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

PubMed

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

2016-01-18

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

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

NASA Astrophysics Data System (ADS)

Harlaß, Jan; Latif, Mojib; Park, Wonsun

2018-04-01

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

Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity

NASA Astrophysics Data System (ADS)

Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego

2015-04-01

Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity over the last two decades. The co-variability of a range of climate oscillation indices and newly-derived records of fluorescence and vegetation optical depth is analyzed using a statistical framework based on correlations, bootstrapping and Empirical Orthogonal Functions (EOFs). Results will enable us to characterize regional hotspots where particular climatic oscillations control vegetation productivity, as well as allowing us to underpin the climatic variables behind this control.

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 .

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

NASA Astrophysics Data System (ADS)

Muhammad, A.

2015-12-01

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

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

Effects of watershed management on sources and fluxes of water, carbon, and nitrogen in streams: Climate implications

EPA Science Inventory

Background/Question/Methods Due to the interactive effects of urbanization and climate variability, managing impacts on watershed hydrology and biogeochemical processing has become increasingly important, particularly due to the enhanced potential for eutrophication and hypoxia i...

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.

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.

Low cloud properties influenced by cosmic rays

PubMed

Marsh; Svensmark

2000-12-04

The influence of solar variability on climate is currently uncertain. Recent observations have indicated a possible mechanism via the influence of solar modulated cosmic rays on global cloud cover. Surprisingly the influence of solar variability is strongest in low clouds (

Interannual abundance changes of gelatinous carnivore zooplankton unveil climate-driven hydrographic variations in the Iberian Peninsula, Portugal.

PubMed

D'Ambrosio, Mariaelena; Molinero, Juan C; Azeiteiro, Ulisses M; Pardal, Miguel A; Primo, Ana L; Nyitrai, Daniel; Marques, Sónia C

2016-09-01

The persistent massive blooms of gelatinous zooplankton recorded during recent decades may be indicative of marine ecosystem changes. In this study, we investigated the potential influence of the North Atlantic climate (NAO) variability on decadal abundance changes of gelatinous carnivore zooplankton in the Mondego estuary, Portugal, over the period 2003-2013. During the 11-year study, the community of gelatinous carnivores encompassed a larger diversity of hydromedusae than siphonophores; the former dominated by Obelia spp., Lizzia blondina, Clythia hemisphaerica, Liriope tetraphylla and Solmaris corona, while the latter dominated by Muggiaea atlantica. Gelatinous carnivore zooplankton displayed marked interannual variability and mounting species richness over the period examined. Their pattern of abundance shifted towards larger abundances ca. 2007 and significant phenological changes. The latter included a shift in the mean annual pattern (from unimodal to bimodal peak, prior and after 2007 respectively) and an earlier timing of the first annual peak concurrent with enhanced temperatures. These changes were concurrent with the climate-driven environmental variability mainly controlled by the NAO, which displayed larger variance after 2007 along with an enhanced upwelling activity. Structural equation modelling allowed depicting cascading effects derived from the NAO influence on regional climate and upwelling variability further shaping water temperature. Such cascading effect percolated the structure and dynamics of the community of gelatinous carnivore zooplankton in the Mondego estuary. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Pandey, Suraj

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

Building Climate Resilience in the Blue Nile/Abay Highlands: A Role for Earth System Sciences

PubMed Central

Zaitchik, Benjamin F.; Simane, Belay; Habib, Shahid; Anderson, Martha C.; Ozdogan, Mutlu; Foltz, Jeremy D.

2012-01-01

The Blue Nile (Abay) Highlands of Ethiopia are characterized by significant interannual climate variability, complex topography and associated local climate contrasts, erosive rains and erodible soils, and intense land pressure due to an increasing population and an economy that is almost entirely dependent on smallholder, low-input agriculture. As a result, these highland zones are highly vulnerable to negative impacts of climate variability. As patterns of variability and precipitation intensity alter under anthropogenic climate change, there is concern that this vulnerability will increase, threatening economic development and food security in the region. In order to overcome these challenges and to enhance sustainable development in the context of climate change, it is necessary to establish climate resilient development strategies that are informed by best-available Earth System Science (ESS) information. This requirement is complicated by the fact that climate projections for the Abay Highlands contain significant and perhaps irreducible uncertainties. A critical challenge for ESS, then, is to generate and to communicate meaningful information for climate resilient development in the context of a highly uncertain climate forecast. Here we report on a framework for applying ESS to climate resilient development in the Abay Highlands, with a focus on the challenge of reducing land degradation. PMID:22470302

Soil water improvements with the long-term use of a winter rye cover crop

USDA-ARS?s Scientific Manuscript database

The Midwestern United States, a region that produces one-third of maize and one-quarter of soybeans globally, is projected to experience increasing rainfall variability with future climate change. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance ...

A Variable Resolution Stretched Grid General Circulation Model: Regional Climate Simulation

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.; Takacs, Lawrence L.; Govindaraju, Ravi C.; Suarez, Max J.

2000-01-01

The development of and results obtained with a variable resolution stretched-grid GCM for the regional climate simulation mode, are presented. A global variable resolution stretched- grid used in the study has enhanced horizontal resolution over the U.S. as the area of interest The stretched-grid approach is an ideal tool for representing regional to global scale interaction& It is an alternative to the widely used nested grid approach introduced over a decade ago as a pioneering step in regional climate modeling. The major results of the study are presented for the successful stretched-grid GCM simulation of the anomalous climate event of the 1988 U.S. summer drought- The straightforward (with no updates) two month simulation is performed with 60 km regional resolution- The major drought fields, patterns and characteristics such as the time averaged 500 hPa heights precipitation and the low level jet over the drought area. appear to be close to the verifying analyses for the stretched-grid simulation- In other words, the stretched-grid GCM provides an efficient down-scaling over the area of interest with enhanced horizontal resolution. It is also shown that the GCM skill is sustained throughout the simulation extended to one year. The developed and tested in a simulation mode stretched-grid GCM is a viable tool for regional and subregional climate studies and applications.

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

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

Maslowski, Wieslaw

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

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

Exploring adaptations to climate change with stakeholders: A participatory method to design grassland-based farming systems.

