects the reconstructed spatial patterns and the Northern Hemispheric mean temperature time series with all CFR methods investigated. In order to further analyze CFRs' sensitivities to the abovementioned procedural choices, we assemble an updated multi-proxy network and produce a new 2000-year-long global temperature reconstruction. The network expands upon the existing M08 network by screening tree-ring proxies for the 'divergence problem' [D'Arrigo et al., 2008] and adds 58 non tree-ring proxies, of which 28 are located in the tropics and 11 are available within at least the past 1500 years. Overall, considerable differences are still evident among reconstructions using different CFR methods. Yet such differences are smaller using the updated proxy network compared with using the M08 network, consistent with pseudoproxy studies [Wang et al, 2013]. Our results collectively highlight the fragility of reconstructed patterns in the current state of proxy networks and CFR methods. We conclude that dynamical interpretations of such patterns are premature until these technical aspects are resolved. Reference: Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J. E., and Rajaratnam, B.: Evaluating climate field reconstruction techniques using improved emulations of real-world conditions, Clim. Past Discuss., 9, 3015-3060, doi:10.5194/cpd-9-3015-2013, 2013.

Climate Change Education in Informal Settings: Using Boundary Objects to Frame Network Dissemination

ERIC Educational Resources Information Center

Steiner, Mary Ann

2016-01-01

This study of climate change education dissemination takes place in the context of a larger project where institutions in four cities worked together to develop a linked set of informal learning experiences about climate change. Each city developed an organizational network to explore new ways to connect urban audiences with climate change…

From Theory to Practice: How Mass Audubon Is Incorporating Strategic Framing about Climate Change

ERIC Educational Resources Information Center

Fleischer, Amy

2013-01-01

Mass Audubon recognized that climate change was significantly impacting bird species distribution and seasonality. Unsure of how and when to engage visitors to their network of wildlife sanctuaries on the topic of climate change, its educators turned to the National Network of Ocean and Climate Change Interpreters' Study Circle (NNOCCI). Through…

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

PubMed Central

Lange, Stefan; Donges, Jonathan F.; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation. Building on a recent study by Feldhoff et al. [1] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system. Three types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed. PMID:25856374

Local difference measures between complex networks for dynamical system model evaluation.

PubMed

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed.

Considering Climate Change in Road and Building Design

NASA Astrophysics Data System (ADS)

Jacobs, Jennifer M.; Kirshen, Paul H.; Daniel, Jo Sias

2013-07-01

What is the role of climate in infrastructure design? How can engineers design for a changing climate? How can climate scientists better inform the design process? These were the questions posed at the first Infrastructure and Climate Network (ICNet) Steering Committee Workshop, which was sponsored by a U.S. National Science Foundation research grant (CBET-1231326) from the Research Coordination Networks-Science, Engineering and Education for Sustainability (RCN-SEES) program.

From Hills to Holes: How Climate Change and Mining are Altering Runoff Processes in Canada

NASA Astrophysics Data System (ADS)

Carey, S. K.

2015-12-01

Canadian environments are under considerable pressure from both climate and land-use change. While warming temperatures are widespread and amplified in the north, surface mining has resulted in large-scale landscape disturbance. How these changes affect catchment response is profound, fundamentally altering the cycling and delivery of water and geochemicals to the drainage network. In permafrost-underlain environments, coupled mass and energy processes control runoff response, and as ground thaw increases, new subsurface pathways become accessible while changing overall catchment storage. With surface mining, watersheds are altered such that they bare little resemblance to what existed prior to mining. In this presentation, data will be presented from long-term experiments exploring the impact of climate and mining on runoff processes in cold catchments using stable isotopes of water and associated hydrometric measurements. In southern Yukon, results from the Wolf Creek Research Basin highlights the influence of surface energy balances on controlling the timing and magnitude of flow response, with inter-annual variability largely driven by how atmospheric forcing interacts with permafrost-underlain areas of the catchment. In mountainous areas of southern British Columbia, surface mining reconfigures landscapes as valleys are filled with waste-rock. Mine-influenced catchments exhibit attenuated flows with delays in spring freshet and a more muted to precipitation. Stable isotopes in stream water suggests that both waste-rock and reference catchments are well mixed, however reference catchments are more responsive to enrichment and depletion events and that mine-influenced catchments had a heavier isotope signature than reference watersheds, suggesting enhanced influence of rainfall on recharge. In both cases, snow storage and release exerts considerable control on streamflow responses, and future changes in streamflow regimes will reflect both a changes in the snow regime and inherent catchment storage properties that are dynamic with time.

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2015-04-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2014-12-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterised and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterised uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

PEP725 Pan European Phenological Database

NASA Astrophysics Data System (ADS)

Koch, Elisabeth; Adler, Silke; Ungersböck, Markus; Zach-Hermann, Susanne

2010-05-01

Europe is in the fortunate situation that it has a long tradition in phenological networking: the history of collecting phenological data and using them in climatology has its starting point in 1751 when Carl von Linné outlined in his work Philosophia Botanica methods for compiling annual plant calendars of leaf opening, flowering, fruiting and leaf fall together with climatological observations "so as to show how areas differ". The Societas Meteorologicae Palatinae at Mannheim well known for its first European wide meteorological network also established a phenological network which was active from 1781 to 1792. Recently in most European countries, phenological observations have been carried out routinely for more than 50 years by different governmental and non governmental organisations and following different observation guidelines, the data stored at different places in different formats. This has been really hampering pan European studies, as one has to address many National Observations Programs (NOP) to get access to the data before one can start to bring them in a uniform style. From 2004 to 2005 the COST-action 725 was running with the main objective to establish a European reference data set of phenological observations that can be used for climatological purposes, especially climate monitoring, and detection of changes. So far the common database/reference data set of COST725 comprises 7687248 data from 7285 observation sites in 15 countries and International Phenological Gardens (IPG) spanning the timeframe from 1951 to 2000. ZAMG is hosting the database. In January 2010 PEP725 has started and will take over not only the part of maintaining, updating the database, but also to bring in phenological data from the time before 1951, developing better quality checking procedures and ensuring an open access to the database. An attractive webpage will make phenology and climate impacts on vegetation more visible in the public enabling a monitoring of vegetation development.

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

PubMed Central

Riosmena, Fernando; Hunter, Lori M.; Runfola, Daniel M.

2015-01-01

Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks – the ties connecting an origin and destination – may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place. PMID:26692656

Trap-Nesting Hymenoptera and Their Network with Parasites in Recovered Riparian Forests Brazil.

PubMed

Araujo, G J; Fagundes, R; Antonini, Y

2018-02-01

Different aspects of human activities can cause environmental change that endanger species persistence, alter species distributions, and lead to changes in antagonistic and mutualistic interactions, whereas deforestation and flooding of riparian forest results in landscapes consisting of patchily distributed riparian forest fragments in a matrix of pastures, plantations, and urban areas. Therefore, we assessed the richness, abundance, and trophic interactions of trap-nesting Hymenoptera and their parasites at four patches of restored riparian forest and at one reference natural fragment, of different sizes and ages, located at the Volta Grande Reservoir, in Minas Gerais and São Paulo states to answer the following questions: (1) Does the richness and abundance of cavity-nesting bees and wasps differ in riparian forest fragments according to the seasonal periods? (2) Does the composition of cavity-nesting bees and wasps vary among restoration and reference sites and between climate seasons (wet and dry)? (3) How do the degrees of specialization of the parasites vary among the patches of forest? We recorded 12 species of wasps, eight of bees, and nine species of parasites. Areas with longer time since restoration (reference site) showed higher species richness. However, the abundance was higher in most recent areas. The composition of bee and wasp assembly has not significantly changed between the climate seasons, although it is different between sampling areas. The richness and abundance were higher in warmer and rainy periods. The rate of bee and wasp mortality was high. The degree of specialization of parasites varies among sampling units, and the network of host-parasite interaction has a modular configuration with generalists and specialists. We concluded that the restored areas with more complex habitat could provide better conditions for the reestablishment of ecological interactions among these insects, the local flora, and other invertebrates, which together contribute to the success of the restored environments.

U.S. Geological Survey Ground-Water Climate Response Network

USGS Publications Warehouse

,

2007-01-01

The U.S. Geological Survey serves the Nation by providing reliable hydrologic information used by others to manage the Nation's water resources. The U.S. Geological Survey (USGS) measures more than 20,000 wells each year for a variety of objectives as part of Federal programs and in cooperation with State and local agencies. Water-level data are collected using consistent data-collection and quality-control methods. A small subset of these wells meets the criteria necessary to be included in a 'Climate Response Network' of wells designed to illustrate the response of the ground-water system to climate variations nationwide. The primary purpose of the Climate Response Network is to portray the effect of climate on ground-water levels in unconfined aquifers or near-surface confined aquifers that are minimally affected by pumping or other anthropogenic stresses. The Climate Response Network Web site (http://groundwaterwatch.usgs.gov/) is the official USGS Web site for illustrating current ground-water conditions in the United States and Puerto Rico. The Climate Response Network Web pages provide information on ground-water conditions at a variety of scales. A national map provides a broad overview of water-table conditions across the Nation. State maps provide a more local picture of ground-water conditions. Site pages provide the details about a specific well.

Collaborating for Climate Education - A Look at Strategic Partnerships

NASA Astrophysics Data System (ADS)

Bozuwa, J.; Lewis, C.

2015-12-01

Collaborating for Climate Education WeekEarth Day Network (EDN) developed Climate Education Week toolkit, a turnkey online resource for grades K-12 that provided teachers with everything they needed to deliver lessons, activities, contests, and service learning projects that related to climate science during Climate Education Week (April 18-25). EDN assembled an Advisory Group to develop the survey, lesson plans and activities, and resources. The Advisory Group consisted of experts and partners in environmental education, including representatives from other government and non-governmental organizations working with the White House on Climate Education, as well as educators in our Educator's Network. EDN's Climate Education Week Advisory Board brought together top academics and major stakeholders in climate education throughout the development and outreach processes. The Advisory Board included representatives from the Alliance for Climate Education (ACE), The CLEAN Network, NOAA, The Department of Energy, and NASA. The representatives from the board helped to identify and streamline the most effective and necessary lesson plans, strategic themes to maintain throughout the toolkit, and avenues for increased outreach. EDN also partnered with Connect4Climate, PBS's Plum Landing, Young Voices of Climate Change, FEMA, and The Wild Center to develop content and to broaden the reach of the toolkit. Each of the seven days had a different theme that addressed a specific climate education topic, with highlighted activities and resources for elementary, middle and high school levels. The toolkit provided educators with a comprehensive view of climate change—beginning with the science, the anthropogenic causes, and societal impacts and then providing solutions, ways to take action, and the green economy transition. This online resource connected educators to a network of effective resources from our partners, all of which saw a significant uptick in their online viewership. Using the highly recognized Earth Day platform, the high level of involvement from partners and Advisory Board members, and EDN's ever-growing network, EDN had the ability to reach thousands of educators and students, and further the climate conversation.

Experimental Reconstructions of Surface Temperature using the PAGES 2k Network

NASA Astrophysics Data System (ADS)

Wang, Jianghao; Emile-Geay, Julien; Vaccaro, Adam; Guillot, Dominique; Rajaratnam, Bala

2014-05-01

Climate field reconstructions (CFRs) of the Common Era provide uniquely detailed characterizations of natural, low-frequency climate variability beyond the instrumental era. However, the accuracy and robustness of global-scale CFRs remains an open question. For instance, Wang et al. (2013) showed that CFRs are greatly method-dependent, highlighting the danger of forming dynamical interpretations based on a single reconstruction (e.g. Mann et al., 2009). This study will present a set of new reconstructions of global surface temperature and compare them with existing reconstructions from the IPCC AR5. The reconstructions are derived using the PAGES 2k network, which is composed of 501 high-resolution temperature-sensitive proxies from eight continental-scale regions (PAGES2K Consortium, 2013). Four CFR techniques are used to produce reconstructions, including RegEM-TTLS, the Mann et al. (2009) implementation of RegEM-TTLS (hereinafter M09-TTLS), CCA (Smerdon et al., 2010) and GraphEM (Guillot et al., submitted). First, we show that CFRs derived from the PAGES 2k network exhibit greater inter-method similarities than the same methods applied to the proxy network of Mann et al. (2009) (hereinafter M09 network). For instance, reconstructed NH mean temperature series using the PAGES 2k network are in better agreement over the last millennium than the M09-based reconstructions. Remarkably, for the reconstructed temperature difference between the Medieval Climate Anomaly and the Little Ice Age, the spatial patterns of the M09-based reconstructions are greatly divergent amongst methods. On the other hand, not a single PAGES 2k-based CFR displays the La Niña-like pattern found in Mann et al. (2009); rather, no systematic pattern emerges between the two epochs. Next, we quantify uncertainties associated with the PAGES 2k-based CFRs via ensemble methods, and show that GraphEM and CCA are less sensitive to random noise than RegEM-TTLS and M09-TTLS, consistent with pseudoproxy studies (Wang et al., 2014). The updated set of reconstructions, with uncertainties, will provide a broader context for the evaluation of the unusual character of the 20th century warming. The reconstructions will also be used to constrain fingerprinting analyses, which is particularly useful in discriminating between externally forced signals and internal variability. Reference: Guillot, D., B. Rajaratnam, and J. Emile-Geay, Statistical paleoclimate reconstructions via markov random fields, Ann. Appl. Stat., submitted. Mann, M. E., Z. Zhang, S. Rutherford, R. S. Bradley, M. K. Hughes, D. Shindell, C. Ammann, G. Faluvegi, and F. Ni, Global signatures and dynamical origins of the little ice age and medieval climate anomaly, Science, 326 (5957), 1256-1260, 2009. PAGES2K Consortium, Continental-scale temperature variability during the past two millennia, Nature Geosci, 6(5), 339-346, 2013. Smerdon, J. E., A. Kaplan, D. Chang, and M. N. Evans, A pseudoproxy evaluation of the CCA and RegEM methods for reconstructing climate fields of the last millennium*, J. Clim., 23(18), 4856-4880, 2010. Wang, J., J. Emile-Geay, A. D. Vaccaro, and D. Guillot, Fragility of estimated spatial temperature patterns in climate field reconstructions of the Common Era, Abstract PP41B-03 presented at Fall Meeting, AGU, San Francisco, Calif., 2013. Wang, J., J. Emile-Geay, D. Guillot, J. Smerdon, and B. Rajaratnam, Evaluating climate field reconstruction techniques using improved emulations of real-world conditions, Clim.Past, 10(1), 1-19, 2014.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Reference Manual on Making School Climate Improvements. School Climate Improvement Resource Package, 2017

ERIC Educational Resources Information Center

Yoder, N.; Darling-Churchill, K.; Colombi, G. D.; Ruddy, S.; Neiman, S.; Chagnon, E.; Mayo, R.

2017-01-01

This reference manual identifies five overarching sets of activities for improving school climate, with the goal of improving student outcomes (e.g., achievement, attendance, behaviors, and skills). These sets of activities help to initiate, implement, and sustain school climate improvements. For each activity set, the manual presents a clear…

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-12-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanization and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanization and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to interannual climate variability. However, urbanization arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. In addition to improving our understanding of Roman water resource management, our cost-distance-based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

Dermody, B. J.; van Beek, R. P. H.; Meeks, E.; Klein Goldewijk, K.; Scheidel, W.; van der Velde, Y.; Bierkens, M. F. P.; Wassen, M. J.; Dekker, S. C.

2014-06-01

The Romans were perhaps the most impressive exponents of water resource management in preindustrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socioeconomic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we find that irrigation and virtual water trade increased Roman resilience to climate variability in the short term. However, urbanisation arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and reduced its resilience to climate variability in the long-term. In addition to improving our understanding of Roman water resource management, our cost-distance based analysis illuminates how increases in import costs arising from climatic and population pressures are likely to be distributed in the future global virtual water network.

Mapping Climate Science Information Needs and Networks in the Northwest, USA through Evaluating the Northwest Climate Science Center Climate Science Digest

NASA Astrophysics Data System (ADS)

Gergel, D. R.; Watts, L. H.; Salathe, E. P.; Mankowski, J. D.

2017-12-01

Climate science, already a highly interdisciplinary field, is rapidly evolving, and natural resource managers are increasingly involved in policymaking and adaptation decisions to address climate change that need to be informed by state-of-the-art climate science. Consequently, there is a strong demand for unique organizations that engender collaboration and cooperation between government, non-profit, academic and for-profit sectors that are addressing issues relating to natural resources management and climate adaptation and resilience. These organizations are often referred to as boundary organizations. The Northwest Climate Science Center (NW CSC) and the North Pacific Landscape Conservation Cooperative (NP LCC) are two such boundary organizations operating in different contexts. Together, the NW CSC and the NP LCC fulfill the need for sites of co-production between researchers and managers working on climate-related issues, and a key component of this work is a monthly climate science newsletter that includes recent climate science journal articles, reports, and climate-related events. Our study evaluates the effectiveness of the climate science digest (CSD) through a three-pronged approach: a) in-depth interviews with natural resource managers who use the CSD, b) poll questions distributed to CSD subscribers, and c) quantitative analysis of CSD effectiveness using analytics from MailChimp distribution. We aim to a) map the reach of the CSD across the Northwest and at a national level; b) understand the efficacy of the CSD at communicating climate science to diverse audiences; c) evaluate the usefulness of CSD content for diverse constituencies of subscribers; d) glean transferrable knowledge for future evaluations of boundary management tools; and e) establish a protocol for designing climate science newsletters for other agencies disseminating climate science information. We will present results from all three steps of our evaluation process and describe their implications for future evaluations of climate science communications products and other boundary management tools in the field of natural resources management.

The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record

NASA Astrophysics Data System (ADS)

de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne

2015-04-01

Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.

Climate and ET: Does Plant Water Requirements Increase during Droughts?

NASA Astrophysics Data System (ADS)

Fipps, G.; Bonaiti, G.; Swanson, C.

2012-04-01

With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. Historically, governmental and private organizations have used estimates of plant water use estimated from a variety of methods for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. In recent years, there has been an expansion of agricultural weather station networks which report daily ETo (potential evapotranspiration) and commercial irrigation controllers with instrumentation which calculate real-time ETo from weather parameters. Efforts are underway to use this more precise information for regional water planning and ETo is routinely used for designing and implementing drought response programs. The year 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the summer of 2011. In 2011, real-time ETo (reference evapotranspiration) data in Texas was 30 to 50% higher than historic averages. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between long term average ETo and ETo measurements (from 2006 to 2011) for selected weather stations of the Texas ET Network.

Climate Change Literacy across the Critical Zone Observatory Network

NASA Astrophysics Data System (ADS)

Moore, A.; Derry, L. A.; Zabel, I.; Duggan-Haas, D.; Ross, R. M.

2017-12-01

Earth's Critical Zone extends from the top of the tree canopy to the base of the groundwater lens. Thus the Critical Zone is examined as a suite of interconnected systems and study of the CZ is inherently interdisciplinary. Climate change is an important driver of CZ processes. The US Critical Zone Observatory Network comprises nine observatories and a coordinating National Office. Educational programs and materials developed at each CZO and the National Office have been collected, reviewed, and presented on-line at the CZONO (criticalzone.org/national/education-outreach/resources). Because the CZOs are designed to observe and measure a suite of common parameters on varying geological substrates and within different ecological contexts, educational resources reflect the diversity of processes represented across the network. As climate change has a network-wide impact, the fundamental building blocks of climate change literacy are key elements in many activities within the CZONO resource collection. Carbon-cycle and hydrologic cycle processes are well-represented, with emphasis on human interactions with these resources, as well as the impact of extreme events and the changing climate. Current work on the resource collection focuses on connecting individual resources to "Teach Climate Science" project and the Teacher-Friendly Guide to Climate Change (teachclimatescience.wordpress.com). The Teacher-Friendly Guide is a manual for K-12 teachers that presents both the fundamentals of climate science alongside resources for effective teaching of this controversial topic. Using the reach of the CZO network we hope to disseminate effective climate literacy resources and support to the K-12 community.

Publishing high-quality climate data on the semantic web

NASA Astrophysics Data System (ADS)

Woolf, Andrew; Haller, Armin; Lefort, Laurent; Taylor, Kerry

2013-04-01

The effort over more than a decade to establish the semantic web [Berners-Lee et. al., 2001] has received a major boost in recent years through the Open Government movement. Governments around the world are seeking technical solutions to enable more open and transparent access to Public Sector Information (PSI) they hold. Existing technical protocols and data standards tend to be domain specific, and so limit the ability to publish and integrate data across domains (health, environment, statistics, education, etc.). The web provides a domain-neutral platform for information publishing, and has proven itself beyond expectations for publishing and linking human-readable electronic documents. Extending the web pattern to data (often called Web 3.0) offers enormous potential. The semantic web applies the basic web principles to data [Berners-Lee, 2006]: using URIs as identifiers (for data objects and real-world 'things', instead of documents) making the URIs actionable by providing useful information via HTTP using a common exchange standard (serialised RDF for data instead of HTML for documents) establishing typed links between information objects to enable linking and integration Leading examples of 'linked data' for publishing PSI may be found in both the UK (http://data.gov.uk/linked-data) and US (http://www.data.gov/page/semantic-web). The Bureau of Meteorology (BoM) is Australia's national meteorological agency, and has a new mandate to establish a national environmental information infrastructure (under the National Plan for Environmental Information, NPEI [BoM, 2012a]). While the initial approach is based on the existing best practice Spatial Data Infrastructure (SDI) architecture, linked-data is being explored as a technological alternative that shows great promise for the future. We report here the first trial of government linked-data in Australia under data.gov.au. In this initial pilot study, we have taken BoM's new high-quality reference surface temperature dataset, Australian Climate Observations Reference Network - Surface Air Temperature (ACORN-SAT) [BoM, 2012b]. This dataset contains daily homogenised surface temperature observations for 112 locations around Australia, dating back to 1910. An ontology for the dataset was developed [Lefort et. al., 2012], based on the existing Semantic Sensor Network ontology [Compton et. al., 2012] and the W3C RDF Data Cube vocabulary [W3C, 2012]. Additional vocabularies were developed, e.g. for BoM weather stations and rainfall districts. The dataset was converted to RDF and loaded into an RDF triplestore. The Linked-Data API (http://code.google.com/p/linked-data-api) was used to configure specific URI query patterns (e.g. for observation timeseries slices by station), and a SPARQL endpoint was provided for direct querying. In addition, some demonstration 'mash-ups' were developed, providing an interactive browser-based interface to the temperature timeseries. References [Berners-Lee et. al., 2001] Tim Berners-Lee, James Hendler and Ora Lassila (2001), "The Semantic Web", Scientific American, May 2001. [Berners-Lee, 2006] Tim Berners-Lee (2006), "Linked Data - Design Issues", W3C [http://www.w3.org/DesignIssues/LinkedData.html] [BoM, 2012a] Bureau of Meteorology (2012), "Environmental information" [http://www.bom.gov.au/environment/] [BoM, 2012b] Bureau of Meteorology (2012), "Australian Climate Observations Reference Network - Surface Air Temperature" [http://www.bom.gov.au/climate/change/acorn-sat/] [Compton et. al., 2012] Michael Compton, Payam Barnaghi, Luis Bermudez, Raul Garcia-Castro, Oscar Corcho, Simon Cox, John Graybeal, Manfred Hauswirth, Cory Henson, Arthur Herzog, Vincent Huang, Krzysztof Janowicz, W. David Kelsey, Danh Le Phuoc, Laurent Lefort, Myriam Leggieri, Holger Neuhaus, Andriy Nikolov, Kevin Page, Alexandre Passant, Amit Sheth, Kerry Taylor (2012), "The SSN Ontology of the W3C Semantic Sensor Network Incubator Group", J. Web Semantics, 17 (2012) [http://dx.doi.org/10.1016/j.websem.2012.05.003] [Lefort et. al., 2012] Laurent Lefort, Josh Bobruk, Armin Haller, Kerry Taylor and Andrew Woolf (2012), "A Linked Sensor Data Cube for a 100 Year Homogenised daily temperature dataset", Proc. Semantic Sensor Networks 2012 [http://ceur-ws.org/Vol-904/paper10.pdf] [W3C, 2012] W3C (2012), "The RDF Data Cube Vocabulary", [http://www.w3.org/TR/vocab-data-cube/

Use of NEXRAD radar-based observations for quality control of in-situ rain gauge measurements

NASA Astrophysics Data System (ADS)

Nelson, B. R.; Prat, O.; Leeper, R.

2017-12-01

Rain gauge quality control is an often over looked important step in the archive of historical precipitation estimates. We investigate the possibilities that exist for using ground based radar networks for quality control of rain gauge measurements. This process includes the point to pixel comparisons of the rain gauge measurements with NEXRAD observations. There are two NEXRAD based data sets used for reference; the NCEP stage IV and the NWS MRMS gridded data sets. The NCEP stage IV data set is available at 4km hourly for the period 2002-present and includes the radar-gauge bias adjusted precipitation estimate. The NWS MRMS data set includes several different variables such as reflectivity, radar-only estimates, precipitation flag, and radar-gauge bias adjusted precipitation estimates. The latter product provides for much more information to apply quality control such as identification of precipitation type, identification of storm type and Z-R relation. In addition, some of the variables are available at 5-minute scale. The rain gauge networks that are investigated are the Climate Reference Network (CRN), the Fischer-Porter Hourly Precipitation Database (HPD), and the Hydrometeorological Automated Data System (HADS). The CRN network is available at the 5-minute scale, the HPD network is available at the 15-minute and hourly scale, and HADS is available at the hourly scale. The varying scales present challenges for comparisons. However given the higher resolution radar-based products we identify an optimal combination of rain gauge observations that can be compared to the radar-based information. The quality control process focuses on identifying faulty gauges in direct comparison while a deeper investigation focuses on event-based differences from light rain to extreme storms.

Climate Solutions Presentations on Science On a Sphere (SOS) and SOS Explorer achieve acceptance of Climate Science among Policymakers as well as the Public: US National Academy of Sciences Symposium/Open House Example

NASA Astrophysics Data System (ADS)

Sievering, H.

2015-12-01

The outcomes of climate science are inherently rife with discussions of dire consequences for humans that leave many listeners feeling helpless and hopeless. We have found that a focus on clean energy solutions, without reference to dirty energy, substantially reduces (may even eliminate) the negativity associated with sea level rise, extreme weather and other climate change presentations. US audiences respond well to discussion of California's clean energy transformation with solar, wind, geothermal and water power together now approaching 25% of total energy supply for the world's sixth largest economy. For both policymakers and the general public, a "positive climate change" presentation does not generally suffice on its own. Clear visual display of climate science information is essential. We have found the Science On a Sphere (SOS) National Oceanic and Atmospheric Administration science education tool, to be exceptional in this regard. Further, broad dissemination is possible given the SOS network consists of over 120 sites in 23 countries. The new SOS Explorer system, an advanced science education tool, can readily utilize the over 500 available SOS data sets. We have recently developed an arctic amplification and mid-latitude climate change impacts program for the upcoming US National Academy of Sciences' Arctic Matters Symposium/Open House. This SOS and SOS Explorer education program will be described with emphasis on the climate solutions incorporated into this module targeted at US policymakers and invited open house public.

Climate change education in informal settings: Using boundary objects to frame network dissemination

NASA Astrophysics Data System (ADS)

Steiner, Mary Ann

This study of climate change education dissemination takes place in the context of a larger project where institutions in four cities worked together to develop a linked set of informal learning experiences about climate change. Each city developed an organizational network to explore new ways to connect urban audiences with climate change education. The four city-specific networks shared tools, resources, and knowledge with each other. The networks were related in mission and goals, but were structured and functioned differently depending on the city context. This study illustrates how the tools, resources, and knowledge developed in one network were shared with networks in two additional cities. Boundary crossing theory frames the study to describe the role of objects and processes in sharing between networks. Findings suggest that the goals, capacity and composition of networks resulted in a different emphasis in dissemination efforts, in one case to push the approach out to partners for their own work and in the other to pull partners into a more collaborative stance. Learning experiences developed in each city as a result of the dissemination reflected these differences in the city-specific emphasis with the push city diving into messy examples of the approach to make their own examples, and the pull city offering polished experiences to partners in order to build confidence in the climate change messaging. The networks themselves underwent different kinds of growth and change as a result of dissemination. The emphasis on push and use of messy examples resulted in active use of the principles of the approach and the pull emphasis with polished examples resulted in the cultivation of partnerships with the hub and the potential to engage in the educational approach. These findings have implications for boundary object theory as a useful grounding for dissemination designs in the context of networks of informal learning organizations to support a shift in communication approach, particularly when developing interventions for wicked socio-scientific issues such as climate change.

Impact of the choice of the precipitation reference data set on climate model selection and the resulting climate change signal

NASA Astrophysics Data System (ADS)

Gampe, D.; Ludwig, R.

2017-12-01

Regional Climate Models (RCMs) that downscale General Circulation Models (GCMs) are the primary tool to project future climate and serve as input to many impact models to assess the related changes and impacts under such climate conditions. Such RCMs are made available through the Coordinated Regional climate Downscaling Experiment (CORDEX). The ensemble of models provides a range of possible future climate changes around the ensemble mean climate change signal. The model outputs however are prone to biases compared to regional observations. A bias correction of these deviations is a crucial step in the impact modelling chain to allow the reproduction of historic conditions of i.e. river discharge. However, the detection and quantification of model biases are highly dependent on the selected regional reference data set. Additionally, in practice due to computational constraints it is usually not feasible to consider the entire ensembles of climate simulations with all members as input for impact models which provide information to support decision-making. Although more and more studies focus on model selection based on the preservation of the climate model spread, a selection based on validity, i.e. the representation of the historic conditions is still a widely applied approach. In this study, several available reference data sets for precipitation are selected to detect the model bias for the reference period 1989 - 2008 over the alpine catchment of the Adige River located in Northern Italy. The reference data sets originate from various sources, such as station data or reanalysis. These data sets are remapped to the common RCM grid at 0.11° resolution and several indicators, such as dry and wet spells, extreme precipitation and general climatology, are calculate to evaluate the capability of the RCMs to produce the historical conditions. The resulting RCM spread is compared against the spread of the reference data set to determine the related uncertainties and detect potential model biases with respect to each reference data set. The RCMs are then ranked based on various statistical measures for each indicator and a score matrix is derived to select a subset of RCMs. We show the impact and importance of the reference data set with respect to the resulting climate change signal on the catchment scale.

Interdisciplinarity and Knowledge Networking: Co-Production of Climate-Authoritative Knowledge in Southern South America

ERIC Educational Resources Information Center

Hidalgo, Cecilia

2016-01-01

Interdisciplinarity and knowledge networking are at the core of current global, regional, and national initiatives concerning climate. Both scientifc knowledge and public participation are essential to enhance the capacity of different sectors and governments to respond to challenges posed by climate variability and change. Exchange and bridge…

Responses to Climate Change: Exploring Organisational Learning across Internationally Networked Organisations for Development

ERIC Educational Resources Information Center

Boyd, Emily; Osbahr, Henny

2010-01-01

Drawing from the organisational learning and governance literature, this paper assesses four internationally networked governmental and non-governmental organisations in the UK addressing climate change. We analyse how those concerned understand the climate change crisis, what mechanisms are put in place to address information flows, and what…

The MedCLIVAR Network

NASA Astrophysics Data System (ADS)

Lionello, Piero; Medclivar Sc, The

2014-05-01

MedCLIVAR serves as a scientific network to promote interaction among different scientific disciplines and to develop a multidisciplinary vision of the evolution of the Mediterranean climate through studies that integrate atmospheric, marine, and terrestrial climate components at time scales ranging from paleoreconstructions to future climate scenarios. The network deals with scientific issues including past climate variability; connections between the Mediterranean and global climate; the Mediterranean Sea circulation and sea level; feedbacks on the global climate system; and regional responses to greenhouse gas, air pollution, and aerosols. The MedCLIVAR initiative was proposed at the 2003 European Geosciences Union assembly in Nice, France. In 2005, it was endorsed by the International Climate Variability and Predictability (CLIVAR) office. Subsequently, the MedCLIVAR Research Network Project was formally approved by the European Science Foundation and launched in May 2006 for a five year duration. Now MedCLIVAR is continuing with self supporting initiatives, such as the third MedCLIVAR conference, which will be held in June 2014 in Ankara (Turkey) , the publication of a special issue of Regional Environmental Change devoted to the climate of the Mediterranean region, and a newsletter, which is published every six months. More information available in Lionello, P., Gacic, M., Gomis, D., Garcia-Herrera, R., Giorgi, F., Planton, S., Trigo, R., (...), Xoplaki, E. (2012) Program focuses on climate of the Mediterranean region, Eos Trans. AGU 93:105-106

Using social network analysis to evaluate health-related adaptation decision-making in Cambodia.

PubMed

Bowen, Kathryn J; Alexander, Damon; Miller, Fiona; Dany, Va

2014-01-30

Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or 'shadow networks') in the context of climate change adaptation policy and activities. The health governance 'map' in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes.

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

PubMed Central

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

2011-01-01

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

Decadal changes in the frequency of major floods in near-natural catchments across North America and Europe

NASA Astrophysics Data System (ADS)

Hodgkins, Glenn A.; Hannaford, Jamie; Whitfield, Paul H.; Burn, Donald H.; Fleig, Anne; Stahl, Kerstin; Renard, Benjamin; Korhonen, Johanna; Murphy, Conor; Crochet, Philippe; Wilson, Donna; Madsen, Henrik

2013-04-01

Recent major floods in North America and Europe have received much press, with some concluding that these floods are more frequent in recent years as a result of anthropogenic warming. There has therefore been considerable scientific effort invested in establishing whether observed flood records show evidence of trends or variability in flood frequency, and to determine whether these patterns can be linked to climatic changes. However, the river catchments used in many published studies are influenced by direct human alteration such as reservoir regulation and urbanisation, which can confound the interpretation of climate-driven variability. Furthermore, a majority of previous studies have analysed changes in low magnitude floods, such as the annual peak flow, at a national scale. Few studies are known that have analysed changes in large floods (greater than 25-year floods) on a continental scale. To fill this research gap, the current study is analysing flood flows from reference hydrologic networks (RHNs) or RHN-like gauges across a large study domain embracing North America and much of Europe. RHNs comprise gauging stations with minimally disturbed catchment conditions, which have a near-natural flow regime and provide good quality data; RHN analyses thus allow hydro-climatic variability to be distinguished from direct artificial disturbances or data inhomogeneities. One of the key innovations in this study is the definition of an RHN-like network on a continental scale. The network incorporates existing, well-established RHNs in Canada, the US, the UK, Ireland and Norway, alongside RHN-like catchments from Europe (France, Switzerland, Iceland, Denmark, Sweden, Finland), which have been incorporated in the network following a major effort to ensure RHN-like status of candidate gauges through consultation with local experts. As the aim of the study is to examine long-term variability in the number of major floods, annual exceedances of 25-, 50-, and 100-year floods during the last 40-100 years are estimated for all study gauges across North America and Europe. These are then pooled, and regional and continental flood frequency time series computed, including separate groups for different types of hydrological regime (pluvial, nival, mixed etc). Preliminary results will be presented, focusing on whether there is evidence for interdecadal variability in the occurrence of flooding at the large scale in Europe and North America. The unique intercontinental dataset is an example of successful international collaboration on hydro-climatic data exchange, which is potentially a step towards establishing RHN-like networks on a global scale. Such networks will make a valuable contribution to the understanding of hydrological change in future.

Influence of social ties to environmentalists on public climate change perceptions

NASA Astrophysics Data System (ADS)

Tindall, D. B.; Piggot, Georgia

2015-06-01

An emerging body of research proposes that climate change concern is shaped by one's social ties and cultural milieu. This work aligns with findings in the well-established field of social network analysis, whereby individuals are understood as being embedded in social networks, and network position can be used to predict attitudes. Here we examine whether having ties to environmental movement organization members is correlated with climate change attitudes amongst the general public. We use data from a nationwide survey of the Canadian public to demonstrate that having social ties to environmental organization members increases the likelihood that an individual member of the public has a plan to deal with climate change. These findings reinforce the value of focusing on social context when examining climate change attitudes, and highlight the role that environmental organization members play in mobilizing climate change responses.

Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

NASA Astrophysics Data System (ADS)

Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

2017-12-01

Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

Framework for a hydrologic climate-response network in New England

USGS Publications Warehouse

Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2015-01-01

Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.

Building a stakeholder network for the Indiana Climate Change Impacts Assessment

NASA Astrophysics Data System (ADS)

Dukes, J. S.; Widhalm, M.

2017-12-01

The Indiana Climate Change Impacts Assessment (IN CCIA) is a stakeholder-informed, service-driven resource developed under the coordination of the Purdue Climate Change Research Center (PCCRC) and with involvement from a diverse mix of contributors throughout the state. The IN CCIA brings together the best available climate change research into a series of reports aimed at helping Hoosiers better understand climate change-related risks so they can prepare for challenges and capitalize on opportunities. The IN CCIA development process aims to 1) increase the dialogue about climate change across the state, 2) provide Indiana decision makers with accessible, credible climate impact information, and 3) build a network of experts and stakeholders to support ongoing assessment efforts and knowledge sharing. This presentation will report on our experience with developing and maintaining a diverse stakeholder network. We will describe our efforts to connect with stakeholders before, during, and after the development of assessment reports and share the top themes that emerged from our pre-assessment inquires and other interactions.

Effects of climate change and wildfire on stream temperatures and salmonid thermal habitat in a mountain river network

Treesearch

Daniel J. Isaak; Charles H. Luce; Bruce E. Rieman; David E. Nagel; Erin E. Peterson; Dona L. Horan; Sharon Parkes; Gwynne L. Chandler

2010-01-01

Mountain streams provide important habitats for many species, but their faunas are especially vulnerable to climate change because of ectothermic physiologies and movements that are constrained to linear networks that are easily fragmented. Effectively conserving biodiversity in these systems requires accurate downscaling of climatic trends to local habitat conditions...

Navigating future uncertainty in marine protected area governance: Lessons from the Scottish MPA network

NASA Astrophysics Data System (ADS)

Hopkins, Charlotte Rachael; Bailey, David Mark; Potts, Tavis

2018-07-01

As international pressure for marine protection has increased, Scotland has increased spatial protection through the development of a Marine Protected Area (MPA) network. Few MPA networks to date have included specific considerations of climate change in the design, monitoring or management of the network. The Scottish MPA network followed a feature-led approach to identify a series of MPAs across the Scottish marine area and incorporated the diverse views of many different stakeholders. This feature led approach has led to wide ranging opinions and understandings regarding the success of the MPA network. Translating ideas of success into a policy approach whilst also considering how climate change may affect these ideas of success is a complex challenge. This paper presents the results of a Delphi process that aimed to facilitate clear communication between academics, policy makers and stakeholders in order to identify specific climate change considerations applicable to the Scottish MPA network. This study engaged a group of academic and non-academic stakeholders to discuss potential options that could be translated into an operational process for management of the MPA network. The results of Delphi process discussion are presented with the output of a management matrix tool, which could aid in future decisions for MPA management under scenarios of climate change.

Collaboration and co-production of climate knowledge: lessons from a network on the front-line

NASA Astrophysics Data System (ADS)

Kettle, N.

2016-12-01

The science-practice gap is broadly considered a major barrier to the production and application of decision-relevant science. This study uses a social network analysis, based on 126 interviews, to analyze the roles and network ties among climate scientists, service providers, and decision makers in Alaska. Our research highlights the importance of key actors and significant differences in bonding and bridging ties across roles - structural characteristics that provide a basis for informing recommendations to build adaptive capacity and support the co-production of knowledge. Our findings also illustrate that some individuals in the network engage in multiple roles, suggesting that conceptualizing the science-practice interface as consisting of "producers" and "consumers" oversimplifies how individuals engage in climate science, services, and decision making. This research supports the notion that the development and use of climate information is a networked phenomenon. It also emphasizes the importance of centralized individuals who are capable of engaging in multiple roles for the transition of knowledge action.

Climate Controls on Tree Growth in the Western Mediterranean

NASA Technical Reports Server (NTRS)

Touchan, Ramzi; Anchukaitis, Kevin J.; Meko, David M.; Kerchouche, Dalila; Slimani, Said; Ilmen, Rachid; Hasnaoui, Fouad; Guibal, Frederic; Canarerim Hesys Hykui; Sanchez-Salguero, Raul;

Stochastic Geomorphology: A Framework for Creating General Principles on Erosion and Sedimentation in River Basins (Invited)

NASA Astrophysics Data System (ADS)

Benda, L. E.

2009-12-01

Stochastic geomorphology refers to the interaction of the stochastic field of sediment supply with hierarchically branching river networks where erosion, sediment flux and sediment storage are described by their probability densities. There are a number of general principles (hypotheses) that stem from this conceptual and numerical framework that may inform the science of erosion and sedimentation in river basins. Rainstorms and other perturbations, characterized by probability distributions of event frequency and magnitude, stochastically drive sediment influx to channel networks. The frequency-magnitude distribution of sediment supply that is typically skewed reflects strong interactions among climate, topography, vegetation, and geotechnical controls that vary between regions; the distribution varies systematically with basin area and the spatial pattern of erosion sources. Probability densities of sediment flux and storage evolve from more to less skewed forms downstream in river networks due to the convolution of the population of sediment sources in a watershed that should vary with climate, network patterns, topography, spatial scale, and degree of erosion asynchrony. The sediment flux and storage distributions are also transformed downstream due to diffusion, storage, interference, and attrition. In stochastic systems, the characteristically pulsed sediment supply and transport can create translational or stationary-diffusive valley and channel depositional landforms, the geometries of which are governed by sediment flux-network interactions. Episodic releases of sediment to the network can also drive a system memory reflected in a Hurst Effect in sediment yields and thus in sedimentological records. Similarly, discreet events of punctuated erosion on hillslopes can lead to altered surface and subsurface properties of a population of erosion source areas that can echo through time and affect subsequent erosion and sediment flux rates. Spatial patterns of probability densities have implications for the frequency and magnitude of sediment transport and storage and thus for the formation of alluvial and colluvial landforms throughout watersheds. For instance, the combination and interference of probability densities of sediment flux at confluences creates patterns of riverine heterogeneity, including standing waves of sediment with associated age distributions of deposits that can vary from younger to older depending on network geometry and position. Although the watershed world of probability densities is rarified and typically confined to research endeavors, it has real world implications for the day-to-day work on hillslopes and in fluvial systems, including measuring erosion, sediment transport, mapping channel morphology and aquatic habitats, interpreting deposit stratigraphy, conducting channel restoration, and applying environmental regulations. A question for the geomorphology community is whether the stochastic framework is useful for advancing our understanding of erosion and sedimentation and whether it should stimulate research to further develop, refine and test these and other principles. For example, a changing climate should lead to shifts in probability densities of erosion, sediment flux, storage, and associated habitats and thus provide a useful index of climate change in earth science forecast models.

Validation of Copernicus Height-resolved Ozone data Products from Sentinel-5P TROPOMI using global sonde and lidar networks (CHEOPS-5P)

NASA Astrophysics Data System (ADS)

Keppens, Arno; Lambert, Jean-Christopher; Hubert, Daan; Verhoelst, Tijl; Granville, José; Ancellet, Gérard; Balis, Dimitris; Delcloo, Andy; Duflot, Valentin; Godin-Beekmann, Sophie; Koukouli, Marilisa; Leblanc, Thierry; Stavrakou, Trissevgeni; Steinbrecht, Wolfgang; Stübi, Réné; Thompson, Anne

2017-04-01

Monitoring of and research on air quality, stratospheric ozone and climate change require global and long-term observation of the vertical distribution of atmospheric ozone, at ever-improving resolution and accuracy. Global tropospheric and stratospheric ozone profile measurement capabilities from space have therefore improved substantially over the last decades. Being a part of the space segment of the Copernicus Atmosphere and Climate Services that is currently under implementation, the upcoming Sentinel-5 Precursor (S5P) mission with its imaging spectrometer TROPOMI (Tropospheric Monitoring Instrument) is dedicated to the measurement of nadir atmospheric radiance and solar irradiance in the UV-VIS-NIR-SWIR spectral range. Ozone profile and tropospheric ozone column data will be retrieved from these measurements by use of several complementary retrieval methods. The geophysical validation of the enhanced height-resolved ozone data products, as well as support to the continuous evolution of the associated retrieval algorithms, is a key objective of the CHEOPS-5P project, a contributor to the ESA-led S5P Validation Team (S5PVT). This work describes the principles and implementation of the CHEOPS-5P quality assessment (QA) and validation system. The QA/validation methodology relies on the analysis of S5P retrieval diagnostics and on comparisons of S5P data with reference ozone profile measurements. The latter are collected from ozonesonde, stratospheric lidar and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch, including the NDACC global and SHADOZ tropical networks. After adaptation of the Multi-TASTE versatile satellite validation environment currently operational in the context of ESA's CCI, EUMETSAT O3M-SAF, and CEOS and SPARC initiatives, a list of S5P data Quality Indicators (QI) will be derived from complementary investigations: (1) data content and information content studies of the S5P data retrievals; (2) traceable preparation of the S5P data and correlative measurements in view of data comparisons (co-location studies, unit and representation conversions, handling of smoothing and sampling issues, independent estimate of tropopause altitude, (sub-)column integration...), with associated error propagation; (3) data comparisons leading to statistical estimates of the systematic bias and random difference between S5P and reference network data as a function of latitude, their cycles, their long-term evolution, and their dependences on influence quantities (e.g., clouds, solar zenith angle, and slant column density); (4) and finally the assessment of compliance with user requirements as formulated, e.g., by Copernicus Atmosphere and Climate services and by GCOS.

Globalization to amplify economic climate losses

NASA Astrophysics Data System (ADS)

Otto, C.; Wenz, L.; Levermann, A.

2015-12-01

Economic welfare under enhanced anthropogenic carbon emissions and associated future warming poses a major challenge for a society with an evolving globally connected economy. Unabated climate change will impact economic output for example through heat-stress-related reductions in productivity. Since meteorologically-induced production reductions can propagate along supply chains, structural changes in the economic network may influence climate-related losses. The role of the economic network evolution for climate impacts has been neither quantified nor qualitatively understood. Here we show that since the beginning of the 21st century the structural change of the global supply network has been such that an increase of spillover losses due to unanticipated climatic events has to be expected. We quantify primary, secondary and higher-order losses from reduced labor productivity under past and present economic and climatic conditions and find that indirect losses are significant and increase with rising temperatures. The connectivity of the economic network has increased in such a way as to foster the propagation of production loss. This supply chain connectivity robustly exhibits the characteristic distribution of self-organized criticality which has been shifted towards higher values since 2001. Losses due to this structural evolution dominated over the effect of comparably weak climatic changes during this decade. Our finding suggests that the current form of globalization may amplify losses due to climatic extremes and thus necessitate structural adaptation that requires more foresight than presently prevalent.

Inference of directed climate networks: role of instability of causality estimation methods

NASA Astrophysics Data System (ADS)

Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

2013-04-01

Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge weights in the networks is ~ 0.6. The networks constructed using nonlinear measures were in general less stable both in real data and stationarized surrogates. Interestingly, when the nonlinear method parameters are optimized with respect to temporal stability of the networks, the networks seem to converge close to those detected by linear Granger causality. This provides further evidence for the hypothesis of overall sparsity and weakness of nonlinear coupling in climate networks on this spatial and temporal scale [3] and sufficient support for the use of linear methods in this context, unless specific clearly detectable nonlinear phenomena are targeted. Acknowledgement: This study is supported by the Czech Science Foundation, Project No. P103/11/J068. [1] Boccaletti, S.; Latora, V.; Moreno, Y.; Chavez, M. & Hwang, D. U.: Complex networks: Structure and dynamics, Physics Reports, 2006, 424, 175-308 [2] Barnett, L.; Barrett, A. B. & Seth, A. K.: Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables, Physical Review Letters, 2009, 103, 238701 [3] Hlinka, J.; Hartman, D.; Vejmelka, M.; Novotná, D.; Paluš, M.: Non-linear dependence and teleconnections in climate data: sources, relevance, nonstationarity, submitted preprint (http://arxiv.org/abs/1211.6688)

Inclusion of climatic and touristic factors in the analysis and modelling of the municipal water demand in a Mediterranean region

NASA Astrophysics Data System (ADS)

Toth, Elena; Bragalli, Cristiana; Neri, Mattia

2017-04-01

In Mediterranean regions, inherently affected by water scarcity conditions, the gap between water availability and demand may further increase in the near future due to both climatic and anthropogenic drivers. In particular, the high degree of urbanization and the concentration of population and activities in coastal areas is often severely impacting the water availability also for the residential sector. It is therefore crucial analysing the importance of both climatic and touristic factors as drivers for the water demand in such areas, to better understand and model the expected consumption in order to improve the water management policies and practices. The study presents an analysis referred to a large number of municipalities, covering almost the whole Romagna region, in Northern Italy, representing one of the most economically developed areas in Europe and characterized by an extremely profitable tourist industry, especially in the coastal cities. For this region it is therefore extremely important to assess the significance of the drivers that may influence the demand in the different periods of the year, that is climatic factors (rainfall depths and occurrence, temperature averages and extremes), but also the presence of tourists, in both official tourist accommodation structures and in holidays homes (and the latter are very difficult to estimate). Analyses on the Italian water industry at seasonal or monthly time scale has been so far, extremely limited in the literature by the scarce availability of data on the water demands, that are made public only as annual volumes. All the study municipalities are supplied by the same water company, who provided monthly consumption volumes data at the main inlet points of the entire distribution network for a period of 7 years (2009-2015). For the same period, precipitation and temperature data have been collected and summarised in indexes representing monthly averages, days of occurrence and over threshold values; in addition, information on the tourist flows, at monthly scale, have been collected and processed. Such data have been validated and aggregated at municipal or multi-municipal scale and are analysed, in particular in reference to a severe dry period occurred in 2011-2012, in order to understand the demand pattern and the users' response to a water scarcity condition, examining the influence of the different climatic and anthropogenic (touristic) drivers on the water demand. Finally, a non-linear model, based on a neural network architecture, was implemented for each municipality, for simulating the monthly water demand as a function of previous demands and of the identified climatic and touristic indexes: the outcomes of the models demonstrate the added value of the addition of determinants based on both climatic and touristic data and such value, as expected, is higher for the coastal municipalities, having a higher tourist vocation.

Assessing measurement uncertainty in meteorology in urban environments

NASA Astrophysics Data System (ADS)

Curci, S.; Lavecchia, C.; Frustaci, G.; Paolini, R.; Pilati, S.; Paganelli, C.

2017-10-01

Measurement uncertainty in meteorology has been addressed in a number of recent projects. In urban environments, uncertainty is also affected by local effects which are more difficult to deal with than for synoptic stations. In Italy, beginning in 2010, an urban meteorological network (Climate Network®) was designed, set up and managed at national level according to high metrological standards and homogeneity criteria to support energy applications. The availability of such a high-quality operative automatic weather station network represents an opportunity to investigate the effects of station siting and sensor exposure and to estimate the related measurement uncertainty. An extended metadata set was established for the stations in Milan, including siting and exposure details. Statistical analysis on an almost 3-year-long operational period assessed network homogeneity, quality and reliability. Deviations from reference mean values were then evaluated in selected low-gradient local weather situations in order to investigate siting and exposure effects. In this paper the methodology is depicted and preliminary results of its application to air temperature discussed; this allowed the setting of an upper limit of 1 °C for the added measurement uncertainty at the top of the urban canopy layer.

Global Change Network: Combine Nutrient Network and Drought Net in China

NASA Astrophysics Data System (ADS)

Yu, Q.; Wang, C.; Zhu, J.; Xu, X.; Yang, H.; Wei, C.; Cong, N.; Wu, H.; Li, H.; Tian, D.; An, H.; Yu, G.

2017-12-01

Globally, all ecosystems will be impacted to some extent by changes in climate means and more frequent and severe periods of climatic extremes. Although there have been numerous studies examining the effects of changes in climatic means on ecological processes and ecosystems, research on climate extremes is far less common and is only now emerging as a distinct research field in ecology. Furthermore, although we have learned much in the past 20 years about how individual ecosystems are likely to respond to climate change, extending this knowledge to regional and continental scales has been a far greater challenge because of the inconsistent design of experiments and ecological complexity. In order to better forecast how entire regions will respond to eutrophication and extreme drought, two key network has been set up, i.e. Nutrient Network, Drought Net. However, there were few sites in China in the network studies, where locates Eurasian Steppe (the biggest grassland in the world) and Tibetan Plateau grassland (the world's highest and largest plateau grassland). To fill the great gap, we have set up ten sites in China (including 5 sites in Eurasia Steppe and 5 site in Tibetan Plateau), combing Nutrient Network and Drought Net treatments and also increased precipitation, called Global Change Network. There are 16 treatments with 6 repeats, and thus 96 plots in the global change network. The nutrient addition treatments are the same with Nutrient Network, i.e. 10 treatments. Precipitation change treatments include an extreme drought (the same with Drought Net) and a water addition (the amount is the same with drought treatment) treatment. The interactive treatments were only conducted in control N and NPK.

Building National Capacity for Climate Change Interpretation: The Role of Leaders, Partnerships, and Networks

NASA Astrophysics Data System (ADS)

Spitzer, W.

2015-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. Our project represents a cross-disciplinary partnership among climate scientists, social and cognitive scientists, and informal education practitioners. We have built a growing national network of more than 250 alumni, including approximately 15-20 peer leaders who co-lead both in-depth training programs and introductory workshops. We have found that this alumni network has been assuming increasing importance in providing for ongoing learning, support for implementation, leadership development, and coalition building. As we look toward the future, we are exploring potential partnerships with other existing networks, both to sustain our impact and to expand our reach. This presentation will address what we have learned in terms of network impacts, best practices, factors for success, and future directions.

Asynchronous reference frame agreement in a quantum network

NASA Astrophysics Data System (ADS)

Islam, Tanvirul; Wehner, Stephanie

2016-03-01

An efficient implementation of many multiparty protocols for quantum networks requires that all the nodes in the network share a common reference frame. Establishing such a reference frame from scratch is especially challenging in an asynchronous network where network links might have arbitrary delays and the nodes do not share synchronised clocks. In this work, we study the problem of establishing a common reference frame in an asynchronous network of n nodes of which at most t are affected by arbitrary unknown error, and the identities of the faulty nodes are not known. We present a protocol that allows all the correctly functioning nodes to agree on a common reference frame as long as the network graph is complete and not more than t\\lt n/4 nodes are faulty. As the protocol is asynchronous, it can be used with some assumptions to synchronise clocks over a network. Also, the protocol has the appealing property that it allows any existing two-node asynchronous protocol for reference frame agreement to be lifted to a robust protocol for an asynchronous quantum network.

The Climate Voices Speakers Network: Collaborating with Nontraditional, National Networks to Develop Climate Literacy on a Local Level

NASA Astrophysics Data System (ADS)

Wegner, K.; Schmidt, C.; Herrin, S.

2015-12-01

How can we leverage the successes of the numerous organizations in the climate change communication arena to build momentum rather than reinvent the wheel? Over the past two years, Climate Voices (climatevoices.org) has established a network of nearly 400 speakers and established partnerships to scale programs that address climate change communication and community engagement. In this presentation, we will present how we have identified and fostered win-win partnerships with organizations, such as GreenFaith Interfaith Partners for the Environment and Rotary International, to reach the broader general public. We will also share how, by drawing on the resources from the National Climate Assessment and the expertise of our own community, we developed and provided our speakers the tools to provide their audiences access to basic climate science - contributing to each audience's ability to understand local impacts, make informed decisions, and gain the confidence to engage in solutions-based actions in response to climate change. We will also discuss how we have created webinar coaching presentations by speakers who aren't climate scientists- and why we have chosen to do so.

Comparison Of In Situ Soil Moisture Measurements: An Examination of the Neutron and Dielectric Measurements within the Illinois Climate Network

USDA-ARS?s Scientific Manuscript database

The continuity of soil moisture time series data is crucial for climatic research. Yet, a common problem for continuous data series is the changing of sensors, not only as replacements are necessary, but as technologies evolve. The Illinois Climate Network has one of the longest data records of soi...

United Kingdom Deriving Emissions linked to Climate Change Network: greenhouse gas and ozone depleting substance measurements from a UK network of tall towers

NASA Astrophysics Data System (ADS)

Stanley, Kieran; O'Doherty, Simon; Young, Dickon; Grant, Aoife; Manning, Alistair; Simmonds, Peter; Oram, Dave; Sturges, Bill; Derwent, Richard

2016-04-01

Real-time, high-frequency measurement networks are essential for investigating the emissions of gases linked with climate change and stratospheric ozone depletion. These networks can be used to verify greenhouse gas (GHG) and ozone depleting substances (ODS) emission inventories for the Kyoto and Montreal Protocols. Providing accurate and reliable country- and region-specific emissions to the atmosphere are critical for reporting to the UN agencies. The United Kingdom Deriving Emissions linked to Climate Change (UK DECC) Network, operating since 2012, is distinguished by its capability to measure at high-frequency, the influence of all of the important species in the Kyoto and Montreal Protocols from the UK, Ireland and Continental Europe. Data obtained from the UK DECC network are also fed into the European Integrated Carbon Observation System (ICOS). This presentation will give an overview of the UK DECC Network, detailing the analytical techniques used to determine the suite of GHGs and ODSs, as well as the calibration strategy used within the network. Interannual results of key GHGs from the network will also be presented.

RAINLINK: Retrieval algorithm for rainfall monitoring employing microwave links from a cellular communication network

NASA Astrophysics Data System (ADS)

Uijlenhoet, R.; Overeem, A.; Leijnse, H.; Rios Gaona, M. F.

2017-12-01

The basic principle of rainfall estimation using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated, which can be converted to average rainfall intensities over the length of a link. Microwave links from cellular communication networks have been proposed as a promising new rainfall measurement technique for one decade. They are particularly interesting for those countries where few surface rainfall observations are available. Yet to date no operational (real-time) link-based rainfall products are available. To advance the process towards operational application and upscaling of this technique, there is a need for freely available, user-friendly computer code for microwave link data processing and rainfall mapping. Such software is now available as R package "RAINLINK" on GitHub (https://github.com/overeem11/RAINLINK). It contains a working example to compute link-based 15-min rainfall maps for the entire surface area of The Netherlands for 40 hours from real microwave link data. This is a working example using actual data from an extensive network of commercial microwave links, for the first time, which will allow users to test their own algorithms and compare their results with ours. The package consists of modular functions, which facilitates running only part of the algorithm. The main processings steps are: 1) Preprocessing of link data (initial quality and consistency checks); 2) Wet-dry classification using link data; 3) Reference signal determination; 4) Removal of outliers ; 5) Correction of received signal powers; 6) Computation of mean path-averaged rainfall intensities; 7) Interpolation of rainfall intensities ; 8) Rainfall map visualisation. Some applications of RAINLINK will be shown based on microwave link data from a temperate climate (the Netherlands), and from a subtropical climate (Brazil). We hope that RAINLINK will promote the application of rainfall monitoring using microwave links in poorly gauged regions around the world. We invite researchers to contribute to RAINLINK to make the code more generally applicable to data from different networks and climates.

Quantifying the quality of precipitation data from different sources

NASA Astrophysics Data System (ADS)

Leijnse, Hidde; Wauben, Wiel; Overeem, Aart; de Haij, Marijn

2015-04-01

There is an increasing demand for high-resolution rainfall data. The current manual and automatic networks of climate and meteorological stations provide high quality rainfall data, but they cannot provide the high spatial and temporal resolution required for many applications. This can only partly be solved by using remotely sensed data. It is therefore necessary to consider third-party data, such as rain gauges operated by amateurs and rainfall intensities from commercial cellular communication links. The quality of such third-party data is highly variable and generally lower than that of dedicated networks. Often, such data quality information is missing for third party data. In order to be able to use data from various sources it is vital that quantitative knowledge of the data quality is available. This holds for all data sources, including the rain gauges in the reference networks of climate and meteorological stations. Data quality information is generally either not available or very limited for third-party data sources. For most dedicated climate meteorological networks, this information is only available for the sensor in laboratory conditions. In many cases, however, a significant part of the measurement errors and uncertainties is determined by the siting and maintenance of the sensor, for which generally only qualitative information is available. Furthermore sensors may have limitations under specific conditions. We aim to quantify data quality for different data sources by performing analyses on collocated data sets. Here we present an intercomparison of two years of precipitation data from six different sources (manual rain gauge, automatic rain gauge, present weather sensor, weather radar, commercial cellular communication links, and Meteosat) at three different locations in the Netherlands. We use auxiliary meteorological data to determine if the quality is influenced by other variables (e.g. the temperature influencing the evaporation from the rain gauge). We use three techniques to compare the data sets: 1) direct comparison; 2) triple collocation (see Stoffelen, 1998); and 3) comparison of statistics. Stoffelen, A. (1998). Toward the true near-surface wind speed: Error modeling and calibration using triple collocation. Journal of Geophysical Research: Oceans (1978-2012), 103(C4), 7755-7766.

Formation of Valley Networks in a Cold and Icy Early Mars Climate: Predictions for Erosion Rates and Channel Morphology

NASA Astrophysics Data System (ADS)

Cassanelli, J.

2017-12-01

Mars is host to a diverse array of valley networks, systems of linear-to-sinuous depressions which are widely distributed across the surface and which exhibit branching patterns similar to the dendritic drainage patterns of terrestrial fluvial systems. Characteristics of the valley networks are indicative of an origin by fluvial activity, providing among the most compelling evidence for the past presence of flowing liquid water on the surface of Mars. Stratigraphic and crater age dating techniques suggest that the formation of the valley networks occurred predominantly during the early geologic history of Mars ( 3.7 Ga). However, whether the valley networks formed predominantly by rainfall in a relatively warm and wet early Mars climate, or by snowmelt and episodic rainfall in an ambient cold and icy climate, remains disputed. Understanding the formative environment of the valley networks will help distinguish between these warm and cold end-member early Mars climate models. Here we test a conceptual model for channel incision and evolution under cold and icy conditions with a substrate characterized by the presence of an ice-free dry active layer and subjacent ice-cemented regolith, similar to that found in the Antarctic McMurdo Dry Valleys. We implement numerical thermal models, quantitative erosion and transport estimates, and morphometric analyses in order to outline predictions for (1) the precise nature and structure of the substrate, (2) fluvial erosion/incision rates, and (3) channel morphology. Model predictions are compared against morphologic and morphometric observational data to evaluate consistency with the assumed cold climate scenario. In the cold climate scenario, the substrate is predicted to be characterized by a kilometers-thick globally-continuous cryosphere below a 50-100 meter thick desiccated ice-free zone. Initial results suggest that, with the predicted substrate structure, fluvial channel erosion and morphology in a cold early Mars climate exposed to episodic high temperatures will not differ significantly from that in a warm climate. The fundamentally different hydrologic conditions are likely to influence other aspects of valley network morphology and morphometry including: drainage density, drainage pattern, and stream orders.

Requirements for data integration platforms in biomedical research networks: a reference model.

PubMed

Ganzinger, Matthias; Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper.

A CLEAN Network Initiative - Accelerating Transition to Post Carbon and Resilient Communities through Education and Engagement

NASA Astrophysics Data System (ADS)

Ledley, T. S.; Niepold, F., III; Bozuwa, J.; Davis, A.; Fraser, J.; Kretser, J.; Poppleton, K. L. I.; Qusba, L.; Ruggiero, K.; Spitzer, W.; Stylinski, C.

2016-12-01

The Climate Literacy and Energy Awareness Network (CLEAN) was formed in 2008 to help climate and energy literacy stakeholders implement the Climate and Energy Literacy Essential Principles to enable effective and responsible decisions with regard to actions that may affect climate. The ongoing conversations of the CLEAN Network have cultivated a culture of shared resources and expertise and allowed for the development of collective impact strategies. However, it has become clear that to accelerate and scale change, effective mitigation, adaptation, and resilience strategies must be developed by a diverse network of stakeholders at the community level to deal with the local impacts of climate change and move toward decarbonized and resilient economies. A group of CLEAN Network members, experienced in establishing effective networks and representing mature climate change education programs, came together to discuss at the community level 1) how we can collectively enable larger scale efforts to 2) develop effective strategies, 3) identify gaps in the system that limit action, and 4) coordinate possible vectors for interceding to advance community level decisions related to climate. We will describe our Theory of Change, based on both the power of communities and increasing climate literacy as a key requirement for sustained progress on the crisis climate change presents. From our Theory of Change, we have begun to outline a national monitoring strategy that can provide communities a measured way to understand their local readiness to respond to the impacts of climate change and understand the magnitude of those impacts in relation to their political and ecological economies. The scale would help describe the robustness of their programs and partnerships to address those impacts, the political climate for working in advance of pending change, and the degree of citizen engagement in resilience planning and action. The goal is to provide a common tool equivalent to GDP that communities could use to see their strengths and leverage points, and where they have the local resources to build solutions or co-develop solutions with others. Though this new tool, communities may be better able to focus on mitigation, adaptation, and the building of resilience that will put into practice the identified Theory of Change.

Workplace injuries, safety climate and behaviors: application of an artificial neural network.

PubMed

Abubakar, A Mohammed; Karadal, Himmet; Bayighomog, Steven W; Merdan, Ethem

2018-05-09

This article proposes and tests a model for the interaction effect of the organizational safety climate and behaviors on workplace injuries. Using artificial neural network and survey data from 306 metal casting industry employees in central Anatolia, we found that an organizational safety climate mitigates workplace injuries, and safety behaviors enforce the strength of the negative impact of the safety climate on workplace injuries. The results suggest a complex relationship between the organizational safety climate, safety behavior and workplace injuries. Theoretical and practical implications are discussed in light of decreasing workplace injuries in the Anatolian metal casting industry.

GUMNET - A new long-term monitoring initiative in the Guadarrama Mountains, Madrid, Spain

NASA Astrophysics Data System (ADS)

Rath, Volker; Fidel González Rouco, J.; Yagüe Anguis, Carlos

2014-05-01

We are announcing a new monitoring network in the Guadarrama Mountains north of Madrid, which is planned to be operational in early 2015. This network integrates atmospheric measurements as well as subsurface observations. It aims at improving the characterization of atmosphere-ground interactions in mountainous terrain, the hydrometeorology of the region, climatic change, and related research lines. It will also provide the meteorological and climate data which form the necessary background information for biological, agricultural and hydrological investigations in this area. Currently, the initiative is supported by research groups from the Complutense and Polytechnical Universities of Madrid (UCM and UPM), the Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), the Spanish National Meteorological Agency (AEMET), and finally the Parque Nacional de la Sierra de Guadarrama (PNSG). This infrastructure forms part of the Campus of Excellence Moncloa, and is supposed to become a focus of local as well as of international research. However, it is not associated with a particular project: data will in principle be available to the scientific and public communities. Also, the integration of new instruments (long or short term) will be welcome. The starting setup is as following: A group of WMO-compatible meteorological station in the central area of the massif will be installed, which include also a subsurface component of boreholes (≡20 m depth), where temperature and moisture will be measured. This core group is complemented by a reference site near El Escorial (including a fixed and a mobile tower for micrometeorological investigations). This setup is embedded in a network of meteorological stations run partly by AEMET and partly by the PNSG, which will provide the information necessary for the characterization of regional meteorology and climate. Finally, part of the data will be made available quasi-online on a central web server in Madrid. (temporary web page: http://tifon.fis.ucm.es/~gumnet/)

STAMMEX high resolution gridded daily precipitation dataset over Germany: a new potential for regional precipitation climate research

NASA Astrophysics Data System (ADS)

Zolina, Olga; Simmer, Clemens; Kapala, Alice; Mächel, Hermann; Gulev, Sergey; Groisman, Pavel

2014-05-01

We present new high resolution precipitation daily grids developed at Meteorological Institute, University of Bonn and German Weather Service (DWD) under the STAMMEX project (Spatial and Temporal Scales and Mechanisms of Extreme Precipitation Events over Central Europe). Daily precipitation grids have been developed from the daily-observing precipitation network of DWD, which runs one of the World's densest rain gauge networks comprising more than 7500 stations. Several quality-controlled daily gridded products with homogenized sampling were developed covering the periods 1931-onwards (with 0.5 degree resolution), 1951-onwards (0.25 degree and 0.5 degree), and 1971-2000 (0.1 degree). Different methods were tested to select the best gridding methodology that minimizes errors of integral grid estimates over hilly terrain. Besides daily precipitation values with uncertainty estimates (which include standard estimates of the kriging uncertainty as well as error estimates derived by a bootstrapping algorithm), the STAMMEX data sets include a variety of statistics that characterize temporal and spatial dynamics of the precipitation distribution (quantiles, extremes, wet/dry spells, etc.). Comparisons with existing continental-scale daily precipitation grids (e.g., CRU, ECA E-OBS, GCOS) which include considerably less observations compared to those used in STAMMEX, demonstrate the added value of high-resolution grids for extreme rainfall analyses. These data exhibit spatial variability pattern and trends in precipitation extremes, which are missed or incorrectly reproduced over Central Europe from coarser resolution grids based on sparser networks. The STAMMEX dataset can be used for high-quality climate diagnostics of precipitation variability, as a reference for reanalyses and remotely-sensed precipitation products (including the upcoming Global Precipitation Mission products), and for input into regional climate and operational weather forecast models. We will present numerous application of the STAMMEX grids spanning from case studies of the major Central European floods to long-term changes in different precipitation statistics, including those accounting for the alternation of dry and wet periods and precipitation intensities associated with prolonged rainy episodes.

Quantifying the climate effects of bioenergy – Choice of reference system

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

Koponen, Kati; Soimakallio, Sampo; Kline, Keith L.

In order to understand the climate effects of a bioenergy system, a comparison between the bioenergy system and a reference system is required. The reference system describes the situation that occurs in the absence of the bioenergy system with respect to the use of land, energy, and materials. The importance of reference systems is discussed in the literature but guidance on choosing suitable reference systems for assessing climate effects of bioenergy is limited. The reference system should align with the purpose of the study. Transparency of reference system assumptions is essential for proper interpretation of bioenergy assessments. This paper presentsmore » guidance for selecting suitable reference systems. Particular attention is given to choosing the land reference. If the goal is to study the climate effects of bioenergy as a part of total anthropogenic activity the reference system should illustrate what is expected in the absence of human activities. In such a case the suitable land reference is natural regeneration, and energy or material reference systems are not relevant. If the goal is to assess the effect of a change in bioenergy use, the reference system should incorporate human activities. In this case suitable reference systems describe the most likely alternative uses of the land, energy and materials in the absence of the change in bioenergy use. The definition of the reference system is furthermore subject to the temporal scope of the study. In practice, selecting and characterizing reference systems will involve various choices and uncertainties which should be considered carefully. As a result, it can be instructive to consider how alternative reference systems influence the results and conclusions drawn from bioenergy assessments.« less

Quantifying the climate effects of bioenergy – Choice of reference system

DOE PAGES

Koponen, Kati; Soimakallio, Sampo; Kline, Keith L.; ...

2017-06-27

In order to understand the climate effects of a bioenergy system, a comparison between the bioenergy system and a reference system is required. The reference system describes the situation that occurs in the absence of the bioenergy system with respect to the use of land, energy, and materials. The importance of reference systems is discussed in the literature but guidance on choosing suitable reference systems for assessing climate effects of bioenergy is limited. The reference system should align with the purpose of the study. Transparency of reference system assumptions is essential for proper interpretation of bioenergy assessments. This paper presentsmore » guidance for selecting suitable reference systems. Particular attention is given to choosing the land reference. If the goal is to study the climate effects of bioenergy as a part of total anthropogenic activity the reference system should illustrate what is expected in the absence of human activities. In such a case the suitable land reference is natural regeneration, and energy or material reference systems are not relevant. If the goal is to assess the effect of a change in bioenergy use, the reference system should incorporate human activities. In this case suitable reference systems describe the most likely alternative uses of the land, energy and materials in the absence of the change in bioenergy use. The definition of the reference system is furthermore subject to the temporal scope of the study. In practice, selecting and characterizing reference systems will involve various choices and uncertainties which should be considered carefully. As a result, it can be instructive to consider how alternative reference systems influence the results and conclusions drawn from bioenergy assessments.« less

An ID Network System to Prepare for Global Environmental/Health Concerns

NASA Astrophysics Data System (ADS)

Asano, Shoichiro; Yoneda, Susumu

Climate change and/or pandemics are global life threatening concerns. For verifying and utilizing monitored data for solving to the Climate Change concerns, a network system based on device ID would be proposed. In this paper, we review the recent standardization initiatives in ITU-T, and propose an ID network that can be used to verify the solutions.

Network structure and influence of the climate change counter-movement

NASA Astrophysics Data System (ADS)

Farrell, Justin

2016-04-01

Anthropogenic climate change represents a global threat to human well-being and ecosystem functioning. Yet despite its importance for science and policy, our understanding of the causes of widespread uncertainty and doubt found among the general public remains limited. The political and social processes driving such doubt and uncertainty are difficult to rigorously analyse, and research has tended to focus on the individual-level, rather than the larger institutions and social networks that produce and disseminate contrarian information. This study presents a new approach by using network science to uncover the institutional and corporate structure of the climate change counter-movement, and machine-learning text analysis to show its influence in the news media and bureaucratic politics. The data include a new social network of all known organizations and individuals promoting contrarian viewpoints, as well as the entirety of all written and verbal texts about climate change from 1993-2013 from every organization, three major news outlets, all US presidents, and every occurrence on the floor of the US Congress. Using network and computational text analysis, I find that the organizational power within the contrarian network, and the magnitude of semantic similarity, are both predicted by ties to elite corporate benefactors.

Which early works are cited most frequently in climate change research literature? A bibliometric approach based on Reference Publication Year Spectroscopy.

PubMed

Marx, Werner; Haunschild, Robin; Thor, Andreas; Bornmann, Lutz

2017-01-01

This bibliometric analysis focuses on the general history of climate change research and, more specifically, on the discovery of the greenhouse effect. First, the Reference Publication Year Spectroscopy (RPYS) is applied to a large publication set on climate change of 222,060 papers published between 1980 and 2014. The references cited therein were extracted and analyzed with regard to publications, which are cited most frequently. Second, a new method for establishing a more subject-specific publication set for applying RPYS (based on the co-citations of a marker reference) is proposed (RPYS-CO). The RPYS of the climate change literature focuses on the history of climate change research in total. We identified 35 highly-cited publications across all disciplines, which include fundamental early scientific works of the nineteenth century (with a weak connection to climate change) and some cornerstones of science with a stronger connection to climate change. By using the Arrhenius (Philos Mag J Sci Ser 5(41):237-276, 1896) paper as a RPYS-CO marker paper, we selected only publications specifically discussing the discovery of the greenhouse effect and the role of carbon dioxide. Using different RPYS approaches in this study, we were able to identify the complete range of works of the celebrated icons as well as many less known works relevant for the history of climate change research. The analyses confirmed the potential of the RPYS method for historical studies: Seminal papers are detected on the basis of the references cited by the overall community without any further assumptions.

Spatial variability in sensitivity of reference crop ET to accuracy of climate data in the Texas High Plains

USDA-ARS?s Scientific Manuscript database

A detailed sensitivity analysis was conducted to determine the relative effects of measurement errors in climate data input parameters on the accuracy of calculated reference crop evapotranspiration (ET) using the ASCE-EWRI Standardized Reference ET Equation. Data for the period of 1995 to 2008, fro...

Mainstreaming climate adaptation in the Asia-Pacific: Role of networks and universities in promoting climate literacy

NASA Astrophysics Data System (ADS)

Ling, F. H.; Yasuhara, K.; Tamura, M.; Tabayashi, Y.; Mimura, N.

2011-12-01

As the international climate regime continues to evolve, adaptation has emerged as a key component of responding to climate change. Due to limited scientific, financial, and institutional capacities, as well as perceived competition with multiple priorities, strategies for adaptive measures are not being implemented at the pace needed to address current and future climate risks. Adaptation networks, both global and in the Asia-Pacific region, have formed to overcome the lack of sufficient communication and collaboration among different stakeholders and domains of expertise. In this presentation, we discuss various efforts at Ibaraki University in Japan to integrate technical and social aspects of adaptation into a multidisciplinary effort, to foster synergies among various networks, to clarify the roles of developed and developing countries, and to develop a standard for assessing vulnerability and adaptability across various geographical contexts.

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

PubMed Central

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

2015-01-01

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

The Global Geometry of River Drainage Basins and the Signature of Tectonic and Autogenic Processes

NASA Astrophysics Data System (ADS)

Giachetta, E.; Willett, S.

2015-12-01

The plan-form structure of the world's river basins contains extensive information regarding tectonic, paleo-geographic and paleo-climate conditions, but interpretation of this structure is complicated by the need to disentangle these processes from the autogenic behavior of fluvial processes. One method of interpreting this structure is by utilizing the well-established scaling between drainage area and channel slope. Integration of this scaling relationship predicts a relationship between channel length and downstream integrated drainage area, referred to in recent studies as χ (Willett et al., 2014). In this paper, we apply this methodology at a continental scale by calculating χ for the world's river networks using hydrological information from the HydroSHED (Hydrological data and maps based on SHuttleElevation Derivatives at multiple Scales) suite of geo-referenced data sets (drainage directions and flow accumulations). River pixels were identified using a minimum drainage area of 5 km2. A constant value of m/n of 0.45 was assumed. We applied a new method to correct χ within closed basins where base level is different from sea level. Mapping of χ illustrates the geometric stability of a river network, thus highlighting where tectonic or climatic forcing has perturbed the shape and geometry. Each continent shows characteristic features. Continental rift margins on all continents show clear asymmetric escarpments indicating inland migration. Active orogenic belts break up older river basins, but are difficult to interpret because of spatially variable uplift rates. Regions of recent tilting are evident even in cratonic areas by lateral reorganizations of basins. Past and pending river captures are identified on all continents. Very few regions on Earth appear to be in near-equilibrium, though some are identified; for example the Urals appears to provide a stable continental divide for Eurasia. Our analysis of maps of χ at the global scale quantifies a dynamic view of Earth's river networks and helps to identify past and ongoing evolution of Earth's landscapes. References Willett, S.D., McCoy, S.W., Perron, J.T., Goren, L., Chen C.Y. (2014): Dynamic reorganization of river basins, Science 343, 1248765. DOI: 10.1126/science.1248765.

Changing transport and traffic risks - a CliPDaR spin off

NASA Astrophysics Data System (ADS)

Matulla, Christoph; Namyslo, Joachim; Gringinger, Julia; Andre, Konrad; Chimani, Barbara; Hollosi, Brigitta; Mlinar, Christian; Gschier, Roland; Fuchs, Tobias; Auer, Inge

2014-05-01

The delivery of goods, people's mobility, the supply with services and the free accessibility of vital resources, as hospitals for instance, are indispensable for our society. All that is possible through functioning transport networks. Globalisation, changes in technology, demography and climate as well as the strong increase in freight traffic are fundamental challenges to the reinforcement of systems in place and the planning of future transport corridors. As for climate change we present an approach to estimate the rate and amount of change than has to be managed in the future by the transport authorities. This assessment is based on combinations of weather elements that potentially harm the transport system. Such combinations (called climate indices, CIs) are evaluated for the past and the future. The evaluation of the past is done by the use of observations; the assessment of the future is based on ensembles of scenario projections, since a single projection does not allow deriving uncertainty based statements. Landslides originating from long term rain events may serve as an example. In 2013 a number of landslides caused substantial destruction and downtimes in turn. The perhaps most prominent example took place in Tirol where the Felbertauern road was hit twice by landslides and the avalanche gallery was destroyed. In our presentation at the EGU we will show changes in CIs that are related to landslides, rutting, frost thaw cycles (e.g. responsible for falling roks) and heavy precipitation events (potentially important for the flooding of transport assets as tunnels and drainage systems or dangerous to bridges). These changes refer to two future periods: the near future (2021-2050) and the remote future (2071-2100); and they refer to the climatological normal period (19961-1990). Referring to landslides there are regions showing no change and other areas with substantial increases, which predominantly occur close to topographic complex terrain. Such regions are characterized by precipitation induced by orographic lifting. Increases can be caused by the more frequent advection of moist air masses carrying more water vapour than observed so far. The findings rely on the so called KLIWAS8 ensemble used already by Matulla et al. 2014 in related cases and generated by Imbery et al. 2013. Findings will be depicted by the 15th 50th and 85th percentiles which allow to cover ranges of possible changes. This way proper measures handy for decision making regarding the planning of transport networks and the reinforcement of existing assets may be developed.

Using crowdsourced data from citizen weather stations to analyse air temperature in 'local climate zones' in Berlin, Germany

NASA Astrophysics Data System (ADS)

Fenner, Daniel; Meier, Fred; Bechtel, Benjamin; Otto, Marco; Scherer, Dieter

2017-04-01

Provision of observational data with high spatial coverage over extended time periods still remains as one of the biggest challenges in urban climate research. Classical meteorological networks are seldomly designed to monitor atmospheric conditions in a broad variety of urban environments, though the heterogeneity of urban structures leads to distinct thermal characteristics on local scales, i.e., hundreds of metres to several kilometres. One approach to overcome the aforementioned challenges of observation networks is to use data from weather stations that are maintained by citizens. The private company 'netatmo' (www.netatmo.com) produces and distributes such citizen weather stations (CWS) around the world. The stations automatically send their data to the netatmo server, and the user decides if data are publicly shared. Shared data can freely be retrieved via an application programming interface. We collected air temperature (T) data for the year 2015 for the city of Berlin, Germany, and surroundings with more than 1500 'netatmo' CWS in the study area. The entire data set was thoroughly quality checked, and filter techniques, involving data from a reference network, were developed to address different types of errors associated with CWS data. Additionally, the accuracy of 'netatmo' CWS was checked in a climate chamber and in a long-term field experiment. Since the terms 'urban' and 'rural' are ambiguous in urban climate studies, Stewart and Oke (2012) developed the 'local climate zone' (LCZ) concept to enhance understanding and interpretation of air temperature differences in urban regions. LCZ classification for the study region was conducted using the 'WUDAPT' approach by Bechtel et al. (2015). The quality-checked CWS data were used to analyse T characteristics of LCZ classes in Berlin and surroundings. Specifically, we analysed how LCZ classes are represented by CWS in 2015, how T varies within each LCZ class ('intra-LCZ variability'), and if significant differences can be detected between LCZ classes ('inter-LCZ differences'). Results show that most 'built-up' LCZ classes in the study region are represented by CWS, while only few CWS are located in 'natural' LCZ classes (i.e. in inner-city parks or in rural areas). T as measured by CWS showed overall good agreement with data from a network of professional weather stations throughout the year, though for some LCZ classes mean monthly deviations were up to 1 K. Intra-LCZ variability of T was especially pronounced during night-time hours and during summer months. We found significant inter-LCZ differences in T mainly for dissimilar LCZ classes and during night-time. Our results indicate the suitability of CWS data for T monitoring of specific LCZ classes and the applicability of this data set for further scientific research. Bechtel, B., P. J. Alexander, J. Böhner, J. Ching, O. Conrad, J. Feddema, G. Mills, L. See, and I. D. Stewart (2015): Mapping Local Climate Zones for a Worldwide Database of the Form and Function of Cities. ISPRS Int. J. Geo-Inf. 4: 199-219 Stewart, I. D. and T. R. Oke (2012): Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc. 93 (12): 1879-1900

A Framework for Bridging Scientists, Knowledge Brokers and Local Decision Makers in State-level Climate Assessments

NASA Astrophysics Data System (ADS)

Galford, G. L.; Nash, J. L.

2016-12-01

Large-scale analyses like the National Climate Assessment (NCA) contain a wealth of information critical to national and regional responses to climate change but tend to be insufficiently detailed for action at state or local levels. Many states now develop assessments (SCAs) to provide relevant, actionable information to state and local authorities. These assessments generate new or additional primary information, build networks and inform stakeholders. Based on our experience in the Vermont Climate Assessment (VCA), we present a SCA framework to engage local decision makers, using a fluid network of scientific experts and knowledge brokers to conduct subject area prioritization, data analysis, and writing. Knowledge brokers bridged the scientific and stakeholder communities, providing a two-way flow of information by capitalizing on their existing networks. Rich citizen records of climate and climate change impacts associated a human voice, a memorable story, or personal observation with a climate record, improving climate information salience. This engagement process that created salient climate information perceived as credible and legitimate by local and state decision makers. We present this framework as an effective structure for SCAs to foster interaction among scientists, knowledge brokers and stakeholders. We include a qualitative impact evaluation and lessons learned for future SCAs.

Data Requirements for Ceiling and Visibility Products Development

DTIC Science & Technology

1994-04-13

and Water - Cycle Experiment (GEWEX), STORM 1, and the Naval Research Laboratory’s Coastal Me- teorology Accelerated Research Initiative field... Water - Cycle Experiment HPCN High Plains Climate Network lOP Intensive Observation Period ICN Illinois Climate Network ITWS Integrated Terminal Weather

Climate change

USGS Publications Warehouse

Cronin, Thomas M.

2016-01-01

Climate change (including climate variability) refers to regional or global changes in mean climate state or in patterns of climate variability over decades to millions of years often identified using statistical methods and sometimes referred to as changes in long-term weather conditions (IPCC, 2012). Climate is influenced by changes in continent-ocean configurations due to plate tectonic processes, variations in Earth’s orbit, axial tilt and precession, atmospheric greenhouse gas (GHG) concentrations, solar variability, volcanism, internal variability resulting from interactions between the atmosphere, oceans and ice (glaciers, small ice caps, ice sheets, and sea ice), and anthropogenic activities such as greenhouse gas emissions and land use and their effects on carbon cycling.

Do 'school coaches' make a difference in school-based mental health promotion? Results from a large focus group study.

PubMed

Corrieri, Sandro; Conrad, Ines; Riedel-Heller, Steffi G

2014-12-01

Mental disorders in children and adolescents are common and have serious consequences. Schools present a key opportunity to promote mental health and implement prevention measures. Four school coaches in five German schools were enlisted to engage students, teachers and parents in building a sustainably healthy school and classroom climate. Altogether, 58 focus groups with students (N=244), parents (N=54) and teachers (N=62) were conducted longitudinally. Topics included: (1) the development of the school and classroom climate, (2) the role of mental health in the regular curriculum, and (3) the role of school coaches in influencing these aspects. Over time, school coaches became trusted reference persons for an increasing number of school system members. They were able to positively influence the school and classroom climate by increasing the awareness of students, teachers and parents of mental health in daily routines. Nevertheless, topics like bullying and student inclusion remained an issue at follow-up. Overall, the school coach intervention is a good model for establishing the topic of mental health in everyday school life and increasing its importance. Future efforts will focus on building self-supporting structures and networks in order to make these efforts sustainable.

Using Social Network Analysis to Evaluate Health-Related Adaptation Decision-Making in Cambodia

PubMed Central

Bowen, Kathryn J.; Alexander, Damon; Miller, Fiona; Dany, Va

2014-01-01

Climate change adaptation in the health sector requires decisions across sectors, levels of government, and organisations. The networks that link these different institutions, and the relationships among people within these networks, are therefore critical influences on the nature of adaptive responses to climate change in the health sector. This study uses social network research to identify key organisational players engaged in developing health-related adaptation activities in Cambodia. It finds that strong partnerships are reported as developing across sectors and different types of organisations in relation to the health risks from climate change. Government ministries are influential organisations, whereas donors, development banks and non-government organisations do not appear to be as influential in the development of adaptation policy in the health sector. Finally, the study highlights the importance of informal partnerships (or ‘shadow networks’) in the context of climate change adaptation policy and activities. The health governance ‘map’ in relation to health and climate change adaptation that is developed in this paper is a novel way of identifying organisations that are perceived as key agents in the decision-making process, and it holds substantial benefits for both understanding and intervening in a broad range of climate change-related policy problems where collaboration is paramount for successful outcomes. PMID:24487452

Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

DTIC Science & Technology

2017-08-01

This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...emissions diverge from each other regarding fossil fuel use, technology, and other socioeconomic factors. As a result, the estimated emissions for each of

Requirements for data integration platforms in biomedical research networks: a reference model

PubMed Central

Knaup, Petra

2015-01-01

Biomedical research networks need to integrate research data among their members and with external partners. To support such data sharing activities, an adequate information technology infrastructure is necessary. To facilitate the establishment of such an infrastructure, we developed a reference model for the requirements. The reference model consists of five reference goals and 15 reference requirements. Using the Unified Modeling Language, the goals and requirements are set into relation to each other. In addition, all goals and requirements are described textually in tables. This reference model can be used by research networks as a basis for a resource efficient acquisition of their project specific requirements. Furthermore, a concrete instance of the reference model is described for a research network on liver cancer. The reference model is transferred into a requirements model of the specific network. Based on this concrete requirements model, a service-oriented information technology architecture is derived and also described in this paper. PMID:25699205

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land-use change.

PubMed

Albert, Cécile H; Rayfield, Bronwyn; Dumitru, Maria; Gonzalez, Andrew

2017-12-01

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land-use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land-use change projections with the latest developments in network-connectivity research and spatial, multipurpose conservation prioritization. We used land-use change simulations to explore robustness of species' habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land-use change. The application of connectivity criteria alongside habitat-quality criteria for protected-area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade-offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low. © 2017 Society for Conservation Biology.

Can Aerosol Offset Urban Heat Island Effect?

NASA Astrophysics Data System (ADS)

Jin, M. S.; Shepherd, J. M.

2009-12-01

The Urban Heat Island effect (UHI) refers to urban skin or air temperature exceeding the temperatures in surrounding non-urban regions. In a warming climate, the UHI may intensify extreme heat waves and consequently cause significant health and energy problems. Aerosols reduce surface insolation via the direct effect, namely, scattering and absorbing sunlight in the atmosphere. Combining the National Aeronautics and Space Administration (NASA) AERONET (AErosol RObotic NETwork) observations over large cities together with Weather Research and Forecasting Model (WRF) simulations, we find that the aerosol direct reduction of surface insolation range from 40-100 Wm-2, depending on seasonality and aerosol loads. As a result, surface skin temperature can be reduced by 1-2C while 2-m surface air temperature by 0.5-1C. This study suggests that the aerosol direct effect is a competing mechanism for the urban heat island effect (UHI). More importantly, both aerosol and urban land cover effects must be adequately represented in meteorological and climate modeling systems in order to properly characterize urban surface energy budgets and UHI.

Does climate have heavy tails?

NASA Astrophysics Data System (ADS)

Bermejo, Miguel; Mudelsee, Manfred

2013-04-01

When we speak about a distribution with heavy tails, we are referring to the probability of the existence of extreme values will be relatively large. Several heavy-tail models are constructed from Poisson processes, which are the most tractable models. Among such processes, one of the most important are the Lévy processes, which are those process with independent, stationary increments and stochastic continuity. If the random component of a climate process that generates the data exhibits a heavy-tail distribution, and if that fact is ignored by assuming a finite-variance distribution, then there would be serious consequences (in the form, e.g., of bias) for the analysis of extreme values. Yet, it appears that it is an open question to what extent and degree climate data exhibit heavy-tail phenomena. We present a study about the statistical inference in the presence of heavy-tail distribution. In particular, we explore (1) the estimation of tail index of the marginal distribution using several estimation techniques (e.g., Hill estimator, Pickands estimator) and (2) the power of hypothesis tests. The performance of the different methods are compared using artificial time-series by means of Monte Carlo experiments. We systematically apply the heavy tail inference to observed climate data, in particular we focus on time series data. We study several proxy and directly observed climate variables from the instrumental period, the Holocene and the Pleistocene. This work receives financial support from the European Commission (Marie Curie Initial Training Network LINC, No. 289447, within the 7th Framework Programme).

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Past climate change on Sky Islands drives novelty in a core developmental gene network and its phenotype.

PubMed

Favé, Marie-Julie; Johnson, Robert A; Cover, Stefan; Handschuh, Stephan; Metscher, Brian D; Müller, Gerd B; Gopalan, Shyamalika; Abouheif, Ehab

2015-09-04

A fundamental and enduring problem in evolutionary biology is to understand how populations differentiate in the wild, yet little is known about what role organismal development plays in this process. Organismal development integrates environmental inputs with the action of gene regulatory networks to generate the phenotype. Core developmental gene networks have been highly conserved for millions of years across all animals, and therefore, organismal development may bias variation available for selection to work on. Biased variation may facilitate repeatable phenotypic responses when exposed to similar environmental inputs and ecological changes. To gain a more complete understanding of population differentiation in the wild, we integrated evolutionary developmental biology with population genetics, morphology, paleoecology and ecology. This integration was made possible by studying how populations of the ant species Monomorium emersoni respond to climatic and ecological changes across five 'Sky Islands' in Arizona, which are mountain ranges separated by vast 'seas' of desert. Sky Islands represent a replicated natural experiment allowing us to determine how repeatable is the response of M. emersoni populations to climate and ecological changes at the phenotypic, developmental, and gene network levels. We show that a core developmental gene network and its phenotype has kept pace with ecological and climate change on each Sky Island over the last ~90,000 years before present (BP). This response has produced two types of evolutionary change within an ant species: one type is unpredictable and contingent on the pattern of isolation of Sky lsland populations by climate warming, resulting in slight changes in gene expression, organ growth, and morphology. The other type is predictable and deterministic, resulting in the repeated evolution of a novel wingless queen phenotype and its underlying gene network in response to habitat changes induced by climate warming. Our findings reveal dynamics of developmental gene network evolution in wild populations. This holds important implications: (1) for understanding how phenotypic novelty is generated in the wild; (2) for providing a possible bridge between micro- and macroevolution; and (3) for understanding how development mediates the response of organisms to past, and potentially, future climate change.

Assessment of production risks for winter wheat in different German regions under climate change conditions

NASA Astrophysics Data System (ADS)

Kersebaum, K. C.; Gandorfer, M.; Wegehenkel, M.

2012-04-01

The study shows climate change impacts on wheat production in selected regions across Germany. To estimate yield and economic effects the agro-ecosystem model HERMES was used. The model performed runs using 2 different releases of the model WETTREG providing statistically downscaled climate change scenarios for the weather station network of the German Weather Service. Simulations were done using intersected GIS information on soil types and land use identifying the most relevant sites for wheat production. The production risks for wheat yields at the middle of this century were compared to a reference of the present climate. The irrigation demand was determined by the model using an automatic irrigation mode. Production risks with and without irrigation were assessed and the economic feasibility to reduce production risks by irrigation was evaluated. Costs and benefits were compared. Additionally, environmental effects, e.g. groundwater recharge and nitrogen emissions were assessed for irrigated and rain fed systems. Results show that positive and negative effects of climate change occur within most regions depending on the site conditions. Water holding capacity and groundwater distance were the most important factors which determined the vulnerability of sites. Under climate change condition in the middle of the next century we can expect especially at sites with low water holding capacity decreasing average gross margins, higher production risks and a reduced nitrogen use efficiency under rainfed conditions. Irrigation seems to be profitable and risk reducing at those sites, provided that water for irrigation is available. Additionally, the use of irrigation can also increase nitrogen use efficiency which reduced emissions by leaching. Despite the site conditions results depend strongly on the used regional climate scenario and the model approach to consider the effect of elevated CO2 in the atmosphere.

Macroecology of Australian Tall Eucalypt Forests: Baseline Data from a Continental-Scale Permanent Plot Network

PubMed Central

Wood, Sam W.; Prior, Lynda D.; Stephens, Helen C.; Bowman, David M. J. S.

2015-01-01

Tracking the response of forest ecosystems to climate change demands large (≥1 ha) monitoring plots that are repeatedly measured over long time frames and arranged across macro-ecological gradients. Continental scale networks of permanent forest plots have identified links between climate and carbon fluxes by monitoring trends in tree growth, mortality and recruitment. The relationship between tree growth and climate in Australia has been recently articulated through analysis of data from smaller forest plots, but conclusions were limited by (a) absence of data on recruitment and mortality, (b) exclusion of non-eucalypt species, and (c) lack of knowledge of stand age or disturbance histories. To remedy these gaps we established the Ausplots Forest Monitoring Network: a continental scale network of 48 1 ha permanent plots in highly productive tall eucalypt forests in the mature growth stage. These plots are distributed across cool temperate, Mediterranean, subtropical and tropical climates (mean annual precipitation 850 to 1900 mm per year; mean annual temperature 6 to 21°C). Aboveground carbon stocks (AGC) in these forests are dominated by eucalypts (90% of AGC) whilst non-eucalypts in the understorey dominated species diversity and tree abundance (84% of species; 60% of stems). Aboveground carbon stocks were negatively related to mean annual temperature, with forests at the warm end of the temperature range storing approximately half the amount of carbon as forests at the cool end of the temperature range. This may reflect thermal constraints on tree growth detected through other plot networks and physiological studies. Through common protocols and careful sampling design, the Ausplots Forest Monitoring Network will facilitate the integration of tall eucalypt forests into established global forest monitoring initiatives. In the context of projections of rapidly warming and drying climates in Australia, this plot network will enable detection of links between climate and growth, mortality and carbon dynamics of eucalypt forests. PMID:26368919

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Advanced functional network analysis in the geosciences: The pyunicorn package

NASA Astrophysics Data System (ADS)

Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

2013-04-01

Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

Vulnerability of dynamic genetic conservation units of forest trees in Europe to climate change.

PubMed

Schueler, Silvio; Falk, Wolfgang; Koskela, Jarkko; Lefèvre, François; Bozzano, Michele; Hubert, Jason; Kraigher, Hojka; Longauer, Roman; Olrik, Ditte C

2014-05-01

A transnational network of genetic conservation units for forest trees was recently documented in Europe aiming at the conservation of evolutionary processes and the adaptive potential of natural or man-made tree populations. In this study, we quantified the vulnerability of individual conservation units and the whole network to climate change using climate favourability models and the estimated velocity of climate change. Compared to the overall climate niche of the analysed target species populations at the warm and dry end of the species niche are underrepresented in the network. However, by 2100, target species in 33-65 % of conservation units, mostly located in southern Europe, will be at the limit or outside the species' current climatic niche as demonstrated by favourabilities below required model sensitivities of 95%. The highest average decrease in favourabilities throughout the network can be expected for coniferous trees although they are mainly occurring within units in mountainous landscapes for which we estimated lower velocities of change. Generally, the species-specific estimates of favourabilities showed only low correlations to the velocity of climate change in individual units, indicating that both vulnerability measures should be considered for climate risk analysis. The variation in favourabilities among target species within the same conservation units is expected to increase with climate change and will likely require a prioritization among co-occurring species. The present results suggest that there is a strong need to intensify monitoring efforts and to develop additional conservation measures for populations in the most vulnerable units. Also, our results call for continued transnational actions for genetic conservation of European forest trees, including the establishment of dynamic conservation populations outside the current species distribution ranges within European assisted migration schemes. © 2013 John Wiley & Sons Ltd.

Development of a Coordinated National Soil Moisture Network: A Pilot Study

NASA Astrophysics Data System (ADS)

Lucido, J. M.; Quiring, S. M.; Verdin, J. P.; Pulwarty, R. S.; Baker, B.; Cosgrove, B.; Escobar, V. M.; Strobel, M.

2014-12-01

Soil moisture data is critical for accurate drought prediction, flood forecasting, climate modeling, prediction of crop yields and water budgeting. However, soil moisture data are collected by many agencies and organizations in the United States using a variety of instruments and methods for varying applications. These data are often distributed and represented in disparate formats, posing significant challenges for use. In recognition of these challenges, the President's Climate Action Plan articulated the need for a coordinated national soil moisture network. In response to this action plan, a team led by the National Integrated Drought Information System has begun to develop a framework for this network and has instituted a proof-of-concept pilot study. This pilot is located in the south-central plains of the US, and will serve as a reference architecture for the requisite data systems and inform the design of the national network. The pilot comprises both in-situ and modeled soil moisture datasets (historical and real-time) and will serve the following use cases: operational drought monitoring, experimental land surface modeling, and operational hydrological modeling. The pilot will be implemented using a distributed network design in order to serve dispersed data in real-time directly from data providers. Standard service protocols will be used to enable future integration with external clients. The pilot network will additionally contain a catalog of data sets and web service endpoints, which will be used to broker web service calls. A mediation and aggregation service will then intelligently request, compile, and transform the distributed datasets from their native formats into a standardized output. This mediation framework allows data to be hosted and maintained locally by the data owners while simplifying access through a single service interface. These data services will then be used to create visualizations, for example, views of the current soil moisture conditions compared to historical baselines via a map-based web application. This talk will comprise an overview of the pilot design and implementation, a discussion of strategies for integrating in-situ and modeled soil moisture data sets as well as lessons learned during the course of the pilot.

Safety perception referents of permanent and temporary employees: safety climate boundaries in the industrial workplace.

PubMed

Luria, Gil; Yagil, Dana

2010-09-01

To explore the significant referents of safety perceptions among permanent and temporary employees in order to identify the boundaries of safety climate in a heterogeneous workforce. Collection of data from semi-structured interviews with employees in manufacturing organizations, using a combination of qualitative and quantitative methods to identify basic safety perceptions. Independent raters used content analysis to examine the data. Analysis of the data revealed differences between safety themes at organization, group and individual levels. Themes relating to the individual were more prevalent among temporary employees, while those relating to the group and the organization prevailed among permanent employees. Permanent employees view organizational and group levels as significant referents of safety perceptions, while temporary employees focus on the individual level. The results challenge the current view of safety climate as a uniform concept for all employees and prescribe boundary conditions for safety climate. It is suggested that organizations should implement "tailor-made" safety-climate practices according to the referents of employee sub-groups. 2009 Elsevier Ltd. All rights reserved.

Determinants of bird species richness, endemism, and island network roles in Wallacea and the West Indies: is geography sufficient or does current and historical climate matter?

PubMed Central

Dalsgaard, Bo; Carstensen, Daniel W; Fjeldså, Jon; Maruyama, Pietro K; Rahbek, Carsten; Sandel, Brody; Sonne, Jesper; Svenning, Jens-Christian; Wang, Zhiheng; Sutherland, William J

2014-01-01

Island biogeography has greatly contributed to our understanding of the processes determining species' distributions. Previous research has focused on the effects of island geography (i.e., island area, elevation, and isolation) and current climate as drivers of island species richness and endemism. Here, we evaluate the potential additional effects of historical climate on breeding land bird richness and endemism in Wallacea and the West Indies. Furthermore, on the basis of species distributions, we identify island biogeographical network roles and examine their association with geography, current and historical climate, and bird richness/endemism. We found that island geography, especially island area but also isolation and elevation, largely explained the variation in island species richness and endemism. Current and historical climate only added marginally to our understanding of the distribution of species on islands, and this was idiosyncratic to each archipelago. In the West Indies, endemic richness was slightly reduced on islands with historically unstable climates; weak support for the opposite was found in Wallacea. In both archipelagos, large islands with many endemics and situated far from other large islands had high importance for the linkage within modules, indicating that these islands potentially act as speciation pumps and source islands for surrounding smaller islands within the module and, thus, define the biogeographical modules. Large islands situated far from the mainland and/or with a high number of nonendemics acted as links between modules. Additionally, in Wallacea, but not in the West Indies, climatically unstable islands tended to interlink biogeographical modules. The weak and idiosyncratic effect of historical climate on island richness, endemism, and network roles indicates that historical climate had little effects on extinction-immigration dynamics. This is in contrast to the strong effect of historical climate observed on the mainland, possibly because surrounding oceans buffer against strong climate oscillations and because geography is a strong determinant of island richness, endemism and network roles. PMID:25505528

Application of the high resolution regional climate change modelling for local impact study upon the hydrological regime in the Buzau and Ialomita river basins

NASA Astrophysics Data System (ADS)

Mic, R.; Corbus, C.; Caian, M.; Neculau, G.

2009-09-01

This paper is a subject of a stage within the scope of European Project 037005 STREP FP6 - CECILIA ("The assessment of impact and vulnerability of climate changes in the Centre and Eastern Europe"). The aim of this project is to assess the impact of climate changes from the regional scale to local scale of Centre and Eastern Europe area, pointing up very high climate resolution usefulness for catching the effects due to the field complexity of study area. The analysed Buzau and Ialomita river basins from Romania covering an area of 14392 km² are situated outside the Curvature Carpathian Mountains, into a zone where the altitude varies from 2500 m to 50 m. In conformity of altitude, the annual precipitation varied from 1400 mm/year, in the mountainous area to 400 mm/year in the plane area and the evapotranspiration between 500 mm/year in the high area to 850 mm/year in the plane area. However, due to a very high variability of weather conditions, droughts as well as excessive humidity periods occur in the course of a year. For the impact study of the possibly climate changes on the runoff in the Buzau and Ialomita river basins, the WatBal model was used, which have been calibrated through the runoff simulation in 17 cross-sections for the reference period 1971 - 2000. WatBal model has two main components. The first is the water balance component that uses continuous functions to describe water movement into a conceptualised basin and the second is the component that allows the calculation of potential evapotranspiration using the Priestly-Taylor equation. For the calculation of changes in the main climatic parameters (atmospheric precipitation, air temperature, relative humidity, solar radiation and wind speed), used in the analysis of the climate change impact on the hydrological regime, there were used the simulations accomplished with a regional climatic model (regCM3), elaborated by ICTP (Trieste), implemented in Romania and used for monthly, seasonal and climate scenarios numerical simulations, at a high spatial resolution of 10 km. Determination of the grid network nodes of the regional climate model regCM3 related to sub-basins from the Buzau and Ialomita river basins was accomplished with a methodology based on obtaining a digital map of river basins, together with related sub-basins. Overlapping this digital map over the network nodes of the grid was made by georeferencing. The changes were calculated for the periods 2021-2050 and 2071-2100 towards the reference period, for each month, like the differences between the values of the climatic parameters corresponding to the two periods. The monthly mean discharges at 4 gauging stations from the Buzau river basin and 13 gauging stations from Ialomita river basin, in the above mentioned hypotheses, are estimated. Study revealed the following changes in the components of the hydrological cycle due to the climate change: - The increase of the evapotranspiration, especially in the summer months, due to the increase of the air temperature. - The reduction of the depth and duration of snow cover due to the increase of the air temperature during winter time. - The variation of the annual mean runoff recorded an increase from the plain to the mountains, standing out a tendency of smoothing during the year in parallel with a global decrease of these. - The early occurrence of the floods and the reduction of the mixed spring floods (snow and rain) by the desynchronisation of the snow melting with the rainfall occurrence. - The reduction of the annual mean runoff on rivers due especially to the increase of the evapotranstpiration.

Climate change threatens European conservation areas

PubMed Central

Araújo, Miguel B; Alagador, Diogo; Cabeza, Mar; Nogués-Bravo, David; Thuiller, Wilfried

2011-01-01

Europe has the world's most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58 ± 2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63 ± 2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P<0.001), but Natura 2000 areas retain climate suitability for species no better and sometimes less effectively than unprotected areas. The risk is high that ongoing efforts to conserve Europe's biodiversity are jeopardized by climate change. New policies are required to avert this risk. PMID:21447141

Empirical Reference Distributions for Networks of Different Size

PubMed Central

Smith, Anna; Calder, Catherine A.; Browning, Christopher R.

2016-01-01

Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics, i.e. graph-level measures of network structural features, across multiple networks that differ in size. Although “normalized” versions of some network statistics exist, we demonstrate via simulation why direct comparison is often inappropriate. We consider normalizing network statistics relative to a simple fully parameterized reference distribution and demonstrate via simulation how this is an improvement over direct comparison, but still sometimes problematic. We propose a new adjustment method based on a reference distribution constructed as a mixture model of random graphs which reflect the dependence structure exhibited in the observed networks. We show that using simple Bernoulli models as mixture components in this reference distribution can provide adjusted network statistics that are relatively comparable across different network sizes but still describe interesting features of networks, and that this can be accomplished at relatively low computational expense. Finally, we apply this methodology to a collection of ecological networks derived from the Los Angeles Family and Neighborhood Survey activity location data. PMID:27721556

Stratosphere-Troposphere Coupling in the Northern Hemisphere analyzed with climate network measures

NASA Astrophysics Data System (ADS)

Kirsch, C.; Donner, R. V.

2017-12-01

The Stratosphere-Troposphere Coupling (STC) is a climate phenomenon providing additional predictive skills for extended-range weather forecasting. The variability of the winter stratospheric polar vortex can particularly influence the tropospheric circulation and, hence, mid-to-high latitude weather for a few weeks or months by strong or weak vortex signals propagating downward with time. This study investigates the STC with climate networks. For this purpose, we use the geopotential height field between 20°N and 90°N at 37 vertical levels from the ERA-Interim reanalysis data from 1979 until 2016. There are two main research questions: (i) Is it possible to define a new, more robust index of the variability of the polar vortex than the currently used NAM index by exploiting climate network properties? (ii) What additional information on STC is provided by climate networks? By calculating the transitivity of evolving climate networks at 10 hPa height, we obtain a new characteristic measure for tracing evolving patterns in stratospheric variability. A higher value than the baseline transitivity indicates an anomalous (strong or weak) polar vortex. Displayed for all vertical levels, the transitivity also exhibits the downward propagation of pressure anomalies into the troposphere. Beyond these findings, we observe additional peaks in the transitivity that does not coincide with weak and strong vortex events. These peaks could be used for identifying the change between winter and summer circulation, also called final warming. We will discuss how these results could potentially affect the predictability of tropospheric weather during boreal spring.

Predicting body temperature and activity of adult Polyommatus icarus using neural network models under current and projected climate scenarios.

PubMed

Howe, P D; Bryant, S R; Shreeve, T G

2007-10-01

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

High resolution probabilistic precipitation forecast over Spain combining the statistical downscaling tool PROMETEO and the AEMET short range EPS system (AEMET/SREPS)

NASA Astrophysics Data System (ADS)

Cofino, A. S.; Santos, C.; Garcia-Moya, J. A.; Gutierrez, J. M.; Orfila, B.

2009-04-01

The Short-Range Ensemble Prediction System (SREPS) is a multi-LAM (UM, HIRLAM, MM5, LM and HRM) multi analysis/boundary conditions (ECMWF, UKMetOffice, DWD and GFS) run twice a day by AEMET (72 hours lead time) over a European domain, with a total of 5 (LAMs) x 4 (GCMs) = 20 members. One of the main goals of this project is analyzing the impact of models and boundary conditions in the short-range high-resolution forecasted precipitation. A previous validation of this method has been done considering a set of climate networks in Spain, France and Germany, by interpolating the prediction to the gauge locations (SREPS, 2008). In this work we compare these results with those obtained by using a statistical downscaling method to post-process the global predictions, obtaining an "advanced interpolation" for the local precipitation using climate network precipitation observations. In particular, we apply the PROMETEO downscaling system based on analogs and compare the SREPS ensemble of 20 members with the PROMETEO statistical ensemble of 5 (analog ensemble) x 4 (GCMs) = 20 members. Moreover, we will also compare the performance of a combined approach post-processing the SREPS outputs using the PROMETEO system. References: SREPS 2008. 2008 EWGLAM-SRNWP Meeting (http://www.aemet.es/documentos/va/divulgacion/conferencias/prediccion/Ewglam/PRED_CSantos.pdf)

Data from selected U.S. Geological Survey national stream water-quality monitoring networks (WQN) on CD-ROM

USGS Publications Warehouse

Alexander, R.B.; Ludtke, A.S.; Fitzgerald, K.K.; Schertz, T.L.

1996-01-01

Data from two U.S. Geological Survey (USGS) national stream water-quality monitoring networks, the National Stream Quality Accounting Network (NASQAN) and the Hydrologic Benchmark Network (HBN), are now available in a two CD-ROM set. These data on CD-ROM are collectively referred to as WQN, water-quality networks. Data from these networks have been used at the national, regional, and local levels to estimate the rates of chemical flux from watersheds, quantify changes in stream water quality for periods during the past 30 years, and investigate relations between water quality and streamflow as well as the relations of water quality to pollution sources and various physical characteristics of watersheds. The networks include 679 monitoring stations in watersheds that represent diverse climatic, physiographic, and cultural characteristics. The HBN includes 63 stations in relatively small, minimally disturbed basins ranging in size from 2 to 2,000 square miles with a median drainage basin size of 57 square miles. NASQAN includes 618 stations in larger, more culturally-influenced drainage basins ranging in size from one square mile to 1.2 million square miles with a median drainage basin size of about 4,000 square miles. The CD-ROMs contain data for 63 physical, chemical, and biological properties of water (122 total constituents including analyses of dissolved and water suspended-sediment samples) collected during more than 60,000 site visits. These data approximately span the periods 1962-95 for HBN and 1973-95 for NASQAN. The data reflect sampling over a wide range of streamflow conditions and the use of relatively consistent sampling and analytical methods. The CD-ROMs provide ancillary information and data-retrieval tools to allow the national network data to be properly and efficiently used. Ancillary information includes the following: descriptions of the network objectives and history, characteristics of the network stations and water-quality data, historical records of important changes in network sample collection and laboratory analytical methods, water reference sample data for estimating laboratory measurement bias and variability for 34 dissolved constituents for the period 1985-95, discussions of statistical methods for using water reference sample data to evaluate the accuracy of network stream water-quality data, and a bibliography of scientific investigations using national network data and other publications relevant to the networks. The data structure of the CD-ROMs is designed to allow users to efficiently enter the water-quality data to user-supplied software packages including statistical analysis, modeling, or geographic information systems. On one disc, all data are stored in ASCII form accessible from any computer system with a CD-ROM driver. The data also can be accessed using DOS-based retrieval software supplied on a second disc. This software supports logical queries of the water-quality data based on constituent concentrations, sample- collection date, river name, station name, county, state, hydrologic unit number, and 1990 population and 1987 land-cover characteristics for station watersheds. User-selected data may be output in a variety of formats including dBASE, flat ASCII, delimited ASCII, or fixed-field for subsequent use in other software packages.

Is U.S. climatic diversity well represented within the existing federal protection network?

Treesearch

Enric Batllori; Carol Miller; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz

2014-01-01

Establishing protection networks to ensure that biodiversity and associated ecosystem services persist under changing environments is a major challenge for conservation planning. The potential consequences of altered climates for the structure and function of ecosystems necessitates new and complementary approaches be incorporated into traditional conservation plans....

PRISM Climate Group, Oregon State U

Science.gov Websites

FAQ PRISM Climate Data The PRISM Climate Group gathers climate observations from a wide range of monitoring networks, applies sophisticated quality control measures, and develops spatial climate datasets to reveal short- and long-term climate patterns. The resulting datasets incorporate a variety of modeling

Climate and ET: Does Plant Water Requirements Increase during Droughts?

NASA Astrophysics Data System (ADS)

Fipps, G.

2015-12-01

Municipalities, engineering consultants and State agencies use reference evapotranspiration (ETo) data (directly and indirectly) for long-term water planning, for designing hydraulic structures, and for establishing regulatory guidance and conservation programs intended to reduce water waste. The use ETo data for agricultural and landscape irrigation scheduling is becoming more common in Texas as ETo-based controllers and automation technologies become more affordable. Until recently, most ETo data has been available as monthly values averaged over many years. Today, automated weather stations and irrigation controllers equipped with specialized instrumentation allow for real-time ETo measurements. With the expected rise in global warming and increased frequency of extreme climate variability in the coming decades, conservation and efficient use of water resources is essential and must make use of the most accurate and representative data available. 2011 marked the driest year on record in the State of Texas. Compounding the lack of rainfall was record heat during the Summer of 2011. An analysis of real time ETo (reference evapotranspiration) data in Texas found that ET was 30 to 50% higher than historic averages during the 2011 Summer. The implications are quite serious, as most current water planning and drought contingency plans do not take into consideration increases in ET during such periods, and irrigation planning and capacity sizing are based on historic averages of consumptive use. This paper examines the relationship between ET and climate during this extreme climatic event. While the solar radiation was near normal levels, temperature and wind was much higher and dew points much lower than norms. The variability and statistical difference between average monthly ETo data and daily, monthly and seasonal ETo measurements (from 2006 to 2014) for selected weather stations of the Texas ET Network. This study will also examine the suitability of using average ETo rates for use in regional water planning and in irrigation scheduling.

Framework for a U.S. Geological Survey Hydrologic Climate-Response Program in Maine

USGS Publications Warehouse

Hodgkins, Glenn A.; Lent, Robert M.; Dudley, Robert W.; Schalk, Charles W.

2009-01-01

This report presents a framework for a U.S. Geological Survey (USGS) hydrologic climate-response program designed to provide early warning of changes in the seasonal water cycle of Maine. Climate-related hydrologic changes on Maine's rivers and lakes in the winter and spring during the last century are well documented, and several river and lake variables have been shown to be sensitive to air-temperature changes. Monitoring of relevant hydrologic data would provide important baseline information against which future climate change can be measured. The framework of the hydrologic climate-response program presented here consists of four major parts: (1) identifying homogeneous climate-response regions; (2) identifying hydrologic components and key variables of those components that would be included in a hydrologic climate-response data network - as an example, streamflow has been identified as a primary component, with a key variable of streamflow being winter-spring streamflow timing; the data network would be created by maintaining existing USGS data-collection stations and establishing new ones to fill data gaps; (3) regularly updating historical trends of hydrologic data network variables; and (4) establishing basins for process-based studies. Components proposed for inclusion in the hydrologic climate-response data network have at least one key variable for which substantial historical data are available. The proposed components are streamflow, lake ice, river ice, snowpack, and groundwater. The proposed key variables of each component have extensive historical data at multiple sites and are expected to be responsive to climate change in the next few decades. These variables are also important for human water use and (or) ecosystem function. Maine would be divided into seven climate-response regions that follow major river-basin boundaries (basins subdivided to hydrologic units with 8-digit codes or larger) and have relatively homogeneous climates. Key hydrologic variables within each climate-response region would be analyzed regularly to maintain up-to-date analyses of year-to-year variability, decadal variability, and longer term trends. Finally, one basin in each climate-response region would be identified for process-based hydrologic and ecological studies.

Climate Voices: Bridging Scientist Citizens and Local Communities across the United States

NASA Astrophysics Data System (ADS)

Wegner, K.; Ristvey, J. D., Jr.

2016-12-01

Based out of the University Corporation for Atmospheric Research (UCAR), the Climate Voices Science Speakers Network (climatevoices.org) has more than 400 participants across the United States that volunteer their time as scientist citizens in their local communities. Climate Voices experts engage in nonpartisan conversations about the local impacts of climate change with groups such as Rotary clubs, collaborate with faith-based groups on climate action initiatives, and disseminate their research findings to K-12 teachers and classrooms through webinars. To support their participants, Climate Voices develops partnerships with networks of community groups, provides trainings on how to engage these communities, and actively seeks community feedback. In this presentation, we will share case studies of science-community collaborations, including meta-analyses of collaborations and lessons learned.

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

PubMed

Liang, Liang; Schwartz, Mark D

2014-10-01

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

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

The predictive state: Science, territory and the future of the Indian climate.

PubMed

Mahony, Martin

2014-02-01

Acts of scientific calculation have long been considered central to the formation of the modern nation state, yet the transnational spaces of knowledge generation and political action associated with climate change seem to challenge territorial modes of political order. This article explores the changing geographies of climate prediction through a study of the ways in which climate change is rendered knowable at the national scale in India. The recent controversy surrounding an erroneous prediction of melting Himalayan glaciers by the Intergovernmental Panel on Climate Change provides a window onto the complex and, at times, antagonistic relationship between the Panel and Indian political and scientific communities. The Indian reaction to the error, made public in 2009, drew upon a national history of contestation around climate change science and corresponded with the establishment of a scientific assessment network, the Indian Network for Climate Change Assessment, which has given the state a new platform on which to bring together knowledge about the future climate. I argue that the Indian Network for Climate Change Assessment is indicative of the growing use of regional climate models within longer traditions of national territorial knowledge-making, allowing a rescaling of climate change according to local norms and practices of linking scientific knowledge to political action. I illustrate the complex co-production of the epistemic and the normative in climate politics, but also seek to show how co-productionist understandings of science and politics can function as strategic resources in the ongoing negotiation of social order. In this case, scientific rationalities and modes of environmental governance contribute to the contested epistemic construction of territory and the evolving spatiality of the modern nation state under a changing climate.

On the use of harmonized HCHO and NO2 MAXDOAS measurements for the validation of GOME-2 and OMI satellite sensors

NASA Astrophysics Data System (ADS)

Pinardi, Gaia; Hendrick, François; Gielen, Clio; Van Roozendael, Michel; De Smedt, Isabelle; Lambert, Jean-Christopher; Granville, José; Compernolle, Steven; Richter, Andreas; Peters, Enno; Piters, Ankie; Wagner, Thomas; Wang, Yang; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso

2017-04-01

During the last decade, the MAXDOAS technique has been increasingly recognized as a source of Fiducial Reference Measurements (FRM) suitable for the validation of satellite nadir observations of species relevant for climate and air quality like NO2 and HCHO. As part of the EU FP7 QA4ECV (Quality Assurance for Essential Climate Variables; see http://www.qa4ecv.eu/) project, efforts have been recently made to harmonize a network of a dozen of MAXDOAS spectrometers in view of their use to assess the quality of satellite climate data records generated within the same project. Harmonization tasks have addressed both retrieval steps involved in MAXDOAS retrievals, i.e. the DOAS spectral fit providing the differential slant column densities (DSCDs) and the conversion of the retrieved DSCDs into vertical profiles and/or vertical column densities (VCDs). In this work, we illustrate the successive harmonization steps and present the resulting QA4ECV MAXDOAS database v2. The approach adopted for the conversion of slant to vertical columns is based on a simplified look-up-table approach. The strength and limitation of this approach are discussed using reference data retrieved using an optimal estimation scheme. The QA4ECV MAXDOAS database is then used to validate satellite data sets of NO2 and HCHO columns derived from the Aura/OMI and MetOp/GOME-2 sensors. The methodology of comparison, which is also a subject of the QA4ECV project, is reviewed with respect to co-location criteria, impact of vertical and horizontal smoothing and representativeness of validation sites. We conclude by assessing the current strengths and limitations of the existing MAXDOAS datasets for NO2 and HCHO satellite validation.

Evaluation of MuSyQ land surface albedo based on LAnd surface Parameters VAlidation System (LAPVAS)

NASA Astrophysics Data System (ADS)

Dou, B.; Wen, J.; Xinwen, L.; Zhiming, F.; Wu, S.; Zhang, Y.

2016-12-01

satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. However, the accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. A new comprehensive and systemic project of china, called the Remote Sensing Application Network (CRSAN), has been launched recent years. Two subjects of this project is developing a Multi-source data Synergized Quantitative Remote Sensin g Production System ( MuSyQ ) and a Web-based validation system named LAnd surface remote sensing Product VAlidation System (LAPVAS) , which aims to generate a quantitative remote sensing product for ecosystem and environmental monitoring and validate them with a reference validation data and a standard validation system, respectively. Land surface BRDF/albedo is one of product datasets of MuSyQ which has a pentad period with 1km spatial resolution and is derived by Multi-sensor Combined BRDF Inversion ( MCBI ) Model. In this MuSyQ albedo evaluation, a multi-validation strategy is implemented by LAPVAS, including directly and multi-scale validation with field measured albedo and cross validation with MODIS albedo product with different land cover. The results reveal that MuSyQ albedo data with a 5-day temporal resolution is in higher sensibility and accuracy during land cover change period, e.g. snowing. But results without regard to snow or changed land cover, MuSyQ albedo generally is in similar accuracy with MODIS albedo and meet the climate modeling requirement of an absolute accuracy of 0.05.

Climate Science Centers: Growing Federal and Academic Expertise in the Nation's Interests

NASA Astrophysics Data System (ADS)

Ryker, S. J.

2014-12-01

The U.S. Department of the Interior's (Interior) natural and cultural resource managers face increasingly complex challenges exacerbated by climate change. In 2009, under Secretarial Order 3289, Interior created eight regional Climate Science Centers managed by the U.S. Geological Survey's (USGS) National Climate Change and Wildlife Science Center and in partnership with universities. Secretarial Order 3289 provides a framework to coordinate climate change science and adaptation efforts across Interior and to integrate science and resource management expertise from Federal, State, Tribal, private, non-profit, and academic partners. In addition to broad research expertise, these Federal/university partnerships provide opportunities to develop a next generation of climate science professionals. These include opportunities to increase the climate science knowledge base of students and practicing professionals; build students' skills in working across the boundary between research and implementation; facilitate networking among researchers, students, and professionals for the application of research to on-the-ground issues; and support the science pipeline in climate-related fields through structured, intensive professional development. In 2013, Climate Science Centers supported approximately 10 undergraduates, 60 graduate students, and 26 postdoctoral researchers. Additional students trained by Climate Science Center-affiliated faculty also contribute valuable time and expertise, and are effectively part of the Climate Science Center network. The Climate Science Centers' education and training efforts have also reached a number of high school students interested in STEM careers, and professionals in natural and cultural resource management. The Climate Science Centers are coordinating to build on each other's successful education and training efforts. Early successes include several intensive education experiences, such as the Alaska Climate Science Center's Girls on Ice, the Northeast's Consortium Retreat, the Northwest's Climate Science Boot Camp; the whole-network Early Career Climate Forum; the South Central Climate Science Center's Minority Internship; and a growing curriculum through Interior's National Conservation Training Center.

Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS

NASA Astrophysics Data System (ADS)

Tobin, Kenneth J.; Torres, Roberto; Crow, Wade T.; Bennett, Marvin E.

2017-09-01

This study applied the exponential filter to produce an estimate of root-zone soil moisture (RZSM). Four types of microwave-based, surface satellite soil moisture were used. The core remotely sensed data for this study came from NASA's long-lasting AMSR-E mission. Additionally, three other products were obtained from the European Space Agency Climate Change Initiative (CCI). These datasets were blended based on all available satellite observations (CCI-active, CCI-passive, and CCI-combined). All of these products were 0.25° and taken daily. We applied the filter to produce a soil moisture index (SWI) that others have successfully used to estimate RZSM. The only unknown in this approach was the characteristic time of soil moisture variation (T). We examined five different eras (1997-2002; 2002-2005; 2005-2008; 2008-2011; 2011-2014) that represented periods with different satellite data sensors. SWI values were compared with in situ soil moisture data from the International Soil Moisture Network at a depth ranging from 20 to 25 cm. Selected networks included the US Department of Energy Atmospheric Radiation Measurement (ARM) program (25 cm), Soil Climate Analysis Network (SCAN; 20.32 cm), SNOwpack TELemetry (SNOTEL; 20.32 cm), and the US Climate Reference Network (USCRN; 20 cm). We selected in situ stations that had reasonable completeness. These datasets were used to filter out periods with freezing temperatures and rainfall using data from the Parameter elevation Regression on Independent Slopes Model (PRISM). Additionally, we only examined sites where surface and root-zone soil moisture had a reasonably high lagged r value (r > 0. 5). The unknown T value was constrained based on two approaches: optimization of root mean square error (RMSE) and calculation based on the normalized difference vegetation index (NDVI) value. Both approaches yielded comparable results; although, as to be expected, the optimization approach generally outperformed NDVI-based estimates. The best results were noted at stations that had an absolute bias within 10 %. SWI estimates were more impacted by the in situ network than the surface satellite product used to drive the exponential filter. The average Nash-Sutcliffe coefficients (NSs) for ARM ranged from -0. 1 to 0.3 and were similar to the results obtained from the USCRN network (0.2-0.3). NS values from the SCAN and SNOTEL networks were slightly higher (0.1-0.5). These results indicated that this approach had some skill in providing an estimate of RZSM. In terms of RMSE (in volumetric soil moisture), ARM values actually outperformed those from other networks (0.02-0.04). SCAN and USCRN RMSE average values ranged from 0.04 to 0.06 and SNOTEL average RMSE values were higher (0.05-0.07). These values were close to 0.04, which is the baseline value for accuracy designated for many satellite soil moisture missions.

Reference aquaplanet climate in the Community Atmosphere Model, Version 5

DOE PAGES

Medeiros, Brian; Williamson, David L.; Olson, Jerry G.

2016-03-18

In this study, fundamental characteristics of the aquaplanet climate simulated by the Community Atmosphere Model, Version 5.3 (CAM5.3) are presented. The assumptions and simplifications of the configuration are described. A 16 year long, perpetual equinox integration with prescribed SST using the model’s standard 18 grid spacing is presented as a reference simulation. Statistical analysis is presented that shows similar aquaplanet configurations can be run for about 2 years to obtain robust climatological structures, including global and zonal means, eddy statistics, and precipitation distributions. Such a simulation can be compared to the reference simulation to discern differences in the climate, includingmore » an assessment of confidence in the differences. To aid such comparisons, the reference simulation has been made available via earthsystemgrid.org. Examples are shown comparing the reference simulation with simulations from the CAM5 series that make different microphysical assumptions and use a different dynamical core.« less

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

PubMed

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

2018-01-09

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

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change

Treesearch

Kristina J. Anderson-Teixeira; Stuart J. Davies; Amy C. Bennett; Erika B. Gonzalez-Akre; Helene C. Muller-Landau; S. Joseph Wright; Kamariah Abu Salim; Angélica M. Almeyda Zambrano; Alfonso Alonso; Jennifer L. Baltzer; Yves Basset; Norman A. Bourg; Eben N. Broadbent; Warren Y. Brockelman; Sarayudh Bunyavejchewin; David F. R. P. Burslem; Nathalie Butt; Min Cao; Dairon Cardenas; George B. Chuyong; Keith Clay; Susan Cordell; Handanakere S. Dattaraja; Xiaobao Deng; Matteo Detto; Xiaojun Du; Alvaro Duque; David L. Erikson; Corneille E.N. Ewango; Gunter A. Fischer; Christine Fletcher; Robin B. Foster; Christian P. Giardina; Gregory S. Gilbert; Nimal Gunatilleke; Savitri Gunatilleke; Zhanqing Hao; William W. Hargrove; Terese B. Hart; Billy C.H. Hau; Fangliang He; Forrest M. Hoffman; Robert W. Howe; Stephen P. Hubbell; Faith M. Inman-Narahari; Patrick A. Jansen; Mingxi Jiang; Daniel J. Johnson; Mamoru Kanzaki; Abdul Rahman Kassim; David Kenfack; Staline Kibet; Margaret F. Kinnaird; Lisa Korte; Kamil Kral; Jitendra Kumar; Andrew J. Larson; Yide Li; Xiankun Li; Shirong Liu; Shawn K.Y. Lum; James A. Lutz; Keping Ma; Damian M. Maddalena; Jean-Remy Makana; Yadvinder Malhi; Toby Marthews; Rafizah Mat Serudin; Sean M. McMahon; William J. McShea; Hervé R. Memiaghe; Xiangcheng Mi; Takashi Mizuno; Michael Morecroft; Jonathan A. Myers; Vojtech Novotny; Alexandre A. de Oliveira; Perry S. Ong; David A. Orwig; Rebecca Ostertag; Jan den Ouden; Geoffrey G. Parker; Richard P. Phillips; Lawren Sack; Moses N. Sainge; Weiguo Sang; Kriangsak Sri-ngernyuang; Raman Sukumar; I-Fang Sun; Witchaphart Sungpalee; Hebbalalu Sathyanarayana Suresh; Sylvester Tan; Sean C. Thomas; Duncan W. Thomas; Jill Thompson; Benjamin L. Turner; Maria Uriarte; Renato Valencia; Marta I. Vallejo; Alberto Vicentini; Tomáš Vrška; Xihua Wang; Xugao Wang; George Weiblen; Amy Wolf; Han Xu; Sandra Yap; Jess Zimmerman

2014-01-01

Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses...

("un")Doing the Next Generation Science Standards: Climate Change Education Actor-Networks in Oklahoma

ERIC Educational Resources Information Center

Colston, Nicole M.; Ivey, Toni A.

2015-01-01

This exploratory research investigated how science education communities of practice in Oklahoma engage in translations of climate change education (CCE). Applications of actor-network theory to educational policymaking facilitate this analysis of the spaces of prescription and spaces of negotiation that characterize CCE in Oklahoma. Informed by…

Nonlinear dynamics of ice-wedge networks and resulting sensitivity to severe cooling events.

PubMed

Plug, L J; Werner, B T

2002-06-27

Patterns of subsurface wedges of ice that form along cooling-induced tension fractures, expressed at the ground surface by ridges or troughs spaced 10 30 m apart, are ubiquitous in polar lowlands. Fossilized ice wedges, which are widespread at lower latitudes, have been used to infer the duration and mean temperature of cold periods within Proterozoic and Quaternary climates, and recent climate trends have been inferred from fracture frequency in active ice wedges. Here we present simulations from a numerical model for the evolution of ice-wedge networks over a range of climate scenarios, based on the interactions between thermal tensile stress, fracture and ice wedges. We find that short-lived periods of severe cooling permanently alter the spacing between ice wedges as well as their fracture frequency. This affects the rate at which the widths of ice wedges increase as well as the network's response to subsequent climate change. We conclude that wedge spacing and width in ice-wedge networks mainly reflect infrequent episodes of rapidly falling ground temperatures rather than mean conditions.

Early Mars Climate Revisited With a Global Probability Map of Martian Valley Network Origin and Distribution

NASA Astrophysics Data System (ADS)

Grau Galofre, A.; Jellinek, M.; Osinski, G. R.

2016-12-01

Valley networks are among the most arresting features on the surface of Mars. Their provocative morphologic resemblance to river valleys on Earth has lead many scientists to argue for Martian river valleys in a "warm and wet" climate scenario, with conditions similar to the terrestrial mid-to-low latitudes. However, this warm scenario is difficult to reconcile with climate models for an Early Mars receiving radiation from a fainter young Sun. Moreover, recent models suggest a colder scenario, with conditions more similar to present day Greenland or Antarctica. Here we use three independent characterization schemes to show quantitative evidence for fluvial, glacial, groundwater sapping and subglacial meltwater channels to build the first global probability map of Martian valley networks. We distinguish a SW-NE corridor of fluvial drainage networks spanning latitudes from 30ºS to 30ºN. We identify additional widespread patterns related to glaciation, subglacial drainage and channels incised by groundwater springs. This global characterization of Martian valleys has profound implications for the average climate of early Mars as well as its variability in space and time.

MSE-impact of PPP-RTK ZTD estimation strategies

NASA Astrophysics Data System (ADS)

Wang, K.; Khodabandeh, A.; Teunissen, P. J. G.

2018-06-01

In PPP-RTK network processing, the wet component of the zenith tropospheric delay (ZTD) cannot be precisely modelled and thus remains unknown in the observation equations. For small networks, the tropospheric mapping functions of different stations to a given satellite are almost equal to each other, thereby causing a near rank-deficiency between the ZTDs and satellite clocks. The stated near rank-deficiency can be solved by estimating the wet ZTD components relatively to that of the reference receiver, while the wet ZTD component of the reference receiver is constrained to zero. However, by increasing network scale and humidity around the reference receiver, enlarged mismodelled effects could bias the network and the user solutions. To consider both the influences of the noise and the biases, the mean-squared errors (MSEs) of different network and user parameters are studied analytically employing both the ZTD estimation strategies. We conclude that for a certain set of parameters, the difference in their MSE structures using both strategies is only driven by the square of the reference wet ZTD component and the formal variance of its solution. Depending on the network scale and the humidity condition around the reference receiver, the ZTD estimation strategy that delivers more accurate solutions might be different. Simulations are performed to illustrate the conclusions made by analytical studies. We find that estimating the ZTDs relatively in large networks and humid regions (for the reference receiver) could significantly degrade the network ambiguity success rates. Using ambiguity-fixed network-derived PPP-RTK corrections, for networks with an inter-station distance within 100 km, the choices of the ZTD estimation strategy is not crucial for single-epoch ambiguity-fixed user positioning. Using ambiguity-float network corrections, for networks with inter-station distances of 100, 300 and 500 km in humid regions (for the reference receiver), the root-mean-squared errors (RMSEs) of the estimated user coordinates using relative ZTD estimation could be higher than those under the absolute case with differences up to millimetres, centimetres and decimetres, respectively.

Interpretation of link fluctuations in climate networks during El Niño periods

NASA Astrophysics Data System (ADS)

Martin, E. A.; Paczuski, M.; Davidsen, J.

2013-05-01

Recent work has shown that the topologies of functional climate networks are sensitive to El Niño events. One important interpretation of the findings was that parts of the globe act in correlated relationships which become weaker, on average, during El Niño periods (this was shown using monthly averaged data where no time lag is required, and with daily averaged data where time lags were utilized). In contrast to this, we show that El Niño periods actually exhibit higher correlations than “Normal” climate conditions, while typically having lower correlations than La Niña periods. We also show that it is crucial to establish the sensitivity and the robustness of a given method used to extract functional climate networks —parameters such as time lags can significantly influence and even totally alter the outcome.

Understanding, representing and communicating earth system processes in weather and climate within CNRCWP

NASA Astrophysics Data System (ADS)

Sushama, Laxmi; Arora, Vivek; de Elia, Ramon; Déry, Stephen; Duguay, Claude; Gachon, Philippe; Gyakum, John; Laprise, René; Marshall, Shawn; Monahan, Adam; Scinocca, John; Thériault, Julie; Verseghy, Diana; Zwiers, Francis

2017-04-01

The Canadian Network for Regional Climate and Weather Processes (CNRCWP) provides significant advances and innovative research towards the ultimate goal of reducing uncertainty in numerical weather prediction and climate projections for Canada's Northern and Arctic regions. This talk will provide an overview of the Network and selected results related to the assessment of the added value of high-resolution modelling that has helped fill critical knowledge gaps in understanding the dynamics of extreme temperature and precipitation events and the complex land-atmosphere interactions and feedbacks in Canada's northern and Arctic regions. In addition, targeted developments in the Canadian regional climate model, that facilitate direct application of model outputs in impact and adaptation studies, particularly those related to the water, energy and infrastructure sectors will also be discussed. The close collaboration between the Network and its partners and end users contributed significantly to this effort.

Competing actors in the climate change arena in Mexico: A network analysis.

PubMed

Ortega Díaz, Araceli; Gutiérrez, Erika Casamadrid

2018-06-01

This paper analyzes the actors in the climate change arena and their influence in directing Mexico toward policies that decrease greenhouse gas emissions, such as the carbon tax and climate change law. The network analysis of the agreement of these laws and public policies in Mexico is a lesson for any country that is in the process of designing and adopting environmental laws. The research is performed using a network analysis that is derived from interviews with various main actors and a discourse analysis of the media. Results show that actors do not coordinate their efforts-they meet frequently but in different inter-ministerial commissions-and do not enforce the same policies. The actors in the industry have formed strong coalitions against the carbon tax and the General Law on Climate Change, whereas international institutions have formed coalitions that support these policies and laws. Copyright © 2018 Elsevier Ltd. All rights reserved.

Projected climate-induced habitat loss for salmonids in the John Day River network, Oregon, U.S.A.

USGS Publications Warehouse

Ruesch, Aaron S.; Torgersen, Christian E.; Lawler, Joshua J.; Olden, Julian D.; Peterson, Erin E.; Volk, Carol J.; Lawrence, David J.

2012-01-01

Climate change will likely have profound effects on cold-water species of freshwater fishes. As temperatures rise, cold-water fish distributions may shift and contract in response. Predicting the effects of projected stream warming in stream networks is complicated by the generally poor correlation between water temperature and air temperature. Spatial dependencies in stream networks are complex because the geography of stream processes is governed by dimensions of flow direction and network structure. Therefore, forecasting climate-driven range shifts of stream biota has lagged behind similar terrestrial modeling efforts. We predicted climate-induced changes in summer thermal habitat for 3 cold-water fish species—juvenile Chinook salmon, rainbow trout, and bull trout (Oncorhynchus tshawytscha, O. mykiss, and Salvelinus confluentus, respectively)—in the John Day River basin, northwestern United States. We used a spatially explicit statistical model designed to predict water temperature in stream networks on the basis of flow and spatial connectivity. The spatial distribution of stream temperature extremes during summers from 1993 through 2009 was largely governed by solar radiation and interannual extremes of air temperature. For a moderate climate change scenario, estimated declines by 2100 in the volume of habitat for Chinook salmon, rainbow trout, and bull trout were 69–95%, 51–87%, and 86–100%, respectively. Although some restoration strategies may be able to offset these projected effects, such forecasts point to how and where restoration and management efforts might focus.

Documenting Uncertainty and Error in Gridded Growing Degree Day and Spring Onset Maps Generated by the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Switzer, J.; Rosemartin, A.; Marsh, L.; Gerst, K.; Crimmins, M.; Weltzin, J. F.

2016-12-01

Since 2016 the USA National Phenology Network (USA-NPN; www.usanpn.org) has produced and delivered daily maps and short-term forecasts of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States. Because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening, and migration, these data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. We will be expanding the suite of gridded map products offered by the USA-NPN to include predictive species-specific maps of phenological transitions in plants and animals at fine spatial and temporal resolution in the future. Data products, such as the gridded maps currently produced by the USA-NPN, inherently contain uncertainty and error arising from multiple sources, including error propagated forward from underlying climate data and from the models implemented. As providing high-quality, vetted data in a transparent way is central to the USA-NPN, we aim to identify and report the sources and magnitude of uncertainty and error in gridded maps and forecast products. At present, we compare our real-time gridded products to independent, trustworthy data sources, such as the Climate Reference Network, on a daily basis and report Mean Absolute Error and bias through an interactive online dashboard.

Creating soil moisture maps based on radar satellite imagery

NASA Astrophysics Data System (ADS)

Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

2017-10-01

The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network.

PubMed

de Nijs, Patrick J; Berry, Nicholas J; Wells, Geoff J; Reay, Dave S

2014-10-20

The need for smallholder farmers to adapt their practices to a changing climate is well recognised, particularly in Africa. The cost of adapting to climate change in Africa is estimated to be $20 to $30 billion per year, but the total amount pledged to finance adaptation falls significantly short of this requirement. The difficulty of assessing and monitoring when adaptation is achieved is one of the key barriers to the disbursement of performance-based adaptation finance. To demonstrate the potential of Bayesian Belief Networks for describing the impacts of specific activities on climate change resilience, we developed a simple model that incorporates climate projections, local environmental data, information from peer-reviewed literature and expert opinion to account for the adaptation benefits derived from Climate-Smart Agriculture activities in Malawi. This novel approach allows assessment of vulnerability to climate change under different land use activities and can be used to identify appropriate adaptation strategies and to quantify biophysical adaptation benefits from activities that are implemented. We suggest that multiple-indicator Bayesian Belief Network approaches can provide insights into adaptation planning for a wide range of applications and, if further explored, could be part of a set of important catalysts for the expansion of adaptation finance.

Quantification of biophysical adaptation benefits from Climate-Smart Agriculture using a Bayesian Belief Network

NASA Astrophysics Data System (ADS)

de Nijs, Patrick J.; Berry, Nicholas J.; Wells, Geoff J.; Reay, Dave S.

2014-10-01

The need for smallholder farmers to adapt their practices to a changing climate is well recognised, particularly in Africa. The cost of adapting to climate change in Africa is estimated to be $20 to $30 billion per year, but the total amount pledged to finance adaptation falls significantly short of this requirement. The difficulty of assessing and monitoring when adaptation is achieved is one of the key barriers to the disbursement of performance-based adaptation finance. To demonstrate the potential of Bayesian Belief Networks for describing the impacts of specific activities on climate change resilience, we developed a simple model that incorporates climate projections, local environmental data, information from peer-reviewed literature and expert opinion to account for the adaptation benefits derived from Climate-Smart Agriculture activities in Malawi. This novel approach allows assessment of vulnerability to climate change under different land use activities and can be used to identify appropriate adaptation strategies and to quantify biophysical adaptation benefits from activities that are implemented. We suggest that multiple-indicator Bayesian Belief Network approaches can provide insights into adaptation planning for a wide range of applications and, if further explored, could be part of a set of important catalysts for the expansion of adaptation finance.

Toward a phenology network in Turkey

NASA Astrophysics Data System (ADS)

Dalfes, H. N.; Ülgen, H.; Zeydanli, U.; Durak, A. T.

2012-04-01

All climate projections indicate that drastic changes are to occur in the Mediterranean Basin and Southwestern Asia. Detailed studies also foresee strong patterns of change in seasonality for most climate fields all across the country, threatening Turkey's rich biodiversity and diverse ecosystems already in trouble due to massive land use changes and careless resource extraction projects. It is therefore obvious that climate impact studies can benefit from detailed and continuous monitoring of relationships between climate and natural systems. Recently started efforts to build a phenology network for Turkey will hopefully constitute a component of a more comprehensive ecological observation infrastructure. The Phenology Network of Turkey Project saw its debut as a joint initiative of an academic institution (Istanbul Technical University) and a research NGO (Nature Conservation Center). It has been decided from the very beginning to rely a much as possible on Internet technologies (provided by the National High Performance Computing Center of Turkey). The effort is also inspired by and collaborates with already established networks in general and USA National Phenology Network in particular. Many protocols, instructional materials and Nature's Notebook application has been barrowed from the USA NPN. The project has been designed from the start as a two-faceted effort: an infrastructure to accumulate/provide useful data to climate/ecosystem research communities and a 'citizen science' project to raise nature and climate change awareness among all components of the society in Turkey in general and secondary education teachers and students in particular. It has been opted to start by gathering plant phenological data. A set with 20 plant species has been designed to serve as a countrywide 'calibration set'. It is also anticipated to salvage and extend as much of possible historical animal (especially bird and butterfly) observations.

Evaluating the Connectivity of a Protected Areas' Network under the Prism of Global Change: The Efficiency of the European Natura 2000 Network for Four Birds of Prey

PubMed Central

Mazaris, Antonios D.; Papanikolaou, Alexandra D.; Barbet-Massin, Morgane; Kallimanis, Athanasios S.; Jiguet, Frédéric; Schmeller, Dirk S.; Pantis, John D.

2013-01-01

Climate and land use changes are major threats to biodiversity. To preserve biodiversity, networks of protected areas have been established worldwide, like the Natura 2000 network across the European Union (EU). Currently, this reserve network consists of more than 26000 sites covering more than 17% of EU terrestrial territory. Its efficiency to mitigate the detrimental effects of land use and climate change remains an open research question. Here, we examined the potential current and future geographical ranges of four birds of prey under scenarios of both land use and climate changes. By using graph theory, we examined how the current Natura 2000 network will perform in regard to the conservation of these species. This approach determines the importance of a site in regard to the total network and its connectivity. We found that sites becoming unsuitable due to climate change are not a random sample of the network, but are less connected and contribute less to the overall connectivity than the average site and thus their loss does not disrupt the full network. Hence, the connectivity of the remaining network changed only slightly from present day conditions. Our findings highlight the need to establish species-specific management plans with flexible conservation strategies ensuring protection under potential future range expansions. Aquila pomarina is predicted to disappear from the southern part of its range and to become restricted to northeastern Europe. Gyps fulvus, Aquila chrysaetos, and Neophron percnopterus are predicted to locally lose some suitable sites; hence, some isolated small populations may become extinct. However, their geographical range and metapopulation structure will remain relatively unaffected throughout Europe. These species would benefit more from an improved habitat quality and management of the existing network of protected areas than from increased connectivity or assisted migration. PMID:23527237

A global network for the control of snail-borne disease using satellite surveillance and geographic information systems.

PubMed

Malone, J B; Bergquist, N R; Huh, O K; Bavia, M E; Bernardi, M; El Bahy, M M; Fuentes, M V; Kristensen, T K; McCarroll, J C; Yilma, J M; Zhou, X N

2001-04-27

At a team residency sponsored by the Rockefeller Foundation in Bellagio, Italy, 10-14 April 2000 an organizational plan was conceived to create a global network of collaborating health workers and earth scientists dedicated to the development of computer-based models that can be used for improved control programs for schistosomiasis and other snail-borne diseases of medical and veterinary importance. The models will be assembled using GIS methods, global climate model data, sensor data from earth observing satellites, disease prevalence data, the distribution and abundance of snail hosts, and digital maps of key environmental factors that affect development and propagation of snail-borne disease agents. A work plan was developed for research collaboration and data sharing, recruitment of new contributing researchers, and means of access of other medical scientists and national control program managers to GIS models that may be used for more effective control of snail-borne disease. Agreement was reached on the use of compatible GIS formats, software, methods and data resources, including the definition of a 'minimum medical database' to enable seamless incorporation of results from each regional GIS project into a global model. The collaboration plan calls for linking a 'central resource group' at the World Health Organization, the Food and Agriculture Organization, Louisiana State University and the Danish Bilharziasis Laboratory with regional GIS networks to be initiated in Eastern Africa, Southern Africa, West Africa, Latin America and Southern Asia. An Internet site, www.gnosisGIS.org, (GIS Network On Snail-borne Infections with special reference to Schistosomiasis), has been initiated to allow interaction of team members as a 'virtual research group'. When completed, the site will point users to a toolbox of common resources resident on computers at member organizations, provide assistance on routine use of GIS health maps in selected national disease control programs and provide a forum for development of GIS models to predict the health impacts of water development projects and climate variation.

Modeling the impact of climate change in Germany with biosphere models for long-term safety assessment of nuclear waste repositories.

PubMed

Staudt, C; Semiochkina, N; Kaiser, J C; Pröhl, G

2013-01-01

Biosphere models are used to evaluate the exposure of populations to radionuclides from a deep geological repository. Since the time frame for assessments of long-time disposal safety is 1 million years, potential future climate changes need to be accounted for. Potential future climate conditions were defined for northern Germany according to model results from the BIOCLIM project. Nine present day reference climate regions were defined to cover those future climate conditions. A biosphere model was developed according to the BIOMASS methodology of the IAEA and model parameters were adjusted to the conditions at the reference climate regions. The model includes exposure pathways common to those reference climate regions in a stylized biosphere and relevant to the exposure of a hypothetical self-sustaining population at the site of potential radionuclide contamination from a deep geological repository. The end points of the model are Biosphere Dose Conversion factors (BDCF) for a range of radionuclides and scenarios normalized for a constant radionuclide concentration in near-surface groundwater. Model results suggest an increased exposure of in dry climate regions with a high impact of drinking water consumption rates and the amount of irrigation water used for agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Topical Collection: Climate-change research by early-career hydrogeologists

NASA Astrophysics Data System (ADS)

Re, Viviana; Maldaner, Carlos H.; Gurdak, Jason J.; Leblanc, Marc; Resende, Tales Carvalho; Stigter, Tibor Y.

2018-05-01

Scientific outreach, international networking, collaboration and adequate courses are needed in both developed and developing countries to enable early-career hydrogeologists to promote long-term multidisciplinary approaches to cope with climate-change issues and emphasize the importance of groundwater in a global strategy for adaptation. One such collaboration has involved the Early Career Hydrogeologists' Network of the International Association of Hydrogeologists (ECHN-IAH) and the UNESCO International Hydrological Programme's (IHP) Groundwater Resources Assessment under the Pressures of Humanity and Climate Changes (GRAPHIC) project. This collaboration seeks to foster the education and involvement of the future generation of water leaders in the debate over groundwater and climate change.

NOAA/NCEI/Regional Climate Services: Working with Partners and Stakeholders across a Wide Network

NASA Astrophysics Data System (ADS)

Mecray, E. L.

2015-12-01

Federal agencies all require plans to be prepared at the state level that outline the implementation of funding to address wildlife habitat, human health, transportation infrastructure, coastal zone management, environmental management, emergency management, and others. These plans are now requiring the consideration of changing climate conditions. So where does a state turn to discuss lessons learned, obtain tools and information to assess climate conditions, and to work with other states in their region? Regional networks and collaboratives are working to deliver this sector by sector. How do these networks work? Do they fit together in any way? What similarities and differences exist? Is anyone talking across these lines to find common climate information requirements? A sketch is forming that links these efforts, not by blending the sectors, but by finding the areas where coordination is critical, where information needs are common, and where delivery mechanisms can be streamlined. NOAA/National Centers for Environmental Information's Regional Climate Services Directors have been working at the interface of stakeholder-driven information delivery since 2010. This talk will outline the regional climate services delivery framework for the Eastern Region, with examples of regional products and information.

Online matchmaking: It's not just for dating sites anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Astrophysics Data System (ADS)

Wegner, K.; Herrin, S.; Schmidt, C.

2015-12-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

Online Matchmaking: It's Not Just for Dating Sites Anymore! Connecting the Climate Voices Science Speakers Network to Educators

NASA Technical Reports Server (NTRS)

Wegner, Kristin; Herrin, Sara; Schmidt, Cynthia

2015-01-01

Scientists play an integral role in the development of climate literacy skills - for both teachers and students alike. By partnering with local scientists, teachers can gain valuable insights into the science practices highlighted by the Next Generation Science Standards (NGSS), as well as a deeper understanding of cutting-edge scientific discoveries and local impacts of climate change. For students, connecting to local scientists can provide a relevant connection to climate science and STEM skills. Over the past two years, the Climate Voices Science Speakers Network (climatevoices.org) has grown to a robust network of nearly 400 climate science speakers across the United States. Formal and informal educators, K-12 students, and community groups connect with our speakers through our interactive map-based website and invite them to meet through face-to-face and virtual presentations, such as webinars and podcasts. But creating a common language between scientists and educators requires coaching on both sides. In this presentation, we will present the "nitty-gritty" of setting up scientist-educator collaborations, as well as the challenges and opportunities that arise from these partnerships. We will share the impact of these collaborations through case studies, including anecdotal feedback and metrics.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

Seasonal change of topology and resilience of ecological networks in wetlandscapes

NASA Astrophysics Data System (ADS)

Bin, Kim; Park, Jeryang

2017-04-01

Wetlands distributed in a landscape provide various ecosystem services including habitat for flora and fauna, hydrologic controls, and biogeochemical processes. Hydrologic regime of each wetland at a given landscape varies by hydro-climatic and geological conditions as well as the bathymetry, forming a certain pattern in the wetland area distribution and spatial organization. However, its large-scale pattern also changes over time as this wetland complex is subject to stochastic hydro-climatic forcing in various temporal scales. Consequently, temporal variation in the spatial structure of wetlands inevitably affects the dispersal ability of species depending on those wetlands as habitat. Here, we numerically show (1) the spatiotemporal variation of wetlandscapes by forcing seasonally changing stochastic rainfall and (2) the corresponding ecological networks which either deterministically or stochastically forming the dispersal ranges. We selected four vernal pool regions with distinct climate conditions in California. The results indicate that the spatial structure of wetlands in a landscape by measuring the wetland area frequency distribution changes by seasonal hydro-climatic condition but eventually recovers to the initial state. However, the corresponding ecological networks, which the structure and function change by the change of distances between wetlands, and measured by degree distribution and network efficiency, may not recover to the initial state especially in the regions with high seasonal dryness index. Moreover, we observed that the changes in both the spatial structure of wetlands in a landscape and the corresponding ecological networks exhibit hysteresis over seasons. Our analysis indicates that the hydrologic and ecological resilience of a wetlandcape may be low in a dry region with seasonal hydro-climatic forcing. Implications of these results for modelling ecological networks depending on hydrologic systems especially for conservation purposes are discussed.

GPS IPW as a Meteorological Parameter and Climate Global Change Indicator

NASA Astrophysics Data System (ADS)

Kruczyk, M.; Liwosz, T.

2011-12-01

Paper focuses on comprehensive investigation of the GPS derived IPW (Integrated Precipitable Water, also IWV) as a geophysical tool. GPS meteorology is now widely acknowledged indirect method of atmosphere sensing. First we demonstrate GPS IPW quality. Most thorough inter-technique comparisons of directly measured IPW are attainable only for some observatories (note modest percentage of GPS stations equipped with meteorological devices). Nonetheless we have managed to compare IPW series derived from GPS tropospheric solutions (ZTD mostly from IGS and EPN solutions) and some independent techniques. IPW values from meteorological sources we used are: radiosoundings, sun photometer and input fields of numerical weather prediction model. We can treat operational NWP models as meteorological database within which we can calculate IWV for all GPS stations independently from network of direct measurements (COSMO-LM model maintained by Polish Institute of Meteorology and Water Management was tried). Sunphotometer (CIMEL-318, Central Geophysical Observatory IGF PAS, Belsk, Poland) data seems the most genuine source - so we decided for direct collocation of GPS measurements and sunphotometer placing permanent GPS receiver on the roof of Belsk Observatory. Next we analyse IPW as geophysical parameter: IPW demonstrates some physical effects evoked by station location (height and series correlation coefficient as a function of distance) and weather patterns like dominant wind directions (in case of neighbouring stations). Deficiency of surface humidity data to model IPW is presented for different climates. This inadequacy and poor humidity data representation in NWP model extremely encourages investigating information exchange potential between Numerical Model and GPS network. The second and most important aspect of this study concerns long series of IPW (daily averaged) which can serve as climatological information indicator (water vapour role in climate system is hard to exaggerate). Especially intriguing are relatively unique shape of such series in different climates. Long lasting changes in weather conditions: 'dry' and 'wet' years are also visible. The longer and more uniform our series are the better chance to estimate the magnitude of climatological IWV changes. Homogenous ZTD solution during long period is great concern in this approach (problems with GPS strategy and reference system changes). In case of continental network (EUREF Permanent Network) reliable data we get only after reprocessing. Simple sinusoidal model has been adjusted to the IPW series (LS method) for selected stations (mainly Europe but also other continents - IGS stations), every year separately. Not only amplitudes but also phases of annual signal differ from year to year. Longer IPW series (up to 14 years) searched for some climatological signal sometimes reveal weak steady trend. Large number of GPS permanent stations, relative easiness of IPW derivation (only and surface meteo data needed apart from GPS solution) and water vapour significance in water cycle and global climate make this GPS IPW promising element of global environmental change monitoring.

Climatic similarity and biological exchange in the worldwide airline transportation network

PubMed Central

Tatem, Andrew J; Hay, Simon I

2007-01-01

Recent increases in the rates of biological invasion and spread of infectious diseases have been linked to the continued expansion of the worldwide airline transportation network (WAN). Here, the global structure of the WAN is analysed in terms of climatic similarity to illuminate the risk of deliberate or accidental movements of climatically sensitive organisms around the world. From over 44 000 flight routes, we show, for each month of an average year, (i) those scheduled routes that link the most spatially distant but climatically similar airports, (ii) the climatically best-connected airports, and (iii) clusters of airports with similar climatic features. The way in which traffic volumes alter these findings is also examined. Climatic similarity across the WAN is skewed (most geographically close airports are climatically similar) but heavy-tailed (there are considerable numbers of geographically distant but climatically similar airports), with climate similarity highest in the June–August period, matching the annual peak in air traffic. Climatically matched, geographically distant airports form subnetworks within the WAN that change throughout the year. Further, the incorporation of passenger and freight traffic data highlight at greater risk of invasion those airports that are climatically well connected by numerous high capacity routes. PMID:17426013

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.

Small-scale variations of climate change in mountainous forested terrain - a regional study from H.J. Andrews Long Term Ecological Research site in Oregon, USA

NASA Astrophysics Data System (ADS)

Honzakova, Katerina; Hoffmann, Peter; Jones, Julia; Thomas, Christoph

2017-04-01

There has been conflicting evidence as to whether high elevations are experiencing more pronounced climate warming than lower elevations in mountainous regions. In this study we analyze temperature records from H.J. Andrews Long Term Ecological Research, Oregon, USA and several nearby areas, comprising together 28 stations located in Cascade Mountains. The data, starting in 1958, are first checked for quality and homogenized using the Standard Normal Homogeneity Test. As a reference, composite climate time series based on the Global Historic Climate Network is created and together with cross-referencing against station records used to correct breaks and shifts in the data. In the next step, we investigate temperature patterns of the study site from 1958 to 2016 and compare them for valley and hill stations. In particular, we explore seasonality and inter-annual variability of the records and trends of the last day of frost. Additionally, 'cold' sums (positive and negative) are calculated to obtain a link between temperature and ecosystems' responses (such as budbreaks). So far, valley stations seem to be more prone to climate change than ridge or summit stations, contrary to current thinking. Building on previous knowledge, we attempt to provide physical explanations for the temperature records, focusing on wind patterns and associated phenomena such as cold air drainage and pooling. To aid this we analyze wind speed and direction data available for some of the stations since 1996, including seasonality and inter-annual variability of the observed flows.

A new CM SAF Solar Surface Radiation Climate Data Set derived from Meteosat Satellite Observations

NASA Astrophysics Data System (ADS)

Trentmann, J.; Mueller, R. W.; Pfeifroth, U.; Träger-Chatterjee, C.; Cremer, R.

2014-12-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. It is mandatory to monitor this part of the earth's energy balance, and thus gain insights on the state and variability of the climate system. In addition, data sets of the surface solar radiation have received increased attention over the recent years as an important source of information for the planning of solar energy applications. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving surface solar radiation from geostationary and polar-orbiting satellite instruments. While CM SAF is focusing on the generation of high-quality long-term climate data records, also operationally data is provided in short time latency within 8 weeks. Here we present SARAH (Solar Surface Radiation Dataset - Heliosat), i.e. the new CM SAF Solar Surface Radiation data set based on Meteosat satellite observations. SARAH provides instantaneous, daily- and monthly-averaged data of the effective cloud albedo (CAL), the direct normalized solar radiation (DNI) and the solar irradiance (SIS) from 1983 to 2013 for the full view of the Meteosat satellite (i.e, Europe, Africa, parts of South America, and the Atlantic ocean). The data sets are generated with a high spatial resolution of 0.05 deg allowing for detailed regional studies, and are available in netcdf-format at no cost without restrictions at www.cmsaf.eu. We provide an overview of the data sets, including a validation against reference measurements from the BSRN and GEBA surface station networks.

Modeling The effect of elevated CO2 and climate change on reference evapotranspiration in the semi-arid Great Plains

USDA-ARS?s Scientific Manuscript database

Changes in evapotranspiration demand due to global warming will have profound impact on irrigation water demand and agricultural productivity. In this study, effects of possible future anthropogenic climate change on reference evapotranspiration (ETo) was evaluated. The Penman-Monteith equation was ...

Medium-range reference evapotranspiration forecasts for the contiguous United States based on multi-model numerical weather predictions

NASA Astrophysics Data System (ADS)

Medina, Hanoi; Tian, Di; Srivastava, Puneet; Pelosi, Anna; Chirico, Giovanni B.

2018-07-01

Reference evapotranspiration (ET0) plays a fundamental role in agronomic, forestry, and water resources management. Estimating and forecasting ET0 have long been recognized as a major challenge for researchers and practitioners in these communities. This work explored the potential of multiple leading numerical weather predictions (NWPs) for estimating and forecasting summer ET0 at 101 U.S. Regional Climate Reference Network stations over nine climate regions across the contiguous United States (CONUS). Three leading global NWP model forecasts from THORPEX Interactive Grand Global Ensemble (TIGGE) dataset were used in this study, including the single model ensemble forecasts from the European Centre for Medium-Range Weather Forecasts (EC), the National Centers for Environmental Prediction Global Forecast System (NCEP), and the United Kingdom Meteorological Office forecasts (MO), as well as multi-model ensemble forecasts from the combinations of these NWP models. A regression calibration was employed to bias correct the ET0 forecasts. Impact of individual forecast variables on ET0 forecasts were also evaluated. The results showed that the EC forecasts provided the least error and highest skill and reliability, followed by the MO and NCEP forecasts. The multi-model ensembles constructed from the combination of EC and MO forecasts provided slightly better performance than the single model EC forecasts. The regression process greatly improved ET0 forecast performances, particularly for the regions involving stations near the coast, or with a complex orography. The performance of EC forecasts was only slightly influenced by the size of the ensemble members, particularly at short lead times. Even with less ensemble members, EC still performed better than the other two NWPs. Errors in the radiation forecasts, followed by those in the wind, had the most detrimental effects on the ET0 forecast performances.

CTFS/ForestGEO: A global network to monitor forest interactions with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Muller-Landau, H.; McMahon, S.; Davies, S. J.

2013-12-01

Forests are an influential component of the global carbon cycle and strongly influence Earth's climate. Climate change is altering the dynamics of forests globally, which may result in significant climate feedbacks. Forest responses to climate change entail both short-term ecophysiological responses and longer-term directional shifts in community composition. These short- and long-term responses of forest communities to climate change may be better understood through long-term monitoring of large forest plots globally using standardized methodology. Here, we describe a global network of forest research plots (CTFS/ForestGEO) of utility for understanding forest responses to climate change and consequent feedbacks to the climate system. CTFS/ForestGEO is an international network consisting of 51 sites ranging in size from 2-150 ha (median size: 25 ha) and spanning from 25°S to 52°N latitude. At each site, every individual > 1cm DBH is mapped and identified, and recruitment, growth, and mortality are monitored every 5 years. Additional measurements include aboveground productivity, carbon stocks, soil nutrients, plant functional traits, arthropod and vertebrates monitoring, DNA barcoding, airborne and ground-based LiDAR, micrometeorology, and weather monitoring. Data from this network are useful for understanding how forest ecosystem structure and function respond to spatial and temporal variation in abiotic drivers, parameterizing and evaluating ecosystem and earth system models, aligning airborne and ground-based measurements, and identifying directional changes in forest productivity and composition. For instance, CTFS/ForestGEO data have revealed that solar radiation and night-time temperature are important drivers of aboveground productivity in moist tropical forests; that tropical forests are mixed in terms of productivity and biomass trends over the past couple decades; and that the composition of Panamanian forests has shifted towards more drought-tolerant species. Ongoing monitoring will be vital to understanding global forest dynamics in an era of climate change.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

Global terrestrial water storage connectivity revealed using complex climate network analyses

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Chen, J.; Donges, J.

2015-07-01

Terrestrial water storage (TWS) exerts a key control in global water, energy, and biogeochemical cycles. Although certain causal relationship exists between precipitation and TWS, the latter quantity also reflects impacts of anthropogenic activities. Thus, quantification of the spatial patterns of TWS will not only help to understand feedbacks between climate dynamics and the hydrologic cycle, but also provide new insights and model calibration constraints for improving the current land surface models. This work is the first attempt to quantify the spatial connectivity of TWS using the complex network theory, which has received broad attention in the climate modeling community in recent years. Complex networks of TWS anomalies are built using two global TWS data sets, a remote sensing product that is obtained from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and a model-generated data set from the global land data assimilation system's NOAH model (GLDAS-NOAH). Both data sets have 1° × 1° grid resolutions and cover most global land areas except for permafrost regions. TWS networks are built by first quantifying pairwise correlation among all valid TWS anomaly time series, and then applying a cutoff threshold derived from the edge-density function to retain only the most important features in the network. Basinwise network connectivity maps are used to illuminate connectivity of individual river basins with other regions. The constructed network degree centrality maps show the TWS anomaly hotspots around the globe and the patterns are consistent with recent GRACE studies. Parallel analyses of networks constructed using the two data sets reveal that the GLDAS-NOAH model captures many of the spatial patterns shown by GRACE, although significant discrepancies exist in some regions. Thus, our results provide further measures for constraining the current land surface models, especially in data sparse regions.

Climate impact on spreading of airborne infectious diseases. Complex network based modeling of climate influences on influenza like illnesses

NASA Astrophysics Data System (ADS)

Brenner, Frank; Marwan, Norbert; Hoffmann, Peter

2017-06-01

In this study we combined a wide range of data sets to simulate the outbreak of an airborne infectious disease that is directly transmitted from human to human. The basis is a complex network whose structures are inspired by global air traffic data (from openflights.org) containing information about airports, airport locations, direct flight connections and airplane types. Disease spreading inside every node is realized with a Susceptible-Exposed-Infected-Recovered (SEIR) compartmental model. Disease transmission rates in our model are depending on the climate environment and therefore vary in time and from node to node. To implement the correlation between water vapor pressure and influenza transmission rate [J. Shaman, M. Kohn, Proc. Natl. Acad. Sci. 106, 3243 (2009)], we use global available climate reanalysis data (WATCH-Forcing-Data-ERA-Interim, WFDEI). During our sensitivity analysis we found that disease spreading dynamics are strongly depending on network properties, the climatic environment of the epidemic outbreak location, and the season during the year in which the outbreak is happening.

An Adjoint Force-restore Model for Glacier Terminus Fluctuations

NASA Astrophysics Data System (ADS)

Ren, D.; Leslie, L.; Karoly, D.

2006-12-01

A linear inverse formula comprises the basis for an individual treatment of 7 central Asian (25-55°N; 70-95°E) glaciers. The linear forward model is based on first order glacier dynamics, and requires the knowledge of reference states of forcing and glacier perturbation magnitude. In this study, the adjoint based 4D-var method was applied to optimally determine the reference states and make it possible to start the integration at an arbitrarily chosen time, and thus suitable to use the availability of the coupled general circulation model (CGCM) predictions of future temperature scenarios. Two sensitive yet uncertain glacier parameters and reference states at year 1900 are inferred from observed glacier length records distributed irregularly over the 20th century and the regional mean annual temperature anomaly (against 1961-1990 reference) time series. We rotated the temperature forcing for the Hadley Centre- Climatic Research Unit of the University of East Anglia (HadCRUT2), the Global Historical Climatology Network (GHCN) observations, and the ensemble mean of multiple CGCM runs and compared the retrieval results. Because of the high resemblance between the three data sources after 1960, it was decided practicable to use the observed temperature as forcing in retrieving the model parameters and initial states and then run an extended period with forcing from ensemble mean CGCM temperature of the next century. The length fluctuation is estimated for the transient climate period with 9 CGCM simulations under SRES A2 (a strong emission scenario from the Special report on Emissions Scenarios). For the 60-year period 2000- 2060, all glaciers experienced salient shrinkage, especially those with gentle slopes. Although nearly one-third the year 2000 length will be reduced for some small glaciers, the very existence of the glaciers studied here is not threatened by year 2060. The differences in individual glacier responses are very large. No straightforward relationship is found between glacier size and fractional change of its length.

Analysis of the structure of climate networks under El Niño and La Niña conditions

NASA Astrophysics Data System (ADS)

Graciosa, Juan Carlos; Pastor, Marissa

The El Niño-Southern Oscillation (ENSO) is the most important driver of natural climate variability and is characterized by anomalies in the sea surface temperatures (SST) over the tropical Pacific ocean. It has three phases: neutral, a warming phase or El Niño, and a cooling phase called La Niña. In this research, we modeled the climate under the three phases as a network and characterized its properties. We utilized the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) daily surface temperature reanalysis data from January 1950 to December 2016. A network associated to a month was created using the temperature spanning from the previous month to the succeeding month, for a total of three months worth of data for each network. Each site of the included data was a potential node in the network and the existence of links were determined by the strength of their relationship, which was based on mutual information. Interestingly, we found that climate networks exhibit small-world properties and these are found to be more prominent from October to April, coinciding with observations that El Niño occurrences peak from December to March. During these months, the temperature of a relatively large part of the Pacific ocean and its surrounding areas increase and the anomaly values become synchronized. This synchronization in the temperature anomalies forms links around the Pacific, increasing the clustering in the region and in effect, that of the entire network.

The PAGES 2k Network, Phase 3: Themes and Call for Participation

NASA Astrophysics Data System (ADS)

von Gunten, L.; Mcgregor, H. V.; Martrat, B.; St George, S.; Neukom, R.; Bothe, O.; Linderholm, H. W.; Phipps, S. J.; Abram, N.

2017-12-01

The past 2000 years (the "2k" interval) provides critical context for understanding recent anthropogenic forcing of the climate and provides baseline information about the characteristics of natural climate variability. It also presents opportunities to improve the interpretation of proxy observations and to evaluate the climate models used to make future projections. Phases 1 and 2 of the PAGES 2k Network focussed on building regional and global surface temperature reconstructions for terrestrial regions and the oceans, and comparing these with model simulations to identify mechanisms of climate variation on interannual to bicentennial time scales. Phase 3 was launched in May 2017 and aims to address major questions around past hydroclimate, climate processes and proxy uncertainties. Its scientific themes are: Theme 1: "Climate Variability, Modes and Mechanisms"Further understand the mechanisms driving regional climate variability and change on interannual to centennial time scales; Theme 2: "Methods and Uncertainties"Reduce uncertainties in the interpretation of observations imprinted in paleoclimatic archives by environmental sensors; Theme 3: "Proxy and Model Understanding"Identify and analyse the extent of agreement between reconstructions and climate model simulations. Research is organized as a linked network of well-defined projects, identified and led by 2k community members. The 2k projects focus on specific scientific questions aligned with Phase 3 themes, rather than being defined along regional boundaries. New 2k projects can be proposed at any time at http://www.pastglobalchanges.org/ini/wg/2k-network/projects An enduring element of PAGES 2k is a culture of collegiality, transparency, and reciprocity. Phase 3 seeks to stimulate community based projects and facilitate collaboration between researchers from different regions and career stages, drawing on the breadth and depth of the global PAGES 2k community. All PAGES 2k projects also promote best practises in data stewardship for the research community. The network is open to anyone who is interested. If you would like to participate in PAGES 2k or receive updates, please join our mailing list or speak to a coordinating committee member.

A 280-Year Long Series of Phenological Observations of Cherry Tree Blossoming Dates for Switzerland

NASA Astrophysics Data System (ADS)

Rutishauser, T.; Luterbacher, J.; Wanner, H.

2003-04-01

Phenology is generally described as the timing of life cycle phases or activities of plants and animals in their temporal occurrence throughout the year (Lieth 1974). Recent studies have shown that meteorological and climatological impacts leave their 'fingerprints' across natural systems in general and strongly influence the seasonal activities of single animal and plant species. During the 20th century, phenological observation networks have been established around the world to document and analyze the influence of the globally changing climate to plants and wildlife. This work presents a first attempt of a unique 280-year long series of phenological observations of cherry tree blossoming dates for the Swiss plateau region. In Switzerland, a nation-wide phenological observation network has been established in 1951 currently documenting 69 phenophases of 26 different plant species. A guidebook seeks to increase objectiveness in the network observations. The observations of the blooming of the cherry tree (prunus avium) were chosen to calculate a mean series for the Swiss plateau region with observations from altitudes ranging between 370 and 860 asl. A total number of 737 observations from 21 stations were used. A linear regression was established between the mean blooming date and altitude in order to correct the data to a reference altitude level. Other ecological parameters were unaccounted for. The selected network data series from 1951 to 2000 was combined and prolonged with observations from various sources back to 1721. These include several historical observation series by farmers, clergymen and teachers, data from various stations collected at the newly established Swiss meteorological network from 1864 to 1873 and the single long series of observations from Liestal starting in 1894. The homogenized time series of observations will be compared with reconstructions of late winter temperatures as well as statistical estimations of blooming time based on long instrumental data from Europe. In addition, the series is one of the few historical phenological records to assess past climate and ecological changes. Lieth, H. (1974). Phenology and Seasonality Modeling. Berlin, Heidelberg, New York, Springer.

'Weather Value at Risk': A uniform approach to describe and compare sectoral income risks from climate change.

PubMed

Prettenthaler, Franz; Köberl, Judith; Bird, David Neil

2016-02-01

We extend the concept of 'Weather Value at Risk' - initially introduced to measure the economic risks resulting from current weather fluctuations - to describe and compare sectoral income risks from climate change. This is illustrated using the examples of wheat cultivation and summer tourism in (parts of) Sardinia. Based on climate scenario data from four different regional climate models we study the change in the risk of weather-related income losses between some reference (1971-2000) and some future (2041-2070) period. Results from both examples suggest an increase in weather-related risks of income losses due to climate change, which is somewhat more pronounced for summer tourism. Nevertheless, income from wheat cultivation is at much higher risk of weather-related losses than income from summer tourism, both under reference and future climatic conditions. A weather-induced loss of at least 5% - compared to the income associated with average reference weather conditions - shows a 40% (80%) probability of occurrence in the case of wheat cultivation, but only a 0.4% (16%) probability of occurrence in the case of summer tourism, given reference (future) climatic conditions. Whereas in the agricultural example increases in the weather-related income risks mainly result from an overall decrease in average wheat yields, the heightened risk in the tourism example stems mostly from a change in the weather-induced variability of tourism incomes. With the extended 'Weather Value at Risk' concept being able to capture both, impacts from changes in the mean and the variability of the climate, it is a powerful tool for presenting and disseminating the results of climate change impact assessments. Due to its flexibility, the concept can be applied to any economic sector and therefore provides a valuable tool for cross-sectoral comparisons of climate change impacts, but also for the assessment of the costs and benefits of adaptation measures. Copyright © 2015 Elsevier B.V. All rights reserved.

"It Takes a Network": Building National Capacity for Climate Change Interpretation

NASA Astrophysics Data System (ADS)

Spitzer, W.

2014-12-01

Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. More than 1,500 informal science venues (science centers, museums, aquariums, zoos, nature centers, national parks) are visited annually by 61% of the U.S. population. These visitors expect reliable information about environmental issues and solutions. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. Beyond providing in-depth training, we have found that our "alumni network" is assuming an increasingly important role in achieving our goals: 1. Ongoing learning - Training must be ongoing given continuous advances in climate and social science research. 2. Implementation support - Social support is critical as interpreters move from learning to practice, given complex and potentially contentious subject matter. 3. Leadership development - We rely on a national cadre of interpretive leaders to conduct workshops, facilitate study circle trainings, and support alumni. 4. Coalition building - A peer network helps to build and maintain connections with colleagues, and supports further dissemination through the informal science community. We are experimenting with a variety of online and face to face strategies to support the growing alumni network. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy.

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

Koponen, Kati; Soimakallio, Sampo; Kline, Keith L.

In order to understand the climate effects of a bioenergy system, a comparison between the bioenergy system and a reference system is required. The reference system describes the situation that occurs in the absence of the bioenergy system with respect to the use of land, energy, and materials. The importance of reference systems is discussed in the literature but guidance on choosing suitable reference systems for assessing climate effects of bioenergy is limited. The reference system should align with the purpose of the study. Transparency of reference system assumptions is essential for proper interpretation of bioenergy assessments. This paper presentsmore » guidance for selecting suitable reference systems. Particular attention is given to choosing the land reference. If the goal is to study the climate effects of bioenergy as a part of total anthropogenic activity the reference system should illustrate what is expected in the absence of human activities. In such a case the suitable land reference is natural regeneration, and energy or material reference systems are not relevant. If the goal is to assess the effect of a change in bioenergy use, the reference system should incorporate human activities. In this case suitable reference systems describe the most likely alternative uses of the land, energy and materials in the absence of the change in bioenergy use. The definition of the reference system is furthermore subject to the temporal scope of the study. In practice, selecting and characterizing reference systems will involve various choices and uncertainties which should be considered carefully. As a result, it can be instructive to consider how alternative reference systems influence the results and conclusions drawn from bioenergy assessments.« less

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

USGS Publications Warehouse

Isaak, Daniel J.; Young, Michael K; Luce, Charles H; Hostetler, Steven W.; Wengerd, Seth J.; Peterson, Erin E.; Ver Hoef, Jay; Groce, Matthew C.; Horan, Dona L.; Nagel, David E.

2016-01-01

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century.

Federal climate change programs in the water-limited Southwest: intersection of mission, stakeholders and geography to build successful collaboration

NASA Astrophysics Data System (ADS)

Elias, E.; Steele, C. M.; Rango, A.; Reyes, J. J.; Langston, M. A.; Johnson, K.

2016-12-01

As one of the newest federal programs to emerge in response to climate change, the U.S. Department of Agriculture (USDA) Climate Hubs were established to assist farmers, ranchers and forest landowners in their adaptation and mitigation efforts under a changing climate. The Hubs' mission is to deliver science-based information and tools to agricultural and natural resource land managers, to enable climate-informed decision-making. By facilitating and transferring tools and knowledge, the Hubs also provide value to cooperative extension, land grant institutions, and USDA itself, especially in leveraging existing resource capacity. Various federal agencies (NOAA, USGS, USFWS) have also developed climate change coordination networks: RISAs, CSCs, and LCCs. These regionally-based federal networks can best operate in collaboration with one another. At their programmatic level, however, there are fundamental discrepancies in mission, stakeholder definition and geographic region. In this presentation, we seek to compare and contrast these divergent characteristics by identifying `hot spots' and `hot moments' where definitions, programs, or priorities may intersect due to place-based or event-based issues. The Southwest (SW) region of the United States, which presently operates under warm and dry conditions, is projected to become warmer and drier in the future. On-going drought conditions have presented an opportunity to maintain and build professional networks among these federal climate change coordination networks, as well as within USDA, to better understand impacts and respond to stakeholder needs. Projects in the Rio Grande River Valley and with Tribal nations highlight successful collaboration based on geography and common stakeholders, respectively. Aridity and water scarcity characterize the SW region and provide an overarching theme to better support adaptation and mitigation, as well as create opportunities for collaborative success.

Designing optimized multi-species monitoring networks to detect range shifts driven by climate change: a case study with bats in the North of Portugal.

PubMed

Amorim, Francisco; Carvalho, Sílvia B; Honrado, João; Rebelo, Hugo

2014-01-01

Here we develop a framework to design multi-species monitoring networks using species distribution models and conservation planning tools to optimize the location of monitoring stations to detect potential range shifts driven by climate change. For this study, we focused on seven bat species in Northern Portugal (Western Europe). Maximum entropy modelling was used to predict the likely occurrence of those species under present and future climatic conditions. By comparing present and future predicted distributions, we identified areas where each species is likely to gain, lose or maintain suitable climatic space. We then used a decision support tool (the Marxan software) to design three optimized monitoring networks considering: a) changes in species likely occurrence, b) species conservation status, and c) level of volunteer commitment. For present climatic conditions, species distribution models revealed that areas suitable for most species occur in the north-eastern part of the region. However, areas predicted to become climatically suitable in the future shifted towards west. The three simulated monitoring networks, adaptable for an unpredictable volunteer commitment, included 28, 54 and 110 sampling locations respectively, distributed across the study area and covering the potential full range of conditions where species range shifts may occur. Our results show that our framework outperforms the traditional approach that only considers current species ranges, in allocating monitoring stations distributed across different categories of predicted shifts in species distributions. This study presents a straightforward framework to design monitoring schemes aimed specifically at testing hypotheses about where and when species ranges may shift with climatic changes, while also ensuring surveillance of general population trends.

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

PubMed Central

Isaak, Daniel J.; Young, Michael K.; Luce, Charles H.; Hostetler, Steven W.; Wenger, Seth J.; Peterson, Erin E.; Ver Hoef, Jay M.; Groce, Matthew C.; Horan, Dona L.; Nagel, David E.

2016-01-01

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are much weaker than anticipated and may be too subtle for detection given the widespread use of sparse water temperature datasets or imprecise surrogates like elevation and air temperature. Through application of large water-temperature databases evaluated for sensitivity to historical air-temperature variability and computationally interpolated to provide high-resolution thermal habitat information for a 222,000-km network, we estimate a less dire thermal plight for cold-water species within mountains of the northwestern United States. Stream warming rates and climate velocities were both relatively low for 1968–2011 (average warming rate = 0.101 °C/decade; median velocity = 1.07 km/decade) when air temperatures warmed at 0.21 °C/decade. Many cold-water vertebrate species occurred in a subset of the network characterized by low climate velocities, and three native species of conservation concern occurred in extremely cold, slow velocity environments (0.33–0.48 km/decade). Examination of aggressive warming scenarios indicated that although network climate velocities could increase, they remain low in headwaters because of strong local temperature gradients associated with topographic controls. Better information about changing hydrology and disturbance regimes is needed to complement these results, but rather than being climatic cul-de-sacs, many mountain streams appear poised to be redoubts for cold-water biodiversity this century. PMID:27044091

Moving toward Collective Impact in Climate Change Literacy: The Climate Literacy and Energy Awareness Network (CLEAN)

ERIC Educational Resources Information Center

Ledley, Tamara Shapiro; Gold, Anne U.; Niepold, Frank; McCaffrey, Mark

2014-01-01

In recent years, various climate change education efforts have been launched, including federally (National Oceanic and Atmospheric Administration, National Aeronautics and Space Administration, National Science Foundation, etc.) and privately funded projects. In addition, climate literacy and energy literacy frameworks have been developed and…

Regional climate services: A regional partnership between NOAA and USDA

USDA-ARS?s Scientific Manuscript database

Climate services in the Midwest and Northern Plains regions have been enhanced by a recent addition of the USDA Climate Hubs to NOAA’s existing network of partners. This new partnership stems from the intrinsic variability of intra and inter-annual climatic conditions, which makes decision-making fo...

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

A climate stress-test of the financial system

NASA Astrophysics Data System (ADS)

Battiston, Stefano; Mandel, Antoine; Monasterolo, Irene; Schütze, Franziska; Visentin, Gabriele

2017-03-01

The urgency of estimating the impact of climate risks on the financial system is increasingly recognized among scholars and practitioners. By adopting a network approach to financial dependencies, we look at how climate policy risk might propagate through the financial system. We develop a network-based climate stress-test methodology and apply it to large Euro Area banks in a `green' and a `brown' scenario. We find that direct and indirect exposures to climate-policy-relevant sectors represent a large portion of investors' equity portfolios, especially for investment and pension funds. Additionally, the portion of banks' loan portfolios exposed to these sectors is comparable to banks' capital. Our results suggest that climate policy timing matters. An early and stable policy framework would allow for smooth asset value adjustments and lead to potential net winners and losers. In contrast, a late and abrupt policy framework could have adverse systemic consequences.

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams

PubMed Central

Jaeger, Kristin L.; Olden, Julian D.; Pelland, Noel A.

2014-01-01

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6–9% over the course of a year and up to 12–18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna. PMID:25136090

Climate change poised to threaten hydrologic connectivity and endemic fishes in dryland streams.

PubMed

Jaeger, Kristin L; Olden, Julian D; Pelland, Noel A

2014-09-23

Protecting hydrologic connectivity of freshwater ecosystems is fundamental to ensuring species persistence, ecosystem integrity, and human well-being. More frequent and severe droughts associated with climate change are poised to significantly alter flow intermittence patterns and hydrologic connectivity in dryland streams of the American Southwest, with deleterious effects on highly endangered fishes. By integrating local-scale hydrologic modeling with emerging approaches in landscape ecology, we quantify fine-resolution, watershed-scale changes in habitat size, spacing, and connectance under forecasted climate change in the Verde River Basin, United States. Model simulations project annual zero-flow day frequency to increase by 27% by midcentury, with differential seasonal consequences on continuity (temporal continuity at discrete locations) and connectivity (spatial continuity within the network). A 17% increase in the frequency of stream drying events is expected throughout the network with associated increases in the duration of these events. Flowing portions of the river network will diminish between 8% and 20% in spring and early summer and become increasingly isolated by more frequent and longer stretches of dry channel fragments, thus limiting the opportunity for native fishes to access spawning habitats and seasonally available refuges. Model predictions suggest that midcentury and late century climate will reduce network-wide hydrologic connectivity for native fishes by 6-9% over the course of a year and up to 12-18% during spring spawning months. Our work quantifies climate-induced shifts in stream drying and connectivity across a large river network and demonstrates their implications for the persistence of a globally endemic fish fauna.

Datum maintenance of the main Egyptian geodetic control networks by utilizing Precise Point Positioning "PPP" technique

NASA Astrophysics Data System (ADS)

Rabah, Mostafa; Elmewafey, Mahmoud; Farahan, Magda H.

2016-06-01

A geodetic control network is the wire-frame or the skeleton on which continuous and consistent mapping, Geographic Information Systems (GIS), and surveys are based. Traditionally, geodetic control points are established as permanent physical monuments placed in the ground and precisely marked, located, and documented. With the development of satellite surveying methods and their availability and high degree of accuracy, a geodetic control network could be established by using GNSS and referred to an international terrestrial reference frame used as a three-dimensional geocentric reference system for a country. Based on this concept, in 1992, the Egypt Survey Authority (ESA) established two networks, namely High Accuracy Reference Network (HARN) and the National Agricultural Cadastral Network (NACN). To transfer the International Terrestrial Reference Frame to the HARN, the HARN was connected with four IGS stations. The processing results were 1:10,000,000 (Order A) for HARN and 1:1,000,000 (Order B) for NACN relative network accuracy standard between stations defined in ITRF1994 Epoch1996. Since 1996, ESA did not perform any updating or maintaining works for these networks. To see how non-performing maintenance degrading the values of the HARN and NACN, the available HARN and NACN stations in the Nile Delta were observed. The Processing of the tested part was done by CSRS-PPP Service based on utilizing Precise Point Positioning "PPP" and Trimble Business Center "TBC". The study shows the feasibility of Precise Point Positioning in updating the absolute positioning of the HARN network and its role in updating the reference frame (ITRF). The study also confirmed the necessity of the absent role of datum maintenance of Egypt networks.

GEOdetic Data assimilation and EStimation of references for climate change InvEstigation. An overall presentation of the French GEODESIE project

NASA Astrophysics Data System (ADS)

Nahmani, S.; Coulot, D.; Biancale, R.; Bizouard, C.; Bonnefond, P.; Bouquillon, S.; Collilieux, X.; Deleflie, F.; Garayt, B.; Lambert, S. B.; Laurent-Varin, S.; Marty, J. C.; Mercier, F.; Metivier, L.; Meyssignac, B.; Pollet, A.; Rebischung, P.; Reinquin, F.; Richard, J. Y.; Tertre, F.; Woppelmann, G.

2017-12-01

Many major indicators of climate change are monitored with space observations. This monitoring is highly dependent on references that only geodesy can provide. The current accuracy of these references does not permit to fully support the challenges that the constantly evolving Earth system gives rise to, and can consequently limit the accuracy of these indicators. Thus, in the framework of the GGOS, stringent requirements are fixed to the International Terrestrial Reference Frame (ITRF) for the next decade: an accuracy at the level of 1 mm and a stability at the level of 0.1 mm/yr. This means an improvement of the current quality of ITRF by a factor of 5-10. Improving the quality of the geodetic references is an issue which requires a thorough reassessment of the methodologies involved. The most relevant and promising method to improve this quality is the direct combination of the space-geodetic measurements used to compute the official references of the IERS. The GEODESIE project aims at (i) determining highly-accurate global and consistent references and (ii) providing the geophysical and climate research communities with these references, for a better estimation of geocentric sea level rise, ice mass balance and on-going climate changes. Time series of sea levels computed from altimetric data and tide gauge records with these references will also be provided. The geodetic references will be essential bases for Earth's observation and monitoring to support the challenges of the century. The geocentric time series of sea levels will permit to better apprehend (i) the drivers of the global mean sea level rise and of regional variations of sea level and (ii) the contribution of the global climate change induced by anthropogenic greenhouse gases emissions to these drivers. All the results and computation and quality assessment reports will be available at geodesie_anr.ign.fr.This project, supported by the French Agence Nationale de la Recherche (ANR) for the period 2017-2020, will be an unprecedented opportunity to provide the French Groupe de Recherche de Géodésie Spatiale (GRGS) with complete simulation and data processing capabilities to prepare the future arrival of space missions such as the European Geodetic Reference Antenna in SPace (E-GRASP) and to significantly contribute to the GGOS with accurate references.

Robustness and Recovery of Lifeline Infrastructure and Ecosystem Networks

NASA Astrophysics Data System (ADS)

Bhatia, U.; Ganguly, A. R.

2015-12-01

Disruptive events, both natural and man-made, can have widespread impacts on both natural systems and lifeline infrastructure networks leading to the loss of biodiversity and essential functionality, respectively. Projected sea-level rise and climate change can further increase the frequency and severity of large-scale floods on urban-coastal megacities. Nevertheless, Failure in infrastructure systems can trigger cascading impacts on dependent ecosystems, and vice-versa. An important consideration in the behavior of the isolated networks and inter-connected networks following disruptive events is their resilience, or the ability of the network to "bounce back" to a pre-disaster state. Conventional risk analysis and subsequent risk management frameworks have focused on identifying the components' vulnerability and strengthening of the isolated components to withstand these disruptions. But high interconnectedness of these systems, and evolving nature of hazards, particularly in the context of climate extremes, make the component level analysis unrealistic. In this study, we discuss the complex network-based resilience framework to understand fragility and recovery strategies for infrastructure systems impacted by climate-related hazards. We extend the proposed framework to assess the response of ecological networks to multiple species loss and design the restoration management framework to identify the most efficient restoration sequence of species, which can potentially lead to disproportionate gains in biodiversity.

Building a Unified Information Network.

ERIC Educational Resources Information Center

Avram, Henriette D.

1988-01-01

Discusses cooperative efforts between research organizations and libraries to create a national information network. Topics discussed include the Linked System Project (LSP); technical processing versus reference and research functions; Open Systems Interconnection (OSI) Reference Model; the National Science Foundation Network (NSFNET); and…

The Effects of Data Gaps on the Calculated Monthly Mean Maximum and Minimum Temperatures in the Continental United States: A Spatial and Temporal Study.

NASA Astrophysics Data System (ADS)

Stooksbury, David E.; Idso, Craig D.; Hubbard, Kenneth G.

1999-05-01

Gaps in otherwise regularly scheduled observations are often referred to as missing data. This paper explores the spatial and temporal impacts that data gaps in the recorded daily maximum and minimum temperatures have on the calculated monthly mean maximum and minimum temperatures. For this analysis 138 climate stations from the United States Historical Climatology Network Daily Temperature and Precipitation Data set were selected. The selected stations had no missing maximum or minimum temperature values during the period 1951-80. The monthly mean maximum and minimum temperatures were calculated for each station for each month. For each month 1-10 consecutive days of data from each station were randomly removed. This was performed 30 times for each simulated gap period. The spatial and temporal impact of the 1-10-day data gaps were compared. The influence of data gaps is most pronounced in the continental regions during the winter and least pronounced in the southeast during the summer. In the north central plains, 10-day data gaps during January produce a standard deviation value greater than 2°C about the `true' mean. In the southeast, 10-day data gaps in July produce a standard deviation value less than 0.5°C about the mean. The results of this study will be of value in climate variability and climate trend research as well as climate assessment and impact studies.

Climate change, coral reef ecosystems, and management options for marine protected areas.

PubMed

Keller, Brian D; Gleason, Daniel F; McLeod, Elizabeth; Woodley, Christa M; Airamé, Satie; Causey, Billy D; Friedlander, Alan M; Grober-Dunsmore, Rikki; Johnson, Johanna E; Miller, Steven L; Steneck, Robert S

2009-12-01

Marine protected areas (MPAs) provide place-based management of marine ecosystems through various degrees and types of protective actions. Habitats such as coral reefs are especially susceptible to degradation resulting from climate change, as evidenced by mass bleaching events over the past two decades. Marine ecosystems are being altered by direct effects of climate change including ocean warming, ocean acidification, rising sea level, changing circulation patterns, increasing severity of storms, and changing freshwater influxes. As impacts of climate change strengthen they may exacerbate effects of existing stressors and require new or modified management approaches; MPA networks are generally accepted as an improvement over individual MPAs to address multiple threats to the marine environment. While MPA networks are considered a potentially effective management approach for conserving marine biodiversity, they should be established in conjunction with other management strategies, such as fisheries regulations and reductions of nutrients and other forms of land-based pollution. Information about interactions between climate change and more "traditional" stressors is limited. MPA managers are faced with high levels of uncertainty about likely outcomes of management actions because climate change impacts have strong interactions with existing stressors, such as land-based sources of pollution, overfishing and destructive fishing practices, invasive species, and diseases. Management options include ameliorating existing stressors, protecting potentially resilient areas, developing networks of MPAs, and integrating climate change into MPA planning, management, and evaluation.

U.S. Department of the Interior Climate Science Centers and U.S. Geological Survey National Climate Change and Wildlife Science Center—Annual report for 2015

USGS Publications Warehouse

Varela Minder, Elda; Padgett, Holly A.

2016-04-07

2015 was another great year for the Department of the Interior (DOI) Climate Science Centers (CSCs) and U.S. Geological Survey (USGS) National Climate Change and Wildlife Science Center (NCCWSC) network. The DOI CSCs and USGS NCCWSC continued their mission of providing the science, data, and tools that are needed for on-the-ground decision making by natural and cultural resource managers to address the effects of climate change on fish, wildlife, ecosystems, and communities. Our many accomplishments in 2015 included initiating a national effort to understand the influence of drought on wildlife and ecosystems; providing numerous opportunities for students and early career researchers to expand their networks and learn more about climate change effects; and working with tribes and indigenous communities to expand their knowledge of and preparation for the impacts of climate change on important resources and traditional ways of living. Here we illustrate some of these 2015 activities from across the CSCs and NCCWSC.

Old boys' network in general practitioners' referral behavior?

PubMed

Hackl, Franz; Hummer, Michael; Pruckner, Gerald J

2015-09-01

We analyzed the impact of social networks on general practitioners' (GPs) referral behavior based on administrative panel data from 2,684,273 referrals to specialists made between 1998 and 2007. For the definition of social networks, we used information on the doctors' place and time of study and their hospital work history. We found that GPs referred more patients to specialists within their personal networks and that patients referred within a social network had fewer follow-up consultations and less inpatient days thereafter. The effects on patient outcomes (e.g. waiting periods, days in hospital) of referrals within personal networks and affinity-based networks differed. Specifically, whereas empirical evidence showed a concentration on high-quality specialists for referrals within the personal network, suggesting that referrals within personal networks overcome information asymmetry with respect to specialists' abilities, the empirical evidence for affinity-based networks was different and less clear. Same-gender networks tended to refer patients to low-quality specialists. Copyright © 2015 Elsevier B.V. All rights reserved.

Climate Effects on Health

MedlinePlus

... Chapter . Additional information regarding the health effects of climate change and references to supporting literature can be found ... globalchange.gov/engage/activities-products/NCA3/technical-inputs . Climate change, together with other natural and human-made health ...

Vulnerability of eco-environmental health to climate change: the views of government stakeholders and other specialists in Queensland, Australia.

PubMed

Strand, Linn B; Tong, Shilu; Aird, Rosemary; McRae, David

2010-07-28

There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change. Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and non-governmental organisations in South-East Queensland. The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability. The study has addressed some important questions in regard to government stakeholders and other specialists' views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making.

Vulnerability of eco-environmental health to climate change: the views of government stakeholders and other specialists in Queensland, Australia

PubMed Central

2010-01-01

Background There is overwhelming scientific evidence that human activities have changed and will continue to change the climate of the Earth. Eco-environmental health, which refers to the interdependencies between ecological systems and population health and well-being, is likely to be significantly influenced by climate change. The aim of this study was to examine perceptions from government stakeholders and other relevant specialists about the threat of climate change, their capacity to deal with it, and how to develop and implement a framework for assessing vulnerability of eco-environmental health to climate change. Methods Two focus groups were conducted in Brisbane, Australia with representatives from relevant government agencies, non-governmental organisations, and the industry sector (n = 15) involved in the discussions. The participants were specialists on climate change and public health from governmental agencies, industry, and non-governmental organisations in South-East Queensland. Results The specialists perceived climate change to be a threat to eco-environmental health and had substantial knowledge about possible implications and impacts. A range of different methods for assessing vulnerability were suggested by the participants and the complexity of assessment when dealing with multiple hazards was acknowledged. Identified factors influencing vulnerability were perceived to be of a social, physical and/or economic nature. They included population growth, the ageing population with associated declines in general health and changes in the vulnerability of particular geographical areas due to for example, increased coastal development, and financial stress. Education, inter-sectoral collaboration, emergency management (e.g. development of early warning systems), and social networks were all emphasised as a basis for adapting to climate change. To develop a framework, different approaches were discussed for assessing eco-environmental health vulnerability, including literature reviews to examine the components of vulnerability such as natural hazard risk and exposure and to investigate already existing frameworks for assessing vulnerability. Conclusion The study has addressed some important questions in regard to government stakeholders and other specialists' views on the threat of climate change and its potential impacts on eco-environmental health. These findings may have implications in climate change and public health decision-making. PMID:20663227

Comparative effects of climate on ecosystem nitrogen and soil biogeochemistry in U.S. national parks. FY 2001 Annual Report (Res. Rept. No. 94)

USGS Publications Warehouse

Stottlemyer, R.; Edmonds, R.; Scherbarth, L.; Urbanczyk, K.; Van Miegroet, H.; Zak, J.

2002-01-01

In 1998, the USGS Global Change program funded research for a network of Long-Term Reference Ecosystems initially established in national parks and funded by the National Park Service. The network included Noland Divide, Great Smoky Mountains National Park, Tennessee; Pine Canyon, Big Ben National park, Texas; West Twin Creek, Olympic National Park, Washingtona?? Wallace Lake, Isle Royale National Park, Michigan; and the Asik watershed, Noatak National Preserve, Alaska. The watershed ecosystem model was used since this approach permits additional statistical power in detection of trends among variables, and the watershed in increasingly a land unit used in resource management and planning. The ecosystems represent a major fraction of lands administered by the National Park Service, and were chosen generally for the contrasts among sites. For example, tow of the site, Noland and West Twin, are characterized by high precipitation amounts, but Noland receives some of the highest atmospheric nitrogen (N) inputs in North America. In contrast, Pine Canyon and Asik are warm and cold desert sites respectively. The Asik watershed receives <1% the atmospheric N inputs Noland receives. The Asik site is at the northern extent (treeline) of the boreal biome in the North America while Wallace is at the southern ecotone between boreal and northern hardwoods. The research goal for these sites is to gain a basic understanding of ecosystem structure and function, and the response to global change especially atmospheric inputs and climate.

To share or not to share: Drivers and barriers for sharing data via online amateur weather networks

NASA Astrophysics Data System (ADS)

Gharesifard, Mohammad; Wehn, Uta

2016-04-01

Increasing attention is being paid to the importance and potential of crowd-sourced data to complement current environmental data-streams (i.e. in-situ observations and RS data). In parallel, the diffusion of Information Communication Technologies (ICTs) that are interactive and easy to use have provided a way forward in facing extreme climatic events and the threatening hazards resulting from those. The combination of these two trends is referred to as ICT-enabled 'citizen observatories' of the environment. Nevertheless, the success of these citizen observatories hinges on the continued involvement of citizens as central actors of these initiatives. Developing strategies to (further) engage citizens requires in-depth understanding of the behavioral determinants that encourage or impede individuals to collect and share environment-related data. This paper takes the case of citizen-sensed weather data using Personal Weather Stations (PWSs) and looks at the drivers and barriers for sharing such data via online amateur weather networks. This is done employing a behavioral science lens that considers data sharing a decision and systematically investigates the influential factors that affect this decision. The analysis and findings are based on qualitative empirical research carried out in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. This resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management.

The Reference Ability Neural Network Study: Life-time stability of reference-ability neural networks derived from task maps of young adults.

PubMed

Habeck, C; Gazes, Y; Razlighi, Q; Steffener, J; Brickman, A; Barulli, D; Salthouse, T; Stern, Y

2016-01-15

Analyses of large test batteries administered to individuals ranging from young to old have consistently yielded a set of latent variables representing reference abilities (RAs) that capture the majority of the variance in age-related cognitive change: Episodic Memory, Fluid Reasoning, Perceptual Processing Speed, and Vocabulary. In a previous paper (Stern et al., 2014), we introduced the Reference Ability Neural Network Study, which administers 12 cognitive neuroimaging tasks (3 for each RA) to healthy adults age 20-80 in order to derive unique neural networks underlying these 4 RAs and investigate how these networks may be affected by aging. We used a multivariate approach, linear indicator regression, to derive a unique covariance pattern or Reference Ability Neural Network (RANN) for each of the 4 RAs. The RANNs were derived from the neural task data of 64 younger adults of age 30 and below. We then prospectively applied the RANNs to fMRI data from the remaining sample of 227 adults of age 31 and above in order to classify each subject-task map into one of the 4 possible reference domains. Overall classification accuracy across subjects in the sample age 31 and above was 0.80±0.18. Classification accuracy by RA domain was also good, but variable; memory: 0.72±0.32; reasoning: 0.75±0.35; speed: 0.79±0.31; vocabulary: 0.94±0.16. Classification accuracy was not associated with cross-sectional age, suggesting that these networks, and their specificity to the respective reference domain, might remain intact throughout the age range. Higher mean brain volume was correlated with increased overall classification accuracy; better overall performance on the tasks in the scanner was also associated with classification accuracy. For the RANN network scores, we observed for each RANN that a higher score was associated with a higher corresponding classification accuracy for that reference ability. Despite the absence of behavioral performance information in the derivation of these networks, we also observed some brain-behavioral correlations, notably for the fluid-reasoning network whose network score correlated with performance on the memory and fluid-reasoning tasks. While age did not influence the expression of this RANN, the slope of the association between network score and fluid-reasoning performance was negatively associated with higher ages. These results provide support for the hypothesis that a set of specific, age-invariant neural networks underlies these four RAs, and that these networks maintain their cognitive specificity and level of intensity across age. Activation common to all 12 tasks was identified as another activation pattern resulting from a mean-contrast Partial-Least-Squares technique. This common pattern did show associations with age and some subject demographics for some of the reference domains, lending support to the overall conclusion that aspects of neural processing that are specific to any cognitive reference ability stay constant across age, while aspects that are common to all reference abilities differ across age. Copyright © 2015 Elsevier Inc. All rights reserved.

Social aggregation in the pelagic zone with special reference to fish and invertebrates.

PubMed

Ritz, David A; Hobday, Alistair J; Montgomery, John C; Ward, Ashley J W

2011-01-01

Aggregations of organisms, ranging from zooplankton to whales, are an extremely common phenomenon in the pelagic zone; perhaps the best known are fish schools. Social aggregation is a special category that refers to groups that self-organize and maintain cohesion to exploit benefits such as protection from predators, and location and capture of resources more effectively and with greater energy efficiency than could a solitary individual. In this review we explore general aggregation principles, with specific reference to pelagic organisms; describe a range of new technologies either designed for studying aggregations or that could potentially be exploited for this purpose; report on the insights gained from theoretical modelling; discuss the relationship between social aggregation and ocean management; and speculate on the impact of climate change. Examples of aggregation occur in all animal phyla. Among pelagic organisms, it is possible that repeated co-occurrence of stable pairs of individuals, which has been established for some schooling fish, is the likely precursor leading to networks of social interaction and more complex social behaviour. Social network analysis has added new insights into social behaviour and allows us to dissect aggregations and to examine how the constituent individuals interact with each other. This type of analysis is well advanced in pinnipeds and cetaceans, and work on fish is progressing. Detailed three-dimensional analysis of schools has proved to be difficult, especially at sea, but there has been some progress recently. The technological aids for studying social aggregation include video and acoustics, and have benefited from advances in digitization, miniaturization, motion analysis and computing power. New techniques permit three-dimensional tracking of thousands of individual animals within a single group which has allowed novel insights to within-group interactions. Approaches using theoretical modelling of aggregations have a long history but only recently have hypotheses been tested empirically. The lack of synchrony between models and empirical data, and lack of a common framework to schooling models have hitherto hampered progress; however, recent developments in this field offer considerable promise. Further, we speculate that climate change, already having effects on ecosystems, could have dramatic effects on aggregations through its influence on species composition by altering distribution ranges, migration patterns, vertical migration, and oceanic acidity. Because most major commercial fishing targets schooling species, these changes could have important consequences for the dependent businesses. 2011 Elsevier Ltd. All rights reserved.

Application of microwave radiometry to improving climate data records.

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

Liljegren, J. C.; Cadeddu, M. P.; Decision and Information Sciences

2007-01-01

Microwave radiometers deployed by the U. S. Department of Energy's Atmospheric Radiation Measurement (ARM) Program provide crucial data for a wide range of research applications. The accuracy and stability of these instruments also makes them ideal for improving climate data records: to detect and correct discontinuities in the long-term climate records, to validate and calibrate the climate data, to characterize errors in the climate records, and to plan for the future Global Climate Observing System (GCOS) Reference Upper-Air network. This paper presents an overview of these capabilities with examples from ARM data. Two-channel microwave radiometers (MWR) operating at 23.8 andmore » 31.4 GHz are deployed at each of eleven ARM Climate Research Facility (ACRF) field sites in the U.S. Southern Great Plains (SGP), Tropical Western Pacific (TWP), North Slope of Alaska (NSA), and with the ARM Mobile Facility in Niamey, Niger for the purpose of retrieving precipitable water vapor (PWV) and liquid water path (LWP). At these locations PWV ranges from as low as 1 mm (1 kg/m{sup 2}) at the NSA to 70 mm or more in the TWP; LWP can exceed 2 mm at many sites. The MWR accommodates this wide dynamic range for all non-precipitating conditions with a root-mean-square error of about 0.4 mm for PWV and 0.02 mm (20 g/m{sup 2}) for LWP. The calibration of the MWR is continuously and autonomously monitored and updated to maintain accuracy. Comparisons of collocated MWRs will be presented. Site-specific linear statistical retrievals are used operationally; more sophisticated retrievals are applied in post-processing the data. Because PWV is an integral measure, derived from both the relative humidity and temperature profiles of the radiosonde, it is a particularly useful reference quantity. Comparison of PWV measured by the MWR with PWV from radiosondes reveals dry biases and diurnal trends as well as general calibration variability in the radiosondes. To correct the bias and reduce the variability ARM scales the relative humidity measurements from the radiosondes to produce agreement with the PWV measured by the MWR. Comparisons of infrared spectral radiances calculated using these scaled radiosondes with high spectral resolution measurements exhibit dramatically reduced bias and variability. This ability to detect and correct errors in the radiosondes measurements will be critical for detecting climate change. The MWR has also been used for a variety of ground- and satellite-based remote sensor retrieval development and validation studies, including precipitable water vapor and slant water vapor retrievals using the Global Positioning System (GPS). The MWR can provide a valuable comparison for GPS-derived zenith wet delay and PWV values, e.g., for evaluating improved mapping functions and detecting errors due, for example, to multi-path contributions. For precipitable water vapor amounts less than 4 mm, which commonly occur in cold, dry Arctic conditions, the 0.4 mm root-mean-square error of the MWR precipitable water vapor measurement is problematic. To obtain increased sensitivity under these conditions, a new G-band water vapor radiometer (GVR) operating at 183.31 {+-} 1, {+-}3, {+-}7, and {+-}14 GHz is deployed at the NSA Barrow site. The GVR offers a valuable reference for radiosonde and GPS water vapor measurements at Arctic locations that are expected to be particularly sensitive to climate change.« less

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

NASA Astrophysics Data System (ADS)

Li, X.; St George, S.

2013-12-01

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

[Study on eco-climatic applicability of Angelica sinensis].

PubMed

Deng, Zhen-Yong; Yin, Xian-Zhi; Yin, Dong; Yang, Qi-Guo; Zhu, Guo-Qing; Liu, Ming-Chun

2005-06-01

In the interest of establish planting base of Angelica sinensis on a large scale, enhance economic benefit, and improve decision-making reasons, the eco-climatic applicability of A. sinensis was studied. Using integral regression, eco-climatic applicability and the effect of meteorological conditions for the yield of A. sinensis' were analysed by field experimental data. Selected > or =0 degrees C accumulated temperature and annual precipitation as leading index, altitude as assistant index, yield and rate of finished products as reference index, the integrated eco-climatic division index and the planting division applicability of A. sinensis was confirmed. Accordancing to theory of climate similitude and leading index summarisation, combining with assistant index and reference index, the integrated division index of eco-climate was confirmed. The planting division of co-climate applicability was divided into 5 grades as best suitable, suitable hypo-suitable, just suitable and no suitable regions. At the same time,the way to enhanced utilizing efficiency of eco-climate resources was brought forward.

Retrieval and Validation of Zenith and Slant Path Delays From the Irish GPS Network

NASA Astrophysics Data System (ADS)

Hanafin, Jennifer; Jennings, S. Gerard; O'Dowd, Colin; McGrath, Ray; Whelan, Eoin

2010-05-01

Retrieval of atmospheric integrated water vapour (IWV) from ground-based GPS receivers and provision of this data product for meteorological applications has been the focus of a number of Europe-wide networks and projects, most recently the EUMETNET GPS water vapour programme. The results presented here are from a project to provide such information about the state of the atmosphere around Ireland for climate monitoring and improved numerical weather prediction. Two geodetic reference GPS receivers have been deployed at Valentia Observatory in Co. Kerry and Mace Head Atmospheric Research Station in Co. Galway, Ireland. These two receivers supplement the existing Ordnance Survey Ireland active network of 17 permanent ground-based receivers. A system to retrieve column-integrated atmospheric water vapour from the data provided by this network has been developed, based on the GPS Analysis at MIT (GAMIT) software package. The data quality of the zenith retrievals has been assessed using co-located radiosondes at the Valentia site and observations from a microwave profiling radiometer at the Mace Head site. Validation of the slant path retrievals requires a numerical weather prediction model and HIRLAM (High-Resolution Limited Area Model) version 7.2, the current operational forecast model in use at Met Éireann for the region, has been used for this validation work. Results from the data processing and comparisons with the independent observations and model will be presented.

Corporate funding and ideological polarization about climate change

PubMed Central

Farrell, Justin

2016-01-01

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

Corporate funding and ideological polarization about climate change.

PubMed

Farrell, Justin

2016-01-05

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

Smooth information flow in temperature climate network reflects mass transport

NASA Astrophysics Data System (ADS)

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

2017-03-01

A directed climate network is constructed by Granger causality analysis of air temperature time series from a regular grid covering the whole Earth. Using winner-takes-all network thresholding approach, a structure of a smooth information flow is revealed, hidden to previous studies. The relevance of this observation is confirmed by comparison with the air mass transfer defined by the wind field. Their close relation illustrates that although the information transferred due to the causal influence is not a physical quantity, the information transfer is tied to the transfer of mass and energy.

On the Role of Hyper-arid Regions within the Virtual Water Trade Network

NASA Astrophysics Data System (ADS)

Aggrey, James; Alshamsi, Aamena; Molini, Annalisa

2016-04-01

Climate change, economic development, and population growth are bound to increasingly impact global water resources, posing a significant threat to the sustainable development of arid regions, where water consumption highly exceeds the natural carrying capacity, population growth rate is high, and climate variability is going to impact both water consumption and availability. Virtual Water Trade (VWT) - i.e. the international trade network of water-intensive products - has been proposed as a possible solution to optimize the allocation of water resources on the global scale. By increasing food availability and lowering food prices it may in fact help the rapid development of water-scarce regions. The structure of the VWT network has been analyzed by a number of authors both in connection with trade policies, socioeconomic constrains and agricultural efficiency. However a systematic analysis of the structure and the dynamics of the VWT network conditional to aridity, climatic forcing and energy availability, is still missing. Our goal is hence to analyze the role of arid and hyper-arid regions within the VWN under diverse climatic, demographic, and energy constraints with an aim to contribute to the ongoing Energy-Water-Food nexus discussion. In particular, we focus on the hyper-arid lands of the Arabian Peninsula, the role they play in the global network and the assessment of their specific criticalities, as reflected in the VWN resilience.

Identification of tipping elements of the Indian Summer Monsoon using climate network approach

NASA Astrophysics Data System (ADS)

Stolbova, Veronika; Surovyatkina, Elena; Kurths, Jurgen

2015-04-01

Spatial and temporal variability of the rainfall is a vital question for more than one billion of people inhabiting the Indian subcontinent. Indian Summer Monsoon (ISM) rainfall is crucial for India's economy, social welfare, and environment and large efforts are being put into predicting the Indian Summer Monsoon. For predictability of the ISM, it is crucial to identify tipping elements - regions over the Indian subcontinent which play a key role in the spatial organization of the Indian monsoon system. Here, we use climate network approach for identification of such tipping elements of the ISM. First, we build climate networks of the extreme rainfall, surface air temperature and pressure over the Indian subcontinent for pre-monsoon, monsoon and post-monsoon seasons. We construct network of extreme rainfall event using observational satellite data from 1998 to 2012 from the Tropical Rainfall Measuring Mission (TRMM 3B42V7) and reanalysis gridded daily rainfall data for a time period of 57 years (1951-2007) (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE). For the network of surface air temperature and pressure fields, we use re-analysis data provided by the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR). Second, we filter out data by coarse-graining the network through network measures, and identify tipping regions of the ISM. Finally, we compare obtained results of the network analysis with surface wind fields and show that occurrence of the tipping elements is mostly caused by monsoonal wind circulation, migration of the Intertropical Convergence Zone (ITCZ) and Westerlies. We conclude that climate network approach enables to select the most informative regions for the ISM, providing realistic description of the ISM dynamics with fewer data, and also help to identify tipping regions of the ISM. Obtained tipping elements deserve a special attention for the meteorologists and can be used as markers of the ISM variability.

Improved Statistical Method For Hydrographic Climatic Records Quality Control

NASA Astrophysics Data System (ADS)

Gourrion, J.; Szekely, T.

2016-02-01

Climate research benefits from the continuous development of global in-situ hydrographic networks in the last decades. Apart from the increasing volume of observations available on a large range of temporal and spatial scales, a critical aspect concerns the ability to constantly improve the quality of the datasets. In the context of the Coriolis Dataset for ReAnalysis (CORA) version 4.2, a new quality control method based on a local comparison to historical extreme values ever observed is developed, implemented and validated. Temperature, salinity and potential density validity intervals are directly estimated from minimum and maximum values from an historical reference dataset, rather than from traditional mean and standard deviation estimates. Such an approach avoids strong statistical assumptions on the data distributions such as unimodality, absence of skewness and spatially homogeneous kurtosis. As a new feature, it also allows addressing simultaneously the two main objectives of a quality control strategy, i.e. maximizing the number of good detections while minimizing the number of false alarms. The reference dataset is presently built from the fusion of 1) all ARGO profiles up to early 2014, 2) 3 historical CTD datasets and 3) the Sea Mammals CTD profiles from the MEOP database. All datasets are extensively and manually quality controlled. In this communication, the latest method validation results are also presented. The method has been implemented in the latest version of the CORA dataset and will benefit to the next version of the Copernicus CMEMS dataset.

Predicting lodgepole pine site index from climatic parameters in Alberta.

Treesearch

Robert A. Monserud; Shongming Huang; Yuqing Yang

2006-01-01

We sought to evaluate the impact of climatic variables on site productivity of lodgepole pine (Pinus contorta var. latifolia Engelm.) for the province of Alberta. Climatic data were obtained from the Alberta Climate Model, which is based on 30-year normals from the provincial weather station network. Mapping methods were based...

Network-based approaches to climate knowledge discovery

NASA Astrophysics Data System (ADS)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

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.

ENES the European Network for Earth System modelling and its infrastructure projects IS-ENES

NASA Astrophysics Data System (ADS)

Guglielmo, Francesca; Joussaume, Sylvie; Parinet, Marie

2016-04-01

The scientific community working on climate modelling is organized within the European Network for Earth System modelling (ENES). In the past decade, several European university departments, research centres, meteorological services, computer centres, and industrial partners engaged in the creation of ENES with the purpose of working together and cooperating towards the further development of the network, by signing a Memorandum of Understanding. As of 2015, the consortium counts 47 partners. The climate modelling community, and thus ENES, faces challenges which are both science-driven, i.e. analysing of the full complexity of the Earth System to improve our understanding and prediction of climate changes, and have multi-faceted societal implications, as a better representation of climate change on regional scales leads to improved understanding and prediction of impacts and to the development and provision of climate services. ENES, promoting and endorsing projects and initiatives, helps in developing and evaluating of state-of-the-art climate and Earth system models, facilitates model inter-comparison studies, encourages exchanges of software and model results, and fosters the use of high performance computing facilities dedicated to high-resolution multi-model experiments. ENES brings together public and private partners, integrates countries underrepresented in climate modelling studies, and reaches out to different user communities, thus enhancing European expertise and competitiveness. In this need of sophisticated models, world-class, high-performance computers, and state-of-the-art software solutions to make efficient use of models, data and hardware, a key role is played by the constitution and maintenance of a solid infrastructure, developing and providing services to the different user communities. ENES has investigated the infrastructural needs and has received funding from the EU FP7 program for the IS-ENES (InfraStructure for ENES) phase I and II projects. We present here the case study of an existing network of institutions brought together toward common goals by a non-binding agreement, ENES, and of its two IS-ENES projects. These latter will be discussed in their double role as a means to provide and/or maintain the actual infrastructure (hardware, software, skilled human resources, services) to achieve ENES scientific goals -fulfilling the aims set in a strategy document-, but also to inform and provide to the network a structured way of working and of interacting with the extended community. The genesis and evolution of the network and the interaction network/projects will also be analysed in terms of long-term sustainability.

Climate-driven trends in the occurrence of major floods across North America and Europe

NASA Astrophysics Data System (ADS)

Hodgkins, Glenn A.; Whitfield, Paul H.; Burn, Donald H.; Hannaford, Jamie; Renard, Benjamin; Stahl, Kerstin; Fleig, Anne K.; Madsen, Henrik; Mediero, Luis; Korhonen, Johanna; Murphy, Conor; Crochet, Philippe; Wilson, Donna

2016-04-01

Every year river floods cause enormous damage around the world. Recent major floods in North America and Europe, for example, have received much press, with some concluding that these floods are more frequent in recent years as a result of anthropogenic warming. There has been considerable scientific effort invested in establishing whether observed flood records show evidence of trends or variability in flood frequency, and to determine whether these patterns can be linked to climatic changes. However, the river catchments used in many published studies are influenced by direct human alteration such as reservoir regulation and urbanisation, which can confound the interpretation of climate-driven variability. Furthermore, a majority of previous studies have analysed changes in low magnitude floods, such as the annual peak flow, at a national scale. Few studies are known that have analysed changes in large floods (greater than 25-year floods) on a continental scale. To fill this research gap, we present a study analysing flood flows from reference hydrologic networks (RHNs) or RHN-like gauges across a large study domain embracing North America and much of Europe. RHNs comprise gauging stations with minimally disturbed catchment conditions, which have a near-natural flow regime and provide good quality data; RHN analyses thus allow hydro-climatic variability to be distinguished from direct artificial disturbances or data inhomogeneities. One of the key innovations in this study is the definition of an RHN-like network consisting of 1204 catchments on a continental scale. The network incorporates existing, well-established RHNs in Canada, the US, the UK, Ireland and Norway, alongside RHN-like catchments from Europe (France, Switzerland, Iceland, Denmark, Sweden, Finland, Spain), which have been incorporated in the network following a major effort to ensure RHN-like status of candidate gauges through consultation with local experts. As the aim of the study is to examine long-term variability in the number of major floods, annual exceedances of 25-, 50-, and 100-year floods during the last 50 - 80 years are estimated for all study gauges across North America and Europe, and for smaller groups of gauges defined by catchment size, location, climate, flood threshold, and period of record. Trends are computed using logistic regression techniques, supported by a suite of methods used to test the assumptions used in the analysis. We also analyse relationships between major flood occurrence and atmosphere/ocean indices (the AMO, NAO, PDO and SOI). Our analysis finds no compelling evidence for consistent changes over time in major-flood occurrence across North America and Europe, indicating that generalizations about major-flood occurrence trends across large domains or a diversity of catchment types are ungrounded. There are in fact more significant relationships between major-flood occurrence and the AMO than between flood occurrence and time. Flood occurrence overall (based on data from all 1204 gauges in our study) increased from 1961 to 2010 but not significantly, driven primarily by European increases. Non-significant increases were also found overall from 1931 to 2010 (322 gauges) but driven primarily by North American increases. Flood occurrence increased and decreased (including some significant changes) for the various sub-groups of gauges. Overall this study demonstrates that past changes in major-flood occurrence are highly complex and future changes will be likewise. International hydrologic networks containing minimally altered catchments will play a key role in understanding these complexities.

Packet Traffic Dynamics Near Onset of Congestion in Data Communication Network Model

NASA Astrophysics Data System (ADS)

Lawniczak, A. T.; Tang, X.

2006-05-01

The dominant technology of data communication networks is the Packet Switching Network (PSN). It is a complex technology organized as various hierarchical layers according to the International Standard Organization (ISO) Open Systems Interconnect (OSI) Reference Model. The Network Layer of the ISO OSI Reference Model is responsible for delivering packets from their sources to their destinations and for dealing with congestion if it arises in a network. Thus, we focus on this layer and present an abstraction of the Network Layer of the ISO OSI Reference Model. Using this abstraction we investigate how onset of traffic congestion is affected for various routing algorithms by changes in network connection topology. We study how aggregate measures of network performance depend on network connection topology and routing. We explore packets traffic spatio-temporal dynamics near the phase transition point from free flow to congestion for various network connection topologies and routing algorithms. We consider static and adaptive routings. We present selected simulation results.

Leveraging modern climatology to increase adaptive capacity across protected area networks

USGS Publications Warehouse

Davison, J.E.; Graumlich, L.J.; Rowland, E.L.; Pederson, G.T.; Breshears, D.D.

2012-01-01

Human-driven changes in the global environment pose an increasingly urgent challenge for the management of ecosystems that is made all the more difficult by the uncertain future of both environmental conditions and ecological responses. Land managers need strategies to increase regional adaptive capacity, but relevant and rapid assessment approaches are lacking. To address this need, we developed a method to assess regional protected area networks across biophysically important climatic gradients often linked to biodiversity and ecosystem function. We plot the land of the southwestern United States across axes of historical climate space, and identify landscapes that may serve as strategic additions to current protected area portfolios. Considering climate space is straightforward, and it can be applied using a variety of relevant climate parameters across differing levels of land protection status. The resulting maps identify lands that are climatically distinct from existing protected areas, and may be utilized in combination with other ecological and socio-economic information essential to collaborative landscape-scale decision-making. Alongside other strategies intended to protect species of special concern, natural resources, and other ecosystem services, the methods presented herein provide another important hedging strategy intended to increase the adaptive capacity of protected area networks. ?? 2011 Elsevier Ltd.

Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages.

PubMed

Radinger, Johannes; Hölker, Franz; Horký, Pavel; Slavík, Ondřej; Dendoncker, Nicolas; Wolter, Christian

2016-04-01

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts. © 2015 John Wiley & Sons Ltd.

Transforming School Climate: Educational and Psychoanalytic Perspectives: Introduction

ERIC Educational Resources Information Center

Cohen, Jonathan

2009-01-01

School climate refers to the character and quality of school life. It is based on these patterns and reflects norms, goals, values, interpersonal relationships, teaching, learning, leadership practices, and organizational structures. School climate is at the nexus of individual and group experience. School climate is based on the individual's…

Construction and Validation of the Lesbian, Gay, Bisexual, and Transgendered Climate Inventory

ERIC Educational Resources Information Center

Liddle, Becky J.; Luzzo, Darrell Anthony; Hauenstein, Anita L.; Schuck, Kelly

2004-01-01

Workplace climate refers to formal and informal organizational characteristics contributing to employee welfare. Workplace climates for lesbian, gay, bisexual, and transgendered (LGBT) employees range from actively supportive to openly hostile. An instrument measuring LGBT workplace climate will enable research on vocational adjustment of LGBT…

Organisational Climate: Fact or Fantasy? Coombe Lodge Working Paper. Information Bank Number 1848.

ERIC Educational Resources Information Center

Turner, C. M.

Organizational climate refers to workers' perceptions that a given workplace possesses a distinctive atmosphere. Managers appreciate the behavioral implications of this concept, assuming staff performance or well-being might be improved by managing the climate. Attempts to manipulate organizational climate have generally been unsuccessful, and the…

School Climate: Research, Policy, Practice, and Teacher Education

ERIC Educational Resources Information Center

Cohen, Jonathan; McCabe, Libby; Michelli, Nicholas M.; Pickeral, Terry

2009-01-01

Background/Context: Educators have written about and studied school climate for 100 years. School climate refers to the quality and character of school life. School climate is based on patterns of people's experiences of school life and reflects norms, goals, values, interpersonal relationships, teaching and learning practices, and organizational…

Network access to PCDS (SPAN, ESN, SESNET, ARPANET)

NASA Technical Reports Server (NTRS)

Green, J.

1986-01-01

One of the major goals of the National Space Science Data Center is to increase access to NASA data systems by enhancing networking activities. The activities are centered around three basic networking systems: the Space Physics Analysis Network (SPAN); the Earth Science Network (ESN); and the NASA Packet Switched System (NPSS). Each system is described, linkages among systems are explained, and future plans are announced. The inclusion of several new climate nodes on SPAN or ESN are also mentioned. Presently, the Pilot Climate Data System is accessible through SPAN and will be accessible through NPSS by summer and ESN by the end of 1986. Ambitious plans for implementation are underway. The implementation of these plans will represent a major advance in the utilization and accessibility of data worldwide.

Implications for the dynamic health of a glacier from comparison of conventional and reference-surface balances

USGS Publications Warehouse

Harrison, W.D.; Cox, L.H.; Hock, R.; March, R.S.; Pettit, E.C.

2009-01-01

Conventional and reference-surface mass-balance data from Gulkana and Wolverine Glaciers, Alaska, USA, are used to address the questions of how rapidly these glaciers are adjusting (or 'responding') to climate, whether their responses are stable, and whether the glaciers are likely to survive in today's climate. Instability means that a glacier will eventually vanish, or at least become greatly reduced in volume, if the climate stabilizes at its present state. A simple non-linear theory of response is presented for the analysis. The response of Gulkana Glacier is characterized by a timescale of several decades, but its stability and therefore its survival in today's climate are uncertain. Wolverine seems to be responding to climate more slowly, on the timescale of one to several centuries. Its stability is also uncertain, but a slower response time would make it more susceptible to climate changes.

Anticipating changes to future connectivity within a network of marine protected areas.

PubMed

Coleman, Melinda A; Cetina-Heredia, Paulina; Roughan, Moninya; Feng, Ming; van Sebille, Erik; Kelaher, Brendan P

2017-09-01

Continental boundary currents are projected to be altered under future scenarios of climate change. As these currents often influence dispersal and connectivity among populations of many marine organisms, changes to boundary currents may have dramatic implications for population persistence. Networks of marine protected areas (MPAs) often aim to maintain connectivity, but anticipation of the scale and extent of climatic impacts on connectivity are required to achieve this critical conservation goal in a future of climate change. For two key marine species (kelp and sea urchins), we use oceanographic modelling to predict how continental boundary currents are likely to change connectivity among a network of MPAs spanning over 1000 km of coastline off the coast of eastern Australia. Overall change in predicted connectivity among pairs of MPAs within the network did not change significantly over and above temporal variation within climatic scenarios, highlighting the need for future studies to incorporate temporal variation in dispersal to robustly anticipate likely change. However, the intricacies of connectivity between different pairs of MPAs were noteworthy. For kelp, poleward connectivity among pairs of MPAs tended to increase in the future, whereas equatorward connectivity tended to decrease. In contrast, for sea urchins, connectivity among pairs of MPAs generally decreased in both directions. Self-seeding within higher-latitude MPAs tended to increase, and the role of low-latitude MPAs as a sink for urchins changed significantly in contrasting ways. These projected changes have the potential to alter important genetic parameters with implications for adaptation and ecosystem vulnerability to climate change. Considering such changes, in the context of managing and designing MPA networks, may ensure that conservation goals are achieved into the future. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

fMRI evidence for strategic decision-making during resolution of pronoun reference

PubMed Central

McMillan, Corey T.; Clark, Robin; Gunawardena, Delani; Ryant, Neville; Grossman, Murray

2012-01-01

Pronouns are extraordinarily common in daily language yet little is known about the neural mechanisms that support decisions about pronoun reference. We propose a large-scale neural network for resolving pronoun reference that consists of two components. First, a core language network in peri-Sylvian cortex supports syntactic and semantic resources for interpreting pronoun meaning in sentences. Second, a frontal-parietal network that supports strategic decision-making is recruited to support probabilistic and risk-related components of resolving a pronoun’s referent. In an fMRI study of healthy young adults, we observed activation of left inferior frontal and superior temporal cortex, consistent with a language network. We also observed activation of brain regions not associated with traditional language areas. By manipulating the context of the pronoun, we were able to demonstrate recruitment of dorsolateral prefrontal cortex during probabilistic evaluation of a pronoun’s reference, and orbital frontal activation when a pronoun must adopt a risky referent. Together, these findings are consistent with a two-component model for resolving a pronoun’s reference that includes neuroanatomic regions supporting core linguistic and decision-making mechanisms. PMID:22245014

Stakeholders' participatory diagnosis of climate change impacts on subsistence agriculture in Sikkim, India, for identifying adaptation strategies

NASA Astrophysics Data System (ADS)

Azhoni, A.; Goyal, M. K.

2017-12-01

Narrowing the gap between research, policy making and implementing adaptation remains a challenge in many parts of the world where climate change is likely to severely impact subsistence agriculture. This research aims to narrow this gap by matching the adaptation strategies being framed by policy makers and perspectives of consultants and researchers which are expected to be implemented by development agencies farmers in the state of Sikkim in India. Our case study examined the framing and implementation of State Action Plan on Climate Change through semi-structured interviews carried out with decision makers in the State Government, Scientific Organisations, consultants, local academia, implementing and development agencies, and farmers for whom the adaptation strategies are targeted. Using Social Network and Stakeholder Analysis approach, this research unravels the complexities of perceiving climate change impacts, identifying adaptation strategies, and implementing climate change adaptation strategies. While farmers are less aware about the global phenomenon of climate change impacts for their subsistence livelihood, their knowledge of the local conditions and their close interaction with the State Government Agriculture Department provides them an access to new and high value crops. Although important steps are initiated through the Sikkim State Action Plan on Climate Change it is yet to deliver effective means of adaptation implementation and identifying the networks of close coordination between the various implementing agencies will likely to pay rich dividends. While Sikkim being a small and hilly state with specific contextual challenges of climate change impacts, the results from this study highlights how the internal and external networks between various types of stakeholders informs decision makers in identifying local impacts of climate change and plan adaptation strategies.

Interagency collaboration in the Rocky Mountains and Great Plains: Federal-university climate service networks for producing actionable information for climate change adaptation

NASA Astrophysics Data System (ADS)

Ray, A. J.; McNie, E.; Averyt, K.; Morisette, J. T.; Derner, J. D.; Ojima, D. S.; Dilling, L.; Barsugli, J. J.

2014-12-01

Several federal agencies in north-central United States are each working to develop and disseminate useful climate information to enhance resilience to climate change. This talk will discuss how the U.S. Geological Survey (USGS) the North Central Climate Science Center, the National Oceanic and Atmospheric Administration Western Water Assessment RISA, and the U.S. Department of Agriculture Climate Hub, are building and managing a collaborative research and climate-service network in the Rocky Mountains and Great Plains. This presentation will describe the evolution of the interagency collaboration and the partnership with universities to build a climate service network. Such collaboration takes time and intention and must include the right people and organizations to effectively bridge the gap between use-inspired research and application. In particular, we will discuss a focus on the Upper Missouri Basin, developing research to meet needs in a basin that has had relatively less attention on risks of climate change and adaptation to those risks. Each organization has its own mission, stakeholders, and priorities, but there are many commonalities and potential synergies. Together, these organizations, and their agency scientists and university partners, are fostering cross-agency collaboration at the regional scale to optimize efficient allocation of resources while simultaneously enabling information to be generated at a scale that is relevant to decision makers. By each organization knowing the others needs and priorities, there are opportunities to craft research agendas and strategies for providing services that take advantage of the strengths and skills of the different organizations. University partners are key components of each organization, and of the collaboration, who bring in expertise beyond that in the agencies, in particular connections to social scientists, extension services.

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

PubMed Central

Virkkala, Raimo; Heikkinen, Risto K.; Fronzek, Stefan; Leikola, Niko

2013-01-01

National reserve networks are one of the most important means of species conservation, but their efficiency may be diminished due to the projected climatic changes. Using bioclimatic envelope models and spatial data on habitats and conservation areas, we studied how efficient the reserve network will be in preserving 100 forest, mire, marshland, and alpine bird species of conservation concern in Finland in 2051–2080 under three different climate scenarios. The occurrences of the studied bird species were related to the amount of habitat preferred by each species in the different boreal zones. We employed a novel integrated habitat suitability index that takes into account both the species’ probability of occurrence from the bioclimatic models and the availability of suitable habitat. Using this suitability index, the distribution of the topmost 5% suitability squares (“hotspots”) in the four bird species groups in the period 1971–2000 and under the three scenarios were compared with the location of reserves with the highest amounts of the four habitats to study the efficiency of the network. In species of mires, marshlands, and Arctic mountains, a high proportion of protected habitat was included in the 5% hotspots in the scenarios in 2051–2080, showing that protected areas cover a high proportion of occurrences of bird species. In contrast, in forests in the southern and middle boreal zones, only a small proportion of the protected habitat was included in the 5% hotspots, indicating that the efficiency of the protected area network will be insufficient for forest birds in the future. In the northern boreal zone, the efficiency of the reserve network in forests was highly dependent on the strength of climate change varying between the scenarios. Overall, there is no single solution to preserving biodiversity in a changing climate, but several future pathways should be considered. PMID:23700420

Climate change, northern birds of conservation concern and matching the hotspots of habitat suitability with the reserve network.

PubMed

Virkkala, Raimo; Heikkinen, Risto K; Fronzek, Stefan; Leikola, Niko

2013-01-01

National reserve networks are one of the most important means of species conservation, but their efficiency may be diminished due to the projected climatic changes. Using bioclimatic envelope models and spatial data on habitats and conservation areas, we studied how efficient the reserve network will be in preserving 100 forest, mire, marshland, and alpine bird species of conservation concern in Finland in 2051-2080 under three different climate scenarios. The occurrences of the studied bird species were related to the amount of habitat preferred by each species in the different boreal zones. We employed a novel integrated habitat suitability index that takes into account both the species' probability of occurrence from the bioclimatic models and the availability of suitable habitat. Using this suitability index, the distribution of the topmost 5% suitability squares ("hotspots") in the four bird species groups in the period 1971-2000 and under the three scenarios were compared with the location of reserves with the highest amounts of the four habitats to study the efficiency of the network. In species of mires, marshlands, and Arctic mountains, a high proportion of protected habitat was included in the 5% hotspots in the scenarios in 2051-2080, showing that protected areas cover a high proportion of occurrences of bird species. In contrast, in forests in the southern and middle boreal zones, only a small proportion of the protected habitat was included in the 5% hotspots, indicating that the efficiency of the protected area network will be insufficient for forest birds in the future. In the northern boreal zone, the efficiency of the reserve network in forests was highly dependent on the strength of climate change varying between the scenarios. Overall, there is no single solution to preserving biodiversity in a changing climate, but several future pathways should be considered.

The Power of Cooperation in International Paleoclimate Science: Examples from the PAGES 2k Network and the Ocean2k Working Group

NASA Astrophysics Data System (ADS)

Addison, J. A.

2015-12-01

The Past Global Changes (PAGES) project of IGBP and Future Earth supports research to understand the Earth's past environment to improve future climate predictions and inform strategies for sustainability. Within this framework, the PAGES 2k Network was established to provide a focus on the past 2000 years, a period that encompasses Medieval Climate Anomaly warming, Little Ice Age cooling, and recent anthropogenically-forced climate change. The results of these studies are used for testing earth system models, and for understanding decadal- to centennial-scale variability, which is needed for long-term planning. International coordination and cooperation among the nine regional Working Groups that make up the 2k Network has been critical to the success of PAGES 2k. The collaborative approach is moving toward scientific achievements across the regional groups, including: (i) the development of a community-driven open-access proxy climate database; (ii) integration of multi-resolution proxy records; (iii) development of multivariate climate reconstructions; and (iv) a leap forward in the spatial resolution of paleoclimate reconstructions. The last addition to the 2k Network, the Ocean2k Working Group has further innovated the collaborative approach by: (1) creating an open, receptive environment to discuss ideas exclusively in the virtual space; (2) employing an array of real-time collaborative software tools to enable communication, group document writing, and data analysis; (3) consolidating executive leadership teams to oversee project development and manage grassroots-style volunteer pools; and (4) embracing the value-added role that international and interdisciplinary science can play in advancing paleoclimate hypotheses critical to understanding future change. Ongoing efforts for the PAGES 2k Network are focused on developing new standards for data quality control and archiving. These tasks will provide the foundation for new and continuing "trans-regional" 2k projects which address paleoclimate science that transcend regional boundaries. The PAGES 2k Network encourages participation by all investigators interested in this community-wide project.

Evaluation of a new satellite-based precipitation dataset for climate studies in the Xiang River basin, Southern China

NASA Astrophysics Data System (ADS)

Zhu, Q.; Xu, Y. P.; Hsu, K. L.

2017-12-01

A new satellite-based precipitation dataset, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with long-term time series dating back to 1983 can be one valuable dataset for climate studies. This study investigates the feasibility of using PERSIANN-CDR as a reference dataset for climate studies. Sixteen CMIP5 models are evaluated over the Xiang River basin, southern China, by comparing their performance on precipitation projection and streamflow simulation, particularly on extreme precipitation and streamflow events. The results show PERSIANN-CDR is a valuable dataset for climate studies, even on extreme precipitation events. The precipitation estimates and their extreme events from CMIP5 models are improved significantly compared with rain gauge observations after bias-correction by the PERSIANN-CDR precipitation estimates. Given streamflows simulated with raw and bias-corrected precipitation estimates from 16 CMIP5 models, 10 out of 16 are improved after bias-correction. The impact of bias-correction on extreme events for streamflow simulations are unstable, with eight out of 16 models can be clearly claimed they are improved after the bias-correction. Concerning the performance of raw CMIP5 models on precipitation, IPSL-CM5A-MR excels the other CMIP5 models, while MRI-CGCM3 outperforms on extreme events with its better performance on six extreme precipitation metrics. Case studies also show that raw CCSM4, CESM1-CAM5, and MRI-CGCM3 outperform other models on streamflow simulation, while MIROC5-ESM-CHEM, MIROC5-ESM and IPSL-CM5A-MR behaves better than the other models after bias-correction.

Integrating Communication Best Practices in the Third National Climate Assessment

NASA Astrophysics Data System (ADS)

Hassol, S. J.

2014-12-01

Modern climate science assessments now have a history of nearly a quarter-century. This experience, together with important advances in relevant social sciences, has greatly improved our ability to communicate climate science effectively. As a result, the Third National Climate Assessment (NCA) was designed to be truly accessible and useful to all its intended audiences, while still being comprehensive and scientifically accurate. At a time when meeting the challenge of climate change is increasingly recognized as an urgent national and global priority, the NCA is proving to be valuable to decision-makers, the media, and the public. In producing this latest NCA, a communication perspective was an important part of the process from the beginning, rather than an afterthought as has often been the case with scientific reports. Lessons learned from past projects and science communications research fed into developing the communication strategy for the Third NCA. A team of editors and graphic designers worked closely with the authors on language, graphics, and photographs throughout the development of the report, Highlights document, and other products. A web design team helped bring the report to life online. There were also innovations in outreach, including a network of organizations intended to extend the reach of the assessment by engaging stakeholders throughout the process. Professional slide set development and media training were part of the preparation for the report's release. The launch of the NCA in May 2014 saw widespread and ongoing media coverage, continued references to the NCA by decision-makers, and praise from many quarters for its excellence in making complex science clear and accessible. This NCA is a professionally crafted report that exemplifies best practices in 21st century communications.

Mountain Weather and Climate, Third Edition

NASA Astrophysics Data System (ADS)

Hastenrath, Stefan

2009-05-01

For colleagues with diverse interests in the atmosphere, glaciers, radiation, landforms, water resources, vegetation, human implications, and more, Mountain Weather and Climate can be a valuable source of guidance and literature references. The book is organized into seven chapters: 1, Mountains and their climatological study; 2,Geographical controls of mountain meteorological elements; 3, Circulation systems related to orography; 4, Climatic characteristics of mountains; 5, Regional case studies; 6, Mountain bioclimatology; and 7, Changes in mountain climates. These chapters are supported by l78 diagrams and photographs, 47 tables, and some 2000 literature references. The volume has an appendix of units and energy conversion factors and a subject index, but it lacks an author index.

Do networking activities outside of the classroom protect students against being bullied? A field study with students in secondary school settings in Germany.

PubMed

Blickle, Gerhard; Meurs, James A; Schoepe, Christine

2013-01-01

Research has shown that having close relationships with fellow classmates can provide a buffer for students against bullying and the negative outcomes associated with it. But, research has not explicitly examined the potential benefits of social networking behaviors outside of the classroom for those who could be bullied. This study addresses this gap and finds that, although a bullying climate in the classroom increases overall bullying, students high on external networking activities did not experience an increase in the bullying they received when in a classroom with a high bullying climate. However, the same group of students reported the largest degree of received bulling under conditions of a low bullying climate. We discuss the implications of our results and provide directions for future research.

P2S--Coupled simulation with the Precipitation-Runoff Modeling System (PRMS) and the Stream Temperature Network (SNTemp) Models

USGS Publications Warehouse

Markstrom, Steven L.

2012-01-01

A software program, called P2S, has been developed which couples the daily stream temperature simulation capabilities of the U.S. Geological Survey Stream Network Temperature model with the watershed hydrology simulation capabilities of the U.S. Geological Survey Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a modular, deterministic, distributed-parameter, physical-process watershed model that simulates hydrologic response to various combinations of climate and land use. Stream Network Temperature was developed to help aquatic biologists and engineers predict the effects of changes that hydrology and energy have on water temperatures. P2S will allow scientists and watershed managers to evaluate the effects of historical climate and projected climate change, landscape evolution, and resource management scenarios on watershed hydrology and in-stream water temperature.

Birmingham Urban Climate Laboratory (BUCL): Experiences, Challenges and Applications of an Urban Temperature Network

NASA Astrophysics Data System (ADS)

Muller, Catherine; Chapman, Lee; Young, Duick; Grimmond, Sue; Cai, Xiaoming

2013-04-01

The Birmingham Urban Climate Laboratory (BUCL) has recently been established by the University of Birmingham. BUCL is an in-situ, real-time urban network that will incorporate 3 nested networks - a wide-array of 25 weather stations, a dense array of 131 low-cost air temperature sensors and a fine-array of temperature sensor across the city-centre (50/km^2) - with the primary aim of monitoring air temperatures across a morphologically-heterogeneous urban conurbation for a variety of applications. During its installation there have been a number of challenges to overcome, including siting equipment in suitable urban locations, ensuring that the measurements were 'representative' of the local-scale climate, managing a large, near real-time data set and implementing QA/QC procedures. From these experiences, the establishment of a standardised urban meteorological network metadata protocol has been proposed in order to improve data quality, to ensure the end-user has access to all the supplementary information they would require for conducting valid analyses and to encourage the adequate recording and documentation of any changes to in-situ urban networks over time. This paper will provide an introduction to the BUCL in-situ network, give an overview of the challenges and experiences gained from its implementation, and finally discuss the proposed applications of the network, including its use in remote sensing observations of urban temperatures, as well as health and infrastructure applications.

Building Bridges for Collaborative Digital Reference between Libraries and Museums through an Examination of Reference in Special Collections

ERIC Educational Resources Information Center

Lavender, Kenneth; Nicholson, Scott; Pomerantz, Jeffrey

2005-01-01

While a growing number of the digital reference services in libraries have become part of collaborative reference networks, other entities that serve similar information-seeking needs such as special collections and museums have not joined these networks, even though they are answering an increasing number of questions from off-site patrons via…

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Delta-Flux: An eddy covariance network for a climate-smart lower Mississippi basin

USDA-ARS?s Scientific Manuscript database

Networks of remotely monitored research sites are increasingly the model used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and Ameriflux lack contributions from the Lower Mississippi River Basin ...

Research on NGN network control technology

NASA Astrophysics Data System (ADS)

Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

2004-04-01

Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

Recent advances in near-surface moisture monitoring using commercial microwave links in Tel-Aviv University

NASA Astrophysics Data System (ADS)

Alpert, Pinhas; David, Noam; Messer, Hagit

2015-04-01

The propagation of electromagnetic radiation in the lower atmosphere, at centimeter wavelengths, is impaired by atmospheric conditions. Absorption and scattering of the radiation, at frequencies of tens of GHz, are directly related to the atmospheric phenomena, primarily precipitation, oxygen, mist, fog and water vapor. As was recently shown, wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. On the other hand, at present, there are no satisfactory real time flash flood warning facilities found to cope well with this phenomenon. I will exemplify the flash flood warning potential of the commercial wireless communication system for two different semi-arid region cases when floods occurred in the Judean desert and in the northern Negev in Israel. In addition, I will review our recent improvements in monitoring rainfall as well as other-than-rain phenomena like, atmospheric moisture. Special focus on fog monitoring potential will be highlighted. References: N. David, O. Sendik, H. Messer and P. Alpert, "Cellular network infrastructure- the future of fog monitoring?", BAMS, (in press, 2015). N. David, P. Alpert and H. Messer, "The potential of cellular network infrastructures for sudden rainfall monitoring in dry climate regions", Atmospheric Research, 131, 13-21, 2013.

Fractional Snow Cover Mapping by Artificial Neural Networks and Support Vector Machines

NASA Astrophysics Data System (ADS)

Çiftçi, B. B.; Kuter, S.; Akyürek, Z.; Weber, G.-W.

2017-11-01

Snow is an important land cover whose distribution over space and time plays a significant role in various environmental processes. Hence, snow cover mapping with high accuracy is necessary to have a real understanding for present and future climate, water cycle, and ecological changes. This study aims to investigate and compare the design and use of artificial neural networks (ANNs) and support vector machines (SVMs) algorithms for fractional snow cover (FSC) mapping from satellite data. ANN and SVM models with different model building settings are trained by using Moderate Resolution Imaging Spectroradiometer surface reflectance values of bands 1-7, normalized difference snow index and normalized difference vegetation index as predictor variables. Reference FSC maps are generated from higher spatial resolution Landsat ETM+ binary snow cover maps. Results on the independent test data set indicate that the developed ANN model with hyperbolic tangent transfer function in the output layer and the SVM model with radial basis function kernel produce high FSC mapping accuracies with the corresponding values of R = 0.93 and R = 0.92, respectively.

The 1998-2000 SHADOZ (Southern Hemisphere ADditional OZonesondes) Tropical Ozone Climatology. 2; Stratospheric and Tropospheric Ozone Variability and the Zonal Wave-One

NASA Technical Reports Server (NTRS)

Thompson, Anne M.; Witte, Jacquelyn C.; Oltmans, Samuel J.; Schmidlin, Francis J.; Logan, Jennifer A.; Fujiwara, Masatomo; Kirchhoff, Volker W. J. H.; Posny, Francoise; Coetzee, Gert J. R.; Hoegger, Bruno;

Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.

PubMed

Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2017-11-01

The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

The impact of climate change on transportation in the gulf coast

USGS Publications Warehouse

Savonis, M.J.; Burkett, V.R.; Potter, J.R.; Kafalenos, R.; Hyman, R.; Leonard, K.

2009-01-01

Climate affects the design, construction, safety, operations, and maintenance of transportation infrastructure and systems. The prospect of a changing climate raises critical questions regarding how alterations in temperature, precipitation, storm events, and other aspects of the climate could affect the nation's transportation system. This regional assessment of climate change and its potential impacts on transportation systems addresses these questions for the central Gulf Coast between Houston and Mobile. Warming temperatures are likely to increase the costs of transportation construction, maintenance, and operations. More frequent extreme precipitation events will likely disrupt transportation networks with flooding and visibility problems. Relative sea level rise will make much of the existing infrastructure more prone to frequent or permanent inundation. Increased storm intensity may lead to increased service disruption and damage. Consideration of these factors in today's transportation decisions should lead to a more robust, resilient, and cost-effective transportation network in the coming decades. ?? 2009 ASCE.

Implications of climate change on winter road networks in Ontario's Far North and northern Manitoba, Canada, based on climate model projections

NASA Astrophysics Data System (ADS)

Hori, Y.; Cheng, V. Y. S.; Gough, W. A.

2017-12-01

A network of winter roads in northern Canada connects a number of remote First Nations communities to all-season roads and rails. The extent of the winter road networks depends on the geographic features, socio-economic activities, and the numbers of remote First Nations so that it differs among the provinces. The most extensive winter road networks below the 60th parallel south are located in Ontario and Manitoba, serving 32 and 18 communities respectively. In recent years, a warmer climate has resulted in a shorter winter road season and an increase in unreliable road conditions; thus, limiting access among remote communities. This study focused on examining the future freezing degree-days (FDDs) accumulations during the winter road season at selected locations throughout Ontario's Far North and northern Manitoba using recent climate model projections from the multi-model ensembles of General Circulation Models (GCMs) under the Representative Concentration Pathway (RCP) scenarios. First, the non-parametric Mann-Kendall correlation test and the Theil-Sen method were used to identify any statistically significant trends between FDDs and time for the base period (1981-2010). Second, future climate scenarios are developed for the study areas using statistical downscaling methods. This study also examined the lowest threshold of FDDs during the winter road construction in a future period. Our previous study established the lowest threshold of 380 FDDs, which derived from the relationship between the FDDs and the opening dates of James Bay Winter Road near the Hudson-James Bay coast. Thus, this study applied the threshold measure as a conservative estimate of the minimum threshold of FDDs to examine the effects of climate change on the winter road construction period.

Climate Local Information over the Mediterranean to Respond User Needs

NASA Astrophysics Data System (ADS)

Ruti, P.

2012-12-01

CLIM-RUN aims at developing a protocol for applying new methodologies and improved modeling and downscaling tools for the provision of adequate climate information at regional to local scale that is relevant to and usable by different sectors of society (policymakers, industry, cities, etc.). Differently from current approaches, CLIM-RUN will develop a bottom-up protocol directly involving stakeholders early in the process with the aim of identifying well defined needs at the regional to local scale. The improved modeling and downscaling tools will then be used to optimally respond to these specific needs. The protocol is assessed by application to relevant case studies involving interdependent sectors, primarily tourism and energy, and natural hazards (wild fires) for representative target areas (mountainous regions, coastal areas, islands). The region of interest for the project is the Greater Mediterranean area, which is particularly important for two reasons. First, the Mediterranean is a recognized climate change hot-spot, i.e. a region particularly sensitive and vulnerable to global warming. Second, while a number of countries in Central and Northern Europe have already in place well developed climate service networks (e.g. the United Kingdom and Germany), no such network is available in the Mediterranean. CLIM-RUN is thus also intended to provide the seed for the formation of a Mediterranean basin-side climate service network which would eventually converge into a pan-European network. The general time horizon of interest for the project is the future period 2010-2050, a time horizon that encompasses the contributions of both inter-decadal variability and greenhouse-forced climate change. In particular, this time horizon places CLIM-RUN within the context of a new emerging area of research, that of decadal prediction, which will provide a strong potential for novel research.

Climate Science's Globally Distributed Infrastructure

NASA Astrophysics Data System (ADS)

Williams, D. N.

2016-12-01

The Earth System Grid Federation (ESGF) is primarily funded by the Department of Energy's (DOE's) Office of Science (the Office of Biological and Environmental Research [BER] Climate Data Informatics Program and the Office of Advanced Scientific Computing Research Next Generation Network for Science Program), the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), and the National Science Foundation (NSF), the European Infrastructure for the European Network for Earth System Modeling (IS-ENES), and the Australian National University (ANU). Support also comes from other U.S. federal and international agencies. The federation works across multiple worldwide data centers and spans seven international network organizations to provide users with the ability to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a series of geographically distributed peer nodes that are independently administered and united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP; output used by the Intergovernmental Panel on Climate Change assessment reports), multiple model intercomparison projects (MIPs; endorsed by the World Climate Research Programme [WCRP]), and the Accelerated Climate Modeling for Energy (ACME; ESGF is included in the overarching ACME workflow process to store model output). ESGF is a successful example of integration of disparate open-source technologies into a cohesive functional system that serves the needs the global climate science community. Data served by ESGF includes not only model output but also observational data from satellites and instruments, reanalysis, and generated images.

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling

PubMed Central

Shin, Junha; Lee, Insuk

2015-01-01

Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life—Archaea, Bacteria, and Eukaryota—suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co-inheritance analysis within the domains of life will greatly potentiate the use of the expected onslaught of sequenced genomes in the study of molecular pathways in higher eukaryotes. PMID:26394049

Responses to a questionnaire on networking between OIE Reference Laboratories and OIE Collaborating Centres.

PubMed

Brückner, G K; Linnane, S; Diaz, F; Vallat, B

2007-01-01

Two separate questionnaires were distributed to 20 OIE Collaborating Centres and 160 OIE Reference Laboratories to assess the current status of networking and collaboration among OIE Reference Laboratories and between OIE Reference Laboratories and OIE Collaborating Centres. The questionnaire for the OIE Reference Laboratories contained 7 sections with questions on networking between laboratories, reporting of information, biosecurity quality control, and financing. Emphasis was placed in obtaining information on inter-laboratory relationships and exchange of expertise, training needs and sharing of data and information. The questionnaire for the OIE Collaborating Centres contained six sections with the emphasis on aspects related to awareness of services that can be provided, expertise that could be made available, sharing of information and the relationship with the national veterinary services of the countries concerned. The responses to the questionnaires were collated, categorised and statistically evaluated to allow for tentative inferences on the data provided. Valuable information emanated from the data identifying the current status of networking and indicating possible shortcomings that could be addressed to improve networking.

Construction of a pulse-coupled dipole network capable of fear-like and relief-like responses

NASA Astrophysics Data System (ADS)

Lungsi Sharma, B.

2016-07-01

The challenge for neuroscience as an interdisciplinary programme is the integration of ideas among the disciplines to achieve a common goal. This paper deals with the problem of deriving a pulse-coupled neural network that is capable of demonstrating behavioural responses (fear-like and relief-like). Current pulse-coupled neural networks are designed mostly for engineering applications, particularly image processing. The discovered neural network was constructed using the method of minimal anatomies approach. The behavioural response of a level-coded activity-based model was used as a reference. Although the spiking-based model and the activity-based model are of different scales, the use of model-reference principle means that the characteristics that is referenced is its functional properties. It is demonstrated that this strategy of dissection and systematic construction is effective in the functional design of pulse-coupled neural network system with nonlinear signalling. The differential equations for the elastic weights in the reference model are replicated in the pulse-coupled network geometrically. The network reflects a possible solution to the problem of punishment and avoidance. The network developed in this work is a new network topology for pulse-coupled neural networks. Therefore, the model-reference principle is a powerful tool in connecting neuroscience disciplines. The continuity of concepts and phenomena is further maintained by systematic construction using methods like the method of minimal anatomies.

Toward a U.S. National Phenological Assessment

NASA Astrophysics Data System (ADS)

Henebry, Geoffrey M.; Betancourt, Julio L.

2010-01-01

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

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

Dermody, Brian; van Beek, Rens; Meeks, Elijah; Klein Goldewijk, Kees; Scheidel, Walter; van der Velde, Ype; Bierkens, Marc; Wassen, Martin; Dekker, Stefan

2015-04-01

The Romans were perhaps the most impressive exponents of water resource management in pre-industrial times with irrigation and virtual water trade facilitating unprecedented urbanisation and socio-economic stability for hundreds of years in a region of highly variable climate. To understand Roman water resource management in response to urbanisation and climate variability, a Virtual Water Network of the Roman World was developed. Using this network we found that irrigation and virtual water trade increased Roman resilience to inter-annual climate variability. However, urbanisation and population growth arising from virtual water trade likely pushed the Empire closer to the boundary of its water resources, led to an increase in import costs, and eroded its resilience to climate variability in the long term. Our newest findings also assess the impact that persistent climate change associated with Holocene climate anomalies had on Roman water resource management. Specifically we assess the impact of the change in climate from the Roman Warm Period to the Dark Ages Cold Period on the Roman food supply and whether it could have contributed to the fall of the Western Roman Empire.

Environmental networks for large-scale monitoring of Earth and atmosphere

NASA Astrophysics Data System (ADS)

Maurodimou, Olga; Kolios, Stavros; Konstantaras, Antonios; Georgoulas, George; Stylios, Chrysostomos

2013-04-01

Installation and operation of instrument/sensor networks are proven fundamental in the monitoring of the physical environment from local to global scale. The advances in electronics, wireless communications and informatics has led to the development of a huge number of networks at different spatial scales that measure, collect and store a wide range of environmental parameters. These networks have been gradually evolved into integrated information systems that provide real time monitoring, forecasts and different products from the initial collected datasets. Instrument/sensor networks have nowadays become important solutions for environmental monitoring, comprising a basic component of fully automated systems developing worldwide that contribute in the efforts for a sustainable Earth's environment (e.g. Hart et al., 2006, Othman et al., 2012). They are also used as a source of data for models parameterization and as verification tools for accuracy assessment techniques of the satellite imagery. Environmental networks can be incorporated into decision support systems (e.g Rizzi et al., 2012) providing informational background along with data from satellites for decision making, manage problems, suggest solutions and best practices for a sustainable management of the environment. This is a comparative study aiming to examine and highlight the significant role of existing instrument/sensor networks for large-scale monitoring of environmental issues, especially atmospheric and marine environment as well as weather and climate. We provide characteristic examples of integrated systems based on large scale instrument/sensor networks along with other sources of data (like satellite datasets) as informational background to measure, identify, monitor, analyze and forecast a vast series of atmospheric parameters (like CO2, O3, particle matter and solar irradiance), weather, climate and their impacts (e.g., cloud systems, lightnings, rainfall, air and surface temperature, humidity, winds) and marine environment (salinity, water quality, sea surface temperature among others). "ZEUS" lightning detection system (Chronis et al. 2006, Lagouvardos et al. 2009), "UVnet" system that is primarily referred to the UltaViolet solar irradiance (Bais et al. 2006, Kazantzidis et al. 2006) and "GLOBcolour" system for seas monitoring, are some characteristic examples of systems that use networks of instruments/sensors to monitor relative parameters. The chosen examples are focused on the European continent. Basic operating principles of these networks, their usefulness, restrictions and their perspectives in the environmental real time basis monitoring and forecast, are also described. References Bais, A.F., Meleti, C. Kazantzidis, A., Topaloglou, C., Zerefos, C.S., Kosmidis, E. 2006. Greek UV Network: Results and perspectives after three years. 8th Conference on Meteorology - Climatology and Atmospheric Physics, 24-25 May, Athens, Greece. Chronis, T., Anagnostou, E. 2006. Evaluation of a Long-Range Lightning Detection Network with Receivers in Europe and Africa. IEEE Transactions on Geoscience and Remote Sensing, 44, 1504-1510. Hart, K.J., Martinez, K. 2006. Environmental Sensor Networks: A revolution in the Earth system science? Earth-Science Reviews, 78, 178-19. Kazantzidis, A., Bais, A.F, Topaloglou, C., Garane, K., Zempila, M., Meleti, C., Zerefos, C.S. 2006. Quality assurance of the Greek UV Network: preliminary results from the pilot phase operation. Proceedings of SPIE Europe Remote Sensing of Clouds and the Atmosphere XI, vol. 6362, 636229-1 - 636229-10, Stockholm, Sweden, 11-14 September. Lagouvardos, K., Kotroni, V, Betz, D-H., Schmidt, K. 2009. A comparison of lightning data provided by ZEUS and LINET networks over Western Europe. Natural Hazards and Earth Systems Sciences, 9, 1713-1717. Maritorena, S., D'Andon, O.H.F., Mangin, A., Siegel, D.A., 2010. Merged satellite ocean color data products using bio-optical model: Characteristics, benefits and issues. Remote Sensing of Environment, 114, 1791-1804. Othman, M.F., Shazali K., 2012. Wireless Network Applications: A study in environment monitoring system. Procedia Engineering, 41, 1204-1210. Rizzi, J., Torresan, S., Zabeo, A., Gallina, V., Critto, A., Marcomini, A., 2012. A GIS-based Decision Support System to support the implementation of integrated coastal zone management - preliminary results from the PEGASO project. Proceedings of the AGILE' 2012 International Conference on Geographical Information Science, Avignon, April, 24-27.

Evaluation of Integration Degree of the ASG-EUPOS Polish Reference Networks With Ukrainian GeoTerrace Network Stations in the Border Area

NASA Astrophysics Data System (ADS)

Siejka, Zbigniew

2017-09-01

GNSS systems are currently the basic tools for determination of the highest precision station coordinates (e.g. basic control network stations or stations used in the networks for geodynamic studies) as well as for land, maritime and air navigation. All of these tasks are carried out using active, large scale, satellite geodetic networks which are complex, intelligent teleinformatic systems offering post processing services along with corrections delivered in real-time for kinematic measurements. Many countries in the world, also in Europe, have built their own multifunctional networks and enhance them with their own GNSS augmentation systems. Nowadays however, in the era of international integration, there is a necessity to consider collective actions in order to build a unified system, covering e.g. the whole Europe or at least some of its regions. Such actions have already been undertaken in many regions of the world. In Europe such an example is the development for EUPOS which consists of active national networks built in central eastern European countries. So far experience and research show, that the critical areas for connecting these networks are border areas, in which the positioning accuracy decreases (Krzeszowski and Bosy, 2011). This study attempts to evaluate the border area compatibility of Polish ASG-EUPOS (European Position Determination System) reference stations and Ukrainian GeoTerrace system reference stations in the context of their future incorporation into the EUPOS. The two networks analyzed in work feature similar hardware parameters. In the ASG-EUPOS reference stations network, during the analyzed period, 2 stations (WLDW and CHEL) used only one system (GPS), while, in the GeoTerrace network, all the stations were equipped with both GPS and GLONASS receivers. The ASG EUPOS reference station network (95.6%) has its average completeness greater by about 6% when compared to the GeoTerrace network (89.8%).

Identifying Typhoon Tracks based on Event Synchronization derived Spatially Embedded Climate Networks

NASA Astrophysics Data System (ADS)

Ozturk, Ugur; Marwan, Norbert; Kurths, Jürgen

2017-04-01

Complex networks are commonly used for investigating spatiotemporal dynamics of complex systems, e.g. extreme rainfall. Especially directed networks are very effective tools in identifying climatic patterns on spatially embedded networks. They can capture the network flux, so as the principal dynamics of spreading significant phenomena. Network measures, such as network divergence, bare the source-receptor relation of the directed networks. However, it is still a challenge how to catch fast evolving atmospheric events, i.e. typhoons. In this study, we propose a new technique, namely Radial Ranks, to detect the general pattern of typhoons forward direction based on the strength parameter of the event synchronization over Japan. We suggest to subset a circular zone of high correlation around the selected grid based on the strength parameter. Radial sums of the strength parameter along vectors within this zone, radial ranks are measured for potential directions, which allows us to trace the network flux over long distances. We employed also the delay parameter of event synchronization to identify and separate the frontal storms' and typhoons' individual behaviors.

Assessing Elementary Science Methods Students' Understanding about Global Climate Change

ERIC Educational Resources Information Center

Lambert, Julie L.; Lindgren, Joan; Bleicher, Robert

2012-01-01

Global climate change, referred to as climate change in this paper, has become an important planetary issue, and given that K-12 students have numerous alternative conceptions or lack of prior knowledge, it is critical that teachers have an understanding of the fundamental science underlying climate change. Teachers need to understand the natural…

Analyze Technology Options | Climate Neutral Research Campuses | NREL

Science.gov Websites

Analyze Technology Options Analyze Technology Options An effective climate action plan follows a options would fit into a campus climate action plan and provides examples of how others have used these technologies. Links to definitions, technology basics, and references are also provided. Use the Climate Action

Impacts of Climate Change on Operation of the US Rail Network

EPA Science Inventory

The rail network in the US is the largest network within any single country at 140,000 miles of Class 1 tracks. The network is predominantly focused on freight traffic with the exception of key passenger corridors along the eastern seaboard and in the upper Midwest. This extens...

An assessment of climate change impacts on micro-hydropower energy recovery in water supply networks

NASA Astrophysics Data System (ADS)

Brady, Jennifer; Patil, Sopan; McNabola, Aonghus; Gallagher, John; Coughlan, Paul; Harris, Ian; Packwood, Andrew; Williams, Prysor

2015-04-01

Continuity of service of a high quality water supply is vital in sustaining economic and social development. However, water supply and wastewater treatment are highly energy intensive processes and the overall cost of water provision is rising rapidly due to increased energy costs, higher capital investment requirements, and more stringent regulatory compliance in terms of both national and EU legislation. Under the EU Directive 2009/28/EC, both Ireland and the UK are required to have 16% and 15% respectively of their electricity generated by renewable sources by 2020. The projected impacts of climate change, population growth and urbanisation will place additional pressures on resources, further increasing future water demand which in turn will lead to higher energy consumption. Therefore, there is a need to achieve greater efficiencies across the water industry. The implementation of micro-hydropower turbines within the water supply network has shown considerable viability for energy recovery. This is achieved by harnessing energy at points of high flow or pressure along the network which can then be utilised on site or alternatively sold to the national grid. Micro-hydropower can provide greater energy security for utilities together with a reduction in greenhouse gas emissions. However, potential climate change impacts on water resources in the medium-to-long term currently act as a key barrier to industry confidence as changes in flow and pressure within the network can significantly alter the available energy for recovery. The present study aims to address these uncertainties and quantify the regional and local impacts of climate change on the viability of energy recovery across water infrastructure in Ireland and the UK. Specifically, the research focuses on assessing the potential future effects of climate change on flow rates at multiple pressure reducing valve sites along the water supply network and also in terms of flow at a number of wastewater treatment works. This analysis is achieved through development of an empirical model utilising historical climatic data in conjunction with low, medium and high emission IPCC climate scenarios using the HADCM3 global climate model across a baseline condition and two further time steps. Results highlight projected alterations in flow rates together with the potential for increases in the frequency and persistence of drought/flooding events and the resulting impacts on future energy recovery. Critical climate change limits are also identified indicating the tolerable ranges within which hydropower recovery is financially viable, thus allowing for more informed decision making across potential sites.

Detecting instabilities in tree-ring proxy calibration

NASA Astrophysics Data System (ADS)

Visser, H.; Büntgen, U.; D'Arrigo, R.; Petersen, A. C.

2010-06-01

Evidence has been found for reduced sensitivity of tree growth to temperature in a number of forests at high northern latitudes and alpine locations. Furthermore, at some of these sites, emergent subpopulations of trees show negative growth trends with rising temperature. These findings are typically referred to as the "Divergence Problem" (DP). Given the high relevance of paleoclimatic reconstructions for policy-related studies, it is important for dendrochronologists to address this issue of potential model uncertainties associated with the DP. Here we address this issue by proposing a calibration technique, termed "stochastic response function" (SRF), which allows the presence or absence of any instabilities in growth response of trees (or any other climate proxy) to their calibration target to be visualized and detected. Since this framework estimates confidence limits and subsequently provides statistical significance tests, the approach is also very well suited for proxy screening prior to the generation of a climate-reconstruction network. Two examples of tree growth/climate relationships are provided, one from the North American Arctic treeline and the other from the upper treeline in the European Alps. Instabilities were found to be present where stabilities were reported in the literature, and vice versa, stabilities were found where instabilities were reported. We advise to apply SRFs in future proxy-screening schemes, next to the use of correlations and RE/CE statistics. It will improve the strength of reconstruction hindcasts.

Detecting instabilities in tree-ring proxy calibration

NASA Astrophysics Data System (ADS)

Visser, H.; Büntgen, U.; D'Arrigo, R.; Petersen, A. C.

2010-02-01

Evidence has been found for reduced sensitivity of tree growth to temperature in a number of forests at high northern latitudes and alpine locations. Furthermore, at some of these sites, emergent subpopulations of trees show negative growth trends with rising temperature. These findings are typically referred to as the "Divergence Problem" (DP). Given the high relevance of paleoclimatic reconstructions for policy-related studies, it is important for dendrochronologists to address this issue of potential model uncertainties associated with the DP. Here we address this issue by proposing a calibration technique, termed "stochastic response function" (SRF), which allows the presence or absence of any instabilities in growth response of trees (or any other climate proxy) to their calibration target to be visualized and detected. Since this framework estimates confidence limits and subsequently provides statistical significance tests, the approach is also very well suited for proxy screening prior to the generation of a climate-reconstruction network. Two examples of tree growth/climate relationships are provided, one from the North American Arctic treeline and the other from the upper treeline in the European Alps. Instabilities were found to be present where stabilities were reported in the literature, and vice versa, stabilities were found where instabilities were reported. We advise to apply SRFs in future proxy-screening schemes, next to the use of correlations and RE/CE statistics. It will improve the strength of reconstruction hindcasts.

Implication of climate change on urban drainage systems of Chicago and Mainstream and DesPlaines (MS/DP) Tunnel and Reservoir Plan (TARP)

NASA Astrophysics Data System (ADS)

Luo, H.; Schmidt, A.; Garcia, M. H.; Oberg, N.

2016-12-01

The impact of changing climate patterns and rainfall extremes on sewer system and river basin has been brought to attention to the researchers worldwide. In 1972, the Metropolitan Water Reclamation District of Greater Chicago (MWRDGC) adopted the Tunnel and Reservoir Plan (TARP) to address combined sewer overflow (CSO) pollution and flooding problems in the Chicago land area. The hydrosystem laboratory in University of Illinois at Urbana-Champaign developed a series of numerical models accordingly to analyze the complex hydraulic behavior of the as-built TARP system. Due to the interconnected nature of City of Chicago sewer network and MS/DP TARP system, a tightly coupled hydrological and hydraulic model MetroFlow was developed to facilitate such analysis by integrating previous developed models. This study utilized MetroFlow to predict the hydrologic/hydraulic response of the system for a set of pre-determined design and historical storm events. Accordingly, combined sewer overflows (CSO) of Chicago combined sewer system and MS/DP TARP system were evaluated under current and future weather scenarios. The total CSOs from TARP system can be considered as urban point pollution source to the surrounding receiving bodies, hence the potential impact of climate change on CSO fluxes is essential reference to wastewater infrastructure design and operations of the hydraulic regulating structures under storm events to mitigate predicted risks.

Quality Assurance for Essential Climate Variables

NASA Astrophysics Data System (ADS)

Folkert Boersma, K.; Muller, Jan-Peter

2015-04-01

Satellite data are of central interest to the QA4ECV project. Satellites have revolutionized the Earth's observation system of climate change and air quality over the past three decades, providing continuous data for the entire Earth. However, many users of these data are lost in the fog as to the quality of these satellite data. Because of this, the European Union expressed in its 2013 FP7 Space Research Call a need for reliable, traceable, and understandable quality information on satellite data records that could serve as a blueprint contribution to a future Copernicus Climate Change Service. The potential of satellite data to benefit climate change and air quality services is too great to be ignored. QA4ECV therefore bridges the gap between end-users of satellite data and the satellite data products. We are developing an internationally acceptable Quality Assurance (QA) framework that provides understandable and traceable quality information for satellite data used in climate and air quality services. Such a framework should deliver the historically linked long-term data sets that users need, in a format that they can readily use. QA4ECV has approached more than 150 users and suppliers of satellite data to collect their needs and expectations. The project will use their response as a guideline for developing user-friendly tools to obtain information on the completeness, accuracy, and fitness-for-purpose of the satellite datasets. QA4ECV collaborates with 4 joint FP7 Space projects in reaching out to scientists, policy makers, and other end-users of satellite data to improve understanding of the special challenges -and also opportunities- of working with satellite data for climate and air quality purposes. As a demonstration of its capacity, QA4ECV will generate multi-decadal climate data records for 3 atmospheric ECV precursors (nitrogen dioxide, formaldehyde, and carbon monoxide) and 3 land ECVs (albedo, leaf area index and absorbed photosynthetically active radiation), with full uncertainty metrics for every pixel. Multi-use tools and SI/community reference standards will be developed. But QA4ECV is not only about satellites. It is also about exploiting independent reference data obtained from in situ networks, and applying these data with the right, traceable methodologies for quality assurance of the satellite ECVs. The QA4ECV project started in January 2014, as a partnership between 17 research institutes from 7 different European countries working together for a period of 4 years. All QA4ECV partners are closely involved in projects improving, validating, and using satellite data. We hope that QA4ECV will be a major step forward in providing quality assured long-term climate data records that are relevant for policy and climate change assessments. A detailed description of the project can be found at http://qa4ecv.eu.

Phenology for science, resource management, decision making, and education

USGS Publications Warehouse

Nolan, V.P.; Weltzin, J.F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Phenology for Science, Resource Management, Decision Making, and Education

NASA Astrophysics Data System (ADS)

Nolan, Vivian P.; Weltzin, Jake F.

2011-01-01

Fourth USA National Phenology Network (USA-NPN) Research Coordination Network (RCN) Annual Meeting and Stakeholders Workshop; Milwaukee, Wisconsin, 21-22 September 2010; Phenology, the study of recurring plant and animal life cycle events, is rapidly emerging as a fundamental approach for understanding how ecological systems respond to environmental variation and climate change. The USA National Phenology Network (USA-NPN; http://www.usanpn.org) is a large-scale network of governmental and nongovernmental organizations, academic institutions, resource management agencies, and tribes. The network is dedicated to conducting and promoting repeated and integrated plant and animal phenological observations, identifying linkages with other relevant biological and physical data sources, and developing and distributing the tools to analyze these data at local to national scales. The primary goal of the USA-NPN is to improve the ability of decision makers to design strategies for climate adaptation.

Developing convolutional neural networks for measuring climate change opinions from social media data

NASA Astrophysics Data System (ADS)

Mao, H.; Bhaduri, B. L.

2016-12-01

Understanding public opinions on climate change is important for policy making. Public opinion, however, is typically measured with national surveys, which are often too expensive and thus being updated at a low frequency. Twitter has become a major platform for people to express their opinions on social and political issues. Our work attempts to understand if Twitter data can provide complimentary insights about climate change perceptions. Since the nature of social media is real-time, this data source can especially help us understand how public opinion changes over time in response to climate events and hazards, which though is very difficult to be captured by manual surveys. We use the Twitter Streaming API to collect tweets that contain keywords, "climate change" or "#climatechange". Traditional machine-learning based opinion mining algorithms require a significant amount of labeled data. Data labeling is notoriously time consuming. To address this problem, we use hashtags (a significant feature used to mark topics of tweets) to annotate tweets automatically. For example, hashtags, #climatedenial and #climatescam, are negative opinion labels, while #actonclimate and #climateaction are positive. Following this method, we can obtain a large amount of training data without human labor. This labeled dataset is used to train a deep convolutional neural network that classifies tweets into positive (i.e. believe in climate change) and negative (i.e. do not believe). Based on the positive/negative tweets obtained, we will further analyze risk perceptions and opinions towards policy support. In addition, we analyze twitter user profiles to understand the demographics of proponents and opponents of climate change. Deep learning techniques, especially convolutional deep neural networks, have achieved much success in computer vision. In this work, we propose a convolutional neural network architecture for understanding opinions within text. This method is compared with lexicon-based opinion analysis approaches. Results and the advantages/limitations of this method are to be discussed.

Professional Development in Climate Science Education as a Model for Navigating the Next Generations Science Standards - A High School Science Teacher's Perspective

NASA Astrophysics Data System (ADS)

Manning, C.; Buhr, S. M.

2012-12-01

The Next Generation Science Standards attempt to move the American K12 education system into the 21st century by focusing on science and engineering practice, crosscutting concepts, and the core ideas of the different disciplines. Putting these standards into practice will challenge a deeply entrenched system and science educators will need significant financial support from state and local governments, professional development from colleges and universities, and the creation of collegial academic networks that will help solve the many problems that will arise. While all of this sounds overwhelming, there are proven strategies and mechanisms already in place. Educators who tackle challenging topics like global climate change are turning to scientists and other like-minded teachers. Many of these teachers have never taken a class in atmospheric science but are expected to know the basics of climate and understand the emerging science as well. Teachers need scientists to continue to reach out and provide rigorous and in-depth professional development opportunities that enable them to answer difficult student questions and deal with community misconceptions about climate science. Examples of such programs include Earthworks, ICEE (Inspiring Climate Education Excellence) and ESSEA (Earth System Science Education Alliance). Projects like CLEAN (Climate Literacy and Energy Awareness Network) provide excellent resources that teachers can integrate into their lessons. All of these benefit from the umbrella of documents like Climate Literacy: The Essential Principles of Climate Science. Support from the aforementioned networks has encouraged the development of effective approaches for teaching climate science. From the perspective of a Geoscience master teacher and instructional coach, this presentation will demonstrate how scientists, researchers, and science education professionals have created models for professional development that create long-term networks supporting teachers who are willing to change how science is being taught right now. There will be specific examples of clearly written, evidence-based tools that address the general public's lack of critical climate knowledge and help to identify and change students' misconceptions. Specific content areas that continue to be overlooked as "common knowledge" but that need to be addressed in both pre- and in-service teacher instruction, textbooks, and online resources will be identified.

Water management in the Roman world

NASA Astrophysics Data System (ADS)

Dermody, Brian J.; van Beek, Rens L. P. H.; Meeks, Elijah; Klein Goldewijk, Kees; Bierkens, Marc F. P.; Scheidel, Walter; Wassen, Martin J.; van der Velde, Ype; Dekker, Stefan C.

2014-05-01

Climate variability can have extreme impacts on societies in regions that are water-limited for agriculture. A society's ability to manage its water resources in such environments is critical to its long-term viability. Water management can involve improving agricultural yields through in-situ irrigation or redistributing water resources through trade in food. Here, we explore how such water management strategies affected the resilience of the Roman Empire to climate variability in the water-limited region of the Mediterranean. Using the large-scale hydrological model PCR-GLOBWB and estimates of landcover based on the Historical Database of the Global Environment (HYDE) we generate potential agricultural yield maps under variable climate. HYDE maps of population density in conjunction with potential yield estimates are used to develop maps of agricultural surplus and deficit. The surplus and deficit regions are abstracted to nodes on a water redistribution network based on the Stanford Geospatial Network Model of the Roman World (ORBIS). This demand-driven, water redistribution network allows us to quantitatively explore how water management strategies such as irrigation and food trade improved the resilience of the Roman Empire to climate variability.

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Impacts of weighting climate models for hydro-meteorological climate change studies

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel

2017-06-01

Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.

Issues in PCS interoperability and Internetworking

NASA Technical Reports Server (NTRS)

Dean, Richard A.; Estabrook, Polly

1995-01-01

This paper is an expansion of an earlier paper on Satellite/Terrestrial PCS which addressed issues for interoperability that included Networks, Services, Voice Coders and Mobility/Security. This paper focuses on the narrower topic of Network Reference Models and associated interfaces and protocols. The network reference models are addressed from the perspective of the User, the Cellular Carrier, the PSN Carrier, and the Radio Vendor. Each perspective is presented in the way these systems have evolved. The TIA TR46/GSM reference model will be reviewed. Variations in the use of this model that are prevalent in the industry will be discussed. These are the North American Cellular networks, the GSM networks, and the North American Carriers/Bellcore perspective. The paper concludes with the presentation of issues that develop from looking at merging satellite service into a world of many different networks.

Assessing Current State Science Teaching and Learning Standards for Ability to Achieve Climate Science Literacy

NASA Astrophysics Data System (ADS)

Busch, K. C.

2012-12-01

Even though there exists a high degree of consensus among scientists about climate change, doubt has actually increased over the last five years within the general U.S. public. In 2006, 79% of those polled agreed that there is evidence for global warming, while only 59% agreed in 2010 (Pew Research Center, 2010). The source for this doubt can be partially attributed to lack of knowledge. Formal education is one mechanism that potentially can address inadequate public understanding as school is the primary place where students - and future citizens - learn about the climate. In a joint effort, several governmental agencies, non-governmental organizations, scientists and educators have created a framework called The Essential Principles of Climate Science Literacy, detailing seven concepts that are deemed vital for individuals and communities to understand Earth's climate system (USGCRP, 2009). Can students reach climate literacy - as defined by these 7 concepts - if they are taught using a curriculum based on the current state standards? To answer this question, the K-12 state science teaching and learning standards for Texas and California - two states that heavily influence nation-wide textbook creation - were compared against the Essential Principles. The data analysis consisted of two stages, looking for: 1) direct reference to "climate" and "climate change" and 2) indirect reference to the 7 Essential Principles through axial coding. The word "climate" appears in the California K-12 science standards 4 times and in the Texas standards 7 times. The word "climate change" appears in the California and Texas standards only 3 times each. Indirect references to the 7 Essential Principles of climate science literacy were more numerous. Broadly, California covered 6 of the principles while Texas covered all 7. In looking at the 7 principles, the second one "Climate is regulated by complex interactions among component of the Earth system" was the most substantively addressed. Least covered were number 6 "Human activities are impacting the climate system" and number 7 "Climate change will have consequences for the Earth system and human lives." Most references, either direct or indirect, occurred in the high school standards for earth science, a class not required for graduation in either state. This research points to the gaps between what the 7 Essential Principles of Climate Literacy defines as essential knowledge and what students may learn in their K-12 science classes. Thus, the formal system does not seem to offer an experience which can potentially develop a more knowledgeable citizenry who will be able to make wise personal and policy decisions about climate change, falling short of the ultimate goal of achieving widespread climate literacy. Especially troubling was the sparse attention to the principles addressing the human connection to the climate - principles number 6 and 7. If climate literate citizens are to make "wise personal and policy decisions" (USGCRP, 2009), these two principles especially are vital. This research, therefore, has been valuable for identifying current shortcomings in state standards.

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.

Evaluating a European knowledge hub on climate change in agriculture: Are we building a better connected community?

PubMed

Saetnan, Eli Rudinow; Kipling, Richard Philip

In order to maintain food security and sustainability of production under climate change, interdisciplinary and international collaboration in research is essential. In the EU, knowledge hubs are important funding instruments for the development of an interconnected European Research Area. Here, network analysis was used to assess whether the pilot knowledge hub MACSUR has affected interdisciplinary collaboration, using co-authorship of peer reviewed articles as a measure of collaboration. The broad community of all authors identified as active in the field of agriculture and climate change was increasingly well connected over the period studied. Between knowledge hub members, changes in network parameters suggest an increase in collaborative interaction beyond that expected due to network growth, and greater than that found in the broader community. Given that interdisciplinary networks often take several years to have an impact on research outputs, these changes within the relatively new MACSUR community provide evidence that the knowledge hub structure has been effective in stimulating collaboration. However, analysis showed that knowledge hub partners were initially well-connected, suggesting that the initiative may have gathered together researchers with particular resources or inclinations towards collaborative working. Long term, consistent funding and ongoing reflection to improve networking structures may be necessary to sustain the early positive signs from MACSUR, to extend its success to a wider community of researchers, or to repeat it in less connected fields of science. Tackling complex challenges such as climate change will require research structures that can effectively support and utilise the diversity of talents beyond the already well-connected core of scientists at major research institutes. But network research shows that this core, well-connected group are vital brokers in achieving wider integration.

Wrong kind of networking.

PubMed

Ortolon, Ken

2011-04-01

Patients who pay for out-of-network benefits should have the right to use those benefits, the Texas Medical Association believes. But TMA fears that a new CIGNA policy is designed to discourage enrollees from using their out-of-network benefits and will create huge administrative hassles for physicians who refer patients to out-of-network providers. TMA officials say the policy requires physicians to document that they told patients that they are being referred to out-of-network providers and to keep the documentation in their records indefinitely.

Embedded Efficiency: A Social Networks Approach to Popular Support and Dark Network Structure

DTIC Science & Technology

2016-03-01

Raab in “Dark networks as problems ,” (2003) where dark refers to illegal and, covert and bright refers to legal and overt. Throughout this report these...Milward, Jörg Raab, “Dark Networks as Organizational Problems : Elements of a Theory,” International Public Management Journal 9, no.3 ( 2006): 333–360...Emirbayer and Jeff Goodwin, “Network Analysis, Culture and the Problem of Agency,” American Journal of Sociology Vol. 99, No. 6 (May 1994): 1436. 35 Ibid

Exploring the reversibility of marine climate change impacts in temperature overshoot scenarios

NASA Astrophysics Data System (ADS)

Zickfeld, K.; Li, X.; Tokarska, K.; Kohfeld, K. E.

2017-12-01

Artificial carbon dioxide removal (CDR) from the atmosphere has been proposed as a measure for mitigating climate change and restoring the climate system to a `safe' state after overshoot. Previous studies have demonstrated that the changes in surface air temperature due to anthropogenic CO2 emissions can be reversed through CDR, while some oceanic properties, for example thermosteric sea level rise, show a delay in their response to CDR. This research aims to investigate the reversibility of changes in ocean conditions after implementation of CDR with a focus on ocean biogeochemical properties. To achieve this, we analyze climate model simulations based on two sets of emission scenarios. We first use RCP2.6 and its extension until year 2300 as the reference scenario and design several temperature and cumulative CO2 emissions "overshoot" scenarios based on other RCPs, which represents cases with less ambitious mitigation policies in the near term that temporarily exceed the 2 °C target adopted by the Paris Agreement. In addition, we use a set of emission scenarios with a reference scenario limiting warming to 1.5°C in the long term and two overshoot scenarios. The University of Victoria Earth System Climate Model (UVic ESCM), a climate model of intermediate complexity, is forced with these emission scenarios. We compare the response of select ocean variables (seawater temperature, pH, dissolved oxygen) in the overshoot scenarios to that in the respective reference scenario at the time the same amount of cumulative emissions is achieved. Our results suggest that the overshoot and subsequent return to a reference CO2 cumulative emissions level would leave substantial impacts on the marine environment. Although the changes in global mean sea surface variables (temperature, pH and dissolved oxygen) are largely reversible, global mean ocean temperature, dissolved oxygen and pH differ significantly from those in the reference scenario. Large ocean areas exhibit temperature increase and pH and dissolved oxygen decrease relative to the reference scenario without cumulative CO2 emissions overshoot. Furthermore, our results show that the higher the level of overshoot, the lower the reversibility of changes in the marine environment.

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Fluvial valleys in the heavily cratered terrains of Mars: Evidence for paleoclimatic change?

NASA Technical Reports Server (NTRS)

Gulick, V. C.; Baker, V. R.

1993-01-01

Whether the formation of the Martian valley networks provides unequivocal evidence for drastically different climatic conditions remains debatable. Recent theoretical climate modeling precludes the existence of a temperate climate early in Mars' geological history. An alternative hypothesis suggests that Mars had a globally higher heat flow early in its geological history, bringing water tables to within 350 m of the surface. While a globally higher heat flow would initiate ground water circulation at depth, the valley networks probably required water tables to be even closer to the surface. Additionally, it was previously reported that the clustered distribution of the valley networks within terrain types, particularly in the heavily cratered highlands, suggests regional hydrological processes were important. The case for localized hydrothermal systems is summarized and estimates of both erosion volumes and of the implied water volumes for several Martian valley systems are presented.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Estimating the future agriculture freight transportation network needs due to climate change using remote sensing and regional climate models.

DOT National Transportation Integrated Search

2016-12-01

A reoccurring challenge with increasing fuel prices is optimization of multi- and inter-modal freight transport to move products most efficiently. Projections for the future of agriculture in the United States (U.S.) combined with regional climate mo...

Longitudinal thermal heterogeneity in rivers and refugia for coldwater species: effects of scale and climate change

EPA Science Inventory

Climate-change driven increases in water temperature pose multiple challenges for aquatic organisms. Predictions of climate change impacts to biota typically do not account for fine-grained spatiotemporal patterns of stream networks; yet patches of cooler water within rivers c...

GEOdetic Data assimilation and EStimation of references for climate change InvEstigation. An overall presentation of the French GEODESIE project

NASA Astrophysics Data System (ADS)

Coulot, David; Richard, Jean-Yves

2017-04-01

Many major indicators of climate change are monitored with space observations (sea level rise from satellite altimetry, ice melting from dedicated satellites, etc.). This monitoring is highly dependent on references (positions and velocities of ground observing instruments, orbits of satellites, etc.) that only geodesy can provide. The current accuracy of these references does not permit to fully support the challenges that the constantly evolving Earth system gives rise to, and can consequently limit the accuracy of these indicators. For this reason, in the framework of the Global Geodetic Observing System (GGOS), stringent requirements are fixed to the International Terrestrial Reference Frame (ITRF) for the next decade: an accuracy at the level of 1 mm and a stability at the level of 0.1 mm/yr. This means an improvement of the current quality of ITRF by a factor of 5-10. Improving the quality of the geodetic references is an issue which requires a thorough reassessment of the methodologies involved. The most relevant and promising method to improve this quality is the direct combination (Combination at Observation Level - COL) of the space-geodetic measurements used to compute the official references of the International Earth Rotation and Reference Systems Service (IERS). The GEODESIE project aims at (i) determining highly-accurate global and consistent references (time series of Terrestrial Reference Frames and Celestial Reference Frames, of Earth's Orientation Parameters, and orbits of Earth's observation satellites) and (ii) providing the geophysical and climate research communities with these references, for a better estimation of geocentric sea level rise, ice mass balance and on-going climate changes. Time series of sea levels computed from altimetric data and tide gauge records with these references (orbits of satellite altimeters, Terrestrial Reference Frames and related vertical velocities of stations) will also be provided. The geodetic references will be essential bases for Earth's observation and monitoring to support the challenges of the century. The geocentric time series of sea levels will permit to better apprehend (i) the drivers of the global mean sea level rise and of regional variations of sea level and (ii) the contribution of the global climate change induced by anthropogenic greenhouse gases emissions to these drivers. All the results and computation and quality assessment reports will be available on a Website designed and opened in the Summer of 2017. This project, supported by the French Agence Nationale de la Recherche (ANR) for the period 2017-2020, will be an unprecedented opportunity to provide the French Groupe de Recherche de Géodésie Spatiale (GRGS) with complete simulation and data processing capabilities to prepare the future arrival of space missions such as the European Geodetic Reference Antenna in SPace (E-GRASP) and to significantly contribute to the GGOS with accurate references.

fMRI evidence for strategic decision-making during resolution of pronoun reference.

PubMed

McMillan, Corey T; Clark, Robin; Gunawardena, Delani; Ryant, Neville; Grossman, Murray

2012-04-01

Pronouns are extraordinarily common in daily language yet little is known about the neural mechanisms that support decisions about pronoun reference. We propose a large-scale neural network for resolving pronoun reference that consists of two components. First, a core language network in peri-Sylvian cortex supports syntactic and semantic resources for interpreting pronoun meaning in sentences. Second, a frontal-parietal network that supports strategic decision-making is recruited to support probabilistic and risk-related components of resolving a pronoun's referent. In an fMRI study of healthy young adults, we observed activation of left inferior frontal and superior temporal cortex, consistent with a language network. We also observed activation of brain regions not associated with traditional language areas. By manipulating the context of the pronoun, we were able to demonstrate recruitment of dorsolateral prefrontal cortex during probabilistic evaluation of a pronoun's reference, and orbital frontal activation when a pronoun must adopt a risky referent. Together, these findings are consistent with a two-component model for resolving a pronoun's reference that includes neuroanatomic regions supporting core linguistic and decision-making mechanisms. Copyright © 2012 Elsevier Ltd. All rights reserved.

fMRI Evidence for Strategic Decision-Making during Resolution of Pronoun Reference

ERIC Educational Resources Information Center

McMillan, Corey T.; Clark, Robin; Gunawardena, Delani; Ryant, Neville; Grossman, Murray

2012-01-01

Pronouns are extraordinarily common in daily language yet little is known about the neural mechanisms that support decisions about pronoun reference. We propose a large-scale neural network for resolving pronoun reference that consists of two components. First, a core language network in peri-Sylvian cortex supports syntactic and semantic…

Systematic Conservation Planning in the Face of Climate Change: Bet-Hedging on the Columbia Plateau

PubMed Central

Schloss, Carrie A.; Lawler, Joshua J.; Larson, Eric R.; Papendick, Hilary L.; Case, Michael J.; Evans, Daniel M.; DeLap, Jack H.; Langdon, Jesse G. R.; Hall, Sonia A.; McRae, Brad H.

2011-01-01

Systematic conservation planning efforts typically focus on protecting current patterns of biodiversity. Climate change is poised to shift species distributions, reshuffle communities, and alter ecosystem functioning. In such a dynamic environment, lands selected to protect today's biodiversity may fail to do so in the future. One proposed approach to designing reserve networks that are robust to climate change involves protecting the diversity of abiotic conditions that in part determine species distributions and ecological processes. A set of abiotically diverse areas will likely support a diversity of ecological systems both today and into the future, although those two sets of systems might be dramatically different. Here, we demonstrate a conservation planning approach based on representing unique combinations of abiotic factors. We prioritize sites that represent the diversity of soils, topographies, and current climates of the Columbia Plateau. We then compare these sites to sites prioritized to protect current biodiversity. This comparison highlights places that are important for protecting both today's biodiversity and the diversity of abiotic factors that will likely determine biodiversity patterns in the future. It also highlights places where a reserve network designed solely to protect today's biodiversity would fail to capture the diversity of abiotic conditions and where such a network could be augmented to be more robust to climate-change impacts. PMID:22174897

The National Climate Assessment: A Treasure Trove for Education, Communications and Outreach

NASA Astrophysics Data System (ADS)

McCaffrey, M.; Berbeco, M.; Connolly, R.; Niepold, F., III; Poppleton, K. L. I.; Cloyd, E.; Ledley, T. S.

2014-12-01

Required by Congress under the Global Change Act of 1990 to inform the nation on the findings of current climate research, the Third U.S. National Climate Assessment (NCA), released in May 2014, is a rich resource for climate change education, communications and outreach (ECO). Using a website design with mobile applications in mind, NCA takes advantage of mobile learning technology which is revolutionizing how, when and where learning occurs. In an effort to maximize the "teachable moments" inherent in the assessment, a community of experts from the National Center for Science Education and the CLEAN Network, working under the auspices of the National Climate Assessment Network (NCAnet) Education Affinity Group, have developed a series of NCA Learning Pathways that match key NCA messages and resources with reviewed educational materials and trusted online information sources, thereby adding pedagogical depth to the assessment. The NCA Learning Pathways, which focus on the regional chapters of the report, are designed make climate change science more local, human, relevant and, if properly framed by educators and communicators, hopeful for learners. This paper touches on the challenges and opportunities of infusing climate education, communications and outreach into curriculum and society, and details the development and content of NCA Learning Pathways, which are available online through NOAA's Climate.gov website: http://www.climate.gov/teaching

An evaluation of the distribution of sexual references among "Top 8" MySpace friends.

PubMed

Moreno, Megan A; Brockman, Libby; Rogers, Cara B; Christakis, Dimitri A

2010-10-01

To evaluate whether online friends of adolescents who display sexual references on a social networking site also display references. The method used was content analysis. The result of this study was that adolescents who displayed explicit sexual references were more likely to have online friends who displayed references. Thus, social networking sites present new opportunities to investigate adolescent sexual behavior. Copyright © 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

The Climate Change Education Partnership Alliance: Building a Network for Effective Collaboration and Impact (Invited)

NASA Astrophysics Data System (ADS)

Scowcroft, G.

2013-12-01

The mission of the Climate Change Education Partnership Alliance (The Alliance), funded by the National Science Foundation (NSF), is to advance exemplary climate change education through research and innovative partnerships. Through six unique regional projects, The Alliance is reaching wide and diverse audiences across the U.S., while linking groups and institutions that might not otherwise be connected by a common focus on climate change education. The goals for The Alliance include building collaborations between projects and institutions, sharing effective practices, and leveraging resources to create a community in which the whole is greater than the sum of its parts. To foster these goals, NSF has funded a central hub, the Alliance Office. Currently, the Alliance Office is building the infrastructure necessary to support activities and communication between the projects. Successful networks need objectives for their interactions and a common vision held by the partners. In the first national meeting of The Alliance members, held in June 2013, the foundation was laid to begin this work. The Alliance now has a common mission and vision to guide the next four years of activities. An initial 'mapping' of the network has identified the scope and diversity of the network, how members are connected, current boundaries of the network, network strengths and weaknesses, and network needs. This information will serve as a baseline as the network develops. The Alliance has also identified the need for key 'working groups' which provide an opportunity for members to work across the projects on common goals. As The Alliance evolves, building blocks identified by the field of network science will be used to forge a strong and successful collaborative enterprise. Infrastructure is being established to support widespread engagement; social ties are being fostered through face-to-face meetings and monthly teleconferences; time is provided to build and share knowledge; the sharing of new and diverse perspectives is encouraged; and resources will be leveraged across and beyond the projects. This presentation will provide an overview of The Alliance activities, lessons learned thus far, and plans for the future.

78 FR 75313 - Endangered and Threatened Wildlife and Plants; 12-Month Finding on a Petition To Reclassify...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-11

...), and climate change (Factor A). Additionally, the existing regulatory mechanisms are inadequate to...). Climate Change The term ``climate change'' refers to a change in the mean or variability of one or more.... 78). Various types of changes in climate can have direct or indirect effects on species, including...

High altitude environmental monitoring: the SHARE project and CEOP-HE

NASA Astrophysics Data System (ADS)

Tartari, G.

2009-04-01

Mountain areas above 2,500 m a.s.l. constitute about 25% of the Earth's surface and play a fundamental role in the global water balance, while influencing global climate and atmospheric circulation systems. Several millions, including lowlanders, are directly affected by the impacts of climate change on glaciers and water resource distribution. Mountains and high altitude plateaus are subject to the highest rate of temperature increase (e.g., Tibetan Plateau) and are recognized as particularly vulnerable to the effects of climate change. In spite of this, the number of permanent monitoring sites in the major environmental networks decreases with altitude. On a sample of two hundred high altitude automatic weather stations located above 2,500 m a.s.l., less than 20% are over 4,000 m, while there are only 24 stations in the world that could be considered "complete" high altitude observatories. Furthermore, entire mountain areas are left uncovered, creating significant data gaps which make reliable modelling and forecasting nearly impossible. In response to these problems, Ev-K2-CNR has developed the project SHARE (Stations at High Altitude for Research on the Environment) with the support of the Italian government and in collaboration with UNEP. This integrated environmental monitoring and research project aims to improve knowledge on the local, regional and global consequences of climate change in mountain regions and on the influence of high elevations on climate, atmospheric circulation and hydrology. SHARE today boasts a network of 13 permanent monitoring stations between 2,165 m and 8,000 m. Affiliated researchers have produced over 150 scientific publications in atmospheric sciences, meteorology and climate, glaciology, limnology and paleolimnology and geophysics. SHARE network data is also contributed to international programs (UNEP-ABC, WMO-GAW, WCRP-GEWEX-CEOP, NASA-AERONET, ILTER, EU-EUSAAR, EU-ACCENT). Within this context, the CEOP-High Elevations (CEOP-HE) element of regional focus was developed under the GEWEX CEOP programme to study multi-scale variability in water and energy cycles in high elevation areas, and to help improve observations, modelling and data management. Future plans include expansion of the SHARE network, addition of other key research areas including hydrology, and creation of mechanisms to favour exchange of data amongst high altitude networks. In coordination with other global research and monitoring projects (CliC, etc.), SHARE and CEOP-HE could provide a more organic and well-distributed interdisciplinary network, thus allowing governments and international agencies to better face impacts of climate change effects on energy and water budgets and elaborate appropriate adaptation strategies.

European climate variability and human susceptibility over the past 2500 years

NASA Astrophysics Data System (ADS)

Buentgen, U.

2010-09-01

Climate variations including droughts in the western US and African Sahel, landfalls of Atlantic hurricanes, and shifts in the Asian monsoon have affected human societies throughout history mainly by modulating water supply and agricultural productivity, health risk and civil conflict. Yet, discriminations of environmental impacts from political, economical and technological drivers of societal shifts are may be hampered by the indirect effects of climate on society, but certainly by the paucity of high-resolution palaeoclimatic evidence. Here we present a tree-ring network of 7284 precipitation sensitive oak series from lower elevations in France and Germany, and a compilation of 1546 temperature responsive conifers from higher elevations in the Austrian Alps, both covering the past 2500 years. Temporal distribution of historical felling dates of construction timber refers to changes in settlement activity that mirror different stages of economic wealth. Variations in Central European summer precipitation and temperature are contrasted with societal benchmarks. Prolonged periods of generally wet and warm summers, favourable for cultural prosperity, appeared during the Roman epoch between ~200 BC and 200 AD and from ~700-1000 AD, with the latter facilitating the rapid economic, cultural and political growth of medieval Europe. Unprecedented climate variability from ~200-500 AD coincides with the demise of the Western Roman Empire and the subsequent Barbarian Migrations. This period was characterized by continental-scale political turmoil, cultural stagnation and socio-economic instability including settlement abandonment, population migration, and societal collapse. Driest and coldest summers of the Late Holocene concurred in the 6th century, during which regional consolidation began. The recent political, cultural and fiscal reluctance to adapt to and mitigate projected climate change reflects the common belief of societal insusceptibility to environmental conditions. The complex climatic interference with agrarian civilizations, however, challenges the sustainability of this attitude. In addition to the long-term context it provides for instrumentally observed European climate variability, our study reveals critical targets for next-generation climate models to hindcast the temporal footprints and magnitudes of natural fluctuations over the Late Holocene in response to internal dynamics and external forcings.

Sea Surface Temperature for Climate Applications: A New Dataset from the European Space Agency Climate Change Initiative

NASA Astrophysics Data System (ADS)

Merchant, C. J.; Hulley, G. C.

2013-12-01

There are many datasets describing the evolution of global sea surface temperature (SST) over recent decades -- so why make another one? Answer: to provide observations of SST that have particular qualities relevant to climate applications: independence, accuracy and stability. This has been done within the European Space Agency (ESA) Climate Change Initative (CCI) project on SST. Independence refers to the fact that the new SST CCI dataset is not derived from or tuned to in situ observations. This matters for climate because the in situ observing network used to assess marine climate change (1) was not designed to monitor small changes over decadal timescales, and (2) has evolved significantly in its technology and mix of types of observation, even during the past 40 years. The potential for significant artefacts in our picture of global ocean surface warming is clear. Only by having an independent record can we confirm (or refute) that the work done to remove biases/trend artefacts in in-situ datasets has been successful. Accuracy is the degree to which SSTs are unbiased. For climate applications, a common accuracy target is 0.1 K for all regions of the ocean. Stability is the degree to which the bias, if any, in a dataset is constant over time. Long-term instability introduces trend artefacts. To observe trends of the magnitude of 'global warming', SST datasets need to be stable to <5 mK/year. The SST CCI project has produced a satellite-based dataset that addresses these characteristics relevant to climate applications. Satellite radiances (brightness temperatures) have been harmonised exploiting periods of overlapping observations between sensors. Less well-characterised sensors have had their calibration tuned to that of better characterised sensors (at radiance level). Non-conventional retrieval methods (optimal estimation) have been employed to reduce regional biases to the 0.1 K level, a target violated in most satellite SST datasets. Models for quantifying uncertainty have been developed to attach uncertainty to SST across a range of space-time scales. The stability of the data has been validated.

Study of mobile satellite network based on GEO/LEO satellite constellation

NASA Astrophysics Data System (ADS)

Hu, Xiulin; Zeng, Yujiang; Wang, Ying; Wang, Xianhui

2005-11-01

Mobile satellite network with Inter Satellite Links (ISLs), which consists of non-geostationary satellites, has the characteristic of network topology's variability. This is a great challenge to the design and management of mobile satellite network. This paper analyzes the characteristics of mobile satellite network, takes multimedia Quality of Service (QoS) as the chief object and presents a reference model based on Geostationary Earth Orbit (GEO)/ Low Earth Orbit (LEO) satellite constellation which adapts to the design and management of mobile satellite network. In the reference model, LEO satellites constitute service subnet with responsibility for the access, transmission and switch of the multimedia services for mobile users, while GEO satellites constitute management subnet taking on the centralized management to service subnet. Additionally ground control centre realizes the whole monitoring and control via management subnet. Comparing with terrestrial network, the above reference model physically separates management subnet from service subnet, which not only enhances the advantage of centralized management but also overcomes the shortcoming of low reliability in terrestrial network. Routing of mobile satellite network based on GEO/LEO satellite constellation is also discussed in this paper.

An Indoor Positioning Technique Based on a Feed-Forward Artificial Neural Network Using Levenberg-Marquardt Learning Method

NASA Astrophysics Data System (ADS)

Pahlavani, P.; Gholami, A.; Azimi, S.

2017-09-01

This paper presents an indoor positioning technique based on a multi-layer feed-forward (MLFF) artificial neural networks (ANN). Most of the indoor received signal strength (RSS)-based WLAN positioning systems use the fingerprinting technique that can be divided into two phases: the offline (calibration) phase and the online (estimation) phase. In this paper, RSSs were collected for all references points in four directions and two periods of time (Morning and Evening). Hence, RSS readings were sampled at a regular time interval and specific orientation at each reference point. The proposed ANN based model used Levenberg-Marquardt algorithm for learning and fitting the network to the training data. This RSS readings in all references points and the known position of these references points was prepared for training phase of the proposed MLFF neural network. Eventually, the average positioning error for this network using 30% check and validation data was computed approximately 2.20 meter.

A time reference distribution concept for a time division communication network

NASA Technical Reports Server (NTRS)

Stover, H. A.

1973-01-01

Starting with an assumed ideal network having perfect clocks at every node and known fixed transmission delays between nodes, the effects of adding tolerances to both transmission delays and nodal clocks is described. The advantages of controlling tolerances on time rather than frequency are discussed. Then a concept is presented for maintaining these tolerances on time throughout the network. This concept, called time reference distribution, is a systematic technique for distributing time reference to all nodes of the network. It is reliable, survivable and possesses many other desirable characteristics. Some of its features such as an excellent self monitoring capability will be pointed out. Some preliminary estimates of the accuracy that might be expected are developed and there is a brief discussion of the impact upon communication system costs. Time reference distribution is a concept that appears very attractive. It has not had experimental evaluation and has not yet been endorsed for use in any communication network.

Evaporation from weighing precipitation gauges: impacts on automated gauge measurements and quality assurance methods

NASA Astrophysics Data System (ADS)

Leeper, R. D.; Kochendorfer, J.

2014-12-01

The effects of evaporation on precipitation measurements have been understood to bias total precipitation lower. For automated weighing-bucket gauges, the World Meteorological Organization (WMO) suggests the use of evaporative suppressants with frequent observations. However, the use of evaporation suppressants is not always feasible due to environmental hazards and the added cost of maintenance, transport, and disposal of the gauge additive. In addition, research has suggested that evaporation prior to precipitation may affect precipitation measurements from auto-recording gauges operating at sub-hourly frequencies. For further evaluation, a field campaign was conducted to monitor evaporation and its impacts on the quality of precipitation measurements from gauges used at US Climate Reference Network (USCRN) stations. Collocated Geonor gauges with (nonEvap) and without (evap) an evaporative suppressant were compared to evaluate evaporative losses and evaporation biases on precipitation measurements. From June to August, evaporative losses from the evap gauge exceeded accumulated precipitation, with an average loss of 0.12 mm h-1. However, the impact of evaporation on precipitation measurements was sensitive to calculation methods. In general, methods that utilized a longer time series to smooth out sensor noise were more sensitive to gauge (-4.6% bias with respect to control) evaporation than methods computing depth change without smoothing (< +1% bias). These results indicate that while climate and gauge design affect gauge evaporation rates computational methods can influence the magnitude of evaporation bias on precipitation measurements. It is hoped this study will advance QA techniques that mitigate the impact of evaporation biases on precipitation measurements from other automated networks.

A user-targeted synthesis of the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

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

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. We consider different aspects: (1) marginal aspects such as mean, variance and extremes; (2) temporal aspects such as spell length characteristics; (3) spatial aspects such as the de-correlation length of precipitation extremes; and multi-variate aspects such as the interplay of temperature and precipitation or scale-interactions. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur. Experiment 1 (perfect predictors): what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Experiment 2 (Global climate model predictors): how is the overall representation of regional climate, including errors inherited from global climate models? Experiment 3 (pseudo reality): do methods fail in representing regional climate change? Here, we present a user-targeted synthesis of the results of the first VALUE experiment. In this experiment, downscaling methods are driven with ERA-Interim reanalysis data to eliminate global climate model errors, over the period 1979-2008. As reference data we use, depending on the question addressed, (1) observations from 86 meteorological stations distributed across Europe; (2) gridded observations at the corresponding 86 locations or (3) gridded spatially extended observations for selected European regions. With more than 40 contributing methods, this study is the most comprehensive downscaling inter-comparison project so far. The results clearly indicate that for several aspects, the downscaling skill varies considerably between different methods. For specific purposes, some methods can therefore clearly be excluded.

Merging Radar Quantitative Precipitation Estimates (QPEs) from the High-resolution NEXRAD Reanalysis over CONUS with Rain-gauge Observations

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.; Stevens, S. E.; Nickl, E.; Seo, D. J.; Kim, B.; Zhang, J.; Qi, Y.

2015-12-01

The processing of radar-only precipitation via the reanalysis from the National Mosaic and Multi-Sensor Quantitative (NMQ/Q2) based on the WSR-88D Next-generation Radar (Nexrad) network over the Continental United States (CONUS) is completed for the period covering from 2002 to 2011. While this constitutes a unique opportunity to study precipitation processes at higher resolution than conventionally possible (1-km, 5-min), the long-term radar-only product needs to be merged with in-situ information in order to be suitable for hydrological, meteorological and climatological applications. The radar-gauge merging is performed by using rain gauge information at daily (Global Historical Climatology Network-Daily: GHCN-D), hourly (Hydrometeorological Automated Data System: HADS), and 5-min (Automated Surface Observing Systems: ASOS; Climate Reference Network: CRN) resolution. The challenges related to incorporating differing resolution and quality networks to generate long-term large-scale gridded estimates of precipitation are enormous. In that perspective, we are implementing techniques for merging the rain gauge datasets and the radar-only estimates such as Inverse Distance Weighting (IDW), Simple Kriging (SK), Ordinary Kriging (OK), and Conditional Bias-Penalized Kriging (CBPK). An evaluation of the different radar-gauge merging techniques is presented and we provide an estimate of uncertainty for the gridded estimates. In addition, comparisons with a suite of lower resolution QPEs derived from ground based radar measurements (Stage IV) are provided in order to give a detailed picture of the improvements and remaining challenges.

Translating Research into Practice: Establishing a Network of Climate Change Practitioners in Ontario, Canada

NASA Astrophysics Data System (ADS)

Milner, G. A.

2017-12-01

Climate research and information continues to emerge at a rapid pace from the academic and scientific community. Decisions being made today by planners, engineers and staff across the Province of Ontario rely on science and information to plan and build our systems for the long term. Of course, as scientific information evolves continuously to produce lessons learned and new evidence, on the ground decisions often become entrenched in outdated information and need updating. Given this, bridging the gap between research to policy, and research to practice is of critical importance as the Province of Ontario upgrades its infrastructure, plans for long term growth in population within the Great Lakes Basin, and manages its natural systems and resources responsibly. The Ontario Climate Consortium (OCC) is an interdisciplinary network of academics and practitioners established in 2011 in the province that works to mobilize climate research findings towards building capacity, inspiring climate action, and training end-users with the latest science. The OCC has collaborated with more than 39 organizations throughout Ontario and across Canada, including government agencies at all levels (local, provincial and federal), non-profit organizations and private sector companies. This presentation will describe the foundations of climate action in Ontario, Canada including the landscape of climate adaptation practitioners from both public and private organizations. Furthermore, this presentation will feature lessons learned from the OCC network, including: 1) What comprises effective partnerships to undertake climate change adaptation planning for cities; 2) How to build the foundation for capacity at agencies with limited resources or expertise in the climate change field; and 3) How to successfully mobilize complex climate data for end-users to produce usable tools (through a case study research project). The latter will present findings from a two-year research project undertaken with OCC and the City of Vaughan, just northwest of Toronto, which examined vulnerability and risks of climate change to the city's stormwater infrastructure system and produced key tools and information for managers to begin building climate resilience into their planning and operations.

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

PubMed Central

Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna

2016-01-01

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

PubMed

Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

2016-05-17

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.

WSN system design by using an innovative neural network model to perform thermals forecasting in a urban canyon scenario

NASA Astrophysics Data System (ADS)

Giuseppina, Nicolosi; Salvatore, Tirrito

2015-12-01

Wireless Sensor Networks (WSNs) were studied by researchers in order to manage Heating, Ventilating and Air-Conditioning (HVAC) indoor systems. WSN can be useful specially to regulate indoor confort in a urban canyon scenario, where the thermal parameters vary rapidly, influenced by outdoor climate changing. This paper shows an innovative neural network approach, by using WSN data collected, in order to forecast the indoor temperature to varying the outdoor conditions based on climate parameters and boundary conditions typically of urban canyon. In this work more attention will be done to influence of traffic jam and number of vehicles in queue.

Climate Change Risk Management Consulting: The opportunity for an independent business practice

NASA Astrophysics Data System (ADS)

Ciccozzi, R.

2009-04-01

The Paper outlines the main questions to be addressed with reference to the actual demand of climate change risk management consulting, in the financial services. Moreover, the Project shall also try to investigate if the Catastrophe Modelling Industry can start and manage a business practice specialised on climate change risk exposures. In this context, the Paper aims at testing the possibility to build a sound business case, based upon typical MBA course analysis tools, such as PEST(LE), SWOT, etc. Specific references to the tools to be used and to other contribution from academic literature and general documentation are also discussed in the body of the Paper and listed at the end. The analysis shall also focus on the core competencies required for an independent climate change risk management consulting business practice, with the purpose to outline a valid definition of how to achieve competitive advantage in climate change risk management consulting.

How has climate change altered network connectivity in a mountain stream network?

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Johnson, S.

2017-12-01

Connectivity along river networks is broadly recognized as dynamic, with seasonal and event-based expansion and contraction of the network extent. Intermittently flowing streams are particularly important as they define a crucial threshold for continuously connected waters that enable migration by aquatic species. In the Pacific northwestern U.S., changes in atmospheric circulation have been found to alter rainfall patterns and result in decreased summer low-flows in the region. However, the impact of this climate dynamic on network connectivity is heretofore unstudied. Thus, we ask: How has connectivity in the riparian corridor changed in response to observed changes in climate? In this study we take the well-studied H.J. Andrews Experimental Forest as representative of mountain river networks in the Pacific northwestern U.S. First, we analyze 63 years of stream gauge information from a network of 11 gauges to document observed changes in timing and magnitude of stream discharge. We found declining magnitudes of seasonal low-flows and shifting seasonality of water export from the catchment, both of which we attribute to changes in precipitation timing and storage as snow vs. rainfall. Next, we use these discharge data to drive a reduced-complexity model of the river network to simulate network connectivity over 63 years. Model results show that network contraction (i.e., minimum network extent) has decreased over the past 63 years. Unexpectedly, the increasing winter peak flows did not correspond with increasing network expansion, suggesting a geologic control on maximum flowing network extent. We find dynamic expansion and contraction of the network primarily occurs during period of catchment discharge less than about 1 m3/s at the outlet, whereas the network extent is generally constant for discharges from 1 to 300 m3/s. Results of our study are of interest to scientists focused on connectivity as a control on ecological processes both directly (e.g., fish migration) and indirectly (e.g., stream temperature modeling). Additionally, our results inform management and regulatory needs such as estimating connectivity for entire river networks as a basis for regulation, and identifying the complexity of a shifting baseline in identifying a regulatory basis.

Hydro-geomorphological characterization and classification of Chilean river networks using horizontal, vertical and climatological properties

NASA Astrophysics Data System (ADS)

Pereira, A. A.; Gironas, J. A.; Passalacqua, P.; Mejia, A.; Niemann, J. D.

2017-12-01

Previous work has shown that lithological, tectonic and climatic processes have a major influence in shaping the geomorphology of river networks. Accordingly, quantitative classification methods have been developed to identify and characterize network types (dendritic, parallel, pinnate, rectangular and trellis) based solely on the self-affinity of their planform properties, computed from available Digital Elevation Model (DEM) data. In contrast, this research aim is to include both horizontal and vertical properties to evaluate a quantitative classification method for river networks. We include vertical properties to consider the unique surficial conditions (e.g., large and steep height drops, volcanic activity, and complexity of stream networks) of the Andes Mountains. Furthermore, the goal of the research is also to explain the implications and possible relations between the hydro-geomorphological properties and climatic conditions. The classification method is applied to 42 basins in the southern Andes in Chile, ranging in size from 208 Km2 to 8,000 Km2. The planform metrics include the incremental drainage area, stream course irregularity and junction angles, while the vertical metrics include the hypsometric curve and the slope-area relationship. We introduce new network structures (Brush, Funnel and Low Sinuosity Rectangular), possibly unique to the Andes, that can be quantitatively differentiated from previous networks identified in other geographic regions. Then, this research evaluates the effect that excluding different Strahler order streams has on the horizontal properties and therefore in the classification. We found that climatic conditions are not only linked to horizontal parameters, but also to vertical ones, finding significant correlation between climatic variables (average near-surface temperature and rainfall) and vertical measures (parameters associated with the hypsometric curve and slope-area relation). The proposed classification shows differences among basins previously classified as the same type, which are not noticeable in their horizontal properties and helps reduce misclassifications within the old clusters. Additional hydro-geomorphological metrics are to be considered in the classification method to improve the effectiveness of it.

An Artificial Neural Network-Based Ionospheric Model to Predict NmF2 and hmF2 Using Long-Term Data Set of FORMOSAT-3/COSMIC Radio Occultation Observations: Preliminary Results

NASA Astrophysics Data System (ADS)

Sai Gowtam, V.; Tulasi Ram, S.

2017-11-01

Artificial Neural Networks (ANNs) are known to be capable of solving linear as well as highly nonlinear problems. Using the long-term and high-quality data set of Formosa Satellite-3/Constellation Observing System for Meteorology, Ionosphere, and Climate (FORMOSAT-3/COSMIC, in short F3/C) from 2006 to 2015, an ANN-based two-dimensional (2-D) Ionospheric Model (ANNIM) is developed to predict the ionospheric peak parameters, such as NmF2 and hmF2. In this pilot study, the ANNIM results are compared with the original F3/C data, GRACE (Gravity Recovery and Climate Experiment) observations as well as International Reference Ionosphere (IRI)-2016 model to assess the learning efficiency of the neural networks used in the model. The ANNIM could well predict the NmF2 (hmF2) values with RMS errors of 1.87 × 105 el/cm3 (27.9 km) with respect to actual F3/C; and 2.98 × 105 el/cm3 (40.18 km) with respect to independent GRACE data. Further, the ANNIM predictions found to be as good as IRI-2016 model with a slightly smaller RMS error when compared to independent GRACE data. The ANNIM has successfully reproduced the local time, latitude, longitude, and seasonal variations with errors ranging 15-25% for NmF2 and 10-15% for hmF2 compared to actual F3/C data, except the postsunset enhancement in hmF2. Further, the ANNIM has also captured the global-scale ionospheric phenomena such as ionospheric annual anomaly, Weddell Sea Anomaly, and the midlatitude summer nighttime anomaly. Compared to IRI-2016 model, the ANNIM is found to have better represented the fine longitudinal structures and the midlatitude summer nighttime enhancements in both the hemispheres.

Benchmarking homogenization algorithms for monthly data

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

2012-01-01

The COST (European Cooperation in Science and Technology) Action ES0601: advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random independent break-type inhomogeneities with normally distributed breakpoint sizes were added to the simulated datasets. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study. After the deadline at which details of the imposed inhomogeneities were revealed, 22 additional solutions were submitted. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training the users on homogenization software was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that automatic algorithms can perform as well as manual ones.

Benchmarking monthly homogenization algorithms

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratianni, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.

2011-08-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies and because they represent two important types of statistics (additive and multiplicative). The algorithms were validated against a realistic benchmark dataset. The benchmark contains real inhomogeneous data as well as simulated data with inserted inhomogeneities. Random break-type inhomogeneities were added to the simulated datasets modeled as a Poisson process with normally distributed breakpoint sizes. To approximate real world conditions, breaks were introduced that occur simultaneously in multiple station series within a simulated network of station data. The simulated time series also contained outliers, missing data periods and local station trends. Further, a stochastic nonlinear global (network-wide) trend was added. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including (i) the centered root mean square error relative to the true homogeneous value at various averaging scales, (ii) the error in linear trend estimates and (iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Contingency scores by themselves are not very informative. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Training was found to be very important. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.

Network analysis reveals strongly localized impacts of El Niño

NASA Astrophysics Data System (ADS)

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-01

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network “in”-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Network analysis reveals strongly localized impacts of El Niño.

PubMed

Fan, Jingfang; Meng, Jun; Ashkenazy, Yosef; Havlin, Shlomo; Schellnhuber, Hans Joachim

2017-07-18

Climatic conditions influence the culture and economy of societies and the performance of economies. Specifically, El Niño as an extreme climate event is known to have notable effects on health, agriculture, industry, and conflict. Here, we construct directed and weighted climate networks based on near-surface air temperature to investigate the global impacts of El Niño and La Niña. We find that regions that are characterized by higher positive/negative network "in"-weighted links are exhibiting stronger correlations with the El Niño basin and are warmer/cooler during El Niño/La Niña periods. In contrast to non-El Niño periods, these stronger in-weighted activities are found to be concentrated in very localized areas, whereas a large fraction of the globe is not influenced by the events. The regions of localized activity vary from one El Niño (La Niña) event to another; still, some El Niño (La Niña) events are more similar to each other. We quantify this similarity using network community structure. The results and methodology reported here may be used to improve the understanding and prediction of El Niño/La Niña events and also may be applied in the investigation of other climate variables.

Assessing the Climate Resilience of Transport Infrastructure Investments in Tanzania

NASA Astrophysics Data System (ADS)

Hall, J. W.; Pant, R.; Koks, E.; Thacker, S.; Russell, T.

2017-12-01

Whilst there is an urgent need for infrastructure investment in developing countries, there is a risk that poorly planned and built infrastructure will introduce new vulnerabilities. As climate change increases the magnitudes and frequency of natural hazard events, incidence of disruptive infrastructure failures are likely to become more frequent. Therefore, it is important that infrastructure planning and investment is underpinned by climate risk assessment that can inform adaptation planning. Tanzania's rapid economic growth is placing considerable strain on the country's transportation infrastructure (roads, railways, shipping and aviation); especially at the port of Dar es Salaam and its linking transport corridors. A growing number of natural hazard events, in particular flooding, are impacting the reliability of this already over-used network. Here we report on new methodology to analyse vulnerabilities and risks due to failures of key locations in the intermodal transport network of Tanzania, including strategic connectivity to neighboring countries. To perform the national-scale risk analysis we will utilize a system-of-systems methodology. The main components of this general risk assessment, when applied to transportation systems, include: (1) Assembling data on: spatially coherent extreme hazards and intermodal transportation networks; (2) Intersecting hazards with transport network models to initiate failure conditions that trigger failure propagation across interdependent networks; (3) Quantifying failure outcomes in terms of social impacts (customers/passengers disrupted) and/or macroeconomic consequences (across multiple sectors); and (4) Simulating, testing and collecting multiple failure scenarios to perform an exhaustive risk assessment in terms of probabilities and consequences. The methodology is being used to pinpoint vulnerability and reduce climate risks to transport infrastructure investments.

Upper Colorado River Basin Climate Effects Network

USGS Publications Warehouse

Belnap, Jayne; Campbell, Donald; Kershner, Jeff

2011-01-01

The Upper Colorado River Basin (UCRB) Climate Effects Network (CEN) is a science team established to provide information to assist land managers in future decision making processes by providing a better understanding of how future climate change, land use, invasive species, altered fire cycles, human systems, and the interactions among these factors will affect ecosystems and the services they provide to human communities. The goals of this group are to (1) identify science needs and provide tools to assist land managers in addressing these needs, (2) provide a Web site where users can access information pertinent to this region, and (3) provide managers technical assistance when needed. Answers to the team's working science questions are intended to address how interactions among climate change, land use, and management practices may affect key aspects of water availability, ecosystem changes, and societal needs within the UCRB.

The strength of strategically placed in situ networks: The Critical Zone Observatory Program (Invited)

NASA Astrophysics Data System (ADS)

Bauer, S.; Benisch, K.; Li, D.; Beyer, C.; Mitiku, A. B.; Graupner, B.

2011-12-01

The Critical Zone Observatory (CZO) program, initiated by the U.S. National Science Foundation in 2007 with 3 sites, was expanded to 6 sites in 2009 and is expected to grow to at least 8 sites in FY 2014. The CZO program is now maturing into a coordinated network that enables scientific research around terrestrial fluxes of water, carbon and nutrients and informs societal questions around resource management and adaptation to climate change. Individual CZOs have contributed to understanding of the influences of disturbances and of changes in climate on fluxes and stores in critical ecosystems, and to a better predictive ability. CZOs have enabled the disciplinary integration needed to consider controlling processes together, from bedrock to boundary layer, and over sub-daily to millennial or longer times. Together, the CZO network has shown the role of climate versus disturbance on rain, snowfall and snowmelt reaching the ground surface, and the influences of climate, disturbance and regolith properties on partitioning of infiltrated water into evapotranspiration versus streamflow. The influence of disturbance is manifest both through abiotic factors, e.g. boundary-layer meteorology and turbulence, and through biotic influences, e.g. changes in vegetation density due to fire or disease, and thus interception and evapotranspiration. Climatic influences are overlain on this, including i) changes in rain versus snowfall and thus snowpack and soil-water storage, and ii) growing season and thus evapotranspiration. Carbon and nutrient fluxes are closely linked to those of water. Thus rich data sets and improved models from the CZO sites together provide a better understanding of the bi-directional feedbacks between vegetation structure, regolith properties and climate. Going forward, the CZO network as a whole offers well-instrumented sites with many common measurements and multi-disciplinary data across gradient of climate, parent material, vegetation structure and regolith properties. Measurements are at scales that are sufficiently large for research involving water, carbon or nutrient balances. Results are relevant to help guide decisions around vegetation management, and to understand the water, carbon and nutrient implications of vegetation-management options. The CZO network is a community platform for research, with the common, long-term observations across the multiple sites a resource available to all for multi-disciplinary critical-zone science.

The strength of strategically placed in situ networks: The Critical Zone Observatory Program (Invited)

NASA Astrophysics Data System (ADS)

Bales, R. C.; Brooks, P. D.; Molotch, N. P.

2013-12-01

The Critical Zone Observatory (CZO) program, initiated by the U.S. National Science Foundation in 2007 with 3 sites, was expanded to 6 sites in 2009 and is expected to grow to at least 8 sites in FY 2014. The CZO program is now maturing into a coordinated network that enables scientific research around terrestrial fluxes of water, carbon and nutrients and informs societal questions around resource management and adaptation to climate change. Individual CZOs have contributed to understanding of the influences of disturbances and of changes in climate on fluxes and stores in critical ecosystems, and to a better predictive ability. CZOs have enabled the disciplinary integration needed to consider controlling processes together, from bedrock to boundary layer, and over sub-daily to millennial or longer times. Together, the CZO network has shown the role of climate versus disturbance on rain, snowfall and snowmelt reaching the ground surface, and the influences of climate, disturbance and regolith properties on partitioning of infiltrated water into evapotranspiration versus streamflow. The influence of disturbance is manifest both through abiotic factors, e.g. boundary-layer meteorology and turbulence, and through biotic influences, e.g. changes in vegetation density due to fire or disease, and thus interception and evapotranspiration. Climatic influences are overlain on this, including i) changes in rain versus snowfall and thus snowpack and soil-water storage, and ii) growing season and thus evapotranspiration. Carbon and nutrient fluxes are closely linked to those of water. Thus rich data sets and improved models from the CZO sites together provide a better understanding of the bi-directional feedbacks between vegetation structure, regolith properties and climate. Going forward, the CZO network as a whole offers well-instrumented sites with many common measurements and multi-disciplinary data across gradient of climate, parent material, vegetation structure and regolith properties. Measurements are at scales that are sufficiently large for research involving water, carbon or nutrient balances. Results are relevant to help guide decisions around vegetation management, and to understand the water, carbon and nutrient implications of vegetation-management options. The CZO network is a community platform for research, with the common, long-term observations across the multiple sites a resource available to all for multi-disciplinary critical-zone science.

The Modulated Annual Cycle: An Alternative Reference Frame for Climate Anomalies

NASA Astrophysics Data System (ADS)

Wu, Z.

2007-12-01

In climate science, an anomaly is the deviation of a quantity from its annual cycle (AC). There are many ways to define annual cycle. Traditionally, the annual cycle is taken to be an exact repetition of itself year after year. This stationary annual cycle may not reflect well the intrinsic nonlinearity of the climate system, especially under external forcing. In this study, we have reexamined the reference frame for anomalies by reexamining the annual cycle. We propose an alternative reference frame, the modulated annual cycle (MAC) that allows the annual cycle to change from year to year, for defining anomalies. In order for this alternative reference frame to be useful, we need to be able to define the instantaneous annual cycle. We therefore also introduce a new method to extract the MAC from climatic data. In the presence of an MAC, modulated in both amplitude and frequency, we can then define an alternative version of an anomaly, this time with respect to the instantaneous MAC rather than a permanent and unchanging AC. Based on this alternative definition of anomalies, we reexamine some familiar physical processes: in particular, the sea surface temperature (SST) reemergence and the ENSO phase locking to the annual cycle. We find that the re-emergence mechanism may be alternatively interpreted as an explanation of the change of the annual cycle instead of the interannual to interdecadal persistence of SST anomalies. We also find that the ENSO phase locking can largely be attributed to the residual annual cycle (the difference of the MAC and the corresponding traditional annual cycle) contained in the traditional anomaly, and, therefore, can be alternatively interpreted as a part of the annual cycle phase locked to the annual cycle itself. Two additional examples are also presented of the implications of using a MAC against which to define anomalies. We show that using MAC as a reference framework for anomaly can bypass the difficulty brought by concepts such as "decadal variability of summer (or winter) climate" for understanding the low-frequency variability of the climate system. We also point out the drawbacks related to the stationary assumption in previous studies of extreme weather and climate and propose instead the appropriateness of choosing a non-stationary framework to study extreme weather and climate events. The concept of an amplitude and frequency modulated annual cycle, a method to extract it, and its implications for the interpretation of physical processes, all may contribute potentially to a more consistent and fruitful way of examining past and future climate variability and change.

10 CFR 300.1 - General.

Code of Federal Regulations, 2014 CFR

2014-01-01

... CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.1 General. (a) Purpose... under the Climate Leaders or Climate VISION programs to reduce its entity-wide emissions relative to a... (incorporated by reference, see § 300.13) and base its registered reductions on an assessment of annual changes...

10 CFR 300.1 - General.

Code of Federal Regulations, 2012 CFR

2012-01-01

... CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.1 General. (a) Purpose... under the Climate Leaders or Climate VISION programs to reduce its entity-wide emissions relative to a... (incorporated by reference, see § 300.13) and base its registered reductions on an assessment of annual changes...

10 CFR 300.1 - General.

Code of Federal Regulations, 2013 CFR

2013-01-01

... CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.1 General. (a) Purpose... under the Climate Leaders or Climate VISION programs to reduce its entity-wide emissions relative to a... (incorporated by reference, see § 300.13) and base its registered reductions on an assessment of annual changes...

10 CFR 300.1 - General.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.1 General. (a) Purpose... under the Climate Leaders or Climate VISION programs to reduce its entity-wide emissions relative to a... (incorporated by reference, see § 300.13) and base its registered reductions on an assessment of annual changes...

10 CFR 300.1 - General.

Code of Federal Regulations, 2010 CFR

2010-01-01

... CLIMATE CHANGE VOLUNTARY GREENHOUSE GAS REPORTING PROGRAM: GENERAL GUIDELINES § 300.1 General. (a) Purpose... under the Climate Leaders or Climate VISION programs to reduce its entity-wide emissions relative to a... (incorporated by reference, see § 300.13) and base its registered reductions on an assessment of annual changes...

A Planning Guide for Instructional Networks, Part II.

ERIC Educational Resources Information Center

Daly, Kevin F.

1994-01-01

This second in a series of articles on planning for instructional computer networks focuses on site preparation, installation, service, and support. Highlights include an implementation schedule; classroom and computer lab layouts; electrical power needs; workstations; network cable; telephones; furniture; climate control; and security. (LRW)

Compilation of climate data from heterogeneous networks across the Hawaiian Islands

Treesearch

Ryan J. Longman; Thomas W. Giambelluca; Michael A. Nullet; Abby G. Frazier; Kevin Kodama; Shelley D. Crausbay; Paul D. Krushelnycky; Susan Cordell; Martyn P. Clark; Andy J. Newman; Jeffrey R. Arnold

2018-01-01

Long-term, accurate observations of atmospheric phenomena are essential for a myriad of applications, including historic and future climate assessments, resource management, and infrastructure planning. In Hawai‘i, climate data are available from individual researchers, local, State, and Federal agencies, and from large electronic repositories such as the National...

Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

USDA-ARS?s Scientific Manuscript database

Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

Climateurope: a network to support Europe's research and innovation activities in the fields of Earth-System modeling and climate services

NASA Astrophysics Data System (ADS)

Bessembinder, Janette; Kotova, Lola; Manez, Maria; Jacob, Daniela; Hewitt, Chris; Garrett, Natalie; Monfray, Patrick; Doescher, Ralf; Doblas Reyes, Francisco; Joussaume, Sylvie; Toumi, Ralf; Buonocore, Mauro; Gualdi, Silvio; Nickovic, Slobodan

2017-04-01

Changes in the climate are affecting many sectors but the audience of decision- and policy-makers is so wide and varied that the requirements from each application can be quite different. There are a growing number of initiatives at the international and European level, from research networks of data providers, operational services, impact assessments, to coordination of government initiatives and provision of policy relevant recommendations; all provided on a wide range of timescales. The landscape of activities is very diverse. Users and providers of climate information currently face significant challenges in understanding this complex landscape. If we are to maximize the benefits of the investments and provide European citizens with the information and technology to develop a climate-smart society, then a mechanism is needed to coordinate the impressive and varied research and innovation effort. The overall concept behind the EU-project Climateurope is to create and manage a framework to coordinate, integrate and support Europe's research and innovation activities in the fields of Earth-System modeling and climate services. The purpose of this concept is to create greater social and economic value for Europe through improved preparation for, and management of, climate-related risks and opportunities arising from making European world-class knowledge more useable and thus more applicable to policy- and decision-making. This value will be felt by a range of actors including the public sector, governments, business and industry. Climateurope will provide a comprehensive overview of all the relevant activities to ensure the society at large can take full advantage of the investment Europe is making in research and innovation and associated development of services. The Climateurope network will facilitate dialog among climate science communities, funding bodies, climate service providers and users. Through the communication and dissemination activities, Climateurope will establish multidisciplinary expert groups to access the state-of-the-art of Earth system modeling and climate services and will identify existing gaps, new challenges and emerging needs. During this presentation the activities and progress of the project (website, webinars, discussion platform, festivals, state-of-the-art report) will be presented shortly and we will indicate how interested people can join the network.

KNMI Data Centre: Easy access for all

NASA Astrophysics Data System (ADS)

van de Vegte, John; Som de Cerff, Wim; Plieger, Maarten; de Vreede, Ernst; Sluiter, Raymond; Willem Noteboom, Jan; van der Neut, Ian; Verhoef, Hans; van Versendaal, Robert; van Binnendijk, Martin; Kalle, Henk; Knopper, Arthur; Spit, Jasper; Mastop, Joeri; Klos, Olaf; Calis, Gijs; Ha, Siu-Siu; van Moosel, Wim; Klein Ikkink, Henk-Jan; Tosun, Tuncay

2013-04-01

KNMI is the Dutch institute for weather, climate research and seismology. It disseminates weather information to the public at large, the government, aviation and the shipping industry in the interest of safety, the economy and a sustainable environment. To gain insight into long-term developments KNMI conducts research on climate change. Making the knowledge, data and information on hand at KNMI accessible is one core activity. A huge part of the KNMI information is from numerical models, insitu sensor networks and remote sensing satellites. This digital collection is mostly internal only available and is a collection of non searchable , non standardized file formats, lacking documentation and has no references to scientific publications. With the KNMI Data Centre (KDC) project these issues are tackled. In the project a user driven development approach with SCRUM was chosen to get maximum user involvement in a relative short development timeframe. Building on open standards and proven open source technology (which includes in-house developed software like ADAGUC WMS and Portal) resulted in a first release in December 2012 This presentation will focus on the aspects of KDC relating to its technical challenges, the development strategy and the initial usage results of the data centre.

Envisioning the future of wildlife in a changing climate: Collaborative learning for adaptation planning

USGS Publications Warehouse

LeDee, Olivia E.; Karasov, W.H.; Martin, Karl J.; Meyer, Michael W.; Ribic, Christine; Van Deelen, Timothy R.

2011-01-01

Natural resource managers are tasked with assessing the impacts of climate change on conservation targets and developing adaptation strategies to meet agency goals. The complex, transboundary nature of climate change demands the collaboration of scientists, managers, and stakeholders in this effort. To share, integrate, and apply knowledge from these diverse perspectives, we must engage in social learning. In 2009, we initiated a process to engage university researchers and agency scientists and managers in collaborative learning to assess the impacts of climate change on terrestrial fauna in the state of Wisconsin, USA. We constructed conceptual Bayesian networks to depict the influence of climate change, key biotic and abiotic factors, and existing stressors on the distribution and abundance of 3 species: greater prairie-chicken (Tympanuchus cupido), wood frog (Lithobates sylvaticus), and Karner blue butterfly (Plebejus melissa samuelis). For each species, we completed a 2-stage expert review that elicited dialogue on information gaps, management opportunities, and research priorities. From our experience, collaborative network modeling proved to be a powerful tool to develop a common vision of the potential impacts of climate change on conservation targets.

Socioeconomic impacts of climate change on rural communities in the United States

Treesearch

Pankaj Lal; Janaki Alavalapati; D Evan Mercer

2011-01-01

Climate change refers to any distinct change in measures of climate such as temperature, rainfall, snow, or wind patterns lasting for decades or longer (USEPA 2009). In the last decade, there has been a clear consensus among scientists that the world is experiencing a rapid global climate change, much of it attributable to anthropogenic activities. The extent of...

76 FR 78601 - Endangered and Threatened Wildlife and Plants; 90-Day Finding on a Petition To List the Western...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-19

... climate change and provides several references about the effects of climate change in general to support this claim. The petition explains that human-induced climate change is causing global increases of...; Fagre 2005, p. 1; Hall and Fagre 2003, p. 139; Intergovernmental Panel on Climate Change (IPCC) 2007a, p...

Messages promoting genetic modification of crops in the context of climate change: Evidence for psychological reactance.

PubMed

Lu, Hang; McComas, Katherine A; Besley, John C

2017-01-01

Genetic modification (GM) of crops and climate change are arguably two of today's most challenging science communication issues. Increasingly, these two issues are connected in messages proposing GM as a viable option for ensuring global food security threatened by climate change. This study examines the effects of messages promoting the benefits of GM in the context of climate change. Further, it examines whether explicit reference to "climate change," or "global warming" in a GM message results in different effects than each other, or an implicit climate reference. An online sample of U.S. participants (N = 1050) were randomly assigned to one of four conditions: "climate change" cue, "global warming" cue, implicit cue, or control (no message). Generally speaking, framing GM crops as a way to help ensure global food security proved to be an effective messaging strategy in increasing positive attitudes toward GM. In addition, the implicit cue condition led to liberals having more positive attitudes and behavioral intentions toward GM than the "climate change" cue condition, an effect mediated by message evaluations. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

Northern protected areas will become important refuges for biodiversity tracking suitable climates.

PubMed

Berteaux, Dominique; Ricard, Marylène; St-Laurent, Martin-Hugues; Casajus, Nicolas; Périé, Catherine; Beauregard, Frieda; de Blois, Sylvie

2018-03-15

The Northern Biodiversity Paradox predicts that, despite its globally negative effects on biodiversity, climate change will increase biodiversity in northern regions where many species are limited by low temperatures. We assessed the potential impacts of climate change on the biodiversity of a northern network of 1,749 protected areas spread over >600,000 km 2 in Quebec, Canada. Using ecological niche modeling, we calculated potential changes in the probability of occurrence of 529 species to evaluate the potential impacts of climate change on (1) species gain, loss, turnover, and richness in protected areas, (2) representativity of protected areas, and (3) extent of species ranges located in protected areas. We predict a major species turnover over time, with 49% of total protected land area potentially experiencing a species turnover >80%. We also predict increases in regional species richness, representativity of protected areas, and species protection provided by protected areas. Although we did not model the likelihood of species colonising habitats that become suitable as a result of climate change, northern protected areas should ultimately become important refuges for species tracking climate northward. This is the first study to examine in such details the potential effects of climate change on a northern protected area network.

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

Networking DEC and IBM computers

NASA Technical Reports Server (NTRS)

Mish, W. H.

1983-01-01

Local Area Networking of DEC and IBM computers within the structure of the ISO-OSI Seven Layer Reference Model at a raw signaling speed of 1 Mops or greater are discussed. After an introduction to the ISO-OSI Reference Model nd the IEEE-802 Draft Standard for Local Area Networks (LANs), there follows a detailed discussion and comparison of the products available from a variety of manufactures to perform this networking task. A summary of these products is presented in a table.

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.

Future global SLR network evolution and its impact on the terrestrial reference frame

NASA Astrophysics Data System (ADS)

Kehm, Alexander; Bloßfeld, Mathis; Pavlis, Erricos C.; Seitz, Florian

2018-06-01

Satellite laser ranging (SLR) is an important technique that contributes to the determination of terrestrial geodetic reference frames, especially to the realization of the origin and the scale of global networks. One of the major limiting factors of SLR-derived reference frame realizations is the datum accuracy which significantly suffers from the current global SLR station distribution. In this paper, the impact of a potential future development of the SLR network on the estimated datum parameters is investigated. The current status of the SLR network is compared to a simulated potential future network featuring additional stations improving the global network geometry. In addition, possible technical advancements resulting in a higher amount of observations are taken into account as well. As a result, we find that the network improvement causes a decrease in the scatter of the network translation parameters of up to 24%, and up to 20% for the scale, whereas the technological improvement causes a reduction in the scatter of up to 27% for the translations and up to 49% for the scale. The Earth orientation parameters benefit by up to 15% from both effects.

The Tribal Lands Collaboratory: Building partnerships and developing tools to support local Tribal community response to climate change.

NASA Astrophysics Data System (ADS)

Jones, K. D.; Wee, B.; Kuslikis, A.

2015-12-01

Response of Tribal nations and Tribal communities to current and emerging climate change challenges requires active participation of stakeholders who have effective access to relevant data, information and analytical tools. The Tribal Lands Collaboratory (TLC), currently under development, is a joint effort between the American Indian Higher Education Consortium (AIHEC), the Environmental Systems Research Institute (Esri), and the National Ecological Observatory Network (NEON). The vision of the TLC is to create an integrative platform that enables coordination between multiple stakeholders (e.g. Tribal resource managers, Tribal College faculty and students, farmers, ranchers, and other local community members) to collaborate on locally relevant climate change issues. The TLC is intended to facilitate the transformation of data into actionable information that can inform local climate response planning. The TLC will provide the technical mechanisms to access, collect and analyze data from both internal and external sources (e.g. NASA's Giovanni climate data portal, Ameriflux or USA National Phenology Network) while also providing the social scaffolds to enable collaboration across Tribal communities and with members of the national climate change research community. The prototype project focuses on phenology, a branch of science focused on relationships between climate and the seasonal timing of biological phenomena. Monitoring changes in the timing and duration of phenological stages in plant and animal co­­­­mmunities on Tribal lands can provide insight to the direct impacts of climate change on culturally and economically significant Tribal resources . The project will leverage existing phenological observation protocols created by the USA-National Phenology Network and NEON to direct data collection efforts and will be tailored to the specific needs and concerns of the community. Phenology observations will be captured and managed within the Collaboratory environment where these data may then be correlated with regional climate data to investigate interactions between large-scale environmental changes and local impacts. Esri's Story Maps is a candidate mechanism for sharing of those findings among Tribal stakeholders.

Spatial relationship between climatic diversity and biodiversity conservation value.

PubMed

Wang, Junjun; Wu, Ruidong; He, Daming; Yang, Feiling; Hu, Peijun; Lin, Shiwei; Wu, Wei; Diao, Yixin; Guo, Yang

2018-06-04

Capturing the full range of climatic diversity in a reserve network is expected to improve the resilience of biodiversity to climate change. Therefore, a study on systematic conservation planning for climatic diversity that explicitly or implicitly hypothesizes that regions with higher climatic diversity will support greater biodiversity is needed. However, little is known about the extent and generality of this hypothesis. This study utilized the case of Yunnan, southwest China, to quantitatively classify climatic units and modeled 4 climatic diversity indicators, including the variety of climatic units (VCU), rarity of climatic units (RCU), endemism of climatic units (ECU) and a composite index of climatic units (CICD). We used 5 reliable priority conservation area (PCA) schemes to represent the areas with high biodiversity conservation value. We then investigated the spatial relationships between the 4 climatic diversity indicators and the 5 PCA schemes and assessed the representation of climatic diversity within the existing nature reserves. The CICD exhibited the best performance for indicating high conservation value areas, followed by the ECU and RCU. However, contrary to conventional knowledge, VCU did not show a positive association with biodiversity conservation value. The rarer or more endemic climatic units tended to have higher reserve coverage than the more common units. However, only 28 units covering 10.5% of the land in Yunnan had more than 17% of their areas protected. In addition to climatic factors, topography and human disturbances also significantly affected the relationship between climatic diversity and biodiversity conservation value. This analysis suggests that climatic diversity can be an effective surrogate for establishing a more robust reserve network under climate change in Yunnan. Our study improves the understanding of the relationship between climatic diversity and biodiversity and helps build an evidence-based foundation for systematic conservation planning that targets climatic diversity in response to climate change. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Climate change communication through networks and partnerships: A successful model of engaging and educating non-specialist audience in India

NASA Astrophysics Data System (ADS)

Choudhary, S.; Nayak, R.; Gore, A.

2013-12-01

There is an overwhelming international scientific consensus on climate change; however, the global community still lacks the resolve to implement meaningful solutions. No meaningful solutions can be found without educating and engaging non-scientific community in addressing the climate change. With more than 41 percent of world's population falling under 10-34 years age group, the future citizens, inspiring them is a great challenge for the climate scientists. In order to educate the youth and students in India, a model program named 'Climeducate' was created with the help of scientists in Indian Polar Research Network (IPRN), trained climate leaders in ';The Climate Reality Project', and a local organization (Planature Consultancy Services). This model was developed keeping in mind the obstacles that may be faced in reaching out to non-specialist audiences in different parts of India. The identified obstacles were 1- making such a presentation that could reveal the truth about the climate crisis in a way that ignites the moral courage in non-specialist audience 2- lack of funding for travel and boarding expenses of a climate communicator, 3- language barrier in educating local audiences, 4- logistical arrangements at the venue. In this presentation we will share how all the four obstacles were overcome. Audiences were also given short questionnaires before and after the presentation. Remarkable changes in the pattern of answers, data would be shared in the presentation, were observed between the two questionnaires. More importantly, a significant difference in audience engagement was observed comparing a presentation that integrated scientific data with audiovisuals prepared by The Climate Reality Project Chairman, Al Gore (also Former US Vice President) and the other using simple PowerPoint slides. With the success of this program which was implemented among 500 audiences in the eastern India, we aim to replicate this program soon in other parts of India. This presentation will outline how scientific story telling through an effective collaboration of network of scientists, climate mentors, school teachers and local organizations would derive significant results in inspiring, engaging and preparing non-specialists audiences to face the realities of climate change.

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…

Climate Change Adaptation Act : report of the Committee on Commerce, Science, and Transportation on S. 2355

DOT National Transportation Integrated Search

2008-06-05

The Committee on Commerce, Science, and Transportation, to which was referred the bill (S. 2355) to amend the National Climate Program Act to enhance the ability of the United States to : develop and implement climate change adaptation programs and p...

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

Paleoclimate networks: a concept meeting central challenges in the reconstruction of paleoclimate dynamics

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Goswami, Bedartha; Marwan, Norbert; Breitenbach, Sebastian; Kurths, Jürgen

2013-04-01

Statistical analysis of dependencies amongst paleoclimate data helps to infer on the climatic processes they reflect. Three key challenges have to be addressed, however: the datasets are heterogeneous in time (i) and space (ii), and furthermore time itself is a variable that needs to be reconstructed, which (iii) introduces additional uncertainties. To address these issues in a flexible way we developed the paleoclimate network framework, inspired by the increasing application of complex networks in climate research. Nodes in the paleoclimate network represent a paleoclimate archive, and an associated time series. Links between these nodes are assigned, if these time series are significantly similar. Therefore, the base of the paleoclimate network is formed by linear and nonlinear estimators for Pearson correlation, mutual information and event synchronization, which quantify similarity from irregularly sampled time series. Age uncertainties are propagated into the final network analysis using time series ensembles which reflect the uncertainty. We discuss how spatial heterogeneity influences the results obtained from network measures, and demonstrate the power of the approach by inferring teleconnection variability of the Asian summer monsoon for the past 1000 years.

Geocode of River Networks in Global Plateaus

NASA Astrophysics Data System (ADS)

Ni, J.; Wang, Y.; Wang, T.

2017-12-01

As typical hierarchical systems, river networks are of great significance to aquatic organisms and its diversity. Different aspects of river networks have been investigated in previous studies such as network structure, formation cause, material transport, nutrient cycle and habitat variation. Nevertheless, river networks function as biological habitat is far from satisfactory in plateau areas. This paper presents a hierarchical method for habitat characterization of plateau river networks with the geocode extracted from abiotic factors including historical geologic period, climate zone, water source and geomorphic process at different spatial scales. As results, characteristics of biological response with vertical differentiation within typical plateau river networks are elucidated. Altitude, climate and landform are of great influence to habitat and thereby structure of aquatic community, while diverse water source and exogenic action would influence biological abundance or spatiotemporal distribution. Case studies are made in the main stream of the Yellow River and the Yangtze River, respectively extended to the river source to Qinghai-Tibet Plateau, which demonstrate high potentials for decision making support to river protection, ecological rehabilitation and sustainable management of river ecosystems.

Delta-Flux: An eddy covariance network for a climate-smart Lower Mississippi Basin

USGS Publications Warehouse

Runkle, Benjamin R. K.; Rigby, James R.; Reba, Michele L.; Anapalli, Saseendran S.; Bhattacharjee, Joydeep; Krauss, Ken W.; Liang, Lu; Locke, Martin A.; Novick, Kimberly A.; Sui, Ruixiu; Suvočarev, Kosana; White, Paul M.

2017-01-01

Networks of remotely monitored research sites are increasingly the tool used to study regional agricultural impacts on carbon and water fluxes. However, key national networks such as the National Ecological Observatory Network and AmeriFlux lack contributions from the Lower Mississippi River Basin (LMRB), a highly productive agricultural area with opportunities for soil carbon sequestration through conservation practices. The authors describe the rationale to create the new Delta-Flux network, which will coordinate efforts to quantify carbon and water budgets at seventeen eddy covariance flux tower sites in the LMRB. The network structure will facilitate climate-smart management strategies based on production-scale and continuous measurements of carbon and water fluxes from the landscape to the atmosphere under different soil and water management conditions. The seventeen instrumented field sites are expected to monitor fluxes within the most characteristic landscapes of the target area: row-crop fields, pasture, grasslands, forests, and marshes. The network participants are committed to open collaboration and efficient regionalization of site-level findings to support sustainable agricultural and forestry management and conservation of natural resources.

The Swedish Regional Climate Modelling Programme, SWECLIM: a review.

PubMed

Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael

2004-06-01

The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.

Actual evapotranspiration for a reference crop within measured and future changing climate periods in the Mediterranean region

NASA Astrophysics Data System (ADS)

Katerji, Nader; Rana, Gianfranco; Ferrara, Rossana Monica

2017-08-01

The study compares two formulas for calculating the daily evapotranspiration ET0 for a reference crop. The first formula was proposed by Allen et al. (AL), while the second one was proposed by Katerji and Perrier with the addition of the carbon dioxide (CO2) effect on evapotranspiration (KP). The study analyses the impact of the calculation by the two formulas on the irrigation requirement (IR). Both formulas are based on the Penman-Monteith equation but adopt different approaches for parameterising the canopy resistance r c . In the AL formula, r c is assumed constant and not sensitive to climate change, whereas in the KP formula, r c is first parameterised as a function of climatic variables, then ET0 is corrected for the air CO2 concentration. The two formulas were compared in two periods. The first period involves data from two sites in the Mediterranean region within a measured climate change period (1981-2006) when all the input climatic variables were measured. The second period (2070-2100) involves data from a future climate change period at one site when the input climatic variables were forecasted for two future climate scenarios (A2 and B2). The annual cumulated values of ET0 calculated by the AL formula are systematically lower than those determined by the KP formula. The differences between the ET0 estimation with the AL and KP formulas have a strong impact on the determination of the IR for the reference crop. In fact, for the two periods, the annual values of IR when ET0 is calculated by the AL formula are systematically lower than those calculated by the KP formula. For the actual measured climate change period, this reduction varied from 26 to 28 %, while for the future climate change period, it varied based on the scenario from 16 % (A2) to 20 % (B2).

Late Noachian Icy Highlands climate model: Exploring the possibility of transient melting and fluvial/lacustrine activity through peak annual and seasonal temperatures

NASA Astrophysics Data System (ADS)

Palumbo, Ashley M.; Head, James W.; Wordsworth, Robin D.

2018-01-01

The nature of the Late Noachian climate of Mars remains one of the outstanding questions in the study of the evolution of martian geology and climate. Despite abundant evidence for flowing water (valley networks and open/closed basin lakes), climate models have had difficulties reproducing mean annual surface temperatures (MAT) > 273 K in order to generate the ;warm and wet; climate conditions presumed to be necessary to explain the observed fluvial and lacustrine features. Here, we consider a ;cold and icy; climate scenario, characterized by MAT ∼225 K and snow and ice distributed in the southern highlands, and ask: Does the formation of the fluvial and lacustrine features require continuous ;warm and wet; conditions, or could seasonal temperature variation in a ;cold and icy; climate produce sufficient summertime ice melting and surface runoff to account for the observed features? To address this question, we employ the 3D Laboratoire de Météorologie Dynamique global climate model (LMD GCM) for early Mars and (1) analyze peak annual temperature (PAT) maps to determine where on Mars temperatures exceed freezing in the summer season, (2) produce temperature time series at three valley network systems and compare the duration of the time during which temperatures exceed freezing with seasonal temperature variations in the Antarctic McMurdo Dry Valleys (MDV) where similar fluvial and lacustrine features are observed, and (3) perform a positive-degree-day analysis to determine the annual volume of meltwater produced through this mechanism, estimate the necessary duration that this process must repeat to produce sufficient meltwater for valley network formation, and estimate whether runoff rates predicted by this mechanism are comparable to those required to form the observed geomorphology of the valley networks. When considering an ambient CO2 atmosphere, characterized by MAT ∼225 K, we find that: (1) PAT can exceed the melting point of water (>273 K) in topographic lows, such as the northern lowlands and basin floors, and small regions near the equator during peak summer season conditions, despite the much lower MAT; (2) Correlation of PAT > 273 K with the predicted distribution of surface snow and ice shows that melting could occur near the edges of the ice sheet in near-equatorial regions where valley networks are abundant; (3) For the case of a circular orbit, the duration of temperatures >273 K at specific valley network locations suggests that yearly meltwater generation is insufficient to carve the observed fluvial and lacustrine features when compared with the percentage of the year required to sustain similar features in the MDV; (4) For the case of a more eccentric orbit (eccentricity of 0.17), the duration of temperatures >273 K at specific valley network locations suggests that annual meltwater generation may be capable of producing sufficient meltwater for valley network formation when repeated for many years; (5) When considering a slightly warmer climate scenario and a circular orbit, characterized by MAT ∼243 K, we find that this small amount of additional greenhouse warming (∼18 K MAT increase) produces time durations of temperatures >273 K that are similar to those observed in the MDV. Thus, we suggest that peak daytime and seasonal temperatures exceeding 273 K could form the valley networks and lakes with either a relatively high eccentricity condition or a small amount of additional atmospheric warming, rather than the need for a sustained MAT at or above 273 K. The results from our positive-degree-day analysis suggest that: (1) For the conditions of 25° obliquity, 600 mbar atmosphere, and eccentricity of 0.17, this seasonal melting process would be required to continue for ∼(33-1083) × 103 years to produce a sufficient volume of meltwater to form the valley networks and lakes; (2) Similarly, for the conditions of 25° obliquity, 1000 mbar atmosphere, circular orbit, and ∼18 K additional greenhouse warming, the process would be required to continue for ∼(21-550) × 103 years. Therefore, peak seasonal melting of snow and ice could induce the generation of meltwater and fluvial and lacustrine activity in a ;cold and icy; Late Noachian climate in a manner similar to that observed in the MDV. A potential shortcoming of this mechanism is that independent estimates of the required runoff rates for valley network formation are much higher than those predicted by this mechanism when considering a circular orbit, even when accounting for additional atmospheric warming. However, we consider that a relatively higher eccentricity condition (0.17) may produce the necessary runoff rates: for the perihelion scenario in which perihelion occurs during southern hemispheric summer, intense melting will occur in the near-equatorial regions and in the southern hemisphere, producing runoff rates comparable to those required for valley network formation (∼mm/day). In the opposite perihelion scenario, the southern hemisphere will experience very little summertime melting. Thus, this seasonal melting mechanism is a strong candidate for formation of the valley networks when considering a relatively high eccentricity (0.17) because this mechanism is capable of (1) producing meltwater in the equatorial region where valley networks are abundant, (2) continuously producing seasonal meltwater for the estimated time duration of valley network formation, (3) yielding the amount of meltwater necessary to incise the valley networks within this time period, and (4) by considering a perihelion scenario in which half of the duration of valley network formation is spent with peak summertime conditions during perihelion in each hemisphere, higher runoff rates are produced than in a circular orbit and the rates may be comparable to those required for valley network formation.

The worldwide airline network and the dispersal of exotic species: 2007–2010

PubMed Central

Tatem, Andrew J

2009-01-01

International air travel has played a significant role in driving recent increases in the rates of biological invasion and spread of infectious diseases. By providing high speed, busy transport links between spatially distant, but climatically similar regions of the world, the worldwide airline network (WAN) increases the risks of deliberate or accidental movements and establishment of climatically sensitive exotic organisms. With traffic levels continuing to rise and climates changing regionally, these risks will vary, both seasonally and year-by-year. Here, detailed estimates of air traffic trends and climate changes for the period 2007–2010 are used to examine the likely directions and magnitudes of changes in climatically sensitive organism invasion risk across the WAN. Analysis of over 144 million flights from 2007–2010 shows that by 2010, the WAN is likely to change little overall in terms of connecting regions with similar climates, but anticipated increases in traffic and local variations in climatic changes should increase the risks of exotic species movement on the WAN and establishment in new areas. These overall shifts mask spatially and temporally heterogenous changes across the WAN, where, for example, traffic increases and climatic convergence by July 2010 between parts of China and northern Europe and North America raise the likelihood of exotic species invasions, whereas anticipated climatic shifts may actually reduce invasion risks into much of eastern Europe. PMID:20300170

Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century

NASA Astrophysics Data System (ADS)

Kravtsov, Sergey

2017-06-01

Identification and dynamical attribution of multidecadal climate undulations to either variations in external forcings or to internal sources is one of the most important topics of modern climate science, especially in conjunction with the issue of human-induced global warming. Here we utilize ensembles of twentieth century climate simulations to isolate the forced signal and residual internal variability in a network of observed and modeled climate indices. The observed internal variability so estimated exhibits a pronounced multidecadal mode with a distinctive spatiotemporal signature, which is altogether absent in model simulations. This single mode explains a major fraction of model-data differences over the entire climate index network considered; it may reflect either biases in the models' forced response or models' lack of requisite internal dynamics, or a combination of both.