Climate-based seed zones for Mexico: guiding reforestation under observed and projected climate change

Treesearch

Dante Castellanos-Acuña; Kenneth W. Vance-Borland; J. Bradley St. Clair; Andreas Hamann; Javier López-Upton; Erika Gómez-Pineda; Juan Manuel Ortega-Rodríguez; Cuauhtémoc Sáenz-Romero

2018-01-01

Seed zones for forest tree species are a widely used tool in reforestation programs to ensure that seedlings are well adapted to their planting environments. Here, we propose a climate-based seed zone system for Mexico to address observed and projected climate change. The proposed seed zone classification is based on bands of climate variables often related to genetic...

Solar diameter measurements for study of Sun climate coupling

NASA Technical Reports Server (NTRS)

Hill, H. A.

1981-01-01

Variability in solar shape and diameters was examined as a possible probe of an important climatic driving function, solar luminosity variability. The techniques and facilities developed for measuring the solar diameter were used. The observing program and the requisite data reduction were conducted simultaneously. The development of a technique to calibrate the scale in the telescope field progressed to the design and construction phase.

Educators' Perceptions of the Effects of School Uniforms on School Climate in a Selected Metropolitan Disciplinary Alternative Education Program

ERIC Educational Resources Information Center

Chime, Emmanuel Onoh

2010-01-01

The purpose of this study was to examine educators' perceptions regarding the effects of school uniforms on school climate in a selected metropolitan disciplinary alternative education program. More specifically, this study investigated the influence of the variables group status, gender, ethnicity, age and years of experience on the perceptions…

Climate Dynamics and Experimental Prediction (CDEP) and Regional Integrated Science Assessments (RISA) Programs at NOAA Office of Global Programs

NASA Astrophysics Data System (ADS)

Bamzai, A.

2003-04-01

This talk will highlight science and application activities of the CDEP and RISA programs at NOAA OGP. CDEP, through a set of Applied Research Centers (ARCs), supports NOAA's program of quantitative assessments and predictions of global climate variability and its regional implications on time scales of seasons to centuries. The RISA program consolidates results from ongoing disciplinary process research under an integrative framework. Examples of joint CDEP-RISA activities will be presented. Future directions and programmatic challenges will also be discussed.

Multi-objective optimization for evaluation of simulation fidelity for precipitation, cloudiness and insolation in regional climate models

NASA Astrophysics Data System (ADS)

Lee, H.

2016-12-01

Precipitation is one of the most important climate variables that are taken into account in studying regional climate. Nevertheless, how precipitation will respond to a changing climate and even its mean state in the current climate are not well represented in regional climate models (RCMs). Hence, comprehensive and mathematically rigorous methodologies to evaluate precipitation and related variables in multiple RCMs are required. The main objective of the current study is to evaluate the joint variability of climate variables related to model performance in simulating precipitation and condense multiple evaluation metrics into a single summary score. We use multi-objective optimization, a mathematical process that provides a set of optimal tradeoff solutions based on a range of evaluation metrics, to characterize the joint representation of precipitation, cloudiness and insolation in RCMs participating in the North American Regional Climate Change Assessment Program (NARCCAP) and Coordinated Regional Climate Downscaling Experiment-North America (CORDEX-NA). We also leverage ground observations, NASA satellite data and the Regional Climate Model Evaluation System (RCMES). Overall, the quantitative comparison of joint probability density functions between the three variables indicates that performance of each model differs markedly between sub-regions and also shows strong seasonal dependence. Because of the large variability across the models, it is important to evaluate models systematically and make future projections using only models showing relatively good performance. Our results indicate that the optimized multi-model ensemble always shows better performance than the arithmetic ensemble mean and may guide reliable future projections.

Developing NOAA's Climate Data Records From AVHRR and Other Data

NASA Astrophysics Data System (ADS)

Privette, J. L.; Bates, J. J.; Kearns, E. J.

2010-12-01

As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm migration and execution. Timeline of NOAA's polar orbiters that carried AVHRR. NOAA's approach to flying the same or similar instruments sequentially is well-suited to CDR development.

Managing water and salinity with desalination, conveyance, conservation, waste-water treatment and reuse to counteract climate variability in Gaza

NASA Astrophysics Data System (ADS)

Rosenberg, D. E.; Aljuaidi, A. E.; Kaluarachchi, J. J.

2009-12-01

We include demands for water of different salinity concentrations as input parameters and decision variables in a regional hydro-economic optimization model. This specification includes separate demand functions for saline water. We then use stochastic non-linear programming to jointly identify the benefit maximizing set of infrastructure expansions, operational allocations, and use of different water quality types under climate variability. We present a detailed application for the Gaza Strip. The application considers building desalination and waste-water treatment plants and conveyance pipelines, initiating water conservation and leak reduction programs, plus allocating and transferring water of different qualities among agricultural, industrial, and urban sectors and among districts. Results show how to integrate a mix of supply enhancement, conservation, water quality improvement, and water quality management actions into a portfolio that can economically and efficiently respond to changes and uncertainties in surface and groundwater availability due to climate variability. We also show how to put drawn-down and saline Gaza aquifer water to more sustainable and economical use.

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.

Training NOAA Staff on Effective Communication Methods with Local Climate Users

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Mayes, B.

2011-12-01

Since 2002 NOAA National Weather Service (NWS) Climate Services Division (CSD) offered training opportunities to NWS staff. As a result of eight-year-long development of the training program, NWS offers three training courses and about 25 online distance learning modules covering various climate topics: climate data and observations, climate variability and change, NWS national and local climate products, their tools, skill, and interpretation. Leveraging climate information and expertise available at all NOAA line offices and partners allows delivery of the most advanced knowledge and is a very critical aspect of the training program. NWS challenges in providing local climate services includes effective communication techniques on provide highly technical scientific information to local users. Addressing this challenge requires well trained, climate-literate workforce at local level capable of communicating the NOAA climate products and services as well as provide climate-sensitive decision support. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-unimpaired messages and amiable communication techniques such as story telling approach are important in developing an engaged dialog between the climate service providers and users. Several pilot projects NWS CSD conducted in the past year applied the NWS climate services training program to training events for NOAA technical user groups. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring the instructions to the potential applications of each group of users. Training technical user identified the following critical issues: (1) Knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) Leveraging partnership with climate services providers; and, (3) Applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

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.

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

Preview of Our Changing Planet. The U.S. Climate Change Science Program for Fiscal Year 2008

DTIC Science & Technology

2007-04-01

reduce the uncertainty in predictions of the global and regional water cycle and surface climate. Sunlight not reflected back to space provides the...research elements include atmospheric composition, climate variability and change, the global water cycle , land-use and land-cover change, the global...entire planet, and researchers with the ability to better explain observed changes in the climate system. Global Water Cycle – Research associated with

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

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.

Reconstructing Earth's Climate History: Inquiry-Based Exercises for Lab and Class

NASA Astrophysics Data System (ADS)

Wolfe, Brent

2013-04-01

For instructors in natural science undergraduate programs, there is a clear need to have students explore and understand the scientific evidence of past climate variability and learn what this tells us about the role of humans in shaping present-day climate. Indeed, research in the field of paleoclimatology has provided data that identifies one of the most pressing challenges facing society—global warming. Herein lay my motivation to fill an important gap in my university's undergraduate program in geography and environmental studies. To that end, about a year ago I began to develop a new fourth-year course in paleoclimatology.

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

Kuleshov, Y.; Jones, D.; Hendon, H.; Charles, A.; Cottrill, A.; Lim, E.-P.; Langford, S.; de Wit, R.; Shelton, K.

2012-04-01

Seasonal and inter-annual climate variability is a major factor in determining the vulnerability of many Pacific Island Countries to climate change and there is need to improve weekly to seasonal range climate prediction capabilities beyond what is currently available from statistical models. In the seasonal climate prediction project under the Australian Government's Pacific Adaptation Strategy Assistance Program (PASAP), we describe a comprehensive project to strengthen the climate prediction capacities in National Meteorological Services in 14 Pacific Island Countries and East Timor. The intent is particularly to reduce the vulnerability of current services to a changing climate, and improve the overall level of information available assist with managing climate variability. Statistical models cannot account for aspects of climate variability and change that are not represented in the historical record. In contrast, dynamical physics-based models implicitly include the effects of a changing climate whatever its character or cause and can predict outcomes not seen previously. The transition from a statistical to a dynamical prediction system provides more valuable and applicable climate information to a wide range of climate sensitive sectors throughout the countries of the Pacific region. In this project, we have developed seasonal climate outlooks which are based upon the current dynamical model POAMA (Predictive Ocean-Atmosphere Model for Australia) seasonal forecast system. At present, meteorological services of the Pacific Island Countries largely employ statistical models for seasonal outlooks. Outcomes of the PASAP project enhanced capabilities of the Pacific Island Countries in seasonal prediction providing National Meteorological Services with an additional tool to analyse meteorological variables such as sea surface temperatures, air temperature, pressure and rainfall using POAMA outputs and prepare more accurate seasonal climate outlooks.

Climate Trends and Farmers' Perceptions of Climate Change in Zambia.

PubMed

Mulenga, Brian P; Wineman, Ayala; Sitko, Nicholas J

2017-02-01

A number of studies use meteorological records to analyze climate trends and assess the impact of climate change on agricultural yields. While these provide quantitative evidence on climate trends and the likely effects thereof, they incorporate limited qualitative analysis of farmers' perceptions of climate change and/or variability. The present study builds on the quantitative methods used elsewhere to analyze climate trends, and in addition compares local narratives of climate change with evidence found in meteorological records in Zambia. Farmers offer remarkably consistent reports of a rainy season that is growing shorter and less predictable. For some climate parameters-notably, rising average temperature-there is a clear overlap between farmers' observations and patterns found in the meteorological records. However, the data do not support the perception that the rainy season used to begin earlier, and we generally do not detect a reported increase in the frequency of dry spells. Several explanations for these discrepancies are offered. Further, we provide policy recommendations to help farmers adapt to climate change/variability, as well as suggestions to shape future climate change policies, programs, and research in developing countries.

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

NASA Astrophysics Data System (ADS)

Mantua, N.; Snover, A.

2006-12-01

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

Paleoclimates: Understanding climate change past and present

USGS Publications Warehouse

Cronin, Thomas M.

2010-01-01

The field of paleoclimatology relies on physical, chemical, and biological proxies of past climate changes that have been preserved in natural archives such as glacial ice, tree rings, sediments, corals, and speleothems. Paleoclimate archives obtained through field investigations, ocean sediment coring expeditions, ice sheet coring programs, and other projects allow scientists to reconstruct climate change over much of earth's history. When combined with computer model simulations, paleoclimatic reconstructions are used to test hypotheses about the causes of climatic change, such as greenhouse gases, solar variability, earth's orbital variations, and hydrological, oceanic, and tectonic processes. This book is a comprehensive, state-of-the art synthesis of paleoclimate research covering all geological timescales, emphasizing topics that shed light on modern trends in the earth's climate. Thomas M. Cronin discusses recent discoveries about past periods of global warmth, changes in atmospheric greenhouse gas concentrations, abrupt climate and sea-level change, natural temperature variability, and other topics directly relevant to controversies over the causes and impacts of climate change. This text is geared toward advanced undergraduate and graduate students and researchers in geology, geography, biology, glaciology, oceanography, atmospheric sciences, and climate modeling, fields that contribute to paleoclimatology. This volume can also serve as a reference for those requiring a general background on natural climate variability.

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.

Impact of Climate Change and Human Intervention on River Flow Regimes

NASA Astrophysics Data System (ADS)

Singh, Rajendra; Mittal, Neha; Mishra, Ashok

2017-04-01

Climate change and human interventions like dam construction bring freshwater ecosystem under stress by changing flow regime. It is important to analyse their impact at a regional scale along with changes in the extremes of temperature and precipitation which further modify the flow regime components such as magnitude, timing, frequency, duration, and rate of change of flow. In this study, the Kangsabati river is chosen to analyse the hydrological alterations in its flow regime caused by dam, climate change and their combined impact using Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration (IHA) program based on the Range of Variability Approach (RVA). Results show that flow variability is significantly reduced due to dam construction with high flows getting absorbed and pre-monsoon low flows being augmented by the reservoir. Climate change alone reduces the high peaks whereas a combination of dam and climate change significantly reduces variability by affecting both high and low flows, thereby further disrupting the functioning of riverine ecosystems. Analysis shows that in the Kangsabati basin, influence of dam is greater than that of the climate change, thereby emphasising the significance of direct human intervention. Keywords: Climate change, human impact, flow regime, Kangsabati river, SWAT, IHA, RVA.

Communicating the Results and Activities of the U.S. Climate Change Science Program

NASA Astrophysics Data System (ADS)

Chatterjee, K.; Parker, K.

2004-12-01

The Climate Change Science Program (CCSP) has a responsibility for credible and effective communications on issues related to climate variability and climate change science. As an essential part of its mission and responsibilities, the CCSP aims to enhance the quality of public discussion by stressing openness and transparency in its scientific research processes and results, and ensuring the widespread availability of credible, science-based information. The CCSP and individual federal agencies generate substantial amounts of authoritative scientific information on climate variability and change. Research findings are generally well reported in the scientific literature, but relevant aspects of these findings need to be reported in formats suitable for use by diverse audiences whose understanding and familiarity with climate change science issues vary. To further its commitment to the effective communication of climate change science information, the CCSP has established the Communications Interagency Working Group, which has produced an implementation plan for Climate Change communication, aimed at achieving the following goals: * Disseminate the results of CCSP activities credibly and effectively * Make CCSP science findings and products easily available to a diverse set of audiences. In addition to CCSP efforts, the individual federal agencies that comprise CCSP disseminate science-based climate information through their agency networks. The agencies of the CCSP are the Departments of Agriculture, Commerce, Defense, Energy, Health and Human Services, Interior, State, and Transportation and the U.S. EPA, NASA, NSF, Smithsonian Institute, and USAID.

Clouds and more: ARM climate modeling best estimate data: A new data product for climate studies

DOE PAGES

Xie, Shaocheng; McCoy, Renata B.; Klein, Stephen A.; ...

2010-01-01

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation atmosphere. Here, a central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement.

Climate and atmosphere simulator for experiments on ecological systems in changing environments.

PubMed

Verdier, Bruno; Jouanneau, Isabelle; Simonnet, Benoit; Rabin, Christian; Van Dooren, Tom J M; Delpierre, Nicolas; Clobert, Jean; Abbadie, Luc; Ferrière, Régis; Le Galliard, Jean-François

2014-01-01

Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.

The National Oceanic and Atmospheric Administration (NOAA) Climate Services Portal: A New Centralized Resource for Distributed Climate Information

NASA Astrophysics Data System (ADS)

Burroughs, J.; Baldwin, R.; Herring, D.; Lott, N.; Boyd, J.; Handel, S.; Niepold, F.; Shea, E.

2010-09-01

With the rapid rise in the development of Web technologies and climate services across NOAA, there has been an increasing need for greater collaboration regarding NOAA's online climate services. The drivers include the need to enhance NOAA's Web presence in response to customer requirements, emerging needs for improved decision-making capabilities across all sectors of society facing impacts from climate variability and change, and the importance of leveraging climate data and services to support research and public education. To address these needs, NOAA (during fiscal year 2009) embarked upon an ambitious program to develop a NOAA Climate Services Portal (NCS Portal). Four NOAA offices are leading the effort: 1) the NOAA Climate Program Office (CPO), 2) the National Ocean Service's Coastal Services Center (CSC), 3) the National Weather Service's Climate Prediction Center (CPC), and 4) the National Environmental Satellite, Data, and Information Service's (NESDIS) National Climatic Data Center (NCDC). Other offices and programs are also contributing in many ways to the effort. A prototype NCS Portal is being placed online for public access in January 2010, http://www.climate.gov. This website only scratches the surface of the many climate services across NOAA, but this effort, via direct user engagement, will gradually expand the scope and breadth of the NCS Portal to greatly enhance the accessibility and usefulness of NOAA's climate data and services.

A flexible tool for diagnosing water, energy, and entropy budgets in climate models

NASA Astrophysics Data System (ADS)

Lembo, Valerio; Lucarini, Valerio

2017-04-01

We have developed a new flexible software for studying the global energy budget, the hydrological cycle, and the material entropy production of global climate models. The program receives as input radiative, latent and sensible energy fluxes, with the requirement that the variable names are in agreement with the Climate and Forecast (CF) conventions for the production of NetCDF datasets. Annual mean maps, meridional sections and time series are computed by means of Climate Data Operators (CDO) collection of command line operators developed at Max-Planck Institute for Meteorology (MPI-M). If a land-sea mask is provided, the program also computes the required quantities separately on the continents and oceans. Depending on the user's choice, the program also calls the MATLAB software to compute meridional heat transports and location and intensities of the peaks in the two hemispheres. We are currently planning to adapt the program in order to be included in the Earth System Model eValuation Tool (ESMValTool) community diagnostics.

Foreword: The dynamics of change in Alaska’s boreal forests: Resilience and vulnerability in response to climate warming

USGS Publications Warehouse

McGuire, A. David; Chapin, F. Stuart; Ruess, Roger W.

2016-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying the resilience and vulnerability of Alaska's boreal forest in response to climate warming. The overarching question in this endeavor has been “How are boreal ecosystems responding, both gradually and abruptly, to climate warming, and what new landscape patterns are emerging?”

NOAA's Satellite Climate Data Records: The Research to Operations Process and Current State

NASA Astrophysics Data System (ADS)

Privette, J. L.; Bates, J. J.; Kearns, E. J.; NOAA's Climate Data Record Program

2011-12-01

In support of NOAA's mandate to provide climate products and services to the Nation, the National Climatic Data Center initiated the satellite Climate Data Record (CDR) Program. The Program develops and sustains climate information products derived from satellite data that NOAA has collected over the past 30+ years. These are the longest sets of continuous global measurements in existence. Data from other satellite programs, including those in NASA, the Department of Defense, and foreign space agencies, are also used. NOAA is now applying advanced analysis techniques to these historic data. This process is unraveling underlying climate trend and variability information and returning new value from the data. However, the transition of complex data processing chains, voluminous data products and documentation into an systematic, configuration controlled context involves many challenges. In this presentation, we focus on the Program's process for research-to-operations transition and the evolving systems designed to ensure transparency, security, economy and authoritative value. The Program has adopted a two-phase process defined by an Initial Operational Capability (IOC) and a Full Operational Capability (FOC). The principles and procedures for IOC are described, as well as the process for moving CDRs from IOC to FOC. Finally, we will describe the state of the CDRs in all phases the Program, with an emphasis on the seven community-developed CDRs transitioned to NOAA in 2011. Details on CDR access and distribution will be provided.

The Sun as a variable star: Solar and stellar irradiance variations; Colloquium of the International Astronomical Union, 143rd, Boulder, CO, Jun. 20-25, 1993

NASA Technical Reports Server (NTRS)

Pap, Judit M. (Editor); Froehlich, Claus (Editor); Hudson, Hugh S. (Editor); Tobiska, W. Kent (Editor)

1994-01-01

Variations in solar and stellar irradiances have long been of interest. An International Astronomical Union (IAU) colloquium reviewed such relevant subjects as observations, theoretical interpretations, and empirical and physical models, with a special emphasis on climatic impact of solar irradiance variability. Specific topics discussed included: (1) General Reviews on Observations of Solar and Stellar Irradiance Variability; (2) Observational Programs for Solar and Stellar Irradiance Variability; (3) Variability of Solar and Stellar Irradiance Related to the Network, Active Regions (Sunspots and Plages), and Large-Scale Magnetic Structures; (4) Empirical Models of Solar Total and Spectral Irradiance Variability; (5) Solar and Stellar Oscillations, Irradiance Variations and their Interpretations; and (6) The Response of the Earth's Atmosphere to Solar Irradiance Variations and Sun-Climate Connections.

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

NASA Astrophysics Data System (ADS)

Hamdy, A.; Trisorio-Liuzzi, G.

2009-04-01

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

Projected 2050 Model Simulations for the Chesapeake Bay Program

EPA Science Inventory

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

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

USGS Publications Warehouse

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

2012-01-01

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

Technical Report Series on Global Modeling and Data Assimilation, Volume 41 : GDIS Workshop Report

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Schubert, Siegfried; Pozzi, Will; Mo, Kingtse; Wood, Eric F.; Stahl, Kerstin; Hayes, Mike; Vogt, Juergen; Seneviratne, Sonia; Stewart, Ron;

Communication, social capital and workplace health management as determinants of the innovative climate in German banks.

PubMed

Köhler, Thorsten; Janssen, Christian; Plath, Sven-Christoph; Reese, Jens Peter; Lay, Jann; Steinhausen, Simone; Gloede, Tristan; Kowalski, Christoph; Schulz-Nieswandt, Frank; Pfaff, Holger

2010-12-01

The present study aims to measure the determinants of the innovative climate in German banks with a focus on workplace health management (WHM). We analyze the determinants of innovative climate with multiple regressions using a dataset based on standardized telephone interviews conducted with health promotion experts from 198 randomly selected German banks. The regression analysis provided a good explanation of the variance in the dependent variable (R² = 55%). Communication climate (β = 0.55; p < 0.001), social capital (β = 0.21; p < 0.01), the establishment of a WHM program (β = 0.13; p < 0.05) as well as company size (β = 0.15; p < 0.01) were found to have a significant impact on an organization's innovative climate. In order to foster an innovation-friendly climate, organizations should establish shared values. An active step in this direction involves strengthening the organizations' social capital and communication climate through trustworthy management decisions such as the implementation of a WHM program.

Risk Communication: The Role of the South Carolina State Climatology Office.

NASA Astrophysics Data System (ADS)

Smith, David J.; Purvis, John C.; Felts, Arthur

1995-12-01

The federally supported state climatologist program ended in 1972. Thereafter, most states supported these endeavors in coordination with the National Climatic Data Center, but the current state programs vary widely. One of the functions of state climate programs that evolved since 1972 is acting as a liaison between the National Weather Service and various state agencies. This role is most apparent and controversial in coordinating state and local government response to severe weather and extreme climate anomalies such as drought, flood, winter storms, and tropical cyclones. The activities of the climate office in South Carolina during Hurricane Hugo in September 1989 and the October 1990 floods reveal how these interactions occur in one state that mandated these activities. The state climate office had to react to shifting weather conditions and to variable political conditions that affect public organizations. The climate office in South Carolina acts to interpret weather information, develop scenarios and predictions, and to assist in postevent damage surveys. This review is presented to acknowledge and document the expanding role of the state climate office in South Carolina in response to state and local government needs for weather forecast interpretation and expert guidance in the event of severe weather.

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

NASA Technical Reports Server (NTRS)

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

2007-01-01

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

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed Central

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-01-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change. PMID:10753097

The potential health impacts of climate variability and change for the United States: executive summary of the report of the health sector of the U.S. National Assessment.

PubMed

Patz, J A; McGeehin, M A; Bernard, S M; Ebi, K L; Epstein, P R; Grambsch, A; Gubler, D J; Reither, P; Romieu, I; Rose, J B; Samet, J M; Trtanj, J

2000-04-01

We examined the potential impacts of climate variability and change on human health as part of a congressionally mandated study of climate change in the United States. Our author team, comprising experts from academia, government, and the private sector, was selected by the federal interagency U.S. Global Change Research Program, and this report stems from our first 18 months of work. For this assessment we used a set of assumptions and/or projections of future climates developed for all participants in the National Assessment of the Potential Consequences of Climate Variability and Change. We identified five categories of health outcomes that are most likely to be affected by climate change because they are associated with weather and/or climate variables: temperature-related morbidity and mortality; health effects of extreme weather events (storms, tornadoes, hurricanes, and precipitation extremes); air-pollution-related health effects; water- and foodborne diseases; and vector- and rodent-borne diseases. We concluded that the levels of uncertainty preclude any definitive statement on the direction of potential future change for each of these health outcomes, although we developed some hypotheses. Although we mainly addressed adverse health outcomes, we identified some positive health outcomes, notably reduced cold-weather mortality, which has not been extensively examined. We found that at present most of the U.S. population is protected against adverse health outcomes associated with weather and/or climate, although certain demographic and geographic populations are at increased risk. We concluded that vigilance in the maintenance and improvement of public health systems and their responsiveness to changing climate conditions and to identified vulnerable subpopulations should help to protect the U.S. population from any adverse health outcomes of projected climate change.

INTER-ANNUAL AND SEASONAL VARIABILITY OF METEOROLOGICALLY-INFLUENCED EMISSIONS

EPA Science Inventory

The EPA is a participant in the U.S. Global Change Research Program. The air quality portion of the GCRP addresses the effect on air quality attributable to climate change in the intermediate future (e.g., 2050). The first phase of the program examines the change in air quality...

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.

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

NASA Technical Reports Server (NTRS)

Lapenta, William M.

2008-01-01

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

Preparedness for climate change among local health department officials in New York state: a comparison with national survey results.

PubMed

Carr, Jessie L; Sheffield, Perry E; Kinney, Patrick L

2012-01-01

Climate-change adaptation strategies that address locally specific climate hazards are critical for preventing negative health outcomes, and local public health care officials are key foci for adaptation planning. To assess New York State Local Health Department officials' perceptions and preparedness related to climate-sensitive health areas, and compare these with a national sample. Online survey instrument, originally used in a national survey of local health department (LHD) officials. New York State. Eligible participants included all New York State city and county LHD officials, 1 respondent per LHD. LHD officials' perceptions of (1) local climate-related public health effects, (2) preparation status and programming areas of LHDs, and (3) necessary resources to better address climate-related health risks. : Survey participants, representing a 54% response rate (with 93% of respondents completing more than 90% of the questions), perceived climate change as relevant to public health, and most noted that some of their existing programs already use or are planning to use climate adaptation strategies. Overall, fewer New York State respondents identified concerns or related expertise compared with the previous national survey. Many respondents expressed uncertainty regarding necessary additional resources. This type of assessment makes clear the high variability in perceived impacts and capacity at the level of LHD jurisdictions, and underscores the importance of sustained support for local climate-change preparedness programming. The implications of these findings are germane to other states with similar decentralized jurisdiction of public health. Findings from such surveys can bolster existing LHD programs, as well as inform long-term and emergency planning for climate change.

The PIRATA Observing System in the Tropical Atlantic: Enhancements and perspectives

NASA Astrophysics Data System (ADS)

Hernandez, Fabrice; Araujo, Moacyr; Bourlès, Bernard; Brandt, Peter; Campos, Edmo; Giordani, Hervé; Lumpkin, Rick; McPhaden, Michael J.; Nobre, Paulo; Saravanan, Ramalingam

2017-04-01

PIRATA (Prediction and Research Moored Array in the Tropical Atlantic) is a multinational program established to improve our knowledge and understanding of ocean-atmosphere variability in the tropical Atlantic, a region that strongly influences the regional hydro-climates and, consequently, the economies of the regions bordering the Atlantic Ocean (e.g. West Africa, North-Eastern Brazil, the West Indies and the United States). PIRATA is motivated not only by fundamental scientific questions but also by societal needs for improved prediction of climatic variability and its impacts. PIRATA, initiated in 1997, is based around an array of moored buoys providing meteorological and oceanographic measurements transmitted in real-time, disseminated via GTS and Global Data Servers. Then, through yearly mooring maintenance, recorded high frequency data are collected and calibrated. The dedicated cruises of yearly maintenance allow complementary acquisition of a large number of measurements along repeated ship track lines and also provide platforms for deployments of other components of the observing system. Several kinds of operations are carried out in collaboration with other international programs. PIRATA provides invaluable data for numerous and varied applications, among which are analyses of climate variability on intraseasonal-to-decadal timescales, equatorial dynamics, mixed-layer temperature and salinity budgets, air-sea fluxes, data assimilation, and weather and climate forecasts. PIRATA is now 20 years old, well established and recognized as the backbone of the tropical Atlantic sustained observing system. Several enhancements have been achieved during recent years, including progressive updating of mooring systems and sensors, also in collaborations with and as a contribution to other programs (such as EU PREFACE and AtlantOS). Recent major accomplishments in terms of air-sea exchanges and climate predictability will be highlighted in this presentation. Future perspectives for the network will also be discussed in the framework of a sustainable Atlantic Ocean Observing System.

Pacific-Australia Climate Change Science and Adaptation Planning program: supporting climate science and enhancing climate services in Pacific Island Countries

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Jones, David; Hendon, Harry; Charles, Andrew; Shelton, Kay; de Wit, Roald; Cottrill, Andrew; Nakaegawa, Toshiyuki; Atalifo, Terry; Prakash, Bipendra; Seuseu, Sunny; Kaniaha, Salesa

2013-04-01

Over the past few years, significant progress in developing climate science for the Pacific has been achieved through a number of research projects undertaken under the Australian government International Climate Change Adaptation Initiative (ICCAI). Climate change has major impact on Pacific Island Countries and advancement in understanding past, present and futures climate in the region is vital for island nation to develop adaptation strategies to their rapidly changing environment. This new science is now supporting new services for a wide range of stakeholders in the Pacific through the National Meteorological Agencies of the region. Seasonal climate prediction is particularly important for planning in agriculture, tourism and other weather-sensitive industries, with operational services provided by all National Meteorological Services in the region. The interaction between climate variability and climate change, for example during droughts or very warm seasons, means that much of the early impacts of climate change are being felt through seasonal variability. A means to reduce these impacts is to improve forecasts to support decision making. Historically, seasonal climate prediction has been developed based on statistical past relationship. Statistical methods relate meteorological variables (e.g. temperature and rainfall) to indices which describe large-scale environment (e.g. ENSO indices) using historical data. However, with observed climate change, statistical approaches based on historical data are getting less accurate and less reliable. Recognising the value of seasonal forecasts, we have used outputs of a dynamical model POAMA (Predictive Ocean Atmosphere Model for Australia), to develop web-based information tools (http://poama.bom.gov.au/experimental/pasap/index.shtml) which are now used by climate services in 15 partner countries in the Pacific for preparing seasonal climate outlooks. Initial comparison conducted during 2012 has shown that the predictive skill of POAMA is consistently higher than skill of statistical-based method. Presently, under the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program, we are developing dynamical model-based seasonal climate prediction for climate extremes. Of particular concern are tropical cyclones which are the most destructive weather systems that impact on coastal areas of Australia and Pacific Island Countries. To analyse historical cyclone data, we developed a consolidate archive for the Southern Hemisphere and North-Western Pacific (http://www.bom.gov.au/cyclone/history/tracks/). Using dynamical climate models (POAMA and Japan Meteorological Agency's model), we work on improving accuracy of seasonal forecasts of tropical cyclone activity for the regions of Western Pacific. Improved seasonal climate prediction based on dynamical models will further enhance climate services in Australia and Pacific Island Countries.

Fifty Years of Institutional Rehabilitation Outcomes: Inventory and Implications.

ERIC Educational Resources Information Center

Gibson, David; Fields, Donald L.

1983-01-01

Temporal variability within the record was more easily attributed to the adequacy of past accountability research and to public policy than to program effects, socioeconomic climate, or changing receiver group attitudes. (Author/SEW)

How well do the GCMs/RCMs capture the multi-scale temporal variability of precipitation in the Southwestern United States?

NASA Astrophysics Data System (ADS)

Jiang, Peng; Gautam, Mahesh R.; Zhu, Jianting; Yu, Zhongbo

2013-02-01

SummaryMulti-scale temporal variability of precipitation has an established relationship with floods and droughts. In this paper, we present the diagnostics on the ability of 16 General Circulation Models (GCMs) from Bias Corrected and Downscaled (BCSD) World Climate Research Program's (WCRP's) Coupled Model Inter-comparison Project Phase 3 (CMIP3) projections and 10 Regional Climate Models (RCMs) that participated in the North American Regional Climate Change Assessment Program (NARCCAP) to represent multi-scale temporal variability determined from the observed station data. Four regions (Los Angeles, Las Vegas, Tucson, and Cimarron) in the Southwest United States are selected as they represent four different precipitation regions classified by clustering method. We investigate how storm properties and seasonal, inter-annual, and decadal precipitation variabilities differed between GCMs/RCMs and observed records in these regions. We find that current GCMs/RCMs tend to simulate longer storm duration and lower storm intensity compared to those from observed records. Most GCMs/RCMs fail to produce the high-intensity summer storms caused by local convective heat transport associated with the summer monsoon. Both inter-annual and decadal bands are present in the GCM/RCM-simulated precipitation time series; however, these do not line up to the patterns of large-scale ocean oscillations such as El Nino/La Nina Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Our results show that the studied GCMs/RCMs can capture long-term monthly mean as the examined data is bias-corrected and downscaled, but fail to simulate the multi-scale precipitation variability including flood generating extreme events, which suggests their inadequacy for studies on floods and droughts that are strongly associated with multi-scale temporal precipitation variability.

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.

Examining Treatment Climate Across Prison-Based Substance Abuse Treatment Groups.

PubMed

Kelly, Christopher E; Welsh, Wayne N

2016-06-06

With notable exceptions, few studies have looked critically at the role and effects of factors other than individual or programmatic differences that contribute to the climate within substance abuse treatment programs. De Leon's work on the therapeutic community, however, indicates that factors beyond the individual and program can contribute to the overall functioning of similarly situated communities. In this study, we introduce and examine the concept of the "treatment group," the level of aggregation between the individual who participates in treatment and the organization that provides it. The treatment group refers to the social context and dynamics that operate among treatment participants, and we sought to study differences in treatment climate across 12 prison-based treatment groups within a single prison. Using data from 604 participants who were assigned at random to one of the 12 groups, we analyzed differences on seven treatment climate indicators from one month and six months into the program across the treatment groups. No differences were found among the treatment groups at after one month; however, after 6 months, significant differences emerged across the groups on three treatment climate variables: program structure, counselor rapport, and counselor competence. This study is among the first of its kind to conceptualize and examine treatment climate across otherwise similar groups and find that differences emerge on several indicators of climate. As such, we argue that the treatment group may be important to consider in both the delivery and evaluation of substance abuse treatment.

The Nevada NSF EPSCoR infrastructure for climate change science, education, and outreach project: highlights and progress on investigations of ecological change and water resources along elevational gradients

NASA Astrophysics Data System (ADS)

Saito, L.; Biondi, F.; Fenstermaker, L. F.; Arnone, J.; Devitt, D.; Riddle, B.; Young, M.

2010-12-01

In 2008, the Nevada System of Higher Education received a 5-year, $15 million grant from the National Science Foundation’s (NSF) Experimental Program to Stimulate Competitive Research (EPSCoR). The mission of the project is to create a statewide interdisciplinary program to stimulate transformative research, education, and outreach about the effects of regional climate change on ecosystem services (especially water resources), and support use of this knowledge by policy makers and stakeholders. The overarching question that this effort will address is: how will climate change affect water resources, disturbance regimes and linked ecosystem and human services? While the overall project includes cyberinfrastructure, policy, education and climate modeling, this presentation will focus on the ecological change and water resources components. The goals of these two components are: 1) improving understanding of processes controlling local- and basin-wide impacts of climate on species dynamics, disturbance regimes, and water recharge rates; 2) evaluating interactions between landscape-level processes and biophysical indicators; 3) evaluating interactions between surface and groundwater systems; 4) predicting changes in wildfire regime, primary productivity, and biodiversity (including invasive species); and 5) assessing how interactions between water and ecology will differ under climate change and/or climate variability scenarios. To achieve these goals, the two components will quantify present-day climate variability at multiple temporal and spatial scales, including at multiple elevations within Nevada’s Basin and Range ecosystem continuum. This presentation will discuss key elements for achieving these goals, including the establishment of instrumented transects spanning a range of elevations and vegetation zones in eastern and southern Nevada.

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.

Similar millennial climate variability on the Iberian margin during two early Pleistocene glacials and MIS 3

NASA Astrophysics Data System (ADS)

Birner, B.; Hodell, D. A.; Tzedakis, P. C.; Skinner, L. C.

2016-01-01

Although millennial-scale climate variability (<10 ka) has been well studied during the last glacial cycles, little is known about this important aspect of climate in the early Pleistocene, prior to the Middle Pleistocene Transition. Here we present an early Pleistocene climate record at centennial resolution for two representative glacials (marine isotope stages (MIS) 37-41 from approximately 1235 to 1320 ka) during the "41 ka world" at Integrated Ocean Drilling Program Site U1385 (the "Shackleton Site") on the southwest Iberian margin. Millennial-scale climate variability was suppressed during interglacial periods (MIS 37, MIS 39, and MIS 41) and activated during glacial inceptions when benthic δ18O exceeded 3.2‰. Millennial variability during glacials MIS 38 and MIS 40 closely resembled Dansgaard-Oeschger events from the last glacial (MIS 3) in amplitude, shape, and pacing. The phasing of oxygen and carbon isotope variability is consistent with an active oceanic thermal bipolar see-saw between the Northern and Southern Hemispheres during most of the prominent stadials. Surface cooling was associated with systematic decreases in benthic carbon isotopes, indicating concomitant changes in the meridional overturning circulation. A comparison to other North Atlantic records of ice rafting during the early Pleistocene suggests that freshwater forcing, as proposed for the late Pleistocene, was involved in triggering or amplifying perturbations of the North Atlantic circulation that elicited a bipolar see-saw response. Our findings support similarities in the operation of the climate system occurring on millennial time scales before and after the Middle Pleistocene Transition despite the increases in global ice volume and duration of the glacial cycles.

What is the Effect of Interannual Hydroclimatic Variability on Water Supply Reservoir Operations?

NASA Astrophysics Data System (ADS)

Galelli, S.; Turner, S. W. D.

2015-12-01

Rather than deriving from a single distribution and uniform persistence structure, hydroclimatic data exhibit significant trends and shifts in their mean, variance, and lagged correlation through time. Consequentially, observed and reconstructed streamflow records are often characterized by features of interannual variability, including long-term persistence and prolonged droughts. This study examines the effect of these features on the operating performance of water supply reservoirs. We develop a Stochastic Dynamic Programming (SDP) model that can incorporate a regime-shifting climate variable. We then compare the performance of operating policies—designed with and without climate variable—to quantify the contribution of interannual variability to standard policy sub-optimality. The approach uses a discrete-time Markov chain to partition the reservoir inflow time series into small number of 'hidden' climate states. Each state defines a distinct set of inflow transition probability matrices, which are used by the SDP model to condition the release decisions on the reservoir storage, current-period inflow and hidden climate state. The experimental analysis is carried out on 99 hypothetical water supply reservoirs fed from pristine catchments in Australia—all impacted by the Millennium drought. Results show that interannual hydroclimatic variability is a major cause of sub-optimal hedging decisions. The practical import is that conventional optimization methods may misguide operators, particularly in regions susceptible to multi-year droughts.

Growth gains from selective breeding in a spruce hybrid zone do not compromise local adaptation to climate.

PubMed

MacLachlan, Ian R; Yeaman, Sam; Aitken, Sally N

2018-02-01

Hybrid zones contain extensive standing genetic variation that facilitates rapid responses to selection. The Picea glauca  ×  Picea engelmannii hybrid zone in western Canada is the focus of tree breeding programs that annually produce ~90 million reforestation seedlings. Understanding the direct and indirect effects of selective breeding on adaptive variation is necessary to implement assisted gene flow (AGF) polices in Alberta and British Columbia that match these seedlings with future climates. We decomposed relationships among hybrid ancestry, adaptive traits, and climate to understand the implications of selective breeding for climate adaptations and AGF strategies. The effects of selection on associations among hybrid index estimated from ~6,500 SNPs, adaptive traits, and provenance climates were assessed for ~2,400 common garden seedlings. Hybrid index differences between natural and selected seedlings within breeding zones were small in Alberta (average +2%), but larger and more variable in BC (average -7%, range -24% to +1%), slightly favoring P. glauca ancestry. The average height growth gain of selected seedlings over natural seedlings within breeding zones was 36% (range 12%-86%). Clines in growth with temperature-related variables were strong, but differed little between selected and natural populations. Seedling hybrid index and growth trait associations with evapotranspiration-related climate variables were stronger in selected than in natural seedlings, indicating possible preadaptation to drier future climates. Associations among cold hardiness, hybrid ancestry, and cold-related climate variables dominated signals of local adaptation and were preserved in breeding populations. Strong hybrid ancestry-phenotype-climate associations suggest that AGF will be necessary to match interior spruce breeding populations with shifting future climates. The absence of antagonistic selection responses among traits and maintenance of cold adaptation in selected seedlings suggests breeding populations can be safely redeployed using AGF prescriptions similar to those of natural populations.

Interannual to multidecadal climate forcings on groundwater resources of the U.S. West Coast

USGS Publications Warehouse

Velasco, Elzie M.; Gurdak, Jason J.; Dickinson, Jesse; Ferré, T.P.A.; Corona, Claudia

2017-01-01

Study regionThe U.S. West Coast, including the Pacific Northwest and California Coastal Basins aquifer systems.Study focusGroundwater response to interannual to multidecadal climate variability has important implications for security within the water–energy–food nexus. Here we use Singular Spectrum Analysis to quantify the teleconnections between AMO, PDO, ENSO, and PNA and precipitation and groundwater level fluctuations. The computer program DAMP was used to provide insight on the influence of soil texture, depth to water, and mean and period of a surface infiltration flux on the damping of climate signals in the vadose zone.New hydrological insights for the regionWe find that PDO, ENSO, and PNA have significant influence on precipitation and groundwater fluctuations across a north-south gradient of the West Coast, but the lower frequency climate modes (PDO) have a greater influence on hydrologic patterns than higher frequency climate modes (ENSO and PNA). Low frequency signals tend to be preserved better in groundwater fluctuations than high frequency signals, which is a function of the degree of damping of surface variable fluxes related to soil texture, depth to water, mean and period of the infiltration flux. The teleconnection patterns that exist in surface hydrologic processes are not necessarily the same as those preserved in subsurface processes, which are affected by damping of some climate variability signals within infiltrating water.

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.

Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

Shi, X.; Dibike, Y. B.; Coulibaly, P.