PubMed

Sautier, Marion; Piquet, Mathilde; Duru, Michel; Martin-Clouaire, Roger

2017-05-15

Research is expected to produce knowledge, methods and tools to enhance stakeholders' adaptive capacity by helping them to anticipate and cope with the effects of climate change at their own level. Farmers face substantial challenges from climate change, from changes in the average temperatures and the precipitation regime to an increased variability of weather conditions and the frequency of extreme events. Such changes can have dramatic consequences for many types of agricultural production systems such as grassland-based livestock systems for which climate change influences the seasonality and productivity of fodder production. We present a participatory design method called FARMORE (FARM-Oriented REdesign) that allows farmers to design and evaluate adaptations of livestock systems to future climatic conditions. It explicitly considers three climate features in the design and evaluation processes: climate change, climate variability and the limited predictability of weather. FARMORE consists of a sequence of three workshops for which a pre-existing game-like platform was adapted. Various year-round forage production and animal feeding requirements must be assembled by participants with a computerized support system. In workshop 1, farmers aim to produce a configuration that satisfies an average future weather scenario. They refine or revise the previous configuration by considering a sample of the between-year variability of weather in workshop 2. In workshop 3, they explicitly take the limited predictability of weather into account. We present the practical aspects of the method based on four case studies involving twelve farmers from Aveyron (France), and illustrate it through an in-depth description of one of these case studies with three dairy farmers. The case studies shows and discusses how workshop sequencing (1) supports a design process that progressively accommodates complexity of real management contexts by enlarging considerations of climate change to climate variability and low weather predictability, and (2) increases the credibility and salience of the design method. Further enhancements of the method are outlined, especially the selection of pertinent weather scenarios. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

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.

Getting even or moving on? Power, procedural justice, and types of offense as predictors of revenge, forgiveness, reconciliation, and avoidance in organizations.

PubMed

Aquino, Karl; Tripp, Thomas M; Bies, Robert J

2006-05-01

A field study and an experimental study examined relationships among organizational variables and various responses of victims to perceived wrongdoing. Both studies showed that procedural justice climate moderates the effect of organizational variables on the victim's revenge, forgiveness, reconciliation, or avoidance behaviors. In Study 1, a field study, absolute hierarchical status enhanced forgiveness and reconciliation, but only when perceptions of procedural justice climate were high; relative hierarchical status increased revenge, but only when perceptions of procedural justice climate were low. In Study 2, a laboratory experiment, victims were less likely to endorse vengeance or avoidance depending on the type of wrongdoing, but only when perceptions of procedural justice climate were high.

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.

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

USGS Publications Warehouse

Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

2014-01-01

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

Sustainability or Collapse: Interplay Between Decadal Climate Variability and Human Activities Matters

NASA Astrophysics Data System (ADS)

Lu, Y.; Hu, H.; Tian, F.

2016-12-01

The Aral Sea Crisis and the deterioration of Tarim River Basin are representative cases of emergent water deficit problems in arid areas. Comparing cases of water deficit problems in different regions and considering the in the perspective of socio-hydrology is helpful to obtain guidance on integrated management of arid area basins. Analyzing the interplay between decadal climate variability and human activities in both basins, the important role of human activities is observed. Decadal climate variability tempts people to adapt fast to increasing water resources and slowly to decreasing water resources, while using unsustainable technical measures to offset water shortage. Due to this asymmetry the situation deteriorates with technically enhanced capabilities of societies to exploit water resources, and more integrated long-term management capacity is in high demand.

Enhanced recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-04-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

North Atlantic climate model bias influence on multiyear predictability

NASA Astrophysics Data System (ADS)

Wu, Y.; Park, T.; Park, W.; Latif, M.

2018-01-01

The influences of North Atlantic biases on multiyear predictability of unforced surface air temperature (SAT) variability are examined in the Kiel Climate Model (KCM). By employing a freshwater flux correction over the North Atlantic to the model, which strongly alleviates both North Atlantic sea surface salinity (SSS) and sea surface temperature (SST) biases, the freshwater flux-corrected integration depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector in comparison to the uncorrected one. The enhanced SAT predictability in the corrected integration is due to a stronger and more variable Atlantic Meridional Overturning Circulation (AMOC) and its enhanced influence on North Atlantic SST. Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SAT and exhibit a smaller SAT predictability over the North Atlantic sector.

Sensitivity of global terrestrial ecosystems to climate variability.

PubMed

Seddon, Alistair W R; Macias-Fauria, Marc; Long, Peter R; Benz, David; Willis, Kathy J

2016-03-10

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems--be they natural or with a strong anthropogenic signature--to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

Sensitivity of global terrestrial ecosystems to climate variability

NASA Astrophysics Data System (ADS)

Seddon, Alistair W. R.; Macias-Fauria, Marc; Long, Peter R.; Benz, David; Willis, Kathy J.

2016-03-01

The identification of properties that contribute to the persistence and resilience of ecosystems despite climate change constitutes a research priority of global relevance. Here we present a novel, empirical approach to assess the relative sensitivity of ecosystems to climate variability, one property of resilience that builds on theoretical modelling work recognizing that systems closer to critical thresholds respond more sensitively to external perturbations. We develop a new metric, the vegetation sensitivity index, that identifies areas sensitive to climate variability over the past 14 years. The metric uses time series data derived from the moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index, and three climatic variables that drive vegetation productivity (air temperature, water availability and cloud cover). Underlying the analysis is an autoregressive modelling approach used to identify climate drivers of vegetation productivity on monthly timescales, in addition to regions with memory effects and reduced response rates to external forcing. We find ecologically sensitive regions with amplified responses to climate variability in the Arctic tundra, parts of the boreal forest belt, the tropical rainforest, alpine regions worldwide, steppe and prairie regions of central Asia and North and South America, the Caatinga deciduous forest in eastern South America, and eastern areas of Australia. Our study provides a quantitative methodology for assessing the relative response rate of ecosystems—be they natural or with a strong anthropogenic signature—to environmental variability, which is the first step towards addressing why some regions appear to be more sensitive than others, and what impact this has on the resilience of ecosystem service provision and human well-being.

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.

Determining the Effect of the Lunar Nodal Cycle on Tidal Mixing and North Pacific Climate Variability

NASA Astrophysics Data System (ADS)

Ullman, D. J.; Schmittner, A.; Danabasoglu, G.; Norton, N. J.; Müller, M.

2016-02-01

Oscillations in the moon's orbit around the earth modulate regional tidal dissipation with a periodicity of 18.6 years. In regions where the diurnal tidal constituents dominate diapycnal mixing, this Lunar Nodal Cycle (LNC) may be significant enough to influence ocean circulation, sea surface temperature, and climate variability. Such periodicity in the LNC as an external forcing may provide a mechanistic source for Pacific decadal variability (i.e. Pacific Decadal Oscillation, PDO) where diurnal tidal constituents are strong. We have introduced three enhancements to the latest version of the Community Earth System Model (CESM) to better simulate tidal-forced mixing. First, we have produced a sub-grid scale bathymetry scheme that better resolves the vertical distribution of the barotropic energy flux in regions where the native CESM grid does not resolve high spatial-scale bathymetric features. Second, we test a number of alternative barotropic tidal constituent energy flux fields that are derived from various satellite altimeter observations and tidal models. Third, we introduce modulations of the individual diurnal and semi-diurnal tidal constituents, ranging from monthly to decadal periods, as derived from the full lunisolar tidal potential. Using both ocean-only and fully-coupled configurations, we test the influence of these enhancements, particularly the LNC modulations, on ocean mixing and bidecadal climate variability in CESM.

Impact of anthropogenic climate change on wildfire across western US forests.

PubMed

Abatzoglou, John T; Williams, A Park

2016-10-18

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Park Williams, A.

2016-10-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000-2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ˜55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984-2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting.

Relationship between ethical work climate and nurses' perception of organizational support, commitment, job satisfaction and turnover intent.

PubMed

Abou Hashish, Ebtsam Aly

2017-03-01

Healthcare organizations are now challenged to retain nurses' generation and understand why they are leaving their nursing career prematurely. Acquiring knowledge about the effect of ethical work climate and level of perceived organizational support can help organizational leaders to deal effectively with dysfunctional behaviors and make a difference in enhancing nurses' dedication, commitment, satisfaction, and loyalty to their organization. This study aims to determine the relationship between ethical work climate, and perceived organizational support and nurses' organizational commitment, job satisfaction, and turnover intention. A descriptive correlational research design was conducted in all inpatient care units at three major hospitals affiliated to different health sectors at Alexandria governorate. All nurses working in these previous hospitals were included in the study (N = 500). Ethical Climate Questionnaire, Survey of Perceived Organizational Support, Organizational Commitment Questionnaire, Index of Job Satisfaction, and Intention to Turnover scale were used to measure study variables. Ethical considerations: Approval was obtained from Ethics Committee at Faculty of Nursing, Alexandria University. Privacy and confidentiality of data were maintained and assured by obtaining subjects' informed consent to participate in the research before data collection. The result revealed positive significant correlations between nurses' perception of overall ethical work climate and each of perceived organizational support, commitment, as well as their job satisfaction. However, negative significant correlations were found between nurses' turnover intention and each of these variables. Also, approximately 33% of the explained variance of turnover intention is accounted by ethical work climate, organizational support, organizational commitment, and job satisfaction, and these variables independently contributed significantly in the prediction of turnover intention. Strategies to foster and enhance ethical and supportive work climates as well as job-related benefits are considered significant factors in increasing nurses' commitment and satisfaction and decreasing their turnover intention.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Sensitivity of crop cover to climate variability: insights from two Indian agro-ecoregions.

PubMed

Mondal, Pinki; Jain, Meha; DeFries, Ruth S; Galford, Gillian L; Small, Christopher

2015-01-15

Crop productivity in India varies greatly with inter-annual climate variability and is highly dependent on monsoon rainfall and temperature. The sensitivity of yields to future climate variability varies with crop type, access to irrigation and other biophysical and socio-economic factors. To better understand sensitivities to future climate, this study focuses on agro-ecological subregions in Central and Western India that span a range of crops, irrigation, biophysical conditions and socioeconomic characteristics. Climate variability is derived from remotely-sensed data products, Tropical Rainfall Measuring Mission (TRMM - precipitation) and Moderate Resolution Imaging Spectroradiometer (MODIS - temperature). We examined green-leaf phenologies as proxy for crop productivity using the MODIS Enhanced Vegetation Index (EVI) from 2000 to 2012. Using both monsoon and winter growing seasons, we assessed phenological sensitivity to inter-annual variability in precipitation and temperature patterns. Inter-annual EVI phenology anomalies ranged from -25% to 25%, with some highly anomalous values up to 200%. Monsoon crop phenology in the Central India site is highly sensitive to climate, especially the timing of the start and end of the monsoon and intensity of precipitation. In the Western India site, monsoon crop phenology is less sensitive to precipitation variability, yet shows considerable fluctuations in monsoon crop productivity across the years. Temperature is critically important for winter productivity across a range of crop and management types, such that irrigation might not provide a sufficient buffer against projected temperature increases. Better access to weather information and usage of climate-resilient crop types would play pivotal role in maintaining future productivity. Effective strategies to adapt to projected climate changes in the coming decades would also need to be tailored to regional biophysical and socio-economic conditions. Copyright © 2014 Elsevier Ltd. All rights reserved.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

ISCCP-M Data and Informtion

Atmospheric Science Data Center

2018-03-08

ISCCP-M Data and Information Global Cloud Process Studies in the Context of ... Climate Variability: Enhancement and Continuation of Data Analysis for the International Satellite Cloud Climatology Project (ISCCP) ...

Assessing Canada's Forest Carbon Sinks from 1901 TO 2008 BY Combining Inventory with Climate Data (Invited)

NASA Astrophysics Data System (ADS)

Chen, J. M.; Wu, C.; Gonsamo, A.; Kurz, W.; Hember, R.; Price, D. T.; Boisvenue, C.; Zhang, F.; Chang, K.

2013-12-01

The forest carbon cycle is not only controlled by climate, tree species and site conditions, but also by disturbance affecting the biomass and age of forest stands. The Carbon Budget Model of the Canadian forest sector (CBM-CFS3) calculates the complete forest carbon cycle by combining forest inventory data on forest species, biomass and stand age with empirical yield information and statistics on forest disturbances, management and land-use change. It is used for national reporting and climate policy purposes. The Integrated Terrestrial Ecosystem Carbon model (InTEC) is driven by remotely-sensed vegetation parameters (forest type, leaf area index, clumping index) and fire scar, soil and climate data and simulates forest growth and the carbon cycle as a function of stand age using a process-based approach. Gridded forest biomass, stand age and disturbance data based on forest inventory are also used as inputs to InTEC. Efforts are being made to enhance the CBM-CFS3's capacity to assess the impacts of global change on the forest carbon budget by utilizing InTEC process modeling methodology. For this purpose, InTEC is first implemented on 3432 permanent sampling plots in coastal and interior BC, and it is found that climate warming explained 70% and 75% of forest growth enhancement over the period from 1956 to 2001 in coastal and interior BC, respectively, and the remainder is attributed to CO2 and nitrogen fertilization effects. The growth enhancement, in terms of the increase in the stemwood accumulation rate after adjusting for the stand age effect, is about 24% for both areas over the same period. To assess the impact of climate change on the forest carbon cycle across Canada, polygon-based CBM and gridded InTEC results are aggregated to 60 reconciliation units (RU), and their interannual variabilities over the period from 1990 to 2008 are compared in each RU. CBM results show interannual variability in response to forest disturbance, while InTEC results show larger interannual variability because it is affected by both disturbance and climate. The impact of climate at the RU level is generally positive (increased sink) due to warming, but sometimes negative due to water stress. Averaged over Canada, climate warming induced a longer growing season by about one week from 1901 to 2008, enhancing the annual forest carbon sink by about 42×30 TgC y-1 over the period from 1990 to 2008, while CO2 and nitrogen fertilization effects each also contributed about the same amount to Canada's forest carbon sink.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-06-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall, the day-to-day variability is crucial for the risk of flooding, national water supply, and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the AR-5 of the Intergovernmental Panel on Climate Change, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. The relative increase by the period 2071-2100 with respect to the control period 1871-1900 ranges from 13% to 50% under the strongest scenario (Representative Concentration Pathways, RCP-8.5), in the 10 models with the most realistic monsoon climatology; and 13% to 85% when all the 20 models are considered. The spread across models reduces when variability increase per degree of global warming is considered, which is independent of the scenario in most models, and is 8% ± 4%/K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Online Impact Prioritization of Essential Climate Variables on Climate Change

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Ocean eddies and climate predictability

NASA Astrophysics Data System (ADS)

Kirtman, Ben P.; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

Ocean eddies and climate predictability.

PubMed

Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

Establishing the Environment: Setting a Supportive Climate.

ERIC Educational Resources Information Center

Phillips, Kristina M.

Supportive classroom environments can enhance students' learning about their own diversity as well as that of others. Discussing basic diversity variables such as gender, age, and race can raise awareness and conscious decision making about how students use and view communication in their everyday lives. A graduate student instructor enhances her…

Little Ice Age climatic erraticism as an analogue for future enhanced hydroclimatic variability across the American Southwest

PubMed Central

Loisel, Julie; MacDonald, Glen M.; Thomson, Marcus J.

2017-01-01

The American Southwest has experienced a series of severe droughts interspersed with strong wet episodes over the past decades, prompting questions about future climate patterns and potential intensification of weather disruptions under warming conditions. Here we show that interannual hydroclimatic variability in this region has displayed a significant level of non-stationarity over the past millennium. Our tree ring-based analysis of past drought indicates that the Little Ice Age (LIA) experienced high interannual hydroclimatic variability, similar to projections for the 21st century. This is contrary to the Medieval Climate Anomaly (MCA), which had reduced variability and therefore may be misleading as an analog for 21st century warming, notwithstanding its warm (and arid) conditions. Given past non-stationarity, and particularly erratic LIA, a ‘warm LIA’ climate scenario for the coming century that combines high precipitation variability (similar to LIA conditions) with warm and dry conditions (similar to MCA conditions) represents a plausible situation that is supported by recent climate simulations. Our comparison of tree ring-based drought analysis and records from the tropical Pacific Ocean suggests that changing variability in El Niño Southern Oscillation (ENSO) explains much of the contrasting variances between the MCA and LIA conditions across the American Southwest. Greater ENSO variability for the 21st century could be induced by a decrease in meridional sea surface temperature gradient caused by increased greenhouse gas concentration, as shown by several recent climate modeling experiments. Overall, these results coupled with the paleo-record suggests that using the erratic LIA conditions as benchmarks for past hydroclimatic variability can be useful for developing future water-resource management and drought and flood hazard mitigation strategies in the Southwest. PMID:29036207

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

NASA Astrophysics Data System (ADS)

Lorenz, Ruth; Argüeso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Chéruy, Frédérique; Ducharne, Agnès.; Hagemann, Stefan; Meier, Arndt; Milly, P. C. D.; Seneviratne, Sonia I.

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Seasonal modulation of the Asian summer monsoon between the Medieval Warm Period and Little Ice Age: a multi model study

NASA Astrophysics Data System (ADS)

Kamae, Youichi; Kawana, Toshi; Oshiro, Megumi; Ueda, Hiroaki

2017-12-01

Instrumental and proxy records indicate remarkable global climate variability over the last millennium, influenced by solar irradiance, Earth's orbital parameters, volcanic eruptions and human activities. Numerical model simulations and proxy data suggest an enhanced Asian summer monsoon during the Medieval Warm Period (MWP) compared to the Little Ice Age (LIA). Using multiple climate model simulations, we show that anomalous seasonal insolation over the Northern Hemisphere due to a long cycle of orbital parameters results in a modulation of the Asian summer monsoon transition between the MWP and LIA. Ten climate model simulations prescribing historical radiative forcing that includes orbital parameters consistently reproduce an enhanced MWP Asian monsoon in late summer and a weakened monsoon in early summer. Weakened, then enhanced Northern Hemisphere insolation before and after June leads to a seasonally asymmetric temperature response over the Eurasian continent, resulting in a seasonal reversal of the signs of MWP-LIA anomalies in land-sea thermal contrast, atmospheric circulation, and rainfall from early to late summer. This seasonal asymmetry in monsoon response is consistently found among the different climate models and is reproduced by an idealized model simulation forced solely by orbital parameters. The results of this study indicate that slow variation in the Earth's orbital parameters contributes to centennial variability in the Asian monsoon transition.[Figure not available: see fulltext.

Urban green land cover changes and their relation to climatic variables in an anthropogenically impacted area

NASA Astrophysics Data System (ADS)

Zoran, Maria A.; Dida, Adrian I.

2017-10-01

Urban green areas are experiencing rapid land cover change caused by human-induced land degradation and extreme climatic events. Vegetation index time series provide a useful way to monitor urban vegetation phenological variations. This study quantitatively describes Normalized Difference Vegetation Index NDVI) /Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) temporal changes for Bucharest metropolitan region land cover in Romania from the perspective of vegetation phenology and its relation with climate changes and extreme climate events. The time series from 2000 to 2016 of the NOAA AVHRR and MODIS Terra/Aqua satellite data were analyzed to extract anomalies. Time series of climatic variables were also analyzed through anomaly detection techniques and the Fourier Transform. Correlations between NDVI/EVI time series and climatic variables were computed. Temperature, rainfall and radiation were significantly correlated with almost all land-cover classes for the harmonic analysis amplitude term. However, vegetation phenology was not correlated with climatic variables for the harmonic analysis phase term suggesting a delay between climatic variations and vegetation response. Training and validation were based on a reference dataset collected from IKONOS high resolution remote sensing data. The mean detection accuracy for period 2000- 2016 was assessed to be of 87%, with a reasonable balance between change commission errors (19.3%), change omission errors (24.7%), and Kappa coefficient of 0.73. This paper demonstrates the potential of moderate - and high resolution, multispectral imagery to map and monitor the evolution of the physical urban green land cover under climate and anthropogenic pressure.

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

NASA Astrophysics Data System (ADS)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

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

NASA Astrophysics Data System (ADS)

Horton, Radley M.

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

Impact of anthropogenic climate change on wildfire across western US forests

PubMed Central

Williams, A. Park

2016-01-01

Increased forest fire activity across the western continental United States (US) in recent decades has likely been enabled by a number of factors, including the legacy of fire suppression and human settlement, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western United States. Anthropogenic increases in temperature and vapor pressure deficit significantly enhanced fuel aridity across western US forests over the past several decades and, during 2000–2015, contributed to 75% more forested area experiencing high (>1 σ) fire-season fuel aridity and an average of nine additional days per year of high fire potential. Anthropogenic climate change accounted for ∼55% of observed increases in fuel aridity from 1979 to 2015 across western US forests, highlighting both anthropogenic climate change and natural climate variability as important contributors to increased wildfire potential in recent decades. We estimate that human-caused climate change contributed to an additional 4.2 million ha of forest fire area during 1984–2015, nearly doubling the forest fire area expected in its absence. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a driver of increased forest fire activity and should continue to do so while fuels are not limiting. PMID:27791053

To what extent does climate explain variations in reported malaria cases in early 20th century Uganda?

PubMed

Tompkins, Adrian M; Larsen, Laragh; McCreesh, Nicky; Taylor, David

2016-03-31

Malaria case statistics were analysed for the period 1926 to 1960 to identify inter-annual variations in malaria cases for the Uganda Protectorate. The analysis shows the mid-to-late 1930s to be a period of increased reported cases. After World War II, malaria cases trend down to a relative minimum in the early 1950s, before increasing rapidly after 1953 to the end of the decade. Data for the Western Province confirm these national trends, which at the time were attributed to a wide range of causes, including land development and management schemes, population mobility, interventions and misdiagnosis. Climate was occasionally proposed as a contributor to enhanced case numbers, and unusual precipitation patterns were held responsible; temperature was rarely, if ever, considered. In this study, a dynamical malaria model was driven with available precipitation and temperature data from the period for five stations located across a range of environments in Uganda. In line with the historical data, the simulations produced relatively enhanced transmission in the 1930s, although there is considerable variability between locations. In all locations, malaria transmission was low in the late 1940s and early 1950s, steeply increasing after 1954. Results indicate that past climate variability explains some of the variations in numbers of reported malaria cases. The impact of multiannual variability in temperature, while only on the order of 0.5°C, was sufficient to drive some of the trends observed in the statistics and thus the role of climate was likely underestimated in the contemporary reports. As the elimination campaigns of the 1960s followed this partly climate-driven increase in malaria, this emphasises the need to account for climate when planning and evaluating intervention strategies.

Sustained Satellite Missions for Climate Data Records

NASA Technical Reports Server (NTRS)

Halpern, David

2012-01-01

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

Attributing the effects of climate on phenology change suggests high sensitivity in coastal zones

NASA Astrophysics Data System (ADS)

Seyednasrollah, B.; Clark, J. S.

2015-12-01

The impact of climate change on spring phenology depends on many variables that cannot be separated using current models. Phenology can influence carbon sequestration, plant nutrition, forest health, and species distributions. Leaf phenology is sensitive to changes of environmental factors, including climate, species composition, latitude, and solar radiation. The many variables and their interactions frustrate efforts to attribute variation to climate change. We developed a Bayesian framework to quantify the influence of environment on the speed of forest green-up. This study presents a state-space hierarchical model to infer and predict change in forest greenness over time using satellite observations and ground measurements. The framework accommodates both observation and process errors and it allows for main effects of variables and their interactions. We used daily spaceborne remotely sensed data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify temporal variability in the enhanced vegetation index (EVI) along a habitat gradient in the Southeastern United States. The ground measurements of meteorological parameters are obtained from study sites located in the Appalachian Mountains, the Piedmont and the Atlantic Coastal Plain between years 2000 and 2015. Results suggest that warming accelerates spring green-up in the Coastal Plain to a greater degree than in the Piedmont and Appalachian. In other words, regardless of variation in the timing of spring onset, the rate of greenness in non-coastal zones decreases with increasing temperature and hence with time over the spring transitional period. However, in coastal zones, as air temperature increases, leaf expansion becomes faster. This may indicate relative vulnerability to warming in non-coastal regions where moisture could be a limiting factor, whereas high temperatures in regions close to the coast enhance forest physiological activities. Model predictions agree with the remotely sensed observations of the enhanced vegetation index. These findings could be used in forest managements for identifying vulnerable forests based on their habitat type and hydrological status.

Identifying bird and reptile vulnerabilities to climate change in the southwestern United States

USGS Publications Warehouse

Hatten, James R.; Giermakowski, J. Tomasz; Holmes, Jennifer A.; Nowak, Erika M.; Johnson, Matthew J.; Ironside, Kirsten E.; van Riper, Charles; Peters, Michael; Truettner, Charles; Cole, Kenneth L.

2016-07-06

Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.

Topography alters tree growth–climate relationships in a semi-arid forested catchment

DOE PAGES

Adams, Hallie R.; Barnard, Holly R.; Loomis, Alexander K.

2014-11-26

Topography and climate play an integral role in the spatial variability and annual dynamics of aboveground carbon sequestration. Despite knowledge of vegetation–climate–topography relationships on the landscape and hillslope scales, little is known about the influence of complex terrain coupled with hydrologic and topoclimatic variation on tree growth and physiology at the catchment scale. Climate change predictions for the semi-arid, western United States include increased temperatures, more frequent and extreme drought events, and decreases in snowpack, all of which put forests at risk of drought induced mortality and enhanced susceptibility to disturbance events. In this study, we determine how species-specific treemore » growth patterns and water use efficiency respond to interannual climate variability and how this response varies with topographic position. We found that Pinus contorta and Pinus ponderosa both show significant decreases in growth with water-limiting climate conditions, but complex terrain mediates this response by controlling moisture conditions in variable topoclimates. Foliar carbon isotope analyses show increased water use efficiency during drought for Pinus contorta, but indicate no significant difference in water use efficiency of Pinus ponderosa between a drought year and a non-drought year. The responses of the two pine species to climate indicate that semi-arid forests are especially susceptible to changes and risks posed by climate change and that topographic variability will likely play a significant role in determining the future vegetation patterns of semi-arid systems.« less

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul

2016-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning retrospective predictions at the decadal (5-years), seasonal and sub-seasonal time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and sub-seasonal time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; van den Hurk, B.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2016-12-01

The European consortium earth system model (EC-Earth; http://www.ec-earth.org) has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-08-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (twentieth century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2 m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Multi-scale enhancement of climate prediction over land by increasing the model sensitivity to vegetation variability in EC-Earth

NASA Astrophysics Data System (ADS)

Alessandri, Andrea; Catalano, Franco; De Felice, Matteo; Van Den Hurk, Bart; Doblas Reyes, Francisco; Boussetta, Souhail; Balsamo, Gianpaolo; Miller, Paul A.

2017-04-01

The EC-Earth earth system model has been recently developed to include the dynamics of vegetation. In its original formulation, vegetation variability is simply operated by the Leaf Area Index (LAI), which affects climate basically by changing the vegetation physiological resistance to evapotranspiration. This coupling has been found to have only a weak effect on the surface climate modeled by EC-Earth. In reality, the effective sub-grid vegetation fractional coverage will vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the albedo, surface roughness and soil field capacity. To adequately represent this effect in EC-Earth, we included an exponential dependence of the vegetation cover on the LAI. By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal and weather time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation cover tends to correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.

Establishing the common patterns of future tropospheric ozone under diverse climate change scenarios

NASA Astrophysics Data System (ADS)

Jimenez-Guerrero, Pedro; Gómez-Navarro, Juan J.; Jerez, Sonia; Lorente-Plazas, Raquel; Baro, Rocio; Montávez, Juan P.

2013-04-01

The impacts of climate change on air quality may affect long-term air quality planning. However, the policies aimed at improving air quality in the EU directives have not accounted for the variations in the climate. Climate change alone influences future air quality through modifications of gas-phase chemistry, transport, removal, and natural emissions. As such, the aim of this work is to check whether the projected changes in gas-phase air pollution over Europe depends on the scenario driving the regional simulation. For this purpose, two full-transient regional climate change-air quality projections for the first half of the XXI century (1991-2050) have been carried out with MM5+CHIMERE system, including A2 and B2 SRES scenarios. Experiments span the periods 1971-2000, as a reference, and 2071-2100, as future enhanced greenhouse gas and aerosol scenarios (SRES A2 and B2). The atmospheric simulations have a horizontal resolution of 25 km and 23 vertical layers up to 100 mb, and were driven by ECHO-G global climate model outputs. The analysis focuses on the connection between meteorological and air quality variables. Our simulations suggest that the modes of variability for tropospheric ozone and their main precursors hardly change under different SRES scenarios. The effect of changing scenarios has to be sought in the intensity of the changing signal, rather than in the spatial structure of the variation patterns, since the correlation between the spatial patterns of variability in A2 and B2 simulation is r > 0.75 for all gas-phase pollutants included in this study. In both cases, full-transient simulations indicate an enhanced enhanced chemical activity under future scenarios. The causes for tropospheric ozone variations have to be sought in a multiplicity of climate factors, such as increased temperature, different distribution of precipitation patterns across Europe, increased photolysis of primary and secondary pollutants due to lower cloudiness, etc. Nonetheless, according to the results of this work future ozone is conditioned by the dependence of biogenic emissions on the climatological patterns of variability. In this sense, ozone over Europe is mainly driven by the warming-induced increase in biogenic emitting activity (vegetation is kept invariable in the simulations, but estimations of these emissions strongly depends on shortwave radiation and temperature, which are substantially modified in climatic simulations). Moreover, one of the most important drivers for ozone increase is the decrease of cloudiness (related to stronger solar radiation) mostly over southern Europe at the first half of the XXI century. However, given the large uncertainty isoprene sensitivity to climate change and the large uncertainties associated to the cloudiness projections, these results should be carefully considered.

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.

Evaluating Moisture Control of Variable-Capacity Heat Pumps in Mechanically Ventilated, Low-Load Homes in Climate Zone 2A

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

Martin, Eric; Withers, Chuck; McIlvaine, Janet

Low-load homes can present a challenge when selecting appropriate space-conditioning equipment. Conventional, fixed-capacity heating and cooling equipment is often oversized for small homes, causing increased first costs and operating costs. This report evaluates the performance of variable-capacity comfort systems, with a focus on inverter-driven, variable-capacity systems, as well as proposed system enhancements.

Using the NASA Giovanni DICCE Portal to Investigate Land-Ocean Linkages with Satellite and Model Data

NASA Technical Reports Server (NTRS)

Acker, James G.; Zalles, Daniel; Krumhansl, Ruth

2012-01-01

Data-enhanced Investigations for Climate Change Education (DICCE), a NASA climate change education project, employs the NASA Giovanni data system to enable teachers to create climate-related classroom projects using selected satellite and assimilated model data. The easy-to-use DICCE Giovanni portal (DICCE-G) provides data parameters relevant to oceanic, terrestrial, and atmospheric processes. Participants will explore land-ocean linkages using the available data in the DICCE-G portal, in particular focusing on temperature, ocean biology, and precipitation variability related to El Ni?o and La Ni?a events. The demonstration includes the enhanced information for educators developed for the DICCE-G portal. The prototype DICCE Learning Environment (DICCE-LE) for classroom project development will also be demonstrated.

Evaluating the variability in surface water reservoir planning characteristics during climate change impacts assessment

NASA Astrophysics Data System (ADS)

Soundharajan, Bankaru-Swamy; Adeloye, Adebayo J.; Remesan, Renji

2016-07-01

This study employed a Monte-Carlo simulation approach to characterise the uncertainties in climate change induced variations in storage requirements and performance (reliability (time- and volume-based), resilience, vulnerability and sustainability) of surface water reservoirs. Using a calibrated rainfall-runoff (R-R) model, the baseline runoff scenario was first simulated. The R-R inputs (rainfall and temperature) were then perturbed using plausible delta-changes to produce simulated climate change runoff scenarios. Stochastic models of the runoff were developed and used to generate ensembles of both the current and climate-change-perturbed future runoff scenarios. The resulting runoff ensembles were used to force simulation models of the behaviour of the reservoir to produce 'populations' of required reservoir storage capacity to meet demands, and the performance. Comparing these parameters between the current and the perturbed provided the population of climate change effects which was then analysed to determine the variability in the impacts. The methodology was applied to the Pong reservoir on the Beas River in northern India. The reservoir serves irrigation and hydropower needs and the hydrology of the catchment is highly influenced by Himalayan seasonal snow and glaciers, and Monsoon rainfall, both of which are predicted to change due to climate change. The results show that required reservoir capacity is highly variable with a coefficient of variation (CV) as high as 0.3 as the future climate becomes drier. Of the performance indices, the vulnerability recorded the highest variability (CV up to 0.5) while the volume-based reliability was the least variable. Such variabilities or uncertainties will, no doubt, complicate the development of climate change adaptation measures; however, knowledge of their sheer magnitudes as obtained in this study will help in the formulation of appropriate policy and technical interventions for sustaining and possibly enhancing water security for irrigation and other uses served by Pong reservoir.

Late Cenozoic Climate Change and its Implications on the Denudation of Orogen Syntaxes

NASA Astrophysics Data System (ADS)

Mutz, Sebastian; Ehlers, Todd

2017-04-01

The denudation history of active orogens is often interpreted in the context of modern climate gradients. Despite the influence of climatic conditions on erosion rates, information about paleoclimate evolution is often not available and thus not considered when denudation histories are interpreted. In this study, we analyze output from paleoclimate simulations conducted with ECHAM5-wiso at T159 (ca. 80x80km) resolution. Specifically, we analyze simulations of pre-industrial (PI, pre-1850), Mid-Holocene (MH, ca. 6ka), Last Glacial Maximum (LGM, ca. 21ka) and Pliocene (PLIO, ca. 3ka) climates and focus on a selection of orogen syntaxes as study regions (e.g. Himalaya, SE Alaska, Cascadia, and Central Andes). For the selected region, we carry out a cluster analysis using a hybrid of hierarchical and k-means clustering procedures using mean annual temperature (MAT), temperature amplitude, mean annual precipitation (MAP), precipitation amplitude and u-wind and v-wind in different months to provide a general overview of paleoclimates in the study regions. Additionally, we quantify differences between paleoclimates by applying two-group linear discrimination analyses to the simulation output for a similar selection of variables. Results indicate the largest differences to the PI climate are observed for the LGM and PLIO climates in the form of widespread cooling and reduced precipitation in the LGM and warming and enhanced precipitation during the PLIO. These global trends can be observed for most locations in the investigated areas, but the strength varies regionally and the trends in precipitation are less uniform than trends in temperatures. The LGM climate shows the largest deviation in annual precipitation from the PI climate, and shows enhanced precipitation in the temperate Andes, and coastal regions for both SE Alaska and the US Pacific Northwest Pacific. Furthermore, LGM precipitation is reduced in the western Himalayas and enhanced in the eastern Himalayas, resulting in a shift of the wettest regional climates eastward along the orogen towards the eastern syntax. The cluster-analysis results also suggest more climatic variability across latitudes east of the Andes in the PLIO climate than in other time-slice experiments conducted here. Results from the discriminant analysis show that the quantified differences in climate and the relative contribution to these differences by each of the analyzed parameters are highly variable in space for each of the paleoclimates. Taken together, these results highlight significant changes in Late Cenozoic regional climatology over active orogens on time scales ranging from glacial cycles to geologic. As a result, future interpretation of recent and paleo denudation rates in these areas from sediment flux inventories, cosmogenic radionuclides, or low-temperature thermochronology techniques warrant careful consideration of these changes.

Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

NASA Astrophysics Data System (ADS)

Ferrarini, Alessandro; Alsafran, Mohammed H. S. A.; Dai, Junhu; Alatalo, Juha M.

2018-04-01

Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

Estimates of late Cenozoic climate change relevant to Earth surface processes in tectonically active orogens

NASA Astrophysics Data System (ADS)

Mutz, Sebastian G.; Ehlers, Todd A.; Werner, Martin; Lohmann, Gerrit; Stepanek, Christian; Li, Jingmin

2018-04-01

The denudation history of active orogens is often interpreted in the context of modern climate gradients. Here we address the validity of this approach and ask what are the spatial and temporal variations in palaeoclimate for a latitudinally diverse range of active orogens? We do this using high-resolution (T159, ca. 80 × 80 km at the Equator) palaeoclimate simulations from the ECHAM5 global atmospheric general circulation model and a statistical cluster analysis of climate over different orogens (Andes, Himalayas, SE Alaska, Pacific NW USA). Time periods and boundary conditions considered include the Pliocene (PLIO, ˜ 3 Ma), the Last Glacial Maximum (LGM, ˜ 21 ka), mid-Holocene (MH, ˜ 6 ka), and pre-industrial (PI, reference year 1850). The regional simulated climates of each orogen are described by means of cluster analyses based on the variability in precipitation, 2 m air temperature, the intra-annual amplitude of these values, and monsoonal wind speeds where appropriate. Results indicate the largest differences in the PI climate existed for the LGM and PLIO climates in the form of widespread cooling and reduced precipitation in the LGM and warming and enhanced precipitation during the PLIO. The LGM climate shows the largest deviation in annual precipitation from the PI climate and shows enhanced precipitation in the temperate Andes and coastal regions for both SE Alaska and the US Pacific Northwest. Furthermore, LGM precipitation is reduced in the western Himalayas and enhanced in the eastern Himalayas, resulting in a shift of the wettest regional climates eastward along the orogen. The cluster-analysis results also suggest more climatic variability across latitudes east of the Andes in the PLIO climate than in other time slice experiments conducted here. Taken together, these results highlight significant changes in late Cenozoic regional climatology over the last ˜ 3 Myr. Comparison of simulated climate with proxy-based reconstructions for the MH and LGM reveal satisfactory to good performance of the model in reproducing precipitation changes, although in some cases discrepancies between neighbouring proxy observations highlight contradictions between proxy observations themselves. Finally, we document regions where the largest magnitudes of late Cenozoic changes in precipitation and temperature occur and offer the highest potential for future observational studies that quantify the impact of climate change on denudation and weathering rates.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

The Indian summer monsoon shapes the livelihood of a large share of the world's population. About 80% of annual precipitation over India occurs during the monsoon season from June through September. Next to its seasonal mean rainfall the day-to-day variability is crucial for the risk of flooding, national water supply and agricultural productivity. Here we show that the latest ensemble of climate model simulations, prepared for the IPCC's AR-5, consistently projects significant increases in day-to-day rainfall variability under unmitigated climate change. While all models show an increase in day-to-day variability, some models are more realistic in capturing the observed seasonal mean rainfall over India than others. While no model's monsoon rainfall exceeds the observed value by more than two standard deviations, half of the models simulate a significantly weaker monsoon than observed. The relative increase in day-to-day variability by the year 2100 ranges from 15% to 48% under the strongest scenario (RCP-8.5), in the ten models which capture seasonal mean rainfall closest to observations. The variability increase per degree of global warming is independent of the scenario in most models, and is 8% +/- 4% per K on average. This consistent projection across 20 comprehensive climate models provides confidence in the results and suggests the necessity of profound adaptation measures in the case of unmitigated climate change.

Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble

USGS Publications Warehouse

Lorenz, Ruth; Argueso, Daniel; Donat, Markus G.; Pitman, Andrew J.; van den Hurk, Bart; Berg, Alexis; Lawrence, David M.; Cheruy, Frederique; Ducharne, Agnes; Hagemann, Stefan; Meier, Arndt; Milly, Paul C.D.; Seneviratne, Sonia I

2016-01-01

We examine how soil moisture variability and trends affect the simulation of temperature and precipitation extremes in six global climate models using the experimental protocol of the Global Land-Atmosphere Coupling Experiment of the Coupled Model Intercomparison Project, Phase 5 (GLACE-CMIP5). This protocol enables separate examinations of the influences of soil moisture variability and trends on the intensity, frequency, and duration of climate extremes by the end of the 21st century under a business-as-usual (Representative Concentration Pathway 8.5) emission scenario. Removing soil moisture variability significantly reduces temperature extremes over most continental surfaces, while wet precipitation extremes are enhanced in the tropics. Projected drying trends in soil moisture lead to increases in intensity, frequency, and duration of temperature extremes by the end of the 21st century. Wet precipitation extremes are decreased in the tropics with soil moisture trends in the simulations, while dry extremes are enhanced in some regions, in particular the Mediterranean and Australia. However, the ensemble results mask considerable differences in the soil moisture trends simulated by the six climate models. We find that the large differences between the models in soil moisture trends, which are related to an unknown combination of differences in atmospheric forcing (precipitation, net radiation), flux partitioning at the land surface, and how soil moisture is parameterized, imply considerable uncertainty in future changes in climate extremes.

Advanced spectral methods for climatic time series

USGS Publications Warehouse

Ghil, M.; Allen, M.R.; Dettinger, M.D.; Ide, K.; Kondrashov, D.; Mann, M.E.; Robertson, A.W.; Saunders, A.; Tian, Y.; Varadi, F.; Yiou, P.

2002-01-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

Decadal slowdown in global air temperature rise triggered by variability in the Atlantic Meridional Overturning Circulation

NASA Astrophysics Data System (ADS)

England, Matthew H.

2015-04-01

Various explanations have been proposed for the recent slowdown in global surface air temperature (SAT) rise, either involving enhanced ocean heat uptake or reduced radiation reaching Earth's surface. Among the mechanisms postulated involving enhanced ocean heat uptake, past work has argued for both a Pacific and Atlantic origin, with additional contributions from the Southern Ocean. Here we examine the mechanisms driving 'hiatus' periods originating out of the Atlantic Ocean. We show that while Atlantic-driven hiatuses are entirely plausible and consistent with known climate feedbacks associated with variability in the Atlantic Meridional Overturning Circulation (AMOC), the present climate state is configured to enhance global-average SAT, not reduce it. We show that Atlantic hiatuses are instead characterised by anomalously cool fresh oceanic conditions in the North Atlantic, with the atmosphere advecting the cool temperature signature zonally. Compared to the 1980s and 1990s, however, the mean climate since 2001 has been characterised by a warm saline North Atlantic, suggesting the AMOC cannot be implicated as a direct driver of the current hiatus. We further discuss the impacts of a warm tropical Atlantic on the unprecedented trade wind acceleration in the Pacific Ocean, and propose that this is the main way that the Atlantic has contributed to the present "false pause" in global warming.

Organizational climate and self-efficacy as predictors of staff strain in caring for dementia residents: A mediation model.

PubMed

Karantzas, Gery C; McCabe, Marita P; Mellor, David; Von Treuer, Kathryn; Davison, Tanya E; O'Connor, Daniel; Haselden, Rachel; Konis, Anastasia

2016-01-01

To date, no research has investigated how the organizational climate of aged care influences the self-efficacy of staff in caring for residents with dementia, or, how self-efficacy is associated with the strain experienced by staff. This study sought to investigate the extent to which the self-efficacy of aged care staff mediates the association between organizational climate variables (such as autonomy, trusting and supportive workplace relations, and the recognition of competence and ability, and perceptions of workplace pressure) and staff strain. A cross-sectional survey design was implemented in which 255 residential aged care staff recruited across aged care facilities in Melbourne, Australia. Staff completed self-report measures of organizational climate, self-efficacy, and strains in caring for residents with dementia. Indirect effects analyses using bootstrapping indicated that self-efficacy of staff mediated the association between the organizational climate variables of autonomy, trust, support, pressure, and staff strain. The findings of this study emphasize that the aged care sector needs to target organizational climate variables that enhance the self-efficacy of staff, and that this in turn, can help ameliorate the strain experienced by staff caring for residents experiencing dementia. Copyright © 2016. Published by Elsevier Ireland Ltd.

Climate Informed Economic Instruments to Enhance Urban Water Supply Resilience to Hydroclimatological Variability and Change

NASA Astrophysics Data System (ADS)

Brown, