Modern nature and climate changes in Siberia: new methods and results of analysis of instrumented observations

NASA Astrophysics Data System (ADS)

Kabanov, Mikhail V.

2002-02-01

Peculiarity of nature and climate changes in middle latitudes of the Northern Hemisphere and in Siberia is that the temporal variability of meteorological quantities here has a wide range and their spatial variability has a complicated zone structure. Therefore, regional monitoring of modern nature and climate changes in Siberia is of scientific interest from the viewpoint of the global changes observed. Another Siberian peculiarity is associated with the fact that there are many unique objects that have global importance both as natural complexes (boreal forests, water- bog systems, Baikal lake, etc.) And as technogenic objects (oil and gas production, coal mining, metallurgy, transport, etc.). Therefore monitoring and modeling of regional nature and climate changes in Siberia have great practical importance, which is underestimated now, for industrial development of Siberia. Taking into account the above peculiarities and tendencies on investigation of global and regional environmental and climate changes, the multidisciplinary project on Climate and Ecological Monitoring of Siberia (CEMS) was accepted to the research and development program Sibir' since 1993. To realize this project, the Climate and Ecological Observatory was established in Tomsk at the Institute for Optical Monitoring (IOM) SB RAS. At the present time the stations (the basic and background ones) of this observatory are in a progress and theory and instruments for monitoring are being developed as well. In this paper we discuss some results obtained in the framework of CEMS project that were partially published in the monographs, in scientific journals, and will be published in the Proceedings of the 8th Joint International Symposium on Atmospheric and Ocean Optics and Atmosphere Physics. This review has a purpose not only to discuss the obtained regularities but also to formulate scientific and technical tasks for further investigations into the regional changes of technogenic, natural, and climate systems.

Workshop on Satellite and In situ Observations for Climate Prediction

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

Acker, J.G.; Busalacchi, A.

1995-02-01

Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

Workshop on Satellite and In situ Observations for Climate Prediction

NASA Technical Reports Server (NTRS)

Acker, James G.; Busalacchi, Antonio

1995-01-01

Participants in this workshop, which convened in Venice, Italy, 6-8 May 1993, met to consider the current state of climate monitoring programs and instrumentation for the purpose of climatological prediction on short-term (seasonal to interannual) timescales. Data quality and coverage requirements for definition of oceanographic heat and momentum fluxes, scales of inter- and intra-annual variability, and land-ocean-atmosphere exchange processes were examined. Advantages and disadvantages of earth-based and spaceborne monitoring systems were considered, as were the structures for future monitoring networks, research programs, and modeling studies.

Young students, satellites aid understanding of climate-biosphere link

NASA Astrophysics Data System (ADS)

White, Michael A.; Schwartz, Mark D.; Running, Steven W.

Data collected by young students from kindergarten through high school are being combined with satellite data to develop a more consistent understanding of the intimate connection between climate dynamics and the terrestrial biosphere. Comparison of the two sets of data involving the onset of budburst among trees and other vegetation has been extremely encouraging.Surface-atmosphere interactions involving exchanges of carbon, water, and energy are strongly affected by interannual variability in the timing and length of the vegetation growing season, and satellite remote sensing has the unique ability to consistently monitor global spatiotemporal variability in growing season dynamics. But without a clear picture of how satellite information (Figure 1) relates to ground conditions, the application of satellite growing season estimates for monitoring of climate-vegetation interactions, calculation of energy budgets, and large-scale ecological modeling is extremely limited.The integrated phenological analysis of field data, satellite observations, and climate advocated by Schwartz [1998], for example, has been primarily limited by the lack of geographically extensive and consistently measured phenology databases.

Climate Observing Systems: Where are we and where do we need to be in the future

NASA Astrophysics Data System (ADS)

Baker, B.; Diamond, H. J.

2017-12-01

Climate research and monitoring requires an observational strategy that blends long-term, carefully calibrated measurements as well as short-term, focused process studies. The operation and implementation of operational climate observing networks and the provision of related climate services, both have a significant role to play in assisting the development of national climate adaptation policies and in facilitating national economic development. Climate observing systems will require a strong research element for a long time to come. This requires improved observations of the state variables and the ability to set them in a coherent physical (as well as a chemical and biological) framework with models. Climate research and monitoring requires an integrated strategy of land/ocean/atmosphere observations, including both in situ and remote sensing platforms, and modeling and analysis. It is clear that we still need more research and analysis on climate processes, sampling strategies, and processing algorithms.

Accurately measuring sea level change from space: an ESA Climate Change Initiative for MSL closure budget studies

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Cazenave, Anny; Ablain, Michael; Larnicol, Gilles; Benveniste, Jerome; Johannessen, Johnny; Timms, Gary; Andersen, Ole; Cipollini, Paolo; Roca, Monica; Rudenko, Sergei; Fernandes, Joana; Balmaseda, Magdalena; Quartly, Graham; Fenoglio-Marc, Luciana; Meyssignac, Benoit; Scharffenberg, Martin

2016-04-01

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. We will firstly present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. At last, new altimeter standards have been developed and the best one have been recently selected in order to produce a full reprocessing of the dataset (performed in 2016) adapted for climate studies. These new standards will be presented as well as other results regarding the improvement of the sea level estimation in the Arctic Ocean and in coastal areas for which preliminary results suggest that significant improvements can be achieved.

Accurately measuring sea level change from space: an ESA climate change initiative for MSL closure budget studies

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Benveniste, Jérôme

2016-07-01

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of a first version of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. Within phase II, new altimeter standards have been developed and tested in order to reprocess the dataset with the best standards for climate studies. The reprocessed ECV will be released in summer 2016. We will present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. Efforts have also focused on the improvement of the sea level estimation in the Arctic Ocean and in coastal areas for which preliminary results suggest that significant improvements can be achieved.

NPOESS, Essential Climates Variables and Climate Change

NASA Astrophysics Data System (ADS)

Forsythe-Newell, S. P.; Bates, J. J.; Barkstrom, B. R.; Privette, J. L.; Kearns, E. J.

2008-12-01

Advancement in understanding, predicting and mitigating against climate change implies collaboration, close monitoring of Essential Climate Variable (ECV)s through development of Climate Data Record (CDR)s and effective action with specific thematic focus on human and environmental impacts. Towards this end, NCDC's Scientific Data Stewardship (SDS) Program Office developed Climate Long-term Information and Observation system (CLIO) for satellite data identification, characterization and use interrogation. This "proof-of-concept" online tool provides the ability to visualize global CDR information gaps and overlaps with options to temporally zoom-in from satellite instruments to climate products, data sets, data set versions and files. CLIO provides an intuitive one-stop web site that displays past, current and planned launches of environmental satellites in conjunction with associated imagery and detailed information. This tool is also capable of accepting and displaying Web-based input from Subject Matter Expert (SME)s providing a global to sub-regional scale perspective of all ECV's and their impacts upon climate studies. SME's can access and interact with temporal data from the past and present, or for future planning of products, datasets/dataset versions, instruments, platforms and networks. CLIO offers quantifiable prioritization of ECV/CDR impacts that effectively deal with climate change issues, their associated impacts upon climate, and this offers an intuitively objective collaboration and consensus building tool. NCDC's latest tool empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in climate change monitoring strategies and significantly enhances climate change collaboration and awareness.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea.

PubMed

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-06-01

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countries with more limited commitments. In the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

DOE PAGES

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

2015-05-28

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

Variability in climate change simulations affects needed long-term riverine nutrient reductions for the Baltic Sea

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

Bring, Arvid; Rogberg, Peter; Destouni, Georgia

Changes to runoff due to climate change may influence management of nutrient loading to the sea. Assuming unchanged river nutrient concentrations, we evaluate the effects of changing runoff on commitments to nutrient reductions under the Baltic Sea Action Plan. For several countries, climate projections point to large variability in load changes in relation to reduction targets. These changes either increase loads, making the target more difficult to reach, or decrease them, leading instead to a full achievement of the target. The impact of variability in climate projections varies with the size of the reduction target and is larger for countriesmore » with more limited commitments. Finally, in the end, a number of focused actions are needed to manage the effects of climate change on nutrient loads: reducing uncertainty in climate projections, deciding on frameworks to identify best performing models with respect to land surface hydrology, and increasing efforts at sustained monitoring of water flow changes.« less

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Variability of atmospheric greenhouse gases as a biogeochemical processing signal at regional scale in a karstic ecosystem

NASA Astrophysics Data System (ADS)

Borràs, Sílvia; Vazquez, Eusebi; Morguí, Josep-Anton; Àgueda, Alba; Batet, Oscar; Cañas, Lídia; Curcoll, Roger; Grossi, Claudia; Nofuentes, Manel; Occhipinti, Paola; Rodó, Xavier

2015-04-01

The South-eastern area of the Iberian Peninsula is an area where climatic conditions reach extreme climatic conditions during the year, and is also heavily affected by the ENSO and NAO. The Natural Park of Cazorla, Segura de la Sierra and Las Villas is located in this region, and it is the largest protected natural area in Spain (209920 Ha). This area is characterized by important climatic and hydrologic contrasts: although the mean annual precipitation is 770 nm, the karstic soils are the main cause for water scarcity during the summer months, while on the other hand it is in this area where the two main rivers of Southern Spain, the Segura and the Guadalquivir, are born. The protected area comprises many forested landscapes, karstic areas and reservoirs like Tranco de Beas. The temperatures during summer are high, with over 40°C heatwaves occurring each year. But during the winter months, the land surface can be covered by snow for periods of time up until 30 days. The ENSO and NAO influences cause also an important inter annual climatic variability in this area. Under the ENSO, autumnal periods are more humid while the following spring is drier. In this area vegetal Mediterranean communities are dominant. But there are also a high number of endemic species and derelict species typical of temperate climate. Therefore it is a protected area with high specific diversity. Additionally, there is an important agricultural activity in the fringe areas of the Natural Park, mainly for olive production, while inside the Park this activity is focused on mountain wheat production. Therefore the diverse vegetal communities and landscapes can easily be under extreme climatic pressures, affecting in turn the biogeochemical processes at the regional scale. The constant, high-frequency monitoring of greenhouse gases (GHG) (CO2 and CH4) integrates the biogeochemical signal of changes in this area related to the carbon cycle at the regional scale, capturing the high diversity of landscapes and climatic variability. The monitoring is carried out in one of the stations of the ClimaDat network, which consists of eight GHG monitoring stations in highly preserved ecosystems which are very sensitive to climate change in Spain. This constant monitoring will allow relating changes in terrestrial ecosystems, hydrological processes and atmospheric transport of GHG. The goal of the presentation is to show the results obtained since September 2013 through continuous monitoring, focusing on the seasonal changes in precipitation, temperature, and CO2 and CH4 changes in atmospheric concentrations.

Climate change effects on rangelands and rangeland management: Affirming the need for monitoring

Treesearch

Daniel W. Mccollum; John A. Tanaka; Jack A. Morgan; John E. Mitchell; William E. Fox; Kristie A. Maczko; Lori Hidinger; Clifford S. Duke; Urs P. Kreuter

2017-01-01

Uncertainty as to the extent and magnitude of changes in conditions that might occur due to climate change poses a problem for land and resource managers as they seek to adapt to changes and mitigate effects of climate variability. We illustrate using scenarios of projected future conditions on rangelands in the Northern Great Plains and Desert Southwest of the United...

Development and Implementation of Flood Risk Mapping, Water Bodies Monitoring and Climate Information for Human Health

NASA Astrophysics Data System (ADS)

Ceccato, P.; McDonald, K. C.; Jensen, K.; Podest, E.; De La Torre Juarez, M.

2013-12-01

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI), City College of New York (CCNY) and NASA Jet Propulsion Laboratory (JPL) are developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on vector-borne diseases such as malaria, leishmaniasis, rift valley fever. In this poster we present the new and improved products that have been developed for monitoring water bodies for monitoring and forecasting risks of vector-borne disease epidemics. The products include seasonal inundation patterns in the East African region based on the global mappings of inundated water fraction derived at the 25-km scale from both active and passive microwave instruments QuikSCAT, AMSR-E, SSM/I, ERS, ASCAT, and MODIS and LANDSAT data. We also present how the products are integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

Detecting the climatic effects of increasing carbon dioxide

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

MacCracken, M C; Luther, F M

1985-12-01

This report documents what is known about detecting the CO2-induced changes in climate, and describes the uncertainties and unknowns associated with this monitoring and analysis effort. The various approaches for detecting CO2-induced climate changes are discussed first, followed by a review of applications of these strategies to the various climatic variables that are expected to be changing. Recommendations are presented for research and analysis activities. Separate abstracts have been prepared for the individual papers. (ACR)

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

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

The evaporative demand drought index: Part II – CONUS-wide assessment against common drought indicators

USDA-ARS?s Scientific Manuscript database

Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought, however other climatic factors such as solar radiation, wind speed, and specific humidity can be important drivers in the depletion of soil moisture and evolution and persistence of dro...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Capturing subregional variability in regional-scale climate change vulnerability assessments of natural resources.

PubMed

Buotte, Polly C; Peterson, David L; McKelvey, Kevin S; Hicke, Jeffrey A

2016-03-15

Natural resource vulnerability to climate change can depend on the climatology and ecological conditions at a particular site. Here we present a conceptual framework for incorporating spatial variability in natural resource vulnerability to climate change in a regional-scale assessment. The framework was implemented in the first regional-scale vulnerability assessment conducted by the US Forest Service. During this assessment, five subregional workshops were held to capture variability in vulnerability and to develop adaptation tactics. At each workshop, participants answered a questionnaire to: 1) identify species, resources, or other information missing from the regional assessment, and 2) describe subregional vulnerability to climate change. Workshop participants divided into six resource groups; here we focus on wildlife resources. Participants identified information missing from the regional assessment and multiple instances of subregional variability in climate change vulnerability. We provide recommendations for improving the process of capturing subregional variability in a regional vulnerability assessment. We propose a revised conceptual framework structured around pathways of climate influence, each with separate rankings for exposure, sensitivity, and adaptive capacity. These revisions allow for a quantitative ranking of species, pathways, exposure, sensitivity, and adaptive capacity across subregions. Rankings can be used to direct the development and implementation of future regional research and monitoring programs. The revised conceptual framework is equally applicable as a stand-alone model for assessing climate change vulnerability and as a nested model within a regional assessment for capturing subregional variability in vulnerability. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Calibration and Characterization of Earth Remote Sensing and Environmental Monitoring Instruments. Chapter 10

NASA Technical Reports Server (NTRS)

Butler, James J.; Johnson, B. Carol; Barnes, Robert A.

2005-01-01

The use of remote sensing instruments on orbiting satellite platforms in the study of Earth Science and environmental monitoring was officially inaugurated with the April 1, 1960 launch of the Television Infrared Observation Satellite (TIROS) [1]. The first TIROS accommodated two television cameras and operated for only 78 days. However, the TIROS program, in providing in excess of 22,000 pictures of the Earth, achieved its primary goal of providing Earth images from a satellite platform to aid in identifying and monitoring meteorological processes. This marked the beginning of what is now over four decades of Earth observations from satellite platforms. reflected and emitted radiation from the Earth using instruments on satellite platforms. These measurements are input to climate models, and the model results are analyzed in an effort to detect short and long-term changes and trends in the Earth's climate and environment, to identify the cause of those changes, and to predict or influence future changes. Examples of short-term climate change events include the periodic appearance of the El Nino-Southern Oscillation (ENSO) in the tropical Pacific Ocean [2] and the spectacular eruption of Mount Pinatubo on the Philippine island of Luzon in 1991. Examples of long term climate change events, which are more subtle to detect, include the destruction of coral reefs, the disappearance of glaciers, and global warming. Climatic variability can be both large and small scale and can be caused by natural or anthropogenic processes. The periodic El Nino event is an example of a natural process which induces significant climatic variability over a wide range of the Earth. A classic example of a large scale anthropogenic influence on climate is the well-documented rapid increase of atmospheric carbon dioxide occurring since the beginning of the Industrial Revolution [3]. An example of the study of a small-scale anthropogenic influence in climate variability is the Atlanta Land-use Analysis Temperature and Air-quality (ATLANTA) project [4]. This project has found that the replacement of trees and vegetation with concrete and asphalt in Atlanta, Georgia, and its environs has created a microclimate capable of producing wind and thunderstorms. A key objective of climate research is to be able to distinguish the natural versus human roles in climate change and to clearly communicate those findings to those who shape and direct environmental policy.

Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil

NASA Astrophysics Data System (ADS)

de Carvalho, Luiz G.; de Carvalho Alves, Marcelo; de Oliveira, Marcelo S.; Vianello, Rubens L.; Sediyama, Gilberto C.; de Carvalho, Luis M. T.

2010-11-01

The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box-Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state.

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1986-01-01

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

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

Utilizing Satellite Precipitation Products to Understand the Link Between Climate Variability and Malaria

NASA Astrophysics Data System (ADS)

Maggioni, V.; Mousam, A.; Delamater, P. L.; Cash, B. A.; Quispe, A.

2015-12-01

Malaria is a public health threat to people globally leading to 198 million cases and 584,000 deaths annually. Outbreaks of vector borne diseases such as malaria can be significantly impacted by climate variables such as precipitation. For example, an increase in rainfall has the potential to create pools of water that can serve as breeding locations for mosquitos. Peru is a country that is currently controlling malaria, but has not been able to completely eliminate the disease. Despite the various initiatives in order to control malaria - including regional efforts to improve surveillance, early detection, prompt treatment, and vector management - malaria cases in Peru have risen between 2011 and 2014. The purpose of this study is to test the hypothesis that climate variability plays a fundamental role in malaria occurrence over a 12-year period (2003-2014) in Peru. When analyzing climate variability, it is important to obtain high-quality, high-resolution data for a time series long enough to draw conclusion about how climate variables have been and are changing. Remote sensing is a powerful tool for measuring and monitoring climate variables continuously in time and space. A widely used satellite-based precipitation product, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), available globally since 1998, was used to obtain 3-hourly data with a spatial resolution of 0.25° x 0.25°. The precipitation data was linked to weekly (2003-2014) malaria cases collected by health centers and available at a district level all over Peru to investigate the relationship between precipitation and the seasonal and annual variations in malaria incidence. Further studies will incorporate additional climate variables such as temperature, humidity, soil moisture, and surface pressure from remote sensing data products and climate models. Ultimately, this research will help us to understand if climate variability impacts malaria incidence rates and to determine which regions of the country are most affected.

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

NASA Astrophysics Data System (ADS)

Thepaut, Jean-Noel

2016-04-01

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

Climate and Population Health Vulnerabilities to Vector-Borne Diseases: Increasing Resilience Under Climate Change Conditions in Africa

NASA Astrophysics Data System (ADS)

Ceccato, P.; McDonald, K. C.; Podest, E.; De La Torre Juarez, M.; Kruczkiewicz, A.; Lessel, J.; Jensen, K.; Thomson, M. C.

2014-12-01

The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases (i.e. malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities, ministries of health and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above.

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.

Planning for Production of Freshwater Fish Fry in a Variable Climate in Northern Thailand.

PubMed

Uppanunchai, Anuwat; Apirumanekul, Chusit; Lebel, Louis

2015-10-01

Provision of adequate numbers of quality fish fry is often a key constraint on aquaculture development. The management of climate-related risks in hatchery and nursery management operations has not received much attention, but is likely to be a key element of successful adaptation to climate change in the aquaculture sector. This study explored the sensitivities and vulnerability of freshwater fish fry production in 15 government hatcheries across Northern Thailand to climate variability and evaluated the robustness of the proposed adaptation measures. This study found that hatcheries have to consider several factors when planning production, including: taking into account farmer demand; production capacity of the hatchery; availability of water resources; local climate and other area factors; and, individual species requirements. Nile tilapia is the most commonly cultured species of freshwater fish. Most fry production is done in the wet season, as cold spells and drought conditions disrupt hatchery production and reduce fish farm demand in the dry season. In the wet season, some hatcheries are impacted by floods. Using a set of scenarios to capture major uncertainties and variability in climate, this study suggests a couple of strategies that should help make hatchery operations more climate change resilient, in particular: improving hatchery operations and management to deal better with risks under current climate variability; improving monitoring and information systems so that emerging climate-related risks are known sooner and understood better; and, research and development on alternative species, breeding programs, improving water management and other features of hatchery operations.

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

USGS Publications Warehouse

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

2016-01-01

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

An approach for the long-term 30-m land surface snow-free albedo retrieval from historic Landsat surface reflectance and MODIS-based a priori anisotropy knowledge

USDA-ARS?s Scientific Manuscript database

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth’s radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-reso...

Evaluation of the performance of hydrological variables derived from GLDAS-2 and MERRA-2 in Mexico

NASA Astrophysics Data System (ADS)

Real-Rangel, R. A.; Pedrozo-Acuña, A.; Breña-Naranjo, J. A.

2017-12-01

Hydrological studies have found in data assimilation systems and global reanalysis of land surface variables (e.g soil moisture, streamflow) a wide range of applications, from drought monitoring to water balance and hydro-climatology variability assessment. Indeed, these hydrological data sources have led to an improvement in developing and testing monitoring and prediction systems in poorly gauged regions of the world. This work tests the accuracy and error of land surface variables (precipitation, soil moisture, runoff and temperature) derived from the data assimilation reanalysis products GLDAS-2 and MERRA-2. Validate the performance of these data platforms must be thoroughly evaluated in order to consider the error of hydrological variables (i.e., precipitation, soil moisture, runoff and temperature) derived from the reanalysis products. For such purpose, a quantitative assessment was performed at 2,892 climatological stations, 42 stream gauges and 44 soil moisture probes located in Mexico and across different climate regimes (hyper-arid to tropical humid). Results show comparisons between these gridded products against ground-based observational stations for 1979-2014. The results of this analysis display a spatial distribution of errors and accuracy over Mexico discussing differences between climates, enabling the informed use of these products.

Variable temperature seat climate control system

DOEpatents

Karunasiri, Tissa R.; Gallup, David F.; Noles, David R.; Gregory, Christian T.

1997-05-06

A temperature climate control system comprises a variable temperature seat, at least one heat pump, at least one heat pump temperature sensor, and a controller. Each heat pump comprises a number of Peltier thermoelectric modules for temperature conditioning the air in a main heat exchanger and a main exchanger fan for passing the conditioned air from the main exchanger to the variable temperature seat. The Peltier modules and each main fan may be manually adjusted via a control switch or a control signal. Additionally, the temperature climate control system may comprise a number of additional temperature sensors to monitor the temperature of the ambient air surrounding the occupant as well as the temperature of the conditioned air directed to the occupant. The controller is configured to automatically regulate the operation of the Peltier modules and/or each main fan according to a temperature climate control logic designed both to maximize occupant comfort during normal operation, and minimize possible equipment damage, occupant discomfort, or occupant injury in the event of a heat pump malfunction.

Experiment, monitoring, and gradient methods used to infer climate change effects on plant communities yield consistent patterns.

PubMed

Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Fosaa, Anna Maria; Gould, William A; Hermanutz, Luise; Hofgaard, Annika; Jónsdóttir, Ingibjörg S; Jónsdóttir, Ingibjörg I; Jorgenson, Janet C; Lévesque, Esther; Magnusson, Borgþór; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Rixen, Christian; Tweedie, Craig E; Walker, Marilyn D; Walker, Marilyn

2015-01-13

Inference about future climate change impacts typically relies on one of three approaches: manipulative experiments, historical comparisons (broadly defined to include monitoring the response to ambient climate fluctuations using repeat sampling of plots, dendroecology, and paleoecology techniques), and space-for-time substitutions derived from sampling along environmental gradients. Potential limitations of all three approaches are recognized. Here we address the congruence among these three main approaches by comparing the degree to which tundra plant community composition changes (i) in response to in situ experimental warming, (ii) with interannual variability in summer temperature within sites, and (iii) over spatial gradients in summer temperature. We analyzed changes in plant community composition from repeat sampling (85 plant communities in 28 regions) and experimental warming studies (28 experiments in 14 regions) throughout arctic and alpine North America and Europe. Increases in the relative abundance of species with a warmer thermal niche were observed in response to warmer summer temperatures using all three methods; however, effect sizes were greater over broad-scale spatial gradients relative to either temporal variability in summer temperature within a site or summer temperature increases induced by experimental warming. The effect sizes for change over time within a site and with experimental warming were nearly identical. These results support the view that inferences based on space-for-time substitution overestimate the magnitude of responses to contemporary climate warming, because spatial gradients reflect long-term processes. In contrast, in situ experimental warming and monitoring approaches yield consistent estimates of the magnitude of response of plant communities to climate warming.

Bioclimatic Classification of Northeast Asia for climate change response

NASA Astrophysics Data System (ADS)

Choi, Y.; Jeon, S. W.; Lim, C. H.

2016-12-01

As climate change has been getting worse, we should monitor the change of biodiversity, and distribution of species to handle the crisis and take advantage of climate change. The development of bioclimatic map which classifies land into homogenous zones by similar environment properties is the first step to establish a strategy. Statistically derived classifications of land provide useful spatial frameworks to support ecosystem research, monitoring and policy decisions. Many countries are trying to make this kind of map and actively utilize it to ecosystem conservation and management. However, the Northeast Asia including North Korea doesn't have detailed environmental information, and has not built environmental classification map. Therefore, this study presents a bioclimatic map of Northeast Asia based on statistical clustering of bioclimate data. Bioclim data ver1.4 which provided by WorldClim were considered for inclusion in a model. Eight of the most relevant climate variables were selected by correlation analysis, based on previous studies. Principal Components Analysis (PCA) was used to explain 86% of the variation into three independent dimensions, which were subsequently clustered using an ISODATA clustering. The bioclimatic zone of Northeast Asia could consist of 29, 35, and 50 zones. This bioclimatic map has a 30' resolution. To assess the accuracy, the correlation coefficient was calculated between the first principal component values of the classification variables and the vegetation index, Gross Primary Production (GPP). It shows about 0.5 Pearson correlation coefficient. This study constructed Northeast Asia bioclimatic map by statistical method with high resolution, but in order to better reflect the realities, the variety of climate variables should be considered. Also, further studies should do more quantitative and qualitative validation in various ways. Then, this could be used more effectively to support decision making on climate change adaptation.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Is modern climate variability reflected in compund specific hydrogen isotope ratios of sedimentary biomarkers?

NASA Astrophysics Data System (ADS)

Sachse, D.; Radke, J.; Gleixner, G.

2003-04-01

Compound specific hydrogen isotope ratios are emerging as a new palaeoclimatic and palaeohydrological proxy. First reconstructions of palaeoclimate using D/H ratios from n-alkanes are available (Andersen et al. 2001, Sauer et al. 2001, Sachse et al. 2003). However, a systematic approach comparing recent sedimentary biomarkers with climate data is still lacking. We are establishing an ecosystem study of small, ground water fed lakes with known limnology. Nearly all lakes are close to a long-term climate-monitoring site (CARBOEUROPE flux tower site, IAEA precipitation monitoring) delivering ecophysiological and climatic data as temperature, precipitation, evapotranspiration etc. Water, primary biomass, plant, soil and sediment were sampled from lakes and the surrounding ecosystem along a climatic and isotopic gradient in meteoric waters from northern Finland (deltaD: -130 permil vs. VSMOW) to southern Italy (deltaD: -30 permil vs. VSMOW, IAEA 2001). Biomarkers were extracted from the samples to test if climatic variability is reflected in their D/H ratios. First results of the factors influencing the hydrogen isotope composition of sedimentary biomarkers and their use as palaeoclimatic and palaeohydrological proxy will be presented. Andersen N, Paul HA, Bernasconi SM, McKenzie JA, Behrens A, Schaeffer P, Albrecht P (2001) Large and rapid climate variability during the Messinian salinity crisis: Evidence from deuterium concentrations of individual biomarkers. Geology 29:799-802 IAEA (2001) GNIP Maps and Animations. International Atomic Energy Agency, Vienna. Accessible at http://isohis.iaea.org Sachse D, Radke J, Gaupp R, Schwark L, Lüniger G, Gleixner G (2003) Reconstruction of palaeohydrological conditions in a lagoon during the 2nd Zechstein cycle through simultaneous use of deltaD values of individual n-alkanes and delta18O and delta13C values of carbonates. International Journal of Earth Sciences, submitted Sauer PE, Eglington TI, Hayes JM, Schimmelman A, Sessions AL (2001) Compound-specific D/H ratios of lipid biomarkers from sediments as a proxy for environmental and climatic conditions. Geochimica et Cosmochimica Acta 65:213-222

Climate and Health Vulnerability to Vector-Borne Diseases: Increasing Resilience under Climate Change Conditions in Africa

NASA Astrophysics Data System (ADS)

Ceccato, P.

2015-12-01

The International Research Institute for Climate and Society (IRI), the City University of New York (CUNY) and NASA Jet Propulsion Laboratory (JPL) in collaboration with NASA SERVIR are developing tools to monitor climate variables (precipitation, temperature, vegetation, water bodies, inundation) that help projects in Africa to increase resilience to climate change for vector-borne diseases ( malaria, trypanosomiasis, leishmaniasis, and schistosomiasis). Through the development of new products to monitor precipitation, water bodies and inundation, IRI, CUNY and JPL provide tools and capacity building to research communities; ministries of health; the WMO Global Framework for Climate and Services; and World Health Organization in Africa to: 1) Develop research teams' ability to appropriately use climate data as part of their research 2) Enable research teams and ministries to integrate climate information into social and economic drivers of vulnerability and opportunities for adaptation to climate change 3) Inform better policies and programs for climate change adaptation. This oral presentation will demonstrate how IRI, CUNY, and JPL developed new products, tools and capacity building to achieve the three objectives mentioned above with examples in South Africa, Zimbabwe, Tanzania and Malawi.

Climate change and water availability for vulnerable agriculture

NASA Astrophysics Data System (ADS)

Dalezios, Nicolas; Tarquis, Ana Maria

2017-04-01

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

Participatory data collection and monitoring of agricultural pest dynamics for climate-resilient coffee production using Tiko'n, a generic tool to develop agroecological food web models

NASA Astrophysics Data System (ADS)

Rojas, M.; Malard, J. J.; Adamowski, J. F.; Tuy, H.

2016-12-01

Climate variability impacts agricultural processes through many mechanisms. For example, the proliferation of pests and diseases increases with warmer climate and alternated wind patterns, as longer growing seasons allow pest species to complete more reproductive cycles and changes in the weather patterns alter the stages and rates of development of pests and pathogens. Several studies suggest that enhancing plant diversity and complexity in farming systems, such as in agroforestry systems, reduces the vulnerability of farms to extreme climatic events. On the other hand, other authors have argued that vegetation diversity does not necessarily reduce the incidence of pests and diseases, highlighting the importance of understanding how, where and when it is recommendable to diversify vegetation to improve pest and disease control, and emphasising the need for tools to develop, monitor and evaluate agroecosystems. In order to understand how biodiversity can enhance ecosystem services provided by the agroecosystem in the context of climatic variability, it is important to develop comprehensive models that include the role of trophic chains in the regulation of pests, which can be achieved by integrating crop models with pest-predator models, also known as agroecosystem network (AEN) models. Here we present a methodology for the participatory data collection and monitoring necessary for running Tiko'n, an AEN model that can also be coupled to a crop model such as DSSAT. This methodology aims to combine the local and practical knowledge of farmers with the scientific knowledge of entomologists and agronomists, allowing for the simplification of complex ecological networks of plant and insect interactions. This also increases the acceptability, credibility, and comprehension of the model by farmers, allowing them to understand their relationship with the local agroecosystem and their potential to use key agroecosystem principles such as functional diversity to mitigate climate variability impacts. Preliminary results of a study currently being conducted in a coffee agroforestry system in El Quebracho, Guatemala, will be presented, where the data was directly collected by farmers during eight consecutive months. Finally, future recommendations from lessons learnt during this study will be discussed.

Satellite-based climate data records of surface solar radiation from the CM SAF

NASA Astrophysics Data System (ADS)

Trentmann, Jörg; Cremer, Roswitha; Kothe, Steffen; Müller, Richard; Pfeifroth, Uwe

2017-04-01

The incoming surface solar radiation has been defined as an essential climate variable by GCOS. Long term monitoring of this part of the earth's energy budget is required to gain insights on the state and variability of the climate system. In addition, climate data sets of surface solar radiation have received increased attention over the recent years as an important source of information for solar energy assessments, for crop modeling, and for the validation of climate and weather models. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) is deriving climate data records (CDRs) from geostationary and polar-orbiting satellite instruments. Within the CM SAF these CDRs are accompanied by operational data at a short time latency to be used for climate monitoring. All data from the CM SAF is freely available via www.cmsaf.eu. Here we present the regional and the global climate data records of surface solar radiation from the CM SAF. The regional climate data record SARAH (Surface Solar Radiation Dataset - Heliosat, doi: 10.5676/EUM_SAF_CM/SARAH/V002) is based on observations from the series of Meteosat satellites. SARAH provides 30-min, daily- and monthly-averaged data of the effective cloud albedo, the solar irradiance (incl. spectral information), the direct solar radiation (horizontal and normal), and the sunshine duration from 1983 to 2015 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° allowing for detailed regional studies. The global climate data record CLARA (CM SAF Clouds, Albedo and Radiation dataset from AVHRR data, doi: 10.5676/EUM_SAF_CM/CLARA_AVHRR/V002) is based on observations from the series of AVHRR satellite instruments. CLARA provides daily- and monthly-averaged global data of the solar irradiance (SIS) from 1982 to 2015 with a spatial resolution of 0.25°. In addition to the solar surface radiation also the longwave surface radiation as well as surface albedo and numerous cloud properties are provided in CLARA. Here we provide an overview of the climate data records of the surface solar radiation and present the results of the quality assessment of both climate data records against available surface reference observations, e.g., from the BSRN and the GEBA data archive.

Linking the Observation of Essential Variables to Societal Benefits

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.

2017-12-01

Different scientific communities have established sets of commonly agreed upon essential variables to help coordinate data collection in a variety of Earth observation areas. As an example, the World Meteorological Organization Global Climate Observing System has identified 50 Essential Climate Variables (ECVs), such as sea-surface temperature and carbon dioxide, which are required to monitoring the climate and detect and attribute climate change. In addition to supporting climate science, measuring these ECVs deliver many types of societal benefits, ranging from disaster mitigation to agricultural productivity to human health. While communicating the value in maintaining and improving observational records for these variables has been a challenge, quantifying how the measurement of these ECVs results in the delivery of many different societal benefits may help support their continued measurement. The 2016 National Earth Observation Assessment (EOA 2016) quantified the impact of individual Earth observation systems, sensors, networks, and surveys (or Earth observation systems, for short) on the achievement of 217 Federal objectives in 13 societal benefit areas (SBAs). This study will demonstrate the use of the EOA 2016 dataset to show the different Federal objectives and SBAs that are impacted by the Earth observation systems used to measure ECVs. Describing how the measurements from these Earth observation systems are used not only to maintain the climate record but also to meet additional Federal objectives may help articulate the continued measurement of the ECVs. This study will act as a pilot for the use of the EOA 2016 dataset to map between the measurements required to observe additional sets of variables, such as the Essential Ocean Variables and Essential Biodiversity Variables, and the ability to achieve a variety of societal benefits.

Evaluating interannual variability in speleothem records of North American monsoon rainfall

NASA Astrophysics Data System (ADS)

Truebe, S. A.; Cole, J. E.; Ault, T. R.; Kimbrough, A.; Henderson, G. M.; Barmett, H.; Hlohowskyj, S.

2013-12-01

Speleothems can produce long, high resolution, absolutely-dated records of past climate. They are especially useful for past climate reconstruction in areas such as the southwestern United States, where traditional sources of past climate information (corals, lake or ocean sediments, ice cores) are absent. Here we present two records of Holocene rainfall variability from two Arizona caves less than 40km apart: Cave of the Bells (COB) and Fort Huachuca Cave (FHC), spanning 7000 and 4000 years respectively. Both records show a trend towards more negative oxygen isotope values into the modern era. Extensive monthly monitoring suggests that speleothem oxygen isotope composition is an average of the oxygen isotope composition of the summer North American monsoon (NAM) and winter frontal storms, with a bias towards winter likely due to lack of infiltration of intense monsoon rainfall. This bias is stronger in COB than in FHC. Winter rainfall has had an increasing influence at both sites from the mid-Holocene until the present; in other words, the NAM has been weakening over the past few thousand years, in step with changes in other monsoon systems and Northern Hemisphere insolation. Although the records are similar in overall trend, short-term variability is inconsistent. When providing information to water managers about future rainfall availability in the Southwest, having only millennial-scale information does not help much! To investigate the differences between the two records, we use a combination of approaches, including assessing age model uncertainty and modern climate heterogeneity, and monitoring cave-specific processes that may be overprinting the climate signal. We assess age model uncertainty using a statistical age-modeling program, which allows us to develop many physically plausible time series for the same age-depth data. With this age modeling tool, we critically assess whether particular isotope excursions correspond between speleothems and if they are temporally related to global climate events. However, even correlation and coherence analyses across the suites of time series for each speleothem do not elicit a common high-frequency climate story. We further investigate the discrepancy between cave records by assessing modern climate heterogeneity using historical observations. Climate in the arid Southwest is spatially heterogeneous, especially during the summer monsoon, contributing to the mismatch between these two climate records. Finally, after a decade of monitoring at COB, we recognize that storage and mixing in the epikarst above the cave affect what parts (if any) of the seasonal signal are recorded in a speleothem. In addition to new insights about North American monsoon behavior during the Holocene, the important lesson from these speleothem records is that in caves, because of underlying (overlying?) climate heterogeneity, replication of a common climate signal using oxygen isotopes may be an unattainable goal. The COB and FHC records may record very local climate at their respective locations, overprinted by water storage and mixing in the epikarst. Very local-scale reconstructions of past rainfall variability from speleothems can still be useful and important, if interpreted for what they are.

Solar Radiation and Climate Experiment (SORCE) Satellite

NASA Technical Reports Server (NTRS)

2003-01-01

This is a close-up of the NASA-sponsored Solar Radiation and Climate Experiment (SORCE) Satellite. The SORCE mission, launched aboard a Pegasus rocket January 25, 2003, will provide state of the art measurements of incoming x-ray, ultraviolet, visible, near-infrared, and total solar radiation. Critical to studies of the Sun and its effect on our Earth system and mankind, SORCE will provide measurements that specifically address long-term climate change, natural variability and enhanced climate prediction, and atmospheric ozone and UV-B radiation. Orbiting around the Earth accumulating solar data, SORCE measures the Sun's output with the use of state-of-the-art radiometers, spectrometers, photodiodes, detectors, and bolo meters engineered into instruments mounted on a satellite observatory. SORCE is carrying 4 instruments: The Total Irradiance Monitor (TIM); the Solar Stellar Irradiance Comparison Experiment (SOLSTICE); the Spectral Irradiance Monitor (SIM); and the XUV Photometer System (XPS).

Impacts of Climate Anomalies on the Vegetation Patterns in the Arid and Semi-Arid Zones of Uzbekistan

NASA Astrophysics Data System (ADS)

Dildora, Aralova; Toderich, Kristina; Dilshod, Gafurov

2016-08-01

Steadily rising temperature anomalies in last decades are causing changes in vegetation patterns for sensitive to climate change in arid and semi-arid dryland ecosystems. After desiccation of the Aral Sea, Uzbekistan has been left with the challenge to develop drought and heat stress monitoring system and tools (e.g., to monitor vegetation status and/crop pattern dynamics) with using remote sensing technologies in broad scale. This study examines several climate parameters, NDVI and drought indexes within geostatistical method to predict further vegetation status in arid and semi-arid zones of landscapes. This approaches aimed to extract and utilize certain variable environmental data (temperature and precipitation) for assessment and inter-linkages of vegetation cover dynamics, specifically related to predict degraded and recovered zones or desertification process in the drylands due to scarcity of water resources and high risks of climate anomalies in fragile ecosystem of Uzbekistan.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa.

PubMed

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-06-14

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of Knowledge(SM) databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably.

Remote Sensing-Driven Climatic/Environmental Variables for Modelling Malaria Transmission in Sub-Saharan Africa

PubMed Central

Ebhuoma, Osadolor; Gebreslasie, Michael

2016-01-01

Malaria is a serious public health threat in Sub-Saharan Africa (SSA), and its transmission risk varies geographically. Modelling its geographic characteristics is essential for identifying the spatial and temporal risk of malaria transmission. Remote sensing (RS) has been serving as an important tool in providing and assessing a variety of potential climatic/environmental malaria transmission variables in diverse areas. This review focuses on the utilization of RS-driven climatic/environmental variables in determining malaria transmission in SSA. A systematic search on Google Scholar and the Institute for Scientific Information (ISI) Web of KnowledgeSM databases (PubMed, Web of Science and ScienceDirect) was carried out. We identified thirty-five peer-reviewed articles that studied the relationship between remotely-sensed climatic variable(s) and malaria epidemiological data in the SSA sub-regions. The relationship between malaria disease and different climatic/environmental proxies was examined using different statistical methods. Across the SSA sub-region, the normalized difference vegetation index (NDVI) derived from either the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) or Moderate-resolution Imaging Spectrometer (MODIS) satellite sensors was most frequently returned as a statistically-significant variable to model both spatial and temporal malaria transmission. Furthermore, generalized linear models (linear regression, logistic regression and Poisson regression) were the most frequently-employed methods of statistical analysis in determining malaria transmission predictors in East, Southern and West Africa. By contrast, multivariate analysis was used in Central Africa. We stress that the utilization of RS in determining reliable malaria transmission predictors and climatic/environmental monitoring variables would require a tailored approach that will have cognizance of the geographical/climatic setting, the stage of malaria elimination continuum, the characteristics of the RS variables and the analytical approach, which in turn, would support the channeling of intervention resources sustainably. PMID:27314369

Predictability of North Atlantic Multidecadal Climate Variability

PubMed

Griffies; Bryan

1997-01-10

Atmospheric weather systems become unpredictable beyond a few weeks, but climate variations can be predictable over much longer periods because of the coupling of the ocean and atmosphere. With the use of a global coupled ocean-atmosphere model, it is shown that the North Atlantic may have climatic predictability on the order of a decade or longer. These results suggest that variations of the dominant multidecadal sea surface temperature patterns in the North Atlantic, which have been associated with changes in climate over Eurasia, can be predicted if an adequate and sustainable system for monitoring the Atlantic Ocean exists.

Collaboration pathway(s) using new tools for optimizing `operational' climate monitoring from space

NASA Astrophysics Data System (ADS)

Helmuth, Douglas B.; Selva, Daniel; Dwyer, Morgan M.

2015-09-01

Consistently collecting the earth's climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust `operational' constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification30, 32. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We'll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve-Alaska and the Arctic National Wildlife Refuge

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2013; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2014

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2016-03-04

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2014; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P Climate and active-layer data acquired in the National Petroleum Reserve–Alaska and the Arctic National Wildlife Refuge, 1998–2015

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2017-02-06

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2015; this array is part of the Global Terrestrial Network for Permafrost (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methods. The array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature, soil moisture, snow depth, rainfall totals, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

DOI/GTN-P climate and active-layer data acquired in the National Petroleum Reserve: Alaska and the Arctic National Wildlife Refuge, 1998-2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2014-01-01

This report provides data collected by the climate monitoring array of the U.S. Department of the Interior on Federal lands in Arctic Alaska over the period August 1998 to July 2011; this array is part of the Global Terrestrial Network for Permafrost, (DOI/GTN-P). In addition to presenting data, this report also describes monitoring, data collection, and quality-control methodology. This array of 16 monitoring stations spans lat 68.5°N. to 70.5°N. and long 142.5°W. to 161°W., an area of approximately 150,000 square kilometers. Climate summaries are presented along with quality-controlled data. Data collection is ongoing and includes the following climate- and permafrost-related variables: air temperature, wind speed and direction, ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

NASA Technical Reports Server (NTRS)

Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

2011-01-01

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Spatial and Temporal Means and Variability of Arctic Sea Ice Climate Indicators from Satellite Data

NASA Astrophysics Data System (ADS)

Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S.

2017-12-01

Arctic sea ice has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer ice coverage. For the Arctic as a whole, the long-term trend for the annual sea ice extent (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the trends of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea ice climate indicators, such as the annual SIE minimum and maximum, snow/ice melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation.

Natural Variability and Anthropogenic Trends in the Ocean Carbon Sink

NASA Astrophysics Data System (ADS)

McKinley, Galen A.; Fay, Amanda R.; Lovenduski, Nicole S.; Pilcher, Darren J.

2017-01-01

Since preindustrial times, the ocean has removed from the atmosphere 41% of the carbon emitted by human industrial activities. Despite significant uncertainties, the balance of evidence indicates that the globally integrated rate of ocean carbon uptake is increasing in response to increasing atmospheric CO2 concentrations. The El Niño-Southern Oscillation in the equatorial Pacific dominates interannual variability of the globally integrated sink. Modes of climate variability in high latitudes are correlated with variability in regional carbon sinks, but mechanistic understanding is incomplete. Regional sink variability, combined with sparse sampling, means that the growing oceanic sink cannot yet be directly detected from available surface data. Accurate and precise shipboard observations need to be continued and increasingly complemented with autonomous observations. These data, together with a variety of mechanistic and diagnostic models, are needed for better understanding, long-term monitoring, and future projections of this critical climate regulation service.

Earth Observations in Support of Offshore Wind Energy Management in the Euro-Atlantic Region

NASA Astrophysics Data System (ADS)

Liberato, M. L. R.

2017-12-01

Climate change is one of the most important challenges in the 21st century and the energy sector is a major contributor to GHG emissions. Therefore greater attention has been given to the evaluation of offshore wind energy potentials along coastal areas, as it is expected offshore wind energy to be more efficient and cost-effective in the near future. Europe is developing offshore sites for over two decades and has been growing at gigawatt levels in annual capacity. Portugal is among these countries, with the development of a 25MW WindFloat Atlantic wind farm project. The international scientific community has developed robust ability on the research of the climate system components and their interactions. Climate scientists have gained expertise in the observation and analysis of the climate system as well as on the improvement of model and predictive capabilities. Developments on climate science allow advancing our understanding and prediction of the variability and change of Earth's climate on all space and time scales, while improving skilful climate assessments and tools for dealing with future challenges of a warming planet. However the availability of greater datasets amplifies the complexity on manipulation, representation and consequent analysis and interpretation of such datasets. Today the challenge is to translate scientific understanding of the climate system into climate information for society and decision makers. Here we discuss the development of an integration tool for multidisciplinary research, which allows access, management, tailored pre-processing and visualization of datasets, crucial to foster research as a service to society. One application is the assessment and monitoring of renewable energy variability, such as wind or solar energy, at several time and space scales. We demonstrate the ability of the e-science platform for planning, monitoring and management of renewable energy, particularly offshore wind energy in the Euro-Atlantic region. Further we explore the automatization of processes using different domains and datasets, which facilitate further research in evaluating and understanding renewable energy variability. AcknowledgementsThis work is supported by Foundation for Science and Technology (FCT), Portugal, project UID/GEO/50019/2013 - Instituto Dom Luiz.

Climate science and famine early warning

USGS Publications Warehouse

Verdin, James P.; Funk, Chris; Senay, Gabriel B.; Choularton, R.

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Climate science and famine early warning.

PubMed

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-11-29

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised.

Climate science and famine early warning

PubMed Central

Verdin, James; Funk, Chris; Senay, Gabriel; Choularton, Richard

2005-01-01

Food security assessment in sub-Saharan Africa requires simultaneous consideration of multiple socio-economic and environmental variables. Early identification of populations at risk enables timely and appropriate action. Since large and widely dispersed populations depend on rainfed agriculture and pastoralism, climate monitoring and forecasting are important inputs to food security analysis. Satellite rainfall estimates (RFE) fill in gaps in station observations, and serve as input to drought index maps and crop water balance models. Gridded rainfall time-series give historical context, and provide a basis for quantitative interpretation of seasonal precipitation forecasts. RFE are also used to characterize flood hazards, in both simple indices and stream flow models. In the future, many African countries are likely to see negative impacts on subsistence agriculture due to the effects of global warming. Increased climate variability is forecast, with more frequent extreme events. Ethiopia requires special attention. Already facing a food security emergency, troubling persistent dryness has been observed in some areas, associated with a positive trend in Indian Ocean sea surface temperatures. Increased African capacity for rainfall observation, forecasting, data management and modelling applications is urgently needed. Managing climate change and increased climate variability require these fundamental technical capacities if creative coping strategies are to be devised. PMID:16433101

The Inter-Annual Variability Analysis of Carbon Exchange in Low Artic Fen Uncovers The Climate Sensitivity And The Uncertainties Around Net Ecosystem Exchange Partitioning

NASA Astrophysics Data System (ADS)

Blanco, E. L.; Lund, M.; Williams, M. D.; Christensen, T. R.; Tamstorf, M. P.

2015-12-01

An improvement in our process-based understanding of CO2 exchanges in the Arctic, and their climate sensitivity, is critical for examining the role of tundra ecosystems in changing climates. Arctic organic carbon storage has seen increased attention in recent years due to large potential for carbon releases following thaw. Our knowledge about the exact scale and sensitivity for a phase-change of these C stocks are, however, limited. Minor variations in Gross Primary Production (GPP) and Ecosystem Respiration (Reco) driven by changes in the climate can lead to either C sink or C source states, which likely will impact the overall C cycle of the ecosystem. Eddy covariance data is usually used to partition Net Ecosystem Exchange (NEE) into GPP and Reco achieved by flux separation algorithms. However, different partitioning approaches lead to different estimates. as well as undefined uncertainties. The main objectives of this study are to use model-data fusion approaches to (1) determine the inter-annual variability in C source/sink strength for an Arctic fen, and attribute such variations to GPP vs Reco, (2) investigate the climate sensitivity of these processes and (3) explore the uncertainties in NEE partitioning. The intention is to elaborate on the information gathered in an existing catchment area under an extensive cross-disciplinary ecological monitoring program in low Arctic West Greenland, established under the auspices of the Greenland Ecosystem Monitoring (GEM) program. The use of such a thorough long-term (7 years) dataset applied to the exploration in inter-annual variability of carbon exchange, related driving factors and NEE partition uncertainties provides a novel input into our understanding about land-atmosphere CO2 exchange.

Distant drivers or local signals: where do mercury trends in western Arctic belugas originate?

PubMed

Loseto, L L; Stern, G A; Macdonald, R W

2015-03-15

Temporal trends of contaminants are monitored in Arctic higher trophic level species to inform us on the fate, transport and risk of contaminants as well as advise on global emissions. However, monitoring mercury (Hg) trends in species such as belugas challenge us, as their tissue concentrations reflect complex interactions among Hg deposition and methylation, whale physiology, dietary exposure and foraging patterns. The Beaufort Sea beluga population showed significant increases in Hg during the 1990 s; since that time an additional 10 years of data have been collected. During this time of data collection, changes in the Arctic have affected many processes that underlie the Hg cycle. Here, we examine Hg in beluga tissues and investigate factors that could contribute to the observed trends after removing the effect of age and size on Hg concentrations and dietary factors. Finally, we examine available indicators of climate variability (Arctic Oscillation (AO), the Pacific Decadal Oscillation (PDO) and sea-ice minimum (SIM) concentration) to evaluate their potential to explain beluga Hg trends. Results reveal a decline in Hg concentrations from 2002 to 2012 in the liver of older whales and the muscle of large whales. The temporal increases in Hg in the 1990 s followed by recent declines do not follow trends in Hg emission, and are not easily explained by diet markers highlighting the complexity of feeding, food web dynamics and Hg uptake. Among the regional-scale climate variables the PDO exhibited the most significant relationship with beluga Hg at an eight year lag time. This distant signal points us to consider beluga winter feeding areas. Given that changes in climate will impact ecosystems; it is plausible that these climate variables are important in explaining beluga Hg trends. Such relationships require further investigation of the multiple connections between climate variables and beluga Hg. Copyright © 2014 Elsevier B.V. All rights reserved.

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

PubMed

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-02-02

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

PubMed Central

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-01-01

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor. PMID:25648713

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. PMID:28003452

Faithful or not: direct and indirect effects of climate on extra-pair paternities in a population of Alpine marmots.

PubMed

Bichet, Coraline; Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-12-28

Despite being identified an area that is poorly understood regarding the effects of climate change, behavioural responses to climatic variability are seldom explored. Climatic variability is likely to cause large inter-annual variation in the frequency of extra-pair litters produced, a widespread alternative mating tactic to help prevent, correct or minimize the negative consequences of sub-optimal mate choice. In this study, we investigated how climatic variability affects the inter-annual variation in the proportion of extra-pair litters in a wild population of Alpine marmots. During 22 years of monitoring, the annual proportion of extra-pair litters directly increased with the onset of earlier springs and indirectly with increased snow in winters. Snowier winters resulted in a higher proportion of families with sexually mature male subordinates and thus, created a social context within which extra-pair paternity was favoured. Earlier spring snowmelt could create this pattern by relaxing energetic, movement and time constraints. Further, deeper snow in winter could also contribute by increasing litter size and juvenile survival. Optimal mate choice is particularly relevant to generate adaptive genetic diversity. Understanding the influence of environmental conditions and the capacity of the individuals to cope with them is crucial within the context of rapid climate change. © 2016 The Author(s).

Does climate directly influence NPP globally?

PubMed

Chu, Chengjin; Bartlett, Megan; Wang, Youshi; He, Fangliang; Weiner, Jacob; Chave, Jérôme; Sack, Lawren

2016-01-01

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot ) and stand age (a). The authors of that study concluded that the length of the growing season (lgs ) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re-analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum-likelihood model selection, independent-effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot , both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann ), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale. © 2015 John Wiley & Sons Ltd.

Assessment of the 1998–2001 drought impact on forest health in southeastern forests: an analysis of drought severity using FHM data

Treesearch

R. J. Klos; G. G. Wang; W. L. Bauerle

2010-01-01

Analyses of forest health indicators monitored through the Forest Health and Monitoring (FHM) program suggested that weather was the most important cause of tree mortality. Drought is of particular importance among weather variables because several global climate change scenarios predicted more frequent and/or intense drought in the Southeastern United States. During...

Did Climate Change Cause the 2012-2014 California Drought?

NASA Astrophysics Data System (ADS)

Mao, Y.; Clark, E.; Xiao, M.; Nijssen, B.; Lettenmaier, D. P.

2014-12-01

California has experienced severe drought over the last three years, with especially deficient winter precipitation and mountain snowpack in 2013-2014. While the severity of California's water crisis this year is not in question, the causes of the drought are less clear, and there has been debate as to whether human-induced climate change is at least in part a cause of anomalously low winter precipitation (P) and snow water equivalent (SWE) this year, or whether the conditions are simply the result of natural variability that has been manifested in previous severe droughts in California. To provide more scientific insight to this question, we reconstructed, using the Variable Infiltration Capacity (VIC) hydrologic model, SWE and runoff from 1920 to 2014 at a spatial resolution of 1/16 degree over the Sierra Nevada range of California. We forced the VIC model with a temporally consistent set of index precipitation and temperature stations that are also used in the University of Washington's Drought Monitoring System for the West Coast Region (http://www.hydro.washington.edu/forecast/monitor_cali/index.shtml). We carried out trend analysis and examined cumulative probability for accumulated winter precipitation, SWE on Apr 1, annual, spring and winter runoff, average winter temperature (T) and SWE/P fraction. We also did correlation analysis between SWE and P as well as SWE and T. In addition, we used detrended temperature data to force the VIC model in order to analyze the role of climate change in SWE and runoff. Our results show that while the decreasing trend in SWE and earlier runoff peak in the year are related to long-term warming climate, there is no significant trend in winter P and there are lots of variability in the record of all variables. While this year's anomalously warm weather might have exacerbated the ongoing 3-year drought (and winter 2013-14 in particular), we conclude that natural variability is the main cause.

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.

Plant Responses to Climate Change: The Case Study of Betulaceae and Poaceae Pollen Seasons (Northern Italy, Vignola, Emilia-Romagna)

PubMed Central

Mercuri, Anna Maria; Torri, Paola; Fornaciari, Rita; Florenzano, Assunta

2016-01-01

Aerobiological data have especially demonstrated that there is correlation between climate warming and the pollination season of plants. This paper focuses on airborne pollen monitoring of Betulaceae and Poaceae, two of the main plant groups with anemophilous pollen and allergenic proprieties in Northern Italy. The aim is to investigate plant responses to temperature variations by considering long-term pollen series. The 15-year aerobiological analysis is reported from the monitoring station of Vignola (located near Modena, in the Emilia-Romagna region) that had operated in the years 1990–2004 with a Hirst spore trap. The Yearly Pollen Index calculated for these two botanical families has shown contrasting trends in pollen production and release. These trends were well identifiable but fairly variable, depending on both meteorological variables and anthropogenic causes. Based on recent reference literature, we considered that some oscillations in pollen concentration could have been a main effect of temperature variability reflecting global warming. The duration of pollen seasons of Betulaceae and Poaceae, depending on the different species included in each family, has not unequivocally been determined. Phenological responses were particularly evident in Alnus and especially in Corylus as a general moving up of the end of pollination. The study shows that these trees can be affected by global warming more than other, more tolerant, plants. The research can be a contribution to the understanding of phenological plant responses to climate change and suggests that alder and hazelnut trees have to be taken into high consideration as sensible markers of plant responses to climate change. PMID:27929423

Plant Responses to Climate Change: The Case Study of Betulaceae and Poaceae Pollen Seasons (Northern Italy, Vignola, Emilia-Romagna).

PubMed

Mercuri, Anna Maria; Torri, Paola; Fornaciari, Rita; Florenzano, Assunta

2016-12-06

Aerobiological data have especially demonstrated that there is correlation between climate warming and the pollination season of plants. This paper focuses on airborne pollen monitoring of Betulaceae and Poaceae, two of the main plant groups with anemophilous pollen and allergenic proprieties in Northern Italy. The aim is to investigate plant responses to temperature variations by considering long-term pollen series. The 15-year aerobiological analysis is reported from the monitoring station of Vignola (located near Modena, in the Emilia-Romagna region) that had operated in the years 1990-2004 with a Hirst spore trap. The Yearly Pollen Index calculated for these two botanical families has shown contrasting trends in pollen production and release. These trends were well identifiable but fairly variable, depending on both meteorological variables and anthropogenic causes. Based on recent reference literature, we considered that some oscillations in pollen concentration could have been a main effect of temperature variability reflecting global warming. The duration of pollen seasons of Betulaceae and Poaceae, depending on the different species included in each family, has not unequivocally been determined. Phenological responses were particularly evident in Alnus and especially in Corylus as a general moving up of the end of pollination. The study shows that these trees can be affected by global warming more than other, more tolerant, plants. The research can be a contribution to the understanding of phenological plant responses to climate change and suggests that alder and hazelnut trees have to be taken into high consideration as sensible markers of plant responses to climate change.

Online Impact Prioritization of Essential Climate Variables on Climate Change

NASA Astrophysics Data System (ADS)

Forsythe-Newell, S. P.; Barkstrom, B. B.; Roberts, K. P.

2007-12-01

The National Oceanic & Atmospheric Administration (NOAA)'s NCDC Scientific Data Stewardship (SDS) Team has developed an online prototype that is capable of displaying the "big picture" perspective of all Essential Climate Variable (ECV) impacts on society and value to the IPCC. This prototype ECV-Model provides the ability to visualize global ECV information with options to drill down in great detail. It offers a quantifiable prioritization of ECV impacts that potentially may significantly enhance collaboration with respect to dealing effectively with climate change. The ECV-Model prototype assures anonymity and provides an online input mechanism for subject matter experts and decision makers to access, review and submit: (1) ranking of ECV"s, (2) new ECV's and associated impact categories and (3) feedback about ECV"s, satellites, etc. Input and feedback are vetted by experts before changes or additions are implemented online. The SDS prototype also provides an intuitive one-stop web site that displays past, current and planned launches of satellites; and general as well as detailed information in conjunction with imagery. NCDC's version 1.0 release will be available to the public and provide an easy "at-a-glance" interface to rapidly identify gaps and overlaps of satellites and associated instruments monitoring climate change ECV's. The SDS version 1.1 will enhance depiction of gaps and overlaps with instruments associated with In-Situ and Satellites related to ECVs. NOAA's SDS model empowers decision makers and the scientific community to rapidly identify weaknesses and strengths in monitoring climate change ECV's and potentially significantly enhance collaboration.

600 yr High-Resolution Climate Reconstruction of the Atlantic Multidecadal Oscillation deduced from a Puerto Rican Speleothem

NASA Astrophysics Data System (ADS)

Vieten, Rolf; Winter, Amos; Scholz, Denis; Black, David; Spoetl, Christoph; Winterhalder, Sophie; Koltai, Gabriella; Schroeder-Ritzrau, Andrea; Terzer, Stefan; Zanchettin, Davide; Mangini, Augusto

2016-04-01

A multi-proxy speleothem study tracks the regional hydrological variability in Puerto Rico and highlights its close relation to the Atlantic Multidecadal Oscillation (AMO) describing low-frequency sea-surface temperature (SST) variability in the North Atlantic ocean. Our proxy record extends instrumental observations 600 years into the past, and reveals the range of natural hydrologic variability for the region. A detailed interpretation and understanding of the speleothem climate record is achieved by the combination of multi-proxy measurements, thin section petrography, XRD analysis and cave monitoring results. The speleothem was collected in Cueva Larga, a one mile-long cave system that has been monitored since 2012. MC-ICPMS 230Th/U-dating reveals that the speleothem grew constantly over the last 600 years. Trace element ratios (Sr/Ca and Mg/Ca) as well as stable isotope ratios (δ18O and δ13C) elucidate significant changes in atmospheric precipitation at the site. Monthly cave monitoring results demonstrate that the epikarst system responds to multi-annual changes in seepage water recharge. The drip water isotope and trace element composition lack short term or seasonal variability. This hydrological system creates favorable conditions to deduce decadal climate variability from Cueva Larga's climate record. The speleothem time series mimics the most recent AMO reconstruction over the last 200 years (Svendsen et al., 2014) with a time lag of 10-20 years. The lag seems to results from slow atmospheric signal transmission through the epikarst but the effect of dating uncertainties cannot be ruled out. Warm SSTs in the North Atlantic are related to drier conditions in Puerto Rico. During times of decreased rainfall a relative increase in prior calcite precipitation seems to be the main process causing increased Mg/Ca trace element ratios. High trace element ratios correlate to higher δ13C values. The increase in both proxies indicates a shift towards time periods of decreased rainfall. Before 1800 there were two intervals of increased Mg/Ca and δ13C values (dryer conditions) lasting several decades in our speleothem record centered around 1680 CE and 1470 CE. The elevated ratios indicate that drier conditions than present may have occurred in the region during periods of warm Atlantic surface waters.

600 yr High-Resolution Climate Reconstruction of the Atlantic Multidecadal Variability deduced from a Puerto Rican Speleothem

NASA Astrophysics Data System (ADS)

Winter, A.; Vieten, R.

2015-12-01

A multi-proxy speleothem study tracks the regional hydrological variability in Puerto Rico and highlights its close relation to the Atlantic Multidecadal Oscillation. Our proxy record extends instrumental observations 600 years into the past, and reveals the range of natural hydrologic variability for the region. A detailed interpretation and understanding of the speleothem climate record is achieved by the combination of multi-proxy measurements, thin section petrography, XRD analysis and cave monitoring results. The speleothem was collected in Cueva Larga, a one mile-long cave system that has been monitored since 2012. MC-ICPMS 230Th/U-dating reveals that the speleothem grew constantly over the last 600 years. Trace element ratios (Sr/Ca and Mg/Ca) as well as stable isotope ratios (δ18O and δ13C) elucidate significant changes in atmospheric precipitation at the site. Monthly cave monitoring results demonstrate that the epikarst system responds to multi-annual changes in seepage water recharge. The drip water isotope and trace element composition lack short term or seasonal variability. This hydrological system creates favorable conditions to deduce decadal climate variability from Cueva Larga's climate record. The speleothem time series mimics the most-recently published AMO reconstruction over the last 200 years with a time lag of 10-20 years. The time lag seems to results from slow atmospheric signal transmission through the epikarst but the effect of dating uncertainties cannot be ruled out. Warm SSTs in the North Atlantic are related to drier conditions in Puerto Rico. During times of decreased rainfall a relative increase in prior calcite precipitation seems to be the main process causing increased Mg/Ca trace element ratios. High trace element ratios correlate to higher δ13C values. The increase in both proxies indicates a shift towards time periods of decreased rainfall. Over the past 600 years there are two intervals of increased Mg/Ca and δ13C values lasting several decades in our speleothem record. They are centered around 1680 CE and 1470 CE. The elevated ratios indicate that drier conditions than present occurred in the region during periods of warm Atlantic surface waters. This may be a precursor of conditions now and to come.

Analysis of Water Use Efficiency derived from MODIS satellite image in Northeast Asia

NASA Astrophysics Data System (ADS)

Park, J.; Jang, K.; Kang, S.

2014-12-01

Water Use Efficiency (WUE) is defined as ratio of evapotranspriation (ET) to gross primary productivity (GPP). It can detect the changes of ecosystem properties due to the variability of enviromental condition, and provide a chance to understand the linkage between carbon and water processes in terrestrial ecosystem. In a changing climate, the understanding of ecosystem functional responses to climate variability is crucial for evaluating effect. However, continental or sub-continental scale WUE analysis is were rare. In this study, WUE was estimated in the Northeast Asia using satellite data from 2003 to 2010. ET and GPP were estimated using various MODIS products. The estimated ET and GPP showed favorable agreements with flux tower observations. WUE in the study domain showed considerable variations according to the plant functional types and climatic and elevational gradients. The results produced in this study indicate that satellite remote sensing provides a useful tool for monitoring variability of terrestrial ecosystem functions.

Integrating Climate and Ecosystem-Response Sciences in Temperate Western North American Mountains: The CIRMOUNT Initiative

NASA Astrophysics Data System (ADS)

Millar, C. I.; Fagre, D. B.

2004-12-01

Mountain regions are uniquely sensitive to changes in climate, vulnerable to climate effects on biotic and physical factors of intense social concern, and serve as critical early-warning systems of climate impacts. Escalating demands on western North American (WNA) mountain ecosystems increasingly stress both natural resources and rural community capacities; changes in mountain systems cascade to issues of national concern. Although WNA has long been a focus for climate- and climate-related environmental research, these efforts remain disciplinary and poorly integrated, hindering interpretation into policy and management. Knowledge is further hampered by lack of standardized climate monitoring stations at high-elevations in WNA. An initiative is emerging as the Consortium for Integrated Climate Research in Western Mountains (CIRMOUNT) whose primary goal is to improve knowledge of high-elevation climate systems and to better integrate physical, ecological, and social sciences relevant to climate change, ecosystem response, and natural-resource policy in WNA. CIRMOUNT seeks to focus research on climate variability and ecosystem response (progress in understanding synoptic scale processes) that improves interpretation of linkages between ecosystem functions and human processing (progress in understanding human-environment integration), which in turn would yield applicable information and understanding on key societal issues such as mountains as water towers, biodiversity, carbon forest sinks, and wildland hazards such as fire and forest dieback (progress in understanding ecosystem services and key thresholds). Achieving such integration depends first on implementing a network of high-elevation climate-monitoring stations, and linking these with integrated ecosystem-response studies. Achievements since 2003 include convening the 2004 Mountain Climate Sciences Symposium (1, 2) and several special sessions at technical conferences; initiating a biennial mountain climate research symposium (MTNCLIM), the first to be held in spring 2005; developing a strategy for climate-monitoring in WNA; installing and networking high-elevation (>3000m) climate-monitoring stations; and completing three target regions (Glacier National Park, MT; Sierra Nevada and White Mountains, CA) of the international GLORIA (Global Observation Research Initiative in Alpine Environments) plant-monitoring project, the first in WNA. CIRMOUNT emphasizes integration at the regional scale in WNA, collaborating with and complementing projects such as the Western Mountain Initiative, whose mandate is more targeted than CIRMOUNT's, and global programs such as GLORIA and the international Mountain Research Initiative. Achievement of continuing success in WNA hinges on the capacity to secure long-term funding and institutional investment. (1) See associated URL for paper and poster pdfs (2) Discussing the future of western U.S. mountains, climate change, and ecosystems. EOS 31 August 2004, 85(35), p. 329

Global Water Clarity: Continuing a Century-Long Monitoring

EPA Science Inventory

Aquatic systems worldwide are changing due to increasing climate variability and human activities, yet it is difficult to capture such temporal changes without standardized long-term observations [Boyce et al. 2015, Barton et al. 2016]. Unlike the well-established Keeling curve t...

Have bird distributions shifted along an elevational gradient on a tropical mountain?

PubMed

Campos-Cerqueira, Marconi; Arendt, Wayne J; Wunderle, Joseph M; Aide, T Mitchell

2017-12-01

An upward shift in elevation is one of the most conspicuous species responses to climate change. Nevertheless, downward shifts and, apparently, the absences of response have also been recently reported. Given the growing evidence of multiple responses of species distributions due to climate change and the paucity of studies in the tropics, we evaluated the response of a montane bird community to climate change, without the confounding effects of land-use change. To test for elevational shifts, we compared the distribution of 21 avian species in 1998 and 2015 using occupancy models. The historical data set was based on point counts, whereas the contemporary data set was based on acoustic monitoring. We detected a similar number of species in historical (36) and contemporary data sets (33). We show an overall pattern of no significant change in range limits for most species, although there was a significant shift in the range limit of eight species (38%). Elevation limits shifted mostly upward, and this pattern was more common for upper than lower limits. Our results highlight the variability of species responses to climate change and illustrate how acoustic monitoring provides an easy and powerful way to monitor animal populations along elevational gradients.

Advancing drought monitoring using a Small Unmanned Aerial System (sUAS) in a changing climate

NASA Astrophysics Data System (ADS)

Ryu, J.

2016-12-01

Drought as a natural hazard, increasingly threatens the sustainability of regional water resources around the world. Given current trends in climate variability and change, droughts are likely to continue and increase. One of the effective ways to mitigate drought impacts may be to use a Small Unmanned Aerial System (sUAS) to improve understanding of the factors that drive the onset and development of drought conditions at local levels would enable planners and end users to more effectively manage and meter out limited water resources. During the presentation, the author will propose a methodological approach to apply sUAS for drought monitoring along with federal regulations and policies.

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

PubMed

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

2017-05-22

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

Evaluation and time series analysis of mountain snow from MODIS and VIIRS fractional snow cover products

NASA Astrophysics Data System (ADS)

Bormann, K.; Rittger, K.; Painter, T. H.

2016-12-01

The continuation of large-scale snow cover records into the future is crucial for monitoring the impacts of global pressures such as climate change and weather variability on the cryosphere. With daily MODIS records since 2000 from a now ageing MODIS constellation (Terra & Aqua) and daily VIIRS records since 2012 from the Suomi-NPP platform, the consistency of information between the two optical sensors must be understood. First, we evaluated snow cover maps derived from both MODIS and VIIRS retrievals with coincident cloud-free Landsat 8 OLI maps across a range of locations. We found that both MODIS and VIIRS snow cover maps show similar errors when evaluated with Landsat OLI retrievals. Preliminary results also show a general agreement in regional snowline between the two sensors that is maintained during the spring snowline retreat where the proportion of mixed pixels is increased. The agreement between sensors supports the future use of VIIRS snow cover maps to continue the long-term record beyond the lifetime of MODIS. Second, we use snowline elevation to quantify large scale snow cover variability and to monitor potential changes in the rain/snow transition zone where climate change pressures may be enhanced. Despite the large inter-annual variability that is often observed in snow metrics, we expect that over the 16-year time series we will see a rise in seasonal elevation of the snowline and consequently an increasing rain/snow transition boundary in mountain environments. These results form the basis for global snowline elevation monitoring using optical remote sensing data and highlight regional differences in snowline elevation dynamics. The long-term variability in observed snowline elevation provides a recent climatology of mountain snowpack across several regions that will likely to be of interest to those interested in climate change impacts in mountain environments. This work will also be of interest to existing users of MODSCAG and VIIRSCAG snow cover products and those working in remote sensing of the mountain snowpack.

Interaction between urbanization and climate variability amplifies watershed nitrate export in Maryland

USGS Publications Warehouse

Kaushal, S.S.; Groffman, P.M.; Band, L.E.; Shields, C.A.; Morgan, R.P.; Palmer, Margaret A.; Belt, K.T.; Swan, C.M.; Findlay, S.E.G.; Fisher, G.T.

2008-01-01

We investigated regional effects of urbanization and land use change on nitrate concentrations in approximately 1,000 small streams in Maryland during record drought and wet years in 2001-2003. We also investigated changes in nitrate-N export during the same time period in 8 intensively monitored small watersheds across an urbanization gradient in Baltimore, Maryland. Nitrate-N concentrations in Maryland were greatest in agricultural streams, urban streams, and forest streams respectively. During the period of record drought and wet years, nitrate-N exports in Baltimore showed substantial variation in 6 suburban/urban streams (2.9-15.3 kg/ha/y), 1 agricultural stream (3.4-38.9 kg/ha/y), and 1 forest stream (0.03-0.2 kg/ ha/y). Interannual variability was similar for small Baltimore streams and nearby well-monitored tributaries and coincided with record hypoxia in Chesapeake Bay. Discharge-weighted mean annual nitrate concentrations showed a variable tendency to decrease/increase with changes in annual runoff, although total N export generally increased with annual runoff. N retention in small Baltimore watersheds during the 2002 drought was 85%, 99%, and 94% for suburban, forest, and agricultural watersheds, respectively, and declined to 35%, 91%, and 41% during the wet year of 2003. Our results suggest that urban land use change can increase the vulnerability of ecosystem nitrogen retention functions to climatic variability. Further work is necessary to characterize patterns of nitrate-N export and retention in small urbanizing watersheds under varying climatic conditions to improve future forecasting and watershed scale restoration efforts aimed at improving nitrate-N retention. ?? 2008 American Chemical Society.

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

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

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

Cloud cover archiving on a global scale - A discussion of principles

NASA Technical Reports Server (NTRS)

Henderson-Sellers, A.; Hughes, N. A.; Wilson, M.

1981-01-01

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Hydrology of the North Klondike River: carbon export, water balance and inter-annual climate influences within a sub-alpine permafrost catchment.

PubMed

Lapp, Anthony; Clark, Ian; Macumber, Andrew; Patterson, Tim

2017-10-01

Arctic and sub-arctic watersheds are undergoing significant changes due to recent climate warming and degrading permafrost, engendering enhanced monitoring of arctic rivers. Smaller catchments provide understanding of discharge, solute flux and groundwater recharge at the process level that contributes to an understanding of how larger arctic watersheds are responding to climate change. The North Klondike River, located in west central Yukon, is a sub-alpine permafrost catchment, which maintains an active hydrological monitoring station with a record of >40 years. In addition to being able to monitor intra-annual variability, this data set allows for more complex analysis of streamflow records. Streamflow data, geochemistry and stable isotope data for 2014 show a groundwater-dominated system, predominantly recharged during periods of snowmelt. Radiocarbon is shown to be a valuable tracer of soil zone recharge processes and carbon sources. Winter groundwater baseflow contributes 20 % of total annual discharge, and accounts for up to 50 % of total river discharge during the spring and summer months. Although total stream discharge remains unchanged, mean annual groundwater baseflow has increased over the 40-year monitoring period. Wavelet analysis reveals a catchment that responds to El Niño and longer solar cycles, as well as climatic shifts such as the Pacific Decadal Oscillation. Dedicated to Professor Peter Fritz on the occasion of his 80th birthday.

A global satellite assisted precipitation climatology

USGS Publications Warehouse

Funk, Christopher C.; Verdin, Andrew P.; Michaelsen, Joel C.; Pedreros, Diego; Husak, Gregory J.; Peterson, P.

2015-01-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high resolution (0.05°) global precipitation climatologies that perform reasonably well in data sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0,http://dx.doi.org/10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

A global satellite-assisted precipitation climatology

NASA Astrophysics Data System (ADS)

Funk, C.; Verdin, A.; Michaelsen, J.; Peterson, P.; Pedreros, D.; Husak, G.

2015-10-01

Accurate representations of mean climate conditions, especially in areas of complex terrain, are an important part of environmental monitoring systems. As high-resolution satellite monitoring information accumulates with the passage of time, it can be increasingly useful in efforts to better characterize the earth's mean climatology. Current state-of-the-science products rely on complex and sometimes unreliable relationships between elevation and station-based precipitation records, which can result in poor performance in food and water insecure regions with sparse observation networks. These vulnerable areas (like Ethiopia, Afghanistan, or Haiti) are often the critical regions for humanitarian drought monitoring. Here, we show that long period of record geo-synchronous and polar-orbiting satellite observations provide a unique new resource for producing high-resolution (0.05°) global precipitation climatologies that perform reasonably well in data-sparse regions. Traditionally, global climatologies have been produced by combining station observations and physiographic predictors like latitude, longitude, elevation, and slope. While such approaches can work well, especially in areas with reasonably dense observation networks, the fundamental relationship between physiographic variables and the target climate variables can often be indirect and spatially complex. Infrared and microwave satellite observations, on the other hand, directly monitor the earth's energy emissions. These emissions often correspond physically with the location and intensity of precipitation. We show that these relationships provide a good basis for building global climatologies. We also introduce a new geospatial modeling approach based on moving window regressions and inverse distance weighting interpolation. This approach combines satellite fields, gridded physiographic indicators, and in situ climate normals. The resulting global 0.05° monthly precipitation climatology, the Climate Hazards Group's Precipitation Climatology version 1 (CHPclim v.1.0, doi:10.15780/G2159X), is shown to compare favorably with similar global climatology products, especially in areas with complex terrain and low station densities.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity.

PubMed

Bustamante, Mercedes M C; Roitman, Iris; Aide, T Mitchell; Alencar, Ane; Anderson, Liana O; Aragão, Luiz; Asner, Gregory P; Barlow, Jos; Berenguer, Erika; Chambers, Jeffrey; Costa, Marcos H; Fanin, Thierry; Ferreira, Laerte G; Ferreira, Joice; Keller, Michael; Magnusson, William E; Morales-Barquero, Lucia; Morton, Douglas; Ometto, Jean P H B; Palace, Michael; Peres, Carlos A; Silvério, Divino; Trumbore, Susan; Vieira, Ima C G

2016-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process-oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large-scale remote-sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate-change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation. © 2015 John Wiley & Sons Ltd.

CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture.

PubMed

Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

2017-02-01

CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; www.cropwatch.com.cn , Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

CropWatch agroclimatic indicators (CWAIs) for weather impact assessment on global agriculture

NASA Astrophysics Data System (ADS)

Gommes, René; Wu, Bingfang; Zhang, Ning; Feng, Xueliang; Zeng, Hongwei; Li, Zhongyuan; Chen, Bo

2017-02-01

CropWatch agroclimatic indicators (CWAIs) are a monitoring tool developed by the CropWatch global crop monitoring system in the Chinese Academy of Sciences (CAS; http://www.cropwatch.com.cn, Wu et al Int J Digital Earth 7(2):113-137, 2014, Wu et al Remote Sens 7:3907-3933, 2015). Contrary to most other environmental and agroclimatic indicators, they are "agronomic value-added", i.e. they are spatial values averaged over agricultural areas only and they include a weighting that enhances the contribution of the areas with the largest production potential. CWAIs can be computed for any time interval (starting from dekads) and yield one synthetic value per variable over a specific area and time interval, for instance a national annual value. Therefore, they are very compatible with socio-economic and other variables that are usually reported at regular time intervals over administrative units, such as national environmental or agricultural statistics. Two of the CWAIs are satellite-based (RAIN and Photosynthetically Active radiation, PAR) while the third is ground based (TEMP, air temperature); capitals are used when specifically referring to CWAIs rather than the climate variables in general. The paper first provides an overview of some common agroclimatic indicators, describing their procedural, systemic and normative features in subsequent sections, following the terminology of Binder et al Environ Impact Assess Rev 30:71-81 (2010). The discussion focuses on the systemic and normative aspects: the CWAIs are assessed in terms of their coherent description of the agroclimatic crop environment, at different spatial scales (systemic). The final section shows that the CWAIs retain key statistical properties of the underlying climate variables and that they can be compared to a reference value and used as monitoring and early warning variables (normative).

Climate variability drives recent tree mortality in Europe.

PubMed

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

2017-11-01

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

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

PubMed Central

Otmani del Barrio, Mariam

2017-01-01

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

Review of Malaria Epidemics in Ethiopia using Enhanced Climate Services (ENACTS)

NASA Astrophysics Data System (ADS)

Muhammad, A.

2015-12-01

Malaria is a disease directly linked to temperature and rainfall. In Ethiopia, the influence of climate variables on malaria transmission and the subsequent role of ENSO in the rise of malaria incidence are becoming more recognized. Numerous publications attest to the extreme sensitivity of malaria to climate in Ethiopia. The majority of large-scale epidemics in the past were associated with climatic factors such as temperature and rainfall. However, there is limited information on climate variability and ENSO at the district level to aid in public health decision-making. Since 2008, the National Meteorogy Agency (NMA) and the International Research Institute for Climate and Society (IRI) have been collaborating on improving climate services in Ethiopia. This collaboration spurred the implementation of the Enhancing National Climate Services (ENACTS) initiative and the creation of the IRI Data Library (DL) NMA Ethiopia Maproom. ENACTS provides reliable and readily accessible climate data at high resolutions and the Maproom uses ENACTS to build a collection of maps and other figures that monitor climate and societal conditions at present and in the recent past (1981-2010). A recent analysis exploring the relationship of rainfall and temperature ENACTS products to malaria epidemics in proceeding rainy seasons within 12 woredas found above normal temperature anomalies to be more readily associated with epidemics when compared to above normal rainfall anomalies, regardless of the ENSO phase (Figure 1-2).

Using Spacecraft in Climate and Natural Disasters Registration

NASA Astrophysics Data System (ADS)

Sokol, Galyna; Kotlov, Vladyslav; Khorischenko, Oleksandr; Davydova, Angelica; Heti, Kristina

2017-04-01

Since the beginning of the space age it become possible the global monitoring of the planet Earth's state. Since the second half of the 20th century there are observations of the atmosphere's state and the Earth's climate have been held by a spacecraft. Also become possible large-scale monitoring of climate change. An attempt was made to define the role of infrasound in the interaction between a space weather, climate and biosphere of the Earth using spacecraft sensors recording. Many countries are involving in the detection of earthquakes, predicting volcanic eruptions and floods and also the monitoring of irregular solar activity. Understanding this leads to the conclusion that international cooperation for the protection of humanity is not only a political priority in the international arena, but also a question of the quality of living standards of any state. Commonly known following monitoring systems: Disaster Monitoring Constellation (DMC), FUEGO program (Spain), Sentinel-Asia program (Japan) and International aerospace system for monitoring of global phenomena (MAKCM, Russia). The Disaster Monitoring Constellation for International Imaging (DMCii) consists of a number of remote sensing satellites constructed by Surrey Satellite Technology Ltd (SSTL) and operated for the Algerian, Nigerian, Turkish, British and Chinese governments by DMC International Imaging. The DMC has monitored the effects and aftermath of the Indian Ocean Tsunami (December 2004), Hurricane Katrina (August 2005), and many other floods, fires and disasters. The individual DMC satellites are: 1. First generation satellites (AlSAT-1 - Algeria, BilSAT - Turkey, NigeriaSAT-1 - Nigeria, UK-DMC - United Kingdom); 2. Second generation satellites (Beijing - China, UK-DMC 2 - United Kingdom, Deimos-1 - Spanish commercial, NigeriaSAT-2 and NigeriaSAT-X). The sun-synchronous orbits of these satellites are coordinated so that the satellites follow each other around an orbital plane, ascending north over the Equator at 10:15 am local time (and 10:30 am local time for Beijing-1). Some of these satellites also include other imaging payloads and experimental payloads: onboard hardware-based image compression (on BilSAT), a GPS reflectometry experiment and onboard Internet router (on the UK-DMC satellite). The DMC satellites are notable for communicating with their ground stations using the Internet Protocol for payload data transfer and command and control, so extending the Internet into space, and allowing experiments with the Interplanetary Internet to be carried out. Many of the technologies used in the design of the DMC satellites, including Internet Protocol use, were tested in space beforehand on SSTL's earlier UoSAT-12 satellite. Currently, there is a great need to establish combining space and ground-based observation systems that will accurately capture key climate variables on a scale from regional to global and stable functioning for decades to determine climate variability and trends. With the help of modern computer systems were calculated moving of infrasonic waves in the atmosphere. This data can be used to predict the weather.

Temporal variability and annual budget of inorganic dissolved matter in Andean Pacific Rivers located along a climate gradient from northern Ecuador to southern Peru

NASA Astrophysics Data System (ADS)

Moquet, Jean-Sébastien; Guyot, Jean-Loup; Morera, Sergio; Crave, Alain; Rau, Pedro; Vauchel, Philippe; Lagane, Christelle; Sondag, Francis; Lavado, Casimiro Waldo; Pombosa, Rodrigo; Martinez, Jean-Michel

2018-01-01

In Ecuador and Peru, geochemical information from Pacific coastal rivers is limited and scarce. Here, we present an unedited database of major element concentrations from five HYBAM observatory stations monitored monthly between 4 and 10 years, and the discrete sampling of 23 Andean rivers distributed along the climate gradient of the Ecuadorian and Peruvian Pacific coasts. Concentration (C) vs. discharge (Q) relationships of the five monitored basins exhibit a clear dilution behavior for evaporites and/or pyrite solutes, while the solute concentrations delivered by other endmembers are less variable. Spatially, the annual specific fluxes for total dissolved solids (TDS), Ca2+, HCO3-, K+, Mg2+, and SiO2 are controlled on the first order by runoff variability, while Cl-, Na+ and SO42- are controlled by the occurrence of evaporites and/or pyrite. The entire Pacific basin in Ecuador and Peru exported 30 Mt TDS·yr-1, according to a specific flux of ∼70 t·km-2·yr-1. This show that, even under low rainfall conditions, this orogenic context is more active, in terms of solute production, than the global average.

Using hydrologic landscape classification to assess streamflow vulnerability to changes in climate

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

An assessment of streamflow vulnerability to climate using Hydrologic Landscape classification

EPA Science Inventory

Identifying regions with similar hydrology is useful for assessing water quality and quantity across the U.S., especially areas that are difficult or costly to monitor. For example, hydrologic landscapes (HLs) have been used to map streamflow variability and assess the spatial di...

Temporal variability of the Atlantic meridional overturning circulation at 26.5 degrees N.

PubMed

Cunningham, Stuart A; Kanzow, Torsten; Rayner, Darren; Baringer, Molly O; Johns, William E; Marotzke, Jochem; Longworth, Hannah R; Grant, Elizabeth M; Hirschi, Joël J-M; Beal, Lisa M; Meinen, Christopher S; Bryden, Harry L

2007-08-17

The vigor of Atlantic meridional overturning circulation (MOC) is thought to be vulnerable to global warming, but its short-term temporal variability is unknown so changes inferred from sparse observations on the decadal time scale of recent climate change are uncertain. We combine continuous measurements of the MOC (beginning in 2004) using the purposefully designed transatlantic Rapid Climate Change array of moored instruments deployed along 26.5 degrees N, with time series of Gulf Stream transport and surface-layer Ekman transport to quantify its intra-annual variability. The year-long average overturning is 18.7 +/- 5.6 sverdrups (Sv) (range: 4.0 to 34.9 Sv, where 1 Sv = a flow of ocean water of 10(6) cubic meters per second). Interannual changes in the overturning can be monitored with a resolution of 1.5 Sv.

Air temperature, wind speed, and wind direction in the National Petroleum Reserve—Alaska and the Arctic National Wildlife Refuge, 1998–2011

USGS Publications Warehouse

Urban, Frank E.; Clow, Gary D.

2013-01-01

This report provides air temperature, wind speed, and wind direction data collected on Federal lands in Arctic Alaska over the period August 1998 to July 2011 by the U.S. Department of the Interior's climate monitoring array, part of the Global Terrestrial Network for Permafrost. In addition to presenting data, this report also describes monitoring, data collection, and quality control methodology. This array of 16 monitoring stations spans 68.5°N to 70.5°N and 142.5°W to 161°W, an area of roughly 150,000 square kilometers. Climate summaries are presented along with provisional quality-controlled data. Data collection is ongoing and includes several additional climate variables to be released in subsequent reports, including ground temperature and soil moisture, snow depth, rainfall, up- and downwelling shortwave radiation, and atmospheric pressure. These data were collected by the U.S. Geological Survey in close collaboration with the Bureau of Land Management and the U.S. Fish and Wildlife Service.

River chemistry as a monitor of Yosemite Park mountain hydroclimates

USGS Publications Warehouse

Peterson, David; Smith, Richard; Hager, Stephen; Hicke, Jeffrey A.; Dettinger, Michael; Huber, King

2005-01-01

Climate is the major source of variability in U.S. and global water resources. For example, large-scale variations in the global atmosphere and the Pacific Ocean are responsible for much of the variability in river discharge in Hawaii, Alaska, the U.S. Pacific Northwest, and the U.S. Southwest [Cayan and Peterson, 1989], and thus are closely linked to water and energy resources of the western United States [Cayan et al., 2003].

Taimyr Reindeer and Environmental Change: Monitoring Wild Reindeer Migration in Changing Natural and Social Environments

NASA Astrophysics Data System (ADS)

Petrov, A. N.

2016-12-01

The Taimyr Reindeer Herd (TRH) is both the largest and the longest monitored wild reindeer herd in Eurasia. An important part of Arctic ecosystems and Indigenous livelihood, wild reindeer have been continuously monitored for almost 50 years. During this time, herds have exhibited large changes in size and these changes have been recorded in almost all herds across the animal's range. An increasing number of wild reindeer in the Soviet times was followed by a significant population loss in the last decade. In addition, recent monitoring revealed substantial shifts in the distribution of wild populations. The decline in wild reindeer is likely related to natural cycles and changes in the Arctic environment caused by climate variability and anthropogenic activity. This study investigates patterns and possible drives of reindeer population dynamics in space and time. We identify key climatic factors, possible relationships with biomass dynamics, as well as with hunting practices and other human impacts.

The Hydrological Response of Snowmelt Dominated Catchments to Climate Change

NASA Astrophysics Data System (ADS)

Arrigoni, A. S.; Moore, J. N.

2007-12-01

Hydrological systems dominated by snowmelt discharge contribute greater than half the freshwater resource available to the western United States. Globally, the contribution of mountain discharge to total runoff is twice the expected for their geographical coverage. Therefore, snowmelt dominated mountain catchments have proportionally a more prominent role than other systems to our freshwater resource. A changing climate, or even a more variable climate, could have a significant impact on these systems, and consequently on our freshwater resource. Ergo, a better understanding of how changes and variations in climate will influence mountain catchments is a necessity for improving future water management under predicted/proposed climate change. The research presented here is a first order analysis to improve our understanding of these systems by monitoring and analyzing high mountain catchments along the entirety of the Mission Mountain Front, Montana USA. The Mission Mountain Range is an ideal location for conducting this research as it runs directly north to south with elevations progressively increasing from 7600 feet in the northern section, to over 9700 feet at the southern end. The lower elevation catchments will be used as surrogates for variable climate change, while the high elevation catchments will be used as surrogates for a more stable, cooler, climate regime. We use a combination of USGS and Tribal stream gauges, as well as stage gauge loggers in the headwaters of the catchments, SNOTEL datasets, and weather station datasets. This information is used to determine if, how, and why the snowmelt hydrographs vary between catchments, within the catchments between the upper and lower segments, and the dominant driver or drivers of the hydrograph form in relation to changing climatic variables such as temperature and precipitation. This research will improve current comprehension of how mountain catchments respond to climatic variables, and additionally will expand upon the current understanding of general catchment hydrology.

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling.

PubMed

Arenas-Castro, Salvador; Gonçalves, João; Alves, Paulo; Alcaraz-Segura, Domingo; Honrado, João P

2018-01-01

Global environmental changes are rapidly affecting species' distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species' conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

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.

Continuing the Total and Spectral Solar Irradiance Climate Data Record

NASA Astrophysics Data System (ADS)

Coddington, O.; Pilewskie, P.; Kopp, G.; Richard, E. C.; Sparn, T.; Woods, T. N.

2017-12-01

Radiative energy from the Sun establishes the basic climate of the Earth's surface and atmosphere and defines the terrestrial environment that supports all life on the planet. External solar variability on a wide range of scales ubiquitously affects the Earth system, and combines with internal forcings, including anthropogenic changes in greenhouse gases and aerosols, and natural modes such as ENSO, and volcanic forcing, to define past, present, and future climates. Understanding these effects requires continuous measurements of total and spectrally resolved solar irradiance that meet the stringent requirements of climate-quality accuracy and stability over time. The current uninterrupted 39-year total solar irradiance (TSI) climate data record is the result of several overlapping instruments flown on different missions. Measurement continuity, required to link successive instruments to the existing data record to discern long-term trends makes this important climate data record susceptible to loss in the event of a gap in measurements. While improvements in future instrument accuracy will reduce the risk of a gap, the 2017 launch of TSIS-1 ensures continuity of the solar irradiance record into the next decade. There are scientific and programmatic motivations for addressing the challenges of maintaining the solar irradiance data record beyond TSIS-1. The science rests on well-founded requirements of establishing a trusted climate observing network that can monitor trends in fundamental climate variables. Programmatically, the long-term monitoring of solar irradiance must be balanced within the broader goals of NASA Earth Science. New concepts for a low-risk, cost efficient observing strategy is a priority. New highly capable small spacecraft, low-cost launch vehicles and a multi-decadal plan to provide overlapping TSI and SSI data records are components of a low risk/high reliability plan with lower annual cost than past implementations. This paper provides the justification for prioritizing solar irradiance observations and plans for extending the record into the next two decades that adheres to the rigors of quantifiable methods for meeting objectives.

Remote Sensing Approach to Drought Monitoring to Inform Range Management at the Hopi Tribe and Navajo Nation

NASA Astrophysics Data System (ADS)

El Vilaly, M. M.; Van Leeuwen, W. J.; Didan, K.; Marsh, S. E.; Crimmins, , M. A.

2012-12-01

The Hopi Tribe and Navajo Nation are situated in the Northeastern corner of Arizona in the Colorado River Plateau. For more than a decade, the area has faced extensive and persistent drought conditions that have impacted vegetation communities and local water resources while exacerbating soil erosion. Moreover, these persistent droughts threaten ecosystem services, agriculture, and livestock production activities, and make this region sensitive to inter-annual climate variability and change. The limited hydroclimatic observations, bolstered by numerous anecdotal drought impact reports, indicate that the region has been suffering through an almost 15-year long drought which is threatening its socio-economic development. The objective of this research is to employ remote sensing data to monitor the ongoing drought and inform management and decision-making. The overall goals of this study are to develop a common understanding of the current status of drought across the area in order to understand the existing seasonal and inter-annual relationships between climate variability and vegetation dynamics. To analyze and investigate vegetation responses to climate variability, land use practices, and environmental factors in Hopi and Navajo nation during the last 22 years, a drought assessment framework was developed that integrates climate and topographical data with land surface remote sensing time series data. Multi-sensor Normalized Difference Vegetation Index time series data were acquired from the vegetation index and phenology project (vip.arizona.edu) from 1989 to 2010 at 5.6 km, were analyzed to characterize the intra-annual changes of vegetation, seasonal phenology and inter-annual vegetation response to climate variability and environmental factors. Due to the low number of retrieval obtained from TIMESAT software, we developed a new framework that can maximize the number of retrieval. Four vegetation development stages, annual integrated NDVI (Net Primary Production (NPP)), minimum annual NDVI, maximum annual NDVI, and annual amplitude, were extracted using that new framework. A multi-linear regression has been applied to these vegetation phenology metrics as well as to the relationship between pheno-metrics and environmental variables, to detect potential vegetation changes and to examine the existing relationship between vegetation dynamics and rainfall and elevation gradients. The results suggest that vegetation behavior is foremost governed by rainfall gradients (R-square =0.74). Trend analyses confirmed that around 80 percent of pixels showed a general decline of greenness with confidence level of 95% (p< 0.05), while 4 percent showed a general greening up. Vegetation in the area showed a significant and strong relationship with elevation and precipitation gradients. This correlation was more prominent at mid-elevations, which could be explained by the snowmelt dynamics and hydrological redistribution of water at that elevation. These tools, methods and results can be used to aid in monitoring and understanding climate change and variability impacts on vegetation productivity, ecosystem services, and water resources of the region, and to inform decision-makers and range managers at Hopi Tribe and Navajo nation. Keywords: drought, remote sensing, time series, vegetation dynamics, Hopi Tribe and Navajo Nations

Improving Decision-Making Activities for Meningitis and Malaria

NASA Technical Reports Server (NTRS)

Ceccato, Pietro; Trzaska, Sylwia; Garcia-Pando, Carlos Perez; Kalashnikova, Olga; del Corral, John; Cousin, Remi; Blumenthal, M. Benno; Bell, Michael; Connor, Stephen J.; Thomson, Madeleine C.

2013-01-01

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

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.

Climate and landscape drivers of tree decline in a Mediterranean ecoregion

PubMed Central

Brouwers, Niels C; Mercer, Jack; Lyons, Tom; Poot, Pieter; Veneklaas, Erik; Hardy, Giles

2013-01-01

Climate change and anthropogenic land use are increasingly affecting the resilience of natural ecosystems. In Mediterranean ecoregions, forests and woodlands have shown progressive declines in health. This study focuses on the decline of an endemic woodland tree species, Eucalyptus wandoo (wandoo), occurring in the biodiversity hotspot of southwest Western Australia. We determined the change in health of wandoo stands between 2002 and 2008 across its geographic and climatic range, and associated this change in health with non-biotic variables focusing on: (1) fragment metrics; (2) topography; (3) soil characteristics; and (4) climate. Only fragment metrics and climate variables were found to be significantly related to the observed change in health. Stands that were small with high perimeter/area ratios were found to be most sensitive to health declines. Recent increases in autumn temperatures and decreases in annual rainfall were negatively affecting health of wandoo most prominently in the low rainfall zone of its climatic range. Together, these results suggest the onset of range contraction for this ecologically important species, which is likely to be exacerbated by projected future changes in climate. Our results emphasize the importance of establishing monitoring programs to identify changes in health and decline trends early to inform management strategies, particularly in the sensitive Mediterranean ecoregions. PMID:23403899

Early effects of climate change: do they include changes in vector-borne disease?

PubMed Central

Kovats, R S; Campbell-Lendrum, D H; McMichael, A J; Woodward, A; Cox, J S

2001-01-01

The world's climate appears now to be changing at an unprecedented rate. Shifts in the distribution and behaviour of insect and bird species indicate that biological systems are already responding to this change. It is well established that climate is an important determinant of the spatial and temporal distribution of vectors and pathogens. In theory, a change in climate would be expected to cause changes in the geographical range, seasonality (intra-annual variability), and in the incidence rate (with or without changes in geographical or seasonal patterns). The detection and then attribution of such changes to climate change is an emerging task for scientists. We discuss the evidence required to attribute changes in disease and vectors to the early effects of anthropogenic climate change. The literature to date indicates that there is a lack of strong evidence of the impact of climate change on vector-borne diseases (i.e. malaria, dengue, leishmaniasis, tick-borne diseases). New approaches to monitoring, such as frequent and long-term sampling along transects to monitor the full latitudinal and altitudinal range of specific vector species, are necessary in order to provide convincing direct evidence of climate change effects. There is a need to reassess the appropriate levels of evidence, including dealing with the uncertainties attached to detecting the health impacts of global change. PMID:11516383

State of the Art in Large-Scale Soil Moisture Monitoring

NASA Technical Reports Server (NTRS)

Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.;

Developing Climate Resilience Toolkit Decision Support Training Sectio

NASA Astrophysics Data System (ADS)

Livezey, M. M.; Herring, D.; Keck, J.; Meyers, J. C.

2014-12-01

The Climate Resilience Toolkit (CRT) is a Federal government effort to address the U.S. President's Climate Action Plan and Executive Order for Climate Preparedness. The toolkit will provide access to tools and products useful for climate-sensitive decision making. To optimize the user experience, the toolkit will also provide access to training materials. The National Oceanic and Atmospheric Administration (NOAA) has been building a climate training capability for 15 years. The target audience for the training has historically been mainly NOAA staff with some modified training programs for external users and stakeholders. NOAA is now using this climate training capacity for the CRT. To organize the CRT training section, we collaborated with the Association of Climate Change Officers to determine the best strategy and identified four additional complimentary skills needed for successful decision making: climate literacy, environmental literacy, risk assessment and management, and strategic execution and monitoring. Developing the climate literacy skills requires knowledge of climate variability and change, as well as an introduction to the suite of available products and services. For the development of an environmental literacy category, specific topics needed include knowledge of climate impacts on specific environmental systems. Climate risk assessment and management introduces a process for decision making and provides knowledge on communication of climate information and integration of climate information in planning processes. The strategic execution and monitoring category provides information on use of NOAA climate products, services, and partnership opportunities for decision making. In order to use the existing training modules, it was necessary to assess their level of complexity, catalog them, and develop guidance for users on a curriculum to take advantage of the training resources to enhance their learning experience. With the development of this CRT training section, NOAA has made significant progress in sharing resources with the external community.

Interannual variability of rock glacier surface velocities and its relationship to climatic conditions on a decadal scale: Some insights from the European Alps

NASA Astrophysics Data System (ADS)

Kellerer-Pirklbauer, Andreas; Bodin, Xavier; Delaloye, Reynald; Fischer, Andrea; Gärtner-Roer, Isabelle; Hartl, Lea; Kaufmann, Viktor; Krainer, Karl; Lambiel, Christophe; Mair, Volkmar; Marcer, Marco; Morra di Cella, Umberto; Scapozza, Cristian; Schoeneich, Philippe; Staub, Benno

2017-04-01

Active, inactive and relict rock glaciers are widespread periglacial landforms in the European Alps as revealed by several inventories elaborated for Slovenia, Austria, Switzerland, Italy, and France. Rock glaciers indicate present or past permafrost conditions in mountain environments and hence have a high climatic or paleoclimatic relevance. The monitoring of surface velocities at active rock glaciers has a long tradition in the European Alps with first terrestrial photogrammetric surveys in the Swiss and Austrian Alps already in the 1920s. Since the 1990s velocity monitoring activities have been substantially expanded but also institutionalized. Today, several research groups carry out annual or even continuous monitoring of rock glacier creep at more than 30 rock glaciers in Austria, France, Italy, and Switzerland. In many cases such a kinematic monitoring is jointly accomplished with meteorological and ground temperature monitoring in order to better understand the rock glacier-climate relationships and the reaction of rock glacier behavior to climatic changes. In this contribution we present a synthesis of the main results from long-term monitoring of several rock glaciers in the European Alps with at least annually-repeated data. Similarities but also differences of the movement patterns at the different sites are discussed, while the spatio-temporal pattern of the surface displacement is looked at against the climate context. In general, rock glacier surface velocities in the European Alps have been rather low during the 1980s and 1990s and reached a first peak in 2003/04 followed by a drastic drop until c.2007/08. Since then rock glacier surface velocities increased again with new velocity records in 2015/16 superior to the first peak around 2003/04. These creep rate maxima coincide with the warmest permafrost temperatures ever measured in boreholes and are likely a result of the continuously warm conditions at the ground surface over the past seven years.

Development of a ground hydrology model suitable for global climate modeling using soil morphology and vegetation cover, and an evaluation of remotely sensed information

NASA Technical Reports Server (NTRS)

Zobler, L.; Lewis, R.

1988-01-01

The long-term purpose was to contribute to scientific understanding of the role of the planet's land surfaces in modulating the flows of energy and matter which influence the climate, and to quantify and monitor human-induced changes to the land environment that may affect global climate. Highlights of the effort include the following: production of geo-coded, digitized World Soil Data file for use with the Goddard Institute for Space Studies (GISS) climate model; contribution to the development of a numerical physically-based model of ground hydrology; and assessment of the utility of remote sensing for providing data on hydrologically significant land surface variables.

Assessing Climate Change Within Lake Champlain

NASA Astrophysics Data System (ADS)

Leibensperger, E. M.; Pierce, W.; Mihuc, T.; Myers, L.

2016-12-01

Lake Champlain is experiencing environmental stresses that have caused statistically significant biological, chemical, and physical trends. Such trends have already impacted management strategies within the Lake Champlain basin, which lies within the states of New York and Vermont and province of Quebec. A long-term monitoring program initiated in 1992 has revealed warming of upwards of 0.7°C per decade within certain regions of the lake; much faster than observed local atmospheric warming. Here we analyze the observed lake warming in the context of atmospheric variability and assess its uncertainty given monitoring frequency (biweekly to monthly), variable seasonal and hourly observation timing, and synoptic variability of lake dynamics. To address these issues, we use observations from a June-October 2016 deployment of a data buoy on Lake Champlain containing a 1-meter spaced thermistor chain and surface weather station. These new observations, and reanalysis of intensive monitoring during a campaign in 1993, indicate that synoptic variability of lake thermal structure lowers confidence in trends derived from infrequent observations. However, principal component analysis of lake thermal structure reveals two primary modes of variability that are predictable from atmospheric conditions, presenting an opportunity to improve interpretation of existing and future observations.

The impact of warming on greenhouse gas fluxes: an experimental comparison which reveals the varied response of ecosystems to climate change.

NASA Astrophysics Data System (ADS)

Stockdale, James; Ineson, Philip

2016-04-01

Modelled predictions of the response of terrestrial systems to climate change are highly variable, yet the response of net ecosystem exchange (NEE) is a vital ecosystem behaviour to understand due to its inherent feedback to the carbon cycle. The establishment and subsequent monitoring of replicated experimental manipulations are a direct method to reveal these responses, yet are difficult to achieve as they typically resource-heavy and labour intensive. We actively manipulated the temperature at three agricultural grasslands in southern England and deployed novel 'SkyLine' systems, recently developed at the University of York, to continuously monitor GHG fluxes. Each 'SkyLine' is a low-cost and fully autonomous technology yet produces fluxes at a near-continuous temporal frequency and across a wide spatial area. The results produced by 'SkyLine' enable the detail response of each system to increased temperature over diurnal and seasonal timescales. Unexpected differences in NEE are shown between superficially similar ecosystems which, upon investigation, suggest that interactions between a variety of environmental variables are key and that knowledge of pre-existing environmental conditions help to predict a systems response to future climate. For example, the prevailing hydrological conditions at each site appear to affect its response to changing temperature. The high-frequency data shown here, combined with the fully-replicated experimental design reveal complex interactions which must be understood to improve predictions of ecosystem response to a changing climate.

Precipitation dynamics and chemical properties in tropical mountain forests of Ecuador

NASA Astrophysics Data System (ADS)

Rollenbeck, R.; Fabian, P.; Bendix, J.

2006-01-01

Terrestrial ecosystems in southern Ecuador are strongly affected by interannual climate variations. This holds especially true for the episodic El Niño events, which cause above-normal precipitation in the coastal region of Ecuador and below normal values in the eastern provinces of the Amazon basin (Bendix, 1999). For the transitional zone between these two extremes, which consists mainly of the andean slopes and larger interandean basins the effect on interannual climate variability is not well known. The PREDICT project monitors regional climate in the provinces of Loja and Zamora-Chinchipe (4° S/79° W), where a strong gradients of precipitation are observed. Between the eastern slopes of the Cordillera Real and the dry valley of Catamayo, which are only 70km apart, rain totals drop from over 4000 mm to only 300 mm per year. These two extremes represent the both sides of the Andean mountain chain and are completely covered by the study area, which is 120 km in diameter. Methods used are a combination of point measurements (climate stations) and remote sensing devices (weather radar, satellite imagery), which enable a high-resolution real-time observation of rain distribution and underlying processes. By this, ideal conditions are given to monitor a potential shift of the transition zone between below-average and above-average rainfall situated in this region, if another ENSO-anomaly occurs. Furthermore variability of atmospheric nutrient inputs is analysed within the scope of the project, to assess further impacts on this ecosystem.

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalaacchi, Antonio J.

1998-01-01

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

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalacchi, Antonio J.

1999-01-01

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

A new collective view of oceanography of the Arctic and North Atlantic basins

NASA Astrophysics Data System (ADS)

Yashayaev, Igor; Seidov, Dan; Demirov, Entcho

2015-03-01

We review some historical aspects of the major observational programs in the North Atlantic and adjacent regions that contributed to establishing and maintaining the global ocean climate monitoring network. The paper also presents the oceanic perspectives of climate change and touches the important issues of ocean climate variability on time scales from years to decades. Some elements of the improved understanding of the causes and mechanisms of variability in the subpolar North Atlantic and adjacent seas are discussed in detail. The sophistication of current oceanographic analysis, especially in connection with the most recent technological breakthroughs - notably the launch of the global array of profiling Argo floats - allows us to approach new challenges in ocean research. We demonstrate how the ocean-climate changes in the subpolar basins and polar seas correlate with variations in the major climate indices such as the North Atlantic Oscillation and Atlantic Multidecadal Oscillation, and discuss possible connections between the unprecedented changes in the Arctic and Greenland ice-melt rates observed over the past decade and variability of hydrographic conditions in the Labrador Sea. Furthermore, a synthesis of shipboard and Argo measurements in the Labrador Sea reveals the effects of the regional climate trends such as freshening of the upper layer - possible causes of which are also discussed - on the winter convection in the Labrador Sea including its strength, duration and spatial extent. These changes could have a profound impact on the regional and planetary climates. A section with the highlights of all papers comprising the Special Issue concludes the Preface.

Earth Observation for monitoring phenology for european land use and ecosystems over 1998-2011

NASA Astrophysics Data System (ADS)

Ceccherini, Guido; Gobron, Nadine

2013-04-01

Long-term measurements of plant phenology have been used to track vegetation responses to climate change but are often limited to particular species and locations and may not represent synoptic patterns. Given the limitations of working directly with in-situ data, many researchers have instead used available satellite remote sensing. Remote sensing extends the possible spatial coverage and temporal range of phenological assessments of environmental change due to the greater availability of observations. Variations and trends of vegetation dynamics are important because they alter the surface carbon, water and energy balance. For example, the net ecosystem CO2 exchange of vegetation is strongly linked to length of the growing season: extentions and decreases in length of growing season modify carbon uptake and the amount of CO2 in the atmosphere. Advances and delays in starting of growing season also affect the surface energy balance and consequently transpiration. The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is a key climate variable identified by Global Terrestrial Observing System (GTOS) that can be monitored from space. This dimensionless variable - varying between 0 and 1- is directly linked to the photosynthetic activity of vegetation, and therefore, can monitor changes in phenology. In this study, we identify the spatio/temporal patterns of vegetation dynamics using a long-term remotely sensed FAPAR dataset over Europe. Our aim is to provide a quantitative analysis of vegetation dynamics relevant to climate studies in Europe. As part of this analysis, six vegetation phenological metrics have been defined and made routinely in Europe. Over time, such metrics can track simple, yet critical, impacts of climate change on ecosystems. Validation has been performed through a direct comparison against ground-based data over ecological sites. Subsequently, using the spatio/temporal variability of this suite of metrics, we classify areas with similar vegetation dynamics. This permits assessment of variations and trends of vegetation dynamics over Europe. Statistical tests to assess the significance of temporal changes are used to evaluate trends in the metrics derived from the recorded time series of the FAPAR.

Satellite-derived SIF and CO2 Observations Show Coherent Responses to Interannual Climate Variations

NASA Astrophysics Data System (ADS)

Butterfield, Z.; Hogikyan, A.; Kulawik, S. S.; Keppel-Aleks, G.

2017-12-01

Gross primary production (GPP) is the single largest carbon flux in the Earth system, but its sensitivity to changes in climate is subject to significant uncertainty. Satellite measurements of solar-induced chlorophyll fluorescence (SIF) offer insight into spatial and temporal patterns in GPP at a global scale and, combined with other satellite-derived datasets, provide unprecedented opportunity to explore interactions between atmospheric CO2, GPP, and climate variability. To explore potential drivers of GPP in the Northern Hemisphere (NH), we compare monthly-averaged SIF data from the Global Ozone Monitoring Experiment 2 (GOME-2) with observed anomalies in temperature (T; CRU-TS), liquid water equivalent (LWE) from the Gravity Recovery and Climate Experiment (GRACE), and photosynthetically active radiation (PAR; CERES SYN1deg). Using observations from 2007 through 2015 for several NH regions, we calculate month-specific sensitivities of SIF to variability in T, LWE, and PAR. These sensitivities provide insight into the seasonal progression of how productivity is affected by climate variability and can be used to effectively model the observed SIF signal. In general, we find that high temperatures are beneficial to productivity in the spring, but detrimental in the summer. The influences of PAR and LWE are more heterogeneous between regions; for example, higher LWE in North American temperate forest leads to decreased springtime productivity, while exhibiting a contrasting effect in water-limited regions. Lastly, we assess the influence of variations in terrestrial productivity on atmospheric carbon using a new lower tropospheric CO2 product derived from the Greenhouse Gases Observing Satellite (GOSAT). Together, these data shed light on the drivers of interannual variability in the annual cycle of NH atmospheric CO2, and may provide improved constraints on projections of long-term carbon cycle responses to climate change.

Science Writers' Guide to TERRA

NASA Technical Reports Server (NTRS)

2000-01-01

The launch of NASA's Terra spacecraft marks a new era of comprehensive monitoring of the Earth's atmosphere, oceans, and continents from a single space-based platform. Data from the five Terra instruments will create continuous, long-term records of the state of the land, oceans, and atmosphere. Together with data from other satellite systems launched by NASA and other countries, Terra will inaugurate a new self-consistent data record that will be gathered over the next 15 years. The science objectives of NASAs Earth Observing System (EOS) program are to provide global observations and scientific understanding of land cover change and global productivity, climate variability and change, natural hazards, and atmospheric ozone. Observations by the Terra instruments will: provide the first global and seasonal measurements of the Earth system, including such critical functions as biological productivity of the land and oceans, snow and ice, surface temperature, clouds, water vapor, and land cover; improve our ability to detect human impacts on the Earth system and climate, identify the "fingerprint" of human activity on climate, and predict climate change by using the new global observations in climate models; help develop technologies for disaster prediction, characterization, and risk reduction from wildfires, volcanoes, floods, and droughts, and start long-term monitoring of global climate change and environmental change.

A Long-Term and Reproducible Passive Microwave Sea Ice Concentration Data Record for Climate Studies and Monitoring

NASA Technical Reports Server (NTRS)

Peng, G.; Meier, W. N.; Scott, D. J.; Savoie, M. H.

2013-01-01

A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.

Comparative glacio-climatological analysis of mass balance variability along the geographical margin of Europe

NASA Astrophysics Data System (ADS)

Lehoczky, Annamária; Kern, Zoltán; Pongrácz, Rita

2014-05-01

Glacio-climatological studies recognise glacier mass balance changes as high-confident climate indicators. The climatic sensitivity of a glacier does not simply depend on regional climate variability but also influenced via large- and mesoscale atmospheric circulation patterns. This study focuses on recent changes in the mass balance using records from three border regions of Europe, and investigates the relationships between the seasonal mass balance components, regional climatic conditions, and distant atmospheric forcing. Since glaciers in different macro-climatological conditions (i.e., mid-latitudes or high-latitudes, dry-continental or maritime regions) may present strongly diverse mass balance characteristics, the three analysed regions were selected from different glacierised macroregions (using the database of the World Glacier Monitoring Service). These regions belong to the Caucasus Mountains (Central Europe macroregion), the Polar Ural (Northern Asia macroregion), and Svalbard (Arctic Islands macroregion). The analysis focuses on winter, summer, and annual mass balance series of eight glaciers. The climatic variables (atmospheric pressure, air temperature, precipitation) and indices of teleconnection patterns (e.g., North Atlantic Oscillation, Pacific Decadal Oscillation) are used from the gridded databases of the University of East Anglia, Climatic Research Unit and the National Oceanic and Atmospheric Administration, National Center for Environmental Prediction. However, the period and length of available mass balance data in the selected regions vary greatly (the first full record is in 1958, Polar Ural; the last is in 2010, Caucasus Mountains), a comparative analysis can be carried out for the period of 1968-1981. Since glaciers from different regions respond to large- and mesoscale climatic forcings differently, and because the mass balance of glaciers within a region often co-vary, our specific objectives are (i) to examine the variability and the integrative climatic signal in the averaged mass balance records of the selected regions; (ii) to analyse the possible coupling between the mass balance and climatic variables, including the dominant patterns of Northern Hemisphere climate variability; and (iii) to compare the main characteristics of the three regions. Furthermore, (iv) a short discussion is given considering the significant decreasing trend of the cumulative annual mass balances in every region under the detected climatic changes in the second half of the 20th century. Preliminary results suggest that the strongest teleconnection links could be between winter mass balance and winter NAO for the Polar Ural (r=0.46, p<0.05), and between annual mass balance and PDO for Svalbard (r=-0.43, p<0.05). Neither seasonal, nor annual mass balance records showed significant correlation with any of the examined circulation indices for the Caucasus.

Using ensemble forecasting to examine how climate change promotes worldwide invasion of the golden apple snail (Pomacea canaliculata).

PubMed

Lei, Juncheng; Chen, Lian; Li, Hong

2017-08-01

The golden apple snail, Pomacea canaliculata, is one of the world's 100 most notorious invasive alien species. Knowledge about the critical climate variables that limit the global distribution range of the snail, as well as predictions of future species distributions under climate change, is very helpful for management of snail. In this study, the climatically suitable habitats for this kind of snail under current climate conditions were modeled by biomod2 and projected to eight future climate scenarios (2 time periods [2050s, 2080s] × 2 Representative Concentration Pathways [RCPs; RCP2.6, RCP8.5] × 2 atmospheric General Circulation Models [GCMs; Canadian Centre for Climate Modelling and Analysis (CCCMA), Commonwealth Scientific and Industrial Research Organisation (CSIRO)]). The results suggest that the lowest temperature of coldest month is the critical climate variable to restrict the global distribution range of P. canaliculata. It is predicted that the climatically suitable habitats for P. canaliculata will increase by an average of 3.3% in 2050s and 3.8% in 2080s for the RCP2.6 scenario, while they increase by an average of 8.7% in 2050s and 10.3% in 2080s for the RCP8.5 scenario. In general, climate change in the future may promote the global invasion of the invasive species. Therefore, it is necessary to take proactive measures to monitor and preclude the invasion of this species.

NOAA's Scientific Data Stewardship Program

NASA Astrophysics Data System (ADS)

Bates, J. J.

2004-12-01

The NOAA mission is to understand and predict changes in the Earth's environment and conserve and manage coastal and marine resources to meet the Nation's economic, social and environmental needs. NOAA has responsibility for long-term archiving of the United States environmental data and has recently integrated several data management functions into a concept called Scientific Data Stewardship. Scientific Data Stewardship a new paradigm in data management consisting of an integrated suite of functions to preserve and exploit the full scientific value of NOAA's, and the world's, environmental data These functions include careful monitoring of observing system performance for long-term applications, the generation of authoritative long-term climate records from multiple observing platforms, and the proper archival of and timely access to data and metadata. NOAA has developed a conceptual framework to implement the functions of scientific data stewardship. This framework has five objectives: 1) develop real-time monitoring of all satellite observing systems for climate applications, 2) process large volumes of satellite data extending up to decades in length to account for systematic errors and to eliminate artifacts in the raw data (referred to as fundamental climate data records, FCDRs), 3) generate retrieved geophysical parameters from the FCDRs (referred to as thematic climate data records TCDRs) including combining observations from all sources, 4) conduct monitoring and research by analyzing data sets to uncover climate trends and to provide evaluation and feedback for steps 2) and 3), and 5) provide archives of metadata, FCDRs, and TCDRs, and facilitate distribution of these data to the user community. The term `climate data record' and related terms, such as climate data set, have been used for some time, but the climate community has yet to settle on a concensus definition. A recent United States National Academy of Sciences report recommends using the following definition: a climate data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change.

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

USGS Publications Warehouse

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

2003-01-01

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

Response of waves and coastline evolution to climate variability off the Niger Delta coast during the past 110 years

NASA Astrophysics Data System (ADS)

Dada, Olusegun A.; Li, Guangxue; Qiao, Lulu; Ma, Yanyan; Ding, Dong; Xu, Jishang; Li, Pin; Yang, Jichao

2016-08-01

River deltas, low-lying landforms that host critical economic infrastructures and diverse ecosystems as well as high concentrations of human population, are highly vulnerable to the effects of global climate change. In order to understand the wave climate, their potential changes and implication on coastline evolution for environment monitoring and sustainable management of the Niger Delta in the Gulf of Guinea, an investigation was carried out based on offshore wave statistics of an 110-year time series (1900-2010) dataset obtained from the ECMWF ERA-20C atmospheric reanalysis. Results of multivariate regression analyses indicate that interannual mean values of Hs and Tm trends tended to increase over time, especially in the western part of the delta coast, so that they are presently (1980 and 2010) up to 264 mm (300%) and 0.32 s (22%), respectively, higher than 80 years (1900-1930) ago. The maximum directions of the wave have become more westerly (southward) than southerly (westward) by up to 2° (33%) and the mean longshore sediment transport rate has increased by more than 8% over the last 80 years. The linear regression analysis for shoreline changes from 1987 to 2013 shows an erosional trend at the western part of the delta and accretional trends towards eastern part. The relationship between wave climate of the study area and atmospheric circulation using Pearson's correlation shows that the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), East Atlantic pattern (EA) and El-Nino/Southern Oscillation (ENSO) Index explain significant proportion of the seasonal and annual wave variabilities compared to other indices. But it is most likely that the combination of these climatic indices acting together or separately constitutes a powerful and effective mechanism responsible for much of the variability of the offshore Niger Delta wave climate. The study concludes that changing wave climate off the Niger Delta has strong implications on the delta coastline changes. However, other processes (such as fluvial discharge variability due climatic variability and anthropogenic effect) may be acting concomitantly with changes in wave regime and associated littoral transport to influence shoreline evolution along the Niger Delta coast.

Remotely Sensed Spatio-Temporal Variability of Snow Cover in Himalayan Region with Perspective of Climate Change

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

Climate change and its impact of water resource have gained tremendous attention among scientific committee, governments and other stakeholders since last couple of decades, especially in Himalayan region. In this study, we purpose remotely sensed measurements to monitor snow cover, both spatially and temporal, and assess climate change impact on water resource. The snow cover data from MODIS satellite (2000-2010) have been used to analyze some climate change indicators. In particular, the variability in the maximum snow extent with elevations, its temporal variability (8-day, monthly, seasonal and annual), its variation trend and its relation with temperature have been analyzed. The snow products used in this study are the maximum snow extent and fractional snow covers, which come in 8-day temporal and 500m and 0.05 degree spatial resolutions, respectively. The results showed a tremendous potential of the MODIS snow product for studying the spatial and temporal variability of snow as well as the study of climate change impact in large and inaccessible regions like the Himalayas. The snow area extent (SAE) (%) time series exhibits similar patterns during seven hydrological years, even though there are some deviations in the accumulation and melt periods. The analysis showed relatively well inverse relation between the daily mean temperature and SAE during the melting period. Some important trends of snow fall are also observed. In particular, the decreasing trend in January and increasing trend in late winter and early spring may be interpreted as a signal of a possible seasonal shift. However, it requires more years of data to verify this conclusion.

Quantitative Comparison of the Variability in Observed and Simulated Shortwave Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda, L.; Pilewskie, P.; Kindel, B. C.; Feldman, D. R.; Collins, W. D.

2013-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system that has been designed to monitor the Earth's climate with unprecedented absolute radiometric accuracy and SI traceability. Climate Observation System Simulation Experiments (OSSEs) have been generated to simulate CLARREO hyperspectral shortwave imager measurements to help define the measurement characteristics needed for CLARREO to achieve its objectives. To evaluate how well the OSSE-simulated reflectance spectra reproduce the Earth s climate variability at the beginning of the 21st century, we compared the variability of the OSSE reflectance spectra to that of the reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY). Principal component analysis (PCA) is a multivariate decomposition technique used to represent and study the variability of hyperspectral radiation measurements. Using PCA, between 99.7%and 99.9%of the total variance the OSSE and SCIAMACHY data sets can be explained by subspaces defined by six principal components (PCs). To quantify how much information is shared between the simulated and observed data sets, we spectrally decomposed the intersection of the two data set subspaces. The results from four cases in 2004 showed that the two data sets share eight (January and October) and seven (April and July) dimensions, which correspond to about 99.9% of the total SCIAMACHY variance for each month. The spectral nature of these shared spaces, understood by examining the transformed eigenvectors calculated from the subspace intersections, exhibit similar physical characteristics to the original PCs calculated from each data set, such as water vapor absorption, vegetation reflectance, and cloud reflectance.

Hydrological processes and model representation: impact of soft data on calibration

Treesearch

J.G. Arnold; M.A. Youssef; H. Yen; M.J. White; A.Y. Sheshukov; A.M. Sadeghi; D.N. Moriasi; J.L. Steiner; Devendra Amatya; R.W. Skaggs; E.B. Haney; J. Jeong; M. Arabi; P.H. Gowda

2015-01-01

Hydrologic and water quality models are increasingly used to determine the environmental impacts of climate variability and land management. Due to differing model objectives and differences in monitored data, there are currently no universally accepted procedures for model calibration and validation in the literature. In an effort to develop accepted model calibration...

Ecosystem dynamics and disturbance in mountain wildernesses: assessing vulnerability of natural resources to change

Treesearch

Daniel B. Fagre; David L. Peterson

2000-01-01

An integrated program of ecosystem modeling and extensive field studies at Glacier and Olympic National Parks has quantified many of the ecological processes affected by climatic variability and disturbance. Models have successfully estimated snow distribution, annual watershed discharge, and stream temperature variation based on seven years of monitoring. Various...

Environmental variables and levels of exhaled carbon monoxide and carboxyhemoglobin in elderly people taking exercise.

PubMed

Salicio, Marcos Adriano; Mana, Viviane Aparecida Martins; Fett, Waléria Christiane Rezende; Gomes, Luciano Teixeira; Botelho, Clovis

2016-04-01

This article aims to analyze levels of exhaled carbon monoxide, carboxyhemoglobinand cardiopulmonary variables in old people practicing exercise in external environments, and correlate them with climate and pollution factors. Temporal ecological study with118 active elderly people in the city of Cuiabá, in the state of Mato Grosso, Brazil. Data were obtained on use of medication, smoking, anthropometric measurements, spirometry, peak flow, oxygen saturation, heart rate, exhaled carbon monoxide, carboxyhemoglobin, climate, number of farm fires and pollution. Correlations were found between on the one hand environmental temperature, relative humidity of the air and number of farmers' fires, and on the other hand levels of carbon monoxide exhaled and carboxyhemoglobin (p < 0.05).There was a correlation between heart rate and changes in environmental temperature, time of exposure to the sun and relative humidity (p < 0.05). In elderly people, environmental factors influence levels of exhaled carbon monoxide, carboxyhemoglobin and heart rate. There is thus a need for these to be monitored during exercise. The use of a carbon monoxide monitor to evaluate exposure to pollutants is suggested.

The Grand Challenges of WCRP and the Climate Observing System of the Future

NASA Astrophysics Data System (ADS)

Brasseur, G. P.

2017-12-01

The successful implementation the Paris agreement on climate change (COP21) calls for a well-designed global monitoring system of essential climate variables, climate processes and Earth system budgets. The Grand Challenges implemented by the World Climate Research Programme (WCRP) provide an opportunity to investigate issues of high societal relevance, directly related to sea level rise, droughts, floods, extreme heat events, food security, and fresh water availability. These challenges would directly benefit from a well-designed suite of systematic climate observations. Quantification of the evolution of the global energy, water and carbon budgets as well as the development and the production of near-term and regional climate predictions require that a comprehensive, focused, multi-platform observing system (satellites, ground-based and in situ observations) be established in an international context. This system must be accompanied by the development of climate services that should translate and disseminate scientific outcomes as actionable information for users and stakeholders.

Climate and Non-Climate Drivers of Dengue Epidemics in Southern Coastal Ecuador

PubMed Central

Stewart-Ibarra, Anna M.; Lowe, Rachel

2013-01-01

We report a statistical mixed model for assessing the importance of climate and non-climate drivers of interannual variability in dengue fever in southern coastal Ecuador. Local climate data and Pacific sea surface temperatures (Oceanic Niño Index [ONI]) were used to predict dengue standardized morbidity ratios (SMRs; 1995–2010). Unobserved confounding factors were accounted for using non-structured yearly random effects. We found that ONI, rainfall, and minimum temperature were positively associated with dengue, with more cases of dengue during El Niño events. We assessed the influence of non-climatic factors on dengue SMR using a subset of data (2001–2010) and found that the percent of households with Aedes aegypti immatures was also a significant predictor. Our results indicate that monitoring the climate and non-climate drivers identified in this study could provide some predictive lead for forecasting dengue epidemics, showing the potential to develop a dengue early-warning system in this region. PMID:23478584

Regional influence of decadal to multidecadal Atlantic Oscillations during the last two millennia in Morocco, inferred from two high resolution δ18O speleothem records

NASA Astrophysics Data System (ADS)

Ait Brahim, Yassine; Sifeddine, Abdelfettah; Khodri, Myriam; Bouchaou, Lhoussaine; Cruz, Francisco W.; Pérez-Zanón, Núria; Wassenburg, Jasper A.; Cheng, Hai

2017-04-01

Climate projections predict substantial increase of extreme heats and drought occurrences during the coming decades in Morocco. It is however not clear what can be attributed to natural climate variability and to anthropogenic forcing, as hydroclimate variations observed in areas such as Morocco are highly influenced by the Atlantic climate modes. Since observational data sets are too short to resolve properly natural modes of variability acting on decadal to multidecadal timescales, high resolution paleoclimate reconstructions are the only alternative to reconstruct climate variability in the remote past. Herein, we present two high resolution and well dated speleothems oxygen isotope (δ18O) records sampled from Chaara and Ifoulki caves (located in Northeastern and Southwestern Morocco respectively) to investigate hydroclimate variations during the last 2000 years. Our results are supported by a monitoring network of δ18O in precipitation from 17 stations in Morocco. The new paleoclimate records are discussed in the light of existing continental and marine paleoclimate proxies in Morocco to identify significant correlations at various lead times with the main reconstructed oceanic and atmospheric variability modes and possible climate teleconnections that have potentially influenced the climate during the last two millennia in Morocco. The results reveal substantial decadal to multidecadal swings between dry and humid periods, consistent with regional paleorecords. Evidence of dry conditions exist during the Medieval Climate Anomaly (MCA) period and the Climate Warm Period (CWP) and humid conditions during the Little Ice Age (LIA) period. Statistical analyses suggest that the climate of southwestern Morocco remained under the combined influence of both the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) over the last two millennia. Interestingly, the generally warmer MCA and colder LIA at longer multidecadal timescales probably influenced the regional climate in North Africa through the influence on Sahara Low which weakened and strengthened the mean moisture inflow from the Atlantic Ocean during the MCA and LIA respectively. Keywords: Speleothems, δ18O, Morocco, Hydroclimate, AMO, NAO.

Complexity of Tropical Pacific Ecosystem and Biogeochemistry: Diurnal to Decadal, Plankters to Penguins

NASA Astrophysics Data System (ADS)

Murtugudde, R. G.; Wang, X.; Valsala, V.; Karnauskas, K. B.

2016-12-01

Tropical Pacific spans nearly 50% of the global tropics allowing to have its own mind in terms of climate variability and physical-biogeochemical interactions. While the El Niño-Southern Oscillation (ENSO) and its flavors get much attention, it is fairly clear by now that any further improvements in ENSO prediction skills and reliability of global warming projections must begin to observe and represent bio-physical interactions in the climate and Earth System models. Coupled climate variability over the tropical Pacific has a global reach with its diurnal to decadal timescales being manifest in ecosystem and biogechemistry. Zonal and meridional contrasts in biogeochemistry across the tropical Pacific is closely related to seasonal variability, ENSO diversity and the PDO. Apparent dominance of ocean dynamic controls on biogeochemistry belies the potential biogeochemical feedbacks on ocean dynamics which may well explain some of the chronic biases in the state-of-the-art climate models. The east Pacific cold-tongue is the most productive open ocean region in the world and home to a unique physical-biogeochmical laboratory, viz., the Galapagos. The Galapagos islands not only control the coupled climate variability via their ability to terminate the equatorial undercurrent but also offer a clear example of a biological loophole in terms of their impact on local upwelling and an expanding penguin habitat in the face of global warming. The complex bio-physical interactions in the cold-tongue and their influence on climate predictions and projections require a holisti thinking on future observing systems. Tropical Pacific offers a natural laboratory for designing a robust and sustained physical-biogeochemical observation system that can effectively bridge climate predictions and projections into a unified framework for subseasonal to multidecadal timescales. Such a system will be a foundation for establishing similar systems over the rest of the World ocean to seemlessly merge climate predictions and projections with the need to constantly monitor climate impacts on marine resources. This talk will focus on the zonal contrasts of the ocean dynamics and biogechemistry across the tropical Pacific to make a case for integrated physical-biogeochemical observations for climate predictions and projections.

Satellite-based trends of solar radiation and cloud parameters in Europe

NASA Astrophysics Data System (ADS)

Pfeifroth, Uwe; Bojanowski, Jedrzej S.; Clerbaux, Nicolas; Manara, Veronica; Sanchez-Lorenzo, Arturo; Trentmann, Jörg; Walawender, Jakub P.; Hollmann, Rainer

2018-04-01

Solar radiation is the main driver of the Earth's climate. Measuring solar radiation and analysing its interaction with clouds are essential for the understanding of the climate system. The EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF) generates satellite-based, high-quality climate data records, with a focus on the energy balance and water cycle. Here, multiple of these data records are analyzed in a common framework to assess the consistency in trends and spatio-temporal variability of surface solar radiation, top-of-atmosphere reflected solar radiation and cloud fraction. This multi-parameter analysis focuses on Europe and covers the time period from 1992 to 2015. A high correlation between these three variables has been found over Europe. An overall consistency of the climate data records reveals an increase of surface solar radiation and a decrease in top-of-atmosphere reflected radiation. In addition, those trends are confirmed by negative trends in cloud cover. This consistency documents the high quality and stability of the CM SAF climate data records, which are mostly derived independently from each other. The results of this study indicate that one of the main reasons for the positive trend in surface solar radiation since the 1990's is a decrease in cloud coverage even if an aerosol contribution cannot be completely ruled out.

Monitoring snow cover variability (2000-2014) in the Hengduan Mountains based on cloud-removed MODIS products with an adaptive spatio-temporal weighted method

NASA Astrophysics Data System (ADS)

Li, Xinghua; Fu, Wenxuan; Shen, Huanfeng; Huang, Chunlin; Zhang, Liangpei

2017-08-01

Monitoring the variability of snow cover is necessary and meaningful because snow cover is closely connected with climate and ecological change. In this work, 500 m resolution MODIS daily snow cover products from 2000 to 2014 were adopted to analyze the status in Hengduan Mountains. In order to solve the spatial discontinuity caused by clouds in the products, we propose an adaptive spatio-temporal weighted method (ASTWM), which is based on the initial result of a Terra and Aqua combination. This novel method simultaneously considers the temporal and spatial correlations of the snow cover. The simulated experiments indicate that ASTWM removes clouds completely, with a robust overall accuracy (OA) of above 93% under different cloud fractions. The spatio-temporal variability of snow cover in the Hengduan Mountains was investigated with two indices: snow cover days (SCD) and snow fraction. The results reveal that the annual SCD gradually increases and the coefficient of variation (CV) decreases with elevation. The pixel-wise trends of SCD first rise and then drop in most areas. Moreover, intense intra-annual variability of the snow fraction occurs from October to March, during which time there is abundant snow cover. The inter-annual variability, which mainly occurs in high elevation areas, shows an increasing trend before 2004/2005 and a decreasing trend after 2004/2005. In addition, the snow fraction responds to the two climate factors of air temperature and precipitation. For the intra-annual variability, when the air temperature and precipitation decrease, the snow cover increases. Besides, precipitation plays a more important role in the inter-annual variability of snow cover than temperature.

Groundwater and Terrestrial Water Storage

NASA Technical Reports Server (NTRS)

Rodell, Matthew; Chambers, Don P.; Famiglietti, James S.

2012-01-01

Groundwater is a vital resource and also a dynamic component of the water cycle. Unconfined aquifer storage is less responsive to short term weather conditions than the near surface terrestrial water storage (TWS) components (soil moisture, surface water, and snow). However, save for the permanently frozen regions, it typically exhibits a larger range of variability over multi-annual periods than the other components. Groundwater is poorly monitored at the global scale, but terrestrial water storage (TWS) change data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission are a reasonable proxy for unconfined groundwater at climatic scales.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile.

PubMed

Glade, Francisco E; Miranda, Marcelo D; Meza, Francisco J; van Leeuwen, Willem J D

2016-12-01

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.

Analysis of meteorological variables in the Australasian region using ground- and space-based GPS techniques

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Choy, Suelynn; Fu, Erjiang Frank; Chane-Ming, Fabrice; Liou, Yuei-An; Pavelyev, Alexander G.

2016-07-01

Results of analysis of meteorological variables (temperature and moisture) in the Australasian region using the global positioning system (GPS) radio occultation (RO) and GPS ground-based observations verified with in situ radiosonde (RS) data are presented. The potential of using ground-based GPS observations for retrieving column integrated precipitable water vapour (PWV) over the Australian continent has been demonstrated using the Australian ground-based GPS reference stations network. Using data from the 15 ground-based GPS stations, the state of the atmosphere over Victoria during a significant weather event, the March 2010 Melbourne storm, has been investigated, and it has been shown that the GPS observations has potential for monitoring the movement of a weather front that has sharp moisture contrast. Temperature and moisture variability in the atmosphere over various climatic regions (the Indian and the Pacific Oceans, the Antarctic and Australia) has been examined using satellite-based GPS RO and in situ RS observations. Investigating recent atmospheric temperature trends over Antarctica, the time series of the collocated GPS RO and RS data were examined, and strong cooling in the lower stratosphere and warming through the troposphere over Antarctica has been identified, in agreement with outputs of climate models. With further expansion of the Global Navigation Satellite Systems (GNSS) system, it is expected that GNSS satellite- and ground-based measurements would be able to provide an order of magnitude larger amount of data which in turn could significantly advance weather forecasting services, climate monitoring and analysis in the Australasian region.

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

PubMed Central

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

2001-01-01

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

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

PubMed

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

2001-05-01

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

Operational satellites and the global monitoring of snow and ice

NASA Technical Reports Server (NTRS)

Walsh, John E.

1991-01-01

The altitudinal dependence of the global warming projected by global climate models is at least partially attributable to the albedo-temperature feedback involving snow and ice, which must be regarded as key variables in the monitoring for global change. Statistical analyses of data from IR and microwave sensors monitoring the areal coverage and extent of sea ice have led to mixed conclusions about recent trends of hemisphere sea ice coverage. Seasonal snow cover has been mapped for over 20 years by NOAA/NESDIS on the basis of imagery from a variety of satellite sensors. Multichannel passive microwave data show some promise for the routine monitoring of snow depth over unforested land areas.

Solar influences on global change

NASA Technical Reports Server (NTRS)

1994-01-01

Monitoring of the Sun and the Earth has yielded new knowledge essential to this debate. There is now no doubt that the total radiative energy from the Sun that heats the Earth's surface changes over decadal time scales as a consequence of solar activity. Observations indicate as well that changes in ultraviolet radiation and energetic particles from the Sun, also connected with the solar activity, modulate the layer of ozone that protects the biosphere from the solar ultraviolet radiation. This report reassesses solar influences on global change in the light of this new knowledge of solar and atmospheric variability. Moreover, the report considers climate change to be encompassed within the broader concept of global change; thus the biosphere is recognized to be part of a larger, coupled Earth system. Implementing a program to continuously monitor solar irradiance over the next several decades will provide the opportunity to estimate solar influences on global change, assuming continued maintenance of observations of climate and other potential forcing mechanisms. In the lower atmosphere, an increase in solar radiation is expected to cause global warming. In the stratosphere, however, the two effects produce temperature changes of opposite sign. A monitoring program that would augment long term observations of tropospheric parameters with similar observations of stratospheric parameters could separate these diverse climate perturbations and perhaps isolate a greenhouse footprint of climate change. Monitoring global change in the troposphere is a key element of all facets of the United States Global Change Research Program (USGCRP), not just of the study of solar influences on global change. The need for monitoring the stratosphere is also important for global change research in its own right because of the stratospheric ozone layer.

Seasonal associations of climatic drivers and malaria in the highlands of Ethiopia.

PubMed

Midekisa, Alemayehu; Beyene, Belay; Mihretie, Abere; Bayabil, Estifanos; Wimberly, Michael C

2015-06-24

The impacts of interannual climate fluctuations on vector-borne diseases, especially malaria, have received considerable attention in the scientific literature. These effects can be significant in semi-arid and high-elevation areas such as the highlands of East Africa because cooler temperature and seasonally dry conditions limit malaria transmission. Many previous studies have examined short-term lagged effects of climate on malaria (weeks to months), but fewer have explored the possibility of longer-term seasonal effects. This study assessed the interannual variability of malaria occurrence from 2001 to 2009 in the Amhara region of Ethiopia. We tested for associations of climate variables summarized during the dry (January-April), early transition (May-June), and wet (July-September) seasons with malaria incidence in the early peak (May-July) and late peak (September-December) epidemic seasons using generalized linear models. Climate variables included land surface temperature (LST), rainfall, actual evapotranspiration (ET), and the enhanced vegetation index (EVI). We found that both early and late peak malaria incidence had the strongest associations with meteorological conditions in the preceding dry and early transition seasons. Temperature had the strongest influence in the wetter western districts, whereas moisture variables had the strongest influence in the drier eastern districts. We also found a significant correlation between malaria incidence in the early and the subsquent late peak malaria seasons, and the addition of early peak malaria incidence as a predictor substantially improved models of late peak season malaria in both of the study sub-regions. These findings suggest that climatic effects on malaria prior to the main rainy season can carry over through the rainy season and affect the probability of malaria epidemics during the late malaria peak. The results also emphasize the value of combining environmental monitoring with epidemiological surveillance to develop forecasts of malaria outbreaks, as well as the need for spatially stratified approaches that reflect the differential effects of climatic variations in the different sub-regions.

Monitoring Crop Productivity over the U.S. Corn Belt using an Improved Light Use Efficiency Model

NASA Astrophysics Data System (ADS)

Wu, X.; Xiao, X.; Zhang, Y.; Qin, Y.; Doughty, R.

2017-12-01

Large-scale monitoring of crop yield is of great significance for forecasting food production and prices and ensuring food security. Satellite data that provide temporally and spatially continuous information that by themselves or in combination with other data or models, raises possibilities to monitor and understand agricultural productivity regionally. In this study, we first used an improved light use efficiency model-Vegetation Photosynthesis Model (VPM) to simulate the gross primary production (GPP). Model evaluation showed that the simulated GPP (GPPVPM) could well captured the spatio-temporal variation of GPP derived from FLUXNET sites. Then we applied the GPPVPM to further monitor crop productivity for corn and soybean over the U.S. Corn Belt and benchmarked with county-level crop yield statistics. We found VPM-based approach provides pretty good estimates (R2 = 0.88, slope = 1.03). We further showed the impacts of climate extremes on the crop productivity and carbon use efficiency. The study indicates the great potential of VPM in estimating crop yield and in understanding of crop yield responses to climate variability and change.

Development and Analysis of Global, High-Resolution Diagnostic Metrics for Vegetation Monitoring, Yield Estimation and Famine Mitigation

NASA Astrophysics Data System (ADS)

Anderson, B. T.; Zhang, P.; Myneni, R.

2008-12-01

Drought, through its impact on food scarcity and crop prices, can have significant economic, social, and environmental impacts - presently, up to 36 countries and 73 million people are facing food crises around the globe. Because of these adverse affects, there has been a drive to develop drought and vegetation- monitoring metrics that can quantify and predict human vulnerability/susceptibility to drought at high- resolution spatial scales over the entire globe. Here we introduce a new vegetation-monitoring index utilizing data derived from satellite-based instruments (the Moderate Resolution Imaging Spectroradiometer - MODIS) designed to identify the vulnerability of vegetation in a particular region to climate variability during the growing season. In addition, the index can quantify the percentage of annual grid-point vegetation production either gained or lost due to climatic variability in a given month. When integrated over the growing season, this index is shown to be better correlated with end-of-season crop yields than traditional remotely-sensed or meteorological indices. In addition, in-season estimates of the index, which are available in near real-time, provide yield forecasts comparable to concurrent in situ objective yield surveys, which are only available in limited regions of the world. Overall, the cost effectiveness and repetitive, near-global view of earth's surface provided by this satellite-based vegetation monitoring index can potentially improve our ability to mitigate human vulnerability/susceptibility to drought and its impacts upon vegetation and agriculture.

The Copernicus Climate Change Service (C3S): Open Access to a Climate Data Store

NASA Astrophysics Data System (ADS)

Thepaut, Jean-Noel; Dee, Dick

2016-04-01

In November 2014, The European Centre for Medium-range Weather Forecasts (ECMWF) signed an agreement with the European Commission to deliver two of the Copernicus Earth Observation Programme Services on the Commission's behalf. The ECMWF delivered services - the Copernicus Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS) - will bring a consistent standard to how we monitor and predict atmospheric conditions and climate change. They will maximise the potential of past, current and future earth observations - ground, ocean, airborne, satellite - and analyse these to monitor and predict atmospheric conditions and in the future, climate change. With the wealth of free and open data that the services provide, they will help business users to assess the impact of their business decisions and make informed choices, delivering a more energy efficient and climate aware economy. These sound investment decisions now will not only stimulate growth in the short term, but reduce the impact of climate change on the economy and society in the future. C3S is in its proof of concept phase and through its Climate Data Store will provide • global and regional climate data reanalyses; • multi-model seasonal forecasts; • customisable visual data to enable examination of wide range of scenarios and model the impact of changes; • access to all the underlying data, including climate data records from various satellite and in-situ observations. In addition, C3S will provide key indicators on climate change drivers (such as carbon dioxide) and impacts (such as reducing glaciers). The aim of these indicators will be to support European adaptation and mitigation policies in a number of economic sectors. At the heart of the Service is the provision of open access to a one stop shop (the Climate Data Store) of climate data and modelling, analysing more than 20 Essential Climate Variables to build a global picture of our past, present and future climate and developing customisable climate indicators for key economic sectors, such as energy, water management, agriculture, insurance, health… This talk will focus on the Climate Data Store facility, designed as a distributed system, providing improved access to existing datasets though a unified web interface. This service will accommodate the needs of the highly diverse set of users, from policy makers to expert practitioners and scientists.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures.

PubMed

Xie, Gisselle Yang; Olson, Deanna H; Blaustein, Andrew R

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

Schirmer, M.; Peleg, N.; Burlando, P.; Jonas, T.

2017-12-01

Snow in the Alps is affected by climate change with regard to duration, timing and amount. This has implications with respect to important societal issues as drinking water supply or hydropower generation. In Switzerland, the latter received a lot of attention following the political decision to phase out of nuclear electricity production. An increasing number of authorization requests for small hydropower plants located in small alpine catchments was observed in the recent years. This situation generates ecological conflicts, while the expected climate change poses a threat to water availability thus putting at risk investments in such hydropower plants. Reliable high-resolution climate scenarios are thus required, which account for small-scale processes to achieve realistic predictions of snowmelt runoff and its variability in small alpine catchments. We therefore used a novel model chain by coupling a stochastic 2-dimensional weather generator (AWE-GEN-2d) with a state-of-the-art energy balance snow cover model (FSM). AWE-GEN-2d was applied to generate ensembles of climate variables at very fine temporal and spatial resolution, thus providing all climatic input variables required for the energy balance modelling. The land-surface model FSM was used to describe spatially variable snow cover accumulation and melt processes. The FSM was refined to allow applications at very high spatial resolution by specifically accounting for small-scale processes, such as a subgrid-parametrization of snow covered area or an improved representation of forest-snow processes. For the present study, the model chain was tested for current climate conditions using extensive observational dataset of different spatial and temporal coverage. Small-scale spatial processes such as elevation gradients or aspect differences in the snow distribution were evaluated using airborne LiDAR data. 40-year of monitoring data for snow water equivalent, snowmelt and snow-covered area for entire Switzerland was used to verify snow distribution patterns at coarser spatial and temporal scale. The ability of the model chain to reproduce current climate conditions in small alpine catchments makes this model combination an outstanding candidate to produce high resolution climate scenarios of snowmelt in small alpine catchments.

Climate patterns as predictors of amphibians species richness and indicators of potential stress

USGS Publications Warehouse

Battaglin, W.; Hay, L.; McCabe, G.; Nanjappa, P.; Gallant, Alisa L.

2005-01-01

Amphibians occupy a range of habitats throughout the world, but species richness is greatest in regions with moist, warm climates. We modeled the statistical relations of anuran and urodele species richness with mean annual climate for the conterminous United States, and compared the strength of these relations at national and regional levels. Model variables were calculated for county and subcounty mapping units, and included 40-year (1960-1999) annual mean and mean annual climate statistics, mapping unit average elevation, mapping unit land area, and estimates of anuran and urodele species richness. Climate data were derived from more than 7,500 first-order and cooperative meteorological stations and were interpolated to the mapping units using multiple linear regression models. Anuran and urodele species richness were calculated from the United States Geological Survey's Amphibian Research and Monitoring Initiative (ARMI) National Atlas for Amphibian Distributions. The national multivariate linear regression (MLR) model of anuran species richness had an adjusted coefficient of determination (R2) value of 0.64 and the national MLR model for urodele species richness had an R2 value of 0.45. Stratifying the United States by coarse-resolution ecological regions provided models for anUrans that ranged in R2 values from 0.15 to 0.78. Regional models for urodeles had R2 values. ranging from 0.27 to 0.74. In general, regional models for anurans were more strongly influenced by temperature variables, whereas precipitation variables had a larger influence on urodele models.

Regional changes and global connections: monitoring climate variability and change in the western United States

Treesearch

Henry F. Diaz

2004-01-01

Mountain ecosystems of the Western United States are complex and include cold desert biomes, such as those found in Nevada; subpolar biomes found in the upper treeline zone; and tundra ecosystems, occurring above timberline. Many studies (for example, Thompson 2000) suggest that high-elevation environments, comprising glaciers, snow, permafrost, water, and the...

Nevada Monitoring System to Assess Climate Variability and Change

NASA Astrophysics Data System (ADS)

Devitt, D. A.; Arnone, J.; Biondi, F.; Fenstermaker, L. F.; Saito, L.; Young, M.; Riddle, B.; Strachan, S. D.; Bird, B.; McCurdy, G.; Lyles, B. F.

2010-12-01

The Nevada System of Higher Education (University of Nevada Las Vegas, University of Nevada Reno and the Desert Research Institute) was awarded a multiyear NSF EPSCoR grant to support infrastructure associated with regional climate change research. The overall project is comprised of 5 components: education, cyberinfrastructure, policy, climate modeling and water/ecology. The water and ecology components are using their infrastructure funding for the assessment of climate variability and change on ecosystem function and hydrologic services. A series of 10 m tall towers are under construction and are being equipped with a wide array of sensors to monitor atmospheric, soil and plant parameters over time. The towers are located within the Mojave and Great Basin Deserts in two transects; the Mojave Desert transect is located in the southern Nevada Sheep Mountain Range and the Great Basin transect is located in the east central Nevada Snake Mountain Range. The towers are centrally positioned in well-defined vegetation zones. In southern Nevada these zones are represented by the following plant species: Creosote/Bursage (Creosotebush scrub zone); Blackbrush/Joshua Tree (Blackbrush zone); Pinyon/ Juniper (pygmy conifer zone), Ponderosa Pine (montane zone) and Bristlecone Pine (subalpine zone). The Snake Mountain transect incorporates the eastern and western valleys on both sides of the mountain range. The vegetation zones are represented by: Greasewood and mixed shrub (salt desert zone); Big Sage (sagebrush zone); Pinyon/Juniper (pygmy conifer zone); White/Douglas Fir, Ponderosa Pine and Aspen (montane zone); and Bristlecone/Limber Pine and Engelmann Spruce (subalpine zone). We are currently in the third year of funding with a goal of having the majority of towers fully operational by winter 2010. In close collaboration with our cyberinfrastructure component team, all data acquired from the transect monitoring stations will be made available to other researchers and the public in Nevada and elsewhere, cooperating agencies and organizations, and State of Nevada land managers.

The dual threat of urbanisation and climate change in urbanising catchments - integrated science to meet future challenges - a case study of the Thames catchment, United Kingdom.

NASA Astrophysics Data System (ADS)

Miller, J.; Hutchins, M.; McGrane, S. J.; Kjeldsen, T. R.; Rowland, C.; Hagen-Zanker, A.; Rickards, N. J.; Fidal, J.; Vesuviano, G.; Hitt, O.

2016-12-01

Rapid urbanisation coupled with climate change poses a significant threat of increased flooding in urban locations around the world. In the UK there is a lack of joined up science and monitoring data to support model development and management decisions required for a rapidly growing population. Here, we present the findings from a multi-disciplinary research project entitled POLLCURB involving a combination of both monitoring and modelling approaches, including participatory citizen science, to evaluate impacts of urbanisation and climate change on flooding and water quality in the Thames basin, United Kingdom. Empirical analysis of five years of monitoring data in intensely monitored sub-catchments reveals the degree to which urban land-use impacts upon hydrological and water quality response. Analysis reveals hydrological impacts do not always follow the expected urban gradient due to intra-catchment differences in hydraulic functions. Statistical detection and attribution techniques are used to assess long-term river data, highlighting strong signals of urban growth after climate variability is accounted for. Historical land-use change mapping of the Thames basin using remote sensing shows growth in urban coverage from around 13% (1980's) to 15% (2015) and was used to develop and train a cellular automata model. Projections of a business-as-usual scenario indicates future growth of 12% by 2035. Future potential changes to flooding and water quality are assessed under urbanisation and climate scenarios for the Thames region to provide comparative and cumulative analysis of how these drivers will affect existing and new urban areas within the Thames basin. Results show the relative and cumulative impacts that both urbanisation and climate change have on basin hydrology and water quality, and highlight the improvements in modelling accuracy when utilising high-resolution data. Discussion is made of results in relation to modelling, policy, mitigation options, and implications for further scientific research.

Wind and rain are the primary climate factors driving changing phenology of an aerial insectivore.

PubMed

Irons, Rachel D; Harding Scurr, April; Rose, Alexandra P; Hagelin, Julie C; Blake, Tricia; Doak, Daniel F

2017-04-26

While the ecological effects of climate change have been widely observed, most efforts to document these impacts in terrestrial systems have concentrated on the impacts of temperature. We used tree swallow ( Tachycineta bicolor ) nest observations from two widely separated sites in central Alaska to examine the aspects of climate affecting breeding phenology at the northern extent of this species' range. We found that two measures of breeding phenology, annual lay and hatch dates, are more strongly predicted by windiness and precipitation than by temperature. At our longest-monitored site, breeding phenology has advanced at nearly twice the rate seen in more southern populations, and these changes correspond to long-term declines in windiness. Overall, adverse spring climate conditions known to negatively impact foraging success of swallows (wet, windy weather) appear to influence breeding phenology more than variation in temperature. Separate analyses show that short windy periods significantly delay initiation of individual clutches within years. While past reviews have emphasized that increasing variability in climate conditions may create physiological and ecological challenges for natural populations, we find that long-term reductions in inclement weather corresponded to earlier reproduction in one of our study populations. To better predict climate change impacts, ecologists need to more carefully test effects of multiple climate variables, including some, like windiness, that may be of paramount importance to some species, but have rarely been considered as strong drivers of ecological responses to climate alteration. © 2017 The Author(s).

Wind and rain are the primary climate factors driving changing phenology of an aerial insectivore

PubMed Central

Irons, Rachel D.; Harding Scurr, April; Rose, Alexandra P.; Hagelin, Julie C.; Blake, Tricia

2017-01-01

While the ecological effects of climate change have been widely observed, most efforts to document these impacts in terrestrial systems have concentrated on the impacts of temperature. We used tree swallow (Tachycineta bicolor) nest observations from two widely separated sites in central Alaska to examine the aspects of climate affecting breeding phenology at the northern extent of this species' range. We found that two measures of breeding phenology, annual lay and hatch dates, are more strongly predicted by windiness and precipitation than by temperature. At our longest-monitored site, breeding phenology has advanced at nearly twice the rate seen in more southern populations, and these changes correspond to long-term declines in windiness. Overall, adverse spring climate conditions known to negatively impact foraging success of swallows (wet, windy weather) appear to influence breeding phenology more than variation in temperature. Separate analyses show that short windy periods significantly delay initiation of individual clutches within years. While past reviews have emphasized that increasing variability in climate conditions may create physiological and ecological challenges for natural populations, we find that long-term reductions in inclement weather corresponded to earlier reproduction in one of our study populations. To better predict climate change impacts, ecologists need to more carefully test effects of multiple climate variables, including some, like windiness, that may be of paramount importance to some species, but have rarely been considered as strong drivers of ecological responses to climate alteration. PMID:28446701

Real-Time Monitoring of Mountain Conifer Growth Response to Seasonal Climate and the Summer Monsoon in the Great Basin of North America

NASA Astrophysics Data System (ADS)

Strachan, S.; Biondi, F.

2013-12-01

Tree rings in the American intermountain west are often used for palaeoclimatic purposes, including reconstructions of precipitation, temperature, and drought. Specific seasonal phenomena such as the North American Monsoon (NAM) are also being identified in tree-ring studies as being related to certain growth features in the rings (such as early-onset 'false' latewood). These relationships have historically been developed using statistical relationships between tree-ring chronologies and regional weather observations. In zones near the periphery of the NAM, summertime precipitation may be more sporadic, yet localized vegetation assemblages in the northern Mojave desert and Great Basin regions indicate that these events are still important for some ecosystems which have established in areas where NAM activity is present. Major shifts in NAM behavior in the past may have been recorded by tree rings, and identifying the specific mechanisms/circumstances by which this occurs is critical for efforts seeking to model ecosystem response to climate changes. By establishing in-situ monitoring of climate/weather, soils, and tree-growth variables in Pinus ponderosa scopulorum and Pinus monophylla zones at study sites in eastern/southern Nevada, we are able to address these issues at very fine spatial and temporal scales. Data from two seasons of monitoring precipitation, solar radiation, air temperature, soil temperature, soil water content, tree sap flow, tree radial distance increment, and hourly imagery are presented. Point dendrometers along with sap flow sensors monitor growth in these ponderosa pine around the clock to help researchers understand tree-ring/climate relationships.

Long-term monitoring at multiple trophic levels suggests heterogeneity in responses to climate change in the Canadian Arctic tundra

PubMed Central

Gauthier, Gilles; Bêty, Joël; Cadieux, Marie-Christine; Legagneux, Pierre; Doiron, Madeleine; Chevallier, Clément; Lai, Sandra; Tarroux, Arnaud; Berteaux, Dominique

2013-01-01

Arctic wildlife is often presented as being highly at risk in the face of current climate warming. We use the long-term (up to 24 years) monitoring records available on Bylot Island in the Canadian Arctic to examine temporal trends in population attributes of several terrestrial vertebrates and in primary production. Despite a warming trend (e.g. cumulative annual thawing degree-days increased by 37% and snow-melt date advanced by 4–7 days over a 23-year period), we found little evidence for changes in the phenology, abundance or productivity of several vertebrate species (snow goose, foxes, lemmings, avian predators and one passerine). Only primary production showed a response to warming (annual above-ground biomass of wetland graminoids increased by 123% during this period). We nonetheless found evidence for potential mismatches between herbivores and their food plants in response to warming as snow geese adjusted their laying date by only 3.8 days on average for a change in snow-melt of 10 days, half of the corresponding adjustment shown by the timing of plant growth (7.1 days). We discuss several reasons (duration of time series, large annual variability, amplitude of observed climate change, nonlinear dynamic or constraints imposed by various rate of warming with latitude in migrants) to explain the lack of response by herbivores and predators to climate warming at our study site. We also show how length and intensity of monitoring could affect our ability to detect temporal trends and provide recommendations for future monitoring. PMID:23836788

Lake Ice Monitoring with Webcams

NASA Astrophysics Data System (ADS)

Xiao, M.; Rothermel, M.; Tom, M.; Galliani, S.; Baltsavias, E.; Schindler, K.

2018-05-01

Continuous monitoring of climate indicators is important for understanding the dynamics and trends of the climate system. Lake ice has been identified as one such indicator, and has been included in the list of Essential Climate Variables (ECVs). Currently there are two main ways to survey lake ice cover and its change over time, in-situ measurements and satellite remote sensing. The challenge with both of them is to ensure sufficient spatial and temporal resolution. Here, we investigate the possibility to monitor lake ice with video streams acquired by publicly available webcams. Main advantages of webcams are their high temporal frequency and dense spatial sampling. By contrast, they have low spectral resolution and limited image quality. Moreover, the uncontrolled radiometry and low, oblique viewpoints result in heavily varying appearance of water, ice and snow. We present a workflow for pixel-wise semantic segmentation of images into these classes, based on state-of-the-art encoder-decoder Convolutional Neural Networks (CNNs). The proposed segmentation pipeline is evaluated on two sequences featuring different ground sampling distances. The experiment suggests that (networks of) webcams have great potential for lake ice monitoring. The overall per-pixel accuracies for both tested data sets exceed 95 %. Furthermore, per-image discrimination between ice-on and ice-off conditions, derived by accumulating per-pixel results, is 100 % correct for our test data, making it possible to precisely recover freezing and thawing dates.

Monitoring and projecting snow on Hawaii Island

NASA Astrophysics Data System (ADS)

Zhang, Chunxi; Hamilton, Kevin; Wang, Yuqing

2017-05-01

The highest mountain peaks on Hawaii Island are snow covered for part of almost every year. This snow has aesthetic and recreational value as well as cultural significance for residents and visitors. Thus far there have been almost no systematic observations of snowfall, snow cover, or snow depth in Hawaii. Here we use satellite observations to construct a daily index of Hawaii Island snow cover starting from 2000. The seasonal mean of our index displays large interannual variations that are correlated with the seasonal mean freezing level and frequency of trade wind inversions as determined from nearby balloon soundings. Our snow cover index provides a diagnostic for monitoring climate variability and trends within the extensive area of the globe dominated by the North Pacific trade wind meteorological regime. We have also conducted simulations of the Hawaii climate with a regional atmospheric model. Retrospective simulations for 1990-2015 were run with boundary conditions prescribed from gridded observational analyses. Simulations for the end of 21st century employed boundary conditions based on global climate model projections that included standard scenarios for anticipated anthropogenic climate forcing. The future projections indicate that snowfall will nearly disappear by the end of the current century.

The Challenges of Developing a Framework for Global Water Cycle Monitoring and Prediction (Alfred Wegener Medal Lecture)

NASA Astrophysics Data System (ADS)

Wood, Eric F.

2014-05-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ("From Observations to Decisions") recognizes that "water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity", and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the developments at Princeton University towards a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. At every step there are scientific challenges whose solutions are only partially being solved. In addition there are challenges in delivering such systems as "climate services", especially to societies with low technical capacity such as rural agriculturalists in sub-Saharan Africa, but whose needs for such information are great. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Phase I of a National Phenological Assessment

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Henebry, G. M.

2009-12-01

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 timescales. We propose a scoping study to identify, formulate, and refine approaches to the first National Phenological Assessment (NPA) for the U.S. The NPA should be viewed as a data product of the USA-National Phenology Network that will help guide future phenological monitoring and research at the national level. We envision three main objectives for the first NPA: 1) Establish a suite of indicators of phenological change (IPCs) at regional to continental scales, following the Heinz Center model for such national assessments; 2) Using sufficiently long and broad-scale time series of IPCs and legacy phenological data, assess phenological responses to what many scientists are calling the early stages of anthropogenic climate change, specifically the abrupt advance in spring onset in the late 1970’s/early 1980’s 3) Project large-scale phenological changes into 21st Century using GCM and RCM model realizations. Toward this end we see the following tasks as critical preliminary work to plan the first NPA: a) Identify, evaluate, and refine IPCs based on indices developed from standard weather observations, streamflow and other hydrological observations (e.g., center of mass, lake freeze/thaw, etc.), plant and animal phenology observations from legacy datasets, remote sensing datastreams, flux tower observations, and GCM and RCM model realizations; b) Evaluate covariability between IPCs, legacy phenological data, and large-scale modes of climate variability to help detection and attribution of supposed secular trends and development of short and long-lead forecasts for phenological variations; c) identify, evaluate, and refine optimal methods for quantifying what constitutes significant statistical and ecological change in phenological indicators, given uncertainties in both data and methods and defined range of natural variability; d) identify, evaluate, and refine key questions of natural resource managers regarding phenological indicators for monitoring and adaptive management of habitats and wildlife, given the spectrum of management objectives on federal, state, and private lands.

Vegetation optical depth measured by microwave radiometry as an indicator of tree mortality risk

NASA Astrophysics Data System (ADS)

Rao, K.; Anderegg, W.; Sala, A.; Martínez-Vilalta, J.; Konings, A. G.

2017-12-01

Increased drought-related tree mortality has been observed across several regions in recent years. Vast spatial extent and high temporal variability makes field monitoring of tree mortality cumbersome and expensive. With global coverage and high temporal revisit, satellite remote sensing offers an unprecedented tool to monitor terrestrial ecosystems and identify areas at risk of large drought-driven tree mortality events. To date, studies that use remote sensing data to monitor tree mortality have focused on external climatic thresholds such as temperature and evapotranspiration. However, this approach fails to consider internal water stress in vegetation - which can vary across trees even for similar climatic conditions due to differences in hydraulic behavior, soil type, etc - and may therefore be a poor basis for measuring mortality events. There is a consensus that xylem hydraulic failure often precedes drought-induced mortality, suggesting depleted canopy water content shortly before onset of mortality. Observations of vegetation optical depth (VOD) derived from passive microwave are proportional to canopy water content. In this study, we propose to use variations in VOD as an indicator of potential tree mortality. Since VOD accounts for intrinsic water stress undergone by vegetation, it is expected to be more accurate than external climatic stress indicators. Analysis of tree mortality events in California, USA observed by airborne detection shows a consistent relationship between mortality and the proposed VOD metric. Although this approach is limited by the kilometer-scale resolution of passive microwave radiometry, our results nevertheless demonstrate that microwave-derived estimates of vegetation water content can be used to study drought-driven tree mortality, and may be a valuable tool for mortality predictions if they can be combined with higher-resolution variables.

Thermal comfort in Quebec City, Canada: sensitivity analysis of the UTCI and other popular thermal comfort indices in a mid-latitude continental city.

PubMed

Provençal, Simon; Bergeron, Onil; Leduc, Richard; Barrette, Nathalie

2016-04-01

The newly developed Universal Thermal Climate Index (UTCI), along with the physiological equivalent temperature (PET), the humidex (HX) and the wind chill index (WC), was calculated in Quebec City, Canada, a city with a strong seasonal climatic variability, over a 1-year period. The objective of this study is twofold: evaluate the operational benefits of implementing the UTCI for a climate monitoring program of public comfort and health awareness as opposed to relying on traditional and simple indices, and determine whether thermal comfort monitoring specific to dense urban neighborhoods is necessary to adequately fulfill the goals of the program. In order to do so, an analysis is performed to evaluate each of these indices' sensitivity to the meteorological variables that regulate them in different environments. Overall, the UTCI was found to be slightly more sensitive to mean radiant temperature, moderately more sensitive to humidity and much more sensitive to wind speed than the PET. This dynamic changed slightly depending on the environment and the season. In hot weather, the PET was found to be more sensitive to mean radiant temperature and therefore reached high values that could potentially be hazardous more frequently than the UTCI and the HX. In turn, the UTCI's stronger sensitivity to wind speed makes it a superior index to identify potentially hazardous weather in winter compared to the PET and the WC. Adopting the UTCI broadly would be an improvement over the traditionally popular HX and WC indices. The urban environment produced favorable conditions to sustain heat stress conditions, where the indices reached high values more frequently there than in suburban locations, which advocates for weather monitoring specific to denser urban areas.

Thermal comfort in Quebec City, Canada: sensitivity analysis of the UTCI and other popular thermal comfort indices in a mid-latitude continental city

NASA Astrophysics Data System (ADS)

Provençal, Simon; Bergeron, Onil; Leduc, Richard; Barrette, Nathalie

2016-04-01

The newly developed Universal Thermal Climate Index (UTCI), along with the physiological equivalent temperature (PET), the humidex (HX) and the wind chill index (WC), was calculated in Quebec City, Canada, a city with a strong seasonal climatic variability, over a 1-year period. The objective of this study is twofold: evaluate the operational benefits of implementing the UTCI for a climate monitoring program of public comfort and health awareness as opposed to relying on traditional and simple indices, and determine whether thermal comfort monitoring specific to dense urban neighborhoods is necessary to adequately fulfill the goals of the program. In order to do so, an analysis is performed to evaluate each of these indices' sensitivity to the meteorological variables that regulate them in different environments. Overall, the UTCI was found to be slightly more sensitive to mean radiant temperature, moderately more sensitive to humidity and much more sensitive to wind speed than the PET. This dynamic changed slightly depending on the environment and the season. In hot weather, the PET was found to be more sensitive to mean radiant temperature and therefore reached high values that could potentially be hazardous more frequently than the UTCI and the HX. In turn, the UTCI's stronger sensitivity to wind speed makes it a superior index to identify potentially hazardous weather in winter compared to the PET and the WC. Adopting the UTCI broadly would be an improvement over the traditionally popular HX and WC indices. The urban environment produced favorable conditions to sustain heat stress conditions, where the indices reached high values more frequently there than in suburban locations, which advocates for weather monitoring specific to denser urban areas.

Tree-ring δ18O in African mahogany (Entandrophragma utile) records regional precipitation and can be used for climate reconstructions

NASA Astrophysics Data System (ADS)

van der Sleen, Peter; Groenendijk, Peter; Zuidema, Pieter A.

2015-04-01

The availability of instrumental climate data in West and Central Africa is very restricted, both in space and time. This limits the understanding of the regional climate system and the monitoring of climate change and causes a need for proxies that allow the reconstruction of paleoclimatic variability. Here we show that oxygen isotope values (δ18O) in tree rings of Entandrophragma utile from North-western Cameroon correlate to precipitation on a regional to sub-continental scale (1930-2009). All found correlations were negative, following the proposed recording of the 'amount effect' by trees in the tropics. The capacity of E. utile to record the variability of regional precipitation is also confirmed by the significant correlation of tree-ring δ18O with river discharge data (1944-1983), outgoing longwave radiation (a proxy for cloud cover; 1974-2011) and sea surface salinity in the Gulf of Guinea (1950-2011). Furthermore, the high values in the δ18O chronology from 1970 onwards coincide with the Sahel drought period. Given that E. utile presents clear annual growth rings, has a wide-spread distribution in tropical Africa and is long lived (> 250 years), we argue that the analysis of oxygen isotopes in growth rings of this species is a promising tool for the study of paleoclimatic variability during the last centuries in West and Central Africa.

Spatio-temporal patterns and climate variables controlling of biomass carbon stock of global grassland ecosystems from 1982 to 2006

USGS Publications Warehouse

Xia, Jiangzhou; Liu, Shuguang; Liang, Shunlin; Chen, Yang; Xu, Wenfang; Yuan, Wenping

2014-01-01

Grassland ecosystems play an important role in subsistence agriculture and the global carbon cycle. However, the global spatio-temporal patterns and environmental controls of grassland biomass are not well quantified and understood. The goal of this study was to estimate the spatial and temporal patterns of the global grassland biomass and analyze their driving forces using field measurements, Normalized Difference Vegetation Index (NDVI) time series from satellite data, climate reanalysis data, and a satellite-based statistical model. Results showed that the NDVI-based biomass carbon model developed from this study explained 60% of the variance across 38 sites globally. The global carbon stock in grassland aboveground live biomass was 1.05 Pg·C, averaged from 1982 to 2006, and increased at a rate of 2.43 Tg·C·y−1 during this period. Temporal change of the global biomass was significantly and positively correlated with temperature and precipitation. The distribution of biomass carbon density followed the precipitation gradient. The dynamics of regional grassland biomass showed various trends largely determined by regional climate variability, disturbances, and management practices (such as grazing for meat production). The methods and results from this study can be used to monitor the dynamics of grassland aboveground biomass and evaluate grassland susceptibility to climate variability and change, disturbances, and management.

Forecasting climate change impacts to plant community composition in the Sonoran Desert region

USGS Publications Warehouse

Munson, Seth M.; Webb, Robert H.; Belnap, Jayne; Hubbard, J. Andrew; Swann, Don E.; Rutman, Sue

2012-01-01

Hotter and drier conditions projected for the southwestern United States can have a large impact on the abundance and composition of long-lived desert plant species. We used long-term vegetation monitoring results from 39 large plots across four protected sites in the Sonoran Desert region to determine how plant species have responded to past climate variability. This cross-site analysis identified the plant species and functional types susceptible to climate change, the magnitude of their responses, and potential climate thresholds. In the relatively mesic mesquite savanna communities, perennial grasses declined with a decrease in annual precipitation, cacti increased, and there was a reversal of the Prosopis velutina expansion experienced in the 20th century in response to increasing mean annual temperature (MAT). In the more xeric Arizona Upland communities, the dominant leguminous tree, Cercidium microphyllum, declined on hillslopes, and the shrub Fouquieria splendens decreased, especially on south- and west-facing slopes in response to increasing MAT. In the most xeric shrublands, the codominant species Larrea tridentata and its hemiparasite Krameria grayi decreased with a decrease in cool season precipitation and increased aridity, respectively. This regional-scale assessment of plant species response to recent climate variability is critical for forecasting future shifts in plant community composition, structure, and productivity.

The global climate of December 1992-February 1993. Part 2: Large-scale variability across the tropical western Pacific during TOGA COARE

NASA Technical Reports Server (NTRS)

Gutzler, D. S.; Kiladis, G. N.; Meehl, G. A.; Weickmann, K. M.; Wheeler, M.

1994-01-01

Recently, scientists from more than a dozen countries carried out the field phase of a project called the Coupled-Atmosphere Response Experiment (COARE), devoted to describing the ocean-atmosphere system of the western Pacific near-equatorial warm pool. The project was conceived, organized, and funded under the auspices of the International Tropical Ocean Global Atmosphere (TOGA) Program. Although COARE consisted of several field phases, including a year-long atmospheric enhanced monitoring period (1 July 1992 -- 30 June 1993), the heart of COARE was its four-month Intensive Observation Period (IOP) extending from 1 Nov. 1992 through 28 Feb. 1993. An overview of large-scale variability during COARE is presented. The weather and climate observed in the IOP is placed into context with regard to large-scale, low-frequency fluctuations of the ocean-atmosphere system. Aspects of tropical variability beginning in Aug. 1992 and extending through Mar. 1993, with some sounding data for Apr. 1993 are considered. Variability over the large-scale sounding array (LSA) and the intensive flux array (IFA) is emphasized.

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

USGS Publications Warehouse

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

2016-01-01

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

Demographic Responses To Climate Manipulations Across a Species Range

NASA Astrophysics Data System (ADS)

Oldfather, M. F.

2016-12-01

Species biogeographic responses to climate change will occur through the local extinction and establishment of populations. The overall performance of populations across a species range is shaped by the idiosyncratic sensitivities of demographic rates to the changing climate conditions. Heterogeneous topography partially decouples temperature and soil moisture presenting an opportunity to disentangle demographic sensitivity to multiple local climate variables and refine range shift predictions in response to complex climate change. Since 2013, I have monitored 16 populations of a long-lived alpine plant, Ivesia lycopodioides var. scandularis (Rosaceae) across the entirety of its altitudinal range in the arid White Mountains, CA (3350 - 4420m). I quantified microclimatic soil moisture and temperature, and the demographic rates of over 4,000 individuals. Demographic rates exhibited sensitivity to accumulated degree-days (ex. reproduction), soil volumetric water content (ex. germination), or the interaction between these climate variables (ex. survival). These observations motivated an experimental test of the relationship between demography and local climate with manipulations of increased summertime temperature and precipitation in nine populations. All demographic rates were sensitive to the climate manipulations and the magnitude of the demographic response depended on the population's location within the range. However, the modeled population growth rate was only minimally affected by the manipulations in most populations. The inverse responses of many of the demographic rates may allow populations to demographically buffer against the climate manipulations. However, in one low elevation edge population the negative effect of heating on survival overwhelmed the positive effect on germination, indicating that the capacity of populations to demographically buffer may have a limit.

Determination of the spatial variability of temperature and moisture near a tropical Pacific island with MTI satellite images

NASA Astrophysics Data System (ADS)

Kurzeja, Robert J.; O'Steen, Byron L.; Pendergast, Malcolm M.

2002-01-01

The Tropical Pacific Island of Nauru is a US DOE ARM observation site that monitors tropical climate and atmospheric radiation. This observation site is ideal for validating MTI images because of the extensive deployment of continuously operating instruments. MTI images are also useful in assessing the effect of the island on the ocean climate and on the ARM data. An MTI image has been used to determine the spatial distribution of water vapor and sea-surface temperature near the island. The results are compared with a three-dimensional numerical model simulation.

Mediterranean dunes on the go: Evidence from a short term study on coastal herbaceous vegetation

NASA Astrophysics Data System (ADS)

Prisco, Irene; Stanisci, Angela; Acosta, Alicia T. R.

2016-12-01

Detailed monitoring studies on permanent sites are a promising tool for an accurate evaluation of short, medium or long term vegetation dynamics. This work aims to evaluate short-term changes in coastal dune herbaceous plant species and EU Habitats through a multi-temporal analysis using permanent vegetation transects. In particular, (I) we analyze changes in species richness of coastal habitats; (II) we identify changes in plant cover of selected focal plants; and (III) we relate the changes to selected climatic variables and erosion/accretion processes. We selected one of the Italian's peninsula best preserved coastal dune areas (ca. 50 km along the Adriatic sea) with a relatively homogeneous coastal zonation and low anthropic pressure but with different erosion/accretion processes. We explored changes in richness over time using generalized linear models (GLMs). We identified different ecological guilds: focal, ruderal and alien plant species and investigated temporal trends in these guilds' species richness. We also applied GLMs to determine how plant cover of the most important focal species have changed over time. Overall, in this study we observed that the influence of climatic variables was relatively small. However, we found remarkable different trends in response to erosion/accretion processes both at community and at species level. Thus, our results highlight the importance of coastal dynamics in preserving not only coastal vegetation zonation, but also species richness and focal species cover. Moreover, we identified the dune grasslands as the most sensitive habitat for detecting the influence of climatic variables throughout a short term monitoring survey. Information from this study provides useful insights for detecting changes in vegetation, for establishing habitat protection priorities and for improving conservation efforts for these fragile ecosystems.

Solar radiation variability over La Réunion island and associated larger-scale dynamics

NASA Astrophysics Data System (ADS)

Mialhe, Pauline; Morel, Béatrice; Pohl, Benjamin; Bessafi, Miloud; Chabriat, Jean-Pierre

2017-04-01

This study aims to examine the solar radiation variability over La Réunion island and its relationship with large-scale circulation. The Satellite Application Facility on Climate Monitoring (CM SAF) produces a Shortwave Incoming Solar radiation (SIS) data record called Solar surfAce RAdiation Heliosat - East (SARAH-E). A comparison to in situ observations from Météo-France measurements networks quantifies the skill of SARAH-E grids which we use as dataset. First step of the work, irradiance mean cycles are calculated to describe the diurnal-seasonal SIS behaviour over La Réunion island. By analogy with the climate anomalies, instantaneous deviations are computed after removal of the mean states. Finally, we associate these anomalies with larger-scale atmospheric dynamics into the South West Indian Ocean by applying multivariate clustering analyses (Hierarchical Ascending Classification, k-means).

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-09-01

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

Active layer and permafrost thermal regime in a patterned ground soil in Maritime Antarctica, and relationship with climate variability models.

PubMed

Chaves, D A; Lyra, G B; Francelino, M R; Silva, Ldb; Thomazini, A; Schaefer, Cegr

2017-04-15

Permafrost and active layer studies are important to understand and predict regional climate changes. The objectives of this work were: i) to characterize the soil thermal regime (active layer thickness and permafrost formation) and its interannual variability and ii) to evaluate the influence of different climate variability modes to the observed soil thermal regime in a patterned ground soil in Maritime Antarctica. The study was carried out at Keller Peninsula, King George Island, Maritime Antarctica. Six soil temperatures probes were installed at different depths (10, 30 and 80cm) in the polygon center (Tc) and border (Tb) of a patterned ground soil. We applied cross-correlation analysis and standardized series were related to the Antarctic Oscillation Index (AAO). The estimated active layer thickness was approximately 0.75cm in the polygon border and 0.64cm in the center, indicating the presence of permafrost (within 80cm). Results indicate that summer and winter temperatures are becoming colder and warmer, respectively. Considering similar active layer thickness, the polygon border presented greater thawing days, resulting in greater vulnerability to warming, cooling faster than the center, due to its lower volumetric heat capacity (Cs). Cross-correlation analysis indicated statistically significant delay of 1day (at 10cm depth) in the polygon center, and 5days (at 80cm depth) for the thermal response between atmosphere and soil. Air temperature showed a delay of 5months with the climate variability models. The influence of southern winds from high latitudes, in the south facing slopes, favored freeze in the upper soil layers, and also contributed to keep permafrost closer to the surface. The observed cooling trend is linked to the regional climate variability modes influenced by atmospheric circulation, although longer monitoring period is required to reach a more precise scenario. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of the global MODIS 30 arc-second spatially and temporally complete snow-free land surface albedo and reflectance anisotropy dataset

NASA Astrophysics Data System (ADS)

Sun, Qingsong; Wang, Zhuosen; Li, Zhan; Erb, Angela; Schaaf, Crystal B.

2017-06-01

Land surface albedo is an essential variable for surface energy and climate modeling as it describes the proportion of incident solar radiant flux that is reflected from the Earth's surface. To capture the temporal variability and spatial heterogeneity of the land surface, satellite remote sensing must be used to monitor albedo accurately at a global scale. However, large data gaps caused by cloud or ephemeral snow have slowed the adoption of satellite albedo products by the climate modeling community. To address the needs of this community, we used a number of temporal and spatial gap-filling strategies to improve the spatial and temporal coverage of the global land surface MODIS BRDF, albedo and NBAR products. A rigorous evaluation of the gap-filled values shows good agreement with original high quality data (RMSE = 0.027 for the NIR band albedo, 0.020 for the red band albedo). This global snow-free and cloud-free MODIS BRDF and albedo dataset (established from 2001 to 2015) offers unique opportunities to monitor and assess the impact of the changes on the Earth's land surface.

Impacts of climate change on public health in India: future research directions.

PubMed

Bush, Kathleen F; Luber, George; Kotha, S Rani; Dhaliwal, R S; Kapil, Vikas; Pascual, Mercedes; Brown, Daniel G; Frumkin, Howard; Dhiman, R C; Hess, Jeremy; Wilson, Mark L; Balakrishnan, Kalpana; Eisenberg, Joseph; Kaur, Tanvir; Rood, Richard; Batterman, Stuart; Joseph, Aley; Gronlund, Carina J; Agrawal, Arun; Hu, Howard

2011-06-01

Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions. Building on the information presented at the 2009 Joint Indo-U.S. Workshop on Climate Change and Health in Goa, India, we reviewed relevant literature and data, addressed gaps in knowledge, and identified priorities and strategies for future research in India. The scope of the problem in India is enormous, based on the potential for climate change and variability to exacerbate endemic malaria, dengue, yellow fever, cholera, and chikungunya, as well as chronic diseases, particularly among the millions of people who already experience poor sanitation, pollution, malnutrition, and a shortage of drinking water. Ongoing efforts to study these risks were discussed but remain scant. A universal theme of the recommendations developed was the importance of improving the surveillance, monitoring, and integration of meteorological, environmental, geospatial, and health data while working in parallel to implement adaptation strategies. It will be critical for India to invest in improvements in information infrastructure that are innovative and that promote interdisciplinary collaborations while embarking on adaptation strategies. This will require unprecedented levels of collaboration across diverse institutions in India and abroad. The data can be used in research on the likely impacts of climate change on health that reflect India's diverse climates and populations. Local human and technical capacities for risk communication and promoting adaptive behavior must also be enhanced.

Low-resolution Australasian palaeoclimate records of the last 2000 years

NASA Astrophysics Data System (ADS)

Dixon, Bronwyn C.; Tyler, Jonathan J.; Lorrey, Andrew M.; Goodwin, Ian D.; Gergis, Joëlle; Drysdale, Russell N.

2017-10-01

Non-annually resolved palaeoclimate records in the Australasian region were compiled to facilitate investigations of decadal to centennial climate variability over the past 2000 years. A total of 675 lake and wetland, geomorphic, marine, and speleothem records were identified. The majority of records are located near population centres in southeast Australia, in New Zealand, and across the maritime continent, and there are few records from the arid regions of central and western Australia. Each record was assessed against a set of a priori criteria based on temporal resolution, record length, dating methods, and confidence in the proxy-climate relationship over the Common Era. A subset of 22 records met the criteria and were endorsed for subsequent analyses. Chronological uncertainty was the primary reason why records did not meet the selection criteria. New chronologies based on Bayesian techniques were constructed for the high-quality subset to ensure a consistent approach to age modelling and quantification of age uncertainties. The primary reasons for differences between published and reconstructed age-depth models were the consideration of the non-singular distribution of ages in calibrated 14C dates and the use of estimated autocorrelation between sampled depths as a constraint for changes in accumulation rate. Existing proxies and reconstruction techniques that successfully capture climate variability in the region show potential to address spatial gaps and expand the range of climate variables covering the last 2000 years in the Australasian region. Future palaeoclimate research and records in Australasia could be greatly improved through three main actions: (i) greater data availability through the public archiving of published records; (ii) thorough characterisation of proxy-climate relationships through site monitoring and climate sensitivity tests; and (iii) improvement of chronologies through core-top dating, inclusion of tephra layers where possible, and increased date density during the Common Era.

Projection of climatic suitability for Aedes albopictus Skuse (Culicidae) in Europe under climate change conditions

NASA Astrophysics Data System (ADS)

Fischer, Dominik; Thomas, Stephanie Margarete; Niemitz, Franziska; Reineking, Björn; Beierkuhnlein, Carl

2011-07-01

During the last decades the disease vector Aedes albopictus ( Ae. albopictus) has rapidly spread around the globe. The spread of this species raises serious public health concerns. Here, we model the present distribution and the future climatic suitability of Europe for this vector in the face of climate change. In order to achieve the most realistic current prediction and future projection, we compare the performance of four different modelling approaches, differentiated by the selection of climate variables (based on expert knowledge vs. statistical criteria) and by the geographical range of presence records (native range vs. global range). First, models of the native and global range were built with MaxEnt and were either based on (1) statistically selected climatic input variables or (2) input variables selected with expert knowledge from the literature. Native models show high model performance (AUC: 0.91-0.94) for the native range, but do not predict the European distribution well (AUC: 0.70-0.72). Models based on the global distribution of the species, however, were able to identify all regions where Ae. albopictus is currently established, including Europe (AUC: 0.89-0.91). In a second step, the modelled bioclimatic envelope of the global range was projected to future climatic conditions in Europe using two emission scenarios implemented in the regional climate model COSMO-CLM for three time periods 2011-2040, 2041-2070, and 2071-2100. For both global-driven models, the results indicate that climatically suitable areas for the establishment of Ae. albopictus will increase in western and central Europe already in 2011-2040 and with a temporal delay in eastern Europe. On the other hand, a decline in climatically suitable areas in southern Europe is pronounced in the Expert knowledge based model. Our projections appear unaffected by non-analogue climate, as this is not detected by Multivariate Environmental Similarity Surface analysis. The generated risk maps can aid in identifying suitable habitats for Ae. albopictus and hence support monitoring and control activities to avoid disease vector establishment.

Advantages and applicability of commonly used homogenisation methods for climate data

NASA Astrophysics Data System (ADS)

Ribeiro, Sara; Caineta, Júlio; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina

2014-05-01

Homogenisation of climate data is a very relevant subject since these data are required as an input in a wide range of studies, such as atmospheric modelling, weather forecasting, climate change monitoring, or hydrological and environmental projects. Often, climate data series include non-natural irregularities which have to be detected and removed prior to their use, otherwise it would generate biased and erroneous results. Relocation of weather stations or changes in the measuring instruments are amongst the most relevant causes for these inhomogeneities. Depending on the climate variable, its temporal resolution and spatial continuity, homogenisation methods can be more or less effective. For example, due to its natural variability, precipitation is identified as a very challenging variable to be homogenised. During the last two decades, numerous methods have been proposed to homogenise climate data. In order to compare, evaluate and develop those methods, the European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), was released in 2008. Existing homogenisation methods were improved based on the benchmark exercise issued by this project. A recent approach based on Direct Sequential Simulation (DSS), not yet evaluated by the benchmark exercise, is also presented as an innovative methodology for homogenising climate data series. DSS already proved to be a successful geostatistical method in environmental and hydrological studies, and it provides promising results for the homogenisation of climate data. Since DSS is a geostatistical stochastic approach, it accounts for the joint spatial and temporal dependence between observations, as well as the relative importance of stations both in terms of distance and correlation. This work presents a chronological review of the most commonly used homogenisation methods for climate data and available software packages. A short description and classification is provided for each method. Their advantages and applicability are discussed based on literature review and on the results of the HOME project. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").

A Seamless Framework for Global Water Cycle Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Sheffield, J.; Wood, E. F.; Chaney, N.; Fisher, C. K.; Caylor, K. K.

2013-12-01

The Global Earth Observation System of Systems (GEOSS) Water Strategy ('From Observations to Decisions') recognizes that 'water is essential for ensuring food and energy security, for facilitating poverty reduction and health security, and for the maintenance of ecosystems and biodiversity', and that water cycle data and observations are critical for improved water management and water security - especially in less developed regions. The GEOSS Water Strategy has articulated a number of goals for improved water management, including flood and drought preparedness, that include: (i) facilitating the use of Earth Observations for water cycle observations; (ii) facilitating the acquisition, processing, and distribution of data products needed for effective management; (iii) providing expertise, information systems, and datasets to the global, regional, and national water communities. There are several challenges that must be met to advance our capability to provide near real-time water cycle monitoring, early warning of hydrological hazards (floods and droughts) and risk assessment under climate change, regionally and globally. Current approaches to monitoring and predicting hydrological hazards are limited in many parts of the world, and especially in developing countries where national capacity is limited and monitoring networks are inadequate. This presentation describes the development of a seamless monitoring and prediction framework at all time scales that allows for consistent assessment of water variability from historic to current conditions, and from seasonal and decadal predictions to climate change projections. At the center of the framework is an experimental, global water cycle monitoring and seasonal forecast system that has evolved out of regional and continental systems for the US and Africa. The system is based on land surface hydrological modeling that is driven by satellite remote sensing precipitation to predict current hydrological conditions, flood potential and the state of drought. Seasonal climate model forecasts are downscaled and bias-corrected to drive the land surface model to provide hydrological forecasts and drought products out 6-9 months. The system relies on historic reconstructions of water variability over the 20th century, which forms the background climatology to which current conditions can be assessed. Future changes in water availability and drought risk are quantified based on bias-corrected and downscaled climate model projections that are used to drive the land surface models. For regions with lack of on-the-ground data we are field-testing low-cost environmental sensors and along with new satellite products for terrestrial hydrology and vegetation, integrating these into the system for improved monitoring and prediction. We provide an overview of the system and some examples of real-world applications to flood and drought events, with a focus on Africa.

Gauging climate change effects at local scales: weather-based indices to monitor insect harassment in caribou.

PubMed

Witter, Leslie A; Johnson, Chris J; Croft, Bruno; Gunn, Anne; Poirier, Lisa M

2012-09-01

Climate change is occurring at an accelerated rate in the Arctic. Insect harassment may be an important link between increased summer temperature and reduced body condition in caribou and reindeer (both Rangifer tarandus). To examine the effects of climate change at a scale relevant to Rangifer herds, we developed monitoring indices using weather to predict activity of parasitic insects across the central Arctic. During 2007-2009, we recorded weather conditions and used carbon dioxide baited traps to monitor activity of mosquitoes (Culicidae), black flies (Simuliidae), and oestrid flies (Oestridae) on the post-calving and summer range of the Bathurst barren-ground caribou (Rangifer tarandus groenlandicus) herd in Northwest Territories and Nunavut, Canada. We developed statistical models representing hypotheses about effects of weather, habitat, location, and temporal variables on insect activity. We used multinomial logistic regression to model mosquito and black fly activity, and logistic regression to model oestrid fly presence. We used information theory to select models to predict activity levels of insects. Using historical weather data, we used hindcasting to develop a chronology of insect activity on the Bathurst range from 1957 to 2008. Oestrid presence and mosquito and black fly activity levels were explained by temperature. Wind speed, light intensity, barometric pressure, relative humidity, vegetation, topography, location, time of day, and growing degree-days also affected mosquito and black fly levels. High predictive ability of all models justified the use of weather to index insect activity. Retrospective analyses indicated conditions favoring mosquito activity declined since the late 1950s, while predicted black fly and oestrid activity increased. Our indices can be used as monitoring tools to gauge potential changes in insect harassment due to climate change at scales relevant to caribou herds.

Numerical modelling of climate change impacts on freshwater lenses on the North Sea Island of Borkum

NASA Astrophysics Data System (ADS)

Sulzbacher, H.; Wiederhold, H.; Siemon, B.; Grinat, M.; Igel, J.; Burschil, T.; Günther, T.; Hinsby, K.

2012-03-01

A numerical variable-density groundwater model is set up for the North Sea Island of Borkum to estimate climate change impacts on coastal aquifers and especially the situation of barrier islands in the Wadden Sea. The database includes information from boreholes, a seismic survey, a helicopter-borne electromagnetic survey (HEM), monitoring of the freshwater-saltwater boundary by vertical electrode chains in two boreholes, measurements of groundwater table, pumping and slug tests, as well as water samples. Based on a statistical analysis of borehole columns, seismic sections and HEM, a hydrogeological model is set up. The groundwater model is developed using the finite-element programme FEFLOW. The variable-density groundwater model is calibrated on the basis of hydraulic, hydrological and geophysical data, in particular spatial HEM and local monitoring data. Verification runs with the calibrated model show good agreement between measured and computed hydraulic heads. A good agreement is also obtained between measured and computed density or total dissolved solids data for both the entire freshwater lens on a large scale and in the area of the well fields on a small scale. For simulating future changes in this coastal groundwater system until the end of the current century we use the climate scenario A2, specified by the Intergovernmental Panel on Climate Change and in particular the data for the German North Sea coast. Simulation runs show proceeding salinization with time beneath the well fields of the two waterworks Waterdelle and Ostland. The modelling study shows that spreading of well fields is an appropriate protection measure against excessive salinization of the water supply until the end of the current century.

A seamless global hydrological monitoring and forecasting system for water resources assessment and hydrological hazard early warning

NASA Astrophysics Data System (ADS)

Sheffield, Justin; He, Xiaogang; Wood, Eric; Pan, Ming; Wanders, Niko; Zhan, Wang; Peng, Liqing

2017-04-01

Sustainable management of water resources and mitigation of the impacts of hydrological hazards are becoming ever more important at large scales because of inter-basin, inter-country and inter-continental connections in water dependent sectors. These include water resources management, food production, and energy production, whose needs must be weighed against the water needs of ecosystems and preservation of water resources for future generations. The strains on these connections are likely to increase with climate change and increasing demand from burgeoning populations and rapid development, with potential for conflict over water. At the same time, network connections may provide opportunities to alleviate pressures on water availability through more efficient use of resources such as trade in water dependent goods. A key constraint on understanding, monitoring and identifying solutions to increasing competition for water resources and hazard risk is the availability of hydrological data for monitoring and forecasting water resources and hazards. We present a global online system that provides continuous and consistent water products across time scales, from the historic instrumental period, to real-time monitoring, short-term and seasonal forecasts, and climate change projections. The system is intended to provide data and tools for analysis of historic hydrological variability and trends, water resources assessment, monitoring of evolving hazards and forecasts for early warning, and climate change scale projections of changes in water availability and extreme events. The system is particular useful for scientists and stakeholders interested in regions with less available in-situ data, and where forecasts have the potential to help decision making. The system is built on a database of high-resolution climate data from 1950 to present that merges available observational records with bias-corrected reanalysis and satellite data, which then drives a coupled land surface model-flood inundation model to produce hydrological variables and indices at daily, 0.25-degree resolution, globally. The system is updated in near real-time (< 2 days) using satellite precipitation and weather model data, and produces forecasts at short-term (out to 7 days) based on the Global Forecast System (GFS) and seasonal (up to 6 months) based on U.S. National Multi-Model Ensemble (NMME) seasonal forecasts. Climate change projections are based on bias-corrected and downscaled CMIP5 climate data that is used to force the hydrological model. Example products from the system include real-time and forecast drought indices for precipitation, soil moisture, and streamflow, and flood magnitude and extent indices. The model outputs are complemented by satellite based products and indices based on satellite data for vegetation health (MODIS NDVI) and soil moisture (SMAP). We show examples of the validation of the system at regional scales, including how local information can significantly improve predictions, and examples of how the system can be used to understand large-scale water resource issues, and in real-world contexts for early warning, decision making and planning.

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

NASA Technical Reports Server (NTRS)

Greegor, D. H.; Norwine, J.

1981-01-01

A new experimental climatological model/variable termed the sponge, a measure of moisture availability based on daily temperature maxima and minima and precipitation, is tested for potential biogeographic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic from, suggest that, as a generalized climatic index, sponge's simplicity and sensitivity make particularly appropriate for trans-regional biogeographic studies (e.g., large-area and global vegetation monitoring). The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

A gradient model of vegetation and climate utilizing NOAA satellite imagery. Phase 1: Texas transect

NASA Technical Reports Server (NTRS)

Greegor, D.; Norwine, J. (Principal Investigator)

1981-01-01

A climatological model/variable termed the sponge (a measure of moisture availability based on daily temperature maxima and minima, and precipitation) was tested for potential biogeograhic, ecological, and agro-climatological applications. Results, depicted in tabular and graphic form, suggest that, as generalized climatic index, sponge is particularly appropriate for large-area and global vegetation monitoring. The feasibility of utilizing NOAA/AVHRR data for vegetation classification was investigated and a vegetation gradient model that utilizes sponge and AVHRR data was initiated. Along an east-west Texas gradient, vegetation, sponge, and AVHRR pixel data (channels 1 and 2) were obtained for 12 locations. The normalized difference values for the AVHRR data when plotted against vegetation characteristics (biomass, net productivity, leaf area) and sponge values along the Texas gradient suggest that a multivariate gradient model incorporating AVHRR and sponge data may indeed be useful in global vegetation stratification and monitoring.

Mountain hydrology of the western United States

USGS Publications Warehouse

Bales, Roger C.; Molotch, Noah P.; Painter, Thomas H; Dettinger, Michael D.; Rice, Robert; Dozier, Jeff

2006-01-01

Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground‐based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges.

Satellite time-series data for vegetation phenology detection and environmental assessment in Southeast Asia

NASA Astrophysics Data System (ADS)

Suepa, Tanita

The relationship between temporal and spatial data is considered the major advantage of remote sensing in research related to biophysical characteristics. With temporally formatted remote sensing products, it is possible to monitor environmental changes as well as global climate change through time and space by analyzing vegetation phenology. Although a number of different methods have been developed to determine the seasonal cycle using time series of vegetation indices, these methods were not designed to explore and monitor changes and trends of vegetation phenology in Southeast Asia (SEA). SEA is adversely affected by impacts of climate change, which causes considerable environmental problems, and the increase in agricultural land conversion and intensification also adds to those problems. Consequently, exploring and monitoring phenological change and environmental impacts are necessary for a better understanding of the ecosystem dynamics and environmental change in this region. This research aimed to investigate inter-annual variability of vegetation phenology and rainfall seasonality, analyze the possible drivers of phenological changes from both climatic and anthropogenic factors, assess the environmental impacts in agricultural areas, and develop an enhanced visualization method for phenological information dissemination. In this research, spatio-temporal patterns of vegetation phenology were analyzed by using MODIS-EVI time series data over the period of 2001-2010. Rainfall seasonality was derived from TRMM daily rainfall rate. Additionally, this research assessed environmental impacts of GHG emissions by using the environmental model (DNDC) to quantify emissions from rice fields in Thailand. Furthermore, a web mapping application was developed to present the output of phenological and environmental analysis with interactive functions. The results revealed that satellite time-series data provided a great opportunity to study regional vegetation variability and internal climatic fluctuation. The EVI and phenological patterns varied spatially according to climate variations and human management. The overall regional mean EVI value in SEA from 2001 to 2010 has gradually decreased and phenological trends appeared to shift towards a later and slightly longer growing season. Regional vegetation dynamics over SEA exhibited patterns associated with major climate events such as El Nino in 2005. The rainy season tended to start early and end late and the length of rainy season was slightly longer. However, the amount of rainfall has decreased from 2001 to 2010. The relationship between phenology and rainfall varied among different ecosystems. Additionally, the local scale results indicated that rainfall is a dominant force of phenological changes in naturally vegetated areas and rainfed croplands, whereas human management is a key factor in heavily agricultural areas with irrigated systems. The results of estimating GHG emissions from rice fields in Thailand demonstrated that human management, climate variation, and physical geography had a significant influence on the change in GHG emissions. In addition, the complexity of spatio-temporal patterns in phenology and related variables were displayed on the visualization system with effective functions and an interactive interface. The information and knowledge in this research are useful for local and regional environmental management and for identifying mitigation strategies in the context of climate change and ecosystem dynamics in this region.

Climate Prediction Center - Monitoring and Data Index

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News ; Atmospheric Monitoring and Data Monitoring Weather & Climate in Realtime Climate Diagnostics Bulletin Preliminary Climate Diagnostics Bulletin Figures Monthly Atmospheric & Sea Surface Temperature Indices

AgroClimate: Simulating and Monitoring the Risk of Extreme Weather Events from a Crop Phenology Perspective

NASA Astrophysics Data System (ADS)

Fraisse, C.; Pequeno, D.; Staub, C. G.; Perry, C.

2016-12-01

Climate variability, particularly the occurrence of extreme weather conditions such as dry spells and heat stress during sensitive crop developmental phases can substantially increase the prospect of reduced crop yields. Yield losses or crop failure risk due to stressful weather conditions vary mainly due to stress severity and exposure time and duration. The magnitude of stress effects is also crop specific, differing in terms of thresholds and adaptation to environmental conditions. To help producers in the Southeast USA mitigate and monitor the risk of crop losses due to extreme weather events we developed a web-based tool that evaluates the risk of extreme weather events during the season taking into account the crop development stages. Producers can enter their plans for the upcoming season in a given field (e.g. crop, variety, planting date, acreage etc.), select or not a specific El Nino Southern Oscillation (ENSO) phase, and will be presented with the probabilities (ranging from 0 -100%) of extreme weather events occurring during sensitive phases of the growing season for the selected conditions. The DSSAT models CERES-Maize, CROPGRO-Soybean, CROPGRO-Cotton, and N-Wheat phenology models have been translated from FORTRAN to a standalone versions in R language. These models have been tested in collaboration with Extension faculty and producers during the 2016 season and their usefulness for risk mitigation and monitoring evaluated. A companion AgroClimate app was also developed to help producers track and monitor phenology development during the cropping season.

Soil microclimate monitoring in forested and meadow sites

NASA Astrophysics Data System (ADS)

Freyerova, Katerina; Safanda, Jan

2016-04-01

It is well known fact that forest microclimate differs from open area microclimate (Geiger 1965). Less attention is paid to soil temperatures and their long-term monitoring. To evaluate and compare these two environments from the soil microclimate point of view, Institute of Geophysics in Prague monitors soil and air temperatures in Bedřichov in the Jizerské Hory Mountains (Czech Republic). The soil temperatures are measured in three depths (20, 50 and 100 cm) in forest (700 m a. s. l.) and meadow (750 m a. s. l.). Air temperatures are measured at 2m height both in forest and meadow. Nowadays, we have more than three years long time series. The most of studies and experiments described in literature are short-term ones (in order of days or weeks). However, from short-term experiments the seasonal behaviour and trends can be hardly identified and conclusions on soil temperature reaction to climatic extremes such as heat waves, drought or freeze cannot be done with confidence. These drawbacks of the short-term experiments are discussed in literature (eg. Morecroft et al. 1998; Renaud et al. 2011). At the same, with progression of the global warming, the expected increasing frequency of climatic extremes will affect the future form of forest vegetation (Von Arx et al. 2012). The soil and air temperature series, both from the forest and meadow sites, are evaluated and interpreted with respect to long term temperature characteristics and seasonal trends. The emphasis is given on the soil temperature responses to extreme climatic situations. We examine variability between the localities and depths and spatial and temporal changes in this variability. This long-term monitoring allows us to better understand and examine the behaviour of the soil temperature in extreme weather situations. Therefore, we hope to contribute to better prediction of future reactions of this specific environments to the climate change. Literature Geiger, R., 1965. The climate near the ground, Harvard University Press. Available at: https://books.google.cz/books?id=fTpRAAAAMAAJ. Morecroft, M.D., Taylor, M.E. & Oliver, H.R., 1998. Air and soil microclimates of deciduous woodland compared to an open site. Agricultural and Forest Meteorology, 90(1-2), pp.141-156. Renaud, V. et al., 2011. Comparison between open-site and below-canopy climatic conditions in Switzerland for different types of forests over 10 years (1998-2007). Theoretical and Applied Climatology, 105(1-2), pp.119-127. Available at: http://link.springer.com/10.1007/s00704-010-0361-0. Von Arx, G., Dobbertin, M. & Rebetez, M., 2012. Spatio-temporal effects of forest canopy on understory microclimate in a long-term experiment in Switzerland. Agricultural and Forest Meteorology, 166-167, pp.144-155. Available at: http://dx.doi.org/10.1016/j.agrformet.2012.07.018.

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Assessing, Modeling, and Monitoring the Impacts of Extreme Climate Events

NASA Astrophysics Data System (ADS)

Murnane, Richard J.; Diaz, Henry F.

2006-01-01

Extreme weather and climate events provide dramatic content for the news media, and the past few years have supplied plenty of material. The 2004 and 2005 Atlantic hurricane seasons were very active; the United States was struck repeatedly by landfalling major hurricanes. A five-year drought in the southwestern United States was punctuated in 2003 by wildfires in southern California that caused billions of dollars in losses. Ten cyclones of at least tropical storm strength struck Japan in 2004, easily breaking the 1990 and 1993 records of six cyclones each year. Hurricane Catarina was the first recorded hurricane in the South Atlantic. Europe's summer of 2003 saw record-breaking heat that caused tens of thousands of deaths. These events have all been widely publicized, and they naturally raise several questions: Is climate changing, and if so, why? What can we expect in the future? How can we better respond to climate variability regardless of its source?

Aeolian Dunes: New High-Resolution Archives of Past Wind-Intensity and -Direction

NASA Astrophysics Data System (ADS)

Lindhorst, S.; Betzler, C.

2017-12-01

The understanding of the long-term variability of local wind-fields is most relevant for calibrating climate models and for the prediction of the socio-economic consequences of climate change. Continuous instrumental-based weather observations go back less than two centuries; aeolian dunes, however, contain an archive of past wind-field fluctuations which is basically unread. We present new ways to reconstruct annual to seasonal changes of wind intensity and predominant wind direction from dune-sediment composition and -geometries based on ground-penetrating radar (GPR) data, grain-size analyses and different age-dating approaches. Resulting proxy-based data series on wind are validated against instrumental based weather observations. Our approach can be applied to both recent as well as fossil dunes. Potential applications include the validation of climate models, the reconstruction of past supra-regional wind systems and the monitoring of future shifts in the climate system.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Characterizing Mediterranean Land Surfaces as Component of the Regional Climate System by Remote Sensing

NASA Technical Reports Server (NTRS)

Bolle, H.-J.; Koslowsky, D.; Menenti, M.; Nerry, F.; Otterman, Joseph; Starr, D.

1998-01-01

Extensive areas in the Mediterranean region are subject to land degradation and desertification. The high variability of the coupling between the surface and the atmosphere affects the regional climate. Relevant surface characteristics, such as spectral reflectance, surface emissivity in the thermal-infrared region, and vegetation indices, serve as "primary" level indicators for the state of the surface. Their spatial, seasonal and interannual variability can be monitored from satellites. Using relationships between these primary data and combining them with prior information about the land surfaces (such as topography, dominant soil type, land use, collateral ground measurements and models), a second layer of information is built up which specifies the land surfaces as a component of the regional climate system. To this category of parameters which are directly involved in the exchange of energy, momentum and mass between the surface and the atmosphere, belong broadband albedo, thermodynamic surface temperature, vegetation types, vegetation cover density, soil top moisture, and soil heat flux. Information about these parameters finally leads to the computation of sensible and latent heat fluxes. The methodology was tested with pilot data sets. Full resolution, properly calibrated and normalized NOAA-AVHRR multi-annual primary data sets are presently compiled for the whole Mediterranean area, to study interannual variability and longer term trends.

Evaluation of runoff prediction from WEPP-based erosion models for harvested and burned forest watersheds

Treesearch

S. A. Covert; P. R. Robichaud; W. J. Elliot; T. E. Link

2005-01-01

This study evaluates runoff predictions generated by GeoWEPP (Geo-spatial interface to the Water Erosion Prediction Project) and a modified version of WEPP v98.4 for forest soils. Three small (2 to 9 ha) watersheds in the mountains of the interior Northwest were monitored for several years following timber harvest and prescribed fires. Observed climate variables,...

Modern limnology of two lakes in the Tibetan Plateau - evidence from in-situ monitoring

NASA Astrophysics Data System (ADS)

Wang, M.; Li, X.; Lei, L.; He, Y.; Hou, J.

2013-12-01

The mechanisms of climate change in the Tibetan Plateau, known as the Third Pole, receive more and more attention due to its unique geographic location and the influence of multiple climate systems. Among the paleoclimate archives, widespread lakes provide abundant information on past climate changes and have been investigated for decades. Though many high-quality paleolimnological records have been reported in the Tibetan Plateau, little is known about the modern limnological processes in most Tibetan lakes as most lakes are difficult to access and not ready for long-term monitoring. We have installed a series of temperature data logger at different water levels in two Tibetan lakes, Bangong Co and Dagze Co in July 2012 to monitor hourly variability of temperature profile. Bangong Co (33.5°N, 79.8°E, 4245 m asl) is a freshwater lake (salinity ~0.5 g/L) in the westernmost Tibetan Plateau, receiving melt water from mountain glaciers in the basin. Dagze Co (31.9°N, 87.5°E, 4470 m asl) is saline lake (salinity ~15 g/L) in the central Tibetan Plateau, mostly fed by precipitation. In combination with the climate data in the nearby weather stations, we wish to understand the modern limnological processes in the two lakes and their potential effect on the lake biology, sedimentation, and sedimentary biomarkers. Based on the data collected for the first calendar year (Jul 2012 ~ Aug 2013), we anticipate to understand: 1) the influence of climate on the hydrological processes in high elevation lakes; 2) the difference in the metalimnion in meltwater-fed lake (Bangong Co) and precipitation-fed lake (Dagze Co) and their potential effect on the lake biology; 3) the difference in the spring turnover and fall turnover and the effect of meltwater and salinity.

A Model Assessment of Satellite Observed Trends in Polar Sea Ice Extents

NASA Technical Reports Server (NTRS)

Vinnikov, Konstantin Y.; Cavalieri, Donald J.; Parkinson, Claire L.

2005-01-01

For more than three decades now, satellite passive microwave observations have been used to monitor polar sea ice. Here we utilize sea ice extent trends determined from primarily satellite data for both the Northern and Southern Hemispheres for the period 1972(73)-2004 and compare them with results from simulations by eleven climate models. In the Northern Hemisphere, observations show a statistically significant decrease of sea ice extent and an acceleration of sea ice retreat during the past three decades. However, from the modeled natural variability of sea ice extents in control simulations, we conclude that the acceleration is not statistically significant and should not be extrapolated into the future. Observations and model simulations show that the time scale of climate variability in sea ice extent in the Southern Hemisphere is much larger than in the Northern Hemisphere and that the Southern Hemisphere sea ice extent trends are not statistically significant.

Overview of Aerosol Distribution

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

2005-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with clouds and precipitation is still lacking despite decades of research. Understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate. I shall discuss these topics and application of the data to air quality monitoring.

Solar spectral irradiance variability in cycle 24: observations and models

NASA Astrophysics Data System (ADS)

Marchenko, Sergey V.; DeLand, Matthew T.; Lean, Judith L.

2016-12-01

Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265 and 500 nm during the ongoing cycle 24. We supplement the OMI data with concurrent observations from the Global Ozone Monitoring Experiment-2 (GOME-2) and Solar Radiation and Climate Experiment (SORCE) instruments and find fair-to-excellent, depending on wavelength, agreement among the observations, and predictions of the Naval Research Laboratory Solar Spectral Irradiance (NRLSSI2) and Spectral And Total Irradiance REconstruction for the Satellite era (SATIRE-S) models.

Projecting the Global Distribution of the Emerging Amphibian Fungal Pathogen, Batrachochytrium dendrobatidis, Based on IPCC Climate Futures

PubMed Central

Olson, Deanna H.; Blaustein, Andrew R.

2016-01-01

Projected changes in climate conditions are emerging as significant risk factors to numerous species, affecting habitat conditions and community interactions. Projections suggest species range shifts in response to climate change modifying environmental suitability and is supported by observational evidence. Both pathogens and their hosts can shift ranges with climate change. We consider how climate change may influence the distribution of the emerging infectious amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), a pathogen associated with worldwide amphibian population losses. Using an expanded global Bd database and a novel modeling approach, we examined a broad set of climate metrics to model the Bd-climate niche globally and regionally, then project how climate change may influence Bd distributions. Previous research showed that Bd distribution is dependent on climatic variables, in particular temperature. We trained a machine-learning model (random forest) with the most comprehensive global compilation of Bd sampling records (~5,000 site-level records, mid-2014 summary), including 13 climatic variables. We projected future Bd environmental suitability under IPCC scenarios. The learning model was trained with combined worldwide data (non-region specific) and also separately per region (region-specific). One goal of our study was to estimate of how Bd spatial risks may change under climate change based on the best available data. Our models supported differences in Bd-climate relationships among geographic regions. We projected that Bd ranges will shift into higher latitudes and altitudes due to increased environmental suitability in those regions under predicted climate change. Specifically, our model showed a broad expansion of areas environmentally suitable for establishment of Bd on amphibian hosts in the temperate zones of the Northern Hemisphere. Our projections are useful for the development of monitoring designs in these areas, especially for sensitive species and those vulnerable to multiple threats. PMID:27513565

Biodiversity in a changing climate: a synthesis of current and projected trends in the US

USGS Publications Warehouse

Staudinger, Michelle D.; Carter, Shawn L.; Cross, Molly S.; Dubois, Natalie S.; Duffy, J. Emmett; Enquist, Carolyn; Griffis, Roger; Hellmann, Jessica J.; Lawler, Joshua J.; O’Leary, John; Morrison, Scott A.; Sneddon, Lesley; Stein, Bruce A.; Thompson, Laura M.; Turner, Woody

2013-01-01

This paper provides a synthesis of the recent literature describing how global biodiversity is being affected by climate change and is projected to respond in the future. Current studies reinforce earlier findings of major climate-change-related impacts on biological systems and document new, more subtle after-effects. For example, many species are shifting their distributions and phenologies at faster rates than were recorded just a few years ago; however, responses are not uniform across species. Shifts have been idiosyncratic and in some cases counterintuitive, promoting new community compositions and altering biotic interactions. Although genetic diversity enhances species' potential to respond to variable conditions, climate change may outpace intrinsic adaptive capacities and increase the relative vulnerabilities of many organisms. Developing effective adaptation strategies for biodiversity conservation will not only require flexible decision-making and management approaches that account for uncertainties in climate projections and ecological responses but will also necessitate coordinated monitoring efforts.

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

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

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

PubMed

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

2016-05-01

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

GLACIOCLIM-SAMBA: A Terre Adelie / Wilkes Land Antarctic surface mass balance observatory

NASA Astrophysics Data System (ADS)

Genthon, C.; Frezzotti, M.; Le Meur, E.; Magand, O.; Six, D.; Wagnon, P.

2005-12-01

While local measurements at hundreds of sites are now available (although sometimes questionable, e.g. Magand et al., this volume) to verify how large-scale models reproduce the spatial distribution of the surface mass balance (SMB) of Antarctica, few field observations yet make it possible to verify current intra- and inter-annual variability and trends of the SMB in the models, and to evaluate the processes that relate this variability with that of climate. It is a major aim of the GLACIOCLIM-SAMBA observatory (http://lgge.obs.ujf-grenoble.fr/~christo/glacioclim/samba/), initiated in 2004, to provide such observations in the Terre Adelie and Wilkes Land area. Recognizing that the largest absolute changes (and thus contribution to sea-level) of Antarctic SMB are expected where the current mean SMB is largest, that is in the coastal regions, SAMBA is largely focused on ice sheet margin. To sample spatial scales compatible with the scales resolved by models used to predict climate and SMB changes, a 150 km accumulation stakes line is being set up from the coast near the French Dumont d'Urville station, towards to Antarctic plateau in the general direction of the Italy/France Concordia station. Ground penetrating radar survey will provide snap-shot SMB interpolation along the stakes line. A blue ice stretch at the coast is being monitored by a 50-stake ablation network. Three 50-stakes networks are being set up near Concordia station to relate coastal and plateau SMB variability and change. An automatic weather station (AWS, including radiation) deployed at the coast, and the D-10, D-47 and DCII Antarctic Meteorological Research Center (http://amrc.ssec.wisc.edu/) AWSs, provide meteorological information to relate observed SMB and climate. Italian meteorology and radiation programs at Concordia, planned micrometeorology special campaigns at the margin, and precipitation monitoring at both sites, should help decipher the processes that relate SMB and climate variability. As a summary of results on the existing observatory as of Jan; 2005: i) The first year mean SMB along a 50 km stakes line was ~60 cm water equivalent (we), which qualifies 2004 as a very high accumulation year in the Terre Adelie area; ii) Spatial variability along the stakes line is high, ranging from 16 to 125 cm (we), confirming the need for spatial sampling consistent with the scales resolved by climate models; iii) At the coastal blue ice, ablation occurs in summer only while the winter SMB is close to 0. The SAMBA observatory is scheduled to operate for at least 10 years, hopefully more if successful, with main support by the French (IPEV) and Italian (PNRA) Polar Institutes. The French ministry of research and Institut National des Sciences de l'univers (Climate Change and Cryosphere and ORE-GLACIOCLIM programs) also contribute support. All SAMBA observations will be distributed and freely available on the internet as soon as the observatory is fully operational and validated.

U.S. Geological Survey climate and land use change science strategy: a framework for understanding and responding to global change

USGS Publications Warehouse

Burkett, Virginia R.; Kirtland, David A.; Taylor, Ione L.; Belnap, Jayne; Cronin, Thomas M.; Dettinger, Michael D.; Frazier, Eldrich L.; Haines, John W.; Loveland, Thomas R.; Milly, Paul C.D.; ,; ,; ,; Robert, S.; Maule, Alec G.; McMahon, Gerard; Striegl, Robert G.

2013-01-01

In addition to the seven thematic goals, we address the central role of monitoring in accordance with the USGS Science Strategy recommendation that global change research should rely on existing “…decades of observational data and long-term records to interpret consequences of climate variability and change to the Nation’s biological populations, ecosystems, and land and water resources” (U.S. Geological Survey, 2007, p. 19). We also briefly describe specific needs and opportunities for coordinating USGS global change science among USGS Mission Areas and address the need for a comprehensive and sustained communications strategy.

Runoff and recharge processes under a strong semi-arid climatic gradient

NASA Astrophysics Data System (ADS)

Ries, F.; Lange, J.; Sauter, M.; Schmidt, S.

2012-04-01

Hydrological processes in semi-arid environments are highly dynamic. In the eastern slopes of the West Bank these dynamics are even intensified due to the predominant karst morphology, the strong climatic gradient (150-700 mm mean annual precipitation) and the small-scale variability of land use, topography and soil cover. The region is characterized by a scarcity in water resources and a high population growth. Therefore detailed information about the temporal and spatial distribution, amount and variability of available water resources is required. Providing this information by the use of hydrological models is challenging, because available data are extremely limited. From 2007 on, the research area of Wadi Auja, northeast of Jerusalem, has been instrumented with a dense monitoring network. Rainfall distribution and climatic parameters as well as the hydrological reaction of the system along the strong semi-arid climatic gradient are measured on the plot (soil moisture), hillslope (runoff generation) and catchment scale (spring discharge, groundwater level, flood runoff). First data from soil moisture plots situated along the climatic gradient are presented. They allow insights into physical properties of the soil layer and its impact on runoff and recharge processes under different climatic conditions. From continuous soil moisture profiles, soil water balances are calculated for singe events and entire seasons. These data will be used to parameterize the distributed hydrological model TRAIN-ZIN, which has been successfully applied in several studies in the Jordan River Basin.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

Tannat grape composition responses to spatial variability of temperature in an Uruguay's coastal wine region

NASA Astrophysics Data System (ADS)

Fourment, Mercedes; Ferrer, Milka; González-Neves, Gustavo; Barbeau, Gérard; Bonnardot, Valérie; Quénol, Hervé

2017-09-01

Spatial variability of temperature was studied in relation to the berry basic composition and secondary compounds of the Tannat cultivar at harvest from vineyards located in Canelones and Montevideo, the most important wine region of Uruguay. Monitoring of berries and recording of temperature were performed in 10 commercial vineyards of Tannat situated in the southern coastal wine region of the country for three vintages (2012, 2013, and 2014). Results from a multivariate correlation analysis between berry composition and temperature over the three vintages showed that (1) Tannat responses to spatial variability of temperature were different over the vintages, (2) correlations between secondary metabolites and temperature were higher than those between primary metabolites, and (3) correlation values between berry composition and climate variables increased when ripening occurred under dry conditions (below average rainfall). For a particular studied vintage (2013), temperatures explained 82.5% of the spatial variability of the berry composition. Daily thermal amplitude was found to be the most important spatial mode of variability with lower values recorded at plots nearest to the sea and more exposed to La Plata River. The highest levels in secondary compounds were found in berries issued from plots situated as far as 18.3 km from La Plata River. The increasing knowledge of temperature spatial variability and its impact on grape berry composition contributes to providing possible issues to adapt grapevine to climate change.

Modeling Dynamics of South American Rangelands to Climate Variability and Human Impact

NASA Astrophysics Data System (ADS)

Stanimirova, R.; Arevalo, P. A.; Kaufmann, R.; Maus, V.; Lesiv, M.; Havlik, P.; Friedl, M. A.

2017-12-01

The combined pressures of climate change and shifting dietary preferences are creating an urgent need to improve understanding of how climate and land management are jointly affecting the sustainability of rangelands. In particular, our ability to effectively manage rangelands in a manner that satisfies increasing demand for meat and dairy while reducing environmental impact depends on the sensitivity of rangelands to perturbations from both climate (e.g., drought) and land use (e.g., grazing). To characterize the sensitivity of rangeland vegetation to variation in climate, we analyzed gridded time series of satellite and climate data at 0.5-degree spatial resolution from 2003 to 2016 for rangeland ecosystems in South America. We used panel regression and canonical correlation to analyze the relationship between time series of enhanced vegetation index (EVI) derived from NASA's Moderate Spatial Resolution Imaging Spectroradiometer (MODIS) and gridded precipitation and air temperature data from the University of East Anglia's Climate Research Unit. To quantify the degree to which livestock management explains geographic variation of EVI, we used global livestock distribution (FAO) and feed requirements data from the Global Biosphere Management Model (GLOBIOM). Because rangeland ecosystems are sensitive to changes in meteorological variables at different time scales, we evaluated the strength of coupling between anomalies in EVI and anomalies in temperature and standardized precipitation index (SPI) data at 1-6 month lags. Our results show statistically significant relationships between EVI and precipitation during summer, fall, and winter in both tropical and subtropical agroecological zones of South America. Further, lagged precipitation effects, which reflect memory in the system, explain significant variance in winter EVI anomalies. While precipitation emerges as the dominant driver of variability in rangeland greenness, we find evidence of a management-induced signal as well. Our modeling framework integrates satellite observation, meteorological data sets, and land use/cover change information to improve our capability to monitor and manage the long-term sustainability of rangelands.

Variability and Change in the Canadian Cryosphere: A Canadian Science Contribution to International Polar Year

NASA Astrophysics Data System (ADS)

Walker, A. E.; Derksen, C.

2008-12-01

The cryosphere (snow, permafrost and seasonally frozen ground, ice caps and glaciers, sea-, river-, and lake ice) represents a significant feature of the Canadian landscape that impacts climate, hydrology, the economy and the daily lives of all Canadians, especially those living in northern communities. Over the past few decades significant changes have been observed in cryospheric elements (e.g. decreases in snow cover, glacier extent, sea ice cover) that have been attributed to a warming climate. This poster presentation will highlight initial scientific results from the approved Canadian International Polar Year project "Variability and Change in the Canadian Cryosphere" that is being led by Environment Canada and involves 33 co- investigators from government, academia and the private sector and links with international collaborators. This project builds on Canadian strengths in remote sensing, climate analysis and modeling with the overall objective to observe and understand the current state of the cryosphere in Canada and determine how fast it is changing and why. Research activities are focused on: (1) developing new satellite-based capabilities to provide information on the current state of the Canadian cryosphere during the IPY period; (2) placing current cryospheric conditions in the context of the historical record to document the magnitude of changes over the 50 years since the last International Polar Year (IGY 1957-1958); (3) characterizing and explaining the observed variability and changes in the context of the coupled climate cryosphere system; and (4) improving the representation of the cryosphere in Canadian land surface and climate models to provide current and future climate simulations of the cryosphere for climate impact studies. The project also includes several outreach activities to engage northern communities in cryospheric monitoring and incorporate traditional knowledge with remotely-sensed information to generate new maps on local river ice and sea ice conditions to assist residents in planning safe navigation routes.

Prediction of meningococcal meningitis epidemics in western Africa by using climate information

NASA Astrophysics Data System (ADS)

YAKA, D. P.; Sultan, B.; Tarbangdo, F.; Thiaw, W. M.

2013-12-01

The variations of certain climatic parameters and the degradation of ecosystems, can affect human's health by influencing the transmission, the spatiotemporal repartition and the intensity of infectious diseases. It is mainly the case of meningococcal meningitis (MCM) whose epidemics occur particularly in Sahelo-Soudanian climatic area of Western Africa under quite particular climatic conditions. Meningococcal Meningitis (MCM) is a contagious infection disease due to the bacteria Neisseria meningitis. MCM epidemics occur worldwide but the highest incidence is observed in the "meningitis belt" of sub-Saharan Africa, stretching from Senegal to Ethiopia. In spite of standards, strategies of prevention and control of MCS epidemic from World Health Organization (WHO) and States, African Sahelo-Soudanian countries remain frequently afflicted by disastrous epidemics. In fact, each year, during the dry season (February-April), 25 to 250 thousands of cases are observed. Children under 15 are particularly affected. Among favourable conditions for the resurgence and dispersion of the disease, climatic conditions may be important inducing seasonal fluctuations in disease incidence and contributing to explain the spatial pattern of the disease roughly circumscribed to the ecological Sahelo-Sudanian band. In this study, we tried to analyse the relationships between climatic factors, ecosystems degradation and MCM for a better understanding of MCM epidemic dynamic and their prediction. We have shown that MCM epidemics, whether at the regional, national or local level, occur in a specific period of the year, mainly from January to May characterised by a dry, hot and sandy weather. We have identified both in situ (meteorological synoptic stations) and satellitales climatic variables (NCEP reanalysis dataset) whose seasonal variability is dominating in MCM seasonal transmission. Statistical analysis have measured the links between seasonal variation of certain climatic parameters (particularly the meridional wind components) and seasonal recrudescence of MCM cases in order to elaborate seasonal occurrence of MCM epidemics prediction models on different spatiotemporal scales. These predictions have been experienced and evaluated by Burkina Meteorological Authority and Health Protection General Direction since 2009. The encouraging results from the monitoring and evaluation of these predictions given by such simple models enable the development of a monitoring and an early warning integrated system of MCM epidemics in Burkina Faso. This experience could be implemented in others African Sahelo-Soudanian countries.

Impacts of Climate Change on Public Health in India: Future Research Directions

PubMed Central

Bush, Kathleen F.; Luber, George; Kotha, S. Rani; Dhaliwal, R.S.; Kapil, Vikas; Pascual, Mercedes; Brown, Daniel G.; Frumkin, Howard; Dhiman, R.C.; Hess, Jeremy; Wilson, Mark L.; Balakrishnan, Kalpana; Eisenberg, Joseph; Kaur, Tanvir; Rood, Richard; Batterman, Stuart; Joseph, Aley; Gronlund, Carina J.; Agrawal, Arun; Hu, Howard

2011-01-01

Background Climate change and associated increases in climate variability will likely further exacerbate global health disparities. More research is needed, particularly in developing countries, to accurately predict the anticipated impacts and inform effective interventions. Objectives Building on the information presented at the 2009 Joint Indo–U.S. Workshop on Climate Change and Health in Goa, India, we reviewed relevant literature and data, addressed gaps in knowledge, and identified priorities and strategies for future research in India. Discussion The scope of the problem in India is enormous, based on the potential for climate change and variability to exacerbate endemic malaria, dengue, yellow fever, cholera, and chikungunya, as well as chronic diseases, particularly among the millions of people who already experience poor sanitation, pollution, malnutrition, and a shortage of drinking water. Ongoing efforts to study these risks were discussed but remain scant. A universal theme of the recommendations developed was the importance of improving the surveillance, monitoring, and integration of meteorological, environmental, geospatial, and health data while working in parallel to implement adaptation strategies. Conclusions It will be critical for India to invest in improvements in information infrastructure that are innovative and that promote interdisciplinary collaborations while embarking on adaptation strategies. This will require unprecedented levels of collaboration across diverse institutions in India and abroad. The data can be used in research on the likely impacts of climate change on health that reflect India’s diverse climates and populations. Local human and technical capacities for risk communication and promoting adaptive behavior must also be enhanced. PMID:21273162

Experimental Climate Change Modifies Degradative Succession in Boreal Peatland Fungal Communities.

PubMed

Asemaninejad, Asma; Thorn, R Greg; Lindo, Zoë

2017-04-01

Peatlands play an important role in global climate change through sequestration of atmospheric CO 2 . Climate-driven changes in the structure of fungal communities in boreal peatlands that favor saprotrophic fungi can substantially impact carbon dynamics and nutrient cycling in these crucial ecosystems. In a mesocosm study using a full factorial design, 100 intact peat monoliths, complete with living Sphagnum and above-ground vascular vegetation, were subjected to three climate change variables (increased temperature, reduced water table, and elevated CO 2 concentrations). Peat litterbags were placed in mesocosms, and fungal communities in litterbags were monitored over 12 months to assess the impacts of climate change variables on peat-inhabiting fungi. Changes in fungal richness, diversity, and community composition were assessed using Illumina MiSeq sequencing of ribosomal DNA (rDNA). While general fungal richness reduced under warming conditions, Ascomycota exhibited higher diversity under increased temperature treatments over the course of the experiment. Both increased temperature and lowered water table position drove shifts in fungal community composition with a strong positive effect on endophytic and mycorrhizal fungi (including one operational taxonomic unit (OTU) tentatively identified as Barrenia panicia) and different groups of saprotrophs identified as Mortierella, Galerina, and Mycena. These shifts were observed during a predicted degradative succession in the decomposer community as different carbon substrates became available. Since fungi play a central role in peatland communities, increased abundances of saprotrophic fungi under warming conditions, at the expense of reduced fungal richness overall, may increase decomposition rates under future climate scenarios and could potentially aggravate the impacts of climate change.

Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia.

PubMed

Khormi, Hassan M; Kumar, Lalit

2016-11-21

We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model. The match between prediction and reality was found to be high. More than 90% of the observed malaria distribution points were associated with the currently known suitable climate conditions. Climate suitability for malaria is projected to decrease in India, southern Myanmar, southern Thailand, eastern Borneo, and the region bordering Cambodia, Malaysia and the Indonesian islands, while it is expected to increase in southern and south-eastern China and Taiwan. The climatic models for Anopheles mosquitoes presented here should be useful for malaria control, monitoring, and management, particularly considering these future climate scenarios.

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

PubMed Central

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

2013-01-01

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

Climate Research and Seasonal Forecasting for West Africans: Perceptions, Dissemination, and Use?.

NASA Astrophysics Data System (ADS)

Tarhule, Aondover; Lamb, Peter J.

2003-12-01

Beginning in response to the disastrous drought of 1968 73, considerable research and monitoring have focused on the characteristics, causes, predictability, and impacts of West African Soudano Sahel (10° 18°N) rainfall variability and drought. While these efforts have generated substantial information on a range of these topics, very little is known of the extent to which communities, activities at risk, and policy makers are aware of, have access to, or use such information. This situation has prevailed despite Glantz&;s provocative BAMS paper on the use and value of seasonal forecasts for the Sahel more than a quarter century ago. We now provide a systematic reevaluation of these issues based on questionnaire responses of 566 participants (in 13 communities) and 26 organizations in Burkina Faso, Mali, Niger, and Nigeria. The results reveal that rural inhabitants have limited access to climate information, with nongovernmental organizations (NGOs) being the most important source. Moreover, the pathways for information flow are generally weakly connected and informal. As a result, utilization of the results of climate research is very low to nonexistent, even by organizations responsible for managing the effects of climate variability. Similarly, few people have access to seasonal climate forecasts, although the vast majority expressed a willingness to use such information when it becomes available. Those respondents with access expressed great enthusiasm and satisfaction with seasonal forecasts. The results suggest that inhabitants of the Soudano Sahel savanna are keen for changes that improve their ability to cope with climate variability, but the lack of information on alternative courses of action is a major constraint. Our study, thus, essentially leaves unchanged both Glantz&;s negative “tentative conclusion” and more positive “preliminary assessment” of 25 years ago. Specifically, while many of the infrastructural deficiencies and socioeconomic impediments remain, the great yearning for climate information by Soudano Sahalians suggests that the time is finally ripe for fostering increased use. Therefore, a simple model for improved dissemination of climate research and seasonal climate forecast information is proposed. The tragedy is that a quarter century has passed since Glantz&;s clarion call.

Water isotope systematics: Improving our palaeoclimate interpretations

USGS Publications Warehouse

Jones, M. D.; Dee, S.; Anderson, L.; Baker, A.; Bowen, G.; Noone, D.

2016-01-01

The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability.As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work.This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison.Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.

Long and Short Term Variability of the Main Physical Parameters in the Coastal Area of the SE Baltic Proper

NASA Astrophysics Data System (ADS)

Mingelaite, Toma; Rukseniene, Viktorija; Dailidiene, Inga

2015-04-01

Keywords: SE Baltic Sea, coastal upwelling, IR Remote Sensing The memory of the ocean and seas of atmospheric forcing events contributes to the long-term climate change. Intensifying climate change processes in the North Atlantic region including Baltic Sea has drawn widespread interest, as a changing water temperature has ecological, economic and social impact in coastal areas of the Europe seas. In this work we analyse long and short term variability of the main physical parameters in the coastal area of the South Eastern Baltic Sea Proper. The analysis of long term variability is based on monitoring data measured in the South Eastern Baltic Sea for the last 50 years. The main focus of the long term variability is changes of hydro meteorological parameters relevant to the observed changes in the climate.The water salinity variations in the Baltic Sea near the Lithuanian coast and in the Curonian Lagoon, a shallow and enclosed sub-basin of the Baltic Sea, were analysed along with the time series of some related hydroclimatic factors. The short term water temperature and salinity variations were analysed with a strong focus on coastal upwelling events. Combining both remote sensing and in situ monitoring data physical parameters such as vertical salinity variations during upwelling events was analysed. The coastal upwelling in the SE Baltic Sea coast, depending on its scale and intensity, may lead to an intrusion of colder and saltier marine waters to the Curonian Lagoon resulting in hydrodynamic changes and pronounced temperature drop extending for 30-40 km further down the Lagoon. The study results show that increasing trends of water level, air and water temperature, and decreasing ice cover duration are related to the changes in meso-scale atmospheric circulation, and more specifically, to the changes in regional and local wind regime climate. That is in a good agreement with the increasing trends in local higher intensity of westerly winds, and with the winter NAO index that indicates the change and variations of the atmospheric circulation in the North Atlantic region, including the Baltic Sea area. This work is supported by "Lithuanian Maritime Sectors' Technologies and Environmental Research Development" project Nr. VP1-3.1-ŠMM-08-K-01-019 funded by the European Social Fund Agency.

Coupling between air travel and climate

NASA Astrophysics Data System (ADS)

Karnauskas, Kristopher B.; Donnelly, Jeffrey P.; Barkley, Hannah C.; Martin, Jonathan E.

2015-12-01

The airline industry closely monitors the midlatitude jet stream for short-term planning of flight paths and arrival times. In addition to passenger safety and on-time metrics, this is due to the acute sensitivity of airline profits to fuel cost. US carriers spent US$47 billion on jet fuel in 2011, compared with a total industry operating revenue of US$192 billion. Beyond the timescale of synoptic weather, the El Niño/Southern Oscillation (ENSO), Arctic Oscillation (AO) and other modes of variability modulate the strength and position of the Aleutian low and Pacific high on interannual timescales, which influence the tendency of the exit region of the midlatitude Pacific jet stream to extend, retract and meander poleward and equatorward. The impact of global aviation on climate change has been studied for decades owing to the radiative forcing of emitted greenhouse gases, contrails and other effects. The impact of climate variability on air travel, however, has only recently come into focus, primarily in terms of turbulence. Shifting attention to flight durations, here we show that 88% of the interannual variance in domestic flight times between Hawaii and the continental US is explained by a linear combination of ENSO and the AO. Further, we extend our analysis to CMIP5 model projections to explore potential feedbacks between anthropogenic climate change and air travel.

PERSIANN-CDR Daily Precipitation Dataset for Hydrologic Applications and Climate Studies.

NASA Astrophysics Data System (ADS)

Sorooshian, S.; Hsu, K. L.; Ashouri, H.; Braithwaite, D.; Nguyen, P.; Thorstensen, A. R.

2015-12-01

Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network - Climate Data Record (PERSIANN-CDR) is a newly developed and released dataset which covers more than 3 decades (01/01/1983 - 03/31/2015 to date) of daily precipitation estimations at 0.25° resolution for 60°S-60°N latitude band. PERSIANN-CDR is processed using the archive of the Gridded Satellite IRWIN CDR (GridSat-B1) from the International Satellite Cloud Climatology Project (ISCCP), and the Global Precipitation Climatology Project (GPCP) 2.5° monthly product for bias correction. The dataset has been released and made available for public access through NOAA's National Centers for Environmental Information (NCEI) (http://www1.ncdc.noaa.gov/pub/data/sds/cdr/CDRs/PERSIANN/Overview.pdf). PERSIANN-CDR has already shown its usefulness for a wide range of applications, including climate variability and change monitoring, hydrologic applications, and water resources system planning and management. This precipitation CDR data has also been used in studying the behavior of historical extreme precipitation events. Demonstration of PERSIANN-CDR data in detecting trends and variability of precipitation over the past 30 years, the potential usefulness of the dataset for evaluating climate model performance relevant to precipitation in retrospective mode, will be presented.

A Bat's-Eye View of Holocene Climate Change in the Southwest: Resolving Ambiguities in Cave Isotopic Records

NASA Astrophysics Data System (ADS)

Cole, J. E.; Truebe, S. A.; Harrington, M. D.; Woodhead, J. D.; Overpeck, J. T.; Hlohowskyj, S.; Henderson, G. M.

2015-12-01

In dry environments, speleothems provide an outstanding archive of information on past climate change, particularly since lakes are typically absent or intermittent. Speleothem stable isotopes are widely used for climate reconstruction, but the isotope-climate relationship is complex in arid-region precipitation, and within-cave processes further complicate climate interpretations. Our isotope results from 3 southeastern Arizona caves, spanning the past 3.5-12 kyr, collectively indicate a weakening monsoon from 7kyr to present. These records exhibit substantial multidecadal-multicentury variability that is sometimes shared, and sometimes independent among caves. Strategies to overcome ambiguities in isotope records include long-term monitoring of cave dripwaters, multi-site comparisons, and multiproxy measurements. Monthly dripwater measurements from two caves spanning several years highlight substantial seasonal biases that create distinct differences in the climate sensitivity of individual cave records. These biases can lead to lack of correlation between records, but also creates opportunities for seasonally specific moisture reconstructions. New preliminary analyses suggest that elemental data can help to unravel the multivariate signal contained in speleothem oxygen isotope records.

Detecting the global and regional effects of sulphate aerosol geoengineering

NASA Astrophysics Data System (ADS)

Lo, Eunice; Charlton-Perez, Andrew; Highwood, Ellie

2017-04-01

Climate warming is unequivocal. In addition to carbon dioxide emission mitigation, some geoengineering ideas have been proposed to reduce future surface temperature rise. One of these proposals involves injecting sulphate aerosols into the stratosphere to increase the planet's albedo. Monitoring the effectiveness of sulphate aerosol injection (SAI) would require us to be able to distinguish and detect its cooling effect from the climate system's internal variability and other externally forced temperature changes. This research uses optimal fingerprinting techniques together with simulations from the GeoMIP data base to estimate the number of years of observations that would be needed to detect SAI's cooling signal in near-surface air temperature, should 5 Tg of sulphur dioxide be injected into the stratosphere per year on top of RCP4.5 from 2020-2070. The first part of the research compares the application of two detection methods that have different null hypotheses to SAI detection in global mean near-surface temperature. The first method assumes climate noise to be dominated by unforced climate variability and attempts to detect the SAI cooling signal and greenhouse gas driven warming signal in the "observations" simultaneously against this noise. The second method considers greenhouse gas driven warming to be a non-stationary background climate and attempts to detect the net cooling effect of SAI against this background. Results from this part of the research show that the conventional multi-variate detection method that has been extensively used to attribute climate warming to anthropogenic sources could also be applied for geoengineering detection. The second part of the research investigates detection of geoengineering effects on the regional scale. The globe is divided into various sub-continental scale regions and the cooling effect of SAI is looked for in the temperature time series in each of these regions using total least squares multi-variate detection. Results show that surface temperature observations would be most useful for SAI detection in the Northern Hemisphere mid-latitudes, especially in East Asia. This can be used to indicate the optimal observational network for monitoring the effectiveness of SAI in the future, should that be needed.

El Niño-Southern Oscillation and dengue early warning in Ecuador

NASA Astrophysics Data System (ADS)

Stewart, A. M.; Lowe, R.

2012-04-01

Dengue fever, a mosquito-borne viral disease, is one of the most important emerging tropical diseases. Dengue is hyper-endemic in coastal Ecuador, where all four serotypes co-circulate. The El Niño-Southern Oscillation (ENSO) influences climate in Ecuador, with positive phase ENSO (El Niño) associated with wetter and warmer conditions over the southern coastal region. In turn, greater rainfall increases the availability of mosquito breeding sites for the dengue mosquito (Aedes aegypti), while warmer temperatures increase rates of larval development, mosquito biting, and viral replication in the mosquito. We report a statistical model for assessing the importance of climate as a driver for inter-annual variability in dengue fever in southern coastal Ecuador. Climate variables from a local meteorology station (precipitation, number of rainy days, minimum/maximum/mean air temperature), combined with gridded climate products, and anomalies of Pacific sea surface temperatures (Oceanic Niño Index, ONI) were used to predict monthly dengue standardized morbidity ratios (SMR) (1995-2010). Non-climatic confounding factors such as serotype introduction and vector control effort were also considered. Preliminary results indicated a statistically significant positive association between dengue risk and the number of rainy days during the previous month. Both the number of rainy days and dengue SMR were positively associated with the Pacific SST anomalies with a lead time of several months. Due to time lags involved in the climate-disease transmission system, monitoring El Niño / La Niña evolution in the Pacific Ocean could provide some predictive lead time for forecasting dengue epidemics. This is the first study of dengue fever and climate in this region. This research provides the foundation to develop a climate-driven early warning system for dengue fever in Ecuador.

Seasonally-resolved trace element concentrations in stalagmites from a shallow cave in New Mexico

NASA Astrophysics Data System (ADS)

Sekhon, N.; Banner, J.; Miller, N. R.; Carlson, P. E.; Breecker, D.

2017-12-01

High-resolution (sub-annual/seasonal) paleoclimate records extending beyond the instrumental period are required to test climate models and better understand how climate warming/cooling and wetting/drying are manifested seasonally. This is particularly the case for areas such as the southwest United States where precipitation and temperature seasonality dictate the regional climate. Study of a 20thcentury stalagmite (Carlson et al., in prep) documented (1) seasonal variation in trace element compositions of a stalagmite from a shallow, well-ventilated cave and (2) demonstrated the seasonal variation in stalagmite Mg to be in agreement with predicted temperature-dependent fractionation between water and calcite. The seasonal nature of variability was constrained by monitoring the cave on a monthly basis (Casteel and Banner, 2015; Carlson et al., in prep). Here we expand on using stalagmites from shallow, well-ventilated caves as archives of seasonally-resolved climate recorders by studying trace element variations in two coeval modern stalagmites (SBFC-1 and SBFC-2) cored from Sitting Bull Falls, southern New Mexico. Seasonal cycles will be confirmed by analyzing Mg, Ba, and Sr in in-situ calcite precipitated on artificial substrates as available (July, Sept., and Nov. 2017). The chronology is constrained by semi-automated peak counting and 14C bomb-peak. In addition, principal component analyses of trace element data identify two primary underlying modes of trace element variability for soil-derived elements (Cu, Zn, and Fe) and bedrock-derived elements (Mg, Sr, and Ba). We hypothesize that the soil-derived elements are transported by seasonal infiltration of organic colloids and the bedrock-derived elements are ­­controlled by variability in cave air temperature, drip water, and calcite growth rate. The two modes of variability will be calibrated against instrumental data over the 20th century. When complete, these new seasonally resolved proxy records will constrain the pattern and mechanism of the regional climate in southwest United States with a focus on drought indicators.

Modeling water scarcity over south Asia: Incorporating crop growth and irrigation models into the Variable Infiltration Capacity (VIC) model

NASA Astrophysics Data System (ADS)

Troy, Tara J.; Ines, Amor V. M.; Lall, Upmanu; Robertson, Andrew W.

2013-04-01

Large-scale hydrologic models, such as the Variable Infiltration Capacity (VIC) model, are used for a variety of studies, from drought monitoring to projecting the potential impact of climate change on the hydrologic cycle decades in advance. The majority of these models simulates the natural hydrological cycle and neglects the effects of human activities such as irrigation, which can result in streamflow withdrawals and increased evapotranspiration. In some parts of the world, these activities do not significantly affect the hydrologic cycle, but this is not the case in south Asia where irrigated agriculture has a large water footprint. To address this gap, we incorporate a crop growth model and irrigation model into the VIC model in order to simulate the impacts of irrigated and rainfed agriculture on the hydrologic cycle over south Asia (Indus, Ganges, and Brahmaputra basin and peninsular India). The crop growth model responds to climate signals, including temperature and water stress, to simulate the growth of maize, wheat, rice, and millet. For the primarily rainfed maize crop, the crop growth model shows good correlation with observed All-India yields (0.7) with lower correlations for the irrigated wheat and rice crops (0.4). The difference in correlation is because irrigation provides a buffer against climate conditions, so that rainfed crop growth is more tied to climate than irrigated crop growth. The irrigation water demands induce hydrologic water stress in significant parts of the region, particularly in the Indus, with the streamflow unable to meet the irrigation demands. Although rainfall can vary significantly in south Asia, we find that water scarcity is largely chronic due to the irrigation demands rather than being intermittent due to climate variability.

Students Around the World Engaged in Climate Science (Invited)

NASA Astrophysics Data System (ADS)

Sparrow, E. B.; Kopplin, M.; Boger, R.; Jaroensutasinee, K.; Jaroensutasinee, M.; Yoshikawa, K.; Morris, K.; Gordon, L. S.; Yule, S.

2013-12-01

One of the GLOBE (Global Learning and Observations to Benefit the Environment) earth system science projects, Monitoring Seasons Through Global Learning Communities also called Seasons and Biomes, has engaged primary and secondary teachers and their students in weather and climate studies in collaboration with scientists and community experts. In this worldwide inquiry- and project-based initiative, students have been monitoring indicators of interannual variability in seasons, such as green-up and green-down of plants, air and soil temperature, soil moisture, precipitation, cloud types, percent cloud cover, as well as learning the difference between weather and climate. They have used standardized scientific measurements developed in GLOBE for investigations on atmosphere, soils, hydrology, land cover and phenology as well as those developed in Seasons and Biomes, such as ice seasonality protocols, frost tube and mosquito protocols. Studies have ranged from individuals to small groups of students, classes to schools, local to regional to global reach and involvement. Global learning communities have formed through professional development workshops conducted by Seasons and Biomes in the U.S. and other countries (more than 1600 educators in 51 countries) as well as through collaborative projects like the cross-continent videoconferences, GS-Pals project facilitated by GLOBE Alumni, the Mt Kilimanjaro expeditions, Mosquito studies in Thailand, and Permafrost and Active Layer Monitoring (over 22,000 students). Seasons and Biomes and GLOBE have provided the tools and infrastructure for observing, measuring, recording, archiving, and analysis of data, including venues for communicating results. Students have presented their projects locally, nationally and internationally and have contributed to climate studies and cross-cultural enrichment.

Environmental Predictors of Seabird Wrecks in a Tropical Coastal Area

PubMed Central

Fulgencio de Moura, Jailson; Siciliano, Salvatore

2016-01-01

Beached bird surveys have been widely used to monitor the impact of oil pollution in the oceans. However, separating the combined effects of oil pollution, environmental variables and methodological aspects of beach monitoring on seabird stranding patterns is a challenging task. The effects of a comprehensive set of oceanographic and climatic variables and oil pollution on seabird strandings in a tropical area of Brazil were investigated herein, using two robust and innovative methods: Generalized Linear Mixed Models and Structural Equation Modeling. We assessed strandings of four resident seabird species along 480 km of beaches divided into 11 sampling areas, between November 2010 and September 2013. We found that increasing the distance from the nearest breeding island reduce the seabird stranding events. Storm activity and biological productivity were the most important factors affecting the stranding events of brown boobies Sula leucogaster, Cabot’s terns Thalasseus acuflavidus and kelp gulls Larus dominicanus. These species are also indirectly affected by warm tropical waters, which reduce chlorophyll-a concentrations. Beach surveys are, thus, useful to investigate the mortality rates of resident species near breeding sites, where individuals are more abundant and exposed to local factors associated with at-sea mortality. In contrast, conservation actions and monitoring programs for far-ranging seabird species are needed in more distant foraging areas. Furthermore, beach monitoring programs investigating the impact of oil pollution on seabirds need to account for the effects of environmental factors on stranding patterns. The present study also demonstrated that seabirds inhabiting tropical coastal waters are sensitive to climate conditions such as adverse weather, which are expected to increase in frequency and intensity in next decades. PMID:27992578

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.

Examples of Sentinel-2A Mission Exploitation Results

NASA Astrophysics Data System (ADS)

Koetz, Benjamin; Hoersch, Bianca; Gascon, Ferran; Desnos, Yves-Louis; Seifert, Frank Martin; Paganini, Marc; Ramoino, Fabrizio; Arino, Olivier

2017-04-01

The Sentinel-2 Copernicus mission will bring significant breakthrough in the exploitation of space borne optical data. Sentinel-2 time series will transform land cover, agriculture, forestry, in-land water and costal EO applications from mapping to monitoring, from snapshot to time series data analysis, from image-based to pixel-based processing. The 5-days temporal revisiting of the Sentinel-2 satellites, when both units will be operated together, will usher us in a new era for time series analysis at high spatial resolutions (HR) of 10-20 meters. The monitoring of seasonal variations and processes in phenology and hydrology are examples of the many R&D areas to be studied. The mission's large swath and systematic acquisitions will further support unprecedented coverage at the national scale addressing information requirements of national to regional policies. Within ESA programs, such as the Data User Element (DUE), Scientific Exploitation of Operational Missions (SEOM) and Climate Change Initiative (CCI), several R&D activities are preparing the exploitation of the Sentinel-2 mission towards reliable measurements and monitoring of e.g. Essential Climate Variables and indicators for the Sustainable Development Goals. Early Sentinel-2 results will be presented related to a range of applications and scientific domains such as agricultural monitoring at national scale (DUE Sen2Agri), wetland extent and condition over African Ramsar sites (DUE GlobWetland-Africa), land cover mapping for climate change (CCI Land Cover), national land monitoring (Cadaster-Env), forest degradation (DUE ForMoSa), urban mapping (DUE EO4Urban), in-land water quality (DUE SPONGE), map of Mediterranean aquaculture (DUE SMART) and coral reef habitat mapping (SEOM S2-4Sci Coral). The above-mentioned activities are only a few examples from the very active international land imaging community building on the long-term Landsat and Spot heritage and knowledge.

Climate Change Education for General Education Faculty

NASA Astrophysics Data System (ADS)

Ozbay, G.; Fox-Lykens, R.; Fuoco, M. J.; Phalen, L.; Harcourt, P.; Veron, D. E.; Rogers, M.; Merrill, J.

2016-12-01

As MADE-CLEAR scientists, our ultimate goal is to inform the public about climate change through education. Education will provide citizens with important tools for adapting and coping against climate change through the understanding of the cause and effects of climate change, and the role they play in counteracting these effects. MADE-CLEAR is connecting educators with resources such as lesson plans and hands-on activities so they can easily incorporate climate change into their curriculum. This past year Delaware State University held workshops for Chemistry and Math faculty to provide information and resources to help integrate climate change education into their classes. We presented them with information on climate change and demonstrated several laboratory activities that would be applicable to their classes. Such activities included a sea level rise graphing exercise, ocean acidification pH demonstration, ocean acidification's effect on organism's demonstration, carbon dioxide variability and heat trapping gas simulation. The goals of the workshops are to implement a multidisciplinary approach in climate change education. Workshops are prepared hands-on heavy followed by the lectures and video resources. Pre- and post-workshop assessment questions on the workshop contents are provided to monitor faculty understanding of the climate change content. In doing so, we aim to improve climate literacy in our higher education students.

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

USGS Publications Warehouse

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

2013-01-01

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

Water vapour fluxes trends on different time scales and their relationship with weather and soil drivers: a case study from a dehesa site in South Spain

NASA Astrophysics Data System (ADS)

Polo, María José; Egüen, Marta; Andreu, Ana; Carpintero, Elisabet; Gómez-Giráldez, Pedro; Patrocinio González-Dugo, María

2017-04-01

Water vapour fluxes between the soil surface and the atmosphere constitute one of the most important components of the water cycle in the continental areas. Their regime directly affect the availability of water to plants, water storage in surface bodies, air humidity in the boundary layer, snow persistence… among others, and the list of indirectly affected processes comprises a large number of components. Water potential or wetness gradients are some of the main drivers of water vapour fluxes to the atmosphere; soil humidity is usually monitored as key variable in many hydrological and environmental studies, and its estimated series are used to calibrate and validate the modelling of certain hydrological processes. However, such results may differ when water fluxes are used instead of water state variables, such as humidity. This work shows the analysis of high resolution water vapour fluxes series from a dehesa area in South Spain where a complete energy and water fluxes/variables monitoring site has been operating for the last four years. The results include pasture and tree vegetated control points. The daily water budget calculation on both types of sites has been performed from weather and energy fluxes measurements, and soil moisture measurements, and the results have been aggregated on a weekly, monthly and seasonal basis. Comparison between observed trends of soil moisture and calculated trends of water vapour fluxes is included to show the differences arising in terms of the regime of the dominant weather variables in this type of ecosystems. The results identify significant thresholds for each weather variable driver and highlight the importance of the wind regime, which is the somehow forgotten variable in future climate impacts on hydrology. Further work is being carried out to assess water cycle potential trends under future climate conditions and their impacts on the vegetation in dehesa ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Assimilation of AATSR, MERIS and MODIS Data in the Snowmelt Runoff Model (SRM) on the Upper Rio Grande (USA)

NASA Astrophysics Data System (ADS)

Bleiweiss, M. P.; Rampini, A.; Pepe, M.; Rango, A.; Steele, C.; Stein, W. L.; Schmugge, T.

2008-12-01

Current efforts for simulating or forecasting snowmelt are time-consuming and laborious; the AWARE project (A tool for monitoring and forecasting Available WAter REsource in mountain environments) has been motivated by the urgent need to facilitate the prediction of medium-term flows from snowmelt for an effective and sustainable water resources management. Its main goal is to provide innovative tools for monitoring and predicting water availability and distribution in drainage basins where snowmelt is a major component of the annual water balance. The particular objective of the effort reported here is to compare results obtained from the MODIS sensor on NASA Terra and Aqua satellite and next generation sensors AATSR and MERIS on board ESA Envisat satellite. The vehicle for this comparison is the AWARE Geoportal (http://www.aware- eu.info/eng/home.htm) which is a WWW implementation of the Snowmelt Runoff Model (SRM). The river basin chosen for analysis is the Upper Rio Grande of North America. The time period for analysis encompasses the Water Years 2005, 2006, and 2007 (October 2004 - September 2007). The reason for this is to ensure that data from all three sensors are available for use and to investigate variable climate conditions. A successful comparison between the various sensors will help demonstrate that the AWARE approach will facilitate future processing of several years' worth of snow cover data from a variety of sensors that covers large extremes in climate variability. This will allow greater success in developing forecasts and understanding of longer term climate change impacts.

The Copernicus programme and its Climate Change Service (C3S): a European answer to Climate Change

NASA Astrophysics Data System (ADS)

Pinty, Bernard; Thepaut, Jean-Noel; Dee, Dick

2016-07-01

In November 2014, The European Centre for Medium-range Weather Forecasts (ECMWF) signed an agreement with the European Commission to deliver two of the Copernicus Earth Observation Programme Services on the Commission's behalf. The ECMWF delivered services - the Copernicus Climate Change Service (C3S) and Atmosphere Monitoring Service (CAMS) - will bring a consistent standard to how we measure and predict atmospheric conditions and climate change. They will maximise the potential of past, current and future earth observations - ground, ocean, airborne, satellite - and analyse these to monitor and predict atmospheric conditions and in the future, climate change. With the wealth of free and open data that the services provide, they will help business users to assess the impact of their business decisions and make informed choices, delivering a more energy efficient and climate aware economy. These sound investment decisions now will not only stimulate growth in the short term, but reduce the impact of climate change on the economy and society in the future. C3S is in its proof of concept phase and through its climate data store will provide global and regional climate data reanalyses; multi-model seasonal forecasts; customisable visual data to enable examination of wide range of scenarios and model the impact of changes; access to all the underlying data, including climate data records from various satellite and in-situ observations. In addition, C3S will provide key indicators on climate change drivers (such as carbon dioxide) and impacts (such as reducing glaciers). The aim of these indicators will be to support European adaptation and mitigation policies in a number of economic sectors. The presentation will provide an overview of this newly created Service, its various components and activities, and a roadmap towards achieving a fully operational European Climate Service at the horizon 2019-2020. It will focus on the requirements for quality-assured Observation Gridded Products to establish an operational delivery of a series of gridded long-term Climate Data Records (CDRs) of Essential Climate Variables (ECVs), along with associated input data and uncertainty estimation.

Improved Uncertainty Quantification in Groundwater Flux Estimation Using GRACE

NASA Astrophysics Data System (ADS)

Reager, J. T., II; Rao, P.; Famiglietti, J. S.; Turmon, M.

2015-12-01

Groundwater change is difficult to monitor over large scales. One of the most successful approaches is in the remote sensing of time-variable gravity using NASA Gravity Recovery and Climate Experiment (GRACE) mission data, and successful case studies have created the opportunity to move towards a global groundwater monitoring framework for the world's largest aquifers. To achieve these estimates, several approximations are applied, including those in GRACE processing corrections, the formulation of the formal GRACE errors, destriping and signal recovery, and the numerical model estimation of snow water, surface water and soil moisture storage states used to isolate a groundwater component. A major weakness in these approaches is inconsistency: different studies have used different sources of primary and ancillary data, and may achieve different results based on alternative choices in these approximations. In this study, we present two cases of groundwater change estimation in California and the Colorado River basin, selected for their good data availability and varied climates. We achieve a robust numerical estimate of post-processing uncertainties resulting from land-surface model structural shortcomings and model resolution errors. Groundwater variations should demonstrate less variability than the overlying soil moisture state does, as groundwater has a longer memory of past events due to buffering by infiltration and drainage rate limits. We apply a model ensemble approach in a Bayesian framework constrained by the assumption of decreasing signal variability with depth in the soil column. We also discuss time variable errors vs. time constant errors, across-scale errors v. across-model errors, and error spectral content (across scales and across model). More robust uncertainty quantification for GRACE-based groundwater estimates would take all of these issues into account, allowing for more fair use in management applications and for better integration of GRACE-based measurements with observations from other sources.

The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources

NASA Astrophysics Data System (ADS)

Fisher, Joshua B.; Melton, Forrest; Middleton, Elizabeth; Hain, Christopher; Anderson, Martha; Allen, Richard; McCabe, Matthew F.; Hook, Simon; Baldocchi, Dennis; Townsend, Philip A.; Kilic, Ayse; Tu, Kevin; Miralles, Diego D.; Perret, Johan; Lagouarde, Jean-Pierre; Waliser, Duane; Purdy, Adam J.; French, Andrew; Schimel, David; Famiglietti, James S.; Stephens, Graeme; Wood, Eric F.

2017-04-01

The fate of the terrestrial biosphere is highly uncertain given recent and projected changes in climate. This is especially acute for impacts associated with changes in drought frequency and intensity on the distribution and timing of water availability. The development of effective adaptation strategies for these emerging threats to food and water security are compromised by limitations in our understanding of how natural and managed ecosystems are responding to changing hydrological and climatological regimes. This information gap is exacerbated by insufficient monitoring capabilities from local to global scales. Here, we describe how evapotranspiration (ET) represents the key variable in linking ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources, and highlight both the outstanding science and applications questions and the actions, especially from a space-based perspective, necessary to advance them.

The Future of Evapotranspiration: Global Requirements for Ecosystem Functioning, Carbon and Climate Feedbacks, Agricultural Management, and Water Resources

NASA Technical Reports Server (NTRS)

Fisher, Joshua B.; Melton, Forrest; Middleton, Elizabeth; Hain, Christopher; Anderson, Martha; Allen, Richard; McCabe, Matthew F.; Hook, Simon; Baldocchi, Dennis; Townsend, Philip A.;

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

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

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

Use of a Weather Generator for analysis of projections of future daily temperature and its validation with climate change indices

NASA Astrophysics Data System (ADS)

Di Piazza, A.; Cordano, E.; Eccel, E.

2012-04-01

The issue of climate change detection is considered a major challenge. In particular, high temporal resolution climate change scenarios are required in the evaluation of the effects of climate change on agricultural management (crop suitability, yields, risk assessment, etc.) energy production and water management. In this work, a "Weather Generator" technique was used for downscaling climate change scenarios for temperature. An R package (RMAWGEN, Cordano and Eccel, 2011 - available on http://cran.r-project.org) was developed aiming to generate synthetic daily weather conditions by using the theory of vectorial auto-regressive models (VAR). The VAR model was chosen for its ability in maintaining the temporal and spatial correlations among variables. In particular, observed time series of daily maximum and minimum temperature are transformed into "new" normally-distributed variable time series which are used to calibrate the parameters of a VAR model by using ordinary least square methods. Therefore the implemented algorithm, applied to monthly mean climatic values downscaled by Global Climate Model predictions, can generate several stochastic daily scenarios where the statistical consistency among series is saved. Further details are present in RMAWGEN documentation. An application is presented here by using a dataset with daily temperature time series recorded in 41 different sites of Trentino region for the period 1958-2010. Temperature time series were pre-processed to fill missing values (by a site-specific calibrated Inverse Distance Weighting algorithm, corrected with elevation) and to remove inhomogeneities. Several climatic indices were taken into account, useful for several impact assessment applications, and their time trends within the time series were analyzed. The indices go from the more classical ones, as annual mean temperatures, seasonal mean temperatures and their anomalies (from the reference period 1961-1990) to the climate change indices selected from the list recommended by the World Meteorological Organization Commission for Climatology (WMO-CCL) and the Research Programme on Climate Variability and Predictability (CLIVAR) project's Expert Team on Climate Change Detection, Monitoring and Indices (ETCCDMI). Each index was applied to both observed (and processed) data and to synthetic time series produced by the Weather Generator, over the thirty year reference period 1981-2010, in order to validate the procedure. Climate projections were statistically downscaled for a selection of sites for the two 30-year periods 2021-2050 and 2071-2099 of the European project "Ensembles" multi-model output (scenario A1B). The use of several climatic indices strengthens the trend analysis of both the generated synthetic series and future climate projections.

The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H. J.

2017-12-01

The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield simulations driven by "perturbation" of synthetic time-series using "change factors from the CORDEX-SA MME; 2) stakeholder dialogues critically evaluating potential strategies at the grassroots (implementation) level to mitigate impacts of climate variability and change on crop yields.

Fish habitat regression under water scarcity scenarios in the Douro River basin

NASA Astrophysics Data System (ADS)

Segurado, Pedro; Jauch, Eduardo; Neves, Ramiro; Ferreira, Teresa

2015-04-01

Climate change will predictably alter hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goals of this study are to identify the stream reaches that will undergo more pronounced flow reduction under different climate change scenarios and to assess which fish species will be more affected by the consequent regression of suitable habitats. The interplay between changes in flow and temperature and the presence of transversal artificial obstacles (dams and weirs) is analysed. The results will contribute to river management and impact mitigation actions under climate change. This study was carried out in the Tâmega catchment of the Douro basin. A set of 29 Hydrological, climatic, and hydrogeomorphological variables were modelled using a water modelling system (MOHID), based on meteorological data recorded monthly between 2008 and 2014. The same variables were modelled considering future climate change scenarios. The resulting variables were used in empirical habitat models of a set of key species (brown trout Salmo trutta fario, barbell Barbus bocagei, and nase Pseudochondrostoma duriense) using boosted regression trees. The stream segments between tributaries were used as spatial sampling units. Models were developed for the whole Douro basin using 401 fish sampling sites, although the modelled probabilities of species occurrence for each stream segment were predicted only for the Tâmega catchment. These probabilities of occurrence were used to classify stream segments into suitable and unsuitable habitat for each fish species, considering the future climate change scenario. The stream reaches that were predicted to undergo longer flow interruptions were identified and crossed with the resulting predictive maps of habitat suitability to compute the total area of habitat loss per species. Among the target species, the brown trout was predicted to be the most sensitive to habitat regression due to the interplay of flow reduction, increase of temperature and transversal barriers. This species is therefore a good indicator of climate change impacts in rivers and therefore we recommend using this species as a target of monitoring programs to be implemented in the context of climate change adaptation strategies.

Solar Spectral Irradiance Variability in Cycle 24: Model Predictions and OMI Observations

NASA Technical Reports Server (NTRS)

Marchenko, S.; DeLand, M.; Lean, J.

2016-01-01

Utilizing the excellent stability of the Ozone Monitoring Instrument (OMI), we characterize both short-term (solar rotation) and long-term (solar cycle) changes of the solar spectral irradiance (SSI) between 265-500 nanometers during the ongoing Cycle 24. We supplement the OMI data with concurrent observations from the GOME-2 (Global Ozone Monitoring Experiment - 2) and SORCE (Solar Radiation and Climate Experiment) instruments and find fair-to-excellent agreement between the observations and predictions of the NRLSSI2 (Naval Research Laboratory Solar Spectral Irradiance - post SORCE) and SATIRE-S (the Naval Research Laboratory's Spectral And Total Irradiance REconstruction for the Satellite era) models.

Phenological response of an Arizona dryland forest to short-term climatic extremes

USGS Publications Warehouse

Walker, Jessica; de Beurs, Kirsten; Wynne, Randolph

2015-01-01

Baseline information about dryland forest phenology is necessary to accurately anticipate future ecosystem shifts. The overarching goal of our study was to investigate the variability of vegetation phenology across a dryland forest landscape in response to climate alterations. We analyzed the influence of site characteristics and climatic conditions on the phenological patterns of an Arizona, USA, ponderosa pine (Pinus ponderosa) forest during a five-year period (2005 to 2009) that encompassed extreme wet and dry precipitation regimes. We assembled 80 synthetic Landsat images by applying the spatial and temporal adaptive reflectance fusion method (STARFM) to 500 m MODIS and 30 m Landsat-5 Thematic Mapper (TM) data. We tested relationships between site characteristics and the timing of peak Normalized Difference Vegetation Index (NDVI) to assess the effect of climatic stress on the green-up of individual pixels during or after the summer monsoon. Our results show that drought-induced stress led to a fragmented phenological response that was highly dependent on microsite parameters, as both the spatial autocorrelation of peak timing and the number of significant site variables increased during the drought year. Pixels at lower elevations and with higher proportions of herbaceous vegetation were more likely to exhibit dynamic responses to changes in precipitation conditions. Our study demonstrates the complexity of responses within dryland forest ecosystems and highlights the need for standardized monitoring of phenology trends in these areas. The spatial and temporal variability of phenological signals may provide a quantitative solution to the problem of how to evaluate dryland land surface trends across time.

Variability in lateral carbon export from four major tributaries in the Upper Mississippi River Basin

NASA Astrophysics Data System (ADS)

Stanimirova, R.; Arevalo, P. A.; Kaufmann, R.; Maus, V.; Lesiv, M.; Havlik, P.; Friedl, M. A.

2016-12-01

The combined pressures of climate change and shifting dietary preferences are creating an urgent need to improve understanding of how climate and land management are jointly affecting the sustainability of rangelands. In particular, our ability to effectively manage rangelands in a manner that satisfies increasing demand for meat and dairy while reducing environmental impact depends on the sensitivity of rangelands to perturbations from both climate (e.g., drought) and land use (e.g., grazing). To characterize the sensitivity of rangeland vegetation to variation in climate, we analyzed gridded time series of satellite and climate data at 0.5-degree spatial resolution from 2003 to 2016 for rangeland ecosystems in South America. We used panel regression and canonical correlation to analyze the relationship between time series of enhanced vegetation index (EVI) derived from NASA's Moderate Spatial Resolution Imaging Spectroradiometer (MODIS) and gridded precipitation and air temperature data from the University of East Anglia's Climate Research Unit. To quantify the degree to which livestock management explains geographic variation of EVI, we used global livestock distribution (FAO) and feed requirements data from the Global Biosphere Management Model (GLOBIOM). Because rangeland ecosystems are sensitive to changes in meteorological variables at different time scales, we evaluated the strength of coupling between anomalies in EVI and anomalies in temperature and standardized precipitation index (SPI) data at 1-6 month lags. Our results show statistically significant relationships between EVI and precipitation during summer, fall, and winter in both tropical and subtropical agroecological zones of South America. Further, lagged precipitation effects, which reflect memory in the system, explain significant variance in winter EVI anomalies. While precipitation emerges as the dominant driver of variability in rangeland greenness, we find evidence of a management-induced signal as well. Our modeling framework integrates satellite observation, meteorological data sets, and land use/cover change information to improve our capability to monitor and manage the long-term sustainability of rangelands.

Discerning spatial and temporal LAI and clear-sky FAPAR variability during summer at the Toolik Lake vegetation monitoring grid (North Slope, Alaska)

NASA Astrophysics Data System (ADS)

Heim, B.; Beamish, A. L.; Walker, D. A.; Epstein, H. E.; Sachs, T.; Chabrillat, S.; Buchhorn, M.; Prakash, A.

2016-12-01

Ground data for the validation of satellite-derived terrestrial Essential Climate Variables (ECVs) at high latitudes are sparse. Also for regional model evaluation (e.g. climate models, land surface models, permafrost models), we lack accurate ranges of terrestrial ground data and face the problem of a large mismatch in scale. Within the German research programs `Regional Climate Change' (REKLIM) and the Environmental Mapping and Analysis Program (EnMAP), we conducted a study on ground data representativeness for vegetation-related variables within a monitoring grid at the Toolik Lake Long-Term Ecological Research station; the Toolik Lake station lies in the Kuparuk River watershed on the North Slope of the Brooks Mountain Range in Alaska. The Toolik Lake grid covers an area of 1 km2 containing Eight five grid points spaced 100 meters apart. Moist acidic tussock tundra is the most dominant vegetation type within the grid. Eight five permanent 1 m2 plots were also established to be representative of the individual gridpoints. Researchers from the University of Alaska Fairbanks have undertaken assessments at these plots, including Leaf Area Index (LAI) and field spectrometry to derive the Normalized Difference Vegetation Index (NDVI). During summer 2016, we conducted field spectrometry and LAI measurements at selected plots during early, peak and late summer. We experimentally measured LAI on more spatially extensive Elementary Sampling Units (ESUs) to investigate the spatial representativeness of the permanent 1 m2 plots and to map ESUs for various tundra types. LAI measurements are potentially influenced by landscape-inherent microtopography, sparse vascular plant cover, and dead woody matter. From field spectrometer measurements, we derived a clear-sky mid-day Fraction of Absorbed Photosynthetically Active Radiation (FAPAR). We will present the first data analyses comparing FAPAR and LAI, and maps of biophysically-focused ESUs for evaluation of the use of remote sensing data to estimate these ecosystem properties.

Detecting Biosphere anomalies hotspots

NASA Astrophysics Data System (ADS)

Guanche-Garcia, Yanira; Mahecha, Miguel; Flach, Milan; Denzler, Joachim

2017-04-01

The current amount of satellite remote sensing measurements available allow for applying data-driven methods to investigate environmental processes. The detection of anomalies or abnormal events is crucial to monitor the Earth system and to analyze their impacts on ecosystems and society. By means of a combination of statistical methods, this study proposes an intuitive and efficient methodology to detect those areas that present hotspots of anomalies, i.e. higher levels of abnormal or extreme events or more severe phases during our historical records. Biosphere variables from a preliminary version of the Earth System Data Cube developed within the CAB-LAB project (http://earthsystemdatacube.net/) have been used in this study. This database comprises several atmosphere and biosphere variables expanding 11 years (2001-2011) with 8-day of temporal resolution and 0.25° of global spatial resolution. In this study, we have used 10 variables that measure the biosphere. The methodology applied to detect abnormal events follows the intuitive idea that anomalies are assumed to be time steps that are not well represented by a previously estimated statistical model [1].We combine the use of Autoregressive Moving Average (ARMA) models with a distance metric like Mahalanobis distance to detect abnormal events in multiple biosphere variables. In a first step we pre-treat the variables by removing the seasonality and normalizing them locally (μ=0,σ=1). Additionally we have regionalized the area of study into subregions of similar climate conditions, by using the Köppen climate classification. For each climate region and variable we have selected the best ARMA parameters by means of a Bayesian Criteria. Then we have obtained the residuals by comparing the fitted models with the original data. To detect the extreme residuals from the 10 variables, we have computed the Mahalanobis distance to the data's mean (Hotelling's T^2), which considers the covariance matrix of the joint distribution. The proposed methodology has been applied to different areas around the globe. The results show that the method is able to detect historic events and also provides a useful tool to define sensitive regions. This method and results have been developed within the framework of the project BACI (http://baci-h2020.eu/), which aims to integrate Earth Observation data to monitor the earth system and assessing the impacts of terrestrial changes. [1] V. Chandola, A., Banerjee and v., Kumar. Anomaly detection: a survey. ACM computing surveys (CSUR), vol. 41, n. 3, 2009. [2] P. Mahalanobis. On the generalised distance in statistics. Proceedings National Institute of Science, vol. 2, pp 49-55, 1936.

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

PubMed

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

2014-01-01

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

Efficiently enforcing artisanal fisheries to protect estuarine biodiversity.

PubMed

Duarte de Paula Costa, Micheli; Mills, Morena; Richardson, Anthony J; Fuller, Richard A; Muelbert, José H; Possingham, Hugh P

2018-06-26

Artisanal fisheries support millions of livelihoods worldwide, yet ineffective enforcement can allow for continued environmental degradation due to overexploitation. Here, we use spatial planning to design an enforcement strategy for a pre-existing spatial closure for artisanal fisheries considering climate variability, existing seasonal fishing closures, representative conservation targets and enforcement costs. We calculated enforcement cost in three ways, based on different assumptions about who could be responsible for monitoring the fishery. We applied this approach in the Patos Lagoon estuary (Brazil), where we found three important results. First, spatial priorities for enforcement were similar under different climate scenarios. Second, we found that the cost and percentage of area enforced varied among scenarios tested by the conservation planning analysis, with only a modest increase in budget needed to incorporate climate variability. Third, we found that spatial priorities for enforcement depend on whether enforcement is carried out by a central authority or by the community itself. Here, we demonstrated a method that can be used to efficiently design enforcement plans, resulting in the conservation of biodiversity and estuarine resources. Also, cost of enforcement can be potentially reduced when fishers are empowered to enforce management within their fishing grounds. © 2018 by the Ecological Society of America.

Response of Marine Taxa to Climate Variability in the Southeast U.S.

NASA Astrophysics Data System (ADS)

Morley, J. W.; Pinsky, M. L.; Batt, R. D.

2016-02-01

Climate change has led to large-scale redistributions of marine taxa in many coastal regions around North America. Specifically, marine populations respond to spatial shifts in their preferred temperature conditions, or thermal envelope, as they shift across a seascape. The influence of climate change on the coastal fisheries of the southeast U.S. has been largely unexplored. We analyzed 25 years of trawl survey data (1990-2014) from the Southeast Area Monitoring and Assessment Program (SEAMAP), which samples the nearshore continental shelf of the South Atlantic Bight during spring, summer, and fall. Bottom temperatures exhibited no trend over this period and the assemblage showed no net shift north or south. However, taxa distributions were sensitive to interannual temperature variation. Annual projections of taxa thermal envelopes explained variation in centroid location for many species, particularly during spring. Accordingly, long-term latitudinal shifts in taxa-specific thermal envelopes, which trended to the north or south depending on the species, were highly correlated with centroid shifts during spring. One explanation for our results is that the phenology of taxa migration is adaptable to temperature variation. In particular, the inshore-offshore movement of species during spring and fall appears quite responsive to interannual temperature variability.

Determining the relative importance of climatic drivers on spring phenology in grassland ecosystems of semi-arid areas.

PubMed

Zhu, Likai; Meng, Jijun

2015-02-01

Understanding climate controls on spring phenology in grassland ecosystems is critically important in predicting the impacts of future climate change on grassland productivity and carbon storage. The third-generation Global Inventory Monitoring and Modeling System (GIMMS3g) normalized difference vegetation index (NDVI) data were applied to derive the start of the growing season (SOS) from 1982-2010 in grassland ecosystems of Ordos, a typical semi-arid area in China. Then, the conditional Granger causality method was utilized to quantify the directed functional connectivity between key climatic drivers and the SOS. The results show that the asymmetric Gaussian (AG) function is better in reducing noise of NDVI time series than the double logistic (DL) function within our study area. The southeastern Ordos has earlier occurrence and lower variability of the SOS, whereas the northwestern Ordos has later occurrence and higher variability of the SOS. The research also reveals that spring precipitation has stronger causal connectivity with the SOS than other climatic factors over different grassland ecosystem types. There is no statistically significant trend across the study area, while the similar pattern is observed for spring precipitation. Our study highlights the link of spring phenology with different grassland types, and the use of coupling remote sensing and econometric tools. With the dramatic increase in global change research, Granger causality method augurs well for further development and application of time-series modeling of complex social-ecological systems at the intersection of remote sensing and landscape changes.

Seasonal distribution of African savanna fires

NASA Technical Reports Server (NTRS)

Cahoon, Donald R., Jr.; Stocks, Brian J.; Levine, Joel S.; Cofer, Wesley R., III; O'Neill, Katherine P.

1992-01-01

The temporal and spatial distribution of savanna fires over the entire African continent, as determined from nighttime satellite imagery, is described. It is found that, contrary to expectations, most fires are left to burn uncontrolled, so that there is no strong diurnal cycle in the fire frequency. The knowledge gained from this study regarding the distribution and variability of fires is helpful in the monitoring of climatically important trace gases emitted from burning biomass.

Integrating Climate Information and Decision Processes for Regional Climate Resilience

NASA Astrophysics Data System (ADS)

Buizer, James; Goddard, Lisa; Guido, Zackry

2015-04-01

An integrated multi-disciplinary team of researchers from the University of Arizona and the International Research Institute for Climate and Society at Columbia University have joined forces with communities and institutions in the Caribbean, South Asia and West Africa to develop relevant, usable climate information and connect it to real decisions and development challenges. The overall objective of the "Integrating Climate Information and Decision Processes for Regional Climate Resilience" program is to build community resilience to negative impacts of climate variability and change. We produce and provide science-based climate tools and information to vulnerable peoples and the public, private, and civil society organizations that serve them. We face significant institutional challenges because of the geographical and cultural distance between the locale of climate tool-makers and the locale of climate tool-users and because of the complicated, often-inefficient networks that link them. To use an accepted metaphor, there is great institutional difficulty in coordinating the supply of and the demand for useful climate products that can be put to the task of building local resilience and reducing climate vulnerability. Our program is designed to reduce the information constraint and to initiate a linkage that is more demand driven, and which provides a set of priorities for further climate tool generation. A demand-driven approach to the co-production of appropriate and relevant climate tools seeks to meet the direct needs of vulnerable peoples as these needs have been canvassed empirically and as the benefits of application have been adequately evaluated. We first investigate how climate variability and climate change affect the livelihoods of vulnerable peoples. In so doing we assess the complex institutional web within which these peoples live -- the public agencies that serve them, their forms of access to necessary information, the structural constraints under which they make their decisions, and the non-public institutions of support that are available to them. We then interpret this complex reality in terms of the demand for science-based climate products and analyze the channels through which such climate support must pass, thus linking demand assessment with the scientific capacity to create appropriate decision support tools. In summary, the approach we employ is: 1) Demand-driven, beginning with a knowledge of the impacts of climate variability and change upon targeted populations, 2) Focused on vulnerability and resilience, which requires an understanding of broader networks of institutional actors who contribute to the adaptive capacity of vulnerable peoples, 3) Needs-based in that the climate needs matrix set priorities for the assessment of relevant climate products, 4) Dynamic in that the producers of climate products are involved at the point of demand assessment and can respond directly to stated needs, 5) Reflective in that the impacts of climate product interventions are subject to monitoring and evaluation throughout the process. Methods, approaches and preliminary results of our work in the Caribbean will be presented.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMAX-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56% of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Modeling climate effects on hip fracture rate by the multivariate GARCH model in Montreal region, Canada

NASA Astrophysics Data System (ADS)

Modarres, Reza; Ouarda, Taha B. M. J.; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2014-07-01

Changes in extreme meteorological variables and the demographic shift towards an older population have made it important to investigate the association of climate variables and hip fracture by advanced methods in order to determine the climate variables that most affect hip fracture incidence. The nonlinear autoregressive moving average with exogenous variable-generalized autoregressive conditional heteroscedasticity (ARMA X-GARCH) and multivariate GARCH (MGARCH) time series approaches were applied to investigate the nonlinear association between hip fracture rate in female and male patients aged 40-74 and 75+ years and climate variables in the period of 1993-2004, in Montreal, Canada. The models describe 50-56 % of daily variation in hip fracture rate and identify snow depth, air temperature, day length and air pressure as the influencing variables on the time-varying mean and variance of the hip fracture rate. The conditional covariance between climate variables and hip fracture rate is increasing exponentially, showing that the effect of climate variables on hip fracture rate is most acute when rates are high and climate conditions are at their worst. In Montreal, climate variables, particularly snow depth and air temperature, appear to be important predictors of hip fracture incidence. The association of climate variables and hip fracture does not seem to change linearly with time, but increases exponentially under harsh climate conditions. The results of this study can be used to provide an adaptive climate-related public health program and ti guide allocation of services for avoiding hip fracture risk.

Using Copernicus earth observation services to monitor climate change impacts and adaptations

NASA Astrophysics Data System (ADS)

Becker, Daniel; Zebisch, Marc; Sonnenschein, Ruth; Schönthaler, Konstanze; von Andrian-Werburg, Stefan

2016-04-01

In the last years, earth observation made a big leap towards an operational monitoring of the state of environment. Remote sensing provides for instance information on the dynamics, trends and anomalies of snow and glaciers, vegetation, soil moisture or water temperature. In particular, the European Copernicus initiative offers new opportunities through new satellites with a higher temporal and spatial resolution, operational services for environmental monitoring and an open data access policy. With the Copernicus climate change service and the ESA climate change initiative, specific earth observation programs are in place to address the impacts of climate change. However, such products and services are until now rarely picked up in the field of policy or decision making oriented climate impact or climate risk assessments. In this talk, we will present results of a study, which focus on the question, if and how remote sensing approaches could be integrated into operational monitoring activities of climate impacts and response measures on a national and subnational scale. We assessed all existing and planned Copernicus services regarding their relevance for climate impact monitoring by comparing them against the indication fields from an indicator system for climate impact and response monitoring in Germany, which has lately been developed in the framework of the German national adaptation strategy. For several climate impact or response indicators, an immediate integration of remote sensing data could be identified and been recommended. For these cases, we will show practical examples on the benefit of remote sensing data. For other indication fields, promising approaches were found, which need further development. We argue that remote sensing is a very valuable complement to the existing indicator schemes by contributing with spatial explicit, timely information but not always easy to integrate with classical approaches, which are oriented towards consistent long term monitoring. Furthermore, we provide specific recommendations for the Copernicus services to ensure a consistent climate change monitoring in future and we indicate options and limitations for integrating service products into practical assessment and monitoring activities.

Assessment of Human Health Vulnerability to Climate Variability and Change in Cuba

PubMed Central

Bultó, Paulo Lázaro Ortíz; Rodríguez, Antonio Pérez; Valencia, Alina Rivero; Vega, Nicolás León; Gonzalez, Manuel Díaz; Carrera, Alina Pérez

2006-01-01

In this study we assessed the potential effects of climate variability and change on population health in Cuba. We describe the climate of Cuba as well as the patterns of climate-sensitive diseases of primary concern, particularly dengue fever. Analyses of the associations between climatic anomalies and disease patterns highlight current vulnerability to climate variability. We describe current adaptations, including the application of climate predictions to prevent disease outbreaks. Finally, we present the potential economic costs associated with future impacts due to climate change. The tools used in this study can be useful in the development of appropriate and effective adaptation options to address the increased climate variability associated with climate change. PMID:17185289

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

NASA Technical Reports Server (NTRS)

Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.

2016-01-01

In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.

Climate-driven shifts in quantity and seasonality of river discharge over the past 1000 years from the hydrographic apex of North America

NASA Astrophysics Data System (ADS)

Wolfe, Brent B.; Hall, Roland I.; Edwards, Thomas W. D.; Jarvis, Suzanne R.; Sinnatamby, R. Niloshini; Yi, Yi; Johnston, John W.

2008-12-01

Runoff generated from high elevations is the primary source of freshwater for western North America, yet this critical resource is managed on the basis of short instrumental records that capture an insufficient range of climatic conditions. Here we probe the effects of climate change over the past ~1000 years on river discharge in the upper Mackenzie River system based on paleoenvironmental information from the Peace-Athabasca Delta. The delta landscape responds to hydroclimatic changes with marked variability, while Lake Athabasca level appears to directly monitor overall water availability. The latter fluctuated systematically over the past millennium, with the highest levels occurring in concert with maximum glacier extent during the Little Ice Age, and the lowest during the 11th century, prior to medieval glacier expansion. Recent climate-driven hydrological change appears to be on a trajectory to even lower levels as high-elevation snow and glacier meltwater contributions both continue to decline.

Climate variability drives population cycling and synchrony

Treesearch

Lars Y. Pomara; Benjamin Zuckerberg

2017-01-01

Aim There is mounting concern that climate change will lead to the collapse of cyclic population dynamics, yet the influence of climate variability on population cycling remains poorly understood. We hypothesized that variability in survival and fecundity, driven by climate variability at different points in the life cycle, scales up from...

Long-Term Monitoring of Global Climate Forcings and Feedbacks

NASA Technical Reports Server (NTRS)

Hansen, J. (Editor); Rossow, W. (Editor); Fung, I. (Editor)

1993-01-01

A workshop on Long-Term Monitoring of Global Climate Forcings and Feedbacks was held February 3-4, 1992, at NASA's Goddard Institute for Space Studies to discuss the measurements required to interpret long-term global temperature changes, to critique the proposed contributions of a series of small satellites (Climsat), and to identify needed complementary monitoring. The workshop concluded that long-term (several decades) of continuous monitoring of the major climate forcings and feedbacks is essential for understanding long-term climate change.

Multi-proxy monitoring approaches at Kangaroo Island, South Australia

NASA Astrophysics Data System (ADS)

Dixon, Bronwyn; Drysdale, Russell; Tyler, Jonathan; Goodwin, Ian

2017-04-01

Interpretations of geochemical signals preserved in young speleothems are greatly enhanced by comprehensive cave-site monitoring. In the light of this, a cave monitoring project is being conducted concurrently with the development of a new palaeoclimate record from Kelly Hill Cave (Kangaroo Island, South Australia). The site is strategically located because it is situated between longer-lived monitoring sites in southeastern and southwestern Australia, as well as being climatically 'upstream' from major population and agricultural centres. This study aims to understand possible controls on speleothem δ18O in Kelly Hill Cave through i. identification of local and regional δ18O drivers in precipitation; and ii. preservation and modification of climatic signals within the epikarst as indicated by dripwater δ18O. These aims are achieved through analysis of a five-year daily rainfall (amount and δ18O) dataset in conjunction with in-cave drip monitoring. Drivers of precipitation δ18O were identified through linear regression between δ18O values and local meteorological variables, air-parcel back trajectories, and synoptic-typing. Synoptically driven moisture sources were identified through the use of NCEP/NCAR climate reanalysis sea-level pressure, precipitable moisture, and outgoing longwave radiation data in order to trace moisture sources and travel mechanisms from surrounding ocean basins. Local controls on δ18O at Kelly Hill Cave are consistent with published interpretations of southern Australia sites, with oxygen isotopes primarily controlled by rainfall amount on both daily and monthly time scales. Back-trajectory analysis also supports previous observations that the Southern Ocean is the major source for moisture-bearing cold-front systems. However, synoptic typing of daily rainfall δ18O and amount extremes reveals a previously unreported tropical connection and moisture source. This tropical connection appears to be strongest in summer and autumn, but exists throughout the year. This indicates that a wider range of precipitation data sources can be combined to present a more comprehensive understanding of moisture dynamics and interaction of synoptic conditions to drive rainfall geochemistry. Within the cave environment at Kelly Hill Cave there is high spatial variability in drip characteristics, both in terms of drip frequency and drip water δ18O. Ongoing analyses are aimed at determining if monthly and/or seasonal rainfall δ18O drivers are also reflected in dripwater values. Overall, Kangaroo Island presents a new location to investigate the interplay between tropical and temperate influences in southern Australia, as well as a location for east - west comparisons between monitoring sites across southern Australia.

Natural resource mitigation, adaptation and research needs related to climate change in the Great Basin and Mojave Desert

USGS Publications Warehouse

Hughson, Debra L.; Busch, David E.; Davis, Scott; Finn, Sean P.; Caicco, Steve; Verburg, Paul S.J.

2011-01-01

This report synthesizes the knowledge, opinions, and concerns of many Federal and State land managers, scientists, stakeholders, and partners from a workshop, held at the University of Nevada, Las Vegas, on April 20-22, 2010. Land managers, research scientists, and resource specialists identified common concerns regarding the potential effects of climate change on public lands and natural resources in the Great Basin and Mojave Desert and developed recommendations for mitigation, adaptation, and research needs. Water and, conversely, the effects of drought emerged as a common theme in all breakout sessions on terrestrial and aquatic species at risk, managing across boundaries, monitoring, and ecosystem services. Climate change models for the southwestern deserts predict general warming and drying with increasing precipitation variability year to year. Scientists noted that under these changing conditions the past may no longer be a guide to the future in which managers envision increasing conflicts between human water uses and sustaining ecosystems. Increasing environmental stress also is expected as a consequence of shifting ecosystem boundaries and species distributions, expansion of non-native species, and decoupling of biotic mutualisms, leading to increasingly unstable biologic communities. Managers uniformly expressed a desire to work across management and agency boundaries at a landscape scale but conceded that conflicting agency missions and budgetary constraints often impede collaboration. More and better science is needed to cope with the effects of climate change but, perhaps even more important is the application of science to management issues using the methods of adaptive management based on long-term monitoring to assess the merits of management actions. Access to data is essential for science-based land management. Basic inventories, spatial databases, baseline condition assessments, data quality assurance, and data sharing were identified as top information priorities by all participants at this workshop. Optimizing the utility of ecosystem monitoring data will require standardizing monitoring protocols across agencies. Better communication among researchers and managers and cooperation through partnerships to manage resources across boundaries were emphasized as necessary for adapting to changing climatic conditions. However, even these strategies may be insufficient unless policy mandates, agency missions, and funding are coordinated at a high level.

Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall structure of the variance spectrum has important consequences for the probability of multi-year drought. Our lake record suggests there is a significant background threat of multi-year, and even decade-length, drought in western Amazonia, whereas climate model simulations indicate most droughts likely last no longer than one to three years. These findings suggest climate models may underestimate the future risk of extended drought in this important region. In Appendix C, we expand our analysis of climate variability beyond South America. We use observations, well-constrained tropical paleoclimate, and Earth system model data to examine the overall shape of the climate spectrum across interannual to century frequencies. We find a general agreement among observations and models that temperature variability increases with timescale across most of the globe outside the tropics. However, as compared to paleoclimate records, climate models generate too little low-frequency variability in the tropics (e.g., Laepple and Huybers, 2014). When we compare the shape of the simulated climate spectrum to the spectrum of a simple autoregressive process, we find much of the modeled surface temperature variability in the tropics could be explained by ocean smoothing of weather noise. Importantly, modeled precipitation tends to be similar to white noise across much of the globe. By contrast, paleoclimate records of various types from around the globe indicate that both temperature and precipitation variability should experience much more low-frequency variability than a simple autoregressive or white-noise process. In summary, state-of-the-art climate models generate some degree of dynamically driven low-frequency climate variability, especially at high latitudes. However, the latest climate models, observations, and paleoclimate data provide us with drastically different pictures of the background climate system and its associated risks. This research has important consequences for improving how we simulate climate extremes as we enter a warmer (and often drier) world in the coming centuries; if climate models underestimate low-frequency variability, we will underestimate the risk of future abrupt change and extreme events, such as megadroughts.

Interactions of Mean Climate Change and Climate Variability on Food Security Extremes

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; McDermid, Sonali; Mavromatis, Theodoros; Hudson, Nicholas; Morales, Monica; Simmons, John; Prabodha, Agalawatte; Ahmad, Ashfaq; Ahmad, Shakeel; Ahuja, Laj R.

2015-01-01

Recognizing that climate change will affect agricultural systems both through mean changes and through shifts in climate variability and associated extreme events, we present preliminary analyses of climate impacts from a network of 1137 crop modeling sites contributed to the AgMIP Coordinated Climate-Crop Modeling Project (C3MP). At each site sensitivity tests were run according to a common protocol, which enables the fitting of crop model emulators across a range of carbon dioxide, temperature, and water (CTW) changes. C3MP can elucidate several aspects of these changes and quantify crop responses across a wide diversity of farming systems. Here we test the hypothesis that climate change and variability interact in three main ways. First, mean climate changes can affect yields across an entire time period. Second, extreme events (when they do occur) may be more sensitive to climate changes than a year with normal climate. Third, mean climate changes can alter the likelihood of climate extremes, leading to more frequent seasons with anomalies outside of the expected conditions for which management was designed. In this way, shifts in climate variability can result in an increase or reduction of mean yield, as extreme climate events tend to have lower yield than years with normal climate.C3MP maize simulations across 126 farms reveal a clear indication and quantification (as response functions) of mean climate impacts on mean yield and clearly show that mean climate changes will directly affect the variability of yield. Yield reductions from increased climate variability are not as clear as crop models tend to be less sensitive to dangers on the cool and wet extremes of climate variability, likely underestimating losses from water-logging, floods, and frosts.

Effects of climate and water balance across grasslands of varying C3 and C4 grass cover

USGS Publications Warehouse

Witwicki, Dana L.; Munson, Seth M.; Thoma, David P.

2016-01-01

Climate change in grassland ecosystems may lead to divergent shifts in the abundance and distribution of C3 and C4 grasses. Many studies relate mean climate conditions over relatively long time periods to plant cover, but there is still much uncertainty about how the balance of C3and C4 species will be affected by climate at a finer temporal scale than season (individual events to months). We monitored cover at five grassland sites with co-dominant C3 and C4 grass species or only dominant C3 grass species for 6 yr in national parks across the Colorado Plateau region to assess the influence of specific months of climate and water balance on changes in grass cover. C4 grass cover increased and decreased to a larger degree than C3 grass cover with extremely dry and wet consecutive years, but this response varied by ecological site. Climate and water balance explained 10–49% of the inter-annual variability of cover of C3 and C4 grasses at all sites. High precipitation in the spring and in previous year monsoon storms influenced changes in cover of C4 grasses, with measures of water balance in the same months explaining additional variability. C3 grasses in grasslands where they were dominant were influenced primarily by longer periods of climate, while C3 grasses in grasslands where they were co-dominant with C4 grasses were influenced little by climate anomalies at either short or long periods of time. Our results suggest that future changes in spring and summer climate and water balance are likely to affect cover of both C3 and C4 grasses, but cover of C4 grasses may be affected more strongly, and the degree of change will depend on soils and topography where they are growing and the timing of the growing season.

Informing Adaptation Decisions: What Do We Need to Know and What Do We Need to Do?

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.; Webb, R. S.

2014-12-01

The demand for improved climate knowledge and information is well documented. As noted in the IPCC Reports (SREX, AR5) and other assessments, this demand has increased pressure for better information to support planning under changing rates of extremes event occurrence. This demand has focused on mechanisms used to respond to past variability and change, including, integrated resource management (watersheds, coasts), infrastructure design, information systems, technological optimization, financial risk management, and behavioral and institutional change. Climate inputs range from static site design statistics (return periods) to dynamic, emergent thresholds and transitions preceded by steep response curves and punctuated equilibria. Tradeoffs are evident in the use of risk-based anticipatory strategies vs. resilience measures. In such settings, annual decision calendars for operational requirements can confound adaptation expectations. Key knowledge assessment questions include: (1) How predictable are potential impacts of events in the context of other stressors, (2) how is action to anticipate such impacts informed, and (3) How often should criteria for "robustness" be reconsidered? To illustrate, we will discuss the climate information needs and uses for two areas of concern for both short and long-term risks (i) climate and disaster risk financing, and (ii) watershed management. The presentation will focus on the climate information needed for (1) improved monitoring, modeling and methods for understanding and analyzing exposure risks, (2) generating risk profiles, (3) developing information systems and scenarios for critical thresholds across climate time and space scales, (4) embedding annual decision calendars in the context of longer-term risk management, (5) gaming experiments to show the net benefits of new information. We will conclude with a discussion of the essential climate variables needed to implement services-delivery and development efforts such as the Global Framework for Climate Services and the Pilot Program on Climate Resilience.

Influences of climate on aflatoxin producing fungi and aflatoxin contamination.

PubMed

Cotty, Peter J; Jaime-Garcia, Ramon

2007-10-20

Aflatoxins are potent mycotoxins that cause developmental and immune system suppression, cancer, and death. As a result of regulations intended to reduce human exposure, crop contamination with aflatoxins causes significant economic loss for producers, marketers, and processors of diverse susceptible crops. Aflatoxin contamination occurs when specific fungi in the genus Aspergillus infect crops. Many industries frequently affected by aflatoxin contamination know from experience and anecdote that fluctuations in climate impact the extent of contamination. Climate influences contamination, in part, by direct effects on the causative fungi. As climate shifts, so do the complex communities of aflatoxin-producing fungi. This includes changes in the quantity of aflatoxin-producers in the environment and alterations to fungal community structure. Fluctuations in climate also influence predisposition of hosts to contamination by altering crop development and by affecting insects that create wounds on which aflatoxin-producers proliferate. Aflatoxin contamination is prevalent both in warm humid climates and in irrigated hot deserts. In temperate regions, contamination may be severe during drought. The contamination process is frequently broken down into two phases with the first phase occurring on the developing crop and the second phase affecting the crop after maturation. Rain and temperature influence the phases differently with dry, hot conditions favoring the first and warm, wet conditions favoring the second. Contamination varies with climate both temporally and spatially. Geostatistics and multiple regression analyses have shed light on influences of weather on contamination. Geostatistical analyses have been used to identify recurrent contamination patterns and to match these with environmental variables. In the process environmental conditions with the greatest impact on contamination are identified. Likewise, multiple regression analyses allow ranking of environmental variables based on relative influence on contamination. Understanding the impact of climate may allow development of improved management procedures, better allocation of monitoring efforts, and adjustment of agronomic practices in anticipation of global climate change.

78 FR 18323 - Notice of Availability of a Draft Programmatic Environmental Assessment of the Proposed United...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-26

... Proposed United States Regional Climate Reference Network (USRCRN) AGENCY: National Weather Service (NWS..., is proposing to implement, operate, and manage a USRCRN. With other climate monitoring efforts..., high-quality climate data for use in climate-monitoring activities and for placing current climate...

CPC - Monitoring & Data: Regional Climate Maps

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Site Map News Information CPC Web Team HOME > Monitoring and Data > Global Climate Data & Maps > Global Regional Climate Maps Regional Climate Maps Banner The Monthly regional analyses products are usually

Climate Impact of Solar Variability

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H. (Editor); Arking, Albert (Editor)

1990-01-01

The conference on The Climate Impact of Solar Variability, was held at Goddard Space Flight Center from April 24 to 27, 1990. In recent years they developed a renewed interest in the potential effects of increasing greenhouse gases on climate. Carbon dioxide, methane, nitrous oxide, and the chlorofluorocarbons have been increasing at rates that could significantly change climate. There is considerable uncertainty over the magnitude of this anthropogenic change. The climate system is very complex, with feedback processes that are not fully understood. Moreover, there are two sources of natural climate variability (volcanic aerosols and solar variability) added to the anthropogenic changes which may confuse our interpretation of the observed temperature record. Thus, if we could understand the climatic impact of the natural variability, it would aid our interpretation and understanding of man-made climate changes.

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.

2015-01-01

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Spatio-Temporal Variability of Groundwater Storage in India

NASA Technical Reports Server (NTRS)

Bhanja, Soumendra; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2016-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Ground water storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent).In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

Spatio-temporal variability of groundwater storage in India.

PubMed

Bhanja, Soumendra N; Rodell, Matthew; Li, Bailing; Mukherjee, Abhijit

2017-01-01

Groundwater level measurements from 3907 monitoring wells, distributed within 22 major river basins of India, are assessed to characterize their spatial and temporal variability. Groundwater storage (GWS) anomalies (relative to the long-term mean) exhibit strong seasonality, with annual maxima observed during the monsoon season and minima during pre-monsoon season. Spatial variability of GWS anomalies increases with the extent of measurements, following the power law relationship, i.e., log-(spatial variability) is linearly dependent on log-(spatial extent). In addition, the impact of well spacing on spatial variability and the power law relationship is investigated. We found that the mean GWS anomaly sampled at a 0.25 degree grid scale closes to unweighted average over all wells. The absolute error corresponding to each basin grows with increasing scale, i.e., from 0.25 degree to 1 degree. It was observed that small changes in extent could create very large changes in spatial variability at large grid scales. Spatial variability of GWS anomaly has been found to vary with climatic conditions. To our knowledge, this is the first study of the effects of well spacing on groundwater spatial variability. The results may be useful for interpreting large scale groundwater variations from unevenly spaced or sparse groundwater well observations or for siting and prioritizing wells in a network for groundwater management. The output of this study could be used to maintain a cost effective groundwater monitoring network in the study region and the approach can also be used in other parts of the globe.

CLIMCONG: A framework-tool for assessing CLIMate CONGruency

NASA Astrophysics Data System (ADS)

Buras, Allan; Kölling, Christian; Menzel, Annette

2016-04-01

It is widely accepted that the anticipated elevational and latitudinal shifting of climate forces living organisms (including humans) to track these changes in space over a certain time. Due to the complexity of climate change, prediction of consequent migrations is a difficult procedure afflicted with many uncertainties. To simplify climate complexity and ease respective attempts, various approaches aimed at classifying global climates. For instance, the frequently used Köppen-Geiger climate classification (Köppen, 1900) has been applied to predict the shift of climate zones throughout the 21st century (Rubel and Kottek, 2010). Another - more objective but also more complex - classification approach has recently been presented by Metzger et al. (2013). Though being comprehensive, classifications have certain drawbacks, as I) often focusing on few variables, II) having discrete borders at the margins of classes, and III) subjective selection of an arbitrary number of classes. Ecological theory suggests that when only considering temperature and precipitation (such as Köppen, 1900) particular climate features - e.g. radiation and plant water availability - may not be represented with sufficient precision. Furthermore, sharp boundaries among homogeneous classes do not reflect natural gradients. To overcome the aforementioned drawbacks, we here present CLIMCONG - a framework-tool for assessing climate congruency for quantitatively describing climate similarity through continua in space and time. CLIMCONG allows users to individually select variables for calculation of climate congruency. By this, particular foci can be specified, depending on actual research questions posed towards climate change. For instance, while ecologists focus on a multitude of parameters driving net ecosystem productivity, water managers may only be interested in variables related to drought extremes and water availability. Based on the chosen parameters CLIMCONG determines congruency of climates using Manhattan distances among locations. First applications of CLIMCONG were to I) globally cluster congruent eco-climates resulting in a classification being more objective than Köppen (1900) but at comparable complexity, II) successfully model MODIS average annual net primary productivity globally (R² = 0.69), and III) identify recent climates (with foci varying from eco-climates over water availability to extreme events) most similar to the predicted (RCP-scenarios) climate of given locations worldwide without being restricted to classifications. Using CLIMCONG it thereby becomes possible to track the 'migration' of local climate conditions throughout the 20th and 21st century. Further applications are planned and a CLIMCONG 'R'-package is under preparation. Köppen, W., 1900: Versuch einer Klassifikation der Klimate, vorzugsweise nach ihren Beziehungen zur Pflanzenwelt. - Geogr. Zeitschr. 6, 593-611, 657-679. Metzger, M.J., Bunce, R.G.H., Jongman, R.H.G, Sayre, R., Trabucco, A., and Zomer, R., 2013: A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring. Global Ecology and Biogeography, 22, 630-638. Rubel, F., and Kottek, M., 2010: Observed and projected climate shifts 1901-2100 depicted by world maps of the Köppen-Geiger climate classification. Meteorologische Zeitschrift, 19, 135-141.

Broad-spectrum monitoring strategies for predicting occult precipitation contribution to water balance in a coastal watershed in California: Ground-truthing, areal monitoring and isotopic analysis of fog in the San Francisco Bay region

NASA Astrophysics Data System (ADS)

Koohafkan, M.; Thompson, S. E.; Leonardson, R.; Dufour, A.

2013-12-01

We showcase a fog monitoring study designed to quantitatively estimate the contribution of summer fog events to the water balance of a coastal watershed managed by the San Francisco Public Utilities Commission. Two decades of research now clearly show that fog and occult precipitation can be major contributors to the water balance of watersheds worldwide. Monitoring, understanding and predicting occult precipitation is therefore as hydrologically compelling as forecasting precipitation or evaporation, particularly in the face of climate variability. We combine ground-based monitoring and collection strategies with remote sensing technologies, time-lapse imagery, and isotope analysis to trace the ';signature' of fog in physical and ecological processes. Spatial coverage and duration of fog events in the watershed is monitored using time-lapse cameras and leaf wetness sensors strategically positioned to provide estimates of the fog bank extent and cloud base elevation, and this fine-scale data is used to estimate transpiration suppression by fog and is examined in the context of regional climate through the use of satellite imagery. Soil moisture sensors, throughfall collectors and advective fog collectors deployed throughout the watershed provide quantitative estimates of fog drip contribution to soil moisture and plants. Fog incidence records and streamflow monitoring provide daily estimates of fog contribution to streamflow. Isotope analysis of soil water, fog drip, stream water and vegetation samples are used to probe for evidence of direct root and leaf uptake of fog drip by plants. Using this diversity of fog monitoring methods, we develop an empirical framework for the inclusion of fog processes in water balance models.

Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

NASA Astrophysics Data System (ADS)

Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

2013-04-01

Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the growing season are analyzed. Trend analysis with robust statistical test of significance is conducted. Climate variables (precipitation, temperature, radiation) are then used to interpret the anomaly patterns detected in vegetation response.

Development of A Dust Climate Indicator for the US National Climate Assessment

NASA Astrophysics Data System (ADS)

Tong, D.; Wang, J. X. L.; Gill, T. E.; Van Pelt, S.; Kim, D.

2016-12-01

Dust activity is a relatively simple but practical indicator to document the response of dryland ecosystems to climate change, making it an integral part of the National Climate Assessment (NCA). We present here a multi-agency collaboration that aims at developing a suite of dust climate indicators to document and monitor the long-term variability and trend of dust storm activity in the western United States. Recent dust observations have revealed rapid intensification of dust storm activity in the western United States. This trend is also closely correlated with a rapid increase in dust deposition in rainwater and "valley fever" hospitalization in southwestern states. It remains unclear, however, if such a trend, when enhanced by predicted warming and rainfall oscillation in the Southwest, will result in irreversible environmental development such as desertification or even another "Dust Bowl". Based on continuous ground aerosol monitoring, we have reconstructed a long-term dust storm climatology in the western United States. We report here direct evidence of rapid intensification of dust storm activity over US deserts in the past decades (1990 to 2013), in contrast to the decreasing trends in Asia and Africa. The US trend is spatially and temporally correlated with incidences of valley fever, an infectious disease caused by soil-dwelling fungus that has increased eight-fold in the past decade. We further investigate the linkage between dust variations and possible climate drivers and find that the regional dust trends are likely driven by large-scale variations of sea surface temperature in the Pacific Ocean, with the strongest correlation with the Pacific Decadal Oscillation (PDO). Future study will explore the link between the temporal and spatial trends of increase in dustiness and vegetation change in southwestern semi-arid and arid ecosystems.

Multi-year GNSS monitoring of atmospheric IWV over Central and South America for climate studies

NASA Astrophysics Data System (ADS)

Mendoza, Luciano; Bianchi, Clara; Fernández, Laura; Natali, María Paula; Meza, Amalia; Moirano, Juan

2017-04-01

Atmospheric water vapour has been acknowledged as an essential climate variable. Weather prediction and hazard assessment systems benefit from real-time observations, whereas long-term records contribute to climate studies. Nowadays, ground-based GNSS products have become widely employed, complementing satellite observations over the oceans. Although the past decade has seen a significant development of the GNSS infrastructure in Central and South America, its potential for atmospheric water vapour monitoring has not been fully exploited. With this in mind, we have performed a regional, seven-year long and homogeneous analysis, comprising 136 GNSS tracking stations, obtaining high-rate and continuous observations of column integrated water vapour and troposphere zenith total delay (Bianchi et al. 2016). As preliminary application for this data set, we have estimated local water vapour trends, their significance, and their relation with specific climate regimes. We have found evidence of drying at temperate regions in South America, at a rate of about 2% per decade, while a slow moistening of the troposphere over tropical regions is also weakly suggested by our results. Furthermore, we have assessed the regional performance of the empirical model GPT2w to blindly estimate troposphere delays. The model fairly reproduces the observed mean delays, including their annual and semi-annual variations. Nevertheless, a long-term evaluation has shown systematical biases, up to 20 mm, probably inherited form the underling atmospheric reanalysis. Additionally, the complete data set has been made openly available at a scientific repository (doi:10.1594/PANGAEA.858234). References: C. Bianchi, L. Mendoza, L. Fernandez, M. P. Natali, A. Meza, J. F. Moirano, Multi-year GNSS monitoring of atmospheric IWV over Central and South America for climate studies, Ann. Geophys., ISSN 0992-7689, eISSN 1432-0576, 34 (7), 623-639 (doi:10.5194/angeo-34-623-2016).

Effects of Atlantic warm pool variability over climate of South America tropical transition zone

NASA Astrophysics Data System (ADS)

Ricaurte Villota, Constanza; Romero-Rodríguez, Deisy; Andrés Ordoñez-Zuñiga, Silvio; Murcia-Riaño, Magnolia; Coca-Domínguez, Oswaldo

2016-04-01

Colombia is located in the northwestern corner of South America in a climatically complex region due to the influence processes modulators of climate both the Pacific and Atlantic region, becoming in a transition zone between phenomena of northern and southern hemisphere. Variations in the climatic conditions of this region, especially rainfall, have been attributed to the influence of the El Nino Southern Oscillation (ENSO), but little is known about the interaction within Atlantic Ocean and specifically Caribbean Sea with the environmental conditions of this region. In this work We studied the influence of the Atlantic Warm Pool (AWP) on the Colombian Caribbean (CC) climate using data of Sea Surface Temperature (SST) between 1900 - 2014 from ERSST V4, compared with in situ data SIMAC (National System for Coral Reef Monitoring in Colombia - INVEMAR), rainfall between 1953-2013 of meteorological stations located at main airports in the Colombian Caribbean zone, administered by IDEAM, and winds data between 2003 - 2014 from WindSat sensor. The parameters analyzed showed spatial differences throughout the study area. SST anomalies, representing the variability of the AWP, showed to be associated with Multidecadal Atlantic Oscillation (AMO) and with the index of sea surface temperature of the North-tropical Atlantic (NTA), the variations was on 3 to 5 years on the ENSO scale and of approximately 11 years possibly related to solar cycles. Rainfall anomalies in the central and northern CC respond to changes in SST, while in the south zone these are not fully engage and show a high relationship with the ENSO. Finally, the winds also respond to changes in SST and showed a signal approximately 90 days possibly related to the Madden-Julian Oscillation, whose intensity depends on the CC region being analyzed. The results confirm that region is a transition zone in which operate several forcing, the variability of climate conditions is difficult to attribute only one, as ENSO, since the role of the AWP in the climate of this region and especially in the central part proves to be decisive, probably due to changes in moisture and heat flows transferred to the atmosphere.

Climate-driven vital rates do not always mean climate-driven population.

PubMed

Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel

2016-12-01

Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

How to structure and prioritize information needs in support of monitoring design for Integrated Coastal Management

NASA Astrophysics Data System (ADS)

Vugteveen, Pim; van Katwijk, Marieke M.; Rouwette, Etiënne; Hanssen, Lucien

2014-02-01

Integrated Coastal Management cannot operate effectively without reliable information and knowledge on changes in the environment and on the causes of those changes. Monitoring is essential to provide data needed for a real understanding of socio-economic and ecological functioning in multi-user nature areas. We present a web-based and comprehensive assessment methodology to articulate, structure and prioritize information needs and ensuing monitoring needs. We applied this methodology in the Dutch Wadden Sea Region, which includes a designated UNESCO World Heritage nature reserve. The methodology consists of the following steps: i) exploring social-ecological issues of concern and defining the monitoring scope; ii) articulating information needs expressed as tractable questions; iii) elaborating monitoring needs; iv) grounding in scientific models and current monitoring; v) synthesizing assessment findings into target entities, i.e. analysis variables for monitoring. In this paper we focus on the first three steps. As part of our methodology we performed two online surveys amongst a broad range of stakeholders and amongst monitoring professionals. In the case of the Dutch Wadden Sea Region, main monitoring questions were related to biodiversity and food web relations; effects of fisheries and its pressures on the ecosystem; channel and port dredging; spatial planning and multifunctional use; sustainable energy production; and effects of changing storm regimes due to climate change. Subsequently we elaborated these general issues into analysis variables within five themes. The presented methodology enables large scale and unbiased involvement of stakeholders in articulating information needs in a multi-user nature reserve like the Wadden Sea. In addition the methodology facilitates the input and feedback of monitoring professionals by providing a detailed elaboration of monitoring needs.

Science and Technology to Support Fresh Water Availability in the United States

DTIC Science & Technology

2004-11-01

expand research and monitoring efforts to better understand the water cycle , its variability and relation to global climate change, and to provide basic...hydrologi- cal processes on the distribution, structure, and function of ecosys- tems, and on the effects of biotic processes on elements of the water ... cycle .”22 The science has evolved from one that simply indicated what minimum flows might be needed to maintain a particular spe- cies in a river, to

Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale

USGS Publications Warehouse

Munson, Seth M.; Duniway, Michael C.; Johanson, Jamin K.

2015-01-01

Managers of rangeland ecosystems require methods to track the condition of natural resources over large areas and long periods of time as they confront climate change and land use intensification. We demonstrate how rangeland monitoring results can be synthesized using ecological site concepts to understand how climate, site factors, and management actions affect long-term vegetation dynamics at the landscape-scale. Forty-six years of rangeland monitoring conducted by the Bureau of Land Management (BLM) on the Colorado Plateau reveals variable responses of plant species cover to cool-season precipitation, land type (ecological site groups), and grazing intensity. Dominant C3 perennial grasses (Achnatherum hymenoides, Hesperostipa comata), which are essential to support wildlife and livestock on the Colorado Plateau, had responses to cool-season precipitation that were at least twice as large as the dominant C4 perennial grass (Pleuraphis jamesii) and woody vegetation. However, these C3 perennial grass responses to precipitation were reduced by nearly one-third on grassland ecological sites with fine- rather than coarse-textured soils, and there were no detectable C3 perennial grass responses to precipitation on ecological sites dominated by a dense-growing shrub, Coleogyne ramosissima. Heavy grazing intensity further reduced the responses of C3 perennial grasses to cool-season precipitation on ecological sites with coarse-textured soils and surprisingly reduced the responses of shrubs as well. By using ecological site groups to assess rangeland condition, we were able to improve our understanding of the long-term relationships between vegetation change and climate, land use, and site characteristics, which has important implications for developing landscape-scale monitoring strategies.

Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS

NASA Technical Reports Server (NTRS)

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

2008-01-01

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

Hydrologic Evaluation of a Humid Climate Poplar Phytoremediation Barrier

NASA Astrophysics Data System (ADS)

Swensen, K.; Rabideau, A. J.

2016-12-01

The emplacement of hybrid poplar trees to function as phytoremediation barriers is an appealing and sustainable groundwater management strategy because of low maintenance costs and the potential to extract large amounts of groundwater without pumping. While the effectiveness of poplar barriers has been assessed by groundwater quality monitoring, less attention has been given to physical hydrologic evaluations needed to improve barrier designs. In this research, a five year hydrologic evaluation was conducted at a poplar phytoremediation site in western NY, with the goal of quantifying ETg (evapotranspiration from groundwater) as a measure of the barrier's effectiveness in a humid climate. To consider transpiration from both vadose zone and groundwater, the hydrologic evaluation included four components: physical ET measurements, theoretical ET calculations, analysis of diurnal groundwater table fluctuations, and vadose zone modeling. The direct measurements of ETT (total) were obtained using sap flow meters installed on multiple trees within the barrier. These data were interpreted using a regression model that included theoretical ET calculations and site-specific measurements of weather parameters and poplar trunk area. Application of this model was challenged by the spatial variation in rooting depth as determined by tree excavations. To further quantify the removal of groundwater by the phytobarrier (ETg), the White Method was applied to interpret diurnal groundwater fluctuations from monitoring wells located within the barrier, in conjunction with a variably saturated-saturated flow model configured to confirm water extraction from ETg. Taken together, the results of this five year hydrologic evaluation highlight the complexity in quantifying humid climate groundwater extraction, as a large number of variables were found to influence these rates. Improved understanding of these controls will contribute to improved barrier designs that maximize ETg.

How resilient are ecosystems in adapting to climate variability

NASA Astrophysics Data System (ADS)

Savenije, Hubert H. G.

2015-04-01

The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

[Dynamics of sap flow density in stems of typical desert shrub Calligonum mongolicum and its responses to environmental variables].

PubMed

Xu, Shi-qin; Ji, Xi-bin; Jin, Bo-wen

2016-02-01

Independent measurements of stem sap flow in stems of Calligonum mongolicum and environmental variables using commercial sap flow gauges and a micrometeorological monitoring system, respectively, were made to simulate the variation of sap flow density in the middle range of Hexi Corridor, Northwest China during June to September, 2014. The results showed that the diurnal process of sap flow density in C. mongolicum showed a broad unimodal change, and the maximum sap flow density reached about 30 minutes after the maximum of photosynthetically active radiation (PAR) , while about 120 minutes before the maximum of temperature and vapor pressure deficit (VPD). During the studying period, sap flow density closely related with atmosphere evapor-transpiration demand, and mainly affected by PAR, temperature and VPD. The model was developed which directly linked the sap flow density with climatic variables, and good correlation between measured and simulated sap flow density was observed in different climate conditions. The accuracy of simulation was significantly improved if the time-lag effect was taken into consideration, while this model underestimated low and nighttime sap flow densities, which was probably caused by plant physiological characteristics.

Climate Prediction Center - Monitoring & Data: Seasonal ENSO Impacts on

Science.gov Websites

page National Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center , state and local government Web resources and services. HOME > Monitoring and Data > U.S. Climate and Climate Prediction Climate Prediction Center 5830 University Research Court College Park, Maryland

CPC - Monitoring & Data: Pacific Island Climate Data

Science.gov Websites

Weather Service NWS logo - Click to go to the NWS home page Climate Prediction Center Home Site Map News Web resources and services. HOME > Monitoring and Data > Pacific Islands Climate Data & Maps island stations. NOAA/ National Weather Service NOAA Center for Weather and Climate Prediction Climate

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

PubMed Central

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-01-01

Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

PubMed

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-10-01

The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.

Potential breeding distributions of U.S. birds predicted with both short-term variability and long-term average climate data.

PubMed

Bateman, Brooke L; Pidgeon, Anna M; Radeloff, Volker C; Flather, Curtis H; VanDerWal, Jeremy; Akçakaya, H Resit; Thogmartin, Wayne E; Albright, Thomas P; Vavrus, Stephen J; Heglund, Patricia J

2016-12-01

Climate conditions, such as temperature or precipitation, averaged over several decades strongly affect species distributions, as evidenced by experimental results and a plethora of models demonstrating statistical relations between species occurrences and long-term climate averages. However, long-term averages can conceal climate changes that have occurred in recent decades and may not capture actual species occurrence well because the distributions of species, especially at the edges of their range, are typically dynamic and may respond strongly to short-term climate variability. Our goal here was to test whether bird occurrence models can be predicted by either covariates based on short-term climate variability or on long-term climate averages. We parameterized species distribution models (SDMs) based on either short-term variability or long-term average climate covariates for 320 bird species in the conterminous USA and tested whether any life-history trait-based guilds were particularly sensitive to short-term conditions. Models including short-term climate variability performed well based on their cross-validated area-under-the-curve AUC score (0.85), as did models based on long-term climate averages (0.84). Similarly, both models performed well compared to independent presence/absence data from the North American Breeding Bird Survey (independent AUC of 0.89 and 0.90, respectively). However, models based on short-term variability covariates more accurately classified true absences for most species (73% of true absences classified within the lowest quarter of environmental suitability vs. 68%). In addition, they have the advantage that they can reveal the dynamic relationship between species and their environment because they capture the spatial fluctuations of species potential breeding distributions. With this information, we can identify which species and guilds are sensitive to climate variability, identify sites of high conservation value where climate variability is low, and assess how species' potential distributions may have already shifted due recent climate change. However, long-term climate averages require less data and processing time and may be more readily available for some areas of interest. Where data on short-term climate variability are not available, long-term climate information is a sufficient predictor of species distributions in many cases. However, short-term climate variability data may provide information not captured with long-term climate data for use in SDMs. © 2016 by the Ecological Society of America.

Quality assurance report - Loch Vale Watershed, 1999-2002

USGS Publications Warehouse

Botte, Jorin A.; Baron, Jill S.

2004-01-01

The National Park Service initiated the Loch Vale Watershed (LVWS) project in 1980 with funding from the Aquatic Effects Research Program of the National Acid Precipitation Assessment Program. Long-term ecological research and monitoring address watershed-scale ecosystem processes, particularly as they respond to atmospheric deposition and climate variability. Monitoring of meteorological, hydrologic, precipitation chemistry, and surface water quality parameters enable us to use long-term trends to distinguish natural from human-caused disturbances. Research into snow distribution, hydrologic flowpaths, vegetation responses to N deposition, isotopic transformations of N by forest and soil processes, trace metals, and aquatic ecological responses to disturbance enable us to understand processes that influence high elevation ecosystems.

Spatio-Temporal Description of the Rainfall for Colombian Andean Mountainous Region for Weather Forecasting Purposes. Case Study: Manizales - Caldas, Colombia

NASA Astrophysics Data System (ADS)

Suarez Hincapie, J. N.

2014-12-01

Manizales is a city located in west-central Colombian Andes in the Caldas province, whose spatial location coincides with one of the most threatened areas of Colombia (landslides, earthquakes, volcanic eruptions, other). As a middle Andean mountainous city and for being located in the area of influence of the ITCZ presents an equatorial mountain climate with a bimodal rainfall regime, and with an average annual rainfall around 2000 mm, it shows very significant rates of precipitation, on average, 70% of the days of the year it is rainy. This situation favors the formation of large masses of clouds and the presence of macroclimatic phenomena such as ENSO, which has historically caused large-scale impacts in both warm and cold phase. Since last decade different entities have implemented a hydro-meteorological network which measures and transmits telemetrically every five minutes hydro-climatic variables. In general, the real-time weather monitoring should be used for a better understanding of our environmental urban environment and to establish indicators of quality of life and welfare for the community. Despite the city has telemetric data on atmospheric and hydrological variables, there is still no tool or a methodology able to generate a spatio-temporal description of these variables. So, the aim of this work is to establish guidelines to sort all this information of atmospheric variables monitored in real time with the help of data mining techniques, machine learning tools to improve the knowledge of atmospheric patterns at Manizales and to serve for territorial planning and decision makers. To reach this purpose the current data warehouse available at the National University of Colombia at Manizales will be used, and it will be fed with observed variables from hydro-meteorological monitoring stations that transmit in real-time. Then, as mentioned this information will make the corresponding processing with data mining techniques to describe the rainfall patterns. All this complemented with the application of statistical techniques for data analysis and exploration. The main contribution of this research is the creation of tools to be used in numerical modeling with forecasting purposes, aiming to improve the resolution given by mesoscale models, which are currently used for weather forecast in Colombia.

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

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

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

Precise monitoring of global temperature trends from satellites

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Christy, John R.

1990-01-01

Passive microwave radiometry from satellites provides more precise atmospheric temperature information than that obtained from the relatively sparse distribution of thermometers over the earth's surface. Accurate global atmospheric temperature estimates are needed for detection of possible greenhouse warming, evaluation of computer models of climate change, and for understanding important factors in the climate system. Analysis of the first 10 years (1979 to 1988) of satellite measurements of lower atmospheric temperature changes reveals a monthly precision of 0.01 C, large temperature variability on time scales from weeks to several years, but no obvious trend for the 10-year period. The warmest years, in descending order, were 1987, 1988, 1983, and 1980. The years 1984, 1985, and 1986 were the coolest.

Tropical Pacific climate during the Medieval Climate Anomaly: progress and pitfalls

NASA Astrophysics Data System (ADS)

Cobb, K. M.; Westphal, N.; Charles, C.; Sayani, H. R.; Edwards, R. L.; Cheng, H.; Grothe, P. R.; Chen, T.; Hitt, N. T.; O'Connor, G.; Atwood, A. R.

2016-12-01

A vast trove of paleoclimate records indicates that the Medieval Climate Anomaly (MCA; 900-1200AD) was characterized by relative warmth throughout the Northern Hemisphere and significant hydroclimate anomalies - particularly well-resolved over North America - that posed a challenge to human populations. The global-scale nature of the climate anomalies has driven speculation that the tropical Pacific, with its rich spectrum of natural variability and far-reaching impact, may have undergone a prolonged reorganization during the MCA. While some key records from across the tropical Pacific document significant changes in temperature and/or hydrology, a dynamically-consistent picture of the MCA tropical Pacific climate state has proven elusive. In particular, there are few if any robust paleoclimate constraints from the central Pacific, where even modest changes in ocean temperature translate into distinct patterns of global atmospheric teleconnections. Here, we present a new collection of fossil coral multi-proxy records from Christmas Island (2N, 157W) that provide robust constraints on both temperature and hydrological changes during the MCA. We employ both modern coral data, instrumental climate data, and climate model output in developing a framework for quantifying the uncertainties associated with the new fossil coral data. In doing so, we illustrate the clear benefits of modern environmental monitoring campaigns that inform the generation of paleoclimate pseudo-proxies.

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

The impact of climatic variations on the reproductive success of Gentiana lutea L. in a Mediterranean mountain area.

PubMed

Cuena-Lombraña, Alba; Fois, Mauro; Fenu, Giuseppe; Cogoni, Donatella; Bacchetta, Gianluigi

2018-03-30

Increases in temperature have been predicted and reported for the Mediterranean mountain ranges due to global warming and this phenomenon is expected to have profound consequences on biodiversity and ecosystem functioning. We hereby present the case of Gentiana lutea L. subsp. lutea, a rhizomatous long-lived plant living in Central-Southern Europe, which is at the edge of its ecological and distributional range in Sardinia. Concretely, we analysed the reproductive success experienced during three phenological cycles (2013/2014, 2014/2015 and 2015/2016) in four representative populations, with particular attention to the phenological cycle of 2014/2015, which has been recorded as one of the warmest periods of the last decades. The Smirnov-Grubbs test was used to evaluate differences in temperature and precipitation regimes among historical data and the analysed years, while the Kruskal-Wallis followed by the Wilcoxon test was used to measure differences between anthesis and reproductive performances among cycles and populations. In addition, generalised linear models were carried out to check relationships between climate variables and reproductive performance. Significant differences among climate variables and analysed cycles were highlighted, especially for maximum and mean temperatures. Such variations determined a non-flowering stage in two of the four analysed populations in 2014/2015 and significant differences of further five reproductive traits among cycles. These results confirmed that in current unstable climatic conditions, which are particularly evident in seasonal climates, reproductive success can be a sensitive and easily observable indicator of climatic anomalies. Considering the importance of this issue and the ease and cost-effectiveness of reproductive success monitoring, we argue that research in this sense can be a supporting tool for the enhancement of future crucial targets such as biodiversity conservation and the mitigation of global warming effects.

An analysis of relationships among climate forcing and time-integrated NDVI of grasslands over the U.S. northern and central Great Plains

USGS Publications Warehouse

Yang, Limin; Wylie, Bruce K.; Tieszen, Larry L.; Reed, Bradley C.

1998-01-01

Time-integrated normalized difference vegetation index (TI NDVI) derived from the multitemporal satellite imagery (1989–1993) was used as a surrogate for primary production to investigate climate impacts on grassland performance for central and northern Great Plains grasslands. Results suggest that spatial and temporal variability in growing season precipitation, potential evapotranspiration, and growing degree days are the most important controls on grassland performance and productivity. When TI NDVI and climate data of all grassland land cover classes were examined as a whole, a statistical model showed significant positive correlation between the TI NDVI and accumulated spring and summer precipitation, and a negative correlation between TI NDVI and spring potential evapotranspiration. The coefficient of determination (R2) of the general model was 0.45. When the TI NDVI-climate relationship was examined by individual land cover type, the relationship was generally better defined in terms of the variance accounted for by class-specific models . The photosynthetic pathway is an important determinant of grassland performance with northern mixed prairie (mixture of C3 and C4 grassland) TI NDVI affected by both thermal and moisture conditions during the growing season while southern plains grasslands (primarily C4grassland) were predominantly influenced by spring and summer precipitation. Grassland land cover classes associated with sandy soils also demonstrated a strong relationship between TI NDVI and growing season rainfall. Significant impact of interannual climate variability on the TI NDVI–climate relationship was also observed. The study suggests an integrated approach involving numerical models, satellite remote sensing, and field observations to monitor grassland ecosystem dynamics on a regional scale.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

The impact of climatic variations on the reproductive success of Gentiana lutea L. in a Mediterranean mountain area

NASA Astrophysics Data System (ADS)

Cuena-Lombraña, Alba; Fois, Mauro; Fenu, Giuseppe; Cogoni, Donatella; Bacchetta, Gianluigi

2018-03-01

Increases in temperature have been predicted and reported for the Mediterranean mountain ranges due to global warming and this phenomenon is expected to have profound consequences on biodiversity and ecosystem functioning. We hereby present the case of Gentiana lutea L. subsp. lutea, a rhizomatous long-lived plant living in Central-Southern Europe, which is at the edge of its ecological and distributional range in Sardinia. Concretely, we analysed the reproductive success experienced during three phenological cycles (2013/2014, 2014/2015 and 2015/2016) in four representative populations, with particular attention to the phenological cycle of 2014/2015, which has been recorded as one of the warmest periods of the last decades. The Smirnov-Grubbs test was used to evaluate differences in temperature and precipitation regimes among historical data and the analysed years, while the Kruskal-Wallis followed by the Wilcoxon test was used to measure differences between anthesis and reproductive performances among cycles and populations. In addition, generalised linear models were carried out to check relationships between climate variables and reproductive performance. Significant differences among climate variables and analysed cycles were highlighted, especially for maximum and mean temperatures. Such variations determined a non-flowering stage in two of the four analysed populations in 2014/2015 and significant differences of further five reproductive traits among cycles. These results confirmed that in current unstable climatic conditions, which are particularly evident in seasonal climates, reproductive success can be a sensitive and easily observable indicator of climatic anomalies. Considering the importance of this issue and the ease and cost-effectiveness of reproductive success monitoring, we argue that research in this sense can be a supporting tool for the enhancement of future crucial targets such as biodiversity conservation and the mitigation of global warming effects.

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

PubMed

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

2017-11-01

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

Detecting sulphate aerosol geoengineering with different methods

DOE PAGES

Lo, Y. T. Eunice; Charlton-Perez, Andrew J.; Lott, Fraser C.; ...

2016-12-15

Sulphate aerosol injection has been widely discussed as a possible way to engineer future climate. Monitoring it would require detecting its effects amidst internal variability and in the presence of other external forcings. Here, we investigate how the use of different detection methods and filtering techniques affects the detectability of sulphate aerosol geoengineering in annual-mean global-mean near-surface air temperature. This is done by assuming a future scenario that injects 5 Tg yr -1 of sulphur dioxide into the stratosphere and cross-comparing simulations from 5 climate models. 64% of the studied comparisons would require 25 years or more for detection whenmore » no filter and the multi-variate method that has been extensively used for attributing climate change are used, while 66% of the same comparisons would require fewer than 10 years for detection using a trend-based filter. This then highlights the high sensitivity of sulphate aerosol geoengineering detectability to the choice of filter. With the same trend-based filter but a non-stationary method, 80% of the comparisons would require fewer than 10 years for detection. This does not imply sulphate aerosol geoengineering should be deployed, but suggests that both detection methods could be used for monitoring geoengineering in global, annual mean temperature should it be needed.« less

Synoptic meteorological modes of variability for fine particulate matter (PM2.5) air quality in major metropolitan regions of China

NASA Astrophysics Data System (ADS)

Leung, Danny M.; Tai, Amos P. K.; Mickley, Loretta J.; Moch, Jonathan M.; van Donkelaar, Aaron; Shen, Lu; Martin, Randall V.

2018-05-01

In his study, we use a combination of multivariate statistical methods to understand the relationships of PM2.5 with local meteorology and synoptic weather patterns in different regions of China across various timescales. Using June 2014 to May 2017 daily total PM2.5 observations from ˜ 1500 monitors, all deseasonalized and detrended to focus on synoptic-scale variations, we find strong correlations of daily PM2.5 with all selected meteorological variables (e.g., positive correlation with temperature but negative correlation with sea-level pressure throughout China; positive and negative correlation with relative humidity in northern and southern China, respectively). The spatial patterns suggest that the apparent correlations with individual meteorological variables may arise from common association with synoptic systems. Based on a principal component analysis of 1998-2017 meteorological data to diagnose distinct meteorological modes that dominate synoptic weather in four major regions of China, we find strong correlations of PM2.5 with several synoptic modes that explain 10 to 40 % of daily PM2.5 variability. These modes include monsoonal flows and cold frontal passages in northern and central China associated with the Siberian High, onshore flows in eastern China, and frontal rainstorms in southern China. Using the Beijing-Tianjin-Hebei (BTH) region as a case study, we further find strong interannual correlations of regionally averaged satellite-derived annual mean PM2.5 with annual mean relative humidity (RH; positive) and springtime fluctuation frequency of the Siberian High (negative). We apply the resulting PM2.5-to-climate sensitivities to the Intergovernmental Panel on Climate Change (IPCC) Coupled Model Intercomparison Project Phase 5 (CMIP5) climate projections to predict future PM2.5 by the 2050s due to climate change, and find a modest decrease of ˜ 0.5 µg m-3 in annual mean PM2.5 in the BTH region due to more frequent cold frontal ventilation under the RCP8.5 future, representing a small climate benefit, but the RH-induced PM2.5 change is inconclusive due to the large inter-model differences in RH projections.

On climate prediction: how much can we expect from climate memory?

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Huang, Yan; Duan, Jianping; Zhu, Congwen; Xoplaki, Elena; Luterbacher, Jürg

2018-03-01

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part ɛ (t) , climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20% ) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part ɛ (t) , which is an important quantity that determines climate predictive skills.

Providing more informative projections of climate change impact on plant distribution in a mountain environment

NASA Astrophysics Data System (ADS)

Randin, C.; Engler, R.; Pearman, P.; Vittoz, P.; Guisan, A.

2007-12-01

Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In this study, we developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, we assessed the effect of scale on predictor variables and geographic projections of SDM. We also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, we used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, we showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe B1 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the warmer conditions as far as competition is low However, in subalpine grasslands, competition of already present species is probably important and limit establishment of newly arrived species. Results from future simulations also showed that heavy extinctions of alpine plants may start already in 2040, but the latest in 2080. Our study also highlighted the importance of fine scale and regional assessments of climate change impact on mountain vegetation, using more direct predictor variables. Indeed, predictions at the continental scale may fail to predict local refugees or local extinctions, as well as loss of connectivity between local populations. On the other hand, migrations of low-elevation species to higher altitude may be difficult to predict at the local scale.

Climate extremes in the Pacific: improving seasonal prediction of tropical cyclones and extreme ocean temperatures to improve resilience

NASA Astrophysics Data System (ADS)

Kuleshov, Y.; Jones, D.; Spillman, C. M.

2012-04-01

Climate change and climate extremes have a major impact on Australia and Pacific Island countries. Of particular concern are tropical cyclones and extreme ocean temperatures, the first being the most destructive events for terrestrial systems, while the latter has the potential to devastate ocean ecosystems through coral bleaching. As a practical response to climate change, under the Pacific-Australia Climate Change Science and Adaptation Planning program (PACCSAP), we are developing enhanced web-based information tools for providing seasonal forecasts for climatic extremes in the Western Pacific. Tropical cyclones are the most destructive weather systems that impact on coastal areas. Interannual variability in the intensity and distribution of tropical cyclones is large, and presently greater than any trends that are ascribable to climate change. In the warming environment, predicting tropical cyclone occurrence based on historical relationships, with predictors such as sea surface temperatures (SSTs) now frequently lying outside of the range of past variability meaning that it is not possible to find historical analogues for the seasonal conditions often faced by Pacific countries. Elevated SSTs are the primary trigger for mass coral bleaching events, which can lead to widespread damage and mortality on reef systems. Degraded coral reefs present many problems, including long-term loss of tourism and potential loss or degradation of fisheries. The monitoring and prediction of thermal stress events enables the support of a range of adaptive and management activities that could improve reef resilience to extreme conditions. Using the climate model POAMA (Predictive Ocean-Atmosphere Model for Australia), we aim to improve accuracy of seasonal forecasts of tropical cyclone activity and extreme SSTs for the regions of Western Pacific. Improved knowledge of extreme climatic events, with the assistance of tailored forecast tools, will help enhance the resilience and adaptive capacity of Australia and Pacific Island Countries under climate change. Acknowledgement The research discussed in this paper was conducted with the support of the PACCSAP supported by the AusAID and Department of Climate Change and Energy Efficiency and delivered by the Bureau of Meteorology and CSIRO.

Assessing climate impacts

PubMed Central

Wohl, Ellen E.; Pulwarty, Roger S.; Zhang, Jian Yun

2000-01-01

Assessing climate impacts involves identifying sources and characteristics of climate variability, and mitigating potential negative impacts of that variability. Associated research focuses on climate driving mechanisms, biosphere–hydrosphere responses and mediation, and human responses. Examples of climate impacts come from 1998 flooding in the Yangtze River Basin and hurricanes in the Caribbean and Central America. Although we have limited understanding of the fundamental driving-response interactions associated with climate variability, increasingly powerful measurement and modeling techniques make assessing climate impacts a rapidly developing frontier of science. PMID:11027321

A mineralogical record of ocean change: Decadal and centennial patterns in the California mussel.

PubMed

McCoy, Sophie J; Kamenos, Nicholas A; Chung, Peter; Wootton, Timothy J; Pfister, Catherine A

2018-06-01

Ocean acidification, a product of increasing atmospheric carbon dioxide, may already have affected calcified organisms in the coastal zone, such as bivalves and other shellfish. Understanding species' responses to climate change requires the context of long-term dynamics. This can be particularly difficult given the longevity of many important species in contrast with the relatively rapid onset of environmental changes. Here, we present a unique archival dataset of mussel shells from a locale with recent environmental monitoring and historical climate reconstructions. We compare shell structure and composition in modern mussels, mussels from the 1970s, and mussel shells dating back to 1000-2420 years BP. Shell mineralogy has changed dramatically over the past 15 years, despite evidence for consistent mineral structure in the California mussel, Mytilus californianus, over the prior 2500 years. We present evidence for increased disorder in the calcium carbonate shells of mussels and greater variability between individuals. These changes in the last decade contrast markedly from a background of consistent shell mineralogy for centuries. Our results use an archival record of natural specimens to provide centennial-scale context for altered minerology and variability in shell features as a response to acidification stress and illustrate the utility of long-term studies and archival records in global change ecology. Increased variability between individuals is an emerging pattern in climate change responses, which may equally expose the vulnerability of organisms and the potential of populations for resilience. © 2017 John Wiley & Sons Ltd.

Capturing temporal and spatial variability in the chemistry of shallow permafrost ponds

NASA Astrophysics Data System (ADS)

Morison, Matthew Q.; Macrae, Merrin L.; Petrone, Richard M.; Fishback, LeeAnn

2017-12-01

Across the circumpolar north, the fate of small freshwater ponds and lakes (< 1 km2) has been the subject of scientific interest due to their ubiquity in the landscape, capacity to exchange carbon and energy with the atmosphere, and their potential to inform researchers about past climates through sediment records. A changing climate has implications for the capacity of ponds and lakes to support organisms and store carbon, which in turn has important feedbacks to climate change. Thus, an improved understanding of pond biogeochemistry is needed. To characterize spatial and temporal patterns in water column chemistry, a suite of tundra ponds were examined to answer the following research questions: (1) does temporal variability exceed spatial variability? (2) If temporal variability exists, do all ponds (or groups of ponds) behave in a similar temporal pattern, linked to seasonal hydrologic drivers or precipitation events? Six shallow ponds located in the Hudson Bay Lowlands region were monitored between May and October 2015 (inclusive, spanning the entire open-water period). The ponds span a range of biophysical conditions including pond area, perimeter, depth, and shoreline development. Water samples were collected regularly, both bimonthly over the ice-free season and intensively during and following a large summer storm event. Samples were analysed for nitrogen speciation (NO3-, NH4+, dissolved organic nitrogen) and major ions (Cl-, SO42-, K+, Ca2+, Mg2+, Na+). Across all ponds, temporal variability (across the season and within a single rain event) exceeded spatial variability (variation among ponds) in concentrations of several major species (Cl-, SO42-, K+, Ca2+, Na+). Evapoconcentration and dilution of pond water with precipitation and runoff inputs were the dominant processes influencing a set of chemical species which are hydrologically driven (Cl-, Na+, K+, Mg2+, dissolved organic nitrogen), whereas the dissolved inorganic nitrogen species were likely mediated by processes within ponds. This work demonstrates the importance of understanding hydrologically driven chemodynamics in permafrost ponds on multiple scales (seasonal and event scale).

Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

NASA Astrophysics Data System (ADS)

Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.

2009-04-01

The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional investigations in this region of the planet. Reported is an overview of some risk consequences of Climate/Global Change for Siberia environment as follows from results of current scientific activity in climate monitoring and modelling. At present, the challenge facing the weather and climate scientists is to improve the prediction of interactions between weather/climate and Earth system. Taking into account significantly increased computing capacity, a special attention in the report is paid to perspectives of the Earth system modelling.

El Niño, Climate, and Cholera Associations in Piura, Peru, 1991-2001: A Wavelet Analysis.

PubMed

Ramírez, Iván J; Grady, Sue C

2016-03-01

In Peru, it was hypothesized that epidemic cholera in 1991 was linked to El Niño, the warm phase of El Niño-Southern Oscillation. While previous studies demonstrated an association in 1997-1998, using cross-sectional data, they did not assess the consistency of this relationship across the decade. Thus, how strong or variable an El Niño-cholera relationship was in Peru or whether El Niño triggered epidemic cholera early in the decade remains unknown. In this study, wavelet and mediation analyses were used to characterize temporal patterns among El Niño, local climate variables (rainfall, river discharge, and air temperature), and cholera incidence in Piura, Peru from 1991 to 2001 and to estimate the mediating effects of local climate on El Niño-cholera relationships. The study hypothesis is that El Niño-related connections with cholera in Piura were transient and interconnected via local climate pathways. Overall, our findings provide evidence that a strong El Niño-cholera link, mediated by local hydrology, existed in the latter part of the 1990s but found no evidence of an El Niño association in the earlier part of the decade, suggesting that El Niño may not have precipitated cholera emergence in Piura. Further examinations of cholera epicenters in Peru are recommended to support these results in Piura. For public health planning, the results may improve existing efforts that utilize El Niño monitoring for preparedness during future climate-related extremes in the region.

Effect of Climatic Factors on Hand, Foot, and Mouth Disease in South Korea, 2010-2013.

PubMed

Kim, Bryan Inho; Ki, Hyunok; Park, Sunhee; Cho, Eunhi; Chun, Byung Chul

2016-01-01

Hand, foot, and mouth disease (HFMD) causes characteristic blisters and sores mainly in infants and children, and has been monitored in South Korea through sentinel surveillance since 2009. We described the patterns of HFMD occurrence and analyzed the effect of climatic factors on national HFMD incidence. Weekly clinically diagnosed HFMD case rates (per 1,000 outpatients) in sentinel sites and weekly climatic factors, such as average temperature, relative humidity, duration of sunshine, precipitation, and wind speed from 2010 to 2013, were used in this study. A generalized additive model with smoothing splines and climatic variables with time lags of up to 2 weeks were considered in the modeling process. To account for long-term trends and seasonality, we controlled for each year and their corresponding weeks. The autocorrelation issue was also adjusted by using autocorrelation variables. At an average temperature below 18°C, the HFMD rate increased by 10.3% for every 1°C rise in average temperature (95% confidence interval (CI): 8.4, 12.3%). We also saw a 6.6% increase in HFMD rate (95% CI: 3.6, 9.7%) with every 1% increase in relative humidity under 65%, with a 1.5% decrease in HFMD rate observed (95% CI: 0.4, 2.7%) with each 1% humidity increase above 65%. Modeling results have shown that average temperature and relative humidity are related to HFMD rate. Additional research on the environmental risk factors of HFMD transmission is required to understand the underlying mechanism between climatic factors and HFMD incidence.

Observing climate change trends in ocean biogeochemistry: when and where.

PubMed

Henson, Stephanie A; Beaulieu, Claudie; Lampitt, Richard

2016-04-01

Understanding the influence of anthropogenic forcing on the marine biosphere is a high priority. Climate change-driven trends need to be accurately assessed and detected in a timely manner. As part of the effort towards detection of long-term trends, a network of ocean observatories and time series stations provide high quality data for a number of key parameters, such as pH, oxygen concentration or primary production (PP). Here, we use an ensemble of global coupled climate models to assess the temporal and spatial scales over which observations of eight biogeochemically relevant variables must be made to robustly detect a long-term trend. We find that, as a global average, continuous time series are required for between 14 (pH) and 32 (PP) years to distinguish a climate change trend from natural variability. Regional differences are extensive, with low latitudes and the Arctic generally needing shorter time series (<~30 years) to detect trends than other areas. In addition, we quantify the 'footprint' of existing and planned time series stations, that is the area over which a station is representative of a broader region. Footprints are generally largest for pH and sea surface temperature, but nevertheless the existing network of observatories only represents 9-15% of the global ocean surface. Our results present a quantitative framework for assessing the adequacy of current and future ocean observing networks for detection and monitoring of climate change-driven responses in the marine ecosystem. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Solar Variability in the Context of Other Climate Forcing Mechanisms

NASA Technical Reports Server (NTRS)

Hansen, James E.

1999-01-01

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

Extracting Forest Canopy Characteristics from Remote Sensing Imagery: Implications for Sentinel-2 Mission

NASA Astrophysics Data System (ADS)

Gholizadeh, Asa; Kopaekova, Veronika; Rogass, Christian; Mielke, Christian; Misurec, Jan

2016-08-01

Systematic quantification and monitoring of forest biophysical and biochemical variables is required to assess the response of ecosystems to climate change. Remote sensing has been introduced as a time and cost- efficient way to carry out large scale monitoring of vegetation parameters. Red-Edge Position (REP) is a hyperspectrally detectable parameter which is sensitive to vegetation Chl. In the current study, REP was modelled for the Norway spruce forest canopy resampled to HyMap and Sentinel-2 spectral resolution as well as calculated from the real HyMap and Sentinel-2 simulated data. Different REP extraction methods (4PLI, PF, LE, 4PLIH and 4PLIS) were assessed. The study showed the way for effective utilization of the forthcoming hyper and superspectral remote sensing sensors from orbit to monitor vegetation attributes.

Spatial observation and monitoring of the effects of the "New Climate" Warming on Morocco: Situation of the recent urban floods

NASA Astrophysics Data System (ADS)

Karrouk, M. S.

2017-12-01

Since the nineties of the last century, climatological research following a great scientific advance in the field of prediction, not the variability and evolution of the different climatic parameters was beginning to be clearer!But today, since the beginning of 2005, certainly due to oceanic thermal cumulations, and the shift of climatic zones towards poles in selective forms (more intense on the oceans present on the continents); Climatic events do not evolve according to the usual and expected rhythms: atmospheric circulation, precipitation, temperatures, seasonal phenomena, etc. These conditions are a spatiotemporal evolution and distribution, which characterize the new "global climate", by the new atmospheric regime imposing the Meridian Atmospheric Circulation (MAC), alternating the conditions of Freshness (humidity) and Heat (drought) along the year.In this new situation, Morocco, located in the climate transition zone, is fully affected by the "New Climate". Usually, the atmospheric response to major climatic events (ENSO) in this region such as "El Niño" was characterized by the establishment of the NAO positive index, stability and drought, due to dominance Zonal Atmospheric Circulation in winter. On the other hand, in the "La Niña" episode, the negative index of the NAO and the predominant Meridian Atmospheric Circulation and precipitation became abundant.Since the beginning of this century, qualified meteorological events of "exceptional !" causing floods have continued to occur in Morocco and elsewhere, with increasing recurrence, prompting us to wonder about the "new" mode of hydro-thermal function of the climate system that induces torrential rains, as well as its effect on environments and societies.The latest event is the flood disaster in October 2016 in the Laâyoune region of southern Morocco, which specializes in the unusual return of rain in a region considered dry and Saharan.Thanks to spatial observation and monitoring of meteorological conditions over the last 15 years, these types of alternating Heat / Cold conditions have become predictable, enabling decision-makers today to prepare adequately for the management of related risks to the "New Climate" warmed.

Evidence of recent climate change within the historic range of Rio Grande cutthroat trout: implications for management and future persistence

USGS Publications Warehouse

Zeigler, Matthew P.; Todd, Andrew S.; Caldwell, Colleen A.

2012-01-01

Evidence of anthropogenically influenced climate change has motivated natural resource managers to incorporate adaptive measures to minimize risks to sensitive and threatened species. Detecting trends in climate variables (i.e., air temperature and hydrology) can serve as a valuable management tool for protecting vulnerable species by increasing our understanding of localized conditions and trends. The Rio Grande cutthroat trout Oncorhynchus clarkii virginalis has suffered a severe decline in its historical distribution, with the majority of current populations persisting in isolated headwater streams. To evaluate recent climate change within the subspecies' historical range, we examined trends in average air temperatures, biologically important hydrological variables (timing of snowmelt and seasonal flows), and the April 1 snow water equivalent over the last 45 years (1963–2007). While rates of change in all three metrics were variable across sites, rangewide patterns were evident. Across the subspecies' historical range, average annual air temperatures increased (0.29°C per decade) and the timing of snowmelt shifted 10.6 d earlier in the year (2.3 d/decade). Flows increased during biologically important periods, including winter (January 1–March 31; 6.6% increase per decade), prespawning (April 1–May 14; 6.9% increase per decade), and spawning (May 15–June 15; 4.2% increase per decade) and decreased in summer (June 16–September 15; 1.9% decrease per decade). Evidence of decreasing April 1 snow water equivalent (5.3% per decade) was also observed. While the impacts of these changes at the population level are equivocal, it is likely that negative effects would influence the subspecies by altering its distribution, decreasing available habitat, and altering the timing of important life history components. Continued monitoring and proactive management will be required to increase the resiliency of remaining populations to ensure long-term persistence and protection in a changing climate.

On the brink of change: plant responses to climate on the Colorado Plateau

USGS Publications Warehouse

Munson, Seth M.; Belnap, Jayne; Schelz, Charles D.; Moran, Mary; Carolin, Tara W.

2011-01-01

The intensification of aridity due to anthropogenic climate change in the southwestern U.S. is likely to have a large impact on the growth and survival of plant species that may already be vulnerable to water stress. To make accurate predictions of plant responses to climate change, it is essential to determine the long-term dynamics of plant species associated with past climate conditions. Here we show how the plant species and functional types across a wide range of environmental conditions in Colorado Plateau national parks have changed with climate variability over the last twenty years. During this time, regional mean annual temperature increased by 0.18°C per year from 1989–1995, 0.06°C per year from 1995–2003, declined by 0.14°C from 2003–2008, and there was high interannual variability in precipitation. Non-metric multidimensional scaling of plant species at long-term monitoring sites indicated five distinct plant communities. In many of the communities, canopy cover of perennial plants was sensitive to mean annual temperature occurring in the previous year, whereas canopy cover of annual plants responded to cool season precipitation. In the perennial grasslands, there was an overall decline of C3 perennial grasses, no change of C4 perennial grasses, and an increase of shrubs with increasing temperature. In the shrublands, shrubs generally showed no change or slightly increased with increasing temperature. However, certain shrub species declined where soil and physical characteristics of a site limited water availability. In the higher elevation woodlands, Juniperus osteosperma and shrub canopy cover increased with increasing temperature, while Pinus edulis at the highest elevation sites was unresponsive to interannual temperature variability. These results from well-protected national parks highlight the importance of temperature to plant responses in a water-limited region and suggest that projected increases in aridity are likely to promote grass loss and shrub expansion on the Colorado Plateau.

Evaluating meteorological data from weather stations, and from satellites and global models for a multi-site epidemiological study.

PubMed

Colston, Josh M; Ahmed, Tahmeed; Mahopo, Cloupas; Kang, Gagandeep; Kosek, Margaret; de Sousa Junior, Francisco; Shrestha, Prakash Sunder; Svensen, Erling; Turab, Ali; Zaitchik, Benjamin

2018-04-21

Longitudinal and time series analyses are needed to characterize the associations between hydrometeorological parameters and health outcomes. Earth Observation (EO) climate data products derived from satellites and global model-based reanalysis have the potential to be used as surrogates in situations and locations where weather-station based observations are inadequate or incomplete. However, these products often lack direct evaluation at specific sites of epidemiological interest. Standard evaluation metrics of correlation, agreement, bias and error were applied to a set of ten hydrometeorological variables extracted from two quasi-global, commonly used climate data products - the Global Land Data Assimilation System (GLDAS) and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) - to evaluate their performance relative to weather-station derived estimates at the specific geographic locations of the eight sites in a multi-site cohort study. These metrics were calculated for both daily estimates and 7-day averages and for a rotavirus-peak-season subset. Then the variables from the two sources were each used as predictors in longitudinal regression models to test their association with rotavirus infection in the cohort after adjusting for covariates. The availability and completeness of station-based validation data varied depending on the variable and study site. The performance of the two gridded climate models varied considerably within the same location and for the same variable across locations, according to different evaluation criteria and for the peak-season compared to the full dataset in ways that showed no obvious pattern. They also differed in the statistical significance of their association with the rotavirus outcome. For some variables, the station-based records showed a strong association while the EO-derived estimates showed none, while for others, the opposite was true. Researchers wishing to utilize publicly available climate data - whether EO-derived or station based - are advised to recognize their specific limitations both in the analysis and the interpretation of the results. Epidemiologists engaged in prospective research into environmentally driven diseases should install their own weather monitoring stations at their study sites whenever possible, in order to circumvent the constraints of choosing between distant or incomplete station data or unverified EO estimates. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Flexible stocking as a strategy for enhancing ranch profitability in the face of a changing and variable climate

USDA-ARS?s Scientific Manuscript database

Predicted climate change impacts include increased weather variability and increased occurrences of extreme events such as drought. Such climate changes potentially affect cattle performance as well as pasture and range productivity. These climate induced risks are often coupled with variable market...

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

Climate variability is often studied in terms of fluctuations with respect to the mean state, whereas the dependence between the mean and variability is rarely discussed. We propose a new climate metric to measure the relationship between means and standard deviations of annual surface temperature computed over non-overlapping 100-year segments. This metric is analyzed based on equilibrium simulations of the Max Planck Institute-Earth System Model (MPI-ESM): the last millennium climate (800-1799), the future climate projection following the A1B scenario (2100-2199), and the 3100-year unforced control simulation. A linear relationship is globally observed in the control simulation and thus termed intrinsic climate variability, which is most pronounced in the tropical region with negative regression slopes over the Pacific warm pool and positive slopes in the eastern tropical Pacific. It relates to asymmetric changes in temperature extremes and associates fluctuating climate means with increase or decrease in intensity and occurrence of both El Niño and La Niña events. In the future scenario period, the linear regression slopes largely retain their spatial structure with appreciable changes in intensity and geographical locations. Since intrinsic climate variability describes the internal rhythm of the climate system, it may serve as guidance for interpreting climate variability and climate change signals in the past and the future.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Putting Citizen-Collected Observations to Work -- The Community Collaborative Rain, Hail and Snow Network (CoCoRaHS)

NASA Astrophysics Data System (ADS)

Doesken, N.

2015-12-01

When CoCoRaHS was born (1998), climate-relevant information was far from our minds. We were simply enlisting volunteers to help capture, display and communicate the nature of small scale variability within northern Colorado storms. Climate change was talked about then, but not with the sense of concern and urgency as today. Now, many years later, the simple back-yard precipitation measurements being taken by thousands of volunteers across much of North America are creating valuable and easily-accessible data and information serving many and varied purposes from federal and state climate monitoring to drought and extreme storm analysis and research. Many volunteers have been with the project now for a decade or longer and have contributed literally thousands of individual observations and reports. Long-time participants along with recent recruits of all ages are seeing first-hand how day by day observations of weather conditions combine - over time and space -- to define and describe key elements of our climate and its variations. The fact that the data from volunteers are frequently used and applied by scientists and decision makers is one of the key factors in retaining long-term volunteers. Examples will be presented of volunteer precipitation data being used both independently and in combination with data from federal monitoring systems. Challenges of maintaining a large volunteer network will be discussed along with some plans and opportunities for the future.

Soil-plant interaction monitoring: Small scale example of an apple orchard in Trentino, North-Eastern Italy.

PubMed

Cassiani, Giorgio; Boaga, Jacopo; Rossi, Matteo; Putti, Mario; Fadda, Giuseppe; Majone, Bruno; Bellin, Alberto

2016-02-01

Accurate monitoring and modeling of soil-plant systems are a key unresolved issue that currently limits the development of a comprehensive view of the interactions between soil and atmosphere, with a number of practical consequences including the difficulties in predicting climatic change patterns. This paper presents a case study where time-lapse minimal-invasive 3D micro-electrical tomography (ERT) is used to monitor rhizosphere eco-hydrological processes in an apple orchard in the Trentino region, Northern Italy. In particular we aimed at gaining a better understanding of the soil-vegetation water exchanges in the shallow critical zone, as part of a coordinated effort towards predicting climate-induced changes on the hydrology of Mediterranean basins (EU FP7 CLIMB project). The adopted strategy relied upon the installation of a 3D electrical tomography apparatus consisting of four mini-boreholes carrying 12 electrodes each plus 24 mini-electrodes on the ground surface, arranged in order to image roughly a cubic meter of soil surrounding a single apple tree. The monitoring program was initially tested with repeated measurements over about one year. Subsequently, we performed three controlled irrigation tests under different conditions, in order to evaluate the water redistribution under variable root activities and climatic conditions. Laboratory calibration on soil samples allowed us to translate electrical resistivity variations into moisture content changes, supported also by in-situ TDR measurements. Richards equation modeling was used also to explain the monitoring evidence. The results clearly identified the effect of root water uptake and the corresponding subsoil region where active roots are present, but also marked the need to consider the effects of different water salinity in the water infiltration process. We also gained significant insight about the need to measure quantitatively the plant evapotranspiration in order to close the water balance and separate soil structure effects (primarily, hydraulic conductivity) from water dynamics induced by living plants. Copyright © 2015 Elsevier B.V. All rights reserved.

Linking global climate and temperature variability to widespread amphibian declines putatively caused by disease.

PubMed

Rohr, Jason R; Raffel, Thomas R

2010-05-04

The role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial, and the effect of climatic variability, in particular, has largely been ignored. For instance, it was recently revealed that the proposed link between climate change and widespread amphibian declines, putatively caused by the chytrid fungus Batrachochytrium dendrobatidis (Bd), was tenuous because it was based on a temporally confounded correlation. Here we provide temporally unconfounded evidence that global El Niño climatic events drive widespread amphibian losses in genus Atelopus via increased regional temperature variability, which can reduce amphibian defenses against pathogens. Of 26 climate variables tested, only factors associated with temperature variability could account for the spatiotemporal patterns of declines thought to be associated with Bd. Climatic predictors of declines became significant only after controlling for a pattern consistent with epidemic spread (by temporally detrending the data). This presumed spread accounted for 59% of the temporal variation in amphibian losses, whereas El Niño accounted for 59% of the remaining variation. Hence, we could account for 83% of the variation in declines with these two variables alone. Given that global climate change seems to increase temperature variability, extreme climatic events, and the strength of Central Pacific El Niño episodes, climate change might exacerbate worldwide enigmatic declines of amphibians, presumably by increasing susceptibility to disease. These results suggest that changes to temperature variability associated with climate change might be as significant to biodiversity losses and disease emergence as changes to mean temperature.

Active-layer thermal monitoring on the Fildes Peninsula, King George Island, maritime Antarctica

NASA Astrophysics Data System (ADS)

Michel, R. F. M.; Schaefer, C. E. G. R.; Simas, F. M. B.; Francelino, M. R.; Fernandes-Filho, E. I.; Lyra, G. B.; Bockheim, J. G.

2014-12-01

International attention to climate change phenomena has grown in the last decade; the active layer and permafrost are of great importance in understanding processes and future trends due to their role in energy flux regulation. The objective of this paper is to present active-layer temperature data for one Circumpolar Active Layer Monitoring South hemisphere (CALM-S) site located on the Fildes Peninsula, King George Island, maritime Antarctica over an 57-month period (2008-2012). The monitoring site was installed during the summer of 2008 and consists of thermistors (accuracy of ±0.2 °C), arranged vertically with probes at different depths, recording data at hourly intervals in a high-capacity data logger. A series of statistical analyses was performed to describe the soil temperature time series, including a linear fit in order to identify global trends, and a series of autoregressive integrated moving average (ARIMA) models was tested in order to define the best fit for the data. The affects of weather on the thermal regime of the active layer have been identified, providing insights into the influence of climate change on permafrost. The active-layer thermal regime in the studied period was typical of periglacial environments, with extreme variation in surface during the summer resulting in frequent freeze and thaw cycles. The active-layer thickness (ALT) over the studied period shows a degree of variability related to different annual weather conditions, reaching a maximum of 117.5 cm in 2009. The ARIMA model could describe the data adequately and is an important tool for more conclusive analysis and predictions when longer data sets are available. Despite the variability when comparing temperature readings and ACT over the studied period, no trend can be identified.

Effects of short-term variability of meteorological variables on soil temperature in permafrost regions

NASA Astrophysics Data System (ADS)

Beer, Christian; Porada, Philipp; Ekici, Altug; Brakebusch, Matthias

2018-03-01

Effects of the short-term temporal variability of meteorological variables on soil temperature in northern high-latitude regions have been investigated. For this, a process-oriented land surface model has been driven using an artificially manipulated climate dataset. Short-term climate variability mainly impacts snow depth, and the thermal diffusivity of lichens and bryophytes. These impacts of climate variability on insulating surface layers together substantially alter the heat exchange between atmosphere and soil. As a result, soil temperature is 0.1 to 0.8 °C higher when climate variability is reduced. Earth system models project warming of the Arctic region but also increasing variability of meteorological variables and more often extreme meteorological events. Therefore, our results show that projected future increases in permafrost temperature and active-layer thickness in response to climate change will be lower (i) when taking into account future changes in short-term variability of meteorological variables and (ii) when representing dynamic snow and lichen and bryophyte functions in land surface models.

Using mid-altitude regions as observatories of change in snow areas: the Natural Park of Cazorla, Segura y las Villas (South Spain) as study case for early snow regression.

NASA Astrophysics Data System (ADS)

Montilla, Soledad; Pimentel, Rafael; José Pérez-Palazón, María; Aguillar, Cristina; José Polo, María

2017-04-01

Snow plays a key role at the hydrological cycle in semiarid mountainous areas, modifying the energy and water balances that govern the regime of stored water in the snowpack, a key resource for the spring and summer river flow. The Natural and National Park of Sierra Nevada (SNNP), a coastal mountain range up to 3450 m a.s.l. in southern Spain, is a representative example of snow areas in Mediterranean-climate regions; its high altitudinal gradient results in a wide variety of eco-climatic environments, and it is part of the global monitoring network to study climate change. Both monitoring and modelling efforts have been performed to assess this variability and its significant scales; whereas increasing temperature trends have been found, no significant trends are observed so far regarding the precipitation regime both on a seasonal and annual basis, with a highly variable impact on the snow regime in this area, especially in the mid-altitude range. In this context, the study of the snow cover in the neighbouring Natural Park of Cazorla, Segura and Las Villas (CSLVNP), with similar climatic conditions but lower altitudes (up to 2107 m a.s.l.) is proposed as a parallel monitoring site for early warning of impacts of climate change on the snow regime. The CSLVNP is the most extensive protected area in Spain and it is located to the north of SNPN, with less influence of the Mediterranean Sea. This study carried out a first quantification of the snow importance in this area, which exhibits a large transitional zone with a dominant alpine environment, and its relationship with the observed local precipitation-temperature trends. For this, the snow cover fraction on a 30x30 m gridded resolution has been studied during a 5-yr period combining on-site meteorological observations and remote-sensing data analysis, and snow modelling by the distributed and physically based approach for Mediterranean regions proposed by Herrero et al. (2009; 2010). The analysis of the available series of satellite images Landsat 8 OLI/TIRS, Landsat 7 ETM+ and Landsat 4-5 TM were used to obtain snow cover fraction maps with 30x30 m resolution. The study period 2010-2015 was simulated with the distributed snow model and the results were compared against these snow map series. Additionally, the annual and seasonal trends of precipitation, mean daily temperature and global radiation were obtained from the available local data sets. Globally, the simulated results overestimate the snow presence in the study area, very likely due to the estimation of snowfall. However, on a local scale, the model performance improves in the region between 1750 and 2250 m altitude. On the other hand, those zones at lower altitudes, which are a transition of the clearly alpine environment above, present a high variability of results related to the spatial patterns of precipitation, temperature and radiation. Regarding the precipitation-temperature regime, an increasing 0.05 °/yr over the last 30 years (1970-2010) was found, but no significant conclusion can be achieved on precipitation trends. This is also observed in the SNNP, which confirms the potential representativeness of PNCSV as an early warning site. Further work is being carried out to improve the snow modelling at this site and generate longer snow cover fraction maps series and other characteristic variables of the snow in this area.

Timing of climate variability and grassland productivity

PubMed Central

Craine, Joseph M.; Nippert, Jesse B.; Elmore, Andrew J.; Skibbe, Adam M.; Hutchinson, Stacy L.; Brunsell, Nathaniel A.

2012-01-01

Future climates are forecast to include greater precipitation variability and more frequent heat waves, but the degree to which the timing of climate variability impacts ecosystems is uncertain. In a temperate, humid grassland, we examined the seasonal impacts of climate variability on 27 y of grass productivity. Drought and high-intensity precipitation reduced grass productivity only during a 110-d period, whereas high temperatures reduced productivity only during 25 d in July. The effects of drought and heat waves declined over the season and had no detectable impact on grass productivity in August. If these patterns are general across ecosystems, predictions of ecosystem response to climate change will have to account not only for the magnitude of climate variability but also for its timing. PMID:22331914

Selection of climate change scenario data for impact modelling.

PubMed

Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg

2012-01-01

Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.

Continuous wind measurement in the tropical Pacific using VHF radars

NASA Technical Reports Server (NTRS)

Balsley, B. B.; Ecklund, W. L.; Carter, D. A.

1986-01-01

Very High Frequency (VHF) Radar Wind Profilers are being installed on Ponape, East Caroline Islands and Christmas Island, Republic of Kiribati to continuously monitor winds aloft. The purpose of this experiment is to study wind fluctuations on time scales between minutes and days, to determine the longitudinal character of these fluctuations, and to examine their relationship to climate variability. Six-hourly wind profiles will be provided via satellite to the scientific community for Project TOGA (Tropical Ocean Global Atmosphere).

Compilation of 1991 Annual Report of the Navy ELF Communications System Ecological Monitoring Program. Volume 1. Tabs A-B

DTIC Science & Technology

1992-08-01

radiation in the understory or soil nutrient status that may be affected by overstory biomass . The initiation and schedule of each phase of the...possible ELF induced changes in the canopy of the hardwood stand. Reduction of foliage biomass or changes in the timing of leaf expansion would alter...of total N and climate related variables. Backaround The conversion of organically bound N to inorganic N (mineralization) describes two distinct

Means and extremes: building variability into community-level climate change experiments.

PubMed

Thompson, Ross M; Beardall, John; Beringer, Jason; Grace, Mike; Sardina, Paula

2013-06-01

Experimental studies assessing climatic effects on ecological communities have typically applied static warming treatments. Although these studies have been informative, they have usually failed to incorporate either current or predicted future, patterns of variability. Future climates are likely to include extreme events which have greater impacts on ecological systems than changes in means alone. Here, we review the studies which have used experiments to assess impacts of temperature on marine, freshwater and terrestrial communities, and classify them into a set of 'generations' based on how they incorporate variability. The majority of studies have failed to incorporate extreme events. In terrestrial ecosystems in particular, experimental treatments have reduced temperature variability, when most climate models predict increased variability. Marine studies have tended to not concentrate on changes in variability, likely in part because the thermal mass of oceans will moderate variation. In freshwaters, climate change experiments have a much shorter history than in the other ecosystems, and have tended to take a relatively simple approach. We propose a new 'generation' of climate change experiments using down-scaled climate models which incorporate predicted changes in climatic variability, and describe a process for generating data which can be applied as experimental climate change treatments. © 2013 John Wiley & Sons Ltd/CNRS.

Exploring Connections between Global Climate Indices and African Vegetation Phenology

NASA Technical Reports Server (NTRS)

Brown, Molly E.; deBeurs, Kirsten; Vrieling, Anton

2009-01-01

Variations in agricultural production due to rainfall and temperature fluctuations are a primary cause of food insecurity on the continent in Africa. Agriculturally destructive droughts and floods are monitored from space using satellite remote sensing by organizations seeking to provide quantitative and predictive information about food security crises. Better knowledge on the relation between climate indices and food production may increase the use of these indices in famine early warning systems and climate outlook forums on the continent. Here we explore the relationship between phenology metrics derived from the 26 year AVHRR NDVI record and the North Atlantic Oscillation index (NAO), the Indian Ocean Dipole (IOD), the Pacific Decadal Oscillation (PDO), the Multivariate ENSO Index (MEI) and the Southern Oscillation Index (SOI). We explore spatial relationships between growing conditions as measured by the NDVI and the five climate indices in Eastern, Western and Southern Africa to determine the regions and periods when they have a significant impact. The focus is to provide a clear indication as to which climate index has the most impact on the three regions during the past quarter century. We found that the start of season and cumulative NDVI were significantly affected by variations in the climate indices. The particular climate index and the timing showing highest correlation depended heavily on the region examined. The research shows that climate indices can contribute to understanding growing season variability in Eastern, Western and Southern Africa.

Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado

USGS Publications Warehouse

Carrollo, Emily M.; Johnson, Heather E.; Fischer, Justin W.; Hammond, Matthew; Dorsey, Patricia D.; Anderson, Charles; Vercauteren, Kurt C.; Walter, W. David

2017-01-01

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Influence of Precipitation and Crop Germination on Resource Selection by Mule Deer (Odocoileus hemionus) in Southwest Colorado.

PubMed

Carrollo, Emily M; Johnson, Heather E; Fischer, Justin W; Hammond, Matthew; Dorsey, Patricia D; Anderson, Charles; Vercauteren, Kurt C; Walter, W David

2017-11-09

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km 2 , and for two summer seasons that ranged between 5.51 and 6.24 km 2 . Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Monthly Sea Surface Salinity and Freshwater Flux Monitoring

NASA Astrophysics Data System (ADS)

Ren, L.; Xie, P.; Wu, S.

2017-12-01

Taking advantages of the complementary nature of the Sea Surface Salinity (SSS) measurements from the in-situ (CTDs, shipboard, Argo floats, etc.) and satellite retrievals from Soil Moisture Ocean Salinity (SMOS) satellite of the European Space Agency (ESA), the Aquarius of a joint venture between US and Argentina, and the Soil Moisture Active Passive (SMAP) of national Aeronautics and Space Administration (NASA), a technique is developed at NOAA/NCEP/CPC to construct an analysis of monthly SSS, called the NOAA Blended Analysis of Sea-Surface Salinity (BASS). The algorithm is a two-steps approach, i.e. to remove the bias in the satellite data through Probability Density Function (PDF) matching against co-located in situ measurements; and then to combine the bias-corrected satellite data with the in situ measurements through the Optimal Interpolation (OI) method. The BASS SSS product is on a 1° by 1° grid over the global ocean for a 7-year period from 2010. Combined with the NOAA/NCEP/CPC CMORPH satellite precipitation (P) estimates and the Climate Forecast System Reanalysis (CFSR) evaporation (E) fields, a suite of monthly package of the SSS and oceanic freshwater flux (E and P) was developed to monitor the global oceanic water cycle and SSS on a monthly basis. The SSS in BASS product is a suite of long-term SSS and fresh water flux data sets with temporal homogeneity and inter-component consistency better suited for the examination of the long-term changes and monitoring. It presents complete spatial coverage and improved resolution and accuracy, which facilitates the diagnostic analysis of the relationship and co-variability among SSS, freshwater flux, mixed layer processes, oceanic circulation, and assimilation of SSS into global models. At the AGU meeting, we will provide more details on the CPC salinity and fresh water flux data package and its applications in the monitoring and analysis of SSS variations in association with the ENSO and other major climate variability in recent years.

Simulating dissolved organic carbon dynamics at the swedish integrated monitoring sites with the integrated catchments model for carbon, INCA-C.

PubMed

Futter, M N; Löfgren, S; Köhler, S J; Lundin, L; Moldan, F; Bringmark, L

2011-12-01

Surface water concentrations of dissolved organic carbon ([DOC]) are changing throughout the northern hemisphere due to changes in climate, land use and acid deposition. However, the relative importance of these drivers is unclear. Here, we use the Integrated Catchments model for Carbon (INCA-C) to simulate long-term (1996-2008) streamwater [DOC] at the four Swedish integrated monitoring (IM) sites. These are unmanaged headwater catchments with old-growth forests and no major changes in land use. Daily, seasonal and long-term variations in streamwater [DOC] driven by runoff, seasonal temperature and atmospheric sulfate (SO₄(2-)) deposition were observed at all sites. Using INCA-C, it was possible to reproduce observed patterns of variability in streamwater [DOC] at the four IM sites. Runoff was found to be the main short-term control on [DOC]. Seasonal patterns in [DOC] were controlled primarily by soil temperature. Measured SO₄(2-) deposition explained some of the long-term [DOC] variability at all sites.

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

NASA Astrophysics Data System (ADS)

Forsythe, N.; Blenkinsop, S.; Fowler, H. J.

2015-05-01

A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

Intra-event variability of Escherichia coli and total suspended solids in urban stormwater runoff.

PubMed

McCarthy, D T; Hathaway, J M; Hunt, W F; Deletic, A

2012-12-15

Sediment levels are important for environmental health risk assessments of surface water bodies, while faecal pollution can introduce significant public health risks for users of these systems. Urban stormwater is one of the largest sources of contaminants to surface waters, yet the fate and transport of these contaminants (especially those microbiological) have received little attention in the literature. Stormwater runoff from five urbanized catchments were monitored for pathogen indicator bacteria and total suspended solids in two developed countries. Multiple discrete samples were collected during each storm event, allowing an analysis of intra-event characteristics such as initial concentration, peak concentration, maximum rate of change, and relative confidence interval. The data suggest that a catchment's area influences pollutant characteristics, as larger catchments have more complex stormwater infrastructure and more variable pollutant sources. The variability of total suspended solids for many characteristics was similar to Escherichia coli, indicating that the variability of E. coli may not be substantially higher than that of other pollutants as initially speculated. Further, variations in E. coli appeared to be more commonly correlated to antecedent climate, while total suspended solids were more highly correlated to rainfall/runoff characteristics. This emphasizes the importance of climate on microbial persistence and die off in urban systems. Discrete intra-event concentrations of total suspended solids and, to a lesser extent E. coli, were correlated to flow, velocity, and rainfall intensity (adjusted by time of concentrations). Concentration changes were found to be best described by adjusted rainfall intensity, as shown by other researchers. This study has resulted in an increased understanding of the magnitude of intra-event variations of total suspended solids and E. coli and what physical and climatic parameters influence these variations. Copyright © 2012 Elsevier Ltd. All rights reserved.

Tropical Pacific climate variability over the last 6000 years as recorded in Bainbridge Crater Lake, Galápagos

NASA Astrophysics Data System (ADS)

Thompson, Diane M.; Conroy, Jessica L.; Collins, Aaron; Hlohowskyj, Stephan R.; Overpeck, Jonathan T.; Riedinger-Whitmore, Melanie; Cole, Julia E.; Bush, Mark B.; Whitney, H.; Corley, Timothy L.; Kannan, Miriam Steinitz

2017-08-01

Finely laminated sediments within Bainbridge Crater Lake, Galápagos, provide a record of El Niño-Southern Oscillation (ENSO) events over the Holocene. Despite the importance of this sediment record, hypotheses for how climate variability is preserved in the lake sediments have not been tested. Here we present results of long-term monitoring of the local climate and limnology and a revised interpretation of the sediment record. Brown-green, organic-rich, siliciclastic laminae reflect warm, wet conditions typical of El Niño events, whereas carbonate and gypsum precipitate during cool, dry La Niña events and persistent dry periods, respectively. Applying this new interpretation, we find that ENSO events of both phases were generally less frequent during the mid-Holocene ( 6100-4000 calendar years B.P.) relative to the last 1500 calendar years. Abundant carbonate laminations between 3500 and 3000 calendar years B.P. imply that conditions in the Galápagos region were cool and dry during this period when the tropical Pacific E-W sea surface temperature (SST) gradient likely strengthened. The frequency of El Niño and La Niña events then intensified dramatically around 1750-2000 calendar years B.P., consistent with a weaker SST gradient and an increased frequency of ENSO events in other regional records. This strong interannual variability persisted until 700 calendar years B.P., when ENSO-related variability at the lake decreased as the SST gradient strengthened. Persistent, dry conditions then dominated between 300 and 50 calendar years B.P. (A.D. 1650-1900, ± 100 years), whereas wetter conditions and frequent El Niño events dominated in the most recent century.

Greater Baltimore Open Air: an Internet of Things (IoT) approach to citizen science and community-driven climate, air quality, and urban heat island monitoring

NASA Astrophysics Data System (ADS)

Scott, A.; Kelley, C.; Azdoud, Y.; Ambikapathi, R.; Hobson, M.; Lehman, A.; Ghugare, P.; He, C.; Zaitchik, B. F.; Waugh, D.; McCormack, M.; Baja, K.

2017-12-01

Anthropogenic activities alter the urban surface and surface atmosphere, generating heat and pollutants that have known detrimental impacts on health. Monitoring these environmental variables in urban environments is made difficult by the spatial heterogeneity of urban environments, meaning that two nearby locations may have significantly different temperatures, humidities, or gas concentrations. Thus, urban monitoring often requires more densely placed monitors than current standards or budgets allow. Recent advances in low-cost sensors and Internet of Things (IoT) enabled hardware offer possible solutions. We present an autonomous wireless, open-source, IoT-enabled environmental monitor called a WeatherCube, developed for the Greater Baltimore Open Air project, funded in part by the EPA SmartCity Challenge. The WeatherCube is suitable for urban monitoring and capable of measuring meteorological variables (temperature and humidity) as well as air quality (ozone, nitrogen dioxide, and sulfur dioxide). The WeatherCube devices were built in collaboration with Johns Hopkins University, local government, and community members, including through an innovative job training program. Monitors are hosted by community partners and libraries throughout Baltimore city and surrounding communities. We present the first wave of data collected by the Greater Baltimore Open Air project and compare it to data collected by the Maryland Department of the Environment (MDE). Additionally, we will provide an overview of our experience engaging with the local makers, citizen scientists, and environmental groups to improve their urban environmental monitoring. By developing low-cost devices tailored for urban environmental monitoring, we present an innovative model for both conducting research and community outreach.

Atmospheric Teleconnection and Climate Variability: Affecting Rice Productivity of Bihar, India

NASA Astrophysics Data System (ADS)

Saini, A.

2017-12-01

Climate variability brought various negative results to the environment around us and area under rice crop in Bihar has also faced a lot of negative impacts due to variability in temperature and rainfall. Location of Bihar in Northern Plain of India automatically makes it prime location for agriculture and therefore variability in climatic variables brings highly sensitive results to the agricultural production (especially rice). In this study, rainfall and temperature variables are taken into consideration to investigate the impact on rice cultivated area. Change in climate variable with the passage of time is prevailing since the start of geological time scale, how the variability in climate variables has affected the major crops. Climate index of Pacific Ocean and Indian Ocean influences the seasonal weather in Bihar and therefore role of ENSO and IOD is an interesting point of inquiry. Does there exists direct relation between climate variability and area under agricultural crops? How many important variables directly signals towards the change in area under agriculture production? These entire questions are answered with respect to change in area under rice cultivation of Bihar State of India. Temperature, rainfall and ENSO are a good indicator with respect to rice cultivation in Indian subcontinent. Impact on the area under rice has been signaled through ONI, Niño3 and DMI. Increasing range of temperature in the rice productivity declining years is observed since 1990.

A window on the deep ocean: The special value of ocean bottom pressure for monitoring the large-scale, deep-ocean circulation

NASA Astrophysics Data System (ADS)

Hughes, Chris W.; Williams, Joanne; Blaker, Adam; Coward, Andrew; Stepanov, Vladimir

2018-02-01

We show how, by focusing on bottom pressure measurements particularly on the global continental slope, it is possible to avoid the "fog" of mesoscale variability which dominates most observables in the deep ocean. This makes it possible to monitor those aspects of the ocean circulation which are most important for global scale ocean variability and climate. We therefore argue that such measurements should be considered an important future component of the Global Ocean Observing System, to complement the present open-ocean and coastal elements. Our conclusions are founded on both theoretical arguments, and diagnostics from a fine-resolution ocean model that has realistic amplitudes and spectra of mesoscale variability. These show that boundary pressure variations are coherent over along-slope distances of tens of thousands of kilometres, for several vertical modes. We illustrate the value of this in the model Atlantic, by determining the time for boundary and equatorial waves to complete a circuit of the northern basin (115 and 205 days for the first and second vertical modes), showing how the boundary features compare with basin-scale theoretical models, and demonstrating the ability to monitor the meridional overturning circulation using these boundary measurements. Finally, we discuss applicability to the real ocean and make recommendations on how to make such measurements without contamination from instrumental drift.

Analysis of weather condition influencing fire regime in Italy

NASA Astrophysics Data System (ADS)

Bacciu, Valentina; Masala, Francesco; Salis, Michele; Sirca, Costantino; Spano, Donatella

2014-05-01

Fires have a crucial role within Mediterranean ecosystems, with both negative and positive impacts on all biosphere components and with reverberations on different scales. Fire determines the landscape structure and plant composition, but it is also the cause of enormous economic and ecological damages, beside the loss of human life. In addition, several authors are in agreement suggesting that, during the past decades, changes on fire patterns have occurred, especially in terms of fire-prone areas expansion and fire season lengthening. Climate and weather are two of the main controlling agents, directly and indirectly, of fire regime influencing vegetation productivity, causing water stress, igniting fires through lightning, or modulating fire behavior through wind. On the other hand, these relationships could be not warranted in areas where most ignitions are caused by people (Moreno et al. 2009). Specific analyses of the driving forces of fire regime across countries and scales are thus still required in order to better anticipate fire seasons and also to advance our knowledge of future fire regimes. The objective of this work was to improve our knowledge of the relative effects of several weather variables on forest fires in Italy for the period 1985-2008. Meteorological data were obtained through the MARS (Monitoring Agricultural Resources) database, interpolated at 25x25 km scale. Fire data were provided by the JRC (Join Research Center) and the CFVA (Corpo Forestale e di Vigilanza Ambientale, Sardinia). A hierarchical cluster analysis, based on fire and weather data, allowed the identification of six homogeneous areas in terms of fire occurrence and climate (pyro-climatic areas). Two statistical techniques (linear and non-parametric models) were applied in order to assess if inter-annual variability in weather pattern and fire events had a significant trend. Then, through correlation analysis and multi-linear regression modeling, we investigated the influence of weather variables on fire activity across a range of time- and spatial-scales. The analysis revealed a general decrease of both number of fires and burned area, although not everywhere with the same magnitude. Overall, regression models where highly significant (p<0.001), and the explained variance ranged from 36% to 80% for fire number and from 37% to 76% for burned area, depending on pyro-climatic area. Moreover, our results contributed in determining the relative importance of climate variables acting at different timescales as control on intrinsic (i.e. flammability and moisture) and extrinsic (i.e. fuel amount and structure) characteristics of vegetation, thus strongly influencing fire occurrence. The good performance of our models, especially in the most fire affected pyro-climatic areas of Italy, and the better understanding of the main driver of fire variability gained through this work could be of great help for fire management among the different pyro-climatic areas.

Essential climatic variables estimation with satellite imagery

NASA Astrophysics Data System (ADS)

Kolotii, A.; Kussul, N.; Shelestov, A.; Lavreniuk, M. S.

2016-12-01

According to Sendai Framework for Disaster Risk Reduction 2015 - 2030 Leaf Area Index (LAI) is considered as one of essential climatic variables. This variable represents the amount of leaf material in ecosystems and controls the links between biosphere and atmosphere through various processes and enables monitoring and quantitative assessment of vegetation state. LAI has added value for such important global resources monitoring tasks as drought mapping and crop yield forecasting with use of data from different sources [1-2]. Remote sensing data from space can be used to estimate such biophysical parameter at regional and national scale. High temporal satellite imagery is usually required to capture main parameters of crop growth [3]. Sentinel-2 mission launched in 2015 be ESA is a source of high spatial and temporal resolution satellite imagery for mapping biophysical parameters. Products created with use of automated Sen2-Agri system deployed during Sen2-Agri country level demonstration project for Ukraine will be compared with our independent results of biophysical parameters mapping. References Shelestov, A., Kolotii, A., Camacho, F., Skakun, S., Kussul, O., Lavreniuk, M., & Kostetsky, O. (2015, July). Mapping of biophysical parameters based on high resolution EO imagery for JECAM test site in Ukraine. In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 1733-1736 Kolotii, A., Kussul, N., Shelestov, A., Skakun, S., Yailymov, B., Basarab, R., ... & Ostapenko, V. (2015). Comparison of biophysical and satellite predictors for wheat yield forecasting in Ukraine. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 40(7), 39-44. Kussul, N., Lemoine, G., Gallego, F. J., Skakun, S. V., Lavreniuk, M., & Shelestov, A. Y. Parcel-Based Crop Classification in Ukraine Using Landsat-8 Data and Sentinel-1A Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 9 (6), 2500-2508.

Combining multiple sources of data to inform conservation of Lesser Prairie-Chicken populations

USGS Publications Warehouse

Ross, Beth; Haukos, David A.; Hagen, Christian A.; Pitman, James

2018-01-01

Conservation of small populations is often based on limited data from spatially and temporally restricted studies, resulting in management actions based on an incomplete assessment of the population drivers. If fluctuations in abundance are related to changes in weather, proper management is especially important, because extreme weather events could disproportionately affect population abundance. Conservation assessments, especially for vulnerable populations, are aided by a knowledge of how extreme events influence population status and trends. Although important for conservation efforts, data may be limited for small or vulnerable populations. Integrated population models maximize information from various sources of data to yield population estimates that fully incorporate uncertainty from multiple data sources while allowing for the explicit incorporation of environmental covariates of interest. Our goal was to assess the relative influence of population drivers for the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) in the core of its range, western and southern Kansas, USA. We used data from roadside lek count surveys, nest monitoring surveys, and survival data from telemetry monitoring combined with climate (Palmer drought severity index) data in an integrated population model. Our results indicate that variability in population growth rate was most influenced by variability in juvenile survival. The Palmer drought severity index had no measurable direct effects on adult survival or mean number of offspring per female; however, there were declines in population growth rate following severe drought. Because declines in population growth rate occurred at a broad spatial scale, declines in response to drought were likely due to decreases in chick and juvenile survival rather than emigration outside of the study area. Overall, our model highlights the importance of accounting for environmental and demographic sources of variability, and provides a thorough method for simultaneously evaluating population demography in response to long-term climate effects.

A new multi-sensor integrated index for drought monitoring

NASA Astrophysics Data System (ADS)

Jiao, W.; Wang, L.; Tian, C.

2017-12-01

Drought is perceived as one of the most expensive and least understood natural disasters. The remote-sensing-based integrated drought indices, which integrate multiple variables, could reflect the drought conditions more comprehensively than single drought indices. However, most of current remote-sensing-based integrated drought indices focus on agricultural drought (i.e., deficit in soil moisture), their application in monitoring meteorological drought (i.e., deficit in precipitation) was limited. More importantly, most of the remote-sensing-based integrated drought indices did not take into consideration of the spatially non-stationary nature of the related variables, so such indices may lose essential local details when integrating multiple variables. In this regard, we proposed a new mathematical framework for generating integrated drought index for meteorological drought monitoring. The geographically weighted regression (GWR) model and principal component analysis were used to composite Moderate-resolution Imaging Spectroradiometer (MODIS) based temperature condition index (TCI), the Vegetation Index based on the Universal Pattern Decomposition method (VIUPD) based vegetation condition index (VCI), tropical rainfall measuring mission (TRMM) based Precipitation Condition Index (PCI) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) based soil moisture condition index (SMCI). We called the new remote-sensing-based integrated drought index geographical-location-based integrated drought index (GLIDI). We examined the utility of the GLIDI for drought monitoring in various climate divisions across the continental United States (CONUS). GLIDI showed high correlations with in-situ drought indices and outperformed most other existing drought indices. The results also indicate that the performance of GLIDI is not affected by environmental factors such as land cover, precipitation, temperature and soil conditions. As such, the GLIDI has considerable potential for drought monitoring across various environmental conditions.

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.

Beyond Climate Scenarios: Advancing from Changes in the Mean to a Better Understanding of Physical Processes to Enhance Stakeholder Engagement

NASA Astrophysics Data System (ADS)

Yates, D. N.; Kaatz, L.; Ammann, C. M.

2017-12-01

Great strides have been made within the climate sciences community to make Global Climate Model (GCM) output and their results as meaningful as possible to the broad community of stakeholders that might benefit from this information. Regardless of these good intentions, the fact remains that most data from GCMs are viewed as being highly uncertain and thus not actionable for water resources planning. The most common use of GCM data is informing projected future climate by use of a mean change, primarily for temperature, given the generally greater confidence in this variable. In contrast, precipitation is viewed as highly uncertain, primarily because it has not validated well against observed precipitation climatologies at local and regional levels. Simple perturbations to historical mean temperature and precipitation sequences are not as complex as using direct GCM outputs and have fewer analytical requirements. Mean climate change information can still give valuable information to water managers, providing meaningful insights and sign posts into future vulnerabilities and is an approach that is arguably deemed more actionable. These temperature and precipitation sign posts can be monitored and used as indicators when certain actions become necessary and/or until there are improvements in actionable climate science information. Recent advances in regional climate modeling (RCM), particularly those run at very high resolution and are cloud resolving, show promise in advancing our understanding of the interaction among climate variables at the regional level. Thus, in addition to exploring how changes in the mean climate (e.g. 2oC warming) might impact a water system, this bottom-up approach makes use of carefully constructed regional climate experiments that are conducted, for example, under conditions of a warmer atmosphere that can hold more moisture. One can then explore what happens to, for example, rain-snow partitioning at various elevations across a snow dominated basin, what happens to coastal rainfall intensities when ocean temperatures are warmer in the early spring, or how might the daily temperature differential (tmin/max) change?

Hydrologic monitoring using open-source Arduino logging platforms in a socio-hydrological system of the drought-prone tropics, Guanacaste, Costa Rica

NASA Astrophysics Data System (ADS)

Hund, S. V.; Johnson, M. S.; Steyn, D. G.; Keddie, T.; Morillas, L.

2015-12-01

Water supply is highly disputed in the tropics of northwestern Costa Rica where rainfall exhibits high seasonal variability and long annual dry seasons. Water shortages are common during the dry season, and water conflicts emerge between domestic water users, intensively irrigated agriculture, the tourism industry, and ecological flows. Climate change may further increase the variability of precipitation and the risk for droughts, and pose challenges for small rural agricultural communities experiencing water stress. To adapt to seasonal droughts and improve resilience of communities to future changes, it is essential to increase understanding of interactions between components of the coupled hydrological-social system. Yet, hydrological monitoring and data on water use within developing countries of the humid tropics is limited. To address these challenges and contribute to extended monitoring networks, low-cost and open-source monitoring platforms were developed based off Arduino microelectronic boards and software and combined with hydrological sensors to monitor river stage and groundwater levels in two watersheds of Guanacaste, Costa Rica. Hydrologic monitoring stations are located in remote locations and powered by solar panels. Monitoring efforts were made possible through collaboration with local rural communities, and complemented with a mix of digitized water extraction data and community water use narratives to increase understanding of water use and challenges. We will present the development of the Arduino logging system, results of water supply in relation to water use for both the wet and dry season, and discuss these results within a socio-hydrological system context.

Analysis of the Relationship Between Climate and NDVI Variability at Global Scales

NASA Technical Reports Server (NTRS)

Zeng, Fan-Wei; Collatz, G. James; Pinzon, Jorge; Ivanoff, Alvaro

2011-01-01

interannual variability in modeled (CASA) C flux is in part caused by interannual variability in Normalized Difference Vegetation Index (NDVI) Fraction of Photosynthetically Active Radiation (FPAR). This study confirms a mechanism producing variability in modeled NPP: -- NDVI (FPAR) interannual variability is strongly driven by climate; -- The climate driven variability in NDVI (FPAR) can lead to much larger fluctuation in NPP vs. the NPP computed from FPAR climatology

A National Program for Analysis of the Climate System

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Arkin, Phil; Kalnay, Eugenia; Laver, James; Trenberth, Kevin

2002-01-01

Perhaps the single greatest roadblock to fundamental advances in our understanding of climate variability and climate change is the lack of robust and unbiased long-term global observations of the climate system. Such observations are critical for the identification and diagnosis of climate variations, and provide the constraints necessary for developing and validating climate models. The first generation of reanalysis efforts, by using fixed analysis systems, eliminated the artificial climate signals that occurred in analyses generated at the operational numerical weather prediction centers. These datasets are now widely used by the scientific community in a variety of applications including atmosphere-ocean interactions, seasonal prediction, climate monitoring, the hydrological cycle, and a host of regional and other diagnostic studies. These reanalyses, however, had problems that made them sub-optimal or even unusable for some applications. Perhaps the most serious problem for climate applications was that, while the assimilation system remained fixed, changes in the observing systems did produce spurious changes in the perceived climate. The first generation reanalysis products also exposed problems with physical consistency of the products and the accurate representation of physical processes in the climate system. Examples are bias in the estimates of ocean surface fluxes, and inadequate representation of polar hydrology. In this talk, I will describe some initial plans for a national program on reananlysis. The program is envisioned to be part of an on-going activity to maintain, improve, and reprocess our record of climate observations. I will discuss various issues affecting the quality of reanalyses, with a special focus on those relevant to the ocean.

Drought in Northeast Brazil—past, present, and future

NASA Astrophysics Data System (ADS)

Marengo, Jose A.; Torres, Roger Rodrigues; Alves, Lincoln Muniz

2017-08-01

This study provides an overview of the drought situation in Northeast Brazil for the past, present, and future. Droughts affect more people than any other natural hazard owing to their large scale and long-lasting nature. They are recurrent in the region and while some measures have been taken by the governments to mitigate their impacts, there is still a perception that residents, mainly in rural areas, are not yet adapted to these hazards. The drought affecting the Northeast from 2012 to 2015, however, has had an intensity and impact not seen in several decades and has already destroyed large swaths of cropland, affecting hundreds of cities and towns across the region, and leaving ranchers struggling to feed and water cattle. Future climate projections for the area show large temperature increases and rainfall reductions, which, together with a tendency for longer periods with consecutive dry days, suggest the occurrence of more frequent/intense dry spells and droughts and a tendency toward aridification in the region. All these conditions lead to an increase in evaporation from reservoirs and lakes, affecting irrigation and agriculture as well as key water uses including hydropower and industry, and thus, the welfare of the residents. Integrating drought monitoring and seasonal forecasting provides efficient means of assessing impacts of climate variability and change, identifying vulnerabilities, and allowing for better adaptation measures not only for medium- and long-term climate change but also for extremes of the interannual climate variability, particularly droughts.

Climate change and mosquito-borne diseases in China: a review.

PubMed

Bai, Li; Morton, Lindsay Carol; Liu, Qiyong

2013-03-09

China has experienced noticeable changes in climate over the past 100 years and the potential impact climate change has on transmission of mosquito-borne infectious diseases poses a risk to Chinese populations. The aims of this paper are to summarize what is known about the impact of climate change on the incidence and prevalence of malaria, dengue fever and Japanese encephalitis in China and to provide important information and direction for adaptation policy making. Fifty-five papers met the inclusion criteria for this study. Examination of these studies indicates that variability in temperature, precipitation, wind, and extreme weather events is linked to transmission of mosquito-borne diseases in some regions of China. However, study findings are inconsistent across geographical locations and this requires strengthening current evidence for timely development of adaptive options. After synthesis of available information we make several key adaptation recommendations including: improving current surveillance and monitoring systems; concentrating adaptation strategies and policies on vulnerable communities; strengthening adaptive capacity of public health systems; developing multidisciplinary approaches sustained by an new mechanism of inter-sectional coordination; and increasing awareness and mobilization of the general public.

Climate change and mosquito-borne diseases in China: a review

PubMed Central

2013-01-01

China has experienced noticeable changes in climate over the past 100 years and the potential impact climate change has on transmission of mosquito-borne infectious diseases poses a risk to Chinese populations. The aims of this paper are to summarize what is known about the impact of climate change on the incidence and prevalence of malaria, dengue fever and Japanese encephalitis in China and to provide important information and direction for adaptation policy making. Fifty-five papers met the inclusion criteria for this study. Examination of these studies indicates that variability in temperature, precipitation, wind, and extreme weather events is linked to transmission of mosquito-borne diseases in some regions of China. However, study findings are inconsistent across geographical locations and this requires strengthening current evidence for timely development of adaptive options. After synthesis of available information we make several key adaptation recommendations including: improving current surveillance and monitoring systems; concentrating adaptation strategies and policies on vulnerable communities; strengthening adaptive capacity of public health systems; developing multidisciplinary approaches sustained by an new mechanism of inter-sectional coordination; and increasing awareness and mobilization of the general public. PMID:23497420

Flowering phenological changes in relation to climate change in Hungary

NASA Astrophysics Data System (ADS)

Szabó, Barbara; Vincze, Enikő; Czúcz, Bálint

2016-09-01

The importance of long-term plant phenological time series is growing in monitoring of climate change impacts worldwide. To detect trends and assess possible influences of climate in Hungary, we studied flowering phenological records for six species ( Convallaria majalis, Taraxacum officinale, Syringa vulgaris, Sambucus nigra, Robinia pseudoacacia, Tilia cordata) based on phenological observations from the Hungarian Meteorological Service recorded between 1952 and 2000. Altogether, four from the six examined plant species showed significant advancement in flowering onset with an average rate of 1.9-4.4 days per decade. We found that it was the mean temperature of the 2-3 months immediately preceding the mean flowering date, which most prominently influenced its timing. In addition, several species were affected by the late winter (January-March) values of the North Atlantic Oscillation (NAO) index. We also detected sporadic long-term effects for all species, where climatic variables from earlier months exerted influence with varying sign and little recognizable pattern: the temperature/NAO of the previous autumn (August-December) seems to influence Convallaria, and the temperature/precipitation of the previous spring (February-April) has some effect on Tilia flowering.

Pteropods and climate off the Antarctic Peninsula

NASA Astrophysics Data System (ADS)

Loeb, Valerie J.; Santora, Jarrod A.

2013-09-01

Shelled (thecosome) and naked (gymnosome) pteropods are regular, at times abundant, members of Southern Ocean zooplankton assemblages. Regionally, shelled species can play a major role in food webs and carbon cycling. Because of their aragonite shells thecosome pteropods may be vulnerable to the impacts of ocean acidification; without shells they cannot survive and their demise would have major implications for food webs and carbon cycling in the Southern Ocean. Additionally, pteropod species in the southwest Atlantic sector of the Southern Ocean inhabit a region of rapid warming and climate change, the impacts of which are predicted to be observed as poleward distribution shifts. Here we provide baseline information on intraseasonal, interannual and longer scale variability of pteropod populations off the Antarctic Peninsula between 1994 and 2009. Concentrations of the 4 dominant taxa, Limacina helicina antarctica f. antarctica, Clio pyramidata f. sulcata, Spongiobranchaea australis and Clione limacina antarctica, are similar to those monitored during the 1928-1935 Discovery Investigations and reflect generally low values but with episodic interannual abundance peaks that, except for C. pyr. sulcata, are related to basin-scale climate forcing associated with the El Niño-Southern Oscillation (ENSO) climate mode. Significant abundance increases of L. helicina and S. australis after 1998 were associated with a climate regime shift that initiated a period dominated by cool La Niña conditions and increased nearshore influence of the Antarctic Circumpolar Current (ACC). This background information is essential to assess potential future changes in pteropod species distribution and abundance associated with ocean warming and acidification. construct maps of pteropod spatial frequency and mean abundance to assess their oceanographic associations; quantify pteropod abundance anomalies for comparing intraseasonal and interannual variability relative to m-3 environmental variables and climate modes; investigate the presence of long-term trends and/or cycles of peak abundance of the pteropod species in this region as have been described for krill and salps (Loeb et al., 2009, 2010; Loeb and Santora, 2012). We then examine interannual and longer-term variability of pteropod species abundance with respect to possible effects of the El Niño-Southern Oscillation (ENSO) and Southern Annular Mode (SAM) on population size, advection into and retention within the survey area. In doing so we highlight the importance of having sufficient spatial and temporal sampling coverage, as well as appropriate net mesh size, to establish statistically significant abundance changes associated with climate modes and long-term warming.

Resilience, rapid transitions and regime shifts: fingerprinting the responses of Lake Żabińskie (NE Poland) to climate variability and human disturbance since 1000 AD

NASA Astrophysics Data System (ADS)

Tylmann, Wojciech; Hernández-Almeida, Iván; Grosjean, Martin; José Gómez Navarro, Juan; Larocque-Tobler, Isabelle; Bonk, Alicja; Enters, Dirk; Ustrzycka, Alicja; Piotrowska, Natalia; Przybylak, Rajmund; Wacnik, Agnieszka; Witak, Małgorzata

2016-04-01

Rapid ecosystem transitions and adverse effects on ecosystem services as responses to combined climate and human impacts are of major concern. Yet few quantitative observational data exist, particularly for ecosystems that have a long history of human intervention. Here, we combine quantitative summer and winter climate reconstructions, climate model simulations and proxies for three major environmental pressures (land use, nutrients and erosion) to explore the system dynamics, resilience, and the role of disturbance regimes in varved eutrophic Lake Żabińskie since AD 1000. Comparison between regional and global climate simulations and quantitative climate reconstructions indicate that proxy data capture noticeably natural forced climate variability, while internal variability appears as the dominant source of climate variability in the climate model simulations during most parts of the last millennium. Using different multivariate analyses and change point detection techniques, we identify ecosystem changes through time and shifts between rather stable states and highly variable ones, as expressed by the proxies for land-use, erosion and productivity in the lake. Prior to AD 1600, the lake ecosystem was characterized by a high stability and resilience against considerable observed natural climate variability. In contrast, lake-ecosystem conditions started to fluctuate at high frequency across a broad range of states after AD 1600. The period AD 1748-1868 represents the phase with the strongest human disturbance of the ecosystem. Analyses of the frequency of change points in the multi-proxy dataset suggests that the last 400 years were highly variable and flickering with increasing vulnerability of the ecosystem to the combined effects of climate variability and anthropogenic disturbances. This led to significant rapid ecosystem transformations.

Ocean climate indicators: A monitoring inventory and plan for tracking climate change in the north-central California coast and ocean region

USGS Publications Warehouse

Duncan, Benet; Higgason, Kelley; Suchanek, Tom; Largier, John; Stachowicz, Jay; Allen, Sarah; Bograd, Steven; Breen, R.; Gellerman, Holly; Hill, Tessa; Jahncke, Jaime; Johnson, Rebecca L.; Lonhart, Steve I.; Morgan, Steven; Wilkerson, Frances; Roletto, Jan

2013-01-01

The impacts of climate change, defined as increasing atmospheric and oceanic carbon dioxide and associated increases in average global temperature and oceanic acidity, have been observed both globally and on regional scales, such as in the North-central California coast and ocean, a region that extends from Point Arena to Point Año Nuevo and includes the Pacific coastline of the San Francisco Bay Area. Because of the high economic and ecological value of the region’s marine environment, the Gulf of the Farallones National Marine Sanctuary (GFNMS) and other agencies and organizations have recognized the need to evaluate and plan for climate change impacts. Climate change indicators can be developed on global, regional, and site-specific spatial scales, and they provide information about the presence and potential impacts of climate change. While indicators exist for the nation and for the state of California as a whole, no system of ocean climate indicators exist that specifically consider the unique characteristics of the California coast and ocean region. To that end, GFNMS collaborated with over 50 regional, federal, and state natural resource managers, research scientists, and other partners to develop a set of 2 ocean climate indicators specific to this region. A smaller working group of 13 regional partners developed monitoring goals, objectives, strategies, and activities for the indicators and recommended selected species for biological indicators, resulting in the Ocean Climate Indicators Monitoring Inventory and Plan. The working group considered current knowledge of ongoing monitoring, feasibility of monitoring, costs, and logistics in selecting monitoring activities and selected species.

Soil cover patterns influence on the land environmental functions, agroecological quality, land-use and monitoring efficiency in the Central Russia

NASA Astrophysics Data System (ADS)

Vasenev, Ivan; Yashin, Ivan; Lukin, Sergey; Valentini, Riccardo

2015-04-01

First decades of XXI century actualized for soil researches the principal methodical problem of most modern geosciences: what spatial and temporal scale would be optimal for land quality evaluation and land-use practice optimizing? It is becoming obvious that this question cannot have one solution and have to be solved with especial attention on the features of concrete region and landscape, land-use history and practical issues, land current state and environmental functions, soil cover patterns and variability, governmental requirements and local society needs, best available technologies and their potential profitability. Central Russia is one of the most dynamical economic regions with naturally high and man-made complicated landscape and soil cover variability, long-term land-use history and self-contradictory issues, high potential of profitable farming and increased risks of land degradation. Global climate and technological changes essentially complicate the originally high and sharply increased in XX century farming land heterogeneity in the Central Russia that actualizes system analysis of its zonal, intra-zonal and azonal soil cover patterns according to their influence on land environmental functions, agroecological quality, and land-use and monitoring efficiency variability. Developed by the Laboratory of agroecological monitoring, ecosystem modeling & prediction (LAMP / RTSAU with support of RF Governmental projects #11.G34.31.0079 and #14.120.14.4266) regional systems of greenhouse gases environmental monitoring RusFluxNet (6 fixed & 1 mobile eddy covariance stations with zonal functional sets of key plots with chamber investigations in 5 Russian regions) and of agroecological monitoring (in representative key plots with different farming practice in 9 RF regions) allow to do this analysis in frame of enough representative regional multi-factorial matrix of soil cover patterns, bioclimatic conditions, landscape features, and land-use history and current practice versions. Well-elaborated monitoring collaboration with the principal natural reserves in south-taiga and forest-steppe zones provides process-based interaction with long-term data on zonal climatic, landscape and soil features necessary to test the process, functional and evaluation models in the specific conditions of each bioclimatic zone. The dominated erosion and dehumification trends have been essentially activated for last 3-4 decades due to hu¬mus negative balance around 0.6-0.7 t ha-1year-1 and connected disaggregation with annual rate between 1 and 25 g/kg for aggregates 10-0.25 mm. "Standard" monitoring objects and regionally generalized data showed characteristic for Chernozems 2-2.5 % humus drop during this period and active processes of CO2 emission and humus eluvial-illuvial profile redistribution too. Forest-steppe Chernozems are usually characterized by higher stability than steppe ones. The ratio between erosive and biological losses in humus stock can be ten¬tatively estimated as fifty-fifty with essential variability within slope landscape. Both these processes have essential impacts on different sets of soil environmental and agroecological functions (including atmospheric air, surface and ground water quality, biodiversity and profitability) that we need to understand and predict. A drop of humus content below threshold values (for different soils between 1.5 and 6%) considerably reduces not only soil environmental regulation functions but also effectiveness of used fertilizers, crop yield quality and possibility of sustainable agricultural land-use. The carried out long-term researches of representative natural, rural and urban landscapes in Tver, Yaroslavl, Vladimir, Moscow, Kaluga, Kursk, Belgorod, Tambov, Voronezh and Saratov regions give us validation and ranging of the limiting factors of the elementary soil cover patterns current features and transformation processes, environmental functions and agroecological quality, monitoring results functional interpretation, spatial and temporal interpolation and extrapolation. These data allow essentially improve our understanding and quantitative assessments of the regional and within-field variability of land agroecological and environmental functions that is crucial for agroecosystem services evaluation, current and planned land-use environmental impacts, and DSS development for land-use agroecological optimizing taking into attention the regional and local landscapes features and most realistic scenarios of climate change and agro-technology transfer. Developed and verified within the project regionally adapted DSS (ACORD-R - RF #2012612944) gives effective informational and methodological support for land-use agroecological optimization.

[Modelling the effect of local climatic variability on dengue transmission in Medellin (Colombia) by means of time series analysis].

PubMed

Rúa-Uribe, Guillermo L; Suárez-Acosta, Carolina; Chauca, José; Ventosilla, Palmira; Almanza, Rita

2013-09-01

Dengue fever is a major impact on public health vector-borne disease, and its transmission is influenced by entomological, sociocultural and economic factors. Additionally, climate variability plays an important role in the transmission dynamics. A large scientific consensus has indicated that the strong association between climatic variables and disease could be used to develop models to explain the incidence of the disease. To develop a model that provides a better understanding of dengue transmission dynamics in Medellin and predicts increases in the incidence of the disease. The incidence of dengue fever was used as dependent variable, and weekly climatic factors (maximum, mean and minimum temperature, relative humidity and precipitation) as independent variables. Expert Modeler was used to develop a model to better explain the behavior of the disease. Climatic variables with significant association to the dependent variable were selected through ARIMA models. The model explains 34% of observed variability. Precipitation was the climatic variable showing statistically significant association with the incidence of dengue fever, but with a 20 weeks delay. In Medellin, the transmission of dengue fever was influenced by climate variability, especially precipitation. The strong association dengue fever/precipitation allowed the construction of a model to help understand dengue transmission dynamics. This information will be useful to develop appropriate and timely strategies for dengue control.

Climate Change Adaptation Challenges and EO Business Opportunities

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto; Mathieu, Pierre-Philippe; Bansal, Rahul; Del Rey, Maria; Mohamed, Ebrahim; Ruiz, Paz; Signes, Marcos

Climate change is one of the defining challenges of the 21st century, but is no longer a matter of just scientific concern. It encompasses economics, sociology, global politics as well as national and local politics, law, health and environmental security, etc. The challenge of facing the impacts of climate change is often framed in terms of two potential paths that civilization might take: mitigation and adaptation. On the one hand, mitigation involves reducing the magnitude of climate change itself and is composed of emissions reductions and geoengineering. On the other hand and by contrast, adaptation involves efforts to limit our vulnerability to climate change impacts through various measures. It refers to our ability to adjust ourselves to climate change -including climate variability and extremes, to moderate potential damage, to take advantage of opportunities, or to cope with the consequences. Therefore, we are now faced with a double challenge: next to deep cuts in greenhouse gas emissions, we also need to adapt to the changing climate conditions. The use of satellites to monitor processes and trends at the global scale is essential in the context of climate change. Earth Observation has the potential to improve our predictive vision and to advance climate models. Space sciences and technologies constitute a significant issue in Education and Public Awareness of Science. Space missions face the probably largest scientific and industrial challenges of humanity. It is thus a fact that space drives innovation in the major breakthrough and cutting edge technological advances of mankind (techniques, processes, new products, … as well as in markets and business models). Technology and innovation is the basis of all space activities. Space agencies offer an entire range of space-related activities - from space science and environmental monitoring to industrial competitiveness and end-user services. More specifically, Earth Observation satellites have a unique global view of planet Earth, providing us -with better data- with consistent and frequent information on the state of our environment at the regional and global scale, also in important but remote areas. Climate Knowledge and Innovation Communities (Climate-KIC), a relatively new initiative from the European Institute of Innovation & Technology (EIT), provides the innovations, entrepreneurship, education and expert guidance needed to shape Europe's climate change agenda. This paper shows some initiatives that the University of Valencia Climate-KIC Education Group is carrying out in collaboration with the Climate-KIC Central Education Lead in the field of space education to foster and encourage students and entrepreneurs to endevour in these new space business opportunities offered by this step forward towards climate change adaptation challenges.

Reconstruction of Past Mediterranean Climate

NASA Astrophysics Data System (ADS)

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

2007-02-01

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

Climate variability and demand growth as drivers of water scarcity in the Turkwel river basin: a bottom-up risk assessment of a data-sparse basin in Kenya

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Dyer, E.; Hope, R.; Dadson, S. J.

2017-12-01

Sustainable water management and allocation are essential for maintaining human well-being, sustaining healthy ecosystems, and supporting steady economic growth. The Turkwel river basin, located in north-western Kenya, experiences a high level of water scarcity due to its arid climate, high rainfall variability, and rapidly growing water demand. However, due to sparse hydro-climatic data and limited literature, the water resources system of the basin has been poorly understood. Here we apply a bottom-up climate risk assessment method to estimate the resilience of the basin's water resources system to growing demand and climate stressors. First, using a water resource system model and historical climate data, we construct a climate risk map that depicts the way in which the system responds to climate change and variability. Then we develop a set of water demand scenarios to identify the conditions that potentially lead to the risk of unmet water demand and groundwater depletion. Finally, we investigate the impact of climate change and variability by stress testing these development scenarios against historically strong El Niño/Southern Oscillation (ENSO) years and future climate projections from multiple Global Circulation Models (GCMs). The results reveal that climate variability and increased water demand are the main drivers of water scarcity in the basin. Our findings show that increases in water demand due to expanded irrigation and population growth exert the strongest influence on the ability of the system to meet water resource supply requirements, and in all cases considered increase the impacts of droughts caused by future climate variability. Our analysis illustrates the importance of combining analysis of future climate risks with other development decisions that affect water resources planning. Policy and investment decisions which maximise water use efficiency in the present day are likely to impart resilience to climate change and variability under a wide range of future scenarios and therefore constitute low regret measures for climate adaptation.

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Trachsel, M.; Rehfeld, K.; Telford, R.; Laepple, T.

2017-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Climate change and the Delta

USGS Publications Warehouse

Dettinger, Michael; Anderson, Jamie; Anderson, Michael L.; Brown, Larry R.; Cayan, Daniel; Maurer, Edwin P.

2016-01-01

Anthropogenic climate change amounts to a rapidly approaching, “new” stressor in the Sacramento–San Joaquin Delta system. In response to California’s extreme natural hydroclimatic variability, complex water-management systems have been developed, even as the Delta’s natural ecosystems have been largely devastated. Climate change is projected to challenge these management and ecological systems in different ways that are characterized by different levels of uncertainty. For example, there is high certainty that climate will warm by about 2°C more (than late-20th-century averages) by mid-century and about 4°C by end of century, if greenhouse-gas emissions continue their current rates of acceleration. Future precipitation changes are much less certain, with as many climate models projecting wetter conditions as drier. However, the same projections agree that precipitation will be more intense when storms do arrive, even as more dry days will separate storms. Warmer temperatures will likely enhance evaporative demands and raise water temperatures. Consequently, climate change is projected to yield both more extreme flood risks and greater drought risks. Sea level rise (SLR) during the 20th century was about 22cm, and is projected to increase by at least 3-fold this century. SLR together with land subsidence threatens the Delta with greater vulnerabilities to inundation and salinity intrusion. Effects on the Delta ecosystem that are traceable to warming include SLR, reduced snowpack, earlier snowmelt and larger storm-driven streamflows, warmer and longer summers, warmer summer water temperatures, and water-quality changes. These changes and their uncertainties will challenge the operations of water projects and uses throughout the Delta’s watershed and delivery areas. Although the effects of climate change on Delta ecosystems may be profound, the end results are difficult to predict, except that native species will fare worse than invaders. Successful preparation for the coming changes will require greater integration of monitoring, modeling, and decision making across time, variables, and space than has been historically normal.

Observed Changes in Upper-Tropospheric Water Vapor Transport From Satellite Measurements During the Summers of 1987 and 1988

NASA Technical Reports Server (NTRS)

Lerner, Jeffrey A.; Jedlovee, Gary J.; Atkinson, Robert J.

1998-01-01

The research described below focuses on the use of satellite measurements to monitor both monthly and interannual changes in UT (upper tropospheric) water vapor transport. The GOES-7 Pathfinder data set is used to estimate both winds and humidity during the summers (JJA) of 1987 and 1988. These two summers are of particular importance to climate variability since they were characterized by a dramatic shift in the Southern Oscillation index (i.e., 1987 as a warm ENSO event and 1988 as a cold La-Nina period) (Arkin, 1988; Ropelewski 1988). The contrasting features of the summers of '87 and '88 are exploited to demonstrate the utility of satellite wind and humidity estimates to analyze the role of water vapor in climate change.

Methods and techniques for measuring gas emissions from agricultural and animal feeding operations.

PubMed

Hu, Enzhu; Babcock, Esther L; Bialkowski, Stephen E; Jones, Scott B; Tuller, Markus

2014-01-01

Emissions of gases from agricultural and animal feeding operations contribute to climate change, produce odors, degrade sensitive ecosystems, and pose a threat to public health. The complexity of processes and environmental variables affecting these emissions complicate accurate and reliable quantification of gas fluxes and production rates. Although a plethora of measurement technologies exist, each method has its limitations that exacerbate accurate quantification of gas fluxes. Despite a growing interest in gas emission measurements, only a few available technologies include real-time, continuous monitoring capabilities. Commonly applied state-of-the-art measurement frameworks and technologies were critically examined and discussed, and recommendations for future research to address real-time monitoring requirements for forthcoming regulation and management needs are provided.

Using isotopes for design and monitoring of artificial recharge systems

USGS Publications Warehouse

Contributors: Hendriksson, N.; Kulongoski, J.T.; Massmann, G.; Newman, B.

2013-01-01

Over the past years, the IAEA has provided support to a number of Member States engaged in the implementation of hydrological projects dealing with the design and monitoring of artificial recharge ( A R ) systems, primarily situated in arid and semiarid regions. AR is defined as any engineered system designed to introduce water to, and store water in, underlying aquifers. Aquifer storage and recovery (ASR) is a specific type of AR used with the purpose of increasing groundwater resources. Different water management strategies have been tested under various geographical, hydrological and climatic regimes. However, the success of such schemes cannot easily be predicted, since many variables need to be taken into account in the early stages of every AR project.

Co-evolution of Climate, Soil, and Vegetation and their interplay with Hydrological Partitioning at the Catchment Scale

NASA Astrophysics Data System (ADS)

Zapata-Rios, X.; Brooks, P. D.; Troch, P. A. A.; McIntosh, J. C.

2014-12-01

Landscape, climate, and vegetation interactions play a fundamental role in controlling the distribution of available water in hillslopes and catchments. In mid-latitudes, terrain aspect can regulate surface and subsurface hydrological processes, which not only affect the partitioning of energy and precipitation on short time scales, but also soil development, vegetation characteristics on long time scales. In Redondo Peak in northern New Mexico, a volcanic resurgent dome, first order streams drain different slopes around the mountain. In this setting, we study three adjacent first order catchments that share similar physical characteristics, but drain different aspects, allowing for an empirical study of how topographically controlled microclimate and soil influence the integrated hydrological and vegetation response. From 2008 to 2012, catchments were compared for the way they partition precipitation and how vegetation responds to variable water fluxes. Meteorological variables were monitored in 5 stations around Redondo Peak and surface runoff was monitored at the catchments' outlets. Hydrological partitioning at the catchment scale was estimated with the Horton Index, defined as the ratio between vaporization and wetting and it represents a measure of catchment-scale vegetation water use. Vegetation response was estimated using remotely sensed vegetation greenness (NDVI) derived from MODIS every 16 days with a spatial resolution of 250 m. Results show that the predominantly north facing catchment has the largest and least variable baseflow and discharge, consistent with greater mineral weathering fluxes and longer water transit times. In addition, vaporization, wetting and Horton Index, as well as NDVI, are smaller in the north facing catchment compared to the south east facing catchments. The predominant terrain aspect controls soil development, which affects the partitioning of precipitation and vegetation response at the catchment scale. These results also demonstrate how landscape evolution (e.g. depth of weathering profile) can affect various hydrologic processes, including streamflow response to precipitation and water residence time. In turn these processes are first-order controls on the sensitivity of the landscape to land use and climate change.

Recent stability of resident and migratory landbird populations in National Parks of the Pacific Northwest

USGS Publications Warehouse

Ray, Chris; Saracco, James; Holmgren, Mandy; Wilkerson, Robert; Siegel, Rodney; Jenkins, Kurt J.; Ransom, Jason I.; Happe, Patricia J.; Boetsch, John; Huff, Mark

2017-01-01

Monitoring species in National Parks facilitates inference regarding effects of climate change on population dynamics because parks are relatively unaffected by other forms of anthropogenic disturbance. Even at early points in a monitoring program, identifying climate covariates of population density can suggest vulnerabilities to future change. Monitoring landbird populations in parks during the breeding season brings the added benefit of allowing a comparative approach to inference across a large suite of species with diverse requirements. For example, comparing resident and migratory species that vary in exposure to non-park habitats can reveal the relative importance of park effects, such as those related to local climate. We monitored landbirds using breeding-season point-count data collected during 2005–2014 in three wilderness areas of the Pacific Northwest (Mount Rainier, North Cascades, and Olympic National Parks). For 39 species, we estimated recent trends in population density while accounting for individual detection probability using Bayesian hierarchical N-mixture models. Our analyses integrated several recent developments in N-mixture modeling, incorporating interval and distance sampling to estimate distinct components of detection probability while also accommodating count intervals of varying duration, annual variation in the length and number of point-count transects, spatial autocorrelation, random effects, and covariates of detection and density. As covariates of density, we considered metrics of precipitation and temperature hypothesized to affect breeding success. We also considered effects of park and elevational stratum on trend. Regardless of model structure, we estimated stable or increasing densities during 2005–2014 for most populations. Mean trends across species were positive for migrants in every park and for residents in one park. A recent snowfall deficit in this region might have contributed to the positive trend, because population density varied inversely with precipitation-as-snow for both migrants and residents. Densities varied directly but much more weakly with mean spring temperature. Our approach exemplifies an analytical framework for estimating trends from point-count data, and for assessing the role of climatic and other spatiotemporal variables in driving those trends. Understanding population trends and the factors that drive them is critical for adaptive management and resource stewardship in the context of climate change.

Analyzing the responses of species assemblages to climate change across the Great Basin, USA.

NASA Astrophysics Data System (ADS)

Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.

2016-12-01

The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.

Climate variability has a stabilizing effect on the coexistence of prairie grasses

PubMed Central

Adler, Peter B.; HilleRisLambers, Janneke; Kyriakidis, Phaedon C.; Guan, Qingfeng; Levine, Jonathan M.

2006-01-01

How expected increases in climate variability will affect species diversity depends on the role of such variability in regulating the coexistence of competing species. Despite theory linking temporal environmental fluctuations with the maintenance of diversity, the importance of climate variability for stabilizing coexistence remains unknown because of a lack of appropriate long-term observations. Here, we analyze three decades of demographic data from a Kansas prairie to demonstrate that interannual climate variability promotes the coexistence of three common grass species. Specifically, we show that (i) the dynamics of the three species satisfy all requirements of “storage effect” theory based on recruitment variability with overlapping generations, (ii) climate variables are correlated with interannual variation in species performance, and (iii) temporal variability increases low-density growth rates, buffering these species against competitive exclusion. Given that environmental fluctuations are ubiquitous in natural systems, our results suggest that coexistence based on the storage effect may be underappreciated and could provide an important alternative to recent neutral theories of diversity. Field evidence for positive effects of variability on coexistence also emphasizes the need to consider changes in both climate means and variances when forecasting the effects of global change on species diversity. PMID:16908862

Influence of climate drivers on colonization and extinction dynamics of wetland-dependent species

USGS Publications Warehouse

Ray, Andrew M.; Gould, William R.; Hossack, Blake R.; Sepulveda, Adam; Thoma, David P.; Patla, Debra A.; Daley, Rob; Al-Chokhachy, Robert K.

2016-01-01

Freshwater wetlands are particularly vulnerable to climate change. Specifically, changes in temperature, precipitation, and evapotranspiration (i.e., climate drivers) are likely to alter flooding regimes of wetlands and affect the vital rates, abundance, and distributions of wetland-dependent species. Amphibians may be among the most climate-sensitive wetland-dependent groups, as many species rely on shallow or intermittently flooded wetland habitats for breeding. Here, we integrated multiple years of high-resolution gridded climate and amphibian monitoring data from Grand Teton and Yellowstone National Parks to explicitly model how variations in climate drivers and habitat conditions affect the occurrence and breeding dynamics (i.e., annual extinction and colonization rates) of amphibians. Our results showed that models incorporating climate drivers outperformed models of amphibian breeding dynamics that were exclusively habitat based. Moreover, climate-driven variation in extinction rates, but not colonization rates, disproportionately influenced amphibian occupancy in monitored wetlands. Long-term monitoring from national parks coupled with high-resolution climate data sets will be crucial to describing population dynamics and characterizing the sensitivity of amphibians and other wetland-dependent species to climate change. Further, long-term monitoring of wetlands in national parks will help reduce uncertainty surrounding wetland resources and strengthen opportunities to make informed, science-based decisions that have far-reaching benefits.

Global Framework for Climate Services (GFCS): status of implementation

NASA Astrophysics Data System (ADS)

Lucio, Filipe

2014-05-01

The GFCS is a global partnership of governments and UN and international agencies that produce and use climate information and services. WMO, which is leading the initiative in collaboration with UN ISDR, WHO, WFP, FAO, UNESCO, UNDP and other UN and international partners are pooling their expertise and resources in order to co-design and co-produce knowledge, information and services to support effective decision making in response to climate variability and change in four priority areas (agriculture and fod security, water, health and disaster risk reduction). To address the entire value chain for the effective production and application of climate services the GFCS main components or pillars are being implemented, namely: • User Interface Platform — to provide ways for climate service users and providers to interact to identify needs and capacities and improve the effectiveness of the Framework and its climate services; • Climate Services Information System — to produce and distribute climate data, products and information according to the needs of users and to agreed standards; • Observations and Monitoring - to generate the necessary data for climate services according to agreed standards; • Research, Modelling and Prediction — to harness science capabilities and results and develop appropriate tools to meet the needs of climate services; • Capacity Building — to support the systematic development of the institutions, infrastructure and human resources needed for effective climate services. Activities are being implemented in various countries in Africa, the Caribbean and South pacific Islands. This paper will provide details on the status of implementation of the GFCS worldwider.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

Voluntary Field Data Collection for Landscape Phenology and Surface Water Essential Climate Variable Research

NASA Astrophysics Data System (ADS)

Jones, J. W.; Hudson-Dunn, A.; Aquino, K.; Pasa, M.; Paez, F.

2013-12-01

The U.S. Geological Survey is developing techniques to monitor vegetation and surface water condition for improved resource management. Educational materials and data forms that allow volunteer Citizen Scientists to collect information on vegetation and surface water extent to enhance satellite and web camera data analyses (http://egsc.usgs.gov/shenandoah.html) have been developed, tested, and refined. Collection is focused on supplementing landscape phenology and surface water extent (SWE) essential climate variable (ECV) research. Low cost instrumentation, subject education, and measurement calibration techniques all have utility for multiple remote sensing and biophysical studies. Trials have been conducted with subjects ranging from elementary school-aged summer camp children to science major undergraduate and graduate students. Experiments were replicated in several project study areas in Virginia that are also phenology and SWE-ECV research sites. Analysis of volunteer responses and their narrative feedback have improved the ability to request and assess data from volunteers. Children ages 12 and over were able to provide reliable supplemental information for phenology and aquatic research. Finally, trial observation and subject feedback both confirmed that participation furthered volunteer interest in science.

The USA National Phenology Network: A national observatory for assessment of biotic response to environmental variation

NASA Astrophysics Data System (ADS)

Weltzin, J. F.; USA National Phenology Network National Coordinating Office

2011-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org), established in 2007, is a national science and monitoring initiative focused on phenology as a tool to understand how plants, animals and landscapes respond to climatic variability and change. Core functions of the National Coordinating Office (NCO) of USA-NPN are to provide a national information management system including databases, develop and implement internationally standardized phenology monitoring protocols, create partnerships with a variety of organizations including field stations for implementation, facilitate research and the development of decision support tools, and promote education and outreach activities related to phenology and climate change. This presentation will describe programs, tools and materials developed by USA-NPN to facilitate science, management and education related to phenology of plants, animals and landscapes within protected areas at local, regional and national scales. Particular emphasis will be placed on the on-line integrated animal and plant monitoring program, Nature's Notebook, which provides standardized protocols for phenological status monitoring and data management for over 500 animal and plant species. The monitoring system facilitates collection of sampling intensity, absence data, considerable metadata (from site to observation). We recently added functionality for recording estimates of animal abundance and plant canopy development. Real-time raw data for plants (from 2009 to present) and animals (from 2010 to present), including FGDC-compliant metadata and documented methodology, are now available for download from the website. A new data exploration tool premiered in spring 2010 allows sophisticated graphical visualization of integrated phenological and meteorological data. The network seeks to develop partnerships with other organizations interested in (1) implementing vetted, standardized protocols for phenological or ecological monitoring, and (2) using phenology data and information for a variety of modeling applications.

Application of GRACE for Monitoring Groundwater in Data Scarce Regions

NASA Technical Reports Server (NTRS)

Rodell, Matt; Li, Bailing; Famiglietti, Jay; Zaitchik, Ben

2012-01-01

In the United States, groundwater storage is somewhat well monitored (spatial and temporal data gaps notwithstanding) and abundant data are freely and easily accessible. Outside of the U.S., groundwater often is not monitored systematically and where it is the data are rarely centralized and made available. Since 2002 the Gravity Recovery and Climate Experiment (GRACE) satellite mission has delivered gravity field observations which have been used to infer variations in total terrestrial water storage, including groundwater, at regional to continental scales. Challenges to using GRACE for groundwater monitoring include its relatively coarse spatial and temporal resolutions, its inability to differentiate groundwater from other types of water on and under the land surface, and typical 2-3 month data latency. Data assimilation can be used to overcome these challenges, but uncertainty in the results remains and is difficult to quantify without independent observations. Nevertheless, the results are preferable to the alternative - no data at all- and GRACE has already revealed groundwater variability and trends in regions where only anecdotal evidence existed previously.

Green roof soil system affected by soil structural changes: A project initiation

NASA Astrophysics Data System (ADS)

Jelínková, Vladimíra; Dohnal, Michal; Šácha, Jan; Šebestová, Jana; Sněhota, Michal

2014-05-01

Anthropogenic soil systems and structures such as green roofs, permeable or grassed pavements comprise appreciable part of the urban watersheds and are considered to be beneficial regarding to numerous aspects (e.g. carbon dioxide cycle, microclimate, reducing solar absorbance and storm water). Expected performance of these systems is significantly affected by water and heat regimes that are primarily defined by technology and materials used for system construction, local climate condition, amount of precipitation, the orientation and type of the vegetation cover. The benefits and potencies of anthropogenic soil systems could be considerably threatened in case when exposed to structural changes of thin top soil layer in time. Extensive green roof together with experimental green roof segment was established and advanced automated monitoring system of micrometeorological variables was set-up at the experimental site of University Centre for Energy Efficient Buildings as an interdisciplinary research facility of the Czech Technical University in Prague. The key objectives of the project are (i) to characterize hydraulic and thermal properties of soil substrate studied, (ii) to establish seasonal dynamics of water and heat in selected soil systems from continuous monitoring of relevant variables, (iii) to detect structural changes with the use of X-ray Computed Tomography, (iv) to identify with the help of numerical modeling and acquired datasets how water and heat dynamics in anthropogenic soil systems are affected by soil structural changes. Achievements of the objectives will advance understanding of the anthropogenic soil systems behavior in conurbations with the temperate climate.

Application of Satellite Gravimetry for Water Resource Vulnerability Assessment

NASA Technical Reports Server (NTRS)

Rodell, Matthew

2012-01-01

The force of Earth's gravity field varies in proportion to the amount of mass near the surface. Spatial and temporal variations in the gravity field can be measured via their effects on the orbits of satellites. The Gravity Recovery and Climate Experiment (GRACE) is the first satellite mission dedicated to monitoring temporal variations in the gravity field. The monthly gravity anomaly maps that have been delivered by GRACE since 2002 are being used to infer changes in terrestrial water storage (the sum of groundwater, soil moisture, surface waters, and snow and ice), which are the primary source of gravity variability on monthly to decadal timescales after atmospheric and oceanic circulation effects have been removed. Other remote sensing techniques are unable to detect water below the first few centimeters of the land surface. Conventional ground based techniques can be used to monitor terrestrial water storage, but groundwater, soil moisture, and snow observation networks are sparse in most of the world, and the countries that do collect such data rarely are willing to share them. Thus GRACE is unique in its ability to provide global data on variations in the availability of fresh water, which is both vital to life on land and vulnerable to climate variability and mismanagement. This chapter describes the unique and challenging aspects of GRACE terrestrial water storage data, examples of how the data have been used for research and applications related to fresh water vulnerability and change, and prospects for continued contributions of satellite gravimetry to water resources science and policy.

Spatial variability in forest growth—climate relationships in the Olympic Mountains, Washington.

Treesearch

Jill M. Nakawatase; David L. Peterson

2006-01-01

For many Pacific Northwest forests, little is known about the spatial and temporal variability in tree growth - climate relationships, yet it is this information that is needed to predict how forests will respond to future climatic change. We studied the effects of climatic variability on forest growth at 74 plots in the western and northeastern Olympic Mountains....

Frontiers in Decadal Climate Variability: Proceedings of a Workshop

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

Purcell, Amanda

A number of studies indicate an apparent slowdown in the overall rise in global average surface temperature between roughly 1998 and 2014. Most models did not predict such a slowdown--a fact that stimulated a lot of new research on variability of Earth's climate system. At a September 2015 workshop, leading scientists gathered to discuss current understanding of climate variability on decadal timescales (10 to 30 years) and whether and how prediction of it might be improved. Many researchers have focused their attention on the climate system itself, which is known to vary across seasons, decades, and other timescales. Several naturalmore » variables produce "ups and downs" in the climate system, which are superimposed on the long-term warming trend due to human influence. Understanding decadal climate variability is important not only for assessing global climate change but also for improving decision making related to infrastructure, water resources, agriculture, energy, and other realms. Like the well-studied El Nino and La Nina interannual variations, decadal climate variability is associated with specific regional patterns of temperature and precipitation, such as heat waves, cold spells, and droughts. Several participants shared research that assesses decadal predictive capability of current models.« less

Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

PubMed

Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

2017-06-01

To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

Integrating Data from GRACE and Other Observing Systems for Hydrological Research and Applications

NASA Technical Reports Server (NTRS)

Rodell, M.; Famiglietti, J. S.; McWilliams, E.; Beaudoing, H. K.; Li, B.; Zaitchik, B.; Reichle, R.; Bolten, J.

2011-01-01

The Gravity Recovery and Climate Experiment (GRACE) mission provides a unique view of water cycle dynamics, enabling the only space based observations of water on and beneath the land surface that are not limited by depth. GRACE data are immediately useful for large scale applications such as ice sheet ablation monitoring, but they are even more valuable when combined with other types of observations, either directly or within a data assimilation system. Here we describe recent results of hydrological research and applications projects enabled by GRACE. These include the following: 1) global monitoring of interannual variability of terrestrial water storage and groundwater; 2) water balance estimates of evapotranspiration over several large river basins; 3) NASA's Energy and Water Cycle Study (NEWS) state of the global water budget project; 4) drought indicator products now being incorporated into the U.S. Drought Monitor; 5) GRACE data assimilation over several regions.

1993 Earth Observing System reference handbook

NASA Technical Reports Server (NTRS)

Asrar, Ghassem (Editor); Dokken, David Jon (Editor)

1993-01-01

Mission to Planet Earth (MTPE) is a NASA-sponsored concept that uses space- and ground-based measurement systems to provide the scientific basis for understanding global change. The space-based components of MTPE will provide a constellation of satellites to monitor the Earth from space. Sustained observations will allow researchers to monitor climate variables overtime to determine trends; however, space-based monitoring alone is not sufficient. A comprehensive data and information system, a community of scientists performing research with the data acquired, and extensive ground campaigns are all important components. Brief descriptions of the various elements that comprise the overall mission are provided. The Earth Observing System (EOS) - a series of polar-orbiting and low-inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans - is the centerpiece of MTPE. The elements comprising the EOS mission are described in detail.

Post-Fire Recovery of Eco-Hydrologic Behavior Given Historic and Projected Climate Variability in California Mediterranean Type Environments

NASA Astrophysics Data System (ADS)

Seaby, L. P.; Tague, C. L.; Hope, A. S.

2006-12-01

The Mediterranean type environments (MTEs) of California are characterized by a distinct wet and dry season and high variability in inter-annual climate. Water limitation in MTEs makes eco-hydrological processes highly sensitive to both climate variability and frequent fire disturbance. This research modeled post-fire eco- hydrologic behavior under historical and moderate and extreme scenarios of future climate in a semi-arid chaparral dominated southern California MTE. We used a physically-based, spatially-distributed, eco- hydrological model (RHESSys - Regional Hydro-Ecologic Simulation System), to capture linkages between water and vegetation response to the combined effects of fire and historic and future climate variability. We found post-fire eco-hydrologic behavior to be strongly influenced by the episodic nature of MTE climate, which intensifies under projected climate change. Higher rates of post-fire net primary productivity were found under moderate climate change, while more extreme climate change produced water stressed conditions which were less favorable for vegetation productivity. Precipitation variability in the historic record follows the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), and these inter-annual climate characteristics intensify under climate change. Inter-annual variation in streamflow follows these precipitation patterns. Post-fire streamflow and carbon cycling trajectories are strongly dependent on climate characteristics during the first 5 years following fire, and historic intra-climate variability during this period tends to overwhelm longer term trends and variation that might be attributable to climate change. Results have implications for water resource availability, vegetation type conversion from shrubs to grassland, and changes in ecosystem structure and function.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.

PubMed

Boulton, Chris A; Lenton, Timothy M

2015-09-15

Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency--i.e., "redder"--variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This "reddening" of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent "regime shifts." Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.

Influence of climate variability on acute myocardial infarction mortality in Havana, 2001-2012.

PubMed

Rivero, Alina; Bolufé, Javier; Ortiz, Paulo L; Rodríguez, Yunisleydi; Reyes, María C

2015-04-01

Death from acute myocardial infarction is due to many factors; influences on risk to the individual include habits, lifestyle and behavior, as well as weather, climate and other environmental components. Changing climate patterns make it especially important to understand how climatic variability may influence acute myocardial infarction mortality. Describe the relationship between climate variability and acute myocardial infarction mortality during the period 2001-2012 in Havana. An ecological time-series study was conducted. The universe comprised 23,744 deaths from acute myocardial infarction (ICD-10: I21-I22) in Havana residents from 2001 to 2012. Climate variability and seasonal anomalies were described using the Bultó-1 bioclimatic index (comprising variables of temperature, humidity, precipitation, and atmospheric pressure), along with series analysis to determine different seasonal-to-interannual climate variation signals. The role played by climate variables in acute myocardial infarction mortality was determined using factor analysis. The Mann-Kendall and Pettitt statistical tests were used for trend analysis with a significance level of 5%. The strong association between climate variability conditions described using the Bultó-1 bioclimatic index and acute myocardial infarctions accounts for the marked seasonal pattern in AMI mortality. The highest mortality rate occurred during the dry season, i.e., the winter months in Cuba (November-April), with peak numbers in January, December and March. The lowest mortality coincided with the rainy season, i.e., the summer months (May-October). A downward trend in total number of deaths can be seen starting with the change point in April 2009. Climate variability is inversely associated with an increase in acute myocardial infarction mortality as is shown by the Bultó-1 index. This inverse relationship accounts for acute myocardial infarction mortality's seasonal pattern.

Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices

USGS Publications Warehouse

Ault, Toby R.; Schwartz, Mark D.; Zurita-Milla, Raul; Weltzin, Jake F.; Betancourt, Julio L.

2015-01-01

Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous United States. This dataset is derived from daily interpolated meteorological data, and the results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from 20.8 to 21.6 days decade21, while first bloom index trends are between20.4 and 21.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal time scales. Finally, there is some potential for successful subseasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.

Trends and Natural Variability of Spring Onset in the Coterminous United States as Evaluated by a New Gridded Dataset of Spring Indices

NASA Astrophysics Data System (ADS)

Ault, T.; Schwartz, M. D.; Zurita-Milla, R.; Weltzin, J. F.; Betancourt, J. L.

2015-12-01

Climate change is expected to modify the timing of seasonal transitions this century, impacting wildlife migrations, ecosystem function, and agricultural activity. Tracking seasonal transitions in a consistent manner across space and through time requires indices that can be used for monitoring and managing biophysical and ecological systems during the coming decades. Here a new gridded dataset of spring indices is described and used to understand interannual, decadal, and secular trends across the coterminous US. This dataset is derived from daily interpolated meteorological data, and results are compared with historical station data to ensure the trends and variations are robust. Regional trends in the first leaf index range from -0.8 to -1.6 days per decade, while first bloom index trends are between -0.4 and -1.2 for most regions. However, these trends are modulated by interannual to multidecadal variations, which are substantial throughout the regions considered here. These findings emphasize the important role large-scale climate modes of variability play in modulating spring onset on interannual to multidecadal timescales. Finally, there is some potential for successful sub-seasonal forecasts of spring onset, as indices from most regions are significantly correlated with antecedent large-scale modes of variability.

Central Tropical Pacific Variability And ENSO Response To Changing Climate Boundary Conditions: Evidence From Individual Line Island Foraminifera

NASA Astrophysics Data System (ADS)

Rustic, G. T.; Polissar, P. J.; Ravelo, A. C.; White, S. M.

2017-12-01

The El Niño Southern Oscillation (ENSO) plays a dominant role in Earth's climate variability. Paleoceanographic evidence suggests that ENSO has changed in the past, and these changes have been linked to large-scale climatic shifts. While a close relationship between ENSO evolution and climate boundary conditions has been predicted, testing these predictions remains challenging. These climate boundary conditions, including insolation, the mean surface temperature gradient of the tropical Pacific, global ice volume, and tropical thermocline depth, often co-vary and may work together to suppress or enhance the ocean-atmosphere feedbacks that drive ENSO variability. Furthermore, suitable paleo-archives spanning multiple climate states are sparse. We have aimed to test ENSO response to changing climate boundary conditions by generating new reconstructions of mixed-layer variability from sedimentary archives spanning the last three glacial-interglacial cycles from the Central Tropical Pacific Line Islands, where El Niño is strongly expressed. We analyzed Mg/Ca ratios from individual foraminifera to reconstruct mixed-layer variability at discrete time intervals representing combinations of climatic boundary conditions from the middle Holocene to Marine Isotope Stage (MIS) 8. We observe changes in the mixed-layer temperature variability during MIS 5 and during the previous interglacial (MIS 7) showing significant reductions in ENSO amplitude. Differences in variability during glacial and interglacial intervals are also observed. Additionally, we reconstructed mixed-layer and thermocline conditions using multi-species Mg/Ca and stable isotope measurements to more fully characterize the state of the Central Tropical Pacific during these intervals. These reconstructions provide us with a unique view of Central Tropical Pacific variability and water-column structure at discrete intervals under varying boundary climate conditions with which to assess factors that shape ENSO variability.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Application of Remote Sensing to Assess the Impact of Short Term Climate Variability on Coastal Sedimentation

NASA Technical Reports Server (NTRS)

Menzel, W. Paul; Huh, Oscar K.; Walker, Nan

2004-01-01

The purpose of this joint University of Wisconsin (UW) and Louisiana State University (LSU) project has been to relate short term climate variation to response in the coastal zone of Louisiana in an attempt to better understand how the coastal zone is shaped by climate variation. Climate variation in this case largely refers to variation in surface wind conditions that affect wave action and water currents in the coastal zone. The primary region of focus was the Atchafalaya Bay and surrounding bays in the central coastal region of Louisiana. Suspended solids in the water column show response to wind systems both in quantity (through resuspension) and in the pattern of dispersement or transport. Wind systems associated with cold fronts are influenced by short term climate variation. Wind energy was used as the primary signature of climate variation in this study because winds are a significant influence on sediment transport in the micro-tidal Gilf of Mexico coastal zone. Using case studies, the project has been able to investigate the influence of short term climate variation on sediment transport. Wind energy data, collected daily for National Weather Service (NWS) stations at Lake Charles and New Orleans, LA, were used as an indicator of short term climate variation influence on seasonal time scales. A goal was to relate wind energy to coastal impact through sediment transport. This goal was partially accomplished by combining remote sensing and wind energy data. Daily high resolution remote sensing observations are needed to monitor the complex coastal zone environment, where winds, tides, and water level all interact to influence sediment transport. The NASA Earth Observing System (EOS) era brings hope for documenting and revealing response of the complex coastal transport mosaic through regular high spatial resolution observations from the Moderate resolution Imaging Spectrometer (MODIS) instrument. MODIS observations were sampled in this project for information content and should continue to be viewed as a resource for coastal zone monitoring. The project initialized the effort to transfer a suspended sediment concentration (SSC) algorithm to the MODIS platform for case 2 waters. MODIS enables monitoring of turbid coastal zones around the globe. The MODIS SSC algorithm requires refinements in the atmospheric aerosol contribution, sun glint influence, and designation of the sediment inherent optical properties (IOPs); the framework for continued development is in place with a plan to release the algorithm to the MODIS direct broadcast community.

How climate and weather affect the erosion risk in the northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Wahl, T.; Plant, N. G.

2015-12-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

Erosion risk in the northern Gulf of Mexico - the effects of climate and weather

NASA Astrophysics Data System (ADS)

Wahl, Thomas; Plant, Nathaniel G.; Long, Joseph W.

2016-04-01

Oceanographic variables such as mean sea level, tides, storm surges, and waves are drivers of erosion, and they act on different time scales ranging from hours (associated with weather) to seasonal and decadal variations and trends (associated with climate). Here we explore how the related sea-state conditions affect the erosion risk in the northern Gulf of Mexico for past and future climate scenarios. From the climate perspective we find that long-term trends in the relevant variables have caused an increase of ~30% in the erosion risk since the 1980s; at least half of this increase was due to changes in the wave climate. In the next decades, sea level rise will likely become the dominating driver and may, in combination with ongoing changes in the wave climate (and depending on the emission scenario), escalate the erosion risk by up to 300% over the next 30 years. We also find significant changes in the seasonal cycles of sea level and significant wave height, which have in combination caused a considerable increase of the erosion risk in summer and decrease in winter (superimposed onto the long-term trends). The influence of weather is assessed with a copula-based multivariate sea storm model in a Monte-Carlo framework; i.e. we simulate hundreds of thousands of artificial but physically consistent sea-state conditions to quantify how different our understanding of the present day erosion risk would be if we had seen more or less extreme combinations of the different sea-state parameters over the last three decades. We find, for example, that total water levels (tide + surge + wave run-up) associated with 100-year return periods may be underestimated by up to 30% and that the average number of impact hours - when total water levels exceeded the height of the dune toe (collision) or dune crest (overwash) - could have been up to 50% higher than what we inferred based on the actually observed oceanographic conditions. Assessing erosion risk in such a probabilistic way while accounting for non-stationarity due to climate variability and change can help decision makers and planners to implement improved monitoring and adaptation strategies for long-term sustainability of the coastline and barrier islands.

Climate | National Oceanic and Atmospheric Administration

Science.gov Websites

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Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

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

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

Leng, Guoyong

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

Violence and Disorder, School Climate, and PBIS: The Relationship among School Climate, Student Outcomes, and the Use of Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

Eacho, Thomas Christopher

2013-01-01

The primary purpose of this study was to examine the relationship between school climate and student outcome variables. The secondary purpose was to examine the relationship between the use of Positive Behavioral Interventions and Supports (PBIS) and the same student outcome variables. Variables depicting student perceptions of school climate,…

The HOLOANTAR project: Holocene environmental change in the Maritime Antarctic. Interactions between permafrost and the lacustrine environment

NASA Astrophysics Data System (ADS)

Oliva, Marc; Vieira, Gonçalo; Mora, Carla; Trindade, Alexandre; Agrela, Joao; Batista, Vanessa; Correia, António; Schaefer, Carlos; Simas, Felipe; Ramos, Miguel; De Pablo, Miguel Angel; Toro, Manuel; Antoniades, Dermot; Galan, Luis; Giralt, Santiago; Granados, Ignacio; Pla, Sergi; Serrano, Enrique

2013-04-01

The objective of this abstract is to present the HOLOANTAR project, a multidisciplinary research funded by the Portuguese Government. The project integrates 16 researchers from different international institutions (Portugal, Spain, Brazil and Uruguay).. The main purpose of HOLOANTAR is to infer the palaeoenvironmental evolution and associated climate variability occurred over the last millennia in ice-free areas of the Maritime Antarctica based on the study of lake sediments. The South Shetland Islands (SSI) are located in the northwestern tip of the Antarctic Peninsula, one of the Earth's regions that have experienced a stronger warming signal during the second half of the 20th century. In the ice-free areas of this archipelago the terrestrial ecosystem is supported by permafrost, though its reaction to climate change is still poorly known. However, in the recent years a very important effort took place to monitor the thermal state and characteristics of permafrost in order to study its response to the recent warming trend. Many international teams are involved on several of these long-term monitoring projects, but HOLOANTAR, in addition, pretends to offer a new integrated approach aiming to bridge the gap between contemporary and past changes in permafrost environments. HOLOANTAR project is based on two main hypotheses: a) A multi-proxy analysis of lake sediments will allow reconstructing the palaeoecological evolution in the Maritime Antarctic and the role played in it by permafrost and active layer dynamics, b) The detection of activity rates, spatial patterns and geographical controls of contemporary key-geomorphic processes and permafrost distribution, will allow defining their limiting climatic conditions that will be used to interpret the sedimentary record. This approach is innovative since it will focus on both present and past geomorphodynamics as keys for understanding the landscape evolution. In Byers Peninsula (Livingston), the largest ice-free area in the South Shetland Islands, where the environment is dominated by permafrost and active layer dynamics, climate variability should have induced modifications on the erosion rates at the slopes, mass movements, active layer thickness, biological activity, etc. In a context of fast rate of current change in mean annual air temperatures, it is possible that by studying similar features at different altitudes, different movement rates and an altitudinal/climatic boundary for their activity may be found, thus providing important applications for the palaeoenvironmental reconstruction. We will approach the two leading hypothesis in Byers environment by executing five main tasks: geomorphological mapping, geomorphological monitoring and permafrost distribution, sedimentological field work, laboratory analyses and palaeoenvironmental reconstruction. During the first field work campaign that took place in November-December 2012, up to four lakes were sampled. Future studies of these sediments will allow reconstructing the environment in Byers since the deglaciation of westernmost part of Livingston island.

Planning for an uncertain future - Monitoring, integration, and adaptation

USGS Publications Warehouse

Webb, Richard M. T.; Semmens, Darius J.

2009-01-01

The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

PubMed Central

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control.

PubMed

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2016-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

Effects of climatic factors and ecosystem responses on the inter-annual variability of evapotranspiration in a coniferous plantation in subtropical China.

PubMed

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003-2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003-2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May-June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation.

Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China

PubMed Central

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610

Glacier monitoring and glacier-climate interactions in the tropical Andes: A review

NASA Astrophysics Data System (ADS)

Veettil, Bijeesh Kozhikkodan; Wang, Shanshan; Florêncio de Souza, Sergio; Bremer, Ulisses Franz; Simões, Jefferson Cardia

2017-08-01

In this review, we summarized the evolution of glacier monitoring in the tropical Andes during the last few decades, particularly after the development of remote sensing and photogrammetry. Advantages and limitations of glacier mapping, applied so far, in Venezuela, Colombia, Ecuador, Peru and Bolivia are discussed in detail. Glacier parameters such as the equilibrium line altitude, snowline and mass balance were given special attention in understanding the complex cryosphere-climate interactions, particularly using remote sensing techniques. Glaciers in the inner and the outer tropics were considered separately based on the precipitation and temperature conditions within a new framework. The applicability of various methods to use glacier records to understand and reconstruct the tropical Andean climate between the Last Glacial Maximum (11,700 years ago) and the present is also explored in this paper. Results from various studies published recently were analyzed and we tried to understand the differences in the magnitudes of glacier responses towards the climatic perturbations in the inner tropics and the outer tropics. Inner tropical glaciers, particularly those in Venezuela and Colombia near the January Intertropical Convergence Zone (ITCZ), are more vulnerable to increase in temperature. Surface energy balance experiments show that outer tropical glaciers respond to precipitation variability very rapidly in comparison with the temperature variability, particularly when moving towards the subtropics. We also analyzed the gradients in glacier response to climate change from the Pacific coast towards the Amazon Basin as well as with the elevation. Based on the current trends synthesised from recent studies, it is hypothesized that the glaciers in the inner tropics and the southern wet outer tropics will disappear first as a response to global warming whereas glaciers in the northern wet outer tropics and dry outer tropics show resistance to warming trends due to the occurrence of cold phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) together. Mountain glaciers in Ecuador show less retreat in response to the warming trend, probably due to high altitudes (above 5750 m), in comparison to glaciers in Colombia and Venezuela. However, elevation-dependent warming (EDW) is a major concern in the tropical Andes. In a nutshell, smaller glaciers at lower altitudes in the inner tropics and the southern wet outer tropics near the Amazon Basin are disappearing faster than other glaciers in the tropical Andes.

Water-the Nation's Fundamental Climate Issue A White Paper on the U.S. Geological Survey Role and Capabilities

USGS Publications Warehouse

Lins, Harry F.; Hirsch, Robert M.; Kiang, Julie

2010-01-01

Of all the potential threats posed by climatic variability and change, those associated with water resources are arguably the most consequential for both society and the environment (Waggoner, 1990). Climatic effects on agriculture, aquatic ecosystems, energy, and industry are strongly influenced by climatic effects on water. Thus, understanding changes in the distribution, quantity and quality of, and demand for water in response to climate variability and change is essential to planning for and adapting to future climatic conditions. A central role of the U.S. Geological Survey (USGS) with respect to climate is to document environmental changes currently underway and to develop improved capabilities to predict future changes. Indeed, a centerpiece of the USGS role is a new Climate Effects Network of monitoring sites. Measuring the climatic effects on water is an essential component of such a network (along with corresponding effects on terrestrial ecosystems). The USGS needs to be unambiguous in communicating with its customers and stakeholders, and with officials at the Department of the Interior, that although modeling future impacts of climate change is important, there is no more critical role for the USGS in climate change science than that of measuring and describing the changes that are currently underway. One of the best statements of that mission comes from a short paper by Ralph Keeling (2008) that describes the inspiration and the challenges faced by David Keeling in operating the all-important Mauna Loa Observatory over a period of more than four decades. Ralph Keeling stated: 'The only way to figure out what is happening to our planet is to measure it, and this means tracking changes decade after decade and poring over the records.' There are three key ideas that are important to the USGS in the above-mentioned sentence. First, to understand what is happening requires measurement. While models are a tool for learning and testing our understanding, they are not a substitute for observations. The second key idea is that measurement needs to be done over a period of many decades. When viewing hydrologic records over time scales of a few years to a few decades, trends commonly appear. However, when viewed in the context of many decades to centuries, these short-term trends are recognized as being part of much longer term oscillations. Thus, while we might want to initiate monitoring of important aspects of our natural resources, the data that will prove to be most useful in the next few years are those records that already have long-term continuity. USGS streamflow and groundwater level data are excellent examples of such long-term records. These measured data span many decades, follow standard protocols for collection and quality assurance, and are stored in a database that provides access to the full period of record. The third point from the Keeling quote relates to the notion of ?poring over the records.? Important trends will not generally jump off the computer screen at us. Thoughtful analyses are required to get past a number of important but confounding influences in the record, such as the role of seasonal variation, changes in water management, or influences of quasi-periodic phenomena, such as El Ni?o-Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO). No organization is better situated to pore over the records than the USGS because USGS scientists know the data, quality-assure the data, understand the factors that influence the data, and have the ancillary information on the watersheds within which the data are collected. To fulfill the USGS role in understanding climatic variability and change, we need to continually improve and strengthen two of our key capabilities: (1) preserving continuity of long-term water data collection and (2) analyzing and interpreting water data to determine how the Nation's water resources are changing. Understanding change in water resources

Using ERA-Interim reanalysis for creating datasets of energy-relevant climate variables

NASA Astrophysics Data System (ADS)

Jones, Philip D.; Harpham, Colin; Troccoli, Alberto; Gschwind, Benoit; Ranchin, Thierry; Wald, Lucien; Goodess, Clare M.; Dorling, Stephen

2017-07-01

The construction of a bias-adjusted dataset of climate variables at the near surface using ERA-Interim reanalysis is presented. A number of different, variable-dependent, bias-adjustment approaches have been proposed. Here we modify the parameters of different distributions (depending on the variable), adjusting ERA-Interim based on gridded station or direct station observations. The variables are air temperature, dewpoint temperature, precipitation (daily only), solar radiation, wind speed, and relative humidity. These are available on either 3 or 6 h timescales over the period 1979-2016. The resulting bias-adjusted dataset is available through the Climate Data Store (CDS) of the Copernicus Climate Change Data Store (C3S) and can be accessed at present from ftp://ecem.climate.copernicus.eu. The benefit of performing bias adjustment is demonstrated by comparing initial and bias-adjusted ERA-Interim data against gridded observational fields.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Response-Guided Community Detection: Application to Climate Index Discovery

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

Bello, Gonzalo; Angus, Michael; Pedemane, Navya

Discovering climate indices-time series that summarize spatiotemporal climate patterns-is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability.more » Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.« less

Does internal climate variability overwhelm climate change signals in streamflow? The upper Po and Rhone basin case studies.

PubMed

Fatichi, S; Rimkus, S; Burlando, P; Bordoy, R

2014-09-15

Projections of climate change effects in streamflow are increasingly required to plan water management strategies. These projections are however largely uncertain due to the spread among climate model realizations, internal climate variability, and difficulties in transferring climate model results at the spatial and temporal scales required by catchment hydrology. A combination of a stochastic downscaling methodology and distributed hydrological modeling was used in the ACQWA project to provide projections of future streamflow (up to year 2050) for the upper Po and Rhone basins, respectively located in northern Italy and south-western Switzerland. Results suggest that internal (stochastic) climate variability is a fundamental source of uncertainty, typically comparable or larger than the projected climate change signal. Therefore, climate change effects in streamflow mean, frequency, and seasonality can be masked by natural climatic fluctuations in large parts of the analyzed regions. An exception to the overwhelming role of stochastic variability is represented by high elevation catchments fed by glaciers where streamflow is expected to be considerably reduced due to glacier retreat, with consequences appreciable in the main downstream rivers in August and September. Simulations also identify regions (west upper Rhone and Toce, Ticino river basins) where a strong precipitation increase in the February to April period projects streamflow beyond the range of natural climate variability during the melting season. This study emphasizes the importance of including internal climate variability in climate change analyses, especially when compared to the limited uncertainty that would be accounted for by few deterministic projections. The presented results could be useful in guiding more specific impact studies, although design or management decisions should be better based on reliability and vulnerability criteria as suggested by recent literature. Copyright © 2013 Elsevier B.V. All rights reserved.

Understanding controls on biotic assemblages and ecological status in Zambian rivers for the development of sustainable monitoring protocols

NASA Astrophysics Data System (ADS)

Kennedy, Michael; Gibbins, Chris; Lowe, Steven; Dallas, Helen; Taylor, Jonathan; Lang, Pauline; Saili, Kothelani; Sichingabula, Henry; Murphy, Kevin

2014-05-01

The water resources of Zambia are likely to experience increasing multiple pressures in the future as a result of very high predicted population growth, industrial development, land use change, and potentially, altered regional rainfall patterns. It is well known that rivers in tropical regions typically have a rich biodiversity, controlled in part by inter-annual variability in climate and discharge, and in part by local catchment conditions. However, till recently little country-wide work had had been carried out on the biota of Zambian rivers, and little was therefore known about the ecological status, or degree of catchment alteration of many of the rivers. To underpin sustainable water management, protocols have been developed to assess the ecological status of Zambian rivers. This paper describes the development of the protocols and their application to provide the first extensive assessment of the ecological status of rivers in the country. The protocols were designed to be simple, and hence rapid, easy and relatively inexpensive to apply. Status scores were derived for individual sites using sensitivity weightings from 3 major groups (macrophytes, diatoms and macroinvertebrates). The general approach was based on schemes used successfully elsewhere, with species and family sensitivity weightings modified so as be appropriate to Zambia. Modifications were based on a survey of 140 Zambian rivers, incorporating data on species distributions, physical habitat conditions and water quality. Analysis of historical data suggests that established Freshwater Ecoregions reflect hydro-climatic variability across Zambia. Survey data indicate that most of the spatial variation in biological assemblages across the country reflects these same hydro-climatic gradients, in addition to hydrochemical differences linked to geology. Site status scores suggest that rivers are generally in good health, although exceptions occur in some large urban areas and a small number of catchments with major industrial activity. Data form an important baseline against which to assess future changes related to population growth and climate change, and will therefore help inform policy within Zambia for sustainable river monitoring and management.

Climate Prediction Center - Outreach: 41st Annual Climate Diagnostics &

Science.gov Websites

the University of Maine Climate Change Institute and School of Earth and Climate Sciences and is co (drought, heat waves, severe weather, tropical cyclones) in the framework of climate variability and change and including the use of paleoclimate data. Arctic climate variability and change, and linkages to

Building Capacity to Use Earth Observations in Decision Making for Climate, Health, Agriculture and Natural Disasters

NASA Astrophysics Data System (ADS)

Robertson, A. W.; Ceccato, P.

2015-12-01

In order to fill the gaps existing in climate and public health, agriculture, natural disasters knowledge and practices, the International Research Institute for Climate and Society (IRI) has developed a Curriculum for Best Practices in Climate Information. This Curriculum builds on the experience of 10 years courses on 'Climate Information' and captures lessons and experiences from different tailored trainings that have been implemented in many countries in Africa, Asia and Latin America. In this presentation, we will provide examples of training activities we have developed to bring remote sensing products to monitor climatic and environmental information into decision processes that benefited users such as the World Health Organization, Ministries of Health, Ministries of Agriculture, Universities, Research Centers such as CIFOR and FIOCRUZ. The framework developed by IRI to provide capacity building is based on the IDEAS framework: Innovation (research) Around climate impacts, evaluation of interventions, and the value of climate information in reducing risks and maximizing opportunities Demonstration E.g. in-country GFCS projects in Tanzania and Malawi - or El Nino work in Ethiopia Education Academic and professional training efforts Advocacy This might focus on communication of variability and change? We are WHO collaborating center so are engaged through RBM/Global Malaria Programme Service ENACTS and Data library key to this. Country data better quality than NASA as incorporates all relevant station data and NASA products. This presentation will demonstrate how the IDEAS framework has been implemented and lessons learned.

Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.

Beneficial effects of restoration practices can be thwarted by climate extremes.

PubMed

Maccherini, Simona; Bacaro, Giovanni; Marignani, Michela

2018-06-01

The impacts of climate extremes on species, communities and ecosystems have become critical concerns to science and society. Under a changing climate, how restoration outcomes are affected by extreme climate variables is a largely unknown topic. We analyzed the effects of experimental factors (grazing and sowing of native species), extreme climate events (intense precipitation and extreme temperatures indexes) and their combination on the restoration progress of a dry, calcareous grassland in Tuscany (Italy) with a 1 year before/15 years continuous annual monitoring after, control/impact (BACI) experiment. Grazing had a beneficial effect on the diversity of the grassland, while sowing had a limited impact. The climatic index that most affected the entire plant community composition was the number of very heavy precipitation days. The interaction of grazing and extreme climatic indexes had a significant detrimental effect on restoration outcomes, increasing the cover of synanthropic and Cosmopolitan-Subcosmopolitan generalist species and decreasing the cover of more valuable species such endemic species. In the richest grazed plots, species richness showed a lower sensitivity to the average precipitation per wet day but in grazed site, restoration outcomes can be negatively influenced by the intensification of precipitation and temperature extremes. In a context of progressive tropicalization of the Mediterranean area, to assist managers setting achievable restoration goals, restoration practitioners should consider that climate extremes might interfere with the beneficial effects of restoration practices. Copyright © 2018 Elsevier B.V. All rights reserved.

Forecasting Glacier Evolution and Hindcasting Paleoclimates In Light of Mass Balance Nonlinearities

NASA Astrophysics Data System (ADS)

Malone, A.; Doughty, A. M.; MacAyeal, D. R.

2016-12-01

Glaciers are commonly used barometers of present and past climate change, with their variations often being linked to shifts in the mean climate. Climate variability within a unchanging mean state, however, can produce short term mass balance and glacier length anomalies, complicating this linkage. Also, the mass balance response to this variability can be nonlinear, possibly impacting the longer term state of the glacier. We propose a conceptual model to understand these nonlinearities and quantify their impacts on the longer term mass balance and glacier length. The relationship between mass balance and elevation, i.e. the vertical balance profile (VBP), illuminates these nonlinearities (Figure A). The VBP, given here for a wet tropical glacier, is piecewise, which can lead to different mass balance responses to climate anomalies of similar magnitude but opposite sign. We simulate the mass balance response to climate variability by vertically (temperature anomalies) and horizontally (precipitation anomalies) transposing the VBP for the mean climate (Figure A). The resulting anomalous VBP is the superposition of the two translations. We drive a 1-D flowline model with 10,000 years of anomalous VBPs. The aggregate VBP for the mean climate including variability differs from the VBP for the mean climate excluding variability, having a higher equilibrium line altitude (ELA) and a negative mass balance (Figure B). Accordingly, the glacier retreats, and the equilibrium glacier length for the aggregate VBP is the same as the mean length from the 10,000 year flowline simulation (Figure C). The magnitude of the VBP shift and glacier retreat increases with greater temperature variability and larger discontinuities in the VBP slope. These results highlight the importance of both the climate mean and variability in determining the longer term state of the glacier. Thus, forecasting glacier evolution or hindcasting past climates should also include representation of climate variability.

When and where to move: Dynamic occupancy models explain the range dynamics of a food nomadic bird under climate and land cover change.

PubMed

Kalle, Riddhika; Ramesh, Tharmalingam; Downs, Colleen T

2018-01-01

Globally, long-term research is critical to monitor the responses of tropical species to climate and land cover change at the range scale. Citizen science surveys can reveal the long-term persistence of poorly known nomadic tropical birds occupying fragmented forest patches. We applied dynamic occupancy models to 13 years (2002-2014) of citizen science-driven presence/absence data on Cape parrot (Poicephalus robustus), a food nomadic bird endemic to South Africa. We modeled its underlying range dynamics as a function of resource distribution, and change in climate and land cover through the estimation of colonization and extinction patterns. The range occupancy of Cape parrot changed little over time (ψ = 0.75-0.83) because extinction was balanced by recolonization. Yet, there was considerable regional variability in occupancy and detection probability increased over the years. Colonizations increased with warmer temperature and area of orchards, thus explaining their range shifts southeastwards in recent years. Although colonizations were higher in the presence of nests and yellowwood trees (Afrocarpus and Podocarpus spp.), the extinctions in small forest patches (≤227 ha) and during low precipitation (≤41 mm) are attributed to resource constraints and unsuitable climatic conditions. Loss of indigenous forest cover and artificial lake/water bodies increased extinction probabilities of Cape parrot. The land use matrix (fruit farms, gardens, and cultivations) surrounding forest patches provides alternative food sources, thereby facilitating spatiotemporal colonization and extinction in the human-modified matrix. Our models show that Cape parrots are vulnerable to extreme climatic conditions such as drought which is predicted to increase under climate change. Therefore, management of optimum sized high-quality forest patches is essential for long-term survival of Cape parrot populations. Our novel application of dynamic occupancy models to long-term citizen science monitoring data unfolds the complex relationships between the environmental dynamics and range fluctuations of this food nomadic species. © 2017 John Wiley & Sons Ltd.

Impacts of climate change and variability on transportation systems and infrastructure : Gulf Coast study, phase 2 : task 2 : climate variability and change in Mobile, Alabama.

DOT National Transportation Integrated Search

2012-09-01

Despite increasing confidence in global climate change projections in recent years, projections of : climate effects at local scales remains scarce. Location-specific risks to transportation systems : imposed by changes in climate are not yet well kn...

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas

2016-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.

Establishing a baseline precipitation and temperature regime for the Guianas from observations and reanalysis data

NASA Astrophysics Data System (ADS)

Bovolo, C. Isabella; Pereira, Ryan; Parkin, Geoff; Wagner, Thomas

2010-05-01

The tropical rainforests of the Guianas, north of the Amazon, are home to several Amerindian communities, hold high levels of biodiversity and, importantly, remain some of the world's most pristine and intact rainforests. Not only do they have important functions in the global carbon cycle, but they regulate the local and regional climate and help generate rain over vast distances. Despite their significance however, the climate and hydrology of this region is poorly understood. It is important to establish the current climate regime of the area as a baseline against which any impacts of future climate change or deforestation can be measured but observed historical climate datasets are generally sparse and of low quality. Here we examine the available precipitation and temperature datasets for the region and derive tentative precipitation and temperature maps focussed on Guyana. To overcome the limitations in the inadequate observational data coverage we also make use of a reanalysis dataset from the European Centre for Medium-range Weather Forecasts (ECMWF). The ECMWF ERA40 dataset comprises a spatially consistent global historical climate for the period 1957-2002 at a ~125 km2 (1.125 degree) resolution at the equator and is particularly valuable for establishing the climate of data-poor areas. Once validated for the area of interest, ERA40 is used to determine the precipitation and temperature regime of the Guianas. Grid-cell by grid-cell analysis provides a complete picture of spatial patterns of averaged monthly precipitation variability across the area, vital for establishing a basis from which to compare any future effects of climate change. This is the first comprehensive study of the recent historical climate and its variability in this area, placing a new hydroclimate monitoring and research program at the Iwokrama International Centre for Rainforest Conservation and Development, Guyana, into the broader climate context. Mean differences (biases) and annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.

Change in the magnitude and mechanisms of global temperature variability with warming.

PubMed

Brown, Patrick T; Ming, Yi; Li, Wenhong; Hill, Spencer A

2017-01-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

Change in the Magnitude and Mechanisms of Global Temperature Variability with Warming

NASA Astrophysics Data System (ADS)

Brown, P. T.; Ming, Y.; Li, W.; Hill, S. A.

2017-12-01

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modeling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual preindustrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.

The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

NASA Astrophysics Data System (ADS)

Kay, J. E.; Deser, C.

2016-12-01

While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.

Ocean Monitoring Indicators for the Mediterranean Sea biogeochemistry derived from a high-resolution reanalysis

NASA Astrophysics Data System (ADS)

Solidoro, Cosimo; Cossarini, Gianpiero; Bolzon, Giorgio; Salon, Stefano; Teruzzi, Anna; Lazzari, Paolo; Crise, Alessandro

2017-04-01

In recent years the interest in multi-decadal reanalyses of the status of the Mediterranean marine ecosystem has been rising constantly, also in light of the need of information for a proper implementation of European directives (e.g. MSFD). State-of-art reanalyses of the Mediterranean Sea biogeochemistry - being an optimal integration of multi-platforms data and numerical models - constitute an extremely relevant source of information in evaluating the ecosystem status at basin and sub-basin scale. Furthermore, they provide highly valuable data to be used as boundary conditions for local studies. The objective of this work is to produce sensible environmental indicators useful to characterize the environmental status of the Mediterranean starting from an upgraded high-resolution reanalysis of Mediterranean Sea biogeochemistry delivered in the frame of the Copernicus Marine Environment Monitoring Services (CMEMS). The reanalysis was qualified by a comparison against several available data sets, in terms of the main surface and sub-surface biogeochemical essential climate variables (chlorophyll, carbon dioxide partial pressure, ocean acidity, nutrients, oxygen). The reanalysis outputs reproduced spatial patterns, seasonal cycle and inter-annual variability of the assessed variables, allowing for a proper description of recent trends and present status of the Mediterranean Sea biogeochemistry. Our results confirm the vision of the Mediterranean as a mainly oligotrophic ecosystem with the presence of significant biogeochemical gradients from the eastern to the western sub-basins (e.g. in chlorophyll, nutrients, primary production). Our reanalysis can be used to contribute estimating eutrophication MFSD descriptors, atmospheric carbon sequestration fluxes, first assessment of potential resources available for the higher trophic levels and more. Indeed, the reanalysis data set provides a suitable basis for the estimation of the so-called Ocean Monitoring Indicators (OMIs) and Essential Biogeochemical Variables (EBVs), developed within CMEMS for the Ocean State Report. Some of the OMIs that have been proposed so far for the Mediterranean biogeochemistry include indicators describing: the influence of physical forcing on ecosystem (e.g. mixed layer depth); the basic ecosystem status, functioning and changes (e.g. nutrient concentration, oxygen content, chlorophyll and their variability at monthly/seasonal/annual/decadal scale); the ecosystem health (e.g. anoxia indicators, N/P ratio); the relation of ocean ecosystem with fisheries (e.g. integrated primary production, phyto/zooplankton biomasses) and climate change (e.g. acidification, CO2 fluxes). Recent results in the Mediterranean Sea OMIs investigation will be widely discussed in our contribution.

LAMPPOST: A Mnemonic Device for Teaching Climate Variables

ERIC Educational Resources Information Center

Fahrer, Chuck; Harris, Dan

2004-01-01

This article introduces the word "LAMPPOST" as a mnemonic device to aid in the instruction of climate variables. It provides instructors with a framework for discussing climate patterns that is based on eight variables: latitude, altitude, maritime influence and continentality, pressure systems, prevailing winds, ocean currents, storms, and…

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

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

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

Alternating high and low climate variability: The context of natural selection and speciation in Plio-Pleistocene hominin evolution.

PubMed

Potts, Richard; Faith, J Tyler

2015-10-01

Interaction of orbital insolation cycles defines a predictive model of alternating phases of high- and low-climate variability for tropical East Africa over the past 5 million years. This model, which is described in terms of climate variability stages, implies repeated increases in landscape/resource instability and intervening periods of stability in East Africa. It predicts eight prolonged (>192 kyr) eras of intensified habitat instability (high variability stages) in which hominin evolutionary innovations are likely to have occurred, potentially by variability selection. The prediction that repeated shifts toward high climate variability affected paleoenvironments and evolution is tested in three ways. In the first test, deep-sea records of northeast African terrigenous dust flux (Sites 721/722) and eastern Mediterranean sapropels (Site 967A) show increased and decreased variability in concert with predicted shifts in climate variability. These regional measurements of climate dynamics are complemented by stratigraphic observations in five basins with lengthy stratigraphic and paleoenvironmental records: the mid-Pleistocene Olorgesailie Basin, the Plio-Pleistocene Turkana and Olduvai Basins, and the Pliocene Tugen Hills sequence and Hadar Basin--all of which show that highly variable landscapes inhabited by hominin populations were indeed concentrated in predicted stages of prolonged high climate variability. Second, stringent null-model tests demonstrate a significant association of currently known first and last appearance datums (FADs and LADs) of the major hominin lineages, suites of technological behaviors, and dispersal events with the predicted intervals of prolonged high climate variability. Palynological study in the Nihewan Basin, China, provides a third test, which shows the occupation of highly diverse habitats in eastern Asia, consistent with the predicted increase in adaptability in dispersing Oldowan hominins. Integration of fossil, archeological, sedimentary, and paleolandscape evidence illustrates the potential influence of prolonged high variability on the origin and spread of critical adaptations and lineages in the evolution of Homo. The growing body of data concerning environmental dynamics supports the idea that the evolution of adaptability in response to climate and overall ecological instability represents a unifying theme in hominin evolutionary history. Published by Elsevier Ltd.

Remote Assessment of Forest Ecosystem Stress (RAFES): Development of a Real Time Decision Support Tool for the Eastern U.S

NASA Astrophysics Data System (ADS)

Clinton, B.; Vose, J.; Novick, K.; Liu, Y.

2011-12-01

Drier and warmer conditions predicted with climate change models are likely to significantly impact forest ecosystems over the next several decades. The U.S. has experienced significant droughts over the past several years that have increased the susceptibility of forests to insect outbreaks, disease, and wildfire. Weather data collected with traditional approaches provide an indirect measure of drought or temperature stress; however, the significance of short-term or prolonged climate-related stress varies considerably across the landscape as topography, elevations, edaphic condition and antecedent conditions vary. This limits the capacity of land managers to anticipate and initiate management activities that could offset the impacts of climate-related forest stress. Decision support tools are needed that allow fine scale monitoring of stress conditions in forest ecosystems in real time to help land managers evaluate response strategies. To assist land managers in managing the impacts of climate change, we are developing a stress monitoring and decision support system across multiple sites in the eastern U.S. that (1) provides remote data capture of environmental parameters that quantify climate-related forest stress, (2) links remotely captured data with physiologically-based indices of tree water stress, and (3) provides a PC-based analytical tool for land managers to monitor and assess the severity of climate-related stress. Currently the network represents southern coastal plain pine plantation, Atlantic coastal flatwoods mixed pine-hardwood, southern piedmont upland mixed pine-hardwood, southern Appalachian dry ridge and mesic riparian, southern Arkansas managed mature pine, and northern Minnesota mature aspen. The strategy for selecting additional sites for the network will be a focus on at-risk ecosystems deemed particularly vulnerable to the affects of predicted climate change such as those in ecotonal transition regions, or those at the fringes of their ranges. The sensor arrays at each site detect water and temperature stress variables and transmit those data to a field office. Sensors include air and soil temperature, relative humidity, fuel moisture and temperature, xylem sap flux density, soil moisture and matric potential, precipitation, and solar radiation. Data are transmitted in real-time to the NOAA Geostationary Operational Environmental Satellite (GOES). A PC-based software program that downloads monitoring data from the GOES satellite, analyzes the data, and provides the land manager with an assessment of climate-related stress conditions and potential forest health threat levels in real time is under development. Data collection began in early 2010 on most sites, and we have at least one year of data from all nine sites within the network. We are currently comparing estimates of stress levels on our sites with estimates of stress from common drought indices. For this presentation, we are comparing and contrasting four sites representing an environmental gradient within the network.

Beyond a Climate-Centric View of Plant Distribution: Edaphic Variables Add Value to Distribution Models

PubMed Central

Beauregard, Frieda; de Blois, Sylvie

2014-01-01

Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change. PMID:24658097

Beyond a climate-centric view of plant distribution: edaphic variables add value to distribution models.

PubMed

Beauregard, Frieda; de Blois, Sylvie

2014-01-01

Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change.

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

PubMed Central

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

2017-01-01

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

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

NASA Technical Reports Server (NTRS)

Hoffert, M. I.

1986-01-01

Langley, in the late nineteenth century, attempted to measure solar irradiance over an extended period of time in order to detect changes. The problem with this and other early attempts was that ground based measurements are not sufficiently accurate to measure solar irradiance fluctuations, which are on the order of 0.1%. It was not until the Active Cavity Radiometer Irradiance Monitor (ACRIM) experiment on the NASA Solar Maximum Mission (SMM) was launched in 1980 that continuous data with precision 0.1% was available.

Long-term Water Table Monitoring of Rio Grande Riparian Ecosystems for Restoration Potential Amid Hydroclimatic Challenges.

PubMed

Thibault, James R; Cleverly, James R; Dahm, Clifford N

2017-12-01

Hydrological processes drive the ecological functioning and sustainability of cottonwood-dominated riparian ecosystems in the arid southwestern USA. Snowmelt runoff elevates groundwater levels and inundates floodplains, which promotes cottonwood germination. Once established, these phreatophytes rely on accessible water tables (WTs). In New Mexico's Middle Rio Grande corridor diminished flooding and deepening WTs threaten native riparian communities. We monitored surface flows and riparian WTs for up to 14 years, which revealed that WTs and surface flows, including peak snowmelt discharge, respond to basin climate conditions and resource management. WT hydrographs influence the composition of riparian communities and can be used to assess if potential restoration sites meet native vegetation tolerances for WT depths, rates of recession, and variability throughout their life stages. WTs were highly variable in some sites, which can preclude native vegetation less adapted to deep drawdowns during extended droughts. Rates of WT recession varied between sites and should be assessed in regard to recruitment potential. Locations with relatively shallow WTs and limited variability are likely to be more viable for successful restoration. Suitable sites have diminished greatly as the once meandering Rio Grande has been constrained and depleted. Increasing demands on water and the presence of invasive vegetation better adapted to the altered hydrologic regime further impact native riparian communities. Long-term monitoring over a range of sites and hydroclimatic extremes reveals attributes that can be evaluated for restoration potential.

Long-term Water Table Monitoring of Rio Grande Riparian Ecosystems for Restoration Potential Amid Hydroclimatic Challenges

NASA Astrophysics Data System (ADS)

Thibault, James R.; Cleverly, James R.; Dahm, Clifford N.

2017-12-01

Hydrological processes drive the ecological functioning and sustainability of cottonwood-dominated riparian ecosystems in the arid southwestern USA. Snowmelt runoff elevates groundwater levels and inundates floodplains, which promotes cottonwood germination. Once established, these phreatophytes rely on accessible water tables (WTs). In New Mexico's Middle Rio Grande corridor diminished flooding and deepening WTs threaten native riparian communities. We monitored surface flows and riparian WTs for up to 14 years, which revealed that WTs and surface flows, including peak snowmelt discharge, respond to basin climate conditions and resource management. WT hydrographs influence the composition of riparian communities and can be used to assess if potential restoration sites meet native vegetation tolerances for WT depths, rates of recession, and variability throughout their life stages. WTs were highly variable in some sites, which can preclude native vegetation less adapted to deep drawdowns during extended droughts. Rates of WT recession varied between sites and should be assessed in regard to recruitment potential. Locations with relatively shallow WTs and limited variability are likely to be more viable for successful restoration. Suitable sites have diminished greatly as the once meandering Rio Grande has been constrained and depleted. Increasing demands on water and the presence of invasive vegetation better adapted to the altered hydrologic regime further impact native riparian communities. Long-term monitoring over a range of sites and hydroclimatic extremes reveals attributes that can be evaluated for restoration potential.

Controlled soil warming powered by alternative energy for remote field sites.

PubMed

Johnstone, Jill F; Henkelman, Jonathan; Allen, Kirsten; Helgason, Warren; Bedard-Haughn, Angela

2013-01-01

Experiments using controlled manipulation of climate variables in the field are critical for developing and testing mechanistic models of ecosystem responses to climate change. Despite rapid changes in climate observed in many high latitude and high altitude environments, controlled manipulations in these remote regions have largely been limited to passive experimental methods with variable effects on environmental factors. In this study, we tested a method of controlled soil warming suitable for remote field locations that can be powered using alternative energy sources. The design was tested in high latitude, alpine tundra of southern Yukon Territory, Canada, in 2010 and 2011. Electrical warming probes were inserted vertically in the near-surface soil and powered with photovoltaics attached to a monitoring and control system. The warming manipulation achieved a stable target warming of 1.3 to 2 °C in 1 m(2) plots while minimizing disturbance to soil and vegetation. Active control of power output in the warming plots allowed the treatment to closely match spatial and temporal variations in soil temperature while optimizing system performance during periods of low power supply. Active soil heating with vertical electric probes powered by alternative energy is a viable option for remote sites and presents a low-disturbance option for soil warming experiments. This active heating design provides a valuable tool for examining the impacts of soil warming on ecosystem processes.

Disease in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

McMahon, T. A.; Raffel, T.; Rohr, J. R.; Halstead, N.; Venesky, M.; Romansic, J.

2014-12-01

Global climate change is shifting the dynamics of infectious diseases of humans and wildlife with potential adverse consequences for disease control. Despite this, the role of global climate change in the decline of biodiversity and the emergence of infectious diseases remains controversial. Climate change is expected to increase climate variability in addition to increasing mean temperatures, making climate less predictable. However, few empirical or theoretical studies have considered the effects of climate variability or predictability on disease, despite it being likely that hosts and parasites will have differential responses to climatic shifts. Here we present a theoretical framework for how temperature variation and its predictability influence disease risk by affecting host and parasite acclimation responses. Laboratory experiments and field data on disease-associated frog declines in Latin America support this framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis (Bd). Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was inconsistent with the pattern of Bd growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. Consistent with our laboratory experiments, increased regional temperature variability associated with global El Niño climatic events was the best predictor of widespread amphibian losses in the genus Atelopus. Thus, incorporating the effects of small-scale temporal variability in climate can greatly improve our ability to predict the effects of climate change on disease.

Satellite remote sensing for modeling and monitoring of water quality in the Great Lakes

NASA Astrophysics Data System (ADS)

Coffield, S. R.; Crosson, W. L.; Al-Hamdan, M. Z.; Barik, M. G.

2017-12-01

Consistent and accurate monitoring of the Great Lakes is critical for protecting the freshwater ecosystems, quantifying the impacts of climate change, understanding harmful algal blooms, and safeguarding public health for the millions who rely on the Lakes for drinking water. While ground-based monitoring is often hampered by limited sampling resolution, satellite data provide surface reflectance measurements at much more complete spatial and temporal scales. In this study, we implemented NASA data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to build robust water quality models. We developed and validated models for chlorophyll-a, nitrogen, phosphorus, and turbidity based on combinations of the six MODIS Ocean Color bands (412, 443, 488, 531, 547, and 667nm) for 2003-2016. Second, we applied these models to quantify trends in water quality through time and in relation to changing land cover, runoff, and climate for six selected coastal areas in Lakes Michigan and Erie. We found strongest models for chlorophyll-a in Lake Huron (R2 = 0.75), nitrogen in Lake Ontario (R2=0.66), phosphorus in Lake Erie (R2=0.60), and turbidity in Lake Erie (R2=0.86). These offer improvements over previous efforts to model chlorophyll-a while adding nitrogen, phosphorus, and turbidity. Mapped water quality parameters showed high spatial variability, with nitrogen concentrated largely in Superior and coastal Michigan and high turbidity, phosphorus, and chlorophyll near urban and agricultural areas of Erie. Temporal analysis also showed concurrence of high runoff or precipitation and nitrogen in Lake Michigan offshore of wetlands, suggesting that water quality in these areas is sensitive to changes in climate.

The Dynamics of Vulnerability and Implications for Climate Change Adaptation: Lessons from Urban Water Management

NASA Astrophysics Data System (ADS)

Dilling, L.; Daly, M.; Travis, W.; Wilhelmi, O.; Klein, R.; Kenney, D.; Ray, A. J.; Miller, K.

2013-12-01

Recent reports and scholarship have suggested that adapting to current climate variability may represent a "no regrets" strategy for adapting to climate change. Filling "adaptation deficits" and other approaches that rely on addressing current vulnerabilities are of course helpful for responding to current climate variability, but we find here that they are not sufficient for adapting to climate change. First, following a comprehensive review and unique synthesis of the natural hazards and climate adaptation literatures, we advance six reasons why adapting to climate variability is not sufficient for adapting to climate change: 1) Vulnerability is different at different levels of exposure; 2) Coping with climate variability is not equivalent to adaptation to longer term change; 3) The socioeconomic context for vulnerability is constantly changing; 4) The perception of risk associated with climate variability does not necessarily promote adaptive behavior in the face of climate change; 5) Adaptations made to short term climate variability may reduce the flexibility of the system in the long term; and 6) Adaptive actions may shift vulnerabilities to other parts of the system or to other people. Instead we suggest that decision makers faced with choices to adapt to climate change must consider the dynamics of vulnerability in a connected system-- how choices made in one part of the system might impact other valued outcomes or even create new vulnerabilities. Furthermore we suggest that rather than expressing climate change adaptation as an extension of adaptation to climate variability, the research and practice communities would do well to articulate adaptation as an imperfect policy, with tradeoffs and consequences and that decisions be prioritized to preserve flexibility be revisited often as climate change unfolds. We then present the results of a number of empirical studies of decision making for drought in urban water systems in the United States to understand: a) the variety of actions taken; b) the limitations of actions available to water managers; and c) the effectiveness of actions taken to date. Time permitting, we briefly present the results of 3 in-depth case studies of drought response and current perception of preparedness with respect to future drought and climate change among urban water system managers. We examine the role of governance, system connectivity, public perceptions and other factors in driving decision making and outcomes.

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.

The role of climate variability in extreme floods in Europe

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Aerts, Jeroen C. J. H.; Jongman, Brenden; Ward, Philip J.

2017-04-01

Between 1980 and 2015, Europe experienced 18% of worldwide weather-related loss events, which accounted for over US500 billion in damage. Consequently, it is urgent to further develop adaptation strategies to mitigate the consequences of weather-related disasters, such as floods. Europe's capability to prepare for such disasters is challenged by a large range of uncertainties and a limited understanding of the driving forces of hydrometeorological hazards. One of the major sources of uncertainty is the relationship between climate variability and weather-related losses. Previous studies show that climate variability drives temporal changes in hydrometereological variables in Europe. However, their influence on flood risk has received little attention. We investigated the influence of the positive and negative phases of El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO), on the seasonal frequency and intensity of extreme rainfall, and anomalies in flood occurrence and damage compared to the neutral phases of the indices of climate variability. Using statistical methods to analyze relationships between the indices of climate variability and four indicators of flooding, we found that positive and negative phases of NAO and AO are associated with more (or less) frequent and intense seasonal extreme rainfall over large areas of Europe. The relationship between ENSO and both the occurrence of extreme rainfall and intensity of extreme rainfall in Europe is much smaller than the relationship with NAO or AO, but still significant in some regions. We observe that flood damage and flood occurrence have strong links with climate variability, especially in southern and eastern Europe. Therefore, when investigating flooding across Europe, all three indices of climate variability should be considered. Seasonal forecasting of flooding could be enhanced by the inclusion of climate variability indicators .

The IRI/LDEO Climate Data Library: Helping People use Climate Data

NASA Astrophysics Data System (ADS)

Blumenthal, M. B.; Grover-Kopec, E.; Bell, M.; del Corral, J.

2005-12-01

The IRI Climate Data Library (http://iridl.ldeo.columbia.edu/) is a library of datasets. By library we mean a collection of things, collected from both near and far, designed to make them more accessible for the library's users. Our datasets come from many different sources, many different "data cultures", many different formats. By dataset we mean a collection of data organized as multidimensional dependent variables, independent variables, and sub-datasets, along with the metadata (particularly use-metadata) that makes it possible to interpret the data in a meaningful manner. Ingrid, which provides the infrastructure for the Data Library, is an environment that lets one work with datasets: read, write, request, serve, view, select, calculate, transform, ... . It hides an extraordinary amount of technical detail from the user, letting the user think in terms of manipulations to datasets rather that manipulations of files of numbers. Among other things, this hidden technical detail could be accessing data on servers in other places, doing only the small needed portion of an enormous calculation, or translating to and from a variety of formats and between "data cultures". These operations are presented as a collection of virtual directories and documents on a web server, so that an ordinary web client can instantiate a calculation simply by requesting the resulting document or image. Building on this infrastructure, we (and others) have created collections of dynamically-updated images to faciliate monitoring aspects of the climate system, as well as linking these images to the underlying data. We have also created specialized interfaces to address the particular needs of user groups that IRI needs to support.

Phenological adjustment in arctic bird species: relative importance of snow melt and ecological factors

USGS Publications Warehouse

Liebezeit, Joseph R.; Gurney, K. E. B.; Budde, Michael E.; Zack, Steve; Ward, David H.

2014-01-01

Previous studies have documented advancement in clutch initiation dates (CIDs) in response to climate change, most notably for temperate-breeding passerines. Despite accelerated climate change in the Arctic, few studies have examined nest phenology shifts in arctic breeding species. We investigated whether CIDs have advanced for the most abundant breeding shorebird and passerine species at a long-term monitoring site in arctic Alaska. We pooled data from three additional nearby sites to determine the explanatory power of snow melt and ecological variables (predator abundance, green-up) on changes in breeding phenology. As predicted, all species (semipalmated sandpiper, Calidris pusilla, pectoral sandpiper, Calidris melanotos, red-necked phalarope, Phalaropus lobatus, red phalarope, Phalaropus fulicarius, Lapland longspur, Calcarius lapponicus) exhibited advanced CIDs ranging from 0.40 to 0.80 days/year over 9 years. Timing of snow melt was the most important variable in explaining clutch initiation advancement (“climate/snow hypothesis”) for four of the five species, while green-up was a much less important explanatory factor. We found no evidence that high predator abundances led to earlier laying dates (“predator/re-nest hypothesis”). Our results support previous arctic studies in that climate change in the cryosphere will have a strong impact on nesting phenology although factors explaining changes in nest phenology are not necessarily uniform across the entire Arctic. Our results suggest some arctic-breeding shorebird and passerine species are altering their breeding phenology to initiate nesting earlier enabling them to, at least temporarily, avoid the negative consequences of a trophic mismatch.

Malaria early warning tool: linking inter-annual climate and malaria variability in northern Guadalcanal, Solomon Islands.

PubMed

Smith, Jason; Tahani, Lloyd; Bobogare, Albino; Bugoro, Hugo; Otto, Francis; Fafale, George; Hiriasa, David; Kazazic, Adna; Beard, Grant; Amjadali, Amanda; Jeanne, Isabelle

2017-11-21

Malaria control remains a significant challenge in the Solomon Islands. Despite progress made by local malaria control agencies over the past decade, case rates remain high in some areas of the country. Studies from around the world have confirmed important links between climate and malaria transmission. This study focuses on understanding the links between malaria and climate in Guadalcanal, Solomon Islands, with a view towards developing a climate-based monitoring and early warning for periods of enhanced malaria transmission. Climate records were sourced from the Solomon Islands meteorological service (SIMS) and historical malaria case records were sourced from the National Vector-Borne Disease Control Programme (NVBDCP). A declining trend in malaria cases over the last decade associated with improved malaria control was adjusted for. A stepwise regression was performed between climate variables and climate-associated malaria transmission (CMT) at different lag intervals to determine where significant relationships existed. The suitability of these results for use in a three-tiered categorical warning system was then assessed using a Mann-Whitney U test. Of the climate variables considered, only rainfall had a consistently significant relationship with malaria in North Guadalcanal. Optimal lag intervals were determined for prediction using R 2 skill scores. A highly significant negative correlation (R = - 0.86, R 2  = 0.74, p < 0.05, n = 14) was found between October and December rainfall at Honiara and CMT in northern Guadalcanal for the subsequent January-June. This indicates that drier October-December periods are followed by higher malaria transmission periods in January-June. Cross-validation emphasized the suitability of this relationship for forecasting purposes [Formula: see text]  as did Mann-Whitney U test results showing that rainfall below or above specific thresholds was significantly associated with above or below normal malaria transmission, respectively. This study demonstrated that rainfall provides the best predictor of malaria transmission in North Guadalcanal. This relationship is thought to be underpinned by the unique hydrological conditions in northern Guadalcanal which allow sandbars to form across the mouths of estuaries which act to develop or increase stagnant brackish marshes in low rainfall periods. These are ideal habitats for the main mosquito vector, Anopheles farauti. High rainfall accumulations result in the flushing of these habitats, reducing their viability. The results of this study are now being used as the basis of a malaria early warning system which has been jointly implemented by the SIMS, NVBDCP and the Australian Bureau of Meteorology.

Selecting climate change scenarios using impact-relevant sensitivities

Treesearch

Julie A. Vano; John B. Kim; David E. Rupp; Philip W. Mote

2015-01-01

Climate impact studies often require the selection of a small number of climate scenarios. Ideally, a subset would have simulations that both (1) appropriately represent the range of possible futures for the variable/s most important to the impact under investigation and (2) come from global climate models (GCMs) that provide plausible results for future climate in the...

Climate Controls AM Fungal Distributions from Global to Local Scales

NASA Astrophysics Data System (ADS)

Kivlin, S. N.; Hawkes, C.; Muscarella, R.; Treseder, K. K.; Kazenel, M.; Lynn, J.; Rudgers, J.

2016-12-01

Arbuscular mycorrhizal (AM) fungi have key functions in terrestrial biogeochemical processes; thus, determining the relative importance of climate, edaphic factors, and plant community composition on their geographic distributions can improve predictions of their sensitivity to global change. Local adaptation by AM fungi to plant hosts, soil nutrients, and climate suggests that all of these factors may control fungal geographic distributions, but their relative importance is unknown. We created species distribution models for 142 AM fungal taxa at the global scale with data from GenBank. We compared climate variables (BioClim and soil moisture), edaphic variables (phosphorus, carbon, pH, and clay content), and plant variables using model selection on models with (1) all variables, (2) climatic variables only (including soil moisture) and (3) resource-related variables only (all other soil parameters and NPP) using the MaxEnt algorithm evaluated with ENMEval. We also evaluated whether drivers of AM fungal distributions were phylogenetically conserved. To test whether global correlates of AM fungal distributions were reflected at local scales, we then surveyed AM fungi in nine plant hosts along three elevation gradients in the Upper Gunnison Basin, Colorado, USA. At the global scale, the distributions of 55% of AM fungal taxa were affected by both climate and soil resources, whereas 16% were only affected by climate and 29% were only affected by soil resources. Even for AM fungi that were affected by both climate and resources, the effects of climatic variables nearly always outweighed those of resources. Soil moisture and isothermality were the main climatic and NPP and soil carbon the main resource related factors influencing AM fungal distributions. Distributions of closely related AM fungal taxa were similarly affected by climate, but not by resources. Local scale surveys of AM fungi across elevations confirmed that climate was a key driver of AM fungal composition and root colonization, with weaker influences of plant identity and soil nutrients. These two studies across scales suggest prevailing effects of climate on AM fungal distributions. Thus, incorporating climate when forecasting future ranges of AM fungi will enhance predictions of AM fungal abundance and associated ecosystem functions.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Near Real-Time Flood Monitoring and Impact Assessment Systems. Chapter 6; [Case Study: 2011 Flooding in Southeast Asia

NASA Technical Reports Server (NTRS)

Ahamed, Aakash; Bolten, John; Doyle, C.; Fayne, Jessica

2016-01-01

Floods are the costliest natural disaster (United Nations 2004), causing approximately6.8 million deaths in the twentieth century alone (Doocy et al. 2013).Worldwide economic flood damage estimates in 2012 exceed $19 Billion USD(Munich Re 2013). Extended duration floods also pose longer term threats to food security, water, sanitation, hygiene, and community livelihoods, particularly in developing countries (Davies et al. 2014).Projections by the Intergovernmental Panel on Climate Change (IPCC) suggest that precipitation extremes, rainfall intensity, storm intensity, and variability are increasing due to climate change (IPCC 2007). Increasing hydrologic uncertainty will likely lead to unprecedented extreme flood events. As such, there is a vital need to enhance and further develop traditional techniques used to rapidly assessflooding and extend analytical methods to estimate impacted population and infrastructure.

KSC-07pd0706

NASA Image and Video Library

2007-03-16

VANDENBERG AIR FORCE BASE, CALIF. -- In a clean-room environment at North Vandenberg Air Force Base, a technician monitors the AIM spacecraft after illumination testing on the spacecraft's solar array panels. The AIM spacecraft will fly three instruments designed to study those clouds located at the edge of space, 50 miles above the Earth's surface in the coldest part of the planet's atmosphere. The mission's primary goal is to explain why these clouds form and what has caused them to become brighter and more numerous and appear at lower latitudes in recent years. AIM's results will provide the basis for the study of long-term variability in the mesospheric climate and its relationship to global climate change. AIM is scheduled to be mated to the Pegasus XL during the second week of April, after which final inspections will be conducted. Launch is scheduled for April 25.

Orbital Sciences Pegasus XL AIM Processing

NASA Image and Video Library

2007-03-16

In a clean-room environment at North Vandenberg Air Force Base, a technician monitors the AIM spacecraft after illumination testing on the spacecraft's solar array panels. The AIM spacecraft will fly three instruments designed to study those clouds located at the edge of space, 50 miles above the Earth's surface in the coldest part of the planet's atmosphere. The mission's primary goal is to explain why these clouds form and what has caused them to become brighter and more numerous and appear at lower latitudes in recent years. AIM's results will provide the basis for the study of long-term variability in the mesospheric climate and its relationship to global climate change. AIM is scheduled to be mated to the Pegasus XL during the second week of April, after which final inspections will be conducted. Launch is scheduled for April 25.

Geostationary Carbon Process Mapper (GCPM)

NASA Technical Reports Server (NTRS)

Key, Richard; Sander, Stanley; Eldering, Annmarie; Miller, Charles; Frankenberg, Christian; Natraj, Vijay; Rider, David; Blavier, Jean-Francois; Bekker, Dmitriy; Wu, Yen-Hung

2012-01-01

Geostationary Carbon Process Mapper (GCPM) is an earth science mission to measure key atmospheric trace gases related to climate change and human activity.Understanding of sources and sinks of CO2 is currently limited by frequency of observations and uncertainty in vertical transport. GCPM improves this situation by making simultaneous high resolution measurements of CO2, CH4, CF, and CO in near-IR, many times per day. GCPM is able to investigate processes with time scales of minutes to hours. CO2, CH4, CF, Co selected because their combination provides information needed to disentangle natural and anthropogenic sources/sinks. Quasi-continuous monitoring effectively eliminates atmospheric transport uncertainties from source/sink inversion modeling. will have one instrument (GeoFTS), hosted on a commercial communications satellite, planned for two years operation. GCPM will affordably advance the understanding of observed cycle variability improving future climate projections.

Testing competing forms of the Milankovitch hypothesis: A multivariate approach

NASA Astrophysics Data System (ADS)

Kaufmann, Robert K.; Juselius, Katarina

2016-02-01

We test competing forms of the Milankovitch hypothesis by estimating the coefficients and diagnostic statistics for a cointegrated vector autoregressive model that includes 10 climate variables and four exogenous variables for solar insolation. The estimates are consistent with the physical mechanisms postulated to drive glacial cycles. They show that the climate variables are driven partly by solar insolation, determining the timing and magnitude of glaciations and terminations, and partly by internal feedback dynamics, pushing the climate variables away from equilibrium. We argue that the latter is consistent with a weak form of the Milankovitch hypothesis and that it should be restated as follows: internal climate dynamics impose perturbations on glacial cycles that are driven by solar insolation. Our results show that these perturbations are likely caused by slow adjustment between land ice volume and solar insolation. The estimated adjustment dynamics show that solar insolation affects an array of climate variables other than ice volume, each at a unique rate. This implies that previous efforts to test the strong form of the Milankovitch hypothesis by examining the relationship between solar insolation and a single climate variable are likely to suffer from omitted variable bias.

Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho

2017-05-01

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV)], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

Near-continuous thermal monitoring of a diverse tropical forest canopy

NASA Astrophysics Data System (ADS)

Pau, S.; Still, C. J.; Kim, Y.; Detto, M.

2015-12-01

Tropical species may be highly sensitive to temperature increases associated with climate change because of their narrow thermal tolerances. Recent work has highlighted the importance of temperature in tropical forest function, however most studies use air temperature measurements from sparse meteorological stations even though surface temperatures are known to deviate from air temperatures. Tropical organisms exist in microclimates that are highly variable in space and time and not easily measured in natural environments. This is in part because of the complex structure of tropical forests and the potential for organisms themselves to modify their own environment. In the case of plants, leaf temperature is linked to the water and surface energy balance of their microenvironment. Here we present results from near-continuous thermal camera monitoring of the forest canopy in Barro Colorado Island, Panama (5-minute intervals for approximately 9 months). We compare daytime (maximum) vs. nighttime (minimum) differences between canopy temperature and air temperature, relative humidity, solar radiation, and precipitation. On average, canopy temperatures are consistently ~2 degrees Celsius higher than air temperatures. These data can paired with flux tower data on-site and used to advance understanding of temperature controls on the structure and function of tropical forests, such as carbon assimilation, phenology, and habitat monitoring, and can be integrated into models to improve predictions of tropical forest response to future climate change.

Uranium isotopes (U-234/U-238) in rivers of the Yukon Basin (Alaska and Canada) as an aid in identifying water sources, with implications for monitoring hydrologic change in arctic regions

USGS Publications Warehouse

Kraemer, Thomas F.; Brabets, Timothy P.

2012-01-01

The ability to detect hydrologic variation in large arctic river systems is of major importance in understanding and predicting effects of climate change in high-latitude environments. Monitoring uranium isotopes (234U and 238U) in river water of the Yukon River Basin of Alaska and northwestern Canada (2001–2005) has enhanced the ability to identify water sources to rivers, as well as detect flow changes that have occurred over the 5-year study. Uranium isotopic data for the Yukon River and major tributaries (the Porcupine and Tanana rivers) identify several sources that contribute to river flow, including: deep groundwater, seasonally frozen river-valley alluvium groundwater, and high-elevation glacial melt water. The main-stem Yukon River exhibits patterns of uranium isotopic variation at several locations that reflect input from ice melt and shallow groundwater in the spring, as well as a multi-year pattern of increased variability in timing and relative amount of water supplied from higher elevations within the basin. Results of this study demonstrate both the utility of uranium isotopes in revealing sources of water in large river systems and of incorporating uranium isotope analysis in long-term monitoring of arctic river systems that attempt to assess the effects of climate change.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Environmental variability drives shifts in the foraging behaviour and reproductive success of an inshore seabird.

PubMed

Kowalczyk, Nicole D; Reina, Richard D; Preston, Tiana J; Chiaradia, André

2015-08-01

Marine animals forage in areas that aggregate prey to maximize their energy intake. However, these foraging 'hot spots' experience environmental variability, which can substantially alter prey availability. To survive and reproduce animals need to modify their foraging in response to these prey shifts. By monitoring their inter-annual foraging behaviours, we can understand which environmental variables affect their foraging efficiency, and can assess how they respond to environmental variability. Here, we monitored the foraging behaviour and isotopic niche of little penguins (Eudyptula minor), over 3 years (2008, 2011, and 2012) of climatic and prey variability within Port Phillip Bay, Australia. During drought (2008), penguins foraged in close proximity to the Yarra River outlet on a predominantly anchovy-based diet. In periods of heavy rainfall, when water depth in the largest tributary into the bay (Yarra River) was high, the total distance travelled, maximum distance travelled, distance to core-range, and size of core- and home-ranges of penguins increased significantly. This larger foraging range was associated with broad dietary diversity and high reproductive success. These results suggest the increased foraging range and dietary diversity of penguins were a means to maximize resource acquisition rather than a strategy to overcome local depletions in prey. Our results demonstrate the significance of the Yarra River in structuring predator-prey interactions in this enclosed bay, as well as the flexible foraging strategies of penguins in response to environmental variability. This plasticity is central to the survival of this small-ranging, resident seabird species.

Wetlands inform how climate extremes influence surface water expansion and contraction

NASA Astrophysics Data System (ADS)

Vanderhoof, Melanie K.; Lane, Charles R.; McManus, Michael G.; Alexander, Laurie C.; Christensen, Jay R.

2018-03-01

Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface water dynamics. We used Landsat imagery to characterize variability in surface water extent across 11 Landsat path/rows representing the PPR and NP (images spanned 1985-2015). The PPR not only experienced a 2.6-fold greater surface water extent under median conditions relative to the NP, but also showed a 3.4-fold greater change in surface water extent between drought and deluge conditions. The relationship between surface water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area, but lower total wetland density. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface water quantity. Accurate predictions regarding the effect of climate change on surface water quantity will require consideration of hydrology-related landscape characteristics including wetland storage and arrangement.