2004-05-01

Climate change impact studies on watershed hydrology require reliable data at appropriate spatial and temporal resolution. However, the outputs of the current global climate models (GCMs) cannot be used directly because GCM do not provide hourly or daily precipitation and temperature reliable enough for hydrological modeling. Nevertheless, we can get more reliable data corresponding to future climate scenarios derived from GCM outputs using the so called 'downscaling techniques'. This study applies Genetic Programming (GP) based technique to downscale daily precipitation and temperature values at the Chute-du-Diable basin of the Saguenay watershed in Canada. In applying GP downscaling technique, the objective is to find a relationship between the large-scale predictor variables (NCEP data which provide daily information concerning the observed large-scale state of the atmosphere) and the predictand (meteorological data which describes conditions at the site scale). The selection of the most relevant predictor variables is achieved using the Pearson's coefficient of determination ( R2) (between the large-scale predictor variables and the daily meteorological data). In this case, the period (1961 - 2000) is identified to represent the current climate condition. For the forty years of data, the first 30 years (1961-1990) are considered for calibrating the models while the remaining ten years of data (1991-2000) are used to validate those models. In general, the R2 between the predictor variables and each predictand is very low in case of precipitation compared to that of maximum and minimum temperature. Moreover, the strength of individual predictors varies for every month and for each GP grammar. Therefore, the most appropriate combination of predictors has to be chosen by looking at the output analysis of all the twelve months and the different GP grammars. During the calibration of the GP model for precipitation downscaling, in addition to the mean daily precipitation and daily precipitation variability for each month, monthly average dry and wet-spell lengths are also considered as performance criteria. For the cases of Tmax and Tmin, means and variances of these variables corresponding to each month were considered as performance criteria. The GP downscaling results show satisfactory agreement between the observed daily temperature (Tmax and Tmin) and the simulated temperature. However, the downscaling results for the daily precipitation still require some improvement - suggesting further investigation of other grammars. KEY WORDS: Climate change; GP downscaling; GCM.

Centennial-scale vegetation dynamics and climate variability in SE Europe during Marine Isotope Stage 11 based on a pollen record from Lake Ohrid

NASA Astrophysics Data System (ADS)

Kousis, Ilias; Koutsodendris, Andreas; Peyron, Odile; Leicher, Niklas; Francke, Alexander; Wagner, Bernd; Giaccio, Biagio; Knipping, Maria; Pross, Jörg

2018-06-01

To better understand climate variability during Marine Isotope Stage (MIS) 11, we here present a new, centennial-scale-resolution pollen record from Lake Ohrid (Balkan Peninsula) derived from sediment cores retrieved during an International Continental Scientific Drilling Program (ICDP) campaign. Our palynological data, augmented by quantitative pollen-based climate reconstructions, provide insight into the vegetation dynamics and thus also climate variability in SE Europe during one of the best orbital analogues for the Holocene. Comparison of our palynological results with other proxy data from Lake Ohrid as well as with regional and global climate records shows that the vegetation in SE Europe responded sensitively both to long- and short-term climate change during MIS 11. The chronology of our palynological record is based on orbital tuning, and is further supported by the detection of a new tephra from the Vico volcano, central Italy, dated to 410 ± 2 ka. Our study indicates that MIS 11c (∼424-398 ka) was the warmest interval of MIS 11. The younger part of the interglacial (i.e., MIS 11b-11a; ∼398-367 ka) exhibits a gradual cooling trend passing over into MIS 10. It is characterized by considerable millennial-scale variability as inferred by six abrupt forest-contraction events. Interestingly, the first forest contraction occurred during full interglacial conditions of MIS 11c; this event lasted for ∼1.7 kyrs (406.2-404.5 ka) and was characterized by substantial reductions in winter temperature and annual precipitation. Most notably, it occurred ∼7 ka before the end of MIS 11c and ∼15 ka before the first strong ice-rafted debris event in the North Atlantic. Our findings suggest that millennial-scale climate variability during MIS 11 was established in Southern Europe already during MIS 11c, which is earlier than in the North Atlantic where it is registered only from MIS 11b onwards.

Recent Naval Postgraduate School Publications.

DTIC Science & Technology

1982-04-01

477 p. Haney, R L; et al.; eds. Ocean models for climate research: A workshop Sponsored by the U.S. Committee for the Global Atmos. Hes. Program. Nat... climate variability Oceanus, vol. 21, no. 4, p. 33-39, (1978). Williams, R T A review of theoretical models of atmospheric frontogenesis Chapman Conf...structure in large-scale optimization models Symp. 9 n Computer-Assisted Analysis and Model Simpification, Boulder, Colo., Mar. 24, 1980. Brown, G G

Numerical Simulations, Mean Field Theory and Modulational Stability Analysis of Thermohaline Intrusions

DTIC Science & Technology

2011-09-01

on the exchange and storage of freshwater. It is an excellent tracer of circulation, which is 3 important in the redistribution of heat and carbon ... dioxide . The Climate Variability and Predictability Program (CLIVAR) was created to investigate the “slowly varying components of the climate...fingers in the thermocline of the tropical Atlantic. Science Magazine, 308, 685–688. Schmitt, R. W., 1979: The growth rate of supercritical salt

Dynamics of change in Alaska's boreal forests: resilience and vulnerability in response to climate warming

Treesearch

A. David McGuire; F.S. Chapin; R.W. Ruess

2010-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying...

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.

Advancing NOAA NWS Arctic Program Development

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Horsfall, F. M. C.; Meyers, J. C.; Churma, M.; Thoman, R.

2016-12-01

Environmental changes in the Arctic require changes in the way the National Oceanic and Atmospheric Administration (NOAA) delivers hydrological and meteorological information to prepare the region's societies and indigenous population for emerging challenges. These challenges include changing weather patterns, changes in the timing and extent of sea ice, accelerated soil erosion due to permafrost decline, increasing coastal vulnerably, and changes in the traditional food supply. The decline in Arctic sea ice is opening new opportunities for exploitation of natural resources, commerce, tourism, and military interest. These societal challenges and economic opportunities call for a NOAA integrated approach for delivery of environmental information including climate, water, and weather data, forecasts, and warnings. Presently the NOAA Arctic Task Force provides leadership in programmatic coordination across NOAA line offices. National Weather Service (NWS) Alaska Region and the National Centers for Environmental Prediction (NCEP) provide the foundational operational hydro-meteorological products and services in the Arctic. Starting in 2016, NOAA's NWS will work toward improving its role in programmatic coordination and development through assembling an NWS Arctic Task Team. The team will foster ties in the Arctic between the 11 NWS national service programs in climate, water, and weather information, as well as between Arctic programs in NWS and other NOAA line offices and external partners. One of the team outcomes is improving decision support tools for the Arctic. The Local Climate Analysis Tool (LCAT) currently has more than 1100 registered users, including NOAA staff and technical partners. The tool has been available online since 2013 (http://nws.weather.gov/lcat/ ). The tool links trusted, recommended NOAA data and analytical capabilities to assess impacts of climate variability and climate change at local levels. A new capability currently being developed will enable analysis of sea ice changes in different parts of the Arctic, and allow users to link those change to phases of climate variability such as El Nino Southern Oscillation Arctic Oscillation, etc.

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

NASA Astrophysics Data System (ADS)

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

2007-05-01

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

The MedCLIVAR Network

NASA Astrophysics Data System (ADS)

Lionello, Piero; Medclivar Sc, The

2014-05-01

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

The Regional Integrated Sciences and Assessments (RISA) Program, Climate Services, and Meeting the National Climate Change Adaptation Challenge

NASA Astrophysics Data System (ADS)

Overpeck, J. T.; Udall, B.; Miles, E.; Dow, K.; Anderson, C.; Cayan, D.; Dettinger, M.; Hartmann, H.; Jones, J.; Mote, P.; Ray, A.; Shafer, M.; White, D.

2008-12-01

The NOAA-led RISA Program has grown steadily to nine regions and a focus that includes both natural climate variability and human-driven climate change. The RISAs are, at their core, university-based and heavily invested in partnerships, particularly with stakeholders, NOAA, and other federal agencies. RISA research, assessment and partnerships have led to new operational climate services within NOAA and other agencies, and have become important foundations in the development of local, state and regional climate change adaptation initiatives. The RISA experience indicates that a national climate service is needed, and must include: (1) services prioritized based on stakeholder needs; (2) sustained, ongoing regional interactions with users, (3) a commitment to improve climate literacy; (4) support for assessment as an ongoing, iterative process; (5) full recognition that stakeholder decisions are seldom made using climate information alone; (6) strong interagency partnership; (7) national implementation and regional in focus; (8) capability spanning local, state, tribal, regional, national and international space scales, and weeks to millennia time scales; and (9) institutional design and scientific support flexible enough to assure the effort is nimble enough to respond to rapidly-changing stakeholder needs. The RISA experience also highlights the central role that universities must play in national climate change adaptation programs. Universities have a tradition of trusted regional stakeholder partnerships, as well as the interdisciplinary expertise - including social science, ecosystem science, law, and economics - required to meet stakeholder climate-related needs; project workforce can also shift rapidly in universities. Universities have a proven ability to build and sustain interagency partnerships. Universities excel in most forms of education and training. And universities often have proven entrepreneurship, technology transfer and private sector partnership capability.

Assessing and Upgrading Ocean Mixing for the Study of Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Lindo, F.; Tulsee, V.; Canuto, V.; Cheng, Y.; Dubovikov, M. S.; Leboissetier, A.

2016-12-01

Climate is critical. Climate variability affects us all; Climate Change is a burning issue. Droughts, floods, other extreme events, and Global Warming's effects on these and problems such as sea-level rise and ecosystem disruption threaten lives. Citizens must be informed to make decisions concerning climate such as "business as usual" vs. mitigating emissions to keep warming within bounds. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. To make useful predictions we must realistically model each component of the climate system, including the ocean, whose critical role includes transporting&storing heat and dissolved CO2. We need physically based parameterizations of key ocean processes that can't be put explicitly in a global climate model, e.g. vertical&lateral mixing. The NASA-GISS turbulence group uses theory to model mixing including: 1) a comprehensive scheme for small scale vertical mixing, including convection&shear, internal waves & double-diffusion, and bottom tides 2) a new parameterization for the lateral&vertical mixing by mesoscale eddies. For better understanding we write our own programs. To assess the modelling MATLAB programs visualize and calculate statistics, including means, standard deviations and correlations, on NASA-GISS OGCM output with different mixing schemes and help us study drift from observations. We also try to upgrade the schemes, e.g. the bottom tidal mixing parameterizations' roughness, calculated from high resolution topographic data using Gaussian weighting functions with cut-offs. We study the effects of their parameters to improve them. A FORTRAN program extracts topography data subsets of manageable size for a MATLAB program, tested on idealized cases, to visualize&calculate roughness on. Students are introduced to modeling a complex system, gain a deeper appreciation of climate science, programming skills and familiarity with MATLAB, while furthering climate science by improving our mixing schemes. We are incorporating climate research into our college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293.

The forcing of southwestern Asia teleconnections by low-frequency sea surface temperature variability during boreal winter

USGS Publications Warehouse

Hoell, Andrew; Funk, Christopher C.; Mathew Barlow,

2015-01-01

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

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

IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Das, Kamalika; Kodali, Anuradha; Szubert, Marcin; Ganguly, Sangram; Bongard, Joshua

2016-01-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.

2016-12-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) scientific advances and future west pacific coordination

NASA Astrophysics Data System (ADS)

Ganachaud, A. S.; Sprintall, J.; Lin, X.; Ando, K.

2016-02-01

The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR (Climate Variability and Predictability). The key objectives are to understand the Southwest Pacific Ocean circulation and Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. It was designed to measure and monitor the ocean circulation, and to validate and improve numerical models. South Pacific oceanic waters are carried from the subtropical gyre centre in the westward flowing South Equatorial Current (SEC), towards the southwest Pacific-a major circulation pathway that redistributes water from the subtropics to the equator and Southern Ocean. Water transit through the Coral and Solomon Seas is potentially of great importance to tropical climate prediction because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate ENSO and produce basin-scale climate feedbacks. On average, the oceanic circulation is driven by the Trade Winds, and subject to substantial variability, related with the SPCZ position and intensity. The circulation is complex, with the SEC splitting into zonal jets upon encountering island archipelagos, before joining either the East Australian Current or the New Guinea Costal UnderCurrent towards the equator. SPICE included large, coordinated in situ measurement programs and high resolution numerical simulations of the area. After 8 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. We will review the recent advancements and discuss our current knowledge gaps and important emerging research directions. In particular we will discuss how SPICE, along with the Northwestern Pacific Ocean Circulation and Climate Experiment (NPOCE) and Indonesian ThroughFlow (ITF) programs could evolve toward an integrative observing system under CLIVAR coordination.

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.

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

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

Gutowski, William J.

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

National Institute for Global Environmental Change. Final Technical Report 1990-2007

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

Athanasios Toulopoulos

Research conducted by the six NIGEC Regional Centers during recent years is reported. An overview of the NIGEC program from its beginnings provides a description and evaluation of the program's vision, strategy and major accomplishments. The program's purpose was to support academic research on environmental change in regions of the country that had historically received relatively little federal funding. The overall vision of NIGEC may be stated as the performance of academic research on the regional interactions between ecosystems and climate. NIGEC's research presents important evidence on the impacts of climate variability and change, and in some cases adaptability, formore » a broad range of both managed and unmanaged ecosystems, and has thereby documented significant regional issues on the environmental responses to climate change. NIGEC's research has demonstrated large regional differences in the atmospheric carbon exchange budgets of croplands and forests, that there are significant variations of this exchange on diurnal, synoptic, seasonal and interannual time scales due to atmospheric variability (including temperature, precipitation and cloudiness), and that management practices and past history have predominant effects in grasslands and croplands. It is the mid-latitude forests, however, that have received more attention in NIGEC than any other specific ecosystem, and NIGEC's initiation of and participation in the AmeriFlux program, network of carbon flux measurement sites in North American old-growth forests, is generally considered to be its most significant single accomplishment. By including appendices with complete listings of NIGEC publications, principal investigators and participating institutions, this report may also serve as a useful comprehensive documentation of NIGEC.« less

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

Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.

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.

Hydro-climatic control of stream water dissolved organic carbon (DOC) across northern catchments within the North-Watch program

NASA Astrophysics Data System (ADS)

Laudon, Hjalmar; Tetzlaff, Doerthe; Seibert, Jan; Soulsby, Chris; Carey, Sean; Buttle, Jim; McDonnell, Jeff; McGuire, Kevin; Caissie, Daniel; Shanley, Jamie

2010-05-01

There has been an increasing interest in understanding the regulating mechanisms of surface water dissolved organic carbon (DOC) the last decade. A majority of this recent work has been based on individual well characterized research catchments or on regional synoptic datasets combined with readily available landscape and climatic variables. However, as the production and transport of DOC primarily is a function of hydro-climatic conditions a better description of catchment hydrological functioning across large geographic regions would be favorable for moving the mechanistic understanding forward. To do this we report from a first assessment of catchment DOC within the international inter-catchment comparison program North-Watch (http://www.abdn.ac.uk/northwatch/). North-Watch includes long-term research catchments ranging from northern temperate regions to the boreal and sub-arctic biomes with the aim to better understand the variable hydrological and biogeochemical responses in Northern catchments to climate change. The North-Watch catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the US (Sleepers River and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). The annual average DOC concentration in the nine catchments investigated were directly linked to hydro-climatic influences (e.g. temperature, water storage) and landscape configuration. In general, the DOC concentration followed a parabolic shape with temperature, where the highest concentrations were found in the boreal and near boreal sites and with the lowest concentrations in the temperate and sub-arctic catchments. The between catchment variability in DOC concentration could also be explained by catchment water storage and amount of wetlands in the catchment. Whereas there is a mechanistic link between long-term climatic conditions and the areal coverage of wetlands, the total catchment storage of water is more strongly linked to topography, parent material and soil depth. The result from this analysis will serve as a conceptual framework for understanding biogeochemical response to environmental change across northern catchments. The next step in this work will be to include more detailed comparisons of the role catchment hydrological functioning for explaining the patterns and dynamics of catchment DOC of these northern watersheds.

Regional climate science: lessons and opportunities

NASA Astrophysics Data System (ADS)

Mote, P. W.; Miles, E. L.; Whitely Binder, L.

2008-12-01

Since its founding in 1995, the Climate Impacts Group (CIG) at the University of Washington (UW) has achieved remarkable success at translating global- and regional-scale science into forms and products that are useful to, and used by, decision-makers. From GCM scenarios to research on the connection between global climate patterns and locally important factors like floods and wildfires, CIG's strong physical science foundation is matched by a vigorous and successful outreach program. As a result, CIG and its partner the Office of Washington State Climatologist at UW have made substantial progress at bridging the gap between climate science and decision-making, and are deeply involved in advising all levels of government and many business interests on adapting to climate variability and change. This talk will showcase some of the specific activities and tools, describe lessons learned, and illustrate how such efforts fit into a "National Climate Service."

Carbon pollution increases health inequities: lessons in resilience from the most vulnerable.

PubMed

Ebi, Kristie L; Fawcett, Stephen B; Spiegel, Jerry; Tovalin, Horacio

2016-09-01

Climate change is a social justice as well as an environmental issue. The magnitude and pattern of changes in weather and climate variables are creating differential exposures, vulnerabilities, and health risks that increase stress on health systems while exacerbating existing and creating new health inequities. Examples from national and local health adaptation projects highlight that developing partnerships across sectors and levels are critical for building climate-resilient health systems and communities. Strengthening current and implementing new health interventions, such as using environmental information to develop early warning systems, can be effective in protecting the most vulnerable. However, not all projected risks of climate change can be avoided by climate policies and programs, so health system strengthening is also critical. Applying a health inequity lens can reduce current vulnerabilities while building resilience to longer-term climate change. Taking inequities into account is critical if societies are to effectively prepare for and manage the challenges ahead.

Impacts of rainfall variability and expected rainfall changes on cost-effective adaptation of water systems to climate change.

PubMed

van der Pol, T D; van Ierland, E C; Gabbert, S; Weikard, H-P; Hendrix, E M T

2015-05-01

Stormwater drainage and other water systems are vulnerable to changes in rainfall and runoff and need to be adapted to climate change. This paper studies impacts of rainfall variability and changing return periods of rainfall extremes on cost-effective adaptation of water systems to climate change given a predefined system performance target, for example a flood risk standard. Rainfall variability causes system performance estimates to be volatile. These estimates may be used to recurrently evaluate system performance. This paper presents a model for this setting, and develops a solution method to identify cost-effective investments in stormwater drainage adaptations. Runoff and water levels are simulated with rainfall from stationary rainfall distributions, and time series of annual rainfall maxima are simulated for a climate scenario. Cost-effective investment strategies are determined by dynamic programming. The method is applied to study the choice of volume for a storage basin in a Dutch polder. We find that 'white noise', i.e. trend-free variability of rainfall, might cause earlier re-investment than expected under projected changes in rainfall. The risk of early re-investment may be reduced by increasing initial investment. This can be cost-effective if the investment involves fixed costs. Increasing initial investments, therefore, not only increases water system robustness to structural changes in rainfall, but could also offer insurance against additional costs that would occur if system performance is underestimated and re-investment becomes inevitable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization and Quantification of Uncertainty in the NARCCAP Regional Climate Model Ensemble and Application to Impacts on Water Systems

NASA Astrophysics Data System (ADS)

Mearns, L. O.; Sain, S. R.; McGinnis, S. A.; Steinschneider, S.; Brown, C. M.

2015-12-01

In this talk we present the development of a joint Bayesian Probabilistic Model for the climate change results of the North American Regional Climate Change Assessment Program (NARCCAP) that uses a unique prior in the model formulation. We use the climate change results (joint distribution of seasonal temperature and precipitation changes (future vs. current)) from the global climate models (GCMs) that provided boundary conditions for the six different regional climate models used in the program as informative priors for the bivariate Bayesian Model. The two variables involved are seasonal temperature and precipitation over sub-regions (i.e., Bukovsky Regions) of the full NARCCAP domain. The basic approach to the joint Bayesian hierarchical model follows the approach of Tebaldi and Sansó (2009). We compare model results using informative (i.e., GCM information) as well as uninformative priors. We apply these results to the Water Evaluation and Planning System (WEAP) model for the Colorado Springs Utility in Colorado. We investigate the layout of the joint pdfs in the context of the water model sensitivities to ranges of temperature and precipitation results to determine the likelihoods of future climate conditions that cannot be accommodated by possible adaptation options. Comparisons may also be made with joint pdfs formed from the CMIP5 collection of global climate models and empirically downscaled to the region of interest.

Mentor and protege attitudes towards the science mentoring program

NASA Astrophysics Data System (ADS)

Rios Jimenez, Noemaris

The purpose of this study was to examine mentor and protege attitudes towards the science mentoring program. This study focused on the attitudes that proteges and mentors participating in the Puerto Rico Statewide Systemic Initiative (PRSSI) have towards the PRSSI mentoring program and the mentoring relationship. The data was gathered from a questionnaire for mentors and beginning teachers designed by Reiman and Edelfelt in 1990. It was used to measure the mentor and protege attitudes towards the science mentoring program by three variables: mentor-protege relationship, professional development, and supportive school climate. Data were collected from 56 science teachers (proteges) and 21 mentors from fourteen (14) junior high schools. Descriptive statistics were used to indicate both proteges and mentor attitudes towards the science mentoring program. T-tests were conducted to establish if there was a statistically significant difference between protege and mentor attitudes. In conclusion, the attitudes of mentors and proteges in regard to mentor-protege relationship, professional development, and supportive school climate were similar.

Current Climate Variability & Change

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Probabilistic Climate Scenario Information for Risk Assessment

NASA Astrophysics Data System (ADS)

Dairaku, K.; Ueno, G.; Takayabu, I.

2014-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. In order to develop probabilistic regional climate information that represents the uncertainty in climate scenario experiments in Japan, we compared the physics ensemble experiments using the 60km global atmospheric model of the Meteorological Research Institute (MRI-AGCM) with multi-model ensemble experiments with global atmospheric-ocean coupled models (CMIP3) of SRES A1b scenario experiments. The MRI-AGCM shows relatively good skills particularly in tropics for temperature and geopotential height. Variability in surface air temperature of physical ensemble experiments with MRI-AGCM was within the range of one standard deviation of the CMIP3 model in the Asia region. On the other hand, the variability of precipitation was relatively well represented compared with the variation of the CMIP3 models. Models which show the similar reproducibility in the present climate shows different future climate change. We couldn't find clear relationships between present climate and future climate change in temperature and precipitation. We develop a new method to produce probabilistic information of climate change scenarios by weighting model ensemble experiments based on a regression model (Krishnamurti et al., Science, 1999). The method can be easily applicable to other regions and other physical quantities, and also to downscale to finer-scale dependent on availability of observation dataset. The prototype of probabilistic information in Japan represents the quantified structural uncertainties of multi-model ensemble experiments of climate change scenarios. Acknowledgments: This study was supported by the SOUSEI Program, funded by Ministry of Education, Culture, Sports, Science and Technology, Government of Japan.

INTER-ANNUAL AND SEASONAL VARIABILITY OF METEOROLOGICALLY-INFLUENCED EMISSIONS

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) is a participant in the U.S. Global Change Research Program (CGRP). The air quality portion of the GCRP addresses the effect on air quality attributable to climate change in the intermediate future (e.g., 2050). The first phase of ...

Promoting Climate Literacy and Conceptual Understanding among In-service Secondary Science Teachers requires an Epistemological Perspective

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Forbes, C.; Roehrig, G.; Chandler, M. A.

2017-12-01

Promoting climate literacy among in-service science teachers necessitates an understanding of fundamental concepts about the Earth's climate System (USGCRP, 2009). Very few teachers report having any formal instruction in climate science (Plutzer et al., 2016), therefore, rather simple conceptions of climate systems and their variability exist, which has implications for students' science learning (Francies et al., 1993; Libarkin, 2005; Rebich, 2005). This study uses the inferences from a NASA Innovations in Climate Education (NICE) teacher professional development program (CYCLES) to establish the necessity for developing an epistemological perspective among teachers. In CYCLES, 19 middle and high school (male=8, female=11) teachers were assessed for their understanding of global climate change (GCC). A qualitative analysis of their concept maps and an alignment of their conceptions with the Essential Principles of Climate Literacy (NOAA, 2009) demonstrated that participants emphasized on EPCL 1, 3, 6, 7 focusing on the Earth system, atmospheric, social and ecological impacts of GCC. However, EPCL 4 (variability in climate) and 5 (data-based observations and modeling) were least represented and emphasized upon. Thus, participants' descriptions about global climatic patterns were often factual rather than incorporating causation (why the temperatures are increasing) and/or correlation (describing what other factors might influence global temperatures). Therefore, engaging with epistemic dimensions of climate science to understand the processes, tools, and norms through which climate scientists study the Earth's climate system (Huxter et al., 2013) is critical for developing an in-depth conceptual understanding of climate. CLiMES (Climate Modeling and Epistemology of Science), a NSF initiative proposes to use EzGCM (EzGlobal Climate Model) to engage students and teachers in designing and running simulations, performing data processing activities, and analyzing computational models to develop their own evidence-based claims about the Earth's climate system. We describe how epistemological investigations can be conducted using EzGCM to bring the scientific process and authentic climate science practice to middle and high school classrooms.

Mainstreaming Climate Change: Recent and Ongoing Efforts to Understand, Improve, and Expand Consideration of Climate Change in Federal Water Resources Planning

NASA Astrophysics Data System (ADS)

Ferguson, I. M.; McGuire, M.; Broman, D.; Gangopadhyay, S.

2017-12-01

The Bureau of Reclamation is a Federal agency tasked with developing and managing water supply and hydropower projects in the Western U.S. Climate and hydrologic variability and change significantly impact management actions and outcomes across Reclamation's programs and initiatives, including water resource planning and operations, infrastructure design and maintenance, hydropower generation, and ecosystem restoration, among others. Planning, design, and implementation of these programs therefore requires consideration of future climate and hydrologic conditions will impact program objectives. Over the past decade, Reclamation and other Federal agencies have adopted new guidelines, directives, and mandates that require consideration of climate change in water resources planning and decision making. Meanwhile, the scientific community has developed a large number of climate projections, along with an array of models, methods, and tools to facilitate consideration of climate projections in planning and decision making. However, water resources engineers, planners, and decision makers continue to face challenges regarding how best to use the available data and tools to support major decisions, including decisions regarding infrastructure investments and long-term operating criteria. This presentation will discuss recent and ongoing research towards understanding, improving, and expanding consideration of climate projections and related uncertainties in Federal water resources planning and decision making. These research efforts address a variety of challenges, including: How to choose between available climate projection datasets and related methods, models, and tools—many of which are considered experimental or research tools? How to select an appropriate decision framework when design or operating alternatives may differ between climate scenarios? How to effectively communicate results of a climate impacts analysis to decision makers? And, how to improve robustness and resilience of water resources systems in the face of significant uncertainty? Discussion will focus on the intersection between technical challenges and decision making paradigms and the need for improved scientist-decision maker engagement through the lens of this Federal water management agency.

Statistical and Biophysical Models for Predicting Total and Outdoor Water Use in Los Angeles

NASA Astrophysics Data System (ADS)

Mini, C.; Hogue, T. S.; Pincetl, S.

2012-04-01

Modeling water demand is a complex exercise in the choice of the functional form, techniques and variables to integrate in the model. The goal of the current research is to identify the determinants that control total and outdoor residential water use in semi-arid cities and to utilize that information in the development of statistical and biophysical models that can forecast spatial and temporal urban water use. The City of Los Angeles is unique in its highly diverse socio-demographic, economic and cultural characteristics across neighborhoods, which introduces significant challenges in modeling water use. Increasing climate variability also contributes to uncertainties in water use predictions in urban areas. Monthly individual water use records were acquired from the Los Angeles Department of Water and Power (LADWP) for the 2000 to 2010 period. Study predictors of residential water use include socio-demographic, economic, climate and landscaping variables at the zip code level collected from US Census database. Climate variables are estimated from ground-based observations and calculated at the centroid of each zip code by inverse-distance weighting method. Remotely-sensed products of vegetation biomass and landscape land cover are also utilized. Two linear regression models were developed based on the panel data and variables described: a pooled-OLS regression model and a linear mixed effects model. Both models show income per capita and the percentage of landscape areas in each zip code as being statistically significant predictors. The pooled-OLS model tends to over-estimate higher water use zip codes and both models provide similar RMSE values.Outdoor water use was estimated at the census tract level as the residual between total water use and indoor use. This residual is being compared with the output from a biophysical model including tree and grass cover areas, climate variables and estimates of evapotranspiration at very high spatial resolution. A genetic algorithm based model (Shuffled Complex Evolution-UA; SCE-UA) is also being developed to provide estimates of the predictions and parameters uncertainties and to compare against the linear regression models. Ultimately, models will be selected to undertake predictions for a range of climate change and landscape scenarios. Finally, project results will contribute to a better understanding of water demand to help predict future water use and implement targeted landscaping conservation programs to maintain sustainable water needs for a growing population under uncertain climate variability.

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.

The Geographic Climate Information System Project (GEOCLIMA): Overview and preliminary results

NASA Astrophysics Data System (ADS)

Feidas, H.; Zanis, P.; Melas, D.; Vaitis, M.; Anadranistakis, E.; Symeonidis, P.; Pantelopoulos, S.

2012-04-01

The project GEOCLIMA aims at developing an integrated Geographic Information System (GIS) allowing the user to manage, analyze and visualize the information which is directly or indirectly related to climate and its future projections in Greece. The main components of the project are: a) collection and homogenization of climate and environmental related information, b) estimation of future climate change based on existing regional climate model (RCM) simulations as well as a supplementary high resolution (10 km x 10 km) simulation over the period 1961-2100 using RegCM3, c) compilation of an integrated uniform geographic database, and d) mapping of climate data, creation of digital thematic maps, and development of the integrated web GIS application. This paper provides an overview of the ongoing research efforts and preliminary results of the project. First, the trends in the annual and seasonal time series of precipitation and air temperature observations for all available stations in Greece are assessed. Then the set-up of the high resolution RCM simulation (10 km x 10 km) is discussed with respect to the selected convective scheme. Finally, the relationship of climatic variables with geophysical features over Greece such as altitude, location, distance from the sea, slope, aspect, distance from climatic barriers, land cover etc) is investigated, to support climate mapping. The research has been co-financed by the European Union (European Regional Development Fund) and Greek national funds through the Operational Program "Competitiveness and Entrepreneurship" of the National Strategic Reference Framework (NSRF) - Research Funding Program COOPERATION 2009.

Evaluating climatic response to external radiative forcing during the late Miocene to early Pliocene: New perspectives from eastern equatorial Pacific (IODP U1338) and North Atlantic (ODP 982) locations

NASA Astrophysics Data System (ADS)

Drury, Anna Joy; John, Cédric M.; Shevenell, Amelia E.

2016-01-01

Orbital-scale climate variability during the latest Miocene-early Pliocene is poorly understood due to a lack of high-resolution records spanning 8.0-3.5 Ma, which resolve all orbital cycles. Assessing this variability improves understanding of how Earth's system sensitivity to insolation evolves and provides insight into the factors driving the Messinian Salinity Crisis (MSC) and the Late Miocene Carbon Isotope Shift (LMCIS). New high-resolution benthic foraminiferal Cibicidoides mundulus δ18O and δ13C records from equatorial Pacific International Ocean Drilling Program Site U1338 are correlated to North Atlantic Ocean Drilling Program Site 982 to obtain a global perspective. Four long-term benthic δ18O variations are identified: the Tortonian-Messinian, Miocene-Pliocene, and Early-Pliocene Oxygen Isotope Lows (8-7, 5.9-4.9, and 4.8-3.5 Ma) and the Messinian Oxygen Isotope High (MOH; 7-5.9 Ma). Obliquity-paced variability dominates throughout, except during the MOH. Eleven new orbital-scale isotopic stages are identified between 7.4 and 7.1 Ma. Cryosphere and carbon cycle sensitivities, estimated from δ18O and δ13C variability, suggest a weak cryosphere-carbon cycle coupling. The MSC termination coincided with moderate cryosphere sensitivity and reduced global ice sheets. The LMCIS coincided with reduced carbon cycle sensitivity, suggesting a driving force independent of insolation changes. The response of the cryosphere and carbon cycle to obliquity forcing is established, defined as Earth System Response (ESR). Observations reveal that two late Miocene-early Pliocene climate states existed. The first is a prevailing dynamic state with moderate ESR and obliquity-driven Antarctic ice variations, associated with reduced global ice volumes. The second is a stable state, which occurred during the MOH, with reduced ESR and lower obliquity-driven variability, associated with expanded global ice volumes.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Towards an integrated set of surface meterological observations for climate science and applications

NASA Astrophysics Data System (ADS)

Dunn, Robert; Thorne, Peter

2017-04-01

We cannot predict what is not observed, and we cannot analyse what is not archived. To meet current scientific and societal demands, as well as future requirements for climate services, it is vital that the management and curation of land-based meteorological data holdings is improved. A comprehensive global set of data holdings, of known provenance, integrated across both climate variable and timescale are required to meet the wide range of user needs. Presently, the land-based holdings are highly fractured into global, region and national holdings for different variables and timescales, from a variety of sources, and in a mixture of formats. We present a high level overview, based on broad community input, of the steps that are required to bring about this integration and progress towards such a database. Any long-term, international, program creating such an integrated database will transform the our collective ability to provide societally relevant research, analysis and predictions across the globe.

Indian Ocean dipole and rainfall drive a Moran effect in East Africa malaria transmission.

PubMed

Chaves, Luis Fernando; Satake, Akiko; Hashizume, Masahiro; Minakawa, Noboru

2012-06-15

Patterns of concerted fluctuation in populations-synchrony-can reveal impacts of climatic variability on disease dynamics. We examined whether malaria transmission has been synchronous in an area with a common rainfall regime and sensitive to the Indian Ocean Dipole (IOD), a global climatic phenomenon affecting weather patterns in East Africa. We studied malaria synchrony in 5 15-year long (1984-1999) monthly time series that encompass an altitudinal gradient, approximately 1000 m to 2000 m, along Lake Victoria basin. We quantified the association patterns between rainfall and malaria time series at different altitudes and across the altitudinal gradient encompassed by the study locations. We found a positive seasonal association of rainfall with malaria, which decreased with altitude. By contrast, IOD and interannual rainfall impacts on interannual disease cycles increased with altitude. Our analysis revealed a nondecaying synchrony of similar magnitude in both malaria and rainfall, as expected under a Moran effect, supporting a role for climatic variability on malaria epidemic frequency, which might reflect rainfall-mediated changes in mosquito abundance. Synchronous malaria epidemics call for the integration of knowledge on the forcing of malaria transmission by environmental variability to develop robust malaria control and elimination programs.

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

An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO

NASA Technical Reports Server (NTRS)

Han, Rongqing; Wang, Hui; Hu, Zeng-Zhen; Kumar, Arun; Li, Weijing; Long, Lindsey N.; Schemm, Jae-Kyung E.; Peng, Peitao; Wang, Wanqiu; Si, Dong;

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...

Daily Rainfall Simulation Using Climate Variables and Nonhomogeneous Hidden Markov Model

NASA Astrophysics Data System (ADS)

Jung, J.; Kim, H. S.; Joo, H. J.; Han, D.

2017-12-01

Markov chain is an easy method to handle when we compare it with other ones for the rainfall simulation. However, it also has limitations in reflecting seasonal variability of rainfall or change on rainfall patterns caused by climate change. This study applied a Nonhomogeneous Hidden Markov Model(NHMM) to consider these problems. The NHMM compared with a Hidden Markov Model(HMM) for the evaluation of a goodness of the model. First, we chose Gum river basin in Korea to apply the models and collected daily rainfall data from the stations. Also, the climate variables of geopotential height, temperature, zonal wind, and meridional wind date were collected from NCEP/NCAR reanalysis data to consider external factors affecting the rainfall event. We conducted a correlation analysis between rainfall and climate variables then developed a linear regression equation using the climate variables which have high correlation with rainfall. The monthly rainfall was obtained by the regression equation and it became input data of NHMM. Finally, the daily rainfall by NHMM was simulated and we evaluated the goodness of fit and prediction capability of NHMM by comparing with those of HMM. As a result of simulation by HMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.2076 and 10.8243/131.1304mm each. In case of NHMM, the correlation coefficient and root mean square error of daily/monthly rainfall were 0.6652 and 10.5112/100.9865mm each. We could verify that the error of daily and monthly rainfall simulated by NHMM was improved by 2.89% and 22.99% compared with HMM. Therefore, it is expected that the results of the study could provide more accurate data for hydrologic analysis. Acknowledgements This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science, ICT & Future Planning(2017R1A2B3005695)

Remote sensing of land surface phenology

USGS Publications Warehouse

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

Medium term hurricane catastrophe models: a validation experiment

NASA Astrophysics Data System (ADS)

Bonazzi, Alessandro; Turner, Jessica; Dobbin, Alison; Wilson, Paul; Mitas, Christos; Bellone, Enrica

2013-04-01

Climate variability is a major source of uncertainty for the insurance industry underwriting hurricane risk. Catastrophe models provide their users with a stochastic set of events that expands the scope of the historical catalogue by including synthetic events that are likely to happen in a defined time-frame. The use of these catastrophe models is widespread in the insurance industry but it is only in recent years that climate variability has been explicitly accounted for. In the insurance parlance "medium term catastrophe model" refers to products that provide an adjusted view of risk that is meant to represent hurricane activity on a 1 to 5 year horizon, as opposed to long term models that integrate across the climate variability of the longest available time series of observations. In this presentation we discuss how a simple reinsurance program can be used to assess the value of medium term catastrophe models. We elaborate on similar concepts as discussed in "Potential Economic Value of Seasonal Hurricane Forecasts" by Emanuel et al. (2012, WCAS) and provide an example based on 24 years of historical data of the Chicago Mercantile Hurricane Index (CHI), an insured loss proxy. Profit and loss volatility of a hypothetical primary insurer are used to score medium term models versus their long term counterpart. Results show that medium term catastrophe models could help a hypothetical primary insurer to improve their financial resiliency to varying climate conditions.

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.

The Roles of Individual and Organizational Factors in Burnout among Community-Based Mental Health Service Providers

PubMed Central

Green, Amy E.; Albanese, Brian J.; Shapiro, Nicole M.; Aarons, Gregory A.

2014-01-01

Public sector mental health care providers are at high risk for burnout which negatively affects not only provider well-being but also the quality of services for clients and the functioning of organizations. This study examines the influence of demographics, work characteristic, and organizational variables on levels of burnout among child and adolescent mental health service providers operating within a public sector mental health service system. Additionally, given the dearth of research examining differences in burnout levels among mental health sub-disciplines (e.g., social work, psychology, marital and family therapy) and mental health programs (e.g., outpatient, day treatment, Wraparound, case management), analyses were conducted to compare levels of burnout among multiple mental health disciplines and program types. Surveys were completed by 285 providers across 49 mental health programs in a large urban public mental health system. Variables representing dimensions of organizational climate and transformational leadership accounted for the greatest amount of variance in provider reported burnout. Analyses demonstrated significantly lower levels of depersonalization among Wraparound providers compared to traditional case managers. Age was the only demographic variable related to burnout. Additionally, no significant effects were found for provider discipline or for agency tenure and caseload size. Results suggest the need to consider organizational development strategies aimed at creating more functional and less stressful climates and increasing levels of transformational leadership behaviors in order to reduce levels of burnout among clinicians working in public mental health settings for youth and families. PMID:24564442

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.

U.S. Funding is insufficient to address the human health impacts of and public health responses to climate variability and change.

PubMed

Ebi, Kristie L; Balbus, John; Kinney, Patrick L; Lipp, Erin; Mills, David; O'Neill, Marie S; Wilson, Mark L

2009-06-01

The need to identify and try to prevent adverse health impacts of climate change has risen to the forefront of climate change policy debates and become a top priority of the public health community. Given the observed and projected changes in climate and weather patterns, their current and anticipated health impacts, and the significant degree of regulatory discussion underway in the U.S. government, it is reasonable to determine the extent of federal investment in research to understand, avoid, prepare for, and respond to the human health impacts of climate change in the United States. In this commentary we summarize the health risks of climate change in the United States and examine the extent of federal funding devoted to understanding, avoiding, preparing for, and responding to the human health risks of climate change. Future climate change is projected to exacerbate various current health problems, including heat-related mortality, diarrheal diseases, and diseases associated with exposure to ozone and aeroallergens. Demographic trends and geophysical and socioeconomic factors could increase overall vulnerability. Despite these risks, extramural federal funding of climate change and health research is estimated to be < $3 million per year. Given the real risks that climate change poses for U.S. populations, the National Institutes of Health, Centers for Disease Control and Prevention, U.S. Environmental Protection Agency, and other agencies need to have robust intramural and extramural programs, with funding of > $200 million annually. Oversight of the size and priorities of these programs could be provided by a standing committee within the National Academy of Sciences.

Air Leakage of US Homes: Regression Analysis and Improvements from Retrofit

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

Chan, Wanyu R.; Joh, Jeffrey; Sherman, Max H.

2012-08-01

LBNL Residential Diagnostics Database (ResDB) contains blower door measurements and other diagnostic test results of homes in United States. Of these, approximately 134,000 single-family detached homes have sufficient information for the analysis of air leakage in relation to a number of housing characteristics. We performed regression analysis to consider the correlation between normalized leakage and a number of explanatory variables: IECC climate zone, floor area, height, year built, foundation type, duct location, and other characteristics. The regression model explains 68% of the observed variability in normalized leakage. ResDB also contains the before and after retrofit air leakage measurements of approximatelymore » 23,000 homes that participated in weatherization assistant programs (WAPs) or residential energy efficiency programs. The two types of programs achieve rather similar reductions in normalized leakage: 30% for WAPs and 20% for other energy programs.« less

Career, Family, and Institutional Variables in the Work Lives of Academic Women in the Chemical Sciences

NASA Astrophysics Data System (ADS)

Fassinger, Ruth E.; Scantlebury, Kathryn; Richmond, Geraldine

This article presents quantitative results of a study of 139 academic women in the chemical sciences who participated in a professional development program sponsored by the Committee on the Advancement of Women Chemists. The study investigated variables frequently examined in the vocational psychology of women: approaches to achievement, coping strategies, career advancement, the home-work interface, workplace climate, and mentoring. The article presents and discusses results in the context of unique issues faced by women in scientific careers.

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...

Principals' instructional management skills and middle school science teacher job satisfaction

NASA Astrophysics Data System (ADS)

Gibbs-Harper, Nzinga A.

The purpose of this research study was to determine if a relationship exists between teachers' perceptions of principals' instructional leadership behaviors and middle school teacher job satisfaction. Additionally, this study sought to assess whether principal's instructional leadership skills were predictors of middle school teachers' satisfaction with work itself. This study drew from 13 middle schools in an urban Mississippi school district. Participants included teachers who taught science. Each teacher was given the Principal Instructional Management Rating Scale (PIMRS; Hallinger, 2011) and the Teacher Job Satisfaction Questionnaire (TJSQ; Lester, 1987) to answer the research questions. The study was guided by two research questions: (a) Is there a relationship between the independent variables Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program and the dependent variable Work Itself?; (b) Are Defining the School's Mission, Managing the Instructional Program, and Developing the School Learning Climate Program predictors of Work Itself? The Pearson's correlation and multiple regression analysis were utilized to examine the relationship between the three dimensions of principals' instructional leadership and teacher satisfaction with work itself. The data revealed that there was a strong, positive correlation between all three dimensions of principals' instructional leadership and teacher satisfaction with work itself. However, the multiple regression analysis determined that teachers' perceptions of principals' instructional management skills is a slight predictor of Defining the School's Mission only.

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.

Climate variability and vulnerability to climate change: a review

PubMed Central

Thornton, Philip K; Ericksen, Polly J; Herrero, Mario; Challinor, Andrew J

2014-01-01

The focus of the great majority of climate change impact studies is on changes in mean climate. In terms of climate model output, these changes are more robust than changes in climate variability. By concentrating on changes in climate means, the full impacts of climate change on biological and human systems are probably being seriously underestimated. Here, we briefly review the possible impacts of changes in climate variability and the frequency of extreme events on biological and food systems, with a focus on the developing world. We present new analysis that tentatively links increases in climate variability with increasing food insecurity in the future. We consider the ways in which people deal with climate variability and extremes and how they may adapt in the future. Key knowledge and data gaps are highlighted. These include the timing and interactions of different climatic stresses on plant growth and development, particularly at higher temperatures, and the impacts on crops, livestock and farming systems of changes in climate variability and extreme events on pest-weed-disease complexes. We highlight the need to reframe research questions in such a way that they can provide decision makers throughout the food system with actionable answers, and the need for investment in climate and environmental monitoring. Improved understanding of the full range of impacts of climate change on biological and food systems is a critical step in being able to address effectively the effects of climate variability and extreme events on human vulnerability and food security, particularly in agriculturally based developing countries facing the challenge of having to feed rapidly growing populations in the coming decades. PMID:24668802

Statistical surrogate models for prediction of high-consequence climate change.

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

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

IAI Training in Climate and Health in the Americas

NASA Astrophysics Data System (ADS)

Aron, J. L.

2007-05-01

The Inter-American Institute for Global Change Research (IAI) has addressed training in climate and health in the Americas in two major ways. First, IAI supports students to engage in research training. A multi-country health activity funded by IAI was the collaborative research network (CRN) on Diagnostics and Prediction of Human Health Impacts in the Tropical Americas, which focused principally on the effect of El Nino/Southern Oscillation and other aspects of climate variability on mosquito-borne diseases malaria and dengue. The CRN involved students in Brazil, Mexico, Venezuela, Colombia and Jamaica. The CRN was also linked to other climate and health projects that used a similar approach. Second, IAI organizes training institutes to expand the network of global change research scientists and facilitate the transfer of global change research into practice. The IAI Training Institute on Climate and Health in the Americas was held on November 7 - 18, 2005 at the University of the West Indies in Kingston, Jamaica, engaging participants from the CRN and other programs in the Americas. The Training Institute's central objective was to help strengthen local and regional capacity to address the impacts of climate variability and climate change on human health in the populations of the Americas, particularly Latin America and the Caribbean. The Training Institute had three core components: Science; Applications; and Proposal Development for Seed Grants. Recommendations for future Training Institutes included incorporating new technologies and communicating with policy-makers to develop more proactive societal strategies to manage risks.

A High-Resolution Record of Holocene Climate Variability from a Western Canadian Coastal Inlet

NASA Astrophysics Data System (ADS)

Dallimore, A.; Thomson, R. E.; Enkin, R. J.; Kulikov, E. A.; Bertram, M. A.; Wright, C. A.; Southon, J. R.; Barrie, J. V.; Baker, J.; Pienitz, R.; Calvert, S. E.; Chang, A. S.; Pedersen, T. F.

2004-12-01

Conditions within the Pacific Ocean have a major effect on the climate of northwestern North America. High resolution records of present and past northeast Pacific climate are revealed in our multi-disciplinary study of annually laminated marine sediments from anoxic coastal inlets of British Columbia. Past climate conditions for the entire Holocene are recorded in the sediment record contained in a 40 meter, annually laminated marine sediment core taken in Effingham Inlet, on the west coast of Vancouver Island, British Columbia, from the French ship the Marion Dufresne, as part of the international IMAGES program. By combining our eight year continuous instrument record of modern coastal ocean dynamics and climate with high-resolution analysis of depositional processes, we have been able to develop proxy measurements of past climatic and oceanographic changes on annual to millennial time scales. Results indicate that regional climate has oscillated on a variety of time scales throughout the Holocene. At times, climatic change has been dramatically rapid. We are also developing digital methods for statistical time-series analyses of physical sediment properties through the Holocene in order to obtain a more objective quantitative approach for detecting cyclicity in our data. Results of the time series analysis of lamination thickness reveals statistically significant spectral peaks of climate scale variability at established decadal to century time scales. These in turn may be related to solar cycles and quasi-cyclical ocean processes such as the Pacific Decadal Oscillation. However, the annually laminated time series are periodically interrupted by massive mud intervals which are related to bottom currents and at times paleo-seismic events, illustrating the need for a full understanding of modern oceanographic and sedimentation processes, so an accurate proxy record of past climate can be established.

Setting Goals for Urban Scale Climate Governance

NASA Astrophysics Data System (ADS)

Rosenthal, J. K.; Brunner, E.

2007-12-01

The impacts of climate change on temperate urban areas may include the increase in frequency and intensity of damaging extreme weather events, such as heat waves, hurricanes, heavy rainfall or drought, and coastal flooding and erosion, and potential adverse impacts on infrastructure, energy systems, and public health. Warmer average summertime temperatures are also associated with environmental and public health liabilities, such as decreased air quality and increased peak electrical demand. Simultaneously, a strong global trend towards urbanization of poverty exists, with increased challenges for local governments to protect and sustain the well-being of growing cities and populations currently stressed by poverty, health and economic inequities. In the context of these trends, research at the city scale has sought to understand the social and economic impacts of climate change and variability and to evaluate strategies in the built environment that might serve as adaptive and mitigative responses to climate change. We review the goals and outcomes of several municipal climate protection programs, generally categorized as approaches based on technological innovation (e.g., new materials); changes in behavior and public education (e.g., neighborhood watch programs and cooling centers); improvements in urban design (e.g., zoning for mixed land-use; the use of water, vegetation and plazas to reduce the urban heat island effect); and efforts to incentivize the use of non-fossil-fuel based energy sources. Urban initiatives in European and American cities are assessed within the context of the global collective efforts enacted by the Kyoto Protocol and United Nations Framework Convention on Climate Change. Our concern is to understand the active networked role of urban managers in climate policies and programs in relation to supranational objectives and non-state actors.

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.

The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO2 in the United States

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, A.D.; Helfrich, J.

1999-01-01

We use the Terrestrial Ecosystem Model (TEM, Version 4.1) and the land cover data set of the international geosphere-biosphere program to investigate how increasing atmospheric CO2 concentration and climate variability during 1900-1994 affect the carbon storage of terrestrial ecosystems in the conterminous USA, and how carbon storage has been affected by land-use change. The estimates of TEM indicate that over the past 95 years a combination of increasing atmospheric CO2 with historical temperature and precipitation variability causes a 4.2% (4.3 Pg C) decrease in total carbon storage of potential vegetation in the conterminous US, with vegetation carbon decreasing by 7.2% (3.2 Pg C) and soil organic carbon decreasing by 1.9% (1.1 Pg C). Several dry periods including the 1930s and 1950s are responsible for the loss of carbon storage. Our factorial experiments indicate that precipitation variability alone decreases total carbon storage by 9.5%. Temperature variability alone does not significantly affect carbon storage. The effect of CO2 fertilization alone increases total carbon storage by 4.4%. The effects of increasing atmospheric CO2 and climate variability are not additive. Interactions among CO2, temperature and precipitation increase total carbon storage by 1.1%. Our study also shows substantial year-to-year variations in net carbon exchange between the atmosphere and terrestrial ecosystems due to climate variability. Since the 1960s, we estimate these terrestrial ecosystems have acted primarily as a sink of atmospheric CO2 as a result of wetter weather and higher atmospheric CO2 concentrations. For the 1980s, we estimate the natural terrestrial ecosystems, excluding cropland and urban areas, of the conterminous US have accumulated 78.2 Tg C yr-1 because of the combined effect of increasing atmospheric CO2 and climate variability. For the conterminous US, we estimate that the conversion of natural ecosystems to cropland and urban areas has caused a 18.2% (17.7 Pg C) reduction in total carbon storage from that estimated for potential vegetation. The carbon sink capacity of natural terrestrial ecosystems in the conterminous US is about 69% of that estimated for potential vegetation.

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.

Holocene dinoflagellate cyst record of climate and marine primary productivity change in the Santa Barbara Basin, southern California.

NASA Astrophysics Data System (ADS)

Pospelova, Vera; Mertens, Kenneth N.; Hendy, Ingrid, L.; Pedersen, Thomas F.

2015-04-01

High-resolution sedimentary records of dinoflagellate cysts and other marine palynomorphs from the Santa Barbara Basin (Ocean Drilling Program Hole 893A) demonstrate large variability of primary productivity during the Holocene, as the California Current System responded to climate change. Throughout the sequence, dinoflagellate cyst assemblages are characterized by the dominance of cysts produced by heterotrophic dinoflagellates, and particularly by Brigantedinium, accompanied by other upwelling-related taxa such as Echinidinium and cysts of Protoperidinium americanum. During the early Holocene (~12-7 ka), the species richness is relatively low (16 taxa) and genius Brigantedinium reaches the highest relative abundance, thus indicating nutrient-rich and highly productive waters. The middle Holocene (~7-3.5 ka) is characterized by relatively constant cyst concentrations, and dinoflagellate cyst assemblages are indicative of a slight decrease in sea-surface temperature. A noticeable increase and greater range of fluctuations in the cyst concentrations during the late Holocene (~3.5-1 ka) indicate enhanced marine primary productivity and increased climatic variability, most likely related to the intensification of El Niño-like conditions. Keywords: dinoflagellate cysts, Holocene, North Pacific, climate, primary productivity.

A Brazilian Vulnerability Index Towards Natural Disasters and Climatic Change - Flashfloods and Landslides.

NASA Astrophysics Data System (ADS)

Debortoli, N. S.; Camarinha, P. I., Sr.; Marengo, J. A.; Rodrigues, R.

2015-12-01

There are some evidences that hydrological climate extremes events have become more frequent an intense in the last decades due to climatic change. In Brazil, flashfloods and landslides were responsible for 74% of the deaths related to natural disasters in 1991-2010 period. In this sense, climate change could be considered a threat which can further increase these numbers, if actions of adaptation and reducing vulnerability are not taken. To evaluate Brazil's vulnerability hotspots to these disasters, two vulnerability indexes were developed using three sets of variables: (1) climate, with IPCC climate extreme indexes; (2) environmental, including land use, drainage systems, relief map, slope, road density and hydrography variables; (3) socioeconomic, including Gini coefficient, HDI (Human Development Index), housing conditions and poverty-related index. The variables were normalized on a scale between 0 to 1 and related using Map Algebra technique (ArcGIS). As part of the effort to contribute to the elaboration of the Third National Communication to the United Nations Framework Convention on Climate Change (UNFCCC), and to contribute to the assessment of impacts on strategic country's issues, simulations at higher resolution were carried out using Eta-20km RCM (Regional Climate Model) nested with two global climate models: HadGEM ES and MIROC 5 (INPE Brazilian National Institute for Space Research). For the baseline period of 1961-1990, the vulnerability indexes were adjusted by an iterative process, which was validated by comparing it to the Brazilian National Disasters Data. The same indexes found at baseline were used to estimate the vulnerability until the end of the XXI century, using the 4.5 and 8.5 IPCC/AR5 RCP (Representative Concentration Pathways) scenarios. The results indicate a large increase in Brazil's vulnerability to landslides mainly in coastal zone, southern states, high lands of southeast states, and along the Amazon River due to climatic aspects only, not considering other factors such as increase in population size, etc. Flashfloods vulnerability, on the other hand, increases mostly in the south/southeast regions, the northeast coastal zone and parts of the Amazon basin. Funded by: Ministry of Science and Technology of Brazil and the United Nations Development Program in Brazil.

Local weather, regional climate, and annual survival of the northern spotted owl

USGS Publications Warehouse

Glenn, E.M.; Anthony, R.G.; Forsman, E.D.; Olson, G.S.

2011-01-01

We used an information-theoretical approach and Cormack-Jolly-Seber models for open populations in program MARK to examine relationships between survival rates of Northern Spotted Owls and a variety of local weather variables and long-term climate variables. In four of the six populations examined, survival was positively associated with wetter than normal conditions during the growing season or high summer temperatures. At the three study areas located at the highest elevations, survival was positively associated with winter temperature but also had a negative or quadratic relation with the number of storms and winter precipitation. A metaanalysis of all six areas combined indicated that annual survival was most strongly associated with phase shifts in the Southern Oscillation and Pacific Decadal Oscillation, which reflect large-scale temperature and precipitation patterns in this region. Climate accounted for a variable amount (1-41%) of the total process variation in annual survival but for more year-to-year variation (3-66%) than did spatial variation among owl territories (0-7%). Negative associations between survival and cold, wet winters and nesting seasons were similar to those found in other studies of the Spotted Owl. The relationships between survival and growing-season precipitation and regional climate patterns, however, had not been reported for this species previously. Climate-change models for the first half of the 21st century predict warmer, wetter winters and hotter, drier summers for the Pacific Northwest. Our results indicate that these conditions could decrease Spotted Owl survival in some areas. Copyright ?? The Cooper Ornithological Society 2011.

Hydrologic impacts of climate and land use changes over the Three-North region of China: implication for the forestation programs in arid and semiarid regions

NASA Astrophysics Data System (ADS)

Xie, X.; Liang, S.

2013-12-01

The Three-North region of China, including the northeastern, northern, and northwestern areas, covers an area of more than three million square kilometers. This region is featured for its arid and semiarid environments with annual rainfall less than 450 mm. During the past few decades, the Three-North region has experienced noticeable water-cycle variations owing to the climate and land use changes. Typically, several large-scale forestation programs such as the Three Norths Forest Shelterbelt Program began since late 1970s, have been implemented across this region in order to solve desertification and dust storm problems, and to combat the loss of water and soil. These programs raised debates, however, because their effectiveness does not likely achieve what was expected and they even imposed negative influences on the eco-hydrologic system in some areas. Currently most studies were based on in-situ measurements and individual catchments and primarily attributed the water-cycle variations to the forestation. In this study we attempt to evaluate the impact of combined climate and land use changes using remote sensing data and a sophisticated land surface model, i.e., the Three-Layer Variable Infiltration Capacity (VIC-3L). Four land use maps derived from Landsat TM images for 1990, 1995, 2000 and 2005 were used to detect the land use changes in the three-north regions, and leaf area index (LAI) from the Global Land Surface Satellite (GLASS) LAI product was employed to assess the land cover change and the effect of forestation programs. After model calibration and validation based on gauged streamflow and evapotranspiration from China FluxNet, a series of simulation scenarios were designed to examine the impacts of climate and land use changes on soil moisture, runoff and evapotranspiration and to identify each contribution to water fluxes. It was found that within the study area as a whole, LAI shows an increasing trend during 1980-2009 in response to the forestation programs. However, the hydrologic variables (i.e., the soil moisture, runoff and evapotranspiration) in northern and northwestern regions are more significantly affected by the precipitation and temperature than by the land use changes, although the impacts of land use change are uneven across the entire region. So, the forestation probably plays a modest role in the hydrologic system.

Using altimetry to help explain patchy changes in hydrographic carbon measurements

NASA Astrophysics Data System (ADS)

Rodgers, Keith B.; Key, Robert M.; Gnanadesikan, Anand; Sarmiento, Jorge L.; Aumont, Olivier; Bopp, Laurent; Doney, Scott C.; Dunne, John P.; Glover, David M.; Ishida, Akio; Ishii, Masao; Jacobson, Andrew R.; Lo Monaco, Claire; Maier-Reimer, Ernst; Mercier, Herlé; Metzl, Nicolas; PéRez, Fiz F.; Rios, Aida F.; Wanninkhof, Rik; Wetzel, Patrick; Winn, Christopher D.; Yamanaka, Yasuhiro

2009-09-01

Here we use observations and ocean models to identify mechanisms driving large seasonal to interannual variations in dissolved inorganic carbon (DIC) and dissolved oxygen (O2) in the upper ocean. We begin with observations linking variations in upper ocean DIC and O2 inventories with changes in the physical state of the ocean. Models are subsequently used to address the extent to which the relationships derived from short-timescale (6 months to 2 years) repeat measurements are representative of variations over larger spatial and temporal scales. The main new result is that convergence and divergence (column stretching) attributed to baroclinic Rossby waves can make a first-order contribution to DIC and O2 variability in the upper ocean. This results in a close correspondence between natural variations in DIC and O2 column inventory variations and sea surface height (SSH) variations over much of the ocean. Oceanic Rossby wave activity is an intrinsic part of the natural variability in the climate system and is elevated even in the absence of significant interannual variability in climate mode indices. The close correspondence between SSH and both DIC and O2 column inventories for many regions suggests that SSH changes (inferred from satellite altimetry) may prove useful in reducing uncertainty in separating natural and anthropogenic DIC signals (using measurements from Climate Variability and Predictability's CO2/Repeat Hydrography program).

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.

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.

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

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

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

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

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

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

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.

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.

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.

Climate Change Impacts on Migration in the Vulnerable Countries

NASA Astrophysics Data System (ADS)

An, Nazan; Incealtin, Gamze; Kurnaz, M. Levent; Şengün Ucal, Meltem

2014-05-01

This work focuses on the economic, demographic and environmental drivers of migration related with the sustainable development in underdeveloped and developed countries, which are the most vulnerable to the climate change impacts through the Climate-Development Modeling including climate modeling and panel logit data analysis. We have studied some countries namely Bangladesh, Netherlands, Morocco, Malaysia, Ethiopia and Bolivia. We have analyzed these countries according to their economic, demographic and environmental indicators related with the determinants of migration, and we tried to indicate that their conditions differ according to all these factors concerning with the climate change impacts. This modeling covers some explanatory variables, which have the relationship with the migration, including GDP per capita, population, temperature and precipitation, which indicate the seasonal differences according to the years, the occurrence of natural hazards over the years, coastal location of countries, permanent cropland areas and fish capture which represents the amount of capturing over the years. We analyzed that whether there is a relationship between the migration and these explanatory variables. In order to achieve sustainable development by preventing or decreasing environmental migration due to climate change impacts or related other factors, these countries need to maintain economic, social, political, demographic, and in particular environmental performance. There are some significant risks stemming from climate change, which is not under control. When the economic and environmental conditions are considered, we have to regard climate change to be the more destructive force for those who are less defensible against all of these risks and impacts of uncontrolled climate change. This work was supported by the BU Research Fund under the project number 6990. One of the authors (MLK) was partially supported by Mercator-IPC Fellowship Program.

Ocean climate data for user community in West and Central Africa: Needs, opportunities, and challenges

NASA Technical Reports Server (NTRS)

Ojo, S. O.

1992-01-01

The urgent need to improve data delivery systems needed by scientists studying ocean role in climate and climate characteristics has been manifested in recent years because of the unprecedented climatic events experienced in many parts of the world. Indeed, there has been a striking and growing realization by governments and the general public indicating that national economies and human welfare depend on climate and its variability. In West and Central Africa, for instance climatic events, which have resulted in floods and droughts, have caused a lot of concern to both governments and people of the region. In particular, the droughts have been so widespread that greater awareness and concern have become generated for the need to find solutions to the problems created by the consequences of the climatic events. Particularly in the southern border regions of the Sahara Desert as well as in the Sahel region, the drought episodes considerably reduced food production and led to series of socioeconomic problems, not only in the areas affected by the droughts, but also in the other parts of West Africa. The various climatic variabilities which have caused the climatic events are no doubt related to the ocean-atmosphere interactions. Unfortunately, not much has been done on the understanding of these interactions, particularly as they affect developing countries. Indeed, not much has been done to develop programs which will reflect the general concerns and needs for researching into the ocean-atmosphere systems and their implications on man-environmental systems in many developing countries. This is for example, true of West and Central Africa, where compared with the middle latitude countries, much less is known about the characteristics of the ocean-atmosphere systems and their significance on man-environmental systems of the area.

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

Evaluation and prediction of shrub cover in coastal Oregon forests (USA)

Treesearch

Becky K. Kerns; Janet L. Ohmann

2004-01-01

We used data from regional forest inventories and research programs, coupled with mapped climatic and topographic information, to explore relationships and develop multiple linear regression (MLR) and regression tree models for total and deciduous shrub cover in the Oregon coastal province. Results from both types of models indicate that forest structure variables were...

Ground cover, erosion risk and production implications of targeted management practices in Australian mixed farming systems: lessons from the Grain and Graze program

USDA-ARS?s Scientific Manuscript database

Maintaining the productive capacity of the agricultural soils of Australia's broadacre cropping zone requires careful management, given a highly variable climate and soils that are susceptible to degradation. Mixed croplivestock farming systems are the predominant land use across these regions and m...

Establishment and spread of a single parthenogenic genotype of the Mediterranean arundo wasp, Tetramesa romana in the variable climate of Texas

USDA-ARS?s Scientific Manuscript database

As part of a biological control program for the invasive weed, Arundo donax, several genotypically unique populations of the parthenogenetic stem-galling wasp, Tetramesa romana Walker (Hymenoptera: Eurytomidae), from Spain and France were released in the infested riparian zone along the Rio Grande f...

Nature's Notebook and Extension: Engaging Citizen-Scientists and 4-H Youth to Observe a Changing Environment

ERIC Educational Resources Information Center

Posthumus, Erin E.; Barnett, LoriAnne; Crimmins, Theresa M.; Kish, George R.; Sheftall, Will; Stancioff, Esperanza; Warren, Peter

2013-01-01

Extension, with its access to long-term volunteers, has the unique ability to teach citizen scientists about the connection between climate variability and the resulting effects on plants, animals, and thus, humans. The USA National Phenology Network's Nature's Notebook on-line program provides a science learning tool for Extension's Master…

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.

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.

An ecological genetic delineation of local seed-source provenance for ecological restoration

PubMed Central

Krauss, Siegfried L; Sinclair, Elizabeth A; Bussell, John D; Hobbs, Richard J

2013-01-01

An increasingly important practical application of the analysis of spatial genetic structure within plant species is to help define the extent of local provenance seed collection zones that minimize negative impacts in ecological restoration programs. Here, we derive seed sourcing guidelines from a novel range-wide assessment of spatial genetic structure of 24 populations of Banksia menziesii (Proteaceae), a widely distributed Western Australian tree of significance in local ecological restoration programs. An analysis of molecular variance (AMOVA) of 100 amplified fragment length polymorphism (AFLP) markers revealed significant genetic differentiation among populations (ΦPT = 0.18). Pairwise population genetic dissimilarity was correlated with geographic distance, but not environmental distance derived from 15 climate variables, suggesting overall neutrality of these markers with regard to these climate variables. Nevertheless, Bayesian outlier analysis identified four markers potentially under selection, although these were not correlated with the climate variables. We calculated a global R-statistic using analysis of similarities (ANOSIM) to test the statistical significance of population differentiation and to infer a threshold seed collection zone distance of ∼60 km (all markers) and 100 km (outlier markers) when genetic distance was regressed against geographic distance. Population pairs separated by >60 km were, on average, twice as likely to be significantly genetically differentiated than population pairs separated by <60 km, suggesting that habitat-matched sites within a 30-km radius around a restoration site genetically defines a local provenance seed collection zone for B. menziesii. Our approach is a novel probability-based practical solution for the delineation of a local seed collection zone to minimize negative genetic impacts in ecological restoration. PMID:23919158

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.

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.

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.

Are general and strategic measures of organizational context and leadership associated with knowledge and attitudes toward evidence-based practices in public behavioral health settings? A cross-sectional observational study.

PubMed

Powell, Byron J; Mandell, David S; Hadley, Trevor R; Rubin, Ronnie M; Evans, Arthur C; Hurford, Matthew O; Beidas, Rinad S

2017-05-12

Examining the role of modifiable barriers and facilitators is a necessary step toward developing effective implementation strategies. This study examines whether both general (organizational culture, organizational climate, and transformational leadership) and strategic (implementation climate and implementation leadership) organizational-level factors predict therapist-level determinants of implementation (knowledge of and attitudes toward evidence-based practices). Within the context of a system-wide effort to increase the use of evidence-based practices (EBPs) and recovery-oriented care, we conducted an observational, cross-sectional study of 19 child-serving agencies in the City of Philadelphia, including 23 sites, 130 therapists, 36 supervisors, and 22 executive administrators. Organizational variables included characteristics such as EBP initiative participation, program size, and proportion of independent contractor therapists; general factors such as organizational culture and climate (Organizational Social Context Measurement System) and transformational leadership (Multifactor Leadership Questionnaire); and strategic factors such as implementation climate (Implementation Climate Scale) and implementation leadership (Implementation Leadership Scale). Therapist-level variables included demographics, attitudes toward EBPs (Evidence-Based Practice Attitudes Scale), and knowledge of EBPs (Knowledge of Evidence-Based Services Questionnaire). We used linear mixed-effects regression models to estimate the associations between the predictor (organizational characteristics, general and strategic factors) and dependent (knowledge of and attitudes toward EBPs) variables. Several variables were associated with therapists' knowledge of EBPs. Clinicians in organizations with more proficient cultures or higher levels of transformational leadership (idealized influence) had greater knowledge of EBPs; conversely, clinicians in organizations with more resistant cultures, more functional organizational climates, and implementation climates characterized by higher levels of financial reward for EBPs had less knowledge of EBPs. A number of organizational factors were associated with the therapists' attitudes toward EBPs. For example, more engaged organizational cultures, implementation climates characterized by higher levels of educational support, and more proactive implementation leadership were all associated with more positive attitudes toward EBPs. This study provides evidence for the importance of both general and strategic organizational determinants as predictors of knowledge of and attitudes toward EBPs. The findings highlight the need for longitudinal and mixed-methods studies that examine the influence of organizational factors on implementation.

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 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.

The roles of individual and organizational factors in burnout among community-based mental health service providers.

PubMed

Green, Amy E; Albanese, Brian J; Shapiro, Nicole M; Aarons, Gregory A

2014-02-01

Public-sector mental health care providers are at high risk for burnout, which negatively affects not only provider well-being but also the quality of services for clients and the functioning of organizations. This study examines the influence of demographics, work characteristic, and organizational variables on levels of burnout among child and adolescent mental health service providers operating within a public-sector mental health service system. Additionally, given the dearth of research examining differences in burnout levels among mental health subdisciplines (e.g., social work, psychology, marital and family therapy) and mental health programs (e.g., outpatient, day treatment, wraparound, case management), analyses were conducted to compare levels of burnout among multiple mental health disciplines and program types. Surveys were completed by 285 providers across 49 mental health programs in a large urban public mental health system. Variables representing dimensions of organizational climate and transformational leadership accounted for the greatest amount of variance in provider reported burnout. Analyses demonstrated significantly lower levels of depersonalization among wraparound providers compared to traditional case managers. Age was the only demographic variable related to burnout. Additionally, no significant effects were found for provider discipline or for agency tenure and caseload size. Results suggest the need to consider organizational development strategies aimed at creating more functional and less stressful climates and increasing levels of transformational leadership behaviors in order to reduce levels of burnout among clinicians working in public mental health settings for youth and families. PsycINFO Database Record (c) 2014 APA, all rights reserved.

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.

The Integrating Role of the LBA and the LPB Programs as an Example of Cyberinfrastructures in International Scientific Collaboration

NASA Astrophysics Data System (ADS)

Dias, P. L.

2007-05-01

International science collaboration is a key component of research programs such as the The Large Scale Biosphere Atmosphere Interaction Program (LBA) and the La Plata Basin Project (LPB). Both are programs with crosscutting science questions permeating different areas of knowledge related to the functioning of the natural and agricultural ecosystems in the Amazon system (LBA) and the change in the hydrological, agricultural and social systems of the Plata Basin (LPB) ecosystem under natural climatic variability and climate change. Both programs are strongly related to GEWEX, CLIVAR and IGBP and are based on extensive use of data information system (LBA/LPB/DIS) with mirror sites in the US, Europe and South America. These international programs have a significant impact in building up regional scientific capabilities at all levels of education and triggered the establishment of new research groups located in remote areas of South America. The cyberinfrastructure has been fundamental to promote the integration of the research groups, and a remarkable feedback with the operational forecasting systems has been detected. The LBA/LPB should be used as examples on how to promote international scientific and operational collaboration.

Monitoring ecosystem quality and function in arid settings of the Mojave Desert

USGS Publications Warehouse

Belnap, Jayne; Webb, Robert H.; Miller, Mark E.; Miller, David M.; DeFalco, Lesley A.; Medica, Philip A.; Brooks, Matthew L.; Esque, Todd C.; Bedford, Dave

2008-01-01

Monitoring ecosystem quality and function in the Mojave Desert is both a requirement of state and Federal government agencies and a means for determining potential long-term changes induced by climatic fluctuations and land use. Because it is not feasible to measure every attribute and process in the desert ecosystem, the choice of what to measure and where to measure it is the most important starting point of any monitoring program. In the Mojave Desert, ecosystem function is strongly influenced by both abiotic and biotic factors, and an understanding of the temporal and spatial variability induced by climate and landform development is needed to determine where site-specific measurements should be made. We review a wide variety of techniques for sampling, assessing, and measuring climatic variables, desert soils, biological soil crusts, annual and perennial vegetation, reptiles, and small mammals. The complete array of ecosystem attributes and processes that we describe are unlikely to be measured or monitored at any given location, but the array of possibilities allows for the development of specific monitoring protocols, which can be tailored to suit the needs of land-management agencies.

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Shen, Sunhung; Leptoukh, Gregory G.; Gerasimov, Irina

2012-01-01

Vegetation growth depends on local climate. Significant anthropogenic land cover and land use change activities over Asia have changed vegetation distribution as well. On the other hand, vegetation is one of the important land surface variables that influence the Asian Monsoon variability through controlling atmospheric energy and water vapor conditions. In this presentation, the mean and variations of vegetation index of last decade at regional scale resolution (5km and higher) from MODIS have been analyzed. Results indicate that the vegetation index has been reduced significantly during last decade over fast urbanization areas in east China, such as Yangtze River Delta, where local surface temperatures were increased significantly in term of urban heat Island. The relationship between vegetation Index and climate (surface temperature, precipitation) over a grassland in northern Asia and over a woody savannas in southeast Asia are studied. In supporting Monsoon Asian Integrated Regional Study (MAIRS) program, the data in this study have been integrated into Giovanni, the online visualization and analysis system at NASA GES DISC. Most images in this presentation are generated from Giovanni system.

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.

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

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.

The combined and separate impacts of climate extremes on the current and future US rainfed maize and soybean production under elevated CO 2

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

Jin, Zhenong; Zhuang, Qianlai; Wang, Jiali

Heat and drought stresses are two emerging climatic threats to the US maize and soybean production, yet their impacts on yields are collectively determined by the magnitude of climate change and rising atmospheric CO2 concentration. Here we present a study that quantified the current and future yield responses of US rainfed maize and soybean to climate extremes, and for the first time characterized spatial shifts in the relative importance of temperature, heat and drought stress. Crop yields are simulated using the Agricultural Production Systems sIMulator (APSIM), driven by the high-resolution (12 km) Weather Research and Forecasting (WRF) Model downscaled futuremore » climate scenarios at two time slices (1995-2005 and 2085-2094). Our results show that climatic yield gaps and interannual variability are greater in the core production area than in the remaining US by the late 21st century under both Representative Concentration Pathway (RCP) 4.5 and RCP8.5 scenarios, and the magnitude of change is highly dependent on the current climate sensitivity and vulnerability. Elevated CO2 partially offsets the climatic yield gaps and reduces interannual yield variability, and effect is more prominent in soybean than in maize. We demonstrate that drought will continue to be the largest threat to US rainfed maize and soybean production, although its dominant role gradually gives way to other impacts of heat extremes. We also reveal that shifts in the geographic distributions of dominant stressors are characterized by increases in the concurrent stress, especially for the US Midwest. These findings imply the importance of considering drought and extreme heat simultaneously for future agronomic adaptation and mitigation strategies, particularly for breeding programs and crop management.« less

Hydrological alteration of the Upper Nakdong river under AR5 climate change scenarios

NASA Astrophysics Data System (ADS)

Kim, S.; Park, Y.; Cha, W. Y.; Okjeong, L.; Choi, J.; Lee, J.

2016-12-01

One of the tasks faced to water engineers is how to consider the climate change impact in our water resources management. Especially in South Korea, where almost all drinking water is taken from major rivers, the public attention is focused on their eco-hydrologic status. In this study, the effect of climate change on eco-hydrologic regime in the Upper Nakdong river which is one of major rivers in South Korea is investigated using SWAT. The simulation results are measured using the indicators of hydrological alteration (IHA) established by U.S. Nature Conservancy. Future climate information is obtained by scaling historical series, provided by Korean Meteorological Administration RCM (KMA RCM) and four RCP scenarios. KMA RCM has 12.5-km spatial resolution in Korean Peninsula and is produced by UK Hedley Centre regional climate model HadGEM3-RA. The RCM bias is corrected by the Kernel density distribution mapping (KDDM) method. The KDDM estimates the cumulative probability density function (CDF) of each dataset using kernel density estimation, and is implemented by quantile-mapping the CDF of a present climate variable obtained from the RCM onto that of the corresponding observed climate variable. Although the simulation results from different RCP scenarios show diverse hydrologic responses in our watershed, the mainstream of future simulation results indicate that there will be more river flow in southeast Korea. The predicted impacts of hydrological alteration caused by climate change on the aquatic ecosystem in the Upper Nakdong river will be presented. Acknowledgement This research was supported by a grant(14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

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.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Climate Science Performance, Data and Productivity on Titan

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

Mayer, Benjamin W; Worley, Patrick H; Gaddis, Abigail L

2015-01-01

Climate Science models are flagship codes for the largest of high performance computing (HPC) resources, both in visibility, with the newly launched Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) effort, and in terms of significant fractions of system usage. The performance of the DOE ACME model is captured with application level timers and examined through a sizeable run archive. Performance and variability of compute, queue time and ancillary services are examined. As Climate Science advances in the use of HPC resources there has been an increase in the required human and data systems to achieve programs goals.more » A description of current workflow processes (hardware, software, human) and planned automation of the workflow, along with historical and projected data in motion and at rest data usage, are detailed. The combination of these two topics motivates a description of future systems requirements for DOE Climate Modeling efforts, focusing on the growth of data storage and network and disk bandwidth required to handle data at an acceptable rate.« less

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.

Residential Cold Climate Heat Pump (CCHP) w/Variable Speed Technology

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

Messmer, Craig S.

2016-09-30

This report summarizes the results of a three year program awarded to Unico, Inc. to commercialize a residential cold climate heat pump. Several designs were investigated. Compressors were selected using analysis from Oakridge National Laboratories followed by prototype construction and lab testing in a specially built environmental chamber capable of reaching -30°F. The initial design utilized two variable speed compressors in series with very good capacity results and acceptable efficiency at very cold temperatures. The design was then modified to reduce cost and complexity by redesigning the system using three dual-stage compressors: two in parallel followed by one in series.more » Extensive testing found significant challenge with oil management, reliability, weight and cost which prevented the system from being fully commercialized. Further analysis of other conceptual designs indicated that these challenges could be overcome in the future.« less

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

NASA Astrophysics Data System (ADS)

LIM, J.; Lall, U.

2017-12-01

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

Lodgepole pine site index in relation to synoptic measures of climate, soil moisture and soil nutrients.

Treesearch

G. Geoff Wang; Shongming Huang; Robert A. Monserud; Ryan J. Klos

2004-01-01

Lodgepole pine site index was examined in relation to synoptic measures of topography, soil moisture, and soil nutrients in Alberta. Data came from 214 lodgepole pine-dominated stands sampled as a part of the provincial permanent sample plot program. Spatial location (elevation, latitude, and longitude) and natural subregions (NSRs) were topographic variables that...

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.

Improved National Response to Climate Change: Aligning USGCRP reports and the U.S. Climate Resilience Toolkit

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Dahlman, L. E.; Herring, D.; Fox, J. F.

2017-12-01

As part of an effort to coordinate production and distribution of scientific climate information across the U.S. Government, and to spur adaptation actions across the nation, the U.S. Global Change Research Program (USGCRP) has worked to better integrate the U.S. Climate Resilience Toolkit (CRT) and its Climate Explorer (CE) tool into USGCRP activities and products. Much of the initial CRT content was based on the Third National Climate Assessment (NCA3). The opportunity to integrate current development of NCA4—scheduled for release in late 2018—with CRT and CE can enhance all three projects and result in a useable and "living" NCA that is part of USGCRP's approach to sustained climate assessment. To coordinate this work, a USGCRP-led science team worked with CRT staff and CE developers to update the set of climate projections displayed in the CE tool. In concert with the USGCRP scenarios effort, the combined team selected the Localized Constructed Analogs (LOCA) dataset for the updated version of CE, based on its capabilities for capturing climate extremes and local climate variations. The team identified 28 variables from the LOCA dataset for display in the CE; many of these variables will also be used in USGCRP reports. In CRT engagements, communities with vulnerable assets have expressed a high value for the ability to integrate climate data available through the CE with data related to non-climate stressors in their locations. Moving forward, the teams intend to serve climate information needs at additional spatial scales by making NCA4 content available via CE's capability for dynamic interaction with climate-relevant datasets. This will permit users to customize the extent of data they access for decision-making, starting with the static NCA4 report. Additionally, NCA4 case studies and other content can be linked to more in-depth content within the CRT site. This capability will enable more frequent content updates than can be managed with quadrennial NCA reports. Overall, enhanced integration between USGCRP and CRT will provide consistent information for communities that are assessing their climate vulnerabilities or considering adaptation options.

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

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.

Fish Productivity in Open-Ocean Gyre Systems in the Late Oligocene and Miocene

NASA Astrophysics Data System (ADS)

Cuevas, J. M.; Sibert, E. C.; Norris, R. D.

2015-12-01

Understanding how marine ecosystems respond to climate change is very important as we continue to warm the climate. Fish represent a critical protein source for a significant portion of the global population, and as such, an understanding of fish production and its interactions with climate change may help better prepare for the future. Ichthyoliths, fossil fish teeth and shark scales, are a novel fossil group which can be used as an indicator for fish productivity. Several important climate events occurred during the Miocene (7 to 23 Ma), including the Middle Miocene Climatic Optimum. Here we reconstruct fish production from across the Miocene from Pacific and Atlantic Ocean gyres. South Atlantic samples, from Deep Sea Drilling Program (DSDP) Site 522 spanning from 30 to 20 Ma, show fairly variable numbers in the Oligocene (ranging from 100 to 800 ich/cm2/yr), but stabilization in the Early Miocene (around 400 ich/cm2/yr), suggesting that the beginning of the Miocene brought consistent conditions for fish production. In the North Pacific, our record from Ocean Drilling Program (ODP) Site 886 shows a distinct crash in fish productivity at 11 Ma, from 3500 ich/cm2/yr to a steady decline around 100 ich/cm2/yr for the next million years. This crash is followed by a marked increase in the presence of diatoms and biogenous opal. This is somewhat surprising, since in modern oceanic systems, an increase in diatoms and other large-celled phytoplankton is associated with shorter, more efficient food chains and higher levels of fish. It is also interesting to note that denticles remain consistently low at both sites, indicating consistently low shark populations through this time period. Together, these results suggest that the Late Oligocene and Miocene was a time of variable fish production and provide a window into understanding of dynamic ecosystem changes through the Miocene in open-ocean gyre ecosystems.

Living with a Star: New Opportunities in Sun-Climate Research

NASA Technical Reports Server (NTRS)

2003-01-01

Living With a Star is a NASA initiative employing the combination of dedicated spacecraft with targeted research and modeling efforts to improve what we know of solar effects of all kinds on the Earth and its surrounding space environment, with particular emphasis on those that have significant practical impacts on life and society. The highest priority among these concerns is the subject of this report: the potential effects of solar variability on regional and global climate, including the extent to which solar variability has contributed to the well-documented warming of the Earth in the last 100 years. Understanding how the climate system reacts to external forcing from the Sun will also greatly improve our knowledge of how climate will respond to other climate drivers, including those of anthropogenic origin. A parallel element of the LWS program addresses solar effects on space weather : the impulsive emissions of charged particles, short-wave electromagnetic radiation and magnetic disturbances in the upper atmosphere and near-Earth environment that also affect life and society. These include a wide variety of solar impacts on aeronautics, astronautics, electric power transmission, and national defense. Specific examples are (1) the impacts of potentially- damaging high energy radiation and atomic particles of solar origin on satellites and satellite operations, spacecraft electronics systems and components, electronic communications, electric power distribution grids, navigational and GPS systems, and high altitude aircraft; and (2) the threat of sporadic, high-energy solar radiation to astronauts and high altitude aircraft passengers and crews. Elements of the LWS program include an array of dedicated spacecraft in near- Earth and near-Sun orbits that will closely study and observe both the Sun itself and the impacts of its variations on the Earth's radiation belts and magnetosphere, the upper atmosphere, and ionosphere. These spacecraft, positioned to study and monitor changing conditions in the Sun-Earth neighborhood, will also serve as sentinels of solar storms and impulsive events.

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.

Welcome to NASA's Earth Science Enterprise. Version 3

NASA Technical Reports Server (NTRS)

2001-01-01

There are strong scientific indications that natural change in the Earth system is being accelerated by human intervention. As a result, planet Earth faces the possibility of rapid environmental changes that would have a profound impact on all nations. However, we do not fully understand either the short-term effects of our activities, or their long-term implications - many important scientific questions remain unanswered. The National Aeronautics and Space Administration (NASA) is working with the national and international scientific communities to establish a sound scientific basis for addressing these critical issues through research efforts coordinated under the U.S. Global Change Research Program, the International Geosphere-Biosphere Program, and the World Climate Research Program. The Earth Science Enterprise is NASA's contribution to the U.S. Global Change Research Program. NASA's Earth Science Enterprise will use space- and surface-based measurement systems to provide the scientific basis for understanding global change. The space-based components will provide a constellation of satellites to monitor the Earth from space. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). The overall objective of the EOS Program is to determine the extent, causes, and regional consequences of global climate change. EOS will provide sustained space-based observations that will allow researchers to monitor climate variables over time to determine trends. A constellation of EOS satellites will acquire global data, beginning in 1998 and extending well into the 21st century.

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

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.

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.

Drought Prediction Site Specific and Regional up to Three Years in Advance

NASA Astrophysics Data System (ADS)

Suhler, G.; O'Brien, D. P.

2002-12-01

Dynamic Predictables has developed proprietary software that analyzes and predicts future climatic behavior based on past data. The programs employ both a regional thermodynamic model together with a unique predictive algorithm to achieve a high degree of prediction accuracy up to 36 months. The thermodynamic model was developed initially to explain the results of a study on global circulation models done at SUNY-Stony Brook by S. Hameed, R.G. Currie, and H. LaGrone (Int. Jour. Climatology, 15, pp.852-871, 1995). The authors pointed out that on a time scale of 2-70 months the spectrum of sea level pressure is dominated by the harmonics and subharmonics of the seasonal cycle and their combination tones. These oscillations are fundamental to an understanding of climatic variations on a sub-regional to continental basis. The oscillatory nature of these variations allows them to be used as broad based climate predictors. In addition, they can be subtracted from the data to yield residuals. The residuals are then analyzed to determine components that are predictable. The program then combines both the thermodynamic model results (the primary predictive model) with those from the residual data (the secondary model) to yield an estimate of the future behavior of the climatic variable. Spatial resolution is site specific or aggregated regional based upon appropriate length (45 years or more monthly data) and reasonable quality weather observation records. Most climate analysis has been based on monthly time-step data, but time scales on the order of days can be used. Oregon Climate Division 1 (Coastal) precipitation provides an example relating DynaPred's method to nature's observed elements in the early 2000s. The prediction's leading dynamic factors are the strong seasonal in the primary model combined with high secondary model contributions from planet Earth's Chandler Wobble (near 15 months) and what has been called the Quasi-Triennial Oscillation (QTO, near 36 months) in equatorial regions. Examples of regional aggregate and site-specific predictions previously made blind forward and publicly available (AASC Annual Meetings 1998-2002) will be shown. Certain climate dynamics features relevant to extrema prediction and specifically drought prediction will then be discussed. Time steps presented will be monthly. Climate variables examined are mean temperature and accumulated precipitation. NINO3 SST, interior continental and marine/continental transition area examples will be shown. http://www.dynamicpredictables.com

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Jiang, J. H.

2013-12-01

The latest Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with newly available global observations. The traditional approach to climate model evaluation, which compares a single parameter at a time, identifies symptomatic model biases and errors but fails to diagnose the model problems. The model diagnosis process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. To address these challenges, we are developing a parallel, distributed web-service system that enables the physics-based multi-variable model performance evaluations and diagnoses through the comprehensive and synergistic use of multiple observational data, reanalysis data, and model outputs. We have developed a methodology to transform an existing science application code into a web service using a Python wrapper interface and Python web service frameworks (i.e., Flask, Gunicorn, and Tornado). The web-service system, called Climate Model Diagnostic Analyzer (CMDA), currently supports (1) all the datasets from Obs4MIPs and a few ocean datasets from NOAA and Argo, which can serve as observation-based reference data for model evaluation and (2) many of CMIP5 model outputs covering a broad range of atmosphere, ocean, and land variables from the CMIP5 specific historical runs and AMIP runs. Analysis capabilities currently supported by CMDA are (1) the calculation of annual and seasonal means of physical variables, (2) the calculation of time evolution of the means in any specified geographical region, (3) the calculation of correlation between two variables, and (4) the calculation of difference between two variables. A web user interface is chosen for CMDA because it not only lowers the learning curve and removes the adoption barrier of the tool but also enables instantaneous use, avoiding the hassle of local software installation and environment incompatibility. CMDA is planned to be used as an educational tool for the summer school organized by JPL's Center for Climate Science in 2014. The requirements of the educational tool are defined with the interaction with the school organizers, and CMDA is customized to meet the requirements accordingly. The tool needs to be production quality for 30+ simultaneous users. The summer school will thus serve as a valuable testbed for the tool development, preparing CMDA to serve the Earth-science modeling and model-analysis community at the end of the project. This work was funded by the NASA Earth Science Program called Computational Modeling Algorithms and Cyberinfrastructure (CMAC).

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.

Evaluation of mean climate in a chemistry-climate model simulation

NASA Astrophysics Data System (ADS)

Hong, S.; Park, H.; Wie, J.; Park, R.; Lee, S.; Moon, B. K.

2017-12-01

Incorporation of the interactive chemistry is essential for understanding chemistry-climate interactions and feedback processes in climate models. Here we assess a newly developed chemistry-climate model (GRIMs-Chem), which is based on the Global/Regional Integrated Model system (GRIMs) including the aerosol direct effect as well as stratospheric linearized ozone chemistry (LINOZ). We conducted GRIMs-Chem with observed sea surface temperature during the period of 1979-2010, and compared the simulation results with observations and also with CMIP models. To measure the relative performance of our model, we define the quantitative performance metric using the Taylor diagram. This metric allow us to assess overall features in simulating multiple variables. Overall, our model better reproduce the zonal mean spatial pattern of temperature, horizontal wind, vertical motion, and relative humidity relative to other models. However, the model did not produce good simulations at upper troposphere (200 hPa). It is currently unclear which model processes are responsible for this. AcknowledgementsThis research was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program."

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.

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

NASA Astrophysics Data System (ADS)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

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.

Climate | National Oceanic and Atmospheric Administration

Science.gov Websites

to help people understand and prepare for climate variability and change. Climate. NOAA From to help people understand and prepare for climate variability and change. LATEST FEATURES // Ocean Jump to Content Enter Search Terms Weather Climate Oceans & Coasts Fisheries Satellites

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,…

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

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.

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

Parsons, Brian; Cochran, Jaquelin; Watson, Andrea

As a recognized leader in efforts to mitigate global climate change, the Government of Mexico (GOM) works proactively to reduce emissions, demonstrating strong political will and capacity to comprehensively address climate change. Since 2010, the U.S. government (USG) has supported these efforts by partnering with Mexico under the Enhancing Capacity for Low Emission Development Strategies (EC-LEDS) program. Through the program, the USG has partnered with Mexico’s Ministry of Energy (SENER), as well as other government agencies, to support GOM in reaching its clean energy and climate change goals. Specifically, the EC-LEDS program is supporting GOM’s clean energy goal of generatingmore » 35% of its electricity from renewable energy (RE) by 2024. EC-LEDS, through the U.S. Agency for International Development (USAID) and the U.S Department of Energy’s (DOE’s) National Renewable Energy Laboratory (NREL), has been collaborating with SENER and GOM interagency working group—the Consejo Consultivo para las Energías Renovables (Consultative Council on Renewable Energy)—to create a grid integration roadmap for variable RE. 1 A key objective in creating a grid integration roadmap is assessing likely impacts of wind and solar energy on the power system and modifying planning and operations accordingly. This paper applies best practices in conducting a grid integration study to the Mexican context.« less

WASCAL - West African Science Service Center on Climate Change and Adapted Land Use Regional Climate Simulations and Land-Atmosphere Simulations for West Africa at DKRZ and elsewhere

NASA Astrophysics Data System (ADS)

Hamann, Ilse; Arnault, Joel; Bliefernicht, Jan; Klein, Cornelia; Heinzeller, Dominikus; Kunstmann, Harald

2014-05-01

Changing climate and hydro-meteorological boundary conditions are among the most severe challenges to Africa in the 21st century. In particular West Africa faces an urgent need to develop effective adaptation and mitigation strategies to cope with negative impacts on humans and environment due to climate change, increased hydro-meteorological variability and land use changes. To help meet these challenges, the German Federal Ministry of Education and Research (BMBF) started an initiative with institutions in Germany and West African countries to establish together a West African Science Service Center on Climate Change and Adapted Land Use (WASCAL). This activity is accompanied by an establishment of trans-boundary observation networks, an interdisciplinary core research program and graduate research programs on climate change and related issues for strengthening the analytical capabilities of the Science Service Center. A key research activity of the WASCAL Competence Center is the provision of regional climate simulations in a fine spatio-temporal resolution for the core research sites of WASCAL for the present and the near future. The climate information is needed for subsequent local climate impact studies in agriculture, water resources and further socio-economic sectors. The simulation experiments are performed using regional climate models such as COSMO-CLM, RegCM and WRF and statistical techniques for a further refinement of the projections. The core research sites of WASCAL are located in the Sudanian Savannah belt in Northern Ghana, Southern Burkina Faso and Northern Benin. The climate in this region is semi-arid with six rainy months. Due to the strong population growth in West Africa, many areas of the Sudanian Savannah have been already converted to farmland since the majority of the people are living directly or indirectly from the income produced in agriculture. The simulation experiments of the Competence Center and the Core Research Program are accompanied by the WASCAL Graduate Research Program on the West African Climate System. The GRP-WACS provides ten scholarships per year for West African PhD students with a duration of three years. Present and future WASCAL PhD students will constitute one important user group of the Linux cluster that will be installed at the Competence Center in Ouagadougou, Burkina Faso. Regional Land-Atmosphere Simulations A key research activity of the WASCAL Core Research Program is the analysis of interactions between the land surface and the atmosphere to investigate how land surface changes affect hydro-meteorological surface fluxes such as evapotranspiration. Since current land surface models of global and regional climate models neglect dominant lateral hydrological processes such as surface runoff, a novel land surface model is used, the NCAR Distributed Hydrological Modeling System (NDHMS). This model can be coupled to WRF (WRF-Hydro) to perform two-way coupled atmospheric-hydrological simulations for the watershed of interest. Hardware and network prerequisites include a HPC cluster, network switches, internal storage media, Internet connectivity of sufficient bandwidth. Competences needed are HPC, storage, and visualization systems optimized for climate research, parallelization and optimization of climate models and workflows, efficient management of highest data volumes.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Reconstruction of Past Climatic Variability

DTIC Science & Technology

1976-03-01

Research Projects Agency/IPT 1400 Wilson Boulevard 7$ 10 . PROGRAM ELEMENT, PROJECT, TASK AREA S WORK UNIT NUMBERS 62706E AO 2221-3 Mr WCPOWT...Conclusions " II. INTRODUCTION 8 III. COLLECTIONS 10 A. North American Temperate Sites 10 B. North American Arctic Sites 10 C. European...Work Time Required to Collect and Process a ^ ^ 200- to 400-Year Ring-Width Chronology Statistics for 10 Tree-Ring Chronologies

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...

The End of the Penultimate Interglacial Recorded in Santa Barbara Basin, California

NASA Astrophysics Data System (ADS)

Cannariato, K. G.; Kennett, J. P.

2005-12-01

The marine sediments accumulating in the Santa Barbara Basin, located on the southern California margin, represent a remarkable climate archive. The high sediment accumulation rate, location at the intersection of the cool California Current and warm Countercurrent, and other factors affecting the basin have combined to make the paleoclimate records generated from these sediments highly resolved and very sensitive to global climate change. Because of the effort by Dr. James Kennett over a decade ago to persuade the Ocean Drilling Program to core the basin, the paleoceanographic community has been able to produce some of the most detailed records of Northern Hemisphere climate change over most of the last two glacial-interglacial cycles rivaling those of the Greenland ice cores. Here we present high-resolution planktic and benthic oxygen isotope records from that Santa Barbara Basin core, ODP Site 893, covering the penultimate interglacial and the beginning of the last glacial (MIS 5e to 5d transition). The results indicate that the California Current system exhibited millennial and centennial variability during the penultimate interglacial similar to the early-middle Holocene. The magnitude of this millennial variability increased dramatically and quickly during the transition from MIS 5e to 5d. These millennial-scale oscillations appear to be correlated to those recognized in the North Atlantic region. The implications of this variability will be discussed.

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.

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.

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

A cross-assessment of CCI-ECVs and RCSM simulations over the Mediterranean area

NASA Astrophysics Data System (ADS)

D'Errico, Miriam; Planton, Serge; Nabat, Pierre

2017-04-01

A first objective of this study, conducted in the framework of the Climate Modelling Users Group (CMUG), one of the projects of the European Space Agency Climate Change Initiative (ESA CCI) program, is a cross-assessment of simulations of a Med-CORDEX regional climate system model (CNRM-RCSM5) and a sub-set of atmosphere, marine and surface interrelated Satellite-Derived Essential Climate Variables (CCI-ECVs) (i.e. sea surface temperature, sea level, aerosols and soil moisture content) over the Mediterranean area. The consistency between the model and the CCI-ECVs is evaluated through the analysis of a climate specific event that can be observed with the CCI-ECVs, in atmospheric reanalysis and reproduced in the RCSM simulations. In this presentation we focus on the July 2006 heat wave that affected the western part of the Mediterranean continental and marine area. The application of a spectral nudging method using ERA-Interim reanalysis in our simulation allows to reproduce this event with a proper chronology. As a result we show that the consistency between the simulated model aerosol optical depth and the ECV products (being produced by the ESA Aerosol CCI project consortium) depends on the choice of the algorithm used to infer the variable from the satellite observations. In particular the heat wave main characteristics become consistent between the model and the satellite-derived observations for sea surface temperature, soil moisture and sea level. The link between the atmospheric circulation and the aerosols distribution is also investigated.

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.

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

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.

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.

Impacts of climate on shrubland fuels and fire behavior in the Owyhee Basin, Idaho

NASA Astrophysics Data System (ADS)

Vogelmann, J. E.; Shi, H.; Hawbaker, T.; Li, Z.

2013-12-01

There is evidence that wildland fire is increasing as a function of global change. However, fire activity is spatially, temporally and ecologically variable across the globe, and our understanding of fire risk and behavior in many ecosystems is limited. After a series of severe fire seasons that occurred during the late 1990's in the western United States, the LANDFIRE program was developed with the goals of providing the fire community with objective spatial fuel data for assessing wildland fire risk. Even with access to the data provided by LANDFIRE, assessing fire behavior in shrublands in sagebrush-dominated ecosystems of the western United States has proven especially problematic, in part due to the complex nature of the vegetation, the variable influence of understory vegetation including invasive species (e.g. cheatgrass), and prior fire history events. Climate is undoubtedly playing a major role, affecting the intra- and inter-annual variability in vegetation conditions, which in turn impacts fire behavior. In order to further our understanding of climate-vegetation-fire interactions in shrublands, we initiated a study in the Owyhee Basin, which is located in southwestern Idaho and adjacent Nevada. Our goals include: (1) assessing the relationship between climate and vegetation condition, (2) quantifying the range of temporal variability in grassland and shrubland fuel loads, (3) identifying methods to operationally map the variability in fuel loads, and (4) assessing how the variability in fuel loads affect fire spread simulations. To address these goals, we are using a wide variety of geospatial data, including remotely sensed time-series data sets derived from MODIS and Landsat, and climate data from DAYMET and PRISM. Remotely-sensed information is used to characterize climate-induced temporal variability in primary productivity in the Basin, where fire spread can be extensive after senescence when dry vegetation is added to dead fuel loads. Gridded climate data indicate that this area has become warmer and dryer over the previous three decades. We have also observed that fires are especially prevalent in areas that have high Normalized Difference Vegetation Index (NDVI) values in the spring, followed by low NDVI in the summer. At present we are concentrating on the temporally rich MODIS data to map spatial and temporal variability in live fuel loads. To translate NDVI to biomass, we are scaling the range of biomass values using data from the literature. We assume that departure from maximum NDVI, typically occurring during spring, to NDVI values later in the season are related to the proportion of live biomass transferred to dead biomass, which burns more readily than green biomass. Using the FARSITE fire spread model, our initial simulations show that the conversion from live herbaceous fuel to dead fuel increases the burn area by 30% compared with using default static fuel parameters. This indicates that current fuel models underestimate fire spread and areas that could potentially burn. Our study also indicates that a combined remote sensing product with good temporal resolution (MODIS) and spatial resolution (Landsat) is necessary to provide accurate information on the fuel dynamics in shrublands.

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.

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 .

Climate Change Projection for the Department of Energy's Savannah River Site

NASA Astrophysics Data System (ADS)

Werth, D. W.

2014-12-01

As per recent Department of Energy (DOE) sustainability requirements, the Savannah River National Laboratory (SRNL) is developing a climate projection for the DOE's Savannah River Site (SRS) near Aiken, SC. This will comprise data from both a statistical and a dynamic downscaling process, each interpolated to the SRS. We require variables most relevant to operational activities at the site (such as the US Forest Service's forest management program), and select temperature, precipitation, wind, and humidity as being most relevant to energy and water resource requirements, fire and forest ecology, and facility and worker safety. We then develop projections of the means and extremes of these variables, estimate the effect on site operations, and develop long-term mitigation strategies. For example, given that outdoor work while wearing protective gear is a daily facet of site operations, heat stress is of primary importance to work planning, and we use the downscaled data to estimate changes in the occurrence of high temperatures. For the statistical downscaling, we use global climate model (GCM) data from the Climate Model Intercomparison Project, version 5 (CMIP-5), which was used in the IPCC Fifth Assessment Report (AR5). GCM data from five research groups was selected, and two climate change scenarios - RCP 4.5 and RCP 8.5 - are used with observed data from site instruments and other databases to produce the downscaled projections. We apply a quantile regression downscaling method, which involves the use of the observed cumulative distribution function to correct that of the GCM. This produces a downscaled projection with an interannual variability closer to that of the observed data and allows for more extreme values in the projections, which are often absent in GCM data. The statistically downscaled data is complemented with dynamically downscaled data from the NARCCAP database, which comprises output from regional climate models forced with GCM output from the CMIP-3 database of GCM simulations. Applications of the downscaled climate projections to some of the unique operational needs of a large DOE weapons complex site are described.

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.

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.

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.

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.

Generating temporal model using climate variables for the prediction of dengue cases in Subang Jaya, Malaysia

PubMed Central

Dom, Nazri Che; Hassan, A Abu; Latif, Z Abd; Ismail, Rodziah

2013-01-01

Objective To develop a forecasting model for the incidence of dengue cases in Subang Jaya using time series analysis. Methods The model was performed using the Autoregressive Integrated Moving Average (ARIMA) based on data collected from 2005 to 2010. The fitted model was then used to predict dengue incidence for the year 2010 by extrapolating dengue patterns using three different approaches (i.e. 52, 13 and 4 weeks ahead). Finally cross correlation between dengue incidence and climate variable was computed over a range of lags in order to identify significant variables to be included as external regressor. Results The result of this study revealed that the ARIMA (2,0,0) (0,0,1)52 model developed, closely described the trends of dengue incidence and confirmed the existence of dengue fever cases in Subang Jaya for the year 2005 to 2010. The prediction per period of 4 weeks ahead for ARIMA (2,0,0)(0,0,1)52 was found to be best fit and consistent with the observed dengue incidence based on the training data from 2005 to 2010 (Root Mean Square Error=0.61). The predictive power of ARIMA (2,0,0) (0,0,1)52 is enhanced by the inclusion of climate variables as external regressor to forecast the dengue cases for the year 2010. Conclusions The ARIMA model with weekly variation is a useful tool for disease control and prevention program as it is able to effectively predict the number of dengue cases in Malaysia.

Indian-Southern Ocean Latitudinal Transect (ISOLAT): A proposal for the recovery of high-resolution sedimentary records in the western Indian Ocean sector of the Southern Ocean

NASA Astrophysics Data System (ADS)

Mackensen, A.; Zahn, R.; Hall, I.; Kuhn, G.; Koc, N.; Francois, R.; Hemming, S.; Goldstein, S.; Rogers, J.; Ehrmann, W.

2003-04-01

Quantifying oceanic variability at timescales of oceanic, atmospheric, and cryospheric processes are the fundamental objectives of the international IMAGES program. In this context the Southern Ocean plays a leading role in that it is involved, through its influence on global ocean circulation and carbon budget, with the development and maintenance of the Earth's climate system. The seas surrounding Antarctica contain the world's only zonal circum-global current system that entrains water masses from the three main ocean basins, and maintains the thermal isolation of Antarctica from warmer surface waters to the north. Furthermore, the Southern Ocean is a major site of bottom and intermediate water formation and thus actively impacts the global thermohaline circulation (THC). This proposal is an outcome of the IMAGES Southern Ocean Working Group and constitutes one component of a suite of new IMAGES/IODP initiatives that aim at resolving past variability of the Antarctic Circumpolar Current (ACC) on orbital and sub-orbital timescales and its involvement with rapid global ocean variability and climate instability. The primary aim of this proposal is to determine millennial- to sub-centennial scale variability of the ACC and the ensuing Atlantic-Indian water transports, including surface transports and deep-water flow. We will focus on periods of rapid ocean and climate change and assess the role of the Southern Ocean in these changes, both in terms of its thermohaline circulation and biogeochemical inventories. We propose a suite of 11 sites that form a latitudinal transect across the ACC in the westernmost Indian Ocean sector of the Southern Ocean. The transect is designed to allow the reconstruction of ACC variability across a range of latitudes in conjunction with meridional shifts of the surface ocean fronts. The northernmost reaches of the transect extend into the Agulhas Current and its retroflection system which is a key component of the THC warm water return flow to the Atlantic. The principal topics are: (i) the response of the ACC to climate variability; (ii) the history of the Southern Ocean surface ocean fronts during periods of rapid climate change; (iii) the history of North Atlantic Deep Water (NADW) export to the deep South Indian Ocean; (iv) the variability of Southern Ocean biogeochemical fluxes and their influence on Circumpolar Deep Water (CDW) carbon inventories and atmospheric chemistry; and (v) the variability of surface ocean fronts and the Indian-Atlantic surface ocean density flux. To achieve these objectives we will generate fine-scale records of palaeoceanographic proxies that are linked to a variety of climatically relevant ocean parameters. Temporal resolution of the records, depending on sedimentation rates, will range from millennial to sub-centennial time scales. Highest sedimentation rates are expected at coring sites located on current-controlled sediment drifts, whereas dense sampling of cores with moderate sedimentation rates will enable at least millennial-scale events to be resolved.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Emerging Forms of Climate Protection Governance: Urban Initiatives in the European Union

NASA Astrophysics Data System (ADS)

Rosenthal, J. K.; Brunner, E.

2006-12-01

Changes in climate patterns are expected to pose increasing challenges for cities in the following decades, with adverse impacts on urban populations currently stressed by poverty, health and economic inequities. Simultaneously, a strong global trend towards urbanization of poverty exists, with increased challenges for local governments to protect and sustain the well-being of growing cities. In the context of these two overarching trends, interdisciplinary research at the city scale is prioritized for understanding the social impacts of climate change and variability and for the evaluation of strategies in the built environment that might serve as adaptive and mitigative responses to climate change. Urban managers, and transnational networks of municipalities and non-state actors, have taken an increasingly active role in climate protection, through research, policies, programs and agreements on adaptation and mitigation strategies. Concerns for urban impacts of climate change include the potential increase in frequency and intensity of damaging extreme weather events, such as heat waves, hurricanes, heavy rainfall or drought, and coastal flooding and erosion, and potentially adverse impacts on infrastructure, energy systems, and public health. Higher average summertime temperatures in temperate zone cities are also associated with environmental and public health liabilities such as decreased air quality and increased peak electrical demand. We review municipal climate protection programs, generally categorized as approaches based on technological innovation (e.g., new materials); changes in behavior and public education (e.g., use of cooling centers); and improvements in urban design (e.g., zoning for mixed land-use; the use of water, vegetation and plazas to reduce the urban heat island effect). Climate protection initiatives in three European cities are assessed within the context of the global collective efforts enacted by the Kyoto Protocol and United Nations Framework Convention on Climate Change. Initiatives in Stockholm, London and Milan provide evidence that local actions are inevitable and of central importance to mitigate and adapt to the adverse impacts of climate change, the urban heat island effect, and extreme weather events.

Separating out the influence of climatic trend, fluctuations, and extreme events on crop yield: a case study in Hunan Province, China

NASA Astrophysics Data System (ADS)

Wang, Zhu; Shi, Peijun; Zhang, Zhao; Meng, Yongchang; Luan, Yibo; Wang, Jiwei

2017-09-01

Separating out the influence of climatic trend, fluctuations and extreme events on crop yield is of paramount importance to climate change adaptation, resilience, and mitigation. Previous studies lack systematic and explicit assessment of these three fundamental aspects of climate change on crop yield. This research attempts to separate out the impacts on rice yields of climatic trend (linear trend change related to mean value), fluctuations (variability surpassing the "fluctuation threshold" which defined as one standard deviation (1 SD) of the residual between the original data series and the linear trend value for each climatic variable), and extreme events (identified by absolute criterion for each kind of extreme events related to crop yield). The main idea of the research method was to construct climate scenarios combined with crop system simulation model. Comparable climate scenarios were designed to express the impact of each climate change component and, were input to the crop system model (CERES-Rice), which calculated the related simulated yield gap to quantify the percentage impacts of climatic trend, fluctuations, and extreme events. Six Agro-Meteorological Stations (AMS) in Hunan province were selected to study the quantitatively impact of climatic trend, fluctuations and extreme events involving climatic variables (air temperature, precipitation, and sunshine duration) on early rice yield during 1981-2012. The results showed that extreme events were found to have the greatest impact on early rice yield (-2.59 to -15.89%). Followed by climatic fluctuations with a range of -2.60 to -4.46%, and then the climatic trend (4.91-2.12%). Furthermore, the influence of climatic trend on early rice yield presented "trade-offs" among various climate variables and AMS. Climatic trend and extreme events associated with air temperature showed larger effects on early rice yield than other climatic variables, particularly for high-temperature events (-2.11 to -12.99%). Finally, the methodology use to separate out the influences of the climatic trend, fluctuations, and extreme events on crop yield was proved to be feasible and robust. Designing different climate scenarios and feeding them into a crop system model is a potential way to evaluate the quantitative impact of each climate variable.

Designing management strategies for carbon dioxide storage and utilization under uncertainty using inexact modelling

NASA Astrophysics Data System (ADS)

Wang, Yu; Fan, Jie; Xu, Ye; Sun, Wei; Chen, Dong

2017-06-01

Effective application of carbon capture, utilization and storage (CCUS) systems could help to alleviate the influence of climate change by reducing carbon dioxide (CO2) emissions. The research objective of this study is to develop an equilibrium chance-constrained programming model with bi-random variables (ECCP model) for supporting the CCUS management system under random circumstances. The major advantage of the ECCP model is that it tackles random variables as bi-random variables with a normal distribution, where the mean values follow a normal distribution. This could avoid irrational assumptions and oversimplifications in the process of parameter design and enrich the theory of stochastic optimization. The ECCP model is solved by an equilibrium change-constrained programming algorithm, which provides convenience for decision makers to rank the solution set using the natural order of real numbers. The ECCP model is applied to a CCUS management problem, and the solutions could be useful in helping managers to design and generate rational CO2-allocation patterns under complexities and uncertainties.

CORDEX Coordinated Output for Regional Evaluation

NASA Astrophysics Data System (ADS)

Gutowski, William; Giorgi, Filippo; Lake, Irene

2017-04-01

The Science Advisory Team for the Coordinated Regional Downscaling Experiment (CORDEX) has developed a baseline framework of specified regions, resolutions and simulation periods intended to provide a foundation for ongoing regional CORDEX activities: the CORDEX Coordinated Output for Regional Evaluation, or CORDEX-CORE. CORDEX-CORE was conceived in part to be responsive to IPCC needs for coordinated simulations that could provide regional climate downscaling (RCD) that yields fine-scale climate information beyond that resolved by GCMs. For each CORDEX region, a matrix of GCM-RCD experiments is designed based on the need to cover as much as possible different dimensions of the uncertainty space (e.g., different emissions and land-use scenarios, GCMs, RCD models and techniques). An appropriate set of driving GCMs can allow a program of simulations that efficiently addresses key scientific issues within CORDEX, while facilitating comparison and transfer of results and lessons learned across different regions. The CORDEX-CORE program seeks to provide, as much as possible, homogeneity across domains, so it is envisioned that a standard set of regional climate models (RCMs) and empirical statistical downscaling (ESD) methods will downscale a standard set of GCMs over all or at least most CORDEX domains for a minimum set of scenarios (high and low end). The focus is on historical climate simulations for the 20th century and projections for 21st century, implying that data would be needed minimally for the period 1950-2100 (but ideally 1900-2100). This foundational ensemble can be regionally enriched with further contributions (additional GCM-RCD pairs) by individual groups over their selected domains of interest. The RCM model resolution for these core experiments will be in the range of 10-20 km, a resolution that has been shown to provide substantial added value for a variety of climate variables and that represents a significant forward step compared in the CORDEX program. This presentation presents the vision and structure of CORDEX-CORE while also soliciting discussion on plans for implementing the program.

Antarctica and Global Environmental Change - Lessons from the Past Inform Climate Change Policy Today

NASA Astrophysics Data System (ADS)

Dunbar, R. B.; Scientific Team Of Odp Drilling Leg 318; Andrill Science Team

2011-12-01

Antarctic's continental ice, sea ice, and the broader Southern Ocean form a coupled and complex climate system that interacts in important yet poorly understood ways with the low and mid-latitudes. Because of its unusual sovereignty status and the fact that there is no indigenous human population, information about climate change in Antarctica penetrates the policy world less readily than findings from other regions. Yet, Antarctica's potential to impact climate change globally is disproportionately large. Vulnerable portions of the ice sheet may contribute up to 3 to 5 meters of sea level rise in the coming centuries, including significant amounts within the next 50 years. Loss of sea ice and other changes in the Southern Ocean may reduce oceanic uptake of excess atmospheric carbon dioxide, exacerbating global warming worldwide. Antarctica's impact on the Southern Hemisphere wind field is now well-established, contributing to ongoing decadal-scale perturbations in continental precipitation as well as major reorganizations of Southern Ocean food chains. Recent scientific drilling programs in the Ross Sea and off Wilkes Land, Antarctica, provide valuable insights into past climatic and biogeochemical change in Antarctica, insights of great relevance to international and national climate change policy. In this paper, we discuss polar amplification, sea level variability coupled to Antarctic ice volume, and response timescales as seen through the lens of past climate change. One key result emerging from multiple drilling programs is recognition of unanticipated dynamism in the Antarctic ice sheet during portions of the Pliocene (at a time with pCO2 levels equivalent to those anticipated late this century) as well as during "super-interglacials" of the Pleistocene. Evidence for substantially warmer ocean temperatures and reduced sea ice cover at these times suggests that polar amplification of natural climate variability, even under scenarios of relative small amounts of radiative forcing, is strong at all timescales. It also appears that we are committed to the attainment of pCO2 levels within the next several decades that in the past were associated with substantial reductions in Antarctic glacial ice volume, and hence significant amounts of global sea level rise. New and detailed studies of past warm intervals as well as the most recent deglaciation reveal the potential for century-scale (or even more rapid) melt events. A new ultra-high resolution record of East Antarctic climate change extending to the most recent deglaciation reveals unusually large climatic excursions in both the earliest Holocene and mid-Holocene. Taken together, the paleoclimate record derived from geological drilling in Antarctica should be taken by policymakers as substantial and credible new evidence of increased risk of dangerous climate change in the decades and century ahead.

Examining for any impact of climate change on the association between seasonality and hospitalization for mania.

PubMed

Parker, Gordon B; Hadzi-Pavlovic, Dusan; Graham, Rebecca K

2017-01-15

Studies have established higher rates of hospitalization for mania in spring and summer and posit various explanatory climatic variables. As the earth's climate is changing, we pursue whether this is reflected in the yearly seasonal variation in hospitalizations for mania. This would be indicated by the presence of secular changes in both the hospitalization seasonal pattern and climatic variables, and associations between both variable sets. Data were obtained for 21,882 individuals hospitalized to psychiatric hospitals in the Australian state of New South Wales (NSW) over a 14-year period (2000-2014) with ICD-diagnosed mania - and with NSW population figures and salient climatic variables collected for the same period. Regression analyses were conducted to examine the predictive value of climate variables on hospital admissions. Data quantified a peak for manic admissions in spring of the southern hemisphere, in the months of October and November. There was a significant linear increase in manic admissions (0.5%/year) over the 14-year time period, with significant variation across years. In terms of climatic variables, there was a significant linear trend over the interval for solar radiation, although the trend indicated a decrease rather than an increase. Seasonal variation in admissions was most closely associated with two climate variables - evaporation in the current month and temperature in the previous month. Hospitalization rates do not necessarily provide an accurate estimate of the onset of manic episodes and findings may be limited to the southern hemisphere, or New South Wales. While overall findings do not support the hypothesis that climate change is leading to a higher seasonal impact for manic hospital admissions in the southern hemisphere, analyses identified two climate/weather variables - evaporation and temperature - that may account for the yearly spring excess. Copyright © 2016 Elsevier B.V. All rights reserved.

Quantitative approaches in climate change ecology

PubMed Central

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

2011-01-01

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

A method for screening climate change-sensitive infectious diseases.

PubMed

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-14

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change.

A Method for Screening Climate Change-Sensitive Infectious Diseases

PubMed Central

Wang, Yunjing; Rao, Yuhan; Wu, Xiaoxu; Zhao, Hainan; Chen, Jin

2015-01-01

Climate change is a significant and emerging threat to human health, especially where infectious diseases are involved. Because of the complex interactions between climate variables and infectious disease components (i.e., pathogen, host and transmission environment), systematically and quantitatively screening for infectious diseases that are sensitive to climate change is still a challenge. To address this challenge, we propose a new statistical indicator, Relative Sensitivity, to identify the difference between the sensitivity of the infectious disease to climate variables for two different climate statuses (i.e., historical climate and present climate) in non-exposure and exposure groups. The case study in Anhui Province, China has demonstrated the effectiveness of this Relative Sensitivity indicator. The application results indicate significant sensitivity of many epidemic infectious diseases to climate change in the form of changing climatic variables, such as temperature, precipitation and absolute humidity. As novel evidence, this research shows that absolute humidity has a critical influence on many observed infectious diseases in Anhui Province, including dysentery, hand, foot and mouth disease, hepatitis A, hemorrhagic fever, typhoid fever, malaria, meningitis, influenza and schistosomiasis. Moreover, some infectious diseases are more sensitive to climate change in rural areas than in urban areas. This insight provides guidance for future health inputs that consider spatial variability in response to climate change. PMID:25594780

The response of the southwest Western Australian wave climate to Indian Ocean climate variability

NASA Astrophysics Data System (ADS)

Wandres, Moritz; Pattiaratchi, Charitha; Hetzel, Yasha; Wijeratne, E. M. S.

2018-03-01

Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994-2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.

Association between climate variability and malaria epidemics in the East African highlands.

PubMed

Zhou, Guofa; Minakawa, Noboru; Githeko, Andrew K; Yan, Guiyun

2004-02-24

The causes of the recent reemergence of Plasmodium falciparum epidemic malaria in the East African highlands are controversial. Regional climate changes have been invoked as a major factor; however, assessing the impact of climate in malaria resurgence is difficult due to high spatial and temporal climate variability and the lack of long-term data series on malaria cases from different sites. Climate variability, defined as short-term fluctuations around the mean climate state, may be epidemiologically more relevant than mean temperature change, but its effects on malaria epidemics have not been rigorously examined. Here we used nonlinear mixed-regression model to investigate the association between autoregression (number of malaria outpatients during the previous time period), seasonality and climate variability, and the number of monthly malaria outpatients of the past 10-20 years in seven highland sites in East Africa. The model explained 65-81% of the variance in the number of monthly malaria outpatients. Nonlinear and synergistic effects of temperature and rainfall on the number of malaria outpatients were found in all seven sites. The net variance in the number of monthly malaria outpatients caused by autoregression and seasonality varied among sites and ranged from 18 to 63% (mean=38.6%), whereas 12-63% (mean=36.1%) of variance is attributed to climate variability. Our results suggest that there was a high spatial variation in the sensitivity of malaria outpatient number to climate fluctuations in the highlands, and that climate variability played an important role in initiating malaria epidemics in the East African highlands.

Climate variations of Central Asia on orbital to millennial timescales.

PubMed

Cheng, Hai; Spötl, Christoph; Breitenbach, Sebastian F M; Sinha, Ashish; Wassenburg, Jasper A; Jochum, Klaus Peter; Scholz, Denis; Li, Xianglei; Yi, Liang; Peng, Youbing; Lv, Yanbin; Zhang, Pingzhong; Votintseva, Antonina; Loginov, Vadim; Ning, Youfeng; Kathayat, Gayatri; Edwards, R Lawrence

2016-11-11

The extent to which climate variability in Central Asia is causally linked to large-scale changes in the Asian monsoon on varying timescales remains a longstanding question. Here we present precisely dated high-resolution speleothem oxygen-carbon isotope and trace element records of Central Asia's hydroclimate variability from Tonnel'naya cave, Uzbekistan, and Kesang cave, western China. On orbital timescales, the supra-regional climate variance, inferred from our oxygen isotope records, exhibits a precessional rhythm, punctuated by millennial-scale abrupt climate events, suggesting a close coupling with the Asian monsoon. However, the local hydroclimatic variability at both cave sites, inferred from carbon isotope and trace element records, shows climate variations that are distinctly different from their supra-regional modes. Particularly, hydroclimatic changes in both Tonnel'naya and Kesang areas during the Holocene lag behind the supra-regional climate variability by several thousand years. These observations may reconcile the apparent out-of-phase hydroclimatic variability, inferred from the Holocene lake proxy records, between Westerly Central Asia and Monsoon Asia.

Climate variations of Central Asia on orbital to millennial timescales

PubMed Central

Cheng, Hai; Spötl, Christoph; Breitenbach, Sebastian F. M.; Sinha, Ashish; Wassenburg, Jasper A.; Jochum, Klaus Peter; Scholz, Denis; Li, Xianglei; Yi, Liang; Peng, Youbing; Lv, Yanbin; Zhang, Pingzhong; Votintseva, Antonina; Loginov, Vadim; Ning, Youfeng; Kathayat, Gayatri; Edwards, R. Lawrence

2016-01-01

The extent to which climate variability in Central Asia is causally linked to large-scale changes in the Asian monsoon on varying timescales remains a longstanding question. Here we present precisely dated high-resolution speleothem oxygen-carbon isotope and trace element records of Central Asia’s hydroclimate variability from Tonnel’naya cave, Uzbekistan, and Kesang cave, western China. On orbital timescales, the supra-regional climate variance, inferred from our oxygen isotope records, exhibits a precessional rhythm, punctuated by millennial-scale abrupt climate events, suggesting a close coupling with the Asian monsoon. However, the local hydroclimatic variability at both cave sites, inferred from carbon isotope and trace element records, shows climate variations that are distinctly different from their supra-regional modes. Particularly, hydroclimatic changes in both Tonnel’naya and Kesang areas during the Holocene lag behind the supra-regional climate variability by several thousand years. These observations may reconcile the apparent out-of-phase hydroclimatic variability, inferred from the Holocene lake proxy records, between Westerly Central Asia and Monsoon Asia. PMID:27833133

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Licker, R.; Mastrorillo, M.; Bohra-Mishra, P.; Estes, L. D.; Cai, R.

2014-12-01

Climate variability has been associated with a range of societal and individual outcomes including migration, violent conflict, changes in labor productivity, and health impacts. Some of these may be direct responses to changes in mean temperature or precipitation or extreme events, such as displacement of human populations by tropical cyclones. Others may be mediated by a variety of biological, social, or ecological factors such as migration in response to long-term changes in crops yields. Research is beginning to elucidate and distinguish the many channels through which climate variability may influence human behavior (ranging from the individual to the collective, societal level) in order to better understand how to improve resilience in the face of current variability as well as future climate change. Using a variety of data sets from South Africa, we show how climate variability has influenced internal (within country) migration in recent history. We focus on South Africa as it is a country with high levels of internal migration and dramatic temperature and precipitation changes projected for the 21st century. High poverty rates and significant levels of rain-fed, smallholder agriculture leave large portions of South Africa's population base vulnerable to future climate change. In this study, we utilize two complementary statistical models - one micro-level model, driven by individual and household level survey data, and one macro-level model, driven by national census statistics. In both models, we consider the effect of climate on migration both directly (with gridded climate reanalysis data) and indirectly (with agricultural production statistics). With our historical analyses of climate variability, we gain insights into how the migration decisions of South Africans may be influenced by future climate change. We also offer perspective on the utility of micro and macro level approaches in the study of climate change and human migration.

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

PubMed

Steen, Valerie; Skagen, Susan K; Noon, Barry R

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971-2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981-2000 and projected future distributions to climate scenarios for 2040-2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Climate controls the distribution of a widespread invasive species: Implications for future range expansion

USGS Publications Warehouse

McDowell, W.G.; Benson, A.J.; Byers, J.E.

2014-01-01

1. Two dominant drivers of species distributions are climate and habitat, both of which are changing rapidly. Understanding the relative importance of variables that can control distributions is critical, especially for invasive species that may spread rapidly and have strong effects on ecosystems. 2. Here, we examine the relative importance of climate and habitat variables in controlling the distribution of the widespread invasive freshwater clam Corbicula fluminea, and we model its future distribution under a suite of climate scenarios using logistic regression and maximum entropy modelling (MaxEnt). 3. Logistic regression identified climate variables as more important than habitat variables in controlling Corbicula distribution. MaxEnt modelling predicted Corbicula's range expansion westward and northward to occupy half of the contiguous United States. By 2080, Corbicula's potential range will expand 25–32%, with more than half of the continental United States being climatically suitable. 4. Our combination of multiple approaches has revealed the importance of climate over habitat in controlling Corbicula's distribution and validates the climate-only MaxEnt model, which can readily examine the consequences of future climate projections. 5. Given the strong influence of climate variables on Corbicula's distribution, as well as Corbicula's ability to disperse quickly and over long distances, Corbicula is poised to expand into New England and the northern Midwest of the United States. Thus, the direct effects of climate change will probably be compounded by the addition of Corbicula and its own influences on ecosystem function.

The GCOS Reference Upper-Air Network (GRUAN)

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

Development, malaria and adaptation to climate change: a case study from India.

PubMed

Garg, Amit; Dhiman, R C; Bhattacharya, Sumana; Shukla, P R

2009-05-01

India has reasons to be concerned about climate change. Over 650 million people depend on climate-sensitive sectors, such as rain-fed agriculture and forestry, for livelihood and over 973 million people are exposed to vector borne malarial parasites. Projection of climatic factors indicates a wider exposure to malaria for the Indian population in the future. If precautionary measures are not taken and development processes are not managed properly some developmental activities, such as hydro-electric dams and irrigation canal systems, may also exacerbate breeding grounds for malaria. This article integrates climate change and developmental variables in articulating a framework for integrated impact assessment and adaptation responses, with malaria incidence in India as a case study. The climate change variables include temperature, rainfall, humidity, extreme events, and other secondary variables. Development variables are income levels, institutional mechanisms to implement preventive measures, infrastructure development that could promote malarial breeding grounds, and other policies. The case study indicates that sustainable development variables may sometimes reduce the adverse impacts on the system due to climate change alone, while it may sometimes also exacerbate these impacts if the development variables are not managed well and therefore they produce a negative impact on the system. The study concludes that well crafted and well managed developmental policies could result in enhanced resilience of communities and systems, and lower health impacts due to climate change.

Development, Malaria and Adaptation to Climate Change: A Case Study from India

NASA Astrophysics Data System (ADS)

Garg, Amit; Dhiman, R. C.; Bhattacharya, Sumana; Shukla, P. R.

2009-05-01

India has reasons to be concerned about climate change. Over 650 million people depend on climate-sensitive sectors, such as rain-fed agriculture and forestry, for livelihood and over 973 million people are exposed to vector borne malarial parasites. Projection of climatic factors indicates a wider exposure to malaria for the Indian population in the future. If precautionary measures are not taken and development processes are not managed properly some developmental activities, such as hydro-electric dams and irrigation canal systems, may also exacerbate breeding grounds for malaria. This article integrates climate change and developmental variables in articulating a framework for integrated impact assessment and adaptation responses, with malaria incidence in India as a case study. The climate change variables include temperature, rainfall, humidity, extreme events, and other secondary variables. Development variables are income levels, institutional mechanisms to implement preventive measures, infrastructure development that could promote malarial breeding grounds, and other policies. The case study indicates that sustainable development variables may sometimes reduce the adverse impacts on the system due to climate change alone, while it may sometimes also exacerbate these impacts if the development variables are not managed well and therefore they produce a negative impact on the system. The study concludes that well crafted and well managed developmental policies could result in enhanced resilience of communities and systems, and lower health impacts due to climate change.

Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record

NASA Astrophysics Data System (ADS)

Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn

2015-11-01

Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.

Climate Variability and Ecosystem Response

Treesearch

David Greenland; Lloyd W. Swift; [Editors

1990-01-01

Nine papers describe studies of climate variability and ecosystem response. The studies were conducted at LTER (Long-Term Ecological Research) sites representing forest, agricultural, and aquatic ecosystems and systems in which extreme climates limit vegetational cover. An overview paper prepared by the LTER Climate Committee stresses the importance of (1) clear...

Application of Climate Assessment Tool (CAT) to estimate climate variability impacts on nutrient loading from local watersheds

Treesearch

Ying Ouyang; Prem B. Parajuli; Gary Feng; Theodor D. Leininger; Yongshan Wan; Padmanava Dash

2018-01-01

A vast amount of future climate scenario datasets, created by climate models such as general circulation models (GCMs), have been used in conjunction with watershed models to project future climate variability impact on hydrological processes and water quality. However, these low spatial-temporal resolution datasets are often difficult to downscale spatially and...

Innovative Interactive Visitor Experiences Focused on Climate Change

NASA Astrophysics Data System (ADS)

Lettvin, E. E.

2011-12-01

Pacific Science Center has adopted a multi-pronged approach to introduce visitors to the concepts of climate change and linkages to human behavior in an informal science education setting. We leverage key fixed exhibit assets derived from collaborations with NOAA: Science on a Sphere and an exhibit kiosk showcasing local CO2 measurements that are adjacent on our exhibit floor. NOAA PMEL Scientists deployed a sensor at the top of the Space Needle that measures variability in atmospheric CO2 over Seattle; the kiosk showcases these near-real-time, daily, weekly and monthly measurements as well as similar observations from a NOAA buoy near Aberdeen, Washington. Displays of these data enable visitors to see first-hand varying CO2 levels in urban and remote marine environments as well as seasonal cycling. It also reveals quantifiable increases in CO2 levels over a relatively short time (~5 years). Trained interpreters help visitors understand linkages between personal behavior and corresponding CO2 footprints. Interpreters discuss connections between local and regional CO2 measurements displayed on the kiosk, and global Sphere datasets including NOAA Carbon Tracker, changing arctic sea ice coverage and sea level rise projections. Portable Discovery Carts, consisting of props and interactive, hands-on activities provide a platform for facilitated interpretation on a series of topics. We have developed two climate focused carts: 'Sinks and Sources' that examines materials and activities that produce and absorb carbon, and 'Ocean Acidification' that shows how absorption of atmospheric CO2 is changing ocean composition and its habitability for marine life. These carts can be deployed anywhere on the exhibit floor but are primarily used adjacent to the Sphere and the kiosk, making it possible to have a range of conversations about global and local CO2 levels, linkages to individual and collective behaviour and associated implications. Additional collaborations with members of the regional climate research community are showcased during regularly scheduled 'scientist spotlights' and 'research weekends'. Additional climate programs were developed targeting high school students. During the summer of 2010, 10 participants in a teen development program had summer internships with climate researchers working in horticulture, policy, arctic science and geology. The following fall, the teens hosted 4 'Family Climate Workshops' at community centers around Seattle. For these events, the teens developed hands-on activities and posters showcasing the climate research focus of their internships. These events were held in collaboration with the 'Cool School Challenge', a program that teaches how to conduct a greenhouse gas inventory and develop a corresponding action plan. The program culminated in the convening of the first 'High School Climate Change Symposium', held at Pacific Science Center. Nearly 200 teens attended on-site, and hundreds more live-streamed the event. The Symposium consisted of two panels: one focused on the scientific underpinnings of climate change and one focused on policies and implications. This innovative program provided a rare opportunity for teens to directly ask experts questions about climate change and its implications.

75 FR 22391 - Notice of Web Site Publication for the Climate Program Office

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-28

...-01] Notice of Web Site Publication for the Climate Program Office AGENCY: Climate Program Office (CPO... its Web site at http://www.climate.noaa.gov . FOR FURTHER INFORMATION CONTACT: Eric Locklear; Chief... information is available on the Climate Program Office Web site pertaining to the CPO's research strategies...

Past exposure to climate extremes can inform future projections and guide management: coral reefs as a model system

NASA Astrophysics Data System (ADS)

Donner, S. D.

2016-12-01

Coral reefs are thought to be more sensitive to climate change than any other marine ecosystem. Episodes of mass coral bleaching, due to anomalously warm water temperatures, have led to coral mortality, declines in coral cover and shifts in the population of other reef-dwelling organisms. The onset of mass bleaching is typically predicted using accumulated heat stress, specifically when the SST exceeds a local climatological maximum by 1-2 °C for a month or more. However, recent evidence suggests that the threshold at which bleaching occurs depends on the past thermal experience of the coral reef and the composition of the coral community. This presentation describes the results of a long-term field and modelling research program evaluating the influence of climate experience on the susceptibility of coral reef ecosystems to future climate extremes. Modeling work identified Kiribati's equatorial Gilbert Islands, where the El Niño / Southern Oscillation drives year-to-year shifts in current strength, current direction and consequently ocean temperatures, as an ideal natural laboratory for studying ocean climate extremes. The field program then tracked changes in the coral communities over multiple heat stress events (e.g. 2004-5, 2009-10 El Niño) at a matrix of sites exposed to different levels of historical climate variability and human disturbance. Among the results is evidence that coral bleaching patterns are best predicted by the coefficient of variation of past SST, light exposure, and the presence of particular resilient coral taxa, rather than the standard heat stress metrics. The lessons of this research can be applicable other systems where past experience influences the response to climate extremes

Assessing Regional Scale Variability in Extreme Value Statistics Under Altered Climate Scenarios

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

Brunsell, Nathaniel; Mechem, David; Ma, Chunsheng

Recent studies have suggested that low-frequency modes of climate variability can significantly influence regional climate. The climatology associated with extreme events has been shown to be particularly sensitive. This has profound implications for droughts, heat waves, and food production. We propose to examine regional climate simulations conducted over the continental United States by applying a recently developed technique which combines wavelet multi–resolution analysis with information theory metrics. This research is motivated by two fundamental questions concerning the spatial and temporal structure of extreme events. These questions are 1) what temporal scales of the extreme value distributions are most sensitive tomore » alteration by low-frequency climate forcings and 2) what is the nature of the spatial structure of variation in these timescales? The primary objective is to assess to what extent information theory metrics can be useful in characterizing the nature of extreme weather phenomena. Specifically, we hypothesize that (1) changes in the nature of extreme events will impact the temporal probability density functions and that information theory metrics will be sensitive these changes and (2) via a wavelet multi–resolution analysis, we will be able to characterize the relative contribution of different timescales on the stochastic nature of extreme events. In order to address these hypotheses, we propose a unique combination of an established regional climate modeling approach and advanced statistical techniques to assess the effects of low-frequency modes on climate extremes over North America. The behavior of climate extremes in RCM simulations for the 20th century will be compared with statistics calculated from the United States Historical Climatology Network (USHCN) and simulations from the North American Regional Climate Change Assessment Program (NARCCAP). This effort will serve to establish the baseline behavior of climate extremes, the validity of an innovative multi–resolution information theory approach, and the ability of the RCM modeling framework to represent the low-frequency modulation of extreme climate events. Once the skill of the modeling and analysis methodology has been established, we will apply the same approach for the AR5 (IPCC Fifth Assessment Report) climate change scenarios in order to assess how climate extremes and the the influence of lowfrequency variability on climate extremes might vary under changing climate. The research specifically addresses the DOE focus area 2. Simulation of climate extremes under a changing climate. Specific results will include (1) a better understanding of the spatial and temporal structure of extreme events, (2) a thorough quantification of how extreme values are impacted by low-frequency climate teleconnections, (3) increased knowledge of current regional climate models ability to ascertain these influences, and (4) a detailed examination of the how the distribution of extreme events are likely to change under different climate change scenarios. In addition, this research will assess the ability of the innovative wavelet information theory approach to characterize extreme events. Any and all of these results will greatly enhance society’s ability to understand and mitigate the regional ramifications of future global climate change.« less

AMOC decadal variability in Earth system models: Mechanisms and climate impacts

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

Fedorov, Alexey

This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability andmore » predictability, directly relevant to the questions of climate predictability, were at the center of the research work.« less

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

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

Mani, Amir; Tsai, Frank T. -C.; Kao, Shih-Chieh

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimizedmore » conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.« less

Conjunctive management of surface and groundwater resources under projected future climate change scenarios

DOE PAGES

Mani, Amir; Tsai, Frank T. -C.; Kao, Shih-Chieh; ...

2016-06-16

Our study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimizedmore » conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Ultimately, results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraint.« less

Development of a North American paleoclimate pollen-based reconstruction database application

NASA Astrophysics Data System (ADS)

Ladd, Matthew; Mosher, Steven; Viau, Andre

2013-04-01

Recent efforts in synthesizing paleoclimate records across the globe has warranted an effort to standardize the different paleoclimate archives currently available in order to facilitate data-model comparisons and hence improve our estimates of future climate change. It is often the case that the methodology and programs make it challenging for other researchers to reproduce the results for a reconstruction, therefore there is a need for to standardize paleoclimate reconstruction databases in an application specific to proxy data. Here we present a methodology using the open source R language using North American pollen databases (e.g. NAPD, NEOTOMA) where this application can easily be used to perform new reconstructions and quickly analyze and output/plot the data. The application was developed to easily test methodological and spatial/temporal issues that might affect the reconstruction results. The application allows users to spend more time analyzing and interpreting results instead of on data management and processing. Some of the unique features of this R program are the two modules each with a menu making the user feel at ease with the program, the ability to use different pollen sums, select one of 70 climate variables available, substitute an appropriate modern climate dataset, a user-friendly regional target domain, temporal resolution criteria, linear interpolation and many other features for a thorough exploratory data analysis. The application program will be available for North American pollen-based reconstructions and eventually be made available as a package through the CRAN repository by late 2013.

GLOBAL CHANGE RESEARCH NEWS #16: POTENTIAL HEALTH IMPACTS OF CLIMATE VARIABILITY AND CHANGE FOR THE UNITED STATES, EXECUTIVE SUMMARY OF THE REPORT OF THE HEALTH SECTOR OF THE U.S. NATIONAL ASSESSMENT

EPA Science Inventory

The health sector assessment was sponsored by and conducted in partnership with EPA's Global Change Research Program. The report was produced by a Health Sector Work Group, co-chaired by Dr. Jonathan Patz (Johns Hopkins University) and Dr. Michael McGeehin (CDC), and this report ...

Couples' cultural values, shared parenting, and family emotional climate within Mexican American families.

PubMed

Sotomayor-Peterson, Marcela; Figueredo, Aurelio J; Christensen, Donna H; Taylor, Angela R

2012-06-01

This study tested a model of shared parenting as its centerpiece that incorporates cultural values as predictors and family emotional climate as the outcome variable of interest. We aimed to assess the predictive power of the Mexican cultural values of familismo and simpatia over couples' shared parenting practices. We anticipated that higher levels of shared parenting would predict family emotional climate. The participants were 61 Mexican American, low income couples, with at least one child between 3 and 4 years of age, recruited from a home-based Head Start program. The predictive model demonstrated excellent goodness of fit, supporting the hypothesis that a positive emotional climate within the family is fostered when Mexican American couples practice a sufficient level of shared parenting. Empirical evidence was previously scarce on this proposition. The findings also provide evidence for the role of cultural values, highlighting the importance of family solidarity and avoidance of confrontation as a pathway to shared parenting within Mexican American couples. © FPI, Inc.

Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

NASA Astrophysics Data System (ADS)

Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

2012-06-01

This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA&D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA&D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA&D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA&D dataset in the context of regional climate research in the Euro-Mediterranean region.

World Ocean Database and the Global Temperature and Salinity Profile Program Database: Synthesis of historical and near real-time ocean profile data

NASA Astrophysics Data System (ADS)

Boyer, T.; Sun, L.; Locarnini, R. A.; Mishonov, A. V.; Hall, N.; Ouellet, M.

2016-02-01

The World Ocean Database (WOD) contains systematically quality controlled historical and recent ocean profile data (temperature, salinity, oxygen, nutrients, carbon cycle variables, biological variables) ranging from Captain Cooks second voyage (1773) to this year's Argo floats. The US National Centers for Environmental Information (NCEI) also hosts the Global Temperature and Salinity Profile Program (GTSPP) Continuously Managed Database (CMD) which provides quality controlled near-real time ocean profile data and higher level quality controlled temperature and salinity profiles from 1990 to present. Both databases are used extensively for ocean and climate studies. Synchronization of these two databases will allow easier access and use of comprehensive regional and global ocean profile data sets for ocean and climate studies. Synchronizing consists of two distinct phases: 1) a retrospective comparison of data in WOD and GTSPP to ensure that the most comprehensive and highest quality data set is available to researchers without the need to individually combine and contrast the two datasets and 2) web services to allow the constantly accruing near-real time data in the GTSPP CMD and the continuous addition and quality control of historical data in WOD to be made available to researchers together, seamlessly.

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.

Change in the magnitude and mechanisms of global temperature variability with warming

PubMed Central

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. PMID:29391875

Centennial-scale Holocene climate variations amplified by Antarctic Ice Sheet discharge

NASA Astrophysics Data System (ADS)

Bakker, Pepijn; Clark, Peter U.; Golledge, Nicholas R.; Schmittner, Andreas; Weber, Michael E.

2017-01-01

Proxy-based indicators of past climate change show that current global climate models systematically underestimate Holocene-epoch climate variability on centennial to multi-millennial timescales, with the mismatch increasing for longer periods. Proposed explanations for the discrepancy include ocean-atmosphere coupling that is too weak in models, insufficient energy cascades from smaller to larger spatial and temporal scales, or that global climate models do not consider slow climate feedbacks related to the carbon cycle or interactions between ice sheets and climate. Such interactions, however, are known to have strongly affected centennial- to orbital-scale climate variability during past glaciations, and are likely to be important in future climate change. Here we show that fluctuations in Antarctic Ice Sheet discharge caused by relatively small changes in subsurface ocean temperature can amplify multi-centennial climate variability regionally and globally, suggesting that a dynamic Antarctic Ice Sheet may have driven climate fluctuations during the Holocene. We analysed high-temporal-resolution records of iceberg-rafted debris derived from the Antarctic Ice Sheet, and performed both high-spatial-resolution ice-sheet modelling of the Antarctic Ice Sheet and multi-millennial global climate model simulations. Ice-sheet responses to decadal-scale ocean forcing appear to be less important, possibly indicating that the future response of the Antarctic Ice Sheet will be governed more by long-term anthropogenic warming combined with multi-centennial natural variability than by annual or decadal climate oscillations.

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.

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

PubMed

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

2014-08-01

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

Climatic variability effects on summer cropping systems of the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Capa-Morocho, M.; Rodríguez-Fonseca, B.; Ruiz-Ramos, M.

2012-04-01

Climate variability and changes in the frequency of extremes events have a direct impact on crop yield and damages. Climate anomalies projections at monthly and yearly timescale allows us for adapting a cropping system (crops, varieties and management) to take advantage of favorable conditions or reduce the effect of adverse conditions. The objective of this work is to develop indices to evaluate the effect of climatic variability in summer cropping systems of Iberian Peninsula, in an attempt of relating yield variability to climate variability, extending the work of Rodríguez-Puebla (2004). This paper analyses the evolution of the yield anomalies of irrigated maize in several representative agricultural locations in Spain with contrasting temperature and precipitation regimes and compare it to the evolution of different patterns of climate variability, extending the methodology of Porter and Semenov (2005). To simulate maize yields observed daily data of radiation, maximum and minimum temperature and precipitation were used. These data were obtained from the State Meteorological Agency of Spain (AEMET). Time series of simulated maize yields were computed with CERES-maize model for periods ranging from 22 to 49 years, depending on the observed climate data available for each location. The computed standardized anomalies yields were projected on different oceanic and atmospheric anomalous fields and the resulting patterns were compared with a set of documented patterns from the National Oceanic and Atmospheric Administration (NOAA). The results can be useful also for climate change impact assessment, providing a scientific basis for selection of climate change scenarios where combined natural and forced variability represent a hazard for agricultural production. Interpretation of impact projections would also be enhanced.

The relative impacts of climate and land-use change on conterminous United States bird species from 2001 to 2075

USGS Publications Warehouse

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be "suitable" for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

PubMed Central

Sohl, Terry L.

2014-01-01

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges. PMID:25372571

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.

Ad hoc committee on global climate issues: Annual report

USGS Publications Warehouse

Gerhard, L.C.; Hanson, B.M.B.

2000-01-01

The AAPG Ad Hoc Committee on Global Climate Issues has studied the supposition of human-induced climate change since the committee's inception in January 1998. This paper details the progress and findings of the committee through June 1999. At that time there had been essentially no geologic input into the global climate change debate. The following statements reflect the current state of climate knowledge from the geologic perspective as interpreted by the majority of the committee membership. The committee recognizes that new data could change its conclusions. The earth's climate is constantly changing owing to natural variability in earth processes. Natural climate variability over recent geological time is greater than reasonable estimates of potential human-induced greenhouse gas changes. Because no tool is available to test the supposition of human-induced climate change and the range of natural variability is so great, there is no discernible human influence on global climate at this time.

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.

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.

How are interannual modes of variability IOD, ENSO, SAM, AMO excited by natural and anthropogenic forcing?

NASA Astrophysics Data System (ADS)

Maher, Nicola; Marotzke, Jochem

2017-04-01

Natural climate variability is found in observations, paleo-proxies, and climate models. Such climate variability can be intrinsic internal variability or externally forced, for example by changes in greenhouse gases or large volcanic eruptions. There are still questions concerning how external forcing, both natural (e.g., volcanic eruptions and solar variability) and anthropogenic (e.g., greenhouse gases and ozone) may excite both interannual modes of variability in the climate system. This project aims to address some of these problems, utilising the large ensemble of the MPI-ESM-LR climate model. In this study we investigate the statistics of four modes of interannual variability, namely the North Atlantic Oscillation (NAO), the Indian Ocean Dipole (IOD), the Southern Annular Mode (SAM) and the El Niño Southern Oscillation (ENSO). Using the 100-member ensemble of MPI-ESM-LR the statistical properties of these modes (amplitude and standard deviation) can be assessed over time. Here we compare the properties in the pre-industrial control run, historical run and future scenarios (RCP4.5, RCP2.6) and present preliminary results.

Climate models predict increasing temperature variability in poor countries.

PubMed

Bathiany, Sebastian; Dakos, Vasilis; Scheffer, Marten; Lenton, Timothy M

2018-05-01

Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C -1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate.

Climate models predict increasing temperature variability in poor countries

PubMed Central

Dakos, Vasilis; Scheffer, Marten

2018-01-01

Extreme events such as heat waves are among the most challenging aspects of climate change for societies. We show that climate models consistently project increases in temperature variability in tropical countries over the coming decades, with the Amazon as a particular hotspot of concern. During the season with maximum insolation, temperature variability increases by ~15% per degree of global warming in Amazonia and Southern Africa and by up to 10%°C−1 in the Sahel, India, and Southeast Asia. Mechanisms include drying soils and shifts in atmospheric structure. Outside the tropics, temperature variability is projected to decrease on average because of a reduced meridional temperature gradient and sea-ice loss. The countries that have contributed least to climate change, and are most vulnerable to extreme events, are projected to experience the strongest increase in variability. These changes would therefore amplify the inequality associated with the impacts of a changing climate. PMID:29732409

A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

DOE PAGES

Zhang, Yu; Pan, Ming; Sheffield, Justin; ...

2018-01-12

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation ( P), evapotranspiration (ET), runoff ( R), and the totalmore » water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET- R-TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.« less

A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010

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

Zhang, Yu; Pan, Ming; Sheffield, Justin

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation ( P), evapotranspiration (ET), runoff ( R), and the totalmore » water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P-ET- R-TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984–2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.« less

A Climate Data Record (CDR) for the global terrestrial water budget: 1984-2010

NASA Astrophysics Data System (ADS)

Zhang, Yu; Pan, Ming; Sheffield, Justin; Siemann, Amanda L.; Fisher, Colby K.; Liang, Miaoling; Beck, Hylke E.; Wanders, Niko; MacCracken, Rosalyn F.; Houser, Paul R.; Zhou, Tian; Lettenmaier, Dennis P.; Pinker, Rachel T.; Bytheway, Janice; Kummerow, Christian D.; Wood, Eric F.

2018-01-01

Closing the terrestrial water budget is necessary to provide consistent estimates of budget components for understanding water resources and changes over time. Given the lack of in situ observations of budget components at anything but local scale, merging information from multiple data sources (e.g., in situ observation, satellite remote sensing, land surface model, and reanalysis) through data assimilation techniques that optimize the estimation of fluxes is a promising approach. Conditioned on the current limited data availability, a systematic method is developed to optimally combine multiple available data sources for precipitation (P), evapotranspiration (ET), runoff (R), and the total water storage change (TWSC) at 0.5° spatial resolution globally and to obtain water budget closure (i.e., to enforce P - ET - R - TWSC = 0) through a constrained Kalman filter (CKF) data assimilation technique under the assumption that the deviation from the ensemble mean of all data sources for the same budget variable is used as a proxy of the uncertainty in individual water budget variables. The resulting long-term (1984-2010), monthly 0.5° resolution global terrestrial water cycle Climate Data Record (CDR) data set is developed under the auspices of the National Aeronautics and Space Administration (NASA) Earth System Data Records (ESDRs) program. This data set serves to bridge the gap between sparsely gauged regions and the regions with sufficient in situ observations in investigating the temporal and spatial variability in the terrestrial hydrology at multiple scales. The CDR created in this study is validated against in situ measurements like river discharge from the Global Runoff Data Centre (GRDC) and the United States Geological Survey (USGS), and ET from FLUXNET. The data set is shown to be reliable and can serve the scientific community in understanding historical climate variability in water cycle fluxes and stores, benchmarking the current climate, and validating models.

Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

NASA Astrophysics Data System (ADS)

Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

2018-04-01

This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

Halloran, P. R.; Reynolds, D.; Scourse, J. D.; Hall, I. R.

2016-02-01

Paul R. Halloran, David J. Reynolds, Ian R. Hall and James D. Scourse Multidecadal variability in Atlantic sea surface temperatures (SSTs) plays a first order role in determining regional atmospheric circulation and moisture transport, with major climatic consequences. These regional climate impacts range from drought in the Sahel and South America, though increased hurricane activity and temperature extremes, to modified monsoonal rainfall. Multidecadal Atlantic SST variability could arise through internal variability in the Atlantic Meridional Overturning Circulation (AMOC) (e.g., Knight et al., 2006), or through externally forced change (e.g. Booth et al., 2012). It is critical that we know whether internal or external forcing dominates if we are to provide useful near-term climate projections in the Atlantic region. A persuasive argument that internal variability plays an important role in Atlantic Multidecadal Variability is that periodic SST variability has been observed throughout much of the last millennium (Mann et al., 2009), and the hypothesized external forcing of historical Atlantic Multidecadal Variability (Booth et al., 2012) is largely anthropogenic in origin. Here we combine the first annually-resolved millennial marine reconstruction with multi-model analysis, to show that the Atlantic SST variability of the last millennium can be explained by a combination of direct volcanic forcing, and indirect, forced, AMOC variability. Our results indicate that whilst climate models capture the timing of both the directly forced SST and forced AMOC-mediated SST variability, the models fail to capture the magnitude of the forced AMOC change. Does this mean that models underestimate the 21st century reduction in AMOC strength? J. Knight, C. Folland and A. Scaife., Climate impacts of the Atlantic Multidecadal Oscillation, GRL, 2006 B.B.B Booth, N. Dunstone, P.R. Halloran et al., Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 2012 M.E. Mann, Z. Zhang, S. Rutherford et al., Global Signatures and Dynamical Origins of the Little Ice Age and Medieval Climate Anomaly, Science, 2009

Impacts of climate change on marine top predators: Advances and future challenges

NASA Astrophysics Data System (ADS)

Hobday, Alistair J.; Arrizabalaga, Haritz; Evans, Karen; Nicol, Simon; Young, Jock W.; Weng, Kevin C.

2015-03-01

Oceanic top predators are the subject of studies by researchers under the international Climate Impacts on Oceanic Top Predators (CLIOTOP) program. A wide range of data sets have shown that environmental conditions, such as temperature and marine productivity, affect the distribution and biological processes of these species, and thus the activities of the humans that depend on them. In this special issue, 25 papers arising from the 2nd CLIOTOP symposium, held in Noumea, New Caledonia in February 2013 report the importance of realistic physical descriptions of oceanic processes for climate change projections, demonstrate a wide range of predator responses to historical climate variability, describe new analytical approaches for understanding the physiology, behaviour and trophodynamics, and project future distributions for a range of species. Several contributions discuss the implications for conservation and fisheries and show that resolving ecosystem management challenges and conflicts in the face of climate change is possible, but will require attention by decision-makers to issues that are broader than their traditional mandate. In the coming years, an increased focus on the development of management options to reduce the impacts of climate change on top predators and their dependent industries is needed.

Terrestrial essential climate variables (ECVs) at a glance

USGS Publications Warehouse

Stitt, Susan; Dwyer, John; Dye, Dennis; Josberger, Edward

2011-01-01

The Global Terrestrial Observing System, Global Climate Observing System, World Meteorological Organization, and Committee on Earth Observation Satellites all support consistent global land observations and measurements. To accomplish this goal, the Global Terrestrial Observing System defined 'essential climate variables' as measurements of atmosphere, oceans, and land that are technically and economically feasible for systematic observation and that are needed to meet the United Nations Framework Convention on Climate Change and requirements of the Intergovernmental Panel on Climate Change. The following are the climate variables defined by the Global Terrestrial Observing System that relate to terrestrial measurements. Several of them are currently measured most appropriately by in-place observations, whereas others are suitable for measurement by remote sensing technologies. The U.S. Geological Survey is the steward of the Landsat archive, satellite imagery collected from 1972 to the present, that provides a potential basis for deriving long-term, global-scale, accurate, timely and consistent measurements of many of these essential climate variables.

Relationship of suicide rates with climate and economic variables in Europe during 2000-2012.

PubMed

Fountoulakis, Konstantinos N; Chatzikosta, Isaia; Pastiadis, Konstantinos; Zanis, Prodromos; Kawohl, Wolfram; Kerkhof, Ad J F M; Navickas, Alvydas; Höschl, Cyril; Lecic-Tosevski, Dusica; Sorel, Eliot; Rancans, Elmars; Palova, Eva; Juckel, Georg; Isacsson, Goran; Jagodic, Helena Korosec; Botezat-Antonescu, Ileana; Rybakowski, Janusz; Azorin, Jean Michel; Cookson, John; Waddington, John; Pregelj, Peter; Demyttenaere, Koen; Hranov, Luchezar G; Stevovic, Lidija Injac; Pezawas, Lucas; Adida, Marc; Figuera, Maria Luisa; Jakovljević, Miro; Vichi, Monica; Perugi, Giulio; Andreassen, Ole A; Vukovic, Olivera; Mavrogiorgou, Paraskevi; Varnik, Peeter; Dome, Peter; Winkler, Petr; Salokangas, Raimo K R; From, Tiina; Danileviciute, Vita; Gonda, Xenia; Rihmer, Zoltan; Forsman, Jonas; Grady, Anne; Hyphantis, Thomas; Dieset, Ingrid; Soendergaard, Susan; Pompili, Maurizio; Bech, Per

2016-01-01

It is well known that suicidal rates vary considerably among European countries and the reasons for this are unknown, although several theories have been proposed. The effect of economic variables has been extensively studied but not that of climate. Data from 29 European countries covering the years 2000-2012 and concerning male and female standardized suicidal rates (according to WHO), economic variables (according World Bank) and climate variables were gathered. The statistical analysis included cluster and principal component analysis and categorical regression. The derived models explained 62.4 % of the variability of male suicidal rates. Economic variables alone explained 26.9 % and climate variables 37.6 %. For females, the respective figures were 41.7, 11.5 and 28.1 %. Male suicides correlated with high unemployment rate in the frame of high growth rate and high inflation and low GDP per capita, while female suicides correlated negatively with inflation. Both male and female suicides correlated with low temperature. The current study reports that the climatic effect (cold climate) is stronger than the economic one, but both are present. It seems that in Europe suicidality follows the climate/temperature cline which interestingly is not from south to north but from south to north-east. This raises concerns that climate change could lead to an increase in suicide rates. The current study is essentially the first successful attempt to explain the differences across countries in Europe; however, it is an observational analysis based on aggregate data and thus there is a lack of control for confounders.

Climate and climate variability of the wind power resources in the Great Lakes region of the United States

Treesearch

X. Li; S. Zhong; X. Bian; W.E. Heilman

2010-01-01

The climate and climate variability of low-level winds over the Great Lakes region of the United States is examined using 30 year (1979-2008) wind records from the recently released North American Regional Reanalysis (NARR), a three-dimensional, high-spatial and temporal resolution, and dynamically consistent climate data set. The analyses focus on spatial distribution...

The potential impacts of climate variability and change on air pollution-related health effects in the United States.

PubMed Central

Bernard, S M; Samet, J M; Grambsch, A; Ebi, K L; Romieu, I

2001-01-01

Climate change may affect exposures to air pollutants by affecting weather, anthropogenic emissions, and biogenic emissions and by changing the distribution and types of airborne allergens. Local temperature, precipitation, clouds, atmospheric water vapor, wind speed, and wind direction influence atmospheric chemical processes, and interactions occur between local and global-scale environments. If the climate becomes warmer and more variable, air quality is likely to be affected. However, the specific types of change (i.e., local, regional, or global), the direction of change in a particular location (i.e., positive or negative), and the magnitude of change in air quality that may be attributable to climate change are a matter of speculation, based on extrapolating present understanding to future scenarios. There is already extensive evidence on the health effects of air pollution. Ground-level ozone can exacerbate chronic respiratory diseases and cause short-term reductions in lung function. Exposure to particulate matter can aggravate chronic respiratory and cardiovascular diseases, alter host defenses, damage lung tissue, lead to premature death, and possibly contribute to cancer. Health effects of exposures to carbon monoxide, sulfur dioxide, and nitrogen dioxide can include reduced work capacity, aggravation of existing cardiovascular diseases, effects on pulmonary function, respiratory illnesses, lung irritation, and alterations in the lung's defense systems. Adaptations to climate change should include ensuring responsiveness of air quality protection programs to changing pollution levels. Research needs include basic atmospheric science work on the association between weather and air pollutants; improving air pollution models and their linkage with climate change scenarios; and closing gaps in the understanding of exposure patterns and health effects. PMID:11359687

The potential impacts of climate variability and change on air pollution-related health effects in the United States.

PubMed

Bernard, S M; Samet, J M; Grambsch, A; Ebi, K L; Romieu, I

2001-05-01

Climate change may affect exposures to air pollutants by affecting weather, anthropogenic emissions, and biogenic emissions and by changing the distribution and types of airborne allergens. Local temperature, precipitation, clouds, atmospheric water vapor, wind speed, and wind direction influence atmospheric chemical processes, and interactions occur between local and global-scale environments. If the climate becomes warmer and more variable, air quality is likely to be affected. However, the specific types of change (i.e., local, regional, or global), the direction of change in a particular location (i.e., positive or negative), and the magnitude of change in air quality that may be attributable to climate change are a matter of speculation, based on extrapolating present understanding to future scenarios. There is already extensive evidence on the health effects of air pollution. Ground-level ozone can exacerbate chronic respiratory diseases and cause short-term reductions in lung function. Exposure to particulate matter can aggravate chronic respiratory and cardiovascular diseases, alter host defenses, damage lung tissue, lead to premature death, and possibly contribute to cancer. Health effects of exposures to carbon monoxide, sulfur dioxide, and nitrogen dioxide can include reduced work capacity, aggravation of existing cardiovascular diseases, effects on pulmonary function, respiratory illnesses, lung irritation, and alterations in the lung's defense systems. Adaptations to climate change should include ensuring responsiveness of air quality protection programs to changing pollution levels. Research needs include basic atmospheric science work on the association between weather and air pollutants; improving air pollution models and their linkage with climate change scenarios; and closing gaps in the understanding of exposure patterns and health effects.

Skilful multi-year predictions of tropical trans-basin climate variability

PubMed Central

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-01-01

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation. PMID:25897996

Skilful multi-year predictions of tropical trans-basin climate variability.

PubMed

Chikamoto, Yoshimitsu; Timmermann, Axel; Luo, Jing-Jia; Mochizuki, Takashi; Kimoto, Masahide; Watanabe, Masahiro; Ishii, Masayoshi; Xie, Shang-Ping; Jin, Fei-Fei

2015-04-21

Tropical Pacific sea surface temperature anomalies influence the atmospheric circulation, impacting climate far beyond the tropics. The predictability of the corresponding atmospheric signals is typically limited to less than 1 year lead time. Here we present observational and modelling evidence for multi-year predictability of coherent trans-basin climate variations that are characterized by a zonal seesaw in tropical sea surface temperature and sea-level pressure between the Pacific and the other two ocean basins. State-of-the-art climate model forecasts initialized from a realistic ocean state show that the low-frequency trans-basin climate variability, which explains part of the El Niño Southern Oscillation flavours, can be predicted up to 3 years ahead, thus exceeding the predictive skill of current tropical climate forecasts for natural variability. This low-frequency variability emerges from the synchronization of ocean anomalies in all basins via global reorganizations of the atmospheric Walker Circulation.

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.

Qualitatively Assessing Randomness in SVD Results

NASA Astrophysics Data System (ADS)

Lamb, K. W.; Miller, W. P.; Kalra, A.; Anderson, S.; Rodriguez, A.

2012-12-01

Singular Value Decomposition (SVD) is a powerful tool for identifying regions of significant co-variability between two spatially distributed datasets. SVD has been widely used in atmospheric research to define relationships between sea surface temperatures, geopotential height, wind, precipitation and streamflow data for myriad regions across the globe. A typical application for SVD is to identify leading climate drivers (as observed in the wind or pressure data) for a particular hydrologic response variable such as precipitation, streamflow, or soil moisture. One can also investigate the lagged relationship between a climate variable and the hydrologic response variable using SVD. When performing these studies it is important to limit the spatial bounds of the climate variable to reduce the chance of random co-variance relationships being identified. On the other hand, a climate region that is too small may ignore climate signals which have more than a statistical relationship to a hydrologic response variable. The proposed research seeks to identify a qualitative method of identifying random co-variability relationships between two data sets. The research identifies the heterogeneous correlation maps from several past results and compares these results with correlation maps produced using purely random and quasi-random climate data. The comparison identifies a methodology to determine if a particular region on a correlation map may be explained by a physical mechanism or is simply statistical chance.

Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model

NASA Astrophysics Data System (ADS)

Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho

2016-06-01

Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change?

EPA Science Inventory

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site...

Compound extremes of summer temperature and precipitation leading to intensified departures from natural variability.

NASA Astrophysics Data System (ADS)

Mahony, C. R.; Cannon, A. J.

2017-12-01

Climate change can drive local climates outside the range of their historical year-to-year variability, straining the adaptive capacity of ecological and human communities. We demonstrate that interactions between climate variables can produce larger and earlier departures from natural variability than is detectable in individual variables. For example, summer temperature (Tx) and precipitation (Pr) are negatively correlated in most terrestrial regions, such that interannual variability lies along an axis from warm-and-dry to cool-and-wet conditions. A climate change trend perpendicular to this axis, towards warmer-wetter conditions, can depart more quickly from the range of natural variability than a warmer-drier trend. This multivariate "departure intensification" effect is evident in all six CMIP5 models that we examined: 23% (9-34%) of the land area of each model exhibits a pronounced increase in 2σ extremesin the Tx-Pr regime relative to Tx or Pr alone. Observational data suggest that Tx-Pr correlations are sufficient to produce departure intensification in distinct regions on all continents. Departures from the historical Tx-Pr regime may produce ecological disruptions, such as in plant-pathogen interactions and human diseases, that could offset the drought mitigation benefits of increased precipitation. Our study alerts researchers and adaptation practitioners to the presence of multivariate climate change signals and compound extremes that are not detectable in individual climate variables.

Evaluation of Boreal Summer Monsoon Intraseasonal Variability in the GASS-YOTC Multi-Model Physical Processes Experiment

NASA Astrophysics Data System (ADS)

Mani, N. J.; Waliser, D. E.; Jiang, X.

2014-12-01

While the boreal summer monsoon intraseasonal variability (BSISV) exerts profound influence on the south Asian monsoon, the capability of present day dynamical models in simulating and predicting the BSISV is still limited. The global model evaluation project on vertical structure and diabatic processes of the Madden Julian Oscillations (MJO) is a joint venture, coordinated by the Working Group on Numerical Experimentation (WGNE) MJO Task Force and GEWEX Atmospheric System Study (GASS) program, for assessing the model deficiencies in simulating the ISV and for improving our understanding of the underlying processes. In this study the simulation of the northward propagating BSISV is investigated in 26 climate models with special focus on the vertical diabatic heating structure and clouds. Following parallel lines of inquiry as the MJO Task Force has done with the eastward propagating MJO, we utilize previously proposed and newly developed model performance metrics and process diagnostics and apply them to the global climate model simulations of BSISV.

Evaluation of Ten Methods for Initializing a Land Surface Model

NASA Technical Reports Server (NTRS)

Rodell, M.; Houser, P. R.; Berg, A. A.; Famiglietti, J. S.

2005-01-01

Land surface models (LSMs) are computer programs, similar to weather and climate prediction models, which simulate the stocks and fluxes of water (including soil moisture, snow, evaporation, and runoff) and energy (including the temperature of and sensible heat released from the soil) after they arrive on the land surface as precipitation and sunlight. It is not currently possible to measure all of the variables of interest everywhere on Earth with sufficient accuracy and space-time resolution. Hence LSMs have been developed to integrate the available observations with our understanding of the physical processes involved, using powerful computers, in order to map these stocks and fluxes as they change in time. The maps are used to improve weather forecasts, support water resources and agricultural applications, and study the Earth"s water cycle and climate variability. NASA"s Global Land Data Assimilation System (GLDAS) project facilitates testing of several different LSMs with a variety of input datasets (e.g., precipitation, plant type).

Understanding and Improving Ocean Mixing Parameterizations for modeling Climate Change

NASA Astrophysics Data System (ADS)

Howard, A. M.; Fells, J.; Clarke, J.; Cheng, Y.; Canuto, V.; Dubovikov, M. S.

2017-12-01

Climate is vital. Earth is only habitable due to the atmosphere&oceans' distribution of energy. Our Greenhouse Gas emissions shift overall the balance between absorbed and emitted radiation causing Global Warming. How much of these emissions are stored in the ocean vs. entering the atmosphere to cause warming and how the extra heat is distributed depends on atmosphere&ocean dynamics, which we must understand to know risks of both progressive Climate Change and Climate Variability which affect us all in many ways including extreme weather, floods, droughts, sea-level rise and ecosystem disruption. Citizens must be informed to make decisions such as "business as usual" vs. mitigating emissions to avert catastrophe. Simulations of Climate Change provide needed knowledge but in turn need reliable parameterizations of key physical processes, including ocean mixing, which greatly impacts transport&storage of heat and dissolved CO2. The turbulence group at NASA-GISS seeks to use physical theory to improve parameterizations of ocean mixing, including smallscale convective, shear driven, double diffusive, internal wave and tidal driven vertical mixing, as well as mixing by submesoscale eddies, and lateral mixing along isopycnals by mesoscale eddies. Medgar Evers undergraduates aid NASA research while learning climate science and developing computer&math skills. We write our own programs in MATLAB and FORTRAN to visualize and process output of ocean simulations including producing statistics to help judge impacts of different parameterizations on fidelity in reproducing realistic temperatures&salinities, diffusivities and turbulent power. The results can help upgrade the parameterizations. Students are introduced to complex system modeling and gain deeper appreciation of climate science and programming skills, while furthering climate science. We are incorporating climate projects into the Medgar Evers college curriculum. The PI is both a member of the turbulence group at NASA-GISS and an associate professor at Medgar Evers College of CUNY, an urban minority serving institution in central Brooklyn. Supported by NSF Award AGS-1359293 And NASA Award NNX17AC81G.

Linking the variability of atmospheric carbon monoxide to climate modes in the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Buchholz, Rebecca; Monks, Sarah; Hammerling, Dorit; Worden, Helen; Deeter, Merritt; Emmons, Louisa; Edwards, David

2017-04-01

Biomass burning is a major driver of atmospheric carbon monoxide (CO) variability in the Southern Hemisphere. The magnitude of emissions, such as CO, from biomass burning is connected to climate through both the availability and dryness of fuel. We investigate the link between CO and climate using satellite measured CO and climate indices. Observations of total column CO from the satellite instrument MOPITT are used to build a record of interannual variability in CO since 2001. Four biomass burning regions in the Southern Hemisphere are explored. Data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Southern Annular Mode (SAM). Stepwise forward and backward regression is used to select the best statistical model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Implications of the model results are discussed for the Maritime Southeast Asia and Australasia regions. We also draw on the chemistry-climate model CAM-chem to explain the source contribution as well as the relative contributions of emissions and meteorology to CO variability.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

Outcomes of a National Environmental Edutainment Program in High Schools

NASA Astrophysics Data System (ADS)

Lappe, M. D.

2012-12-01

We present results of the first longitudinal evaluation of a nation-wide environmental edutainment program. There has recently been rapid growth in curricula on the environment and climate change, yet few reach large and diverse audiences, and fewer still are evaluated. These results are from high schools participating in the Alliance for Climate Education (ACE) program. ACE is a 3 year-old program that has reached 1.2 million students with an edutainment presentation incorporating music, multi-media, animation, and documentary footage (www.acespace.org). A projected 850 schools across 23 states will see the presentation this year; 6% of schools (3 classes each) are randomly selected to be evaluated. The data described here were collected in Fall 2011 from 1,270 students in 21 schools; the full evaluation will be complete in May 2012. The sample is ethnically and socio-economically diverse — 29% are white, and 46% receive free/reduced lunches (a proxy for socio-economic status). Outcome measures included a test of climate knowledge and intentions to take (and to ask others to take) climate-related actions. The analyses examined direct effects of the ACE program on climate knowledge and intentions, as well as the moderating effects of student gender and age on learning. Before the ACE presentation, boys had significantly higher knowledge scores than girls (54% vs. 48% correct, respectively, p < .001). Afterward, boys and girls both had significantly higher knowledge scores (64% and 63% correct, respectively) and no longer differed from each other in this respect. Before the presentation, girls expressed significantly greater intentions to take climate-related actions than did boys. Afterward, intentions increased significantly in both groups, but the gap between girls and boys remained. The gap-closing pattern was somewhat different for the moderating variable of age. Before the presentation, knowledge and intentions were significantly higher among older students (11th- and 12th-graders) than among younger students (9th- and 10th-graders). Afterward, knowledge and intentions increased significantly in both groups, but the gap between them remained for knowledge and closed for intentions. These promising early results demonstrate how a single well-designed edutaiment presentation can appeal broadly to students and advance environmental education on a large scale.

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

Otterå, Odd Helge; Bentsen, Mats; Drange, Helge; Suo, Lingling

2010-10-01

Instrumental records, proxy data and climate modelling show that multidecadal variability is a dominant feature of North Atlantic sea-surface temperature variations, with potential impacts on regional climate. To understand the observed variability and to gauge any potential for climate predictions it is essential to identify the physical mechanisms that lead to this variability, and to explore the spatial and temporal characteristics of multidecadal variability modes. Here we use a coupled ocean-atmosphere general circulation model to show that the phasing of the multidecadal fluctuations in the North Atlantic during the past 600 years is, to a large degree, governed by changes in the external solar and volcanic forcings. We find that volcanoes play a particularly important part in the phasing of the multidecadal variability through their direct influence on tropical sea-surface temperatures, on the leading mode of northern-hemisphere atmosphere circulation and on the Atlantic thermohaline circulation. We suggest that the implications of our findings for decadal climate prediction are twofold: because volcanic eruptions cannot be predicted a decade in advance, longer-term climate predictability may prove challenging, whereas the systematic post-eruption changes in ocean and atmosphere may hold promise for shorter-term climate prediction.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

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.

Vulnerability Assessment of Natural Disasters for Small and Mid-Sized Streams due to Climate Change and Stream Improvement

NASA Astrophysics Data System (ADS)

Choi, D.; Jun, H. D.; Kim, S.

2012-04-01

Vulnerability assessment plays an important role in drawing up climate change adaptation plans. Although there are some studies on broad vulnerability assessment in Korea, there have been very few studies to develop and apply locally focused and specific sector-oriented climate change vulnerability indicators. Especially, there has seldom been any study to investigate the effect of an adaptation project on assessing the vulnerability status to climate change for fundamental local governments. In order to relieve adverse effects of climate change, Korean government has performed the project of the Major Four Rivers (Han, Geum, Nakdong and Yeongsan river) Restoration since 2008. It is expected that water level in main stream of 4 rivers will be dropped through this project, but flood effect will be mainly occurred in small and mid-sized streams which flows in main stream. Hence, we examined how much the project of the major four rivers restoration relieves natural disasters. Conceptual framework of vulnerability-resilience index to climate change for the Korean fundamental local governments is defined as a function of climate exposure, sensitivity, and adaptive capacity. Then, statistical data on scores of proxy variables assumed to comprise climate change vulnerability for local governments are collected. Proxy variables and estimated temporary weights of them are selected by surveying a panel of experts using Delphi method, and final weights are determined by modified Entropy method. Developed vulnerability-resilience index was applied to Korean fundamental local governments and it is calculated under each scenario as follows. (1) Before the major four rivers restoration, (2) 100 years after represented climate change condition without the major four rivers restoration, (3) After the major four rivers restoration without representing climate change (this means present climate condition) and (4) After the major four rivers restoration and 100 years after represented climate change condition. In the results of calculated vulnerability-resilience index of each scenario, it can be noticed that vulnerability of watersheds which are located near main stream of four rivers is alleviated, but because of climate change, vulnerability is getting high in most watersheds. Also, considering future climate change and river restoration, vulnerability of several watersheds is relieved by river restoration. Acknowledges This work was funded by the National Emergency Management Agency (NEMA) in Korea Program under Grant NEMA-10-NH-04.

Testing the Sun-climate Connection with Paleoclimate Data

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.; Howard, Matthew K.

1990-01-01

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

An 'Observational Large Ensemble' to compare observed and modeled temperature trend uncertainty due to internal variability.

NASA Astrophysics Data System (ADS)

Poppick, A. N.; McKinnon, K. A.; Dunn-Sigouin, E.; Deser, C.

2017-12-01

Initial condition climate model ensembles suggest that regional temperature trends can be highly variable on decadal timescales due to characteristics of internal climate variability. Accounting for trend uncertainty due to internal variability is therefore necessary to contextualize recent observed temperature changes. However, while the variability of trends in a climate model ensemble can be evaluated directly (as the spread across ensemble members), internal variability simulated by a climate model may be inconsistent with observations. Observation-based methods for assessing the role of internal variability on trend uncertainty are therefore required. Here, we use a statistical resampling approach to assess trend uncertainty due to internal variability in historical 50-year (1966-2015) winter near-surface air temperature trends over North America. We compare this estimate of trend uncertainty to simulated trend variability in the NCAR CESM1 Large Ensemble (LENS), finding that uncertainty in wintertime temperature trends over North America due to internal variability is largely overestimated by CESM1, on average by a factor of 32%. Our observation-based resampling approach is combined with the forced signal from LENS to produce an 'Observational Large Ensemble' (OLENS). The members of OLENS indicate a range of spatially coherent fields of temperature trends resulting from different sequences of internal variability consistent with observations. The smaller trend variability in OLENS suggests that uncertainty in the historical climate change signal in observations due to internal variability is less than suggested by LENS.

Organizational Climate Assessment: a Systemic Perspective

NASA Astrophysics Data System (ADS)

Argentero, Piergiorgio; Setti, Ilaria

A number of studies showed how the set up of an involving and motivating work environment represents a source for organizational competitive advantage: in this view organizational climate (OC) research occupies a preferred position in current I/O psychology. The present study is a review carried out to establish the breadth of the literature on the characteristics of OC assessment considered in a systemic perspective. An organization with a strong climate is a work environment whose members have similar understanding of the norms and practices and share the same expectations. OC should be considered as a sort of emergent entity and, as such, it can be studied only within a systemic perspective because it is linked with some organizational variables, in terms of antecedents (such as the organization's internal structure and its environmental features) and consequences (such as job performance, psychological well-being and withdrawal) of the climate itself. In particular, when employees have a positive view of their organizational environment, consistently with their values and interests, they are more likely to identify their personal goals with those of the organization and, in turn, to invest a greater effort to pursue them: the employees' perception of the organizational environment is positively related to the key outcomes such as job involvement, effort and performance. OC analysis could also be considered as an effective Organizational Development (OD) tool: in particular, the Survey Feedback, that is the return of the OC survey results, could be an effective instrument to assess the efficacy of specific OD programs, such as Team Building, TQM and Gainsharing. The present study is focused on the interest to investigate all possible variables which are potential moderators of the climate - outcome relationship: therefore future researches in the OC field should consider a great variety of organizational variables, considered in terms of antecedents and effects of OC, and OC studies should be conducted as cross-level and multilevel researches.

Trends and Controls of inter-annual Variability in the Carbon Budget of Terrestrial Ecosystems

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

The climate sensitivity of the terrestrial carbon budget will substantially affect the sign and strength of the land-climate feedbacks and the future climate trajectories. Current trends in the inter-annual variability of terrestrial carbon fluxes (IAV) may contribute to clarify the relative role of physical and biological controls of ecosystem responses to climate change. For this purpose we investigated how recent climate variability has impacted the carbon fluxes at long-term FLUXNET sites. Using a novel method, the IAV has been factored out in climate induced variability (physical control), variability due to changes in ecosystem functioning (biological control) and the interaction of the two terms. The relative control of the main climatic drivers (temperature, water availability) on the physical and biological sources of IAV has been investigated using both site level fluxes and global gridded products generated from the up-scaling of flux data. Results of this analysis highlight the fundamental role of precipitation trends on the pattern of IAV in the last 30 years. Our findings on the spatial/temporal trends of IAV have been finally confirmed using the signal derived from the global network of atmospheric CO2 concentrations measurements.

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2010-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance.

Quantifying the increasing sensitivity of power systems to climate variability

NASA Astrophysics Data System (ADS)

Bloomfield, H. C.; Brayshaw, D. J.; Shaffrey, L. C.; Coker, P. J.; Thornton, H. E.

2016-12-01

Large quantities of weather-dependent renewable energy generation are expected in power systems under climate change mitigation policies, yet little attention has been given to the impact of long term climate variability. By combining state-of-the-art multi-decadal meteorological records with a parsimonious representation of a power system, this study characterises the impact of year-to-year climate variability on multiple aspects of the power system of Great Britain (including coal, gas and nuclear generation), demonstrating why multi-decadal approaches are necessary. All aspects of the example system are impacted by inter-annual climate variability, with the impacts being most pronounced for baseload generation. The impacts of inter-annual climate variability increase in a 2025 wind-power scenario, with a 4-fold increase in the inter-annual range of operating hours for baseload such as nuclear. The impacts on peak load and peaking-plant are comparably small. Less than 10 years of power supply and demand data are shown to be insufficient for providing robust power system planning guidance. This suggests renewable integration studies—widely used in policy, investment and system design—should adopt a more robust approach to climate characterisation.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Quantifying climate-growth relationships at the stand level in a mature mixed-species conifer forest.

PubMed

Teets, Aaron; Fraver, Shawn; Weiskittel, Aaron R; Hollinger, David Y

2018-03-11

A range of environmental factors regulate tree growth; however, climate is generally thought to most strongly influence year-to-year variability in growth. Numerous dendrochronological (tree-ring) studies have identified climate factors that influence year-to-year variability in growth for given tree species and location. However, traditional dendrochronology methods have limitations that prevent them from adequately assessing stand-level (as opposed to species-level) growth. We argue that stand-level growth analyses provide a more meaningful assessment of forest response to climate fluctuations, as well as the management options that may be employed to sustain forest productivity. Working in a mature, mixed-species stand at the Howland Research Forest of central Maine, USA, we used two alternatives to traditional dendrochronological analyses by (1) selecting trees for coring using a stratified (by size and species), random sampling method that ensures a representative sample of the stand, and (2) converting ring widths to biomass increments, which once summed, produced a representation of stand-level growth, while maintaining species identities or canopy position if needed. We then tested the relative influence of seasonal climate variables on year-to-year variability in the biomass increment using generalized least squares regression, while accounting for temporal autocorrelation. Our results indicate that stand-level growth responded most strongly to previous summer and current spring climate variables, resulting from a combination of individualistic climate responses occurring at the species- and canopy-position level. Our climate models were better fit to stand-level biomass increment than to species-level or canopy-position summaries. The relative growth responses (i.e., percent change) predicted from the most influential climate variables indicate stand-level growth varies less from to year-to-year than species-level or canopy-position growth responses. By assessing stand-level growth response to climate, we provide an alternative perspective on climate-growth relationships of forests, improving our understanding of forest growth dynamics under a fluctuating climate. © 2018 John Wiley & Sons Ltd.

NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso.

PubMed

Sorgho, Raissa; Franke, Jonas; Simboro, Seraphin; Phalkey, Revati; Saeurborn, Rainer

Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3-4 °C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variables through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Vulnerability of Breeding Waterbirds to Climate Change in the Prairie Pothole Region, U.S.A

PubMed Central

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts. PMID:24927165

Vulnerability of breeding waterbirds to climate change in the Prairie Pothole Region, U.S.A.

USGS Publications Warehouse

Steen, Valerie; Skagen, Susan K.; Noon, Barry R.

2014-01-01

The Prairie Pothole Region (PPR) of the north-central U.S. and south-central Canada contains millions of small prairie wetlands that provide critical habitat to many migrating and breeding waterbirds. Due to their small size and the relatively dry climate of the region, these wetlands are considered at high risk for negative climate change effects as temperatures increase. To estimate the potential impacts of climate change on breeding waterbirds, we predicted current and future distributions of species common in the PPR using species distribution models (SDMs). We created regional-scale SDMs for the U.S. PPR using Breeding Bird Survey occurrence records for 1971–2011 and wetland, upland, and climate variables. For each species, we predicted current distribution based on climate records for 1981–2000 and projected future distributions to climate scenarios for 2040–2049. Species were projected to, on average, lose almost half their current habitat (-46%). However, individual species projections varied widely, from +8% (Upland Sandpiper) to -100% (Wilson's Snipe). Variable importance ranks indicated that land cover (wetland and upland) variables were generally more important than climate variables in predicting species distributions. However, climate variables were relatively more important during a drought period. Projected distributions of species responses to climate change contracted within current areas of distribution rather than shifting. Given the large variation in species-level impacts, we suggest that climate change mitigation efforts focus on species projected to be the most vulnerable by enacting targeted wetland management, easement acquisition, and restoration efforts.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

About the Climate Ready Estuaries Program

EPA Pesticide Factsheets

The Climate Ready Estuaries program is a partnership between EPA and the National Estuary Programs to address climate change in coastal areas. It has helped coastal communities prepare for climate change since 2008.

Future hotspots of increasing temperature variability in tropical countries

NASA Astrophysics Data System (ADS)

Bathiany, S.; Dakos, V.; Scheffer, M.; Lenton, T. M.

2017-12-01

Resolving how climate variability will change in future is crucial to determining how challenging it will be for societies and ecosystems to adapt to climate change. We show that the largest increases in temperature variability - that are robust between state-of-the art climate models - are concentrated in tropical countries. On average, temperature variability increases by 15% per degree of global warming in Amazonia and Southern Africa during austral summer, and by up to 10% °C-1 in the Sahel, India and South East Asia. Southern hemisphere changes can be explained by drying soils, whereas shifts in atmospheric structure play a more important role in the Northern hemisphere. These robust regional changes in variability are associated with monthly timescale events, whereas uncertain changes in inter-annual modes of variability make the response of global temperature variability uncertain. Our results suggest that regional changes in temperature variability will create new inequalities in climate change impacts between rich and poor nations.

Climate variability decreases species richness and community stability in a temperate grassland.

PubMed

Zhang, Yunhai; Loreau, Michel; He, Nianpeng; Wang, Junbang; Pan, Qingmin; Bai, Yongfei; Han, Xingguo

2018-06-26

Climate change involves modifications in both the mean and the variability of temperature and precipitation. According to global warming projections, both the magnitude and the frequency of extreme weather events are increasing, thereby increasing climate variability. The previous studies have reported that climate warming tends to decrease biodiversity and the temporal stability of community primary productivity (i.e., community stability), but the effects of the variability of temperature and precipitation on biodiversity, community stability, and their relationship have not been clearly explored. We used a long-term (from 1982 to 2014) field data set from a temperate grassland in northern China to explore the effects of the variability of mean temperature and total precipitation on species richness, community stability, and their relationship. Results showed that species richness promoted community stability through increases in asynchronous dynamics across species (i.e., species asynchrony). Both species richness and species asynchrony were positively associated with the residuals of community stability after controlling for its dependence on the variability of mean temperature and total precipitation. Furthermore, the variability of mean temperature reduced species richness, while the variability of total precipitation decreased species asynchrony and community stability. Overall, the present study revealed that species richness and species asynchrony promoted community stability, but increased climate variability may erode these positive effects and thereby threaten community stability.

Changes in climate variability with reference to land quality and agriculture in Scotland.

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

Intensified Indian Ocean climate variability during the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Thirumalai, K.; DiNezro, P.; Tierney, J. E.; Puy, M.; Mohtadi, M.

2017-12-01

Climate models project increased year-to-year climate variability in the equatorial Indian Ocean in response to greenhouse gas warming. This response has been attributed to changes in the mean climate of the Indian Ocean associated with the zonal sea-surface temperature (SST) gradient. According to these studies, air-sea coupling is enhanced due to a stronger SST gradient driving anomalous easterlies that shoal the thermocline in the eastern Indian Ocean. We propose that this relationship between the variability and the zonal SST gradient is consistent across different mean climate states. We test this hypothesis using simulations of past and future climate performed with the Community Earth System Model Version 1 (CESM1). We constrain the realism of the model for the Last Glacial Maximum (LGM) where CESM1 simulates a mean climate consistent with a stronger SST gradient, agreeing with proxy reconstructions. CESM1 also simulates a pronounced increase in seasonal and interannual variability. We develop new estimates of climate variability on these timescales during the LGM using δ18O analysis of individual foraminifera (IFA). IFA data generated from four different cores located in the eastern Indian Ocean indicate a marked increase in δ18O-variance during the LGM as compared to the late Holocene. Such a significant increase in the IFA-δ18O variance strongly supports the modeling simulations. This agreement further supports the dynamics linking year-to-year variability and an altered SST gradient, increasing our confidence in model projections.

Holocene climate variability in Texas, USA: An integration of existing paleoclimate data and modeling with a new, high-resolution speleothem record

USGS Publications Warehouse

Wong, Corinne I.; Banner, Jay L.; Musgrove, MaryLynn

2015-01-01

Delineating the climate processes governing precipitation variability in drought-prone Texas is critical for predicting and mitigating climate change effects, and requires the reconstruction of past climate beyond the instrumental record. We synthesize existing paleoclimate proxy data and climate simulations to provide an overview of climate variability in Texas during the Holocene. Conditions became progressively warmer and drier transitioning from the early to mid Holocene, culminating between 7 and 3 ka (thousand years ago), and were more variable during the late Holocene. The timing and relative magnitude of Holocene climate variability, however, is poorly constrained owing to considerable variability among the different records. To help address this, we present a new speleothem (NBJ) reconstruction from a central Texas cave that comprises the highest resolution proxy record to date, spanning the mid to late Holocene. NBJ trace-element concentrations indicate variable moisture conditions with no clear temporal trend. There is a decoupling between NBJ growth rate, trace-element concentrations, and δ18O values, which indicate that (i) the often direct relation between speleothem growth rate and moisture availability is likely complicated by changes in the overlying ecosystem that affect subsurface CO2 production, and (ii) speleothem δ18O variations likely reflect changes in moisture source (i.e., proportion of Pacific-vs. Gulf of Mexico-derived moisture) that appear not to be linked to moisture amount.

Hydrological Responses of Andean Lakes and Tropical Floodplains to Climate Variability and Human Intervention: an Integrative Modelling Framework

NASA Astrophysics Data System (ADS)

Hoyos, I. C.; González Morales, C.; Serna López, J. P.; Duque, C. L.; Canon Barriga, J. E.; Dominguez, F.

2013-12-01

Andean water bodies in tropical regions are significantly influenced by fluctuations associated with climatic and anthropogenic drivers, which implies long term changes in mountain snow peaks, land covers and ecosystems, among others. Our work aims at providing an integrative framework to realistically assess the possible future of natural water bodies with different degrees of human intervention. We are studying in particular the evolution of three water bodies in Colombia: two Andean lakes and a floodplain wetland. These natural reservoirs represent the accumulated effect of hydrological processes in their respective basins, which exhibit different patterns of climate variability and distinct human intervention and environmental histories. Modelling the hydrological responses of these local water bodies to climate variability and human intervention require an understanding of the strong linkage between geophysical and social factors. From the geophysical perspective, the challenge is how to downscale global climate projections in the local context: complex orography and relative lack of data. To overcome this challenge we combine the correlational and physically based analysis of several sources of spatially distributed biophysical and meteorological information to accurately determine aspects such as moisture sources and sinks and past, present and future local precipitation and temperature regimes. From the social perspective, the challenge is how to adequately represent and incorporate into the models the likely response of social agents whose water-related interests are diverse and usually conflictive. To deal with the complexity of these systems we develop interaction matrices, which are useful tools to holistically discuss and represent each environment as a complex system. Our goal is to assess partially the uncertainties of the hydrological balances in these intervened water bodies we establish climate/social scenarios, using hybrid models that combine the computational power of numerical simulations (of both physical and social components) with interactive responses given by users who define strategies and make decisions in real time, providing valuable information about people's attitudes and choices regarding future climate perspectives. Part of our interest with this project is to effectively transfer the knowledge and scientific information gathered to the communities in a way that is useful and propositive. To this end we developed a website (http://peerlagoscolombia.udea.edu.co) that includes relevant information about the project outcomes. We also developed and installed telemetric hydrologic stations in each site, whose data on water storage levels and basic meteorological variables can be accessed online. Acknowledgement: this project is funded by the USAID-NSF PEER program (First cycle, project 31).

Estimating the impact of internal climate variability on ice sheet model simulations

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2016-12-01

Rising sea level threatens human societies and coastal habitats and melting ice sheets are a major contributor to sea level rise (SLR). Thus, understanding uncertainty of both forcing and variability within the climate system is essential for assessing long-term risk of SLR given their impact on ice sheet evolution. The predictability of polar climate is limited by uncertainties from the given forcing, the climate model response to this forcing, and the internal variability from feedbacks within the fully coupled climate system. Among those sources of uncertainty, the impact of internal climate variability on ice sheet changes has not yet been robustly assessed. Here we investigate how internal variability affects ice sheet projections using climate fields from two Community Earth System Model (CESM) large-ensemble (LE) experiments to force a three-dimensional ice sheet model. Each ensemble member in an LE experiment undergoes the same external forcings but with unique initial conditions. We find that for both LEs, 2m air temperature variability over Greenland ice sheet (GrIS) can lead to significantly different ice sheet responses. Our results show that the internal variability from two fully coupled CESM LEs can cause about 25 35 mm differences of GrIS's contribution to SLR in 2100 compared to present day (about 20% of the total change), and 100m differences of SLR in 2300. Moreover, only using ensemble-mean climate fields as the forcing in ice sheet model can significantly underestimate the melt of GrIS. As the Arctic region becomes warmer, the role of internal variability is critical given the complex nonlinear interactions between surface temperature and ice sheet. Our results demonstrate that internal variability from coupled atmosphere-ocean general circulation model can affect ice sheet simulations and the resulting sea-level projections. This study highlights an urgent need to reassess associated uncertainties of projecting ice sheet loss over the next few centuries to obtain robust estimates of the contribution of ice sheet melt to SLR.

Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts.

PubMed

Tanner, Evan P; Papeş, Monica; Elmore, R Dwayne; Fuhlendorf, Samuel D; Davis, Craig A

2017-01-01

Ecological niche models (ENMs) have increasingly been used to estimate the potential effects of climate change on species' distributions worldwide. Recently, predictions of species abundance have also been obtained with such models, though knowledge about the climatic variables affecting species abundance is often lacking. To address this, we used a well-studied guild (temperate North American quail) and the Maxent modeling algorithm to compare model performance of three variable selection approaches: correlation/variable contribution (CVC), biological (i.e., variables known to affect species abundance), and random. We then applied the best approach to forecast potential distributions, under future climatic conditions, and analyze future potential distributions in light of available abundance data and presence-only occurrence data. To estimate species' distributional shifts we generated ensemble forecasts using four global circulation models, four representative concentration pathways, and two time periods (2050 and 2070). Furthermore, we present distributional shifts where 75%, 90%, and 100% of our ensemble models agreed. The CVC variable selection approach outperformed our biological approach for four of the six species. Model projections indicated species-specific effects of climate change on future distributions of temperate North American quail. The Gambel's quail (Callipepla gambelii) was the only species predicted to gain area in climatic suitability across all three scenarios of ensemble model agreement. Conversely, the scaled quail (Callipepla squamata) was the only species predicted to lose area in climatic suitability across all three scenarios of ensemble model agreement. Our models projected future loss of areas for the northern bobwhite (Colinus virginianus) and scaled quail in portions of their distributions which are currently areas of high abundance. Climatic variables that influence local abundance may not always scale up to influence species' distributions. Special attention should be given to selecting variables for ENMs, and tests of model performance should be used to validate the choice of variables.

Using physiology to understand climate-driven changes in disease and their implications for conservation.

PubMed

Rohr, Jason R; Raffel, Thomas R; Blaustein, Andrew R; Johnson, Pieter T J; Paull, Sara H; Young, Suzanne

2013-01-01

Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host-parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host-parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change-disease literature. We stress that much of the work on how climate influences host-parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host-parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host-parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations.

Using physiology to understand climate-driven changes in disease and their implications for conservation

PubMed Central

Rohr, Jason R.; Raffel, Thomas R.; Blaustein, Andrew R.; Johnson, Pieter T. J.; Paull, Sara H.; Young, Suzanne

2013-01-01

Controversy persists regarding the contributions of climate change to biodiversity losses, through its effects on the spread and emergence of infectious diseases. One of the reasons for this controversy is that there are few mechanistic studies that explore the links among climate change, infectious disease, and declines of host populations. Given that host–parasite interactions are generally mediated by physiological responses, we submit that physiological models could facilitate the prediction of how host–parasite interactions will respond to climate change, and might offer theoretical and terminological cohesion that has been lacking in the climate change–disease literature. We stress that much of the work on how climate influences host–parasite interactions has emphasized changes in climatic means, despite a hallmark of climate change being changes in climatic variability and extremes. Owing to this gap, we highlight how temporal variability in weather, coupled with non-linearities in responses to mean climate, can be used to predict the effects of climate on host–parasite interactions. We also discuss the climate variability hypothesis for disease-related declines, which posits that increased unpredictable temperature variability might provide a temporary advantage to pathogens because they are smaller and have faster metabolisms than their hosts, allowing more rapid acclimatization following a temperature shift. In support of these hypotheses, we provide case studies on the role of climatic variability in host population declines associated with the emergence of the infectious diseases chytridiomycosis, withering syndrome, and malaria. Finally, we present a mathematical model that provides the scaffolding to integrate metabolic theory, physiological mechanisms, and large-scale spatiotemporal processes to predict how simultaneous changes in climatic means, variances, and extremes will affect host–parasite interactions. However, several outstanding questions remain to be answered before investigators can accurately predict how changes in climatic means and variances will affect infectious diseases and the conservation status of host populations. PMID:27293606

Disease and thermal acclimation in a more variable and unpredictable climate

NASA Astrophysics Data System (ADS)

Raffel, Thomas R.; Romansic, John M.; Halstead, Neal T.; McMahon, Taegan A.; Venesky, Matthew D.; Rohr, Jason R.

2013-02-01

Global climate change is shifting the distribution of infectious diseases of humans and wildlife with potential adverse consequences for disease control. As well as increasing mean temperatures, climate change is expected to increase climate variability, 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 conducted in 80 independent incubators, and field data on disease-associated frog declines in Latin America, support the framework and provide evidence that unpredictable temperature fluctuations, on both monthly and diurnal timescales, decrease frog resistance to the pathogenic chytrid fungus Batrachochytrium dendrobatidis. Furthermore, the pattern of temperature-dependent growth of the fungus on frogs was opposite to the pattern of growth in culture, emphasizing the importance of accounting for the host-parasite interaction when predicting climate-dependent disease dynamics. If similar acclimation responses influence other host-parasite systems, as seems likely, then present models, which generally ignore small-scale temporal variability in climate, might provide poor predictions for climate effects on disease.

Effects of climate change on residential infiltration and air pollution exposure.

PubMed

Ilacqua, Vito; Dawson, John; Breen, Michael; Singer, Sarany; Berg, Ashley

2017-01-01

Air exchange through infiltration is driven partly by indoor/outdoor temperature differences, and as climate change increases ambient temperatures, such differences could vary considerably even with small ambient temperature increments, altering patterns of exposures to both indoor and outdoor pollutants. We calculated changes in air fluxes through infiltration for prototypical detached homes in nine metropolitan areas in the United States (Atlanta, Boston, Chicago, Houston, Los Angeles, Minneapolis, New York, Phoenix, and Seattle) from 1970-2000 to 2040-2070. The Lawrence Berkeley National Laboratory model of infiltration was used in combination with climate data from eight regionally downscaled climate models from the North American Regional Climate Change Assessment Program. Averaged over all study locations, seasons, and climate models, air exchange through infiltration would decrease by ~5%. Localized increased infiltration is expected during the summer months, up to 20-30%. Seasonal and daily variability in infiltration are also expected to increase, particularly during the summer months. Diminished infiltration in future climate scenarios may be expected to increase exposure to indoor sources of air pollution, unless these ventilation reductions are otherwise compensated. Exposure to ambient air pollution, conversely, could be mitigated by lower infiltration, although peak exposure increases during summer months should be considered, as well as other mechanisms.

Cloud-Enabled Climate Analytics-as-a-Service using Reanalysis data: A case study.

NASA Astrophysics Data System (ADS)

Nadeau, D.; Duffy, D.; Schnase, J. L.; McInerney, M.; Tamkin, G.; Potter, G. L.; Thompson, J. H.

2014-12-01

The NASA Center for Climate Simulation (NCCS) maintains advanced data capabilities and facilities that allow researchers to access the enormous volume of data generated by weather and climate models. The NASA Climate Model Data Service (CDS) and the NCCS are merging their efforts to provide Climate Analytics-as-a-Service for the comparative study of the major reanalysis projects: ECMWF ERA-Interim, NASA/GMAO MERRA, NOAA/NCEP CFSR, NOAA/ESRL 20CR, JMA JRA25, and JRA55. These reanalyses have been repackaged to netCDF4 file format following the CMIP5 Climate and Forecast (CF) metadata convention prior to be sequenced into the Hadoop Distributed File System ( HDFS ). A small set of operations that represent a common starting point in many analysis workflows was then created: min, max, sum, count, variance and average. In this example, Reanalysis data exploration was performed with the use of Hadoop MapReduce and accessibility was achieved using the Climate Data Service(CDS) application programming interface (API) created at NCCS. This API provides a uniform treatment of large amount of data. In this case study, we have limited our exploration to 2 variables, temperature and precipitation, using 3 operations, min, max and avg and using 30-year of Reanalysis data for 3 regions of the world: global, polar, subtropical.

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

Final Report: Closeout of the Award NO. DE-FG02-98ER62618 (M.S. Fox-Rabinovitz, P.I.)

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

Fox-Rabinovitz, M. S.

The final report describes the study aimed at exploring the variable-resolution stretched-grid (SG) approach to decadal regional climate modeling using advanced numerical techniques. The obtained results have shown that variable-resolution SG-GCMs using stretched grids with fine resolution over the area(s) of interest, is a viable established approach to regional climate modeling. The developed SG-GCMs have been extensively used for regional climate experimentation. The SG-GCM simulations are aimed at studying the U.S. regional climate variability with an emphasis on studying anomalous summer climate events, the U.S. droughts and floods.

Evaluating the Contribution of Natural Variability and Climate Model Response to Uncertainty in Projections of Climate Change Impacts on U.S. Air Quality

EPA Science Inventory

We examine the effects of internal variability and model response in projections of climate impacts on U.S. ground-level ozone across the 21st century using integrated global system modeling and global atmospheric chemistry simulations. The impact of climate change on air polluti...

Effects of model spatial resolution on ecohydrologic predictions and their sensitivity to inter-annual climate variability

Treesearch

Kyongho Son; Christina Tague; Carolyn Hunsaker

2016-01-01

The effect of fine-scale topographic variability on model estimates of ecohydrologic responses to climate variability in California’s Sierra Nevada watersheds has not been adequately quantified and may be important for supporting reliable climate-impact assessments. This study tested the effect of digital elevation model (DEM) resolution on model accuracy and estimates...

The effects of precipitation variability on C4 photosynthesis, net primary production and soil respiration in a Chihuahuan desert grassland

Treesearch

Michell L. Thomey

2012-01-01

Although the Earth's climate system has always been inherently variable, the magnitude and rate of anthropogenic climate change is subjecting ecosystems and the populations that they contain to novel environmental conditions. Because water is the most limiting resource, arid-semiarid ecosystems are likely to be highly responsive to future climate variability. The...

Interannual and spatial variability of maple syrup yield as related to climatic factors

PubMed Central

Houle, Daniel

2014-01-01

Sugar maple syrup production is an important economic activity for eastern Canada and the northeastern United States. Since annual variations in syrup yield have been related to climate, there are concerns about the impacts of climatic change on the industry in the upcoming decades. Although the temporal variability of syrup yield has been studied for specific sites on different time scales or for large regions, a model capable of accounting for both temporal and regional differences in yield is still lacking. In the present study, we studied the factors responsible for interregional and interannual variability in maple syrup yield over the 2001–2012 period, by combining the data from 8 Quebec regions (Canada) and 10 U.S. states. The resulting model explained 44.5% of the variability in yield. It includes the effect of climatic conditions that precede the sapflow season (variables from the previous growing season and winter), the effect of climatic conditions during the current sapflow season, and terms accounting for intercountry and temporal variability. Optimal conditions for maple syrup production appear to be spatially restricted by less favourable climate conditions occurring during the growing season in the north, and in the south, by the warmer winter and earlier spring conditions. This suggests that climate change may favor maple syrup production northwards, while southern regions are more likely to be negatively affected by adverse spring conditions. PMID:24949244

Effects of climate change and variability on population dynamics in a long-lived shorebird.

PubMed

van de Pol, Martijn; Vindenes, Yngvild; Saether, Bernt-Erik; Engen, Steinar; Ens, Bruno J; Oosterbeek, Kees; Tinbergen, Joost M

2010-04-01

Climate change affects both the mean and variability of climatic variables, but their relative impact on the dynamics of populations is still largely unexplored. Based on a long-term study of the demography of a declining Eurasian Oystercatcher (Haematopus ostralegus) population, we quantify the effect of changes in mean and variance of winter temperature on different vital rates across the life cycle. Subsequently, we quantify, using stochastic stage-structured models, how changes in the mean and variance of this environmental variable affect important characteristics of the future population dynamics, such as the time to extinction. Local mean winter temperature is predicted to strongly increase, and we show that this is likely to increase the population's persistence time via its positive effects on adult survival that outweigh the negative effects that higher temperatures have on fecundity. Interannual variation in winter temperature is predicted to decrease, which is also likely to increase persistence time via its positive effects on adult survival that outweigh the negative effects that lower temperature variability has on fecundity. Overall, a 0.1 degrees C change in mean temperature is predicted to alter median time to extinction by 1.5 times as many years as would a 0.1 degrees C change in the standard deviation in temperature, suggesting that the dynamics of oystercatchers are more sensitive to changes in the mean than in the interannual variability of this climatic variable. Moreover, as climate models predict larger changes in the mean than in the standard deviation of local winter temperature, the effects of future climatic variability on this population's time to extinction are expected to be overwhelmed by the effects of changes in climatic means. We discuss the mechanisms by which climatic variability can either increase or decrease population viability and how this might depend both on species' life histories and on the vital rates affected. This study illustrates that, for making reliable inferences about population consequences in species in which life history changes with age or stage, it is crucial to investigate the impact of climate change on vital rates across the entire life cycle. Disturbingly, such data are unavailable for most species of conservation concern.

The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB V1.0) Contribution to CMIP6

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Kovats, R. Sari;

The Vulnerability, Impacts, Adaptation and Climate Services Advisory Board (VIACS AB v1.0) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Ruane, Alex C.; Teichmann, Claas; Arnell, Nigel W.; Carter, Timothy R.; Ebi, Kristie L.; Frieler, Katja; Goodess, Clare M.; Hewitson, Bruce; Horton, Radley; Sari Kovats, R.; Lotze, Heike K.; Mearns, Linda O.; Navarra, Antonio; Ojima, Dennis S.; Riahi, Keywan; Rosenzweig, Cynthia; Themessl, Matthias; Vincent, Katharine

2016-09-01

This paper describes the motivation for the creation of the Vulnerability, Impacts, Adaptation and Climate Services (VIACS) Advisory Board for the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6), its initial activities, and its plans to serve as a bridge between climate change applications experts and climate modelers. The climate change application community comprises researchers and other specialists who use climate information (alongside socioeconomic and other environmental information) to analyze vulnerability, impacts, and adaptation of natural systems and society in relation to past, ongoing, and projected future climate change. Much of this activity is directed toward the co-development of information needed by decision-makers for managing projected risks. CMIP6 provides a unique opportunity to facilitate a two-way dialog between climate modelers and VIACS experts who are looking to apply CMIP6 results for a wide array of research and climate services objectives. The VIACS Advisory Board convenes leaders of major impact sectors, international programs, and climate services to solicit community feedback that increases the applications relevance of the CMIP6-Endorsed Model Intercomparison Projects (MIPs). As an illustration of its potential, the VIACS community provided CMIP6 leadership with a list of prioritized climate model variables and MIP experiments of the greatest interest to the climate model applications community, indicating the applicability and societal relevance of climate model simulation outputs. The VIACS Advisory Board also recommended an impacts version of Obs4MIPs and indicated user needs for the gridding and processing of model output.

Updating beliefs and combining evidence in adaptive forest management under climate change: a case study of Norway spruce (Picea abies L. Karst) in the Black Forest, Germany.

PubMed

Yousefpour, Rasoul; Temperli, Christian; Bugmann, Harald; Elkin, Che; Hanewinkel, Marc; Meilby, Henrik; Jacobsen, Jette Bredahl; Thorsen, Bo Jellesmark

2013-06-15

We study climate uncertainty and how managers' beliefs about climate change develop and influence their decisions. We develop an approach for updating knowledge and beliefs based on the observation of forest and climate variables and illustrate its application for the adaptive management of an even-aged Norway spruce (Picea abies L. Karst) forest in the Black Forest, Germany. We simulated forest development under a range of climate change scenarios and forest management alternatives. Our analysis used Bayesian updating and Dempster's rule of combination to simulate how observations of climate and forest variables may influence a decision maker's beliefs about climate development and thereby management decisions. While forest managers may be inclined to rely on observed forest variables to infer climate change and impacts, we found that observation of climate state, e.g. temperature or precipitation is superior for updating beliefs and supporting decision-making. However, with little conflict among information sources, the strongest evidence would be offered by a combination of at least two informative variables, e.g., temperature and precipitation. The success of adaptive forest management depends on when managers switch to forward-looking management schemes. Thus, robust climate adaptation policies may depend crucially on a better understanding of what factors influence managers' belief in climate change. Copyright © 2013 Elsevier Ltd. All rights reserved.

Heliophysics

NASA Astrophysics Data System (ADS)

Austin, M.; Guhathakurta, M.; Bhattacharjee, A.; Longcope, D. W.; Sojka, J. J.

2010-12-01

Heliophysics Summer Schools. NASA Living With a Star and the University Corporation for Atmospheric Research, Visiting Scientist Programs sponsor the Heliophysics Summer Schools to build the next generation of scientists in this new field. The series of summer schools (commencing 2007) trains graduate students, postdoctoral fellows and university faculty to learn and develop the science of heliophysics as a broad, coherent discipline that reaches in space from the Earth’s troposphere to the depths of the Sun, and in time from the formation of the solar system to the distant future. The first three years of the school resulted in the publication of three textbooks for use at universities worldwide. Subsequent years will both teach generations of students and faculty and develop the complementary materials that support teaching of heliophysics at both graduate and undergraduate levels. Heliophysics is a developing scientific discipline integrating studies of the Sun’s variability, the surrounding heliopsphere, and climate environments. Over the past few centuries, our understanding of how the Sun drives space weather and climate on the Earth and other planets has advanced at an ever-increasing rate. The three volumes, “Plasma Physics of the Local Cosmos”, “Space Storms and Radiation: Causes and Effects” and “Evolving Solar Activity and the Climates of Space and Earth”, edited by Carolus J. Schrijver, Lockheed Martin, and George L. Siscoe, Boston University, integrate such diverse topics for the first time as a coherent intellectual discipline. The books may be ordered through Cambridge University Press, and provide a foundational reference for researchers in heliophysics, astrophysics, plasma physics, space physics, solar physics, aeronomy, space weather, planetary science and climate science. Heliophysics Postdoctoral Program. Hosting/mentoring scientists and postdoctoral fellows are invited to apply to this new program designed to train the next generation of researchers in heliophysics. Two major topics of focus for LWS are the science of space weather and of the Sun-climate connection. Preference is given to applicants whose proposed research addresses one of these two foci; but any research program relevant to LWS is considered. Since the goal of this fellowship program is to train Sun-Earth system researchers, preference is also given to research projects that cross the traditional heliophysics subdomains of the Sun, heliosphere, magnetosphere, and ionosphere/upper atmosphere, as well as Sun-climate investigations. Host institutions and mentoring scientists will play critical roles. Interested hosts may submit information about their research on a central database for this program: http://www.vsp.ucar.edu/Heliophysics/

Pollen-based reconstruction of Holocene climate variability in the Eifel region evaluated with stable isotopes

NASA Astrophysics Data System (ADS)

Kühl, Norbert; Moschen, Robert; Wagner, Stefanie

2010-05-01

Pollen as well as stable isotopes have great potential as climate proxy data. While variability in these proxy data is frequently assumed to reflect climate variability, other factors than climate, including human impact and statistical noise, can often not be excluded as primary cause for the observed variability. Multiproxy studies offer the opportunity to test different drivers by providing different lines of evidence for environmental change such as climate variability and human impact. In this multiproxy study we use pollen and peat humification to evaluate to which extent stable oxygen and carbon isotope series from the peat bog "Dürres Maar" reflect human impact rather than climate variability. For times before strong anthropogenic vegetation change, isotope series from Dürres Maar were used to validate quantitative reconstructions based on pollen. Our study site is the kettle hole peat bog "Dürres Maar" in the Eifel low mountain range, Germany (450m asl), which grew 12m during the last 10,000 years. Pollen was analysed with a sum of at least 1000 terrestrial pollen grains throughout the profile to minimize statistical effects on the reconstructions. A recently developed probabilistic indicator taxa method ("pdf-method") was used for the quantitative climate estimates (January and July temperature) based on pollen. For isotope analysis, attention was given to use monospecific Sphagnum leaves whenever possible, reducing the potential of a species effect and any potential artefact that can originate from selective degradation of different morphological parts of Sphagnum plants (Moschen et al., 2009). Pollen at "Dürres Maar" reflect the variable and partly strong human impact on vegetation during the last 4000 years. Stable isotope time series were apparently not influenced by human impact at this site. This highlights the potential of stable isotope investigations from peat for climatic interpretation, because stable isotope series from lacustrine sediments might strongly react to anthropogenic deforestation, as carbon isotope time series from the adjacent Lake Holzmaar suggest. Reconstructions based on pollen with the pdf-method are robust to the human impact during the last 4000 years, but do not reproduce the fine scale climate variability that can be derived from the stable isotope series (Kühl et al., in press). In contrast, reconstructions on the basis of pollen data show relatively pronounced climate variability (here: January temperature) during the Mid-Holocene, which is known from many other European records. The oxygen isotope time series as available now indicate that at least some of the observed variability indeed reflects climate variability. However, stable carbon isotopes show little concordance. At this stage our results point in the direction that 1) the isotopic composition might reflect a shift in influencing factors during the Holocene, 2) climate trends can robustly be reconstructed with the pdf method and 3) fine scale climate variability can potentially be reconstructed using the pdf-method, given that climate sensitive taxa at their distribution limit are present. The latter two conclusions are of particular importance for the reconstruction of climatic trends and variability of interglacials older than the Holocene, when sites are rare and pollen is often the only suitable proxy in terrestrial records. Kühl, N., Moschen, R., Wagner, S., Brewer, S., Peyron, O., in press. A multiproxy record of Late Holocene natural and anthropogenic environmental change from the Sphagnum peat bog Dürres Maar, Germany: implications for quantitative climate reconstructions based on pollen. J. Quat. Sci., DOI: 10.1002/jqs.1342. Available online. Moschen, R., Kühl, N., Rehberger, I., Lücke, A., 2009. Stable carbon and oxygen isotopes in sub-fossil Sphagnum: Assessment of their applicability for palaeoclimatology. Chemical Geology 259, 262-272.

Short-term climate change impacts on Mara basin hydrology

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Contributions of meteorology to the phenology of cyanobacterial blooms: implications for future climate change.

PubMed

Zhang, Min; Duan, Hongtao; Shi, Xiaoli; Yu, Yang; Kong, Fanxiang

2012-02-01

Cyanobacterial blooms are often a result of eutrophication. Recently, however, their expansion has also been found to be associated with changes in climate. To elucidate the effects of climatic variables on the expansion of cyanobacterial blooms in Taihu, China, we analyzed the relationships between climatic variables and bloom events which were retrieved by satellite images. We then assessed the contribution of each climate variable to the phenology of blooms using multiple regression models. Our study demonstrates that retrieving ecological information from satellite images is meritorious for large-scale and long-term ecological research in freshwater ecosystems. Our results show that the phenological changes of blooms at an inter-annual scale are strongly linked to climate in Taihu during the past 23 yr. Cyanobacterial blooms occur earlier and last longer with the increase of temperature, sunshine hours, and global radiation and the decrease of wind speed. Furthermore, the duration increases when the daily averages of maximum, mean, and minimum temperature each exceed 20.3 °C, 16.7 °C, and 13.7 °C, respectively. Among these factors, sunshine hours and wind speed are the primary contributors to the onset of the blooms, explaining 84.6% of their variability over the past 23 yr. These factors are also good predictors of the variability in the duration of annual blooms and determined 58.9% of the variability in this parameter. Our results indicate that when nutrients are in sufficiently high quantities to sustain the formation of cyanobacterial blooms, climatic variables become crucial in predicting cyanobacterial bloom events. Climate changes should be considered when we evaluate how much the amount of nutrients should be reduced in Taihu for lake management. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

2016-08-01

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

Relationships between northern Adriatic Sea mucilage events and climate variability.

PubMed

Deserti, Marco; Cacciamani, Carlo; Chiggiato, Jacopo; Rinaldi, Attilio; Ferrari, Carla R

2005-12-15

A long term analysis (1865-2002) of meteorological data collected in the Po Valley and Northern Adriatic Basin have been analysed to find possible links between variability in the climatic parameters and the phenomenon of mucilage. Seasonal anomalies of temperature, calculated as spatial mean over the Po Valley area, and anomalies of North Atlantic Oscillation were compared with the historical record of mucilage episodes. Both climatic indices were found to be positively correlated with mucilage events, suggesting a possible relationship between climatic variability and the increased appearance of mucilage aggregates.

Plausible Effect of Weather on Atlantic Meridional Overturning Circulation with a Coupled General Circulation Model

NASA Astrophysics Data System (ADS)

Liu, Zedong; Wan, Xiuquan

2018-04-01

The Atlantic meridional overturning circulation (AMOC) is a vital component of the global ocean circulation and the heat engine of the climate system. Through the use of a coupled general circulation model, this study examines the role of synoptic systems on the AMOC and presents evidence that internally generated high-frequency, synoptic-scale weather variability in the atmosphere could play a significant role in maintaining the overall strength and variability of the AMOC, thereby affecting climate variability and change. Results of a novel coupling technique show that the strength and variability of the AMOC are greatly reduced once the synoptic weather variability is suppressed in the coupled model. The strength and variability of the AMOC are closely linked to deep convection events at high latitudes, which could be strongly affected by the weather variability. Our results imply that synoptic weather systems are important in driving the AMOC and its variability. Thus, interactions between atmospheric weather variability and AMOC may be an important feedback mechanism of the global climate system and need to be taken into consideration in future climate change studies.

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

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

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern US

USGS Publications Warehouse

Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.

2015-01-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

PubMed

Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

2015-11-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Rainfall variability and extremes over southern Africa: assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C.; Kniveton, D.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset.

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.

Investigating the impact of diurnal cycle of SST on the intraseasonal and climate variability

NASA Astrophysics Data System (ADS)

Tseng, W. L.; Hsu, H. H.; Chang, C. W. J.; Keenlyside, N. S.; Lan, Y. Y.; Tsuang, B. J.; Tu, C. Y.

2016-12-01

The diurnal cycle is a prominent feature of our climate system and the most familiar example of externally forced variability. Despite this it remains poorly simulated in state-of-the-art climate models. A particular problem is the diurnal cycle in sea surface temperature (SST), which is a key variable in air-sea heat flux exchange. In most models the diurnal cycle in SST is not well resolved, due to insufficient vertical resolution in the upper ocean mixed-layer and insufficiently frequent ocean-atmosphere coupling. Here, we coupled a 1-dimensional ocean model (SIT) to two atmospheric general circulation model (ECHAM5 and CAM5). In particular, we focus on improving the representations of the diurnal cycle in SST in a climate model, and investigate the role of the diurnal cycle in climate and intraseasonal variability.

Selecting Populations for Non-Analogous Climate Conditions Using Universal Response Functions: The Case of Douglas-Fir in Central Europe.

PubMed

Chakraborty, Debojyoti; Wang, Tongli; Andre, Konrad; Konnert, Monika; Lexer, Manfred J; Matulla, Christoph; Schueler, Silvio

2015-01-01

Identifying populations within tree species potentially adapted to future climatic conditions is an important requirement for reforestation and assisted migration programmes. Such populations can be identified either by empirical response functions based on correlations of quantitative traits with climate variables or by climate envelope models that compare the climate of seed sources and potential growing areas. In the present study, we analyzed the intraspecific variation in climate growth response of Douglas-fir planted within the non-analogous climate conditions of Central and continental Europe. With data from 50 common garden trials, we developed Universal Response Functions (URF) for tree height and mean basal area and compared the growth performance of the selected best performing populations with that of populations identified through a climate envelope approach. Climate variables of the trial location were found to be stronger predictors of growth performance than climate variables of the population origin. Although the precipitation regime of the population sources varied strongly none of the precipitation related climate variables of population origin was found to be significant within the models. Overall, the URFs explained more than 88% of variation in growth performance. Populations identified by the URF models originate from western Cascades and coastal areas of Washington and Oregon and show significantly higher growth performance than populations identified by the climate envelope approach under both current and climate change scenarios. The URFs predict decreasing growth performance at low and middle elevations of the case study area, but increasing growth performance on high elevation sites. Our analysis suggests that population recommendations based on empirical approaches should be preferred and population selections by climate envelope models without considering climatic constrains of growth performance should be carefully appraised before transferring populations to planting locations with novel or dissimilar climate.

Climate Science Service Learning: Learning In Deed

NASA Astrophysics Data System (ADS)

Glass, D. S.

2012-12-01

Many schools require community service yet students work at a food bank or stream clean-up without understanding causes or solutions for the issues they encounter. Since students learn best when they make connections between scientific concepts and real-world issues that interest them, integrated science service learning is an effective and engaging way to teach. My fifth grade students at National Presbyterian School in Washington, DC learned about climate change through a service learning project to help the environment on campus. The curriculum was aligned with science and climate literacy frameworks, "Benchmarks for Science Literacy," from the American Academy for the Advancement of Science (AAAS) and "The Essential Principles of Climate Sciences," from the U.S. Global Change Research Program / U.S. Climate Change Science Program, and was supported through partnership with NOAA's Climate Stewards Education Program. The service learning project was implemented according to seven best practices of service learning: the students initiated the project, researched the issue, developed a plan, worked with the community, shared their results, reflected on the project, and celebrated their accomplishment. My class of 28 fifth-graders researched and experimented with several environmental variables affecting our campus. They brainstormed service projects they could do to help the environment and decided to focus on reducing idling in the school carpool lane. Students researched how automobile exhaust contributes to climate change, causes acid rain, and harms human health. Students designed a system to measure and eventually minimize the exhaust released by cars idling in the carpool line. They crafted a tally sheet to record the number and size of cars and their idling times. They measured temperature and CO2 data, although they did not find that the number of idling cars affected these variables. Students concluded that over an average week with pleasant weather, 35 of 165 cars (22%) which arrived early for carpool idled for a total of 509 minutes, putting out 75 kg of the greenhouse gas, CO2, other pollution, and costing the drivers $34.00 in fuel. Students used this research to develop an anti-idling campaign, which they presented to the whole student body and posted on the school website and e-newsletter. After the campaign, students again evaluated idling in the carpool lane and discovered that there was a slight decrease in the number of idling cars, 20%, down from 22%. Students hoped for greater improvement, but this second survey took place during a hot week when more people may have wanted to air condition their cars. Students also noted that many of the idlers were nannies who may not have heard the anti-idling campaign. On an assessment of climate science knowledge adapted for elementary students from the Yale Project on Climate change, students showed significant improvement. They also became more confident in their knowledge, moving from an average 3 before the project to an average 8.5 afterwards on a 10-point Likert scale. In sum, this project attests that science service learning can make science more concrete and relatable, teaching students not only about the concepts and techniques of science, but its role as a tool for the public good.

Climate mode links to atmospheric carbon monoxide over fire regions

NASA Astrophysics Data System (ADS)

Buchholz, R. R.; Hammerling, D.; Worden, H. M.; Monks, S. A.; Edwards, D. P.; Deeter, M. N.; Emmons, L. K.

2017-12-01

Fire is a strong contributor to variability in atmospheric carbon monoxide (CO), particularly for the Southern Hemisphere and tropics. The magnitude of emissions, such as CO, from biomass burning are related to climate through both the availability and dryness of fuel. We investigate this link between CO and climate using satellite measured CO and climate indices. Interannual variability in satellite-measured CO is determined for the time period covering 2001-2016. We use MOPITT total column retrievals and focus on biomass burning regions of the Southern Hemisphere and tropics. In each of the regions, data driven relationships are determined between CO and climate indices for the climate modes: El Niño Southern Oscillation (ENSO); the Indian Ocean Dipole (IOD); the Tropical Southern Atlantic (TSA); and the Antarctic Oscillation (AAO). Step-wise forward and backward regression combined with the Bayesian Information Criterion is used to select the best predictive model from combinations of lagged indices. We find evidence for the importance of first-order interaction terms of the climate modes when explaining CO variability. Generally, over 50% of the variability can be explained, with over 70% for the Maritime Southeast Asia and North Australasia regions. To help interpret variability, we draw on the chemistry-climate model CAM-chem, which provides information on source contributions and the relative influence of emissions and meteorology. Our results have implications for applications such as air quality forecasting and verifying climate-chemistry models.

Parenting programs during adolescence: Outcomes from universal and targeted interventions offered in real-world settings.

PubMed

Alfredsson, Elin K; Thorvaldsson, Valgeir; Axberg, Ulf; Broberg, Anders G

2018-04-26

The aim of this naturalistic study was to explore short and long-term outcomes of five different group-based parenting programs offered to parents of 10 to 17-year-olds. Three hundred and fifteen parents (277 mothers and 38 fathers) who had enrolled in a parenting program (universal: Active Parenting, COPE; Connect; targeted: COMET; Leadership training for parents of teenagers [LFT]) answered questionnaires at three measurement waves (baseline, post-measurement, and one-year follow-up). The questions concerned parenting style, parental mental health, family climate and adolescent mental health. Results revealed small to moderate changes in almost all outcome variables and in all parenting programs. Overall, parents in COMET reported the largest short and long-term changes. No substantial differences in change were seen between the other programs. The results support the general effectiveness of parenting programs for parents of adolescents. © 2018 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Impacts of climate change and internal climate variability on french rivers streamflows

NASA Astrophysics Data System (ADS)

Dayon, Gildas; Boé, Julien; Martin, Eric

2016-04-01

The assessment of the impacts of climate change often requires to set up long chains of modeling, from the model to estimate the future concentration of greenhouse gases to the impact model. Throughout the modeling chain, sources of uncertainty accumulate making the exploitation of results for the development of adaptation strategies difficult. It is proposed here to assess the impacts of climate change on the hydrological cycle over France and the associated uncertainties. The contribution of the uncertainties from greenhouse gases emission scenario, climate models and internal variability are addressed in this work. To have a large ensemble of climate simulations, the study is based on Global Climate Models (GCM) simulations from the Coupled Model Intercomparison Phase 5 (CMIP5), including several simulations from the same GCM to properly assess uncertainties from internal climate variability. Simulations from the four Radiative Concentration Pathway (RCP) are downscaled with a statistical method developed in a previous study (Dayon et al. 2015). The hydrological system Isba-Modcou is then driven by the downscaling results on a 8 km grid over France. Isba is a land surface model that calculates the energy and water balance and Modcou a hydrogeological model that routes the surface runoff given by Isba. Based on that framework, uncertainties uncertainties from greenhouse gases emission scenario, climate models and climate internal variability are evaluated. Their relative importance is described for the next decades and the end of this century. In a last part, uncertainties due to internal climate variability on streamflows simulated with downscaled GCM and Isba-Modcou are evaluated against observations and hydrological reconstructions on the whole 20th century. Hydrological reconstructions are based on the downscaling of recent atmospheric reanalyses of the 20th century and observations of temperature and precipitation. We show that the multi-decadal variability of streamflows observed in the 20th century is generally weaker in the hydrological simulations done with the historical simulations from climate models. References: Dayon et al. (2015), Transferability in the future climate of a statistical downscaling mehtod for precipitation in France, J. Geophys. Res. Atmos., 120, 1023-1043, doi:10.1002/2014JD022236

Climate Exposure of US National Parks in a New Era of Change

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901–2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change. PMID:24988483

Climate exposure of US national parks in a new era of change.

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

US national parks are challenged by climate and other forms of broad-scale environmental change that operate beyond administrative boundaries and in some instances are occurring at especially rapid rates. Here, we evaluate the climate change exposure of 289 natural resource parks administered by the US National Park Service (NPS), and ask which are presently (past 10 to 30 years) experiencing extreme (<5th percentile or >95th percentile) climates relative to their 1901-2012 historical range of variability (HRV). We consider parks in a landscape context (including surrounding 30 km) and evaluate both mean and inter-annual variation in 25 biologically relevant climate variables related to temperature, precipitation, frost and wet day frequencies, vapor pressure, cloud cover, and seasonality. We also consider sensitivity of findings to the moving time window of analysis (10, 20, and 30 year windows). Results show that parks are overwhelmingly at the extreme warm end of historical temperature distributions and this is true for several variables (e.g., annual mean temperature, minimum temperature of the coldest month, mean temperature of the warmest quarter). Precipitation and other moisture patterns are geographically more heterogeneous across parks and show greater variation among variables. Across climate variables, recent inter-annual variation is generally well within the range of variability observed since 1901. Moving window size has a measureable effect on these estimates, but parks with extreme climates also tend to exhibit low sensitivity to the time window of analysis. We highlight particular parks that illustrate different extremes and may facilitate understanding responses of park resources to ongoing climate change. We conclude with discussion of how results relate to anticipated future changes in climate, as well as how they can inform NPS and neighboring land management and planning in a new era of change.

Using non-systematic surveys to investigate effects of regional climate variability on Australasian gannets in the Hauraki Gulf, New Zealand

NASA Astrophysics Data System (ADS)

Srinivasan, Mridula; Dassis, Mariela; Benn, Emily; Stockin, Karen A.; Martinez, Emmanuelle; Machovsky-Capuska, Gabriel E.

2015-05-01

Few studies have investigated regional and natural climate variability on seabird populations using ocean reanalysis datasets (e.g. Simple Ocean Data Assimilation (SODA)) that integrate atmospheric information to supplement ocean observations and provide improved estimates of ocean conditions. Herein we use a non-systematic dataset on Australasian gannets (Morus serrator) from 2001 to 2009 to identify potential connections between Gannet Sightings Per Unit Effort (GSPUE) and climate and oceanographic variability in a region of known importance for breeding seabirds, the Hauraki Gulf (HG), New Zealand. While no statistically significant relationships between GSPUE and global climate indices were determined, there was a significant correlation between GSPUE and regional SST anomaly for HG. Also, there appears to be a strong link between global climate indices and regional climate in the HG. Further, based on cross-correlation function coefficients and lagged multiple regression models, we identified potential leading and lagging climate variables, and climate variables but with limited predictive capacity in forecasting future GSPUE. Despite significant inter-annual variability and marginally cooler SSTs since 2001, gannet sightings appear to be increasing. We hypothesize that at present underlying physical changes in the marine ecosystem may be insufficient to affect supply of preferred gannet main prey (pilchard Sardinops spp.), which tolerate a wide thermal range. Our study showcases the potential scientific value of lengthy non-systematic data streams and when designed properly (i.e., contain abundance, flock size, and spatial data), can yield useful information in climate impact studies on seabirds and other marine fauna. Such information can be invaluable for enhancing conservation measures for protected species in fiscally constrained research environments.

Building Training Curricula for Accelerating the Use of NOAA Climate Products and Tools

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Meyers, J. C.; Stevermer, A.; Abshire, W. E.; Beller-Simms, N.; Herring, D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) plays a leading role in U.S. intergovernmental efforts on the Climate Data Initiative and the Climate Resilience Toolkit (CRT). CRT (http://toolkit.climate.gov/) is a valuable resource that provides tools, information, and subject matter expertise to decision makers in various sectors, such as agriculture, water resources and transportation, to help them build resilience to our changing climate. In order to make best use of the toolkit and all the resources within it, a training component is critical. The training section helps building users' understanding of the data, science, and impacts of climate variability and change. CRT identifies five steps in building resilience that includes use of appropriate tools to support decision makers depending on their needs. One tool that can be potentially integrated into CRT is NOAA's Local Climate Analysis Tool (LCAT), which provides access to trusted NOAA data and scientifically-sound analysis techniques for doing regional and local climate studies on climate variability and climate change. However, in order for LCAT to be used effectively, we have found an iterative learning approach using specific examples to train users. For example, for LCAT application in analysis of water resources, we use existing CRT case studies for Arizona and Florida water supply users. The Florida example demonstrates primary sensitivity to climate variability impacts, whereas the Arizona example takes into account longer- term climate change. The types of analyses included in LCAT are time series analysis of local climate and the estimated rate of change in the local climate. It also provides a composite analysis to evaluate the relationship between local climate and climate variability events such as El Niño Southern Oscillation, the Pacific North American Index, and other modes of climate variability. This paper will describe the development of a training module for use of LCAT and its integration into CRT. An iterative approach was used that incorporates specific examples of decision making while working with subject matter experts within the water supply community. The recommended strategy is to use a "stepping stone" learning structure to build users knowledge of best practices for use of LCAT.

Climate change and occurrence of diarrheal diseases: evolving facts from Nepal.

PubMed

Bhandari, G P; Gurung, S; Dhimal, M; Bhusal, C L

2012-09-01

Climate change is becoming huge threat to health especially for those from developing countries. Diarrhea as one of the major diseases linked with changing climate. This study has been carried out to assess the relationship between climatic variables, and malaria and to find out the range of non-climatic factors that can confound the relationship of climate change and human health. It is a Retrospective study where data of past ten years relating to climate and disease (diarrhea) variable were analyzed. The study conducted trend analysis based on correlation. The climate related data were obtained from Department of Hydrology and Meteorology. Time Series analysis was also being conducted. The trend of number of yearly cases of diarrhea has been increasing from 1998 to 2001 after which the cases remain constant till 2006.The climate types in Jhapa vary from humid to per-humid based on the moisture index and Mega-thermal based on thermal efficiency. The mean annual temperature is increasing at an average of 0.04 °C/year with maximum temperature increasing faster than the minimum temperature. The annual total rainfall of Jhapa is decreasing at an average rate of -7.1 mm/year. Statistically significant correlation between diarrheal cases occurrence and temperature and rainfall has been observed. However, climate variables were not the significant predictors of diarrheal occurrence. The association among climate variables and diarrheal disease occurrence cannot be neglected which has been showed by this study. Further prospective longitudinal study adjusting influence of non-climatic factors is recommended.

7 CFR 2.74 - Director, Climate Change Program Office.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 1 2014-01-01 2014-01-01 false Director, Climate Change Program Office. 2.74 Section... Director, Climate Change Program Office. (a) Delegations. Pursuant to § 2.29(a)(12), the following delegations of authority are made by the Chief Economist to the Director, Climate Change Program Office: (1...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

NASA Astrophysics Data System (ADS)

Tsai, C. Y.; Forest, C. E.; Pollard, D.

2017-12-01

The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

Risky business: The impact of climate and climate variability on human population dynamics in Western Europe during the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Burke, Ariane; Kageyama, Masa; Latombe, Guilllaume; Fasel, Marc; Vrac, Mathieu; Ramstein, Gilles; James, Patrick M. A.

2017-05-01

The extent to which climate change has affected the course of human evolution is an enduring question. The ability to maintain spatially extensive social networks and a fluid social structure allows human foragers to ;map onto; the landscape, mitigating the impact of ecological risk and conferring resilience. But what are the limits of resilience and to which environmental variables are foraging populations sensitive? We address this question by testing the impact of a suite of environmental variables, including climate variability, on the distribution of human populations in Western Europe during the Last Glacial Maximum (LGM). Climate variability affects the distribution of plant and animal resources unpredictably, creating an element of risk for foragers for whom mobility comes at a cost. We produce a model of habitat suitability that allows us to generate predictions about the probable distribution of human populations and discuss the implications of these predictions for the structure of human populations and their social and cultural evolution during the LGM.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

NASA Technical Reports Server (NTRS)

Markert, Kel N.; Griffin, Robert; Limaye, Ashutosh S.; McNider, Richard T.; Anderson, Eric R.

2016-01-01

The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

Family climates: family factors specific to disturbed eating and bulimia nervosa.

PubMed

Laliberté, M; Boland, F J; Leichner, P

1999-09-01

More than a decade of research has characterized the families of individuals with bulimia and bulimia anorexia (Anorexia Nervosa, Binge/Purging Type) as less expressive, less cohesive, and experiencing more conflicts than normal control families. This two-part study investigated variables believed more directly related to disturbed eating and bulimia as contributing to a "family climate for eating disorders." In Study 1. a nonclinical sample of 324 women who had just left home for college and a sample of 121 mothers evaluated their families. Principal-components analyses revealed the same factor structure for both students and mothers, with Family Body Satisfaction, Family Social Appearance Orientation, and Family Achievement Emphasis loading together, representing the hypothesized family climate for eating disorders: the remaining variables loaded with the more traditional family process variables (conflict, cohesion, expressiveness), representing a more general family dysfunction. As predicted, the family climate for eating disorders factor score was a more powerful predictor of disturbed eating. Study 2 extended these findings into a clin ical population, examining whether the family climate for eating disorders variables would distinguish individuals with bulimia from both depressed and healthy controls. Groups of eating-disordered patients (n = 40) and depressed (n = 17) and healthy (n = 27) controls completed family measures. The eating-disordered group scored significantly higher on family climate variables than control groups. Family process variables distinguished clinical groups (depressed and eating disordered) from healthy controls, but not from one another. Controlling for depression removed group differences on family process variables, but family climate variables continued to distinguish the eating-disordered group from both control groups. Indications for further research are discussed.

Social vulnerability and climate variability in southern Brazil: a TerraPop case study

NASA Astrophysics Data System (ADS)

Adamo, S. B.; Fitch, C. A.; Kugler, T.; Doxsey-Whitfield, E.

2014-12-01

Climate variability is an inherent characteristic of the Earth's climate, including but not limited to climate change. It affects and impacts human society in different ways, depending on the underlying socioeconomic vulnerability of specific places, social groups, households and individuals. This differential vulnerability presents spatial and temporal variations, and is rooted in historical patterns of development and relations between human and ecological systems. This study aims to assess the impact of climate variability on livelihoods and well-being, as well as their changes over time and across space, and for rural and urban populations. The geographic focus is Southern Brazil-the states of Parana, Santa Catarina and Rio Grande do Sul-- and the objectives include (a) to identify and map critical areas or hotspots of exposure to climate variability (temperature and precipitation), and (b) to identify internal variation or differential vulnerability within these areas and its evolution over time (1980-2010), using newly available integrated data from the Terra Populus project. These data include geo-referenced climate and agricultural data, and data describing demographic and socioeconomic characteristics of individuals, households and places.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

PubMed Central

Porfirio, Luciana L.; Harris, Rebecca M. B.; Lefroy, Edward C.; Hugh, Sonia; Gould, Susan F.; Lee, Greg; Bindoff, Nathaniel L.; Mackey, Brendan

2014-01-01

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models. PMID:25420020

Why inputs matter: Selection of climatic variables for species distribution modelling in the Himalayan region

NASA Astrophysics Data System (ADS)

Bobrowski, Maria; Schickhoff, Udo

2017-04-01

Betula utilis is a major constituent of alpine treeline ecotones in the western and central Himalayan region. The objective of this study is to provide first time analysis of the potential distribution of Betula utilis in the subalpine and alpine belts of the Himalayan region using species distribution modelling. Using Generalized Linear Models (GLM) we aim at examining climatic factors controlling the species distribution under current climate conditions. Furthermore we evaluate the prediction ability of climate data derived from different statistical methods. GLMs were created using least correlated bioclimatic variables derived from two different climate models: 1) interpolated climate data (i.e. Worldclim, Hijmans et al., 2005) and 2) quasi-mechanistical statistical downscaling (i.e. Chelsa; Karger et al., 2016). Model accuracy was evaluated by the ability to predict the potential species distribution range. We found that models based on variables of Chelsa climate data had higher predictive power, whereas models using Worldclim climate data consistently overpredicted the potential suitable habitat for Betula utilis. Although climatic variables of Worldclim are widely used in modelling species distribution, our results suggest to treat them with caution when remote regions like the Himalayan mountains are in focus. Unmindful usage of climatic variables for species distribution models potentially cause misleading projections and may lead to wrong implications and recommendations for nature conservation. References: Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. & Jarvis, A. (2005) Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965-1978. Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N., Linder, H.P. & Kessler, M. (2016) Climatologies at high resolution for the earth land surface areas. arXiv:1607.00217 [physics].

Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

NASA Astrophysics Data System (ADS)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

The rise of the mediocre forest: why chronically stressed trees may better survive extreme episodic climate variability

Treesearch

Steven G. McNulty; Johnny L. Boggs; Ge Sun

2014-01-01

Anthropogenic climate change is a relatively new phenomenon, largely occurring over the past 150 years, and much of the discussion on climate change impacts to forests has focused on long-term shifts in temperature and precipitation. However, individual trees respond to the much shorter impacts of climate variability. Historically, fast growing, fully canopied, non-...

Climatic influences on fire regimes in montane forests of the southern Cascades, California, USA

Treesearch

A. H. Taylor; V. Trouet; C. N. Skinner

2008-01-01

he relationship between climate variability and fire extent was examined in montane and upper montane forests in the southern Cascades. Fire occurrence and extent were reconstructed for seven sites and related to measures of reconstructed climate for the period 1700 to 1900. The climate variables included the Palmer Drought Severity Index (PDSI), summer temperature (...

Climate signals derived from cell anatomy of Scots pine in NE Germany.

PubMed

Liang, Wei; Heinrich, Ingo; Simard, Sonia; Helle, Gerhard; Liñán, Isabel Dorado; Heinken, Thilo

2013-08-01

Tree-ring chronologies of Pinus sylvestris L. from latitudinal and altitudinal limits of the species distribution have been widely used for climate reconstructions, but there are many sites within the temperate climate zone, as is the case in northeastern Germany, at which there is little evidence of a clear climate signal in the chronologies. In this study, we developed long chronologies of several cell structure variables (e.g., average lumen area and cell wall thickness) from P. sylvestris growing in northeastern Germany and investigated the influence of climate on ring widths and cell structure variables. We found significant correlations between cell structure variables and temperature, and between tree-ring width and relative humidity and vapor pressure, respectively, enabling the development of robust reconstructions from temperate sites that have not yet been realized. Moreover, it has been shown that it may not be necessary to detrend chronologies of cell structure variables and thus low-frequency climate signals may be retrieved from longer cell structure chronologies. The relatively extensive resource of archaeological material of P. sylvestris covering approximately the last millennium may now be useful for climate reconstructions in northeastern Germany and other sites in the temperate climate zone.

Impacts of Climate Trends and Variability on Livestock Production in Brazil

NASA Astrophysics Data System (ADS)

Cohn, A.; Munger, J.; Gibbs, H.

2015-12-01

Cattle systems of Brazil are of major economic and environmental importance. They occupy ¼ of the land surface of the country, account for over 15 billion USD of annual revenue through the sale of beef, leather, and milk, are closely associated with deforestation, and have been projected to substantially grow in the coming decades. Sustainable intensification of production in the sector could help to limit environmental harm from increased production, but productivity growth could be inhibited by climate change. Gauging the potential future impacts of climate change on the Brazilian livestock sector can be aided by examining past evidence of the link between climate and cattle production and productivity. We use statistical techniques to investigate the contribution of climate variability and climate change to variability in cattle system output in Brazil's municipalities over the period 1974 to 2013. We find significant impacts of both temperature and precipitation variability and temperature trends on municipality-level exports and the production of both milk and beef. Pasture productivity, represented by a vegetation index, also varies significantly with climate shocks. In some regions, losses from exposure to climate trends were of comparable magnitude to technology and/or market-driven productivity gains over the study period.

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Sometimes processes don't matter: the general effect of short term climate variability on erosional systems.

NASA Astrophysics Data System (ADS)

Deal, Eric; Braun, Jean

2017-04-01

Climatic forcing undoubtedly plays an important role in shaping the Earth's surface. However, precisely how climate affects erosion rates, landscape morphology and the sedimentary record is highly debated. Recently there has been a focus on the influence of short-term variability in rainfall and river discharge on the relationship between climate and erosion rates. Here, we present a simple probabilistic argument, backed by modelling, that demonstrates that the way the Earth's surface responds to short-term climatic forcing variability is primarily determined by the existence and magnitude of erosional thresholds. We find that it is the ratio between the threshold magnitude and the mean magnitude of climatic forcing that determines whether variability matters or not and in which way. This is a fundamental result that applies regardless of the nature of the erosional process. This means, for example, that we can understand the role that discharge variability plays in determining fluvial erosion efficiency despite doubts about the processes involved in fluvial erosion. We can use this finding to reproduce the main conclusions of previous studies on the role of discharge variability in determining long-term fluvial erosion efficiency. Many aspects of the landscape known to influence discharge variability are affected by human activity, such as land use and river damming. Another important control on discharge variability, rainfall intensity, is also expected to increase with warmer temperatures. Among many other implications, our findings help provide a general framework to understand and predict the response of the Earth's surface to changes in mean and variability of rainfall and river discharge associated with the anthropogenic activity. In addition, the process independent nature of our findings suggest that previous work on river discharge variability and erosion thresholds can be applied to other erosional systems.

Novel Modeling Tools for Propagating Climate Change Variability and Uncertainty into Hydrodynamic Forecasts

EPA Science Inventory

Understanding impacts of climate change on hydrodynamic processes and ecosystem response within the Great Lakes is an important and challenging task. Variability in future climate conditions, uncertainty in rainfall-runoff model forecasts, the potential for land use change, and t...

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

PubMed

Merrill, Scott C; Peairs, Frank B

2017-02-01

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

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

PubMed

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Solar radiation increases suicide rate after adjusting for other climate factors in South Korea.

PubMed

Jee, Hee-Jung; Cho, Chul-Hyun; Lee, Yu Jin; Choi, Nari; An, Hyonggin; Lee, Heon-Jeong

2017-03-01

Previous studies have indicated that suicide rates have significant seasonal variations. There is seasonal discordance between temperature and solar radiation due to the monsoon season in South Korea. We investigated the seasonality of suicide and assessed its association with climate variables in South Korea. Suicide rates were obtained from the National Statistical Office of South Korea, and climatic data were obtained from the Korea Meteorological Administration for the period of 1992-2010. We conducted analyses using a generalized additive model (GAM). First, we explored the seasonality of suicide and climate variables such as mean temperature, daily temperature range, solar radiation, and relative humidity. Next, we identified confounding climate variables associated with suicide rate. To estimate the adjusted effect of solar radiation on the suicide rate, we investigated the confounding variables using a multivariable GAM. Suicide rate showed seasonality with a pattern similar to that of solar radiation. We found that the suicide rate increased 1.008 times when solar radiation increased by 1 MJ/m 2 after adjusting for other confounding climate factors (P < 0.001). Solar radiation has a significant linear relationship with suicide after adjusting for region, other climate variables, and time trends. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

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

Pollen-based continental climate reconstructions at 6 and 21 ka: A global synthesis

USGS Publications Warehouse

Bartlein, P.J.; Harrison, S.P.; Brewer, Sandra; Connor, S.; Davis, B.A.S.; Gajewski, K.; Guiot, J.; Harrison-Prentice, T. I.; Henderson, A.; Peyron, O.; Prentice, I.C.; Scholze, M.; Seppa, H.; Shuman, B.; Sugita, S.; Thompson, R.S.; Viau, A.E.; Williams, J.; Wu, H.

2011-01-01

Subfossil pollen and plant macrofossil data derived from 14C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance. ?? 2010 The Author(s).

Impact of Holocene climate variability on Arctic vegetation

NASA Astrophysics Data System (ADS)

Gajewski, K.

2015-10-01

This paper summarizes current knowledge about the postglacial history of the vegetation of the Canadian Arctic Archipelago (CAA) and Greenland. Available pollen data were used to understand the initial migration of taxa across the Arctic, how the plant biodiversity responded to Holocene climate variability, and how past climate variability affected primary production of the vegetation. Current evidence suggests that most of the flora arrived in the area during the Holocene from Europe or refugia south or west of the region immediately after local deglaciation, indicating rapid dispersal of propagules to the region from distant sources. There is some evidence of shrub species arriving later in Greenland, but it is not clear if this is dispersal limited or a response to past climates. Subsequent climate variability had little effect on biodiversity across the CAA, with some evidence of local extinctions in areas of Greenland in the late Holocene. The most significant impact of climate changes is on vegetation density and/or plant production.

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

NASA Astrophysics Data System (ADS)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

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

PubMed

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

2008-12-01

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

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Temporal changes in climatic variables and their impact on crop yields in southwestern China

NASA Astrophysics Data System (ADS)

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P < 0.05). Increased sunshine hours were observed during the oilseed rape growth period ( P < 0.05). Rainy days decreased slightly in annual and oilseed rape growth time series ( P < 0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall ( P < 0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity ( P < 0.01). Tobacco yield increased with mean temperature ( P < 0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Temporal changes in climatic variables and their impact on crop yields in southwestern China.

PubMed

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P<0.05). Increased sunshine hours were observed during the oilseed rape growth period (P<0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P<0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P<0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P<0.01). Tobacco yield increased with mean temperature (P<0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Orbital Sciences Pegasus XL Mate

NASA Image and Video Library

2007-02-28

At Vandenberg Air Force Base in California, the three stages of the Orbital Sciences Pegasus XL are being mated for the launch of NASA's Aeronomy of Ice in the Mesosphere, or AIM, spacecraft. AIM is the seventh Small Explorers mission under NASA's Explorer Program. The program provides frequent flight opportunities for world-class scientific investigations from space within heliophysics and astrophysics. The AIM spacecraft will fly three instruments designed to study polar mesospheric 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

2007-03-10

Inside a clean room at Vandenberg Air Force Base in California, NASA's Aeronomy of Ice in the Mesosphere, or AIM, spacecraft is weighed. AIM is the seventh Small Explorers mission under NASA's Explorer Program. The program provides frequent flight opportunities for world-class scientific investigations from space within heliophysics and astrophysics. The AIM spacecraft will fly three instruments designed to study polar mesospheric 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 Arrival

NASA Image and Video Library

2007-03-10

NASA's Aeronomy of Ice in the Mesosphere, or AIM, spacecraft arrives in a clean room at Vandenberg Air Force Base in California. AIM is the seventh Small Explorers mission under NASA's Explorer Program. The program provides frequent flight opportunities for world-class scientific investigations from space within heliophysics and astrophysics. The AIM spacecraft will fly three instruments designed to study polar mesospheric 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.

A New NOAA Research Initiative on the Seasonal Prediction of U.S. Coastal High Water Levels

NASA Astrophysics Data System (ADS)

Mariotti, A.; Archambault, H. M.; Barrie, D.; Huang, J.

2017-12-01

A crucial part of NOAA's service mission is to make U.S. communities more resilient to rises in coastal sea level, which on a seasonal timescale may increase the threat for nuisance ("sunny day") flooding, as well as enhance the severity of storm surge events. Over a season, variability in climate or ocean dynamics, in combination with longer-term trends, can influence coastal sea level in a way that is potentially predictable. To leverage these emerging scientific findings, the Climate Program Office's Modeling, Analysis, Predictions, and Projections Program, in partnership with the National Marine Fisheries Service, has funded a set of three-year projects starting in FY 2017 to help develop NOAA's capability to produce skillful seasonal (i.e, 2-9 month) predictions of coastal high water levels as well as changing living marine resources. This presentation will describe the goals, scope and intended activities of this research initiative and its coordination via a new MAPP Ocean Prediction Task Force.

Local air temperature tolerance: a sensible basis for estimating climate variability

NASA Astrophysics Data System (ADS)

Kärner, Olavi; Post, Piia

2016-11-01

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.

Investigating the Contribution of Climate Variables to Estimates of Net Primary Productivity in a Tropical Ecosystem in India

NASA Astrophysics Data System (ADS)

Tripathi, P.; Behera, M. D.; Behera, S. K.; Sahu, N.

2016-12-01

Investigating the impact of climate variables on net primary productivity is crucial to evaluate the ecosystem health and the status of forest type response to climate change. The objective of this paper is (1) to analyze the spatio-temporal pattern of net primary productivity (NPP) in a tropical forest ecosystem situated along the Himalayan foothills in India and (2) to investigate the continuous and delayed effects of climatic variables. Weapplied simple Monteith equation based Light use efficiency model for two dominant plant functional types; sal (Shorea robusta) forest and teak (Tectona grandis) plantation to estimate the NPP for a decadal period from 2001 to 2010. The impact of climate variables on NPP for these 10 years was seen by applying two correlation analyses; generalized linear modelling (GLM) and time lag correlation approach.The impact of different climate variables was observed to vary throughout the study period.A decline in mean NPP during 2002-2003, 2005 and 2008 to 2010 could be attributed to drought, increased vapour pressure deficit, and decreased humidity and solar radiation. In time lag correlation analysis, precipitation and humidity were observed to be the major variables affecting NPP; whereas combination of temperature, humidity and VPD showed dominant effect on NPP in GLM. Shorea robusta forest showed slightly higher NPP than that of Tectona grandis plantation throughout the study period. Highest decrease in NPP was observed during 2010,pertaining to lower solar radiation, humidity and precipitation along with increased VPD.Higher gains in NPP by sal during all years indicates their better adaptability to climate compared to teak. Contribution of different climatic variables through some link process is revealed in statistical analysis clearly indicates the co-dominance of all the variables in explaining NPP. Lacking of site specific meteorological observations and microclimate put constraint on broad level analyses.

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.

Leveraging federal science data and tools to help communities & business build climate resilience

NASA Astrophysics Data System (ADS)

Herring, D.

2016-12-01

Decision-makers in every sector and region of the United States are seeking actionable science-based information to help them understand and manage their climate-related risks. Translating data, tools and information from the domain of climate science to the domains of municipal, social, and economic decision-making raises complex questions—e.g., how to communicate causes and impacts of climate variability and change; how to show projections of plausible future climate scenarios; how to characterize and quantify vulnerabilities, risks, and opportunities facing communities and businesses; and how to make and implement "win-win" adaptation plans. These are the types of challenges being addressed by a public-private partnership of federal agencies, academic institutions, non-governmental organizations, and private businesses that are contributing to the development of the U.S. Climate Resilience Toolkit (toolkit.climate.gov), a new website designed to help people build resilience to extreme events caused by both natural climate variability and long-term climate change. The site's Climate Explorer is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Of course, climate change is only one of many variables affecting decisions about the future so the Toolkit also ties climate information to a wide range of other relevant tools and information to help users to explore their vulnerabilities and risks. In this session, we will describe recent enhancements to the Toolkit, lessons learned from user engagements, and evidence that our approach of coupling scientific information with actionable decision-making processes is helping Americans build resilience to climate-related impacts.

"Climate Matters Documoments": Enabling Regionally-Specific Climate Awareness

NASA Astrophysics Data System (ADS)

Keener, V. W.; Finucane, M.

2012-12-01

The Pacific Regional Integrated Sciences & Assessments (RISA) is a multidisciplinary program that enhances the ability of Pacific Island communities to understand, plan for, and adapt to climate-induced change. Using both social and physical science research methods, the Pacific RISA engages a network of regional decision-makers and stakeholders to help solve climate-related issues. Pacific RISA has a broad audience of local and regional decision-makers (i.e. natural resource managers, community planners, state and federal government agencies) and stakeholders (i.e. farmers and ranchers, fishermen, community and native islander groups). The RISA program engages with this audience through a mixed-method approach of two-way communication, including one-on-one interviews, workshops, consensus discussions and public presentations that allow us to tailor our efforts to the needs of specific stakeholders. A recent Pacific RISA project was the creation and production of four short, educational "documoment" videos that explore the different ways in which climate change in Hawaii affects stakeholders from different sectors. The documoments, generally titled "Climate Matters", start with a quote about why climate matters to each stakeholder: a rancher, a coastal hotel owner, the manager of a landfill, and the local branch of the National Weather Service. The narratives then have each stakeholder discussing how climate impacts their professional and personal lives, and describing the types of climate change they have experienced in the islands. Each video ends with a technical fact about how different climate variables in Hawaii (sea level, precipitation, ENSO) have actually changed within the last century of observational data. Freely available on www.PacificRISA.org, the Documoments have been viewed over 350 times, and have inspired similar video projects and received positive attention from different audiences of stakeholders and scientists. In other assessment work the Pacific RISA has done, we found that many stakeholders who regularly make climate sensitive decisions do not always realize it. By viewing videos like the Climate Matters Documoments, it may help a wide variety of community stakeholders and natural resource decision makers realize the myriad ways in which climate change affects their communities and jobs. In addition, when viewed outside of the Pacific Islands region, the different stories told in the Documoments help foster a greater understanding of the unique climate-related issues faced within the Hawaiian Islands.

Predicting phenology by integrating ecology, evolution and climate science

USGS Publications Warehouse

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

2011-01-01

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

Transferability of optimally-selected climate models in the quantification of climate change impacts on hydrology

NASA Astrophysics Data System (ADS)

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

2016-11-01

Given the ever increasing number of climate change simulations being carried out, it has become impractical to use all of them to cover the uncertainty of climate change impacts. Various methods have been proposed to optimally select subsets of a large ensemble of climate simulations for impact studies. However, the behaviour of optimally-selected subsets of climate simulations for climate change impacts is unknown, since the transfer process from climate projections to the impact study world is usually highly non-linear. Consequently, this study investigates the transferability of optimally-selected subsets of climate simulations in the case of hydrological impacts. Two different methods were used for the optimal selection of subsets of climate scenarios, and both were found to be capable of adequately representing the spread of selected climate model variables contained in the original large ensemble. However, in both cases, the optimal subsets had limited transferability to hydrological impacts. To capture a similar variability in the impact model world, many more simulations have to be used than those that are needed to simply cover variability from the climate model variables' perspective. Overall, both optimal subset selection methods were better than random selection when small subsets were selected from a large ensemble for impact studies. However, as the number of selected simulations increased, random selection often performed better than the two optimal methods. To ensure adequate uncertainty coverage, the results of this study imply that selecting as many climate change simulations as possible is the best avenue. Where this was not possible, the two optimal methods were found to perform adequately.

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

PubMed Central

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

2014-01-01

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

Association of genetic and phenotypic variability with geography and climate in three southern California oaks.

PubMed

Riordan, Erin C; Gugger, Paul F; Ortego, Joaquín; Smith, Carrie; Gaddis, Keith; Thompson, Pam; Sork, Victoria L

2016-01-01

Geography and climate shape the distribution of organisms, their genotypes, and their phenotypes. To understand historical and future evolutionary and ecological responses to climate, we compared the association of geography and climate of three oak species (Quercus engelmannii, Quercus berberidifolia, and Quercus cornelius-mulleri) in an environmentally heterogeneous region of southern California at three organizational levels: regional species distributions, genetic variation, and phenotypic variation. We identified climatic variables influencing regional distribution patterns using species distribution models (SDMs), and then tested whether those individual variables are important in shaping genetic (microsatellite) and phenotypic (leaf morphology) variation. We estimated the relative contributions of geography and climate using multivariate redundancy analyses (RDA) with variance partitioning. The modeled distribution of each species was influenced by climate differently. Our analysis of genetic variation using RDA identified small but significant associations between genetic variation with climate and geography in Q. engelmannii and Q. cornelius-mulleri, but not in Q. berberidifolia, and climate explained more of the variation. Our analysis of phenotypic variation in Q. engelmannii indicated that climate had more impact than geography, but not in Q. berberidifolia. Throughout our analyses, we did not find a consistent pattern in effects of individual climatic variables. Our comparative analysis illustrates that climate influences tree response at all organizational levels, but the important climate factors vary depending on the level and on the species. Because of these species-specific and level-specific responses, today's sympatric species are unlikely to have similar distributions in the future. © 2016 Botanical Society of America.

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

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.

Climate and health: observation and modeling of malaria in the Ferlo (Senegal).

PubMed

Diouf, Ibrahima; Deme, Abdoulaye; Ndione, Jacques-André; Gaye, Amadou Thierno; Rodríguez-Fonseca, Belén; Cissé, Moustapha

2013-01-01

The aim of this work, undertaken in the framework of QWeCI (Quantifying Weather and Climate Impacts on health in the developing countries) project, is to study how climate variability could influence malaria seasonal incidence. It will also assess the evolution of vector-borne diseases such as malaria by simulation analysis of climate models according to various climate scenarios for the next years. Climate variability seems to be determinant for the risk of malaria development (Freeman and Bradley, 1996 [1], Lindsay and Birley, 1996 [2], Kuhn et al., 2005 [3]). Climate can impact on the epidemiology of malaria by several mechanisms, directly, via the development rates and survival of both pathogens and vectors, and indirectly, through changes in vegetation and land surface characteristics such as the variability of breeding sites like ponds. Copyright © 2013 Académie des sciences. Published by Elsevier SAS. All rights reserved.

GPM Mission, its Scientific Agenda, and its Ground Validation Program

NASA Technical Reports Server (NTRS)

Smith Eric A.

2004-01-01

The GPM mission is currently planned for start in the late 2010 time frame. From the perspective of NASA s Earth Science Enterprise (ESE) and within the framework of ESE's global water and energy cycle (GWEC) research program, its main scientific goal is to help answer pressing scientific problems concerning how global and regional water cycle processes and precipitation fluctuations and trends influence the variability intrinsic to climate, weather, and hydrology. These problems cut across a hierarchy of space-time scales and include improving understanding of climate-water cycle interactions, developing better techniques for incorporating satellite precipitation measurements into weather and climate predictions, and demonstrating that more accurate, more complete, and better sampled observations of precipitation and other water budget variables used as inputs can improve the ability of prognostic hydrometeorological models in the prediction of hazardous flood-producing storms, seasonal flood/draught conditions, and fresh water resource stores. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar (DPR) and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination (GMI). The other constellation members will include a combination of new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve 3-hour sampling at any spot on the globe -- continuously. The constellation s orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of calibration-quality rainrates, plus cloud-precipitation microphysical processes, to be used in conjunction with more basic rain retrievals from the other constellation satellites to ensure bias-free constellation coverage.

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.

The Impact of Climatological Variables on Kelp Canopy Area in the Santa Barbara Channel

NASA Astrophysics Data System (ADS)

Zigner, K.; Bausell, J.; Kudela, R. M.

2015-12-01

Kelp canopy area (KCA), a proxy for kelp forest health, has important implications for small and large-scale processes pertaining to fisheries, near shore currents, and marine ecosystems. As part of the NASA Airborne Science Research Program (SARP), this study examines the impact of ocean chemistry and climatological variables on KCA in the Santa Barbara Channel through time series analysis. El Niño Southern Oscillation (ENSO), North Pacific Gyre Oscillation (NPGO), North Pacific Oscillation (NPO), and upwelling indices as well as sea surface temperature (SST), salinity, nitrate, and chlorophyll-a concentrations taken within the Santa Barbara channel (1990-2014) were acquired from the Climate Prediction Center (CPC), California Cooperative Oceanic Fisheries Investigation (CalCOFI), and Di Lorenzo's NPGO websites. These data were then averaged for winter (November-January) and summer (May-August) seasons and compared to KCA measurements derived from Landsat images via unsupervised classification. Regression, cumulative sum tests, and cross-correlation coefficients revealed a two year lag between KCA and the NPGO, indicating the presence of an additional factor driving both variables. Further analyses suggests that the NPO may be this driving factor, as indicated by the correlation (lag 0) with KCA. Comparing relationships between kelp and other variables over various time periods supports the acceleration of the NPGO and other variables in more recent years. Exploring relationships between KCA, NPGO, and NPO may provide insight into potential impacts of climate change on coastal marine ecosystems.

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Impact of climate variability on vector-borne disease transmission

USDA-ARS?s Scientific Manuscript database

We will discuss the impact of climate variability on vector borne diseases and demonstrate that global climate teleconnections can be used to anticipate and forecast, in the case of Rift Valley fever, epidemics and epizootics. In this context we will examine significant worldwide weather anomalies t...

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas

NASA Astrophysics Data System (ADS)

Moore, B., III

2014-12-01

Climate Science Centers: An "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. Berrien Moore III (University of Oklahoma) The South Central Climate Science Center (CSC) is one of eight regional centers established by the Department of the Interior (DoI) under Secretarial Order 3289 to address the impacts of climate change on America's water, land, and other natural and cultural resources. Under DoI leadership and funding, these CSCs will provide scientific information tools and techniques to study impacts of climate change synthesize and integrate climate change impact data develop tools that the DoI managers and partners can use when managing the DOI's land, water, fish and wildlife, and cultural heritage resources (emphasis added) The network of Climate Science Centers will provide decision makers with the science, tools, and information they need to address the impacts of climate variability and change on their areas of responsibility. Note from Webster, a tool is a device for doing work; it makes outcomes more realizable and more cost effective, and, in a word, better. Prior to the existence of CSCs, the university and federal scientific world certainly contained a large "set" of scientists with considerable strength in the physical, biological, natural, and social sciences to address the complexities and interdisciplinary nature of the challenges in the areas of climate variability, change, impacts, and adaptation. However, this set of scientists were hardly an integrated community let alone a focused team, but rather a collection of distinguished researchers, educators, and practitioners that were working with disparate though at times linked objectives, and they were rarely aligning themselves formally to an overarching strategic pathway. In addition, data, models, research results, tools, and products were generally somewhat "disconnected" from the broad range of stakeholders. I should note also that NOAA's Regional Integrated Sciences and Assessments ( RISA) program is an earlier "Existence Theorem" for a Federal-University Partnership to Develop Actionable and Needs-Driven Science Agendas. This contribution will discuss the important cultural shift that has flowed from Secretarial Order 3289.

Global Impacts and Regional Actions: Preparing for the 1997-98 El Niño.

NASA Astrophysics Data System (ADS)

Buizer, James L.; Foster, Josh; Lund, David

2000-09-01

It has been estimated that severe El Niño-related flooding and droughts in Africa, Latin America, North America, and Southeast Asia resulted in more than 22 000 lives lost and in excess of $36 billion in damages during 1997-98. As one of the most severe events this century, the 1997-98 El Niño was unique not only in terms of physical magnitude, but also in terms of human response. This response was made possible by recent advances in climate-observing and forecasting systems, creation and dissemination of forecast information by institutions such as the International Research Institute for Climate Prediction and NOAA's Climate Prediction Center, and individuals in climate-sensitive sectors willing to act on forecast information by incorporating it into their decision-making. The supporting link between the forecasts and their practical application was a product of efforts by several national and international organizations, and a primary focus of the United States National Oceanic and Atmospheric Administration Office of Global Programs (NOAA/OGP).NOAA/OGP over the last decade has supported pilot projects in Latin America, the Caribbean, the South Pacific, Southeast Asia, and Africa to improve transfer of forecast information to climate sensitive sectors, study linkages between climate and human health, and distribute climate information products in certain areas. Working with domestic and international partners, NOAA/OGP helped organize a total of 11 Climate Outlook Fora around the world during the 1997-98 El Niño. At each Outlook Forum, climatologists and meteorologists created regional, consensus-based, seasonal precipitation forecasts and representatives from climate-sensitive sectors discussed options for applying forecast information. Additional ongoing activities during 1997-98 included research programs focused on the social and economic impacts of climate change and the regional manifestations of global-scale climate variations and their effect on decision-making in climate-sensitive sectors in the United States.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.The overall intent of NOAA/OGP's activities was to make experimental forecast information broadly available to potential users, and to foster a learning process on how seasonal-to-interannual forecasts could be applied in sectors susceptible to climate variability. This process allowed users to explore the capabilities and limitations of climate forecasts currently available, and forecast producers to receive feedback on the utility of their products. Through activities in which NOAA/OGP and its partners were involved, it became clear that further application of forecast information will be aided by improved forecast accuracy and detail, creation of common validation techniques, continued training in forecast generation and application, alternate methods for presenting forecast information, and a systematic strategy for creation and dissemination of forecast products.

Climate change in the Pacific - is it real or not?

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy

2013-04-01

In this presentation, novel approaches and new ideas for students and young researchers to appreciate the importance of climate science are discussed. These approaches have been applied through conducting a number of training workshops in the Pacific Island Countries and teaching a course on climate change international law and climate change science at the University of the South Pacific (USP) - the first course on this type in the Pacific. Particular focus of this presentation is on broadening students' experience with application of web-based information tools for analysis of climatic extremes and natural hazards such as tropical cyclones. Over the past few years, significant efforts of Australian climate scientists have been dedicated to improving understanding of climate in the Pacific through the International Climate Change Adaptation Initiative (the Australian Government Initiative to assist with high priority climate adaptation needs in vulnerable countries in the Asia-Pacific region). The first comprehensive scientific report about the Pacific climate has been published in 2011, as an outcome of the Pacific Climate Change Science Program (PCCSP). A range of web-based information tools such as the Pacific Tropical Cyclone Data Portal, the Pacific Climate Change Data Portal and the Pacific Seasonal Climate Prediction Portal has been also developed through the PCCSP and the Pacific Adaptation Strategy Assistance Program. Currently, further advancement in seasonal climate prediction science and developing enhanced software tools for the Pacific is undertaken through the Theme 1 of the Pacific Australia Climate Change Science and Adaptation Planning (PACCSAP) Program. This new scientific knowledge needs to be transferred to students to provide them with true information about climate change and its impact on the Pacific Island Countries. Teachers and educators need their knowledge-base regularly updated and tools that will help their students critically evaluate information transmitted via the mass media. This is particularly important when educators present to students cutting edge science knowledge on climate change. Climate change skeptics through mass media attack climate scientists and dismiss their findings about magnitude of climate change. A novel approach implemented in our training workshops and teaching courses gives students practical hands on experience in examining climate data using the developed web-based information tools. Using the tools, students can examine climate of the Pacific Island Countries, derive trends in climate variables such as temperature and rainfall and make their own conclusions. An open forum "Is climate change real or not?" has also been included as an integral part of these workshops and teaching, giving an opportunity for students to present their findings. They have also been asked to provide examples of observed change in the environment in their countries which may be related to climate change. Tropical cyclones are the most destructive severe weather events in the Pacific which regularly affect countries in the region. Understanding importance of updating knowledge about cyclones, extensive training in using the Pacific Tropical Cyclone Data Portal (http://www.bom.gov.au/cyclone/history/tracks/) has also been provided. Using this sophisticated web-based tool, students can learn about occurrences of cyclones in waters around their countries and over the whole Pacific. Positive feedback from university students and participants of training workshops has been obtained and this approach may be recommended for educators to include in their courses. Acknowledgement The research discussed in this paper was conducted through the PASAP, PCCSP and PACCSAP supported by the AusAID and Department of Climate Change and Energy Efficiency and delivered by the Bureau of Meteorology and CSIRO.

U.S. Geological Survey Ground-Water Resources Program, 2001

USGS Publications Warehouse

Grannemann, Norman G.

2001-01-01

Ground water is among the Nation's most important natural resources. It provides drinking water to urban and rural communities, supports irrigation and industry, sustains the flow of streams and rivers, and maintains riparian and wetland ecosystems. In many areas of the Nation, the future sustainability of ground-water resources is at risk from over use and contamination. Because ground-water systems typically respond slowly to human actions and climate variability, a long-term perspective is needed to manage this valuable resource. The U.S. Geological Survey Ground-Water Resources Program provides regional evaluations, fundamental data, and predictive tools to help assure the sustainability of our Nation's ground-water resources.

A solar diameter metrology measurement: the Picard microsatellite program

NASA Astrophysics Data System (ADS)

Damé, Luc; Brun, Jean-Francis; Cugnet, David; Derrien, Marc; Leroy, Claude; Meftah, Mustapha; Meissonnier, Mireille; Porteneuve, Jacques

2017-11-01

The PICARD microsatellite mission will provide 3 to 4 years simultaneous measurements of the solar diameter, differential rotation and solar constant to investigate the nature of their relations and variabilities. The major instrument, SODISM, is a whole Sun imaging telescope of Ø110 mm which will deliver an absolute measure (better than 4 mas) of the solar diameter and solar shape. Now in Phase B, PICARD is expected to be launched by 2005. We recall the scientific goals linked to the diameter measurement with interest for Earth Climate, Space Weather and Helioseismology, present the instrument optical concept and design, and give a brief overview of the program aspects.

Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.

PubMed

Morioka, Yushi; Doi, Takeshi; Behera, Swadhin K

2018-01-26

Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.

Southern Hemisphere climate variability forced by Northern Hemisphere ice-sheet topography

NASA Astrophysics Data System (ADS)

Jones, T. R.; Roberts, W. H. G.; Steig, E. J.; Cuffey, K. M.; Markle, B. R.; White, J. W. C.

2018-02-01

The presence of large Northern Hemisphere ice sheets and reduced greenhouse gas concentrations during the Last Glacial Maximum fundamentally altered global ocean-atmosphere climate dynamics. Model simulations and palaeoclimate records suggest that glacial boundary conditions affected the El Niño-Southern Oscillation, a dominant source of short-term global climate variability. Yet little is known about changes in short-term climate variability at mid- to high latitudes. Here we use a high-resolution water isotope record from West Antarctica to demonstrate that interannual to decadal climate variability at high southern latitudes was almost twice as large at the Last Glacial Maximum as during the ensuing Holocene epoch (the past 11,700 years). Climate model simulations indicate that this increased variability reflects an increase in the teleconnection strength between the tropical Pacific and West Antarctica, owing to a shift in the mean location of tropical convection. This shift, in turn, can be attributed to the influence of topography and albedo of the North American ice sheets on atmospheric circulation. As the planet deglaciated, the largest and most abrupt decline in teleconnection strength occurred between approximately 16,000 years and 15,000 years ago, followed by a slower decline into the early Holocene.

Association between Climatic Variables and Malaria Incidence: A Study in Kokrajhar District of Assam, India

PubMed Central

Nath, Dilip C.; Mwchahary, Dimacha Dwibrang

2013-01-01

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models. PMID:23283041

Association between climatic variables and malaria incidence: a study in Kokrajhar district of Assam, India.

PubMed

Nath, Dilip C; Mwchahary, Dimacha Dwibrang

2012-11-11

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with forest malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models.

Reservoirs performances under climate variability: a case study

NASA Astrophysics Data System (ADS)

Longobardi, A.; Mautone, M.; de Luca, C.

2014-09-01

A case study, the Piano della Rocca dam (southern Italy) is discussed here in order to quantify the system performances under climate variability conditions. Different climate scenarios have been stochastically generated according to the tendencies in precipitation and air temperature observed during recent decades for the studied area. Climate variables have then been filtered through an ARMA model to generate, at the monthly scale, time series of reservoir inflow volumes. Controlled release has been computed considering the reservoir is operated following the standard linear operating policy (SLOP) and reservoir performances have been assessed through the calculation of reliability, resilience and vulnerability indices (Hashimoto et al. 1982), comparing current and future scenarios of climate variability. The proposed approach can be suggested as a valuable tool to mitigate the effects of moderate to severe and persistent droughts periods, through the allocation of new water resources or the planning of appropriate operational rules.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Local oceanographic variability influences the performance of juvenile abalone under climate change.

PubMed

Boch, C A; Micheli, F; AlNajjar, M; Monismith, S G; Beers, J M; Bonilla, J C; Espinoza, A M; Vazquez-Vera, L; Woodson, C B

2018-04-03

Climate change is causing warming, deoxygenation, and acidification of the global ocean. However, manifestation of climate change may vary at local scales due to oceanographic conditions. Variation in stressors, such as high temperature and low oxygen, at local scales may lead to variable biological responses and spatial refuges from climate impacts. We conducted outplant experiments at two locations separated by ~2.5 km and two sites at each location separated by ~200 m in the nearshore of Isla Natividad, Mexico to assess how local ocean conditions (warming and hypoxia) may affect juvenile abalone performance. Here, we show that abalone growth and mortality mapped to variability in stress exposure across sites and locations. These insights indicate that management decisions aimed at maintaining and recovering valuable marine species in the face of climate change need to be informed by local variability in environmental conditions.

Chapter 2: Effects of climatic variability and change. In Effects of Climate Variability and Change on Forest Ecosystems: A Comprehensive Science Synthesis for the U.S. Forest Sector; General Technical Report PNW-GTR-870, Washington DC

EPA Science Inventory

Climate profoundly shapes forests. Forest species composition, productivity, availability of goods and services, disturbance regimes, and location on the landscape are all regulated by climate. Much research attention has focused on the problem of predicting the response of fores...

Earth System Science Education Centered on Natural Climate Variability

NASA Astrophysics Data System (ADS)

Ramirez, P. C.; Ladochy, S.; Patzert, W. C.; Willis, J. K.

2009-12-01

Several new courses and many educational activities related to climate change are available to teachers and students of all grade levels. However, not all new discoveries in climate research have reached the science education community. In particular, effective learning tools explaining natural climate change are scarce. For example, the Pacific Decadal Oscillation (PDO) is a main cause of natural climate variability spanning decades. While most educators are familiar with the shorter-temporal events impacting climate, El Niño and La Niña, very little has trickled into the climate change curriculum on the PDO. We have developed two online educational modules, using an Earth system science approach, on the PDO and its role in climate change and variability. The first concentrates on the discovery of the PDO through records of salmon catch in the Pacific Northwest and Alaska. We present the connection between salmon abundance in the North Pacific to changing sea surface temperature patterns associated with the PDO. The connection between sea surface temperatures and salmon abundance led to the discovery of the PDO. Our activity also lets students explore the role of salmon in the economy and culture of the Pacific Northwest and Alaska and the environmental requirements for salmon survival. The second module is based on the climate of southern California and how changes in the Pacific Ocean , such as the PDO and ENSO (El Niño-Southern Oscillation), influence regional climate variability. PDO and ENSO signals are evident in the long-term temperature and precipitation record of southern California. Students are guided in the module to discover the relationships between Pacific Ocean conditions and southern California climate variability. The module also provides information establishing the relationship between climate change and variability and the state's water, energy, agriculture, wildfires and forestry, air quality and health issues. Both modules will be reviewed for inclusion on the ESSEA (Earth Systems Science Education Alliance) course module list. ESSEA is a NSF-funded organization dedicated to K-12 online Earth system science education.

Rainfall variability and extremes over southern Africa: Assessment of a climate model to reproduce daily extremes

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2009-04-01

It is increasingly accepted that that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite derived rainfall data from the Microwave Infra-Red Algorithm (MIRA). This dataset covers the period from 1993-2002 and the whole of southern Africa at a spatial resolution of 0.1 degree longitude/latitude. The ability of a climate model to simulate current climate provides some indication of how much confidence can be applied to its future predictions. In this paper, simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. This concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of rainfall variability over southern Africa. Secondly, the ability of the model to reproduce daily rainfall extremes will be assessed, again by a comparison with extremes from the MIRA dataset. The paper will conclude by discussing the user needs of satellite rainfall retrievals from a climate change modelling prospective.

Quantitative Analysis of Relevant Soil, Land-use and Climate Characteristics on Landscape Degradation in Hungary

NASA Astrophysics Data System (ADS)

Kertesz, Adam; Mika, Janos; Jakab, Gergely; Palinkas, Melinda

2017-04-01

The objective of our research is to survey degradation processes acting in each micro-region of Hungary in connection with geographical and climatic characteristics. A survey of land degradation processes has been carried out at medium scale (1:50 000) to identify the affected areas of the region. Over 18,000 rectangles of Hungary have been digitally characterised for several types of land degradation. Water-flow type gully erosion and soil-loss (RUSLE, 2015: Esdac-data) are studied for dependent variables in this study. USDA textural classes, available water capacity, bulk density, clay content, coarse fragments, silt content, sand content, soil parent material, soil texture, land-use type (Corine, 2012) are used for non-climatic variables. Some of these characteristics are quantified in a non-scalable way, so the first step was to arrange these qualitative codes or pseudo-numbers into monotonous order for including them into the following multi-regression analyses. Data available from the CarpatClim Project (www.carpatclim-eu.org/pages/home) for 1961-2010 are also used in their 50 years averages is seasonal and annual resolution. The selected variables from this gridded data set are global radiation, daily mean temperature, maximum and minimum temperature, number of extreme cold days (< 20 C), precipitation, extreme wet days (>20 mm), days with utilizable precipitation (>1mm/d), potential evapotranspiration, Palmer Index (PDSI), Palfai Index (PAI), relative humidity and wind speed at 10 m height. The gully erosion processes strongly depend on the investigated non-climatic variables, mostly on parent material and slope. The group of further climatic factors is formed by winter relative humidity, wind speed and all-year round Palmer index. Besides leading role of the above non-climatic factors, additional effects of the significant climate variables are difficult to interpret. Nevertheless, the partial effects of these climate variables are combined with future climate scenarios available from GCM and RCM studies for Hungary. The real climate change effects may likely be stronger, than those obtained by this combination, due to inter-dependences between the non-climatic factors and climate variations. The study has been supported by the OTKA-K108755 project.

Smallholder agriculture in India and adaptation to current and future climate variability and climate change

NASA Astrophysics Data System (ADS)

Murari, K. K.; Jayaraman, T.

2014-12-01

Modeling studies have indicated that global warming, in many regions, will increase the exposure of major crops to rainfall and temperature stress, leading to lower crop yields. Climate variability alone has a potential to decrease yield to an extent comparable to or greater than yield reductions expected due to rising temperature. For India, where agriculture is important, both in terms of food security as well as a source of livelihoods to a majority of its population, climate variability and climate change are subjects of serious concern. There is however a need to distinguish the impact of current climate variability and climate change on Indian agriculture, especially in relation to their socioeconomic impact. This differentiation is difficult to determine due to the secular trend of increasing production and yield of the past several decades. The current research in this aspect is in an initial stage and requires a multi-disciplinary effort. In this study, we assess the potential differential impacts of environmental stress and shock across different socioeconomic strata of the rural population, using village level survey data. The survey data from eight selected villages, based on the Project on Agrarian Relations in India conducted by the Foundation for Agrarian Studies, indicated that income from crop production of the top 20 households (based on the extent of operational land holding, employment of hired labour and asset holdings) is a multiple of the mean income of the village. In sharp contrast, the income of the bottom 20 households is a fraction of the mean and sometimes negative, indicating a net loss from crop production. The considerable differentials in output and incomes suggest that small and marginal farmers are far more susceptible to climate variability and climate change than the other sections. Climate change is effectively an immediate threat to small and marginal farmers, which is driven essentially by socioeconomic conditions. The impact of climate variability on smallholder agriculture in the present can therefore provide important insights into the nature of its vulnerability to future climate change.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Phylogenetic assemblage structure of North American trees is more strongly shaped by glacial-interglacial climate variability in gymnosperms than in angiosperms.

PubMed

Ma, Ziyu; Sandel, Brody; Svenning, Jens-Christian

2016-05-01

How fast does biodiversity respond to climate change? The relationship of past and current climate with phylogenetic assemblage structure helps us to understand this question. Studies of angiosperm tree diversity in North America have already suggested effects of current water-energy balance and tropical niche conservatism. However, the role of glacial-interglacial climate variability remains to be determined, and little is known about any of these relationships for gymnosperms. Moreover, phylogenetic endemism, the concentration of unique lineages in restricted ranges, may also be related to glacial-interglacial climate variability and needs more attention. We used a refined phylogeny of both angiosperms and gymnosperms to map phylogenetic diversity, clustering and endemism of North American trees in 100-km grid cells, and climate change velocity since Last Glacial Maximum together with postglacial accessibility to recolonization to quantify glacial-interglacial climate variability. We found: (1) Current climate is the dominant factor explaining the overall patterns, with more clustered angiosperm assemblages toward lower temperature, consistent with tropical niche conservatism. (2) Long-term climate stability is associated with higher angiosperm endemism, while higher postglacial accessibility is linked to to more phylogenetic clustering and endemism in gymnosperms. (3) Factors linked to glacial-interglacial climate change have stronger effects on gymnosperms than on angiosperms. These results suggest that paleoclimate legacies supplement current climate in shaping phylogenetic patterns in North American trees, and especially so for gymnosperms.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

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

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

Use of color maps and wavelet coherence to discern seasonal and interannual climate influences on streamflow variability in northern catchments

NASA Astrophysics Data System (ADS)

Carey, Sean K.; Tetzlaff, Doerthe; Buttle, Jim; Laudon, Hjalmar; McDonnell, Jeff; McGuire, Kevin; Seibert, Jan; Soulsby, Chris; Shanley, Jamie

2013-10-01

The higher midlatitudes of the northern hemisphere are particularly sensitive to change due to the important role the 0°C isotherm plays in the phase of precipitation and intermediate storage as snow. An international intercatchment comparison program called North-Watch seeks to improve our understanding of the sensitivity of northern catchments to change by examining their hydrological and biogeochemical variability and response. Here eight North-Watch catchments located in Sweden (Krycklan), Scotland (Girnock and Strontian), the United States (Sleepers River, Hubbard Brook, and HJ Andrews), and Canada (Dorset and Wolf Creek) with 10 continuous years of daily precipitation and runoff data were selected to assess daily to seasonal coupling of precipitation (P) and runoff (Q) using wavelet coherency, and to explore the patterns and scales of variability in streamflow using color maps. Wavelet coherency revealed that P and Q were decoupled in catchments with cold winters, yet were strongly coupled during and immediately following the spring snowmelt freshet. In all catchments, coupling at shorter time scales occurred during wet periods when the catchment was responsive and storage deficits were small. At longer time scales, coupling reflected coherence between seasonal cycles, being enhanced at sites with enhanced seasonality in P. Color maps were applied as an alternative method to identify patterns and scales of flow variability. Seasonal versus transient flow variability was identified along with the persistence of that variability on influencing the flow regime. While exploratory in nature, this intercomparison exercise highlights the importance of climate and the 0°C isotherm on the functioning of northern catchments.

Evolving the US Climate Resilience Toolkit to Support a Climate-Smart Nation

NASA Astrophysics Data System (ADS)

Tilmes, C.; Niepold, F., III; Fox, J. F.; Herring, D.; Dahlman, L. E.; Hall, N.; Gardiner, N.

2015-12-01

Communities, businesses, resource managers, and decision-makers at all levels of government need information to understand and ameliorate climate-related risks. Likewise, climate information can expose latent opportunities. Moving from climate science to social and economic decisions raises complex questions about how to communicate the causes and impacts of climate variability and change; how to characterize and quantify vulnerabilities, risks, and opportunities faced by communities and businesses; and how to make and implement "win-win" adaptation plans at local, regional, and national scales. A broad coalition of federal agencies launched the U.S. Climate Resilience Toolkit (toolkit.climate.gov) in November 2014 to help our nation build resilience to climate-related extreme events. The site's primary audience is planners and decision makers in business, resource management, and government (at all levels) who seek science-based climate information and tools to help them in their near- and long-term planning. The Executive Office of the President assembled a task force of dozens of subject experts from across the 13 agencies of the U.S. Global Change Research Program to guide the site's development. The site's ongoing evolution is driven by feedback from the target audience. For example, based on feedback, climate projections will soon play a more prominent role in the site's "Climate Explorer" tool and case studies. The site's five-step adaptation planning process is being improved to better facilitate people getting started and to provide clear benchmarks for evaluating progress along the way. In this session, we will share lessons learned from a series of user engagements around the nation and evidence that the Toolkit couples climate information with actionable decision-making processes in ways that are helping Americans build resilience to climate-related stressors.

Climate Variability and Human Migration in the Netherlands, 1865–1937

PubMed Central

Jennings, Julia A.; Gray, Clark L.

2014-01-01

Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689

Assessment of a climate model to reproduce rainfall variability and extremes over Southern Africa

NASA Astrophysics Data System (ADS)

Williams, C. J. R.; Kniveton, D. R.; Layberry, R.

2010-01-01

It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The sub-continent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability and the identification of rainfall extremes is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. The majority of previous climate model verification studies have compared model output with observational data at monthly timescales. In this research, the assessment of ability of a state of the art climate model to simulate climate at daily timescales is carried out using satellite-derived rainfall data from the Microwave Infrared Rainfall Algorithm (MIRA). This dataset covers the period from 1993 to 2002 and the whole of southern Africa at a spatial resolution of 0.1° longitude/latitude. This paper concentrates primarily on the ability of the model to simulate the spatial and temporal patterns of present-day rainfall variability over southern Africa and is not intended to discuss possible future changes in climate as these have been documented elsewhere. Simulations of current climate from the UK Meteorological Office Hadley Centre's climate model, in both regional and global mode, are firstly compared to the MIRA dataset at daily timescales. Secondly, the ability of the model to reproduce daily rainfall extremes is assessed, again by a comparison with extremes from the MIRA dataset. The results suggest that the model reproduces the number and spatial distribution of rainfall extremes with some accuracy, but that mean rainfall and rainfall variability is under-estimated (over-estimated) over wet (dry) regions of southern Africa.

A CLIMATOLOGY OF WATER BUDGET VARIABLE FOR THE NORTHEASTERN UNITED STATES

EPA Science Inventory

A Climatology of Water Budget Variables for the Northeast United States (Leathers and Robinson 1995). Climatic division precipitation and temperature data are used to calculate water budget variables based on the Thornthwaite/Mather climatic water budget methodology. Two water b...

How does spatial variability of climate affect catchment streamflow predictions?

EPA Science Inventory

Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...

Middle Miocene environmental and climatic evolution at the Wilkes Land margin, East Antarctica

NASA Astrophysics Data System (ADS)

Sangiorgi, Francesca; Bijl, Peter; Passchier, Sandra; Salzmann, Ulrich; Schouten, Stefan; Pross, Jörg; Escutia, Carlota; Brinkhuis, Henk

2015-04-01

Integrated Ocean Drilling Program (IODP) Expedition 318 successfully drilled a Middle Miocene (~ 17 - 12.5 Ma) record from the Wilkes Land Margin at Site U1356A (63°18.6138'S, 135°59.9376'E), located at the transition between the continental rise and the abyssal plain at 4003 mbsl. We present a multiproxy palynological (dinoflagellate cyst, pollen and spores), sedimentological and organic geochemical (TEX86, MBT/CBT) study, which unravels the environmental and climate variability across the Miocene Climatic Optimum (MCO, ~17-15 Ma) and the Mid Miocene Climate Transition (MMCT). Several independent lines of evidence suggest a relatively warm climate during the MCO. Dinocyst and pollen assemblage diversity at the MCO is unprecedented for a Neogene Antarctic record and indicates a temperate, sea ice-free marine environment, with woody sub-antarctic vegetation with elements of forest/shrub tundra and peat lands along the coast. These results are further confirmed by relatively warm TEX86-derived Sea Surface Temperatures and mild MBT-derived continental temperatures, and by the absence of glacially derived deposits and very few ice-rafted clasts. A generally colder but highly dynamic environment is suggested for the interval 15-12.5 Ma.

High-resolution mapping and modelling of surface albedo in Norwegian boreal forests: from remotely sensed data to predictions

NASA Astrophysics Data System (ADS)

Cherubini, Francesco; Hu, Xiangping; Vezhapparambu, Sajith; Stromman, Anders

2017-04-01

Surface albedo, a key parameter of the Earth's climate system, has high variability in space, time, and land cover and its parameterization is among the most important variables in climate models. The lack of extensive estimates for model improvement is one of the main limitations for accurately quantifying the influence of surface albedo changes on the planetary radiation balance. We use multi-year satellite retrievals of MODIS surface albedo (MCD43A3), high resolution land cover maps, and meteorological records to characterize albedo variations in Norway across latitude, seasons, land cover type, and topography. We then use this dataset to elaborate semi-empirical models to predict albedo values as a function of tree species, age, volume and climate variables like temperature and snow water equivalents (SWE). Given the complexity of the dataset and model formulation, we apply an innovative non-linear programming approach simultaneously coupled with linear un-mixing. The MODIS albedo products are at a resolution of about 500 m and 8 days. The land cover maps provide vegetation structure information on relative abundance of tree species, age, and biomass volumes at 16 m resolution (for both deciduous and coniferous species). Daily observations of meteorological information on air temperature and SWE are produced at 1 km resolution from interpolation of meteorological weather stations in Norway. These datasets have different resolution and projection, and are harmonized by identifying, for each MODIS pixel, the intersecting land cover polygons and the percentage area of the MODIS pixel represented by each land cover type. We then filter the subplots according to the following criteria: i) at least 96% of the total pixel area is covered by a single land cover class (either forest or cropland); ii) if forest area, at least 98% of the forest area is covered by spruce, deciduous or pine. Forested pixels are then categorized as spruce, deciduous, or pine dominant if the fraction of the respective tree species is greater than 75%. Results show averages of albedo estimates for forests and cropland depicting spatial (along a latitudinal gradient) and temporal (daily, monthly, and seasonal) variations across Norway. As the case study region is a country with heterogeneous topography, we also study the sensitivity of the albedo estimates to the slope and aspect of the terrain. The mathematical programming approach uses a variety of functional forms, constraints and variables, leading to many different model outputs. There are several models with relatively high performances, allowing for a flexibility in the model selection, with different model variants suitable for different situations. This approach produces albedo predictions at the same resolution of the land cover dataset (16 m, notably higher than the MODIS estimates), can incorporate changes in climate conditions, and is robust to cross-validation between different locations. By integrating satellite measurements and high-resolution vegetation maps, we can thus produce semi-empirical models that can predict albedo values for boreal forests using a variety of input variables representing climate and/or vegetation structure. Further research can explore the possible advantages of its implementation in land surface schemes over existing approaches.

Land use and climate variability amplify carbon, nutrient, and contaminant pulses: a review with management implications

EPA Science Inventory

Nonpoint source pollution from agriculture and urbanization is increasing globally at the same time that climate extremes have increased in frequency and intensity. We review over 160 studies and show how the interaction between land use and climate variability alters the magnit...

Students' Perceptions of School Climate as Determinants of Wellbeing, Resilience and Identity

ERIC Educational Resources Information Center

Aldridge, Jill M.; Fraser, Barry J.; Fozdar, Farida; Ala'i, Kate; Earnest, Jaya; Afari, Ernest

2016-01-01

This study examined the relations between school climate variables and students' feeling of wellbeing, life satisfaction, ethnic identity, moral identity and resilience. Furthermore, the study also examined the interrelationships between these five outcome variables. Six aspects of the school climate were measured: teacher support, peer…

Impacts of Climate Change and Variability on Water Resources in the Southeast USA

Treesearch

Ge Sun; Peter V. Caldwell; Steven G. McNulty; Aris P. Georgakakos; Sankar Arumugam; James Cruise; Richard T. McNider; Adam Terando; Paul A. Conrads; John Feldt; Vasu Misra; Luigi Romolo; Todd C. Rasmussen; Daniel A. Marion

2013-01-01

Key FindingsClimate change is affecting the southeastern USA, particularly increases in rainfall variability and air temperature, which have resulted in more frequent hydrologic extremes, such as high‐intensity storms (tropical storms and hurricanes), flooding, and drought events.Future climate warming likely will...

Climate variability and plant response at the Santa Rita Experimental Range, Arizona

Treesearch

Michael A. Crimmins; Theresa M. Mau-Crimmins

2003-01-01

Climatic variability is reflected in differential establishment, persistence, and spread of plant species. Although studies have investigated these relationships for some species and functional groups, few have attempted to characterize the specific sequences of climatic conditions at various temporal scales (subseasonal, seasonal, and interannual) associated with...

Climate optimized planting windows for cotton in the lower Mississippi Delta region

USDA-ARS?s Scientific Manuscript database

Unique, variable summer climate of the lower Mississippi Delta region poses a critical challenge to cotton producers in deciding when to plant for optimized production. Traditional 2- to 4-year agronomic field trials conducted in this area fail to capture the effects of long-term climate variabiliti...

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

Evaluation of climatic changes in South-Asia

NASA Astrophysics Data System (ADS)

Kjellstrom, Erik; Rana, Arun; Grigory, Nikulin; Renate, Wilcke; Hansson, Ulf; Kolax, Michael

2016-04-01

Literature has sufficient evidences of climate change impact all over the world and its impact on various sectors. In light of new advancements made in climate modeling, availability of several climate downscaling approaches, the more robust bias correction methods with varying complexities and strengths, in the present study we performed a systematic evaluation of climate change impact over South-Asia region. We have used different Regional Climate Models (RCMs) (from CORDEX domain), (Global Climate Models GCMs) and gridded observations for the study area to evaluate the models in historical/control period (1980-2010) and changes in future period (2010-2099). Firstly, GCMs and RCMs are evaluated against the Gridded observational datasets in the area using precipitation and temperature as indicative variables. Observational dataset are also evaluated against the reliable set of observational dataset, as pointed in literature. Bias, Correlation, and changes (among other statistical measures) are calculated for the entire region and both the variables. Eventually, the region was sub-divided into various smaller domains based on homogenous precipitation zones to evaluate the average changes over time period. Spatial and temporal changes for the region are then finally calculated to evaluate the future changes in the region. Future changes are calculated for 2 Representative Concentration Pathways (RCPs), the middle emission (RCP4.5) and high emission (RCP8.5) and for both climatic variables, precipitation and temperature. Lastly, Evaluation of Extremes is performed based on precipitation and temperature based indices for whole region in future dataset. Results have indicated that the whole study region is under extreme stress in future climate scenarios for both climatic variables i.e. precipitation and temperature. Precipitation variability is dependent on the location in the area leading to droughts and floods in various regions in future. Temperature is hinting towards a constant increase throughout the region regardless of location.

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

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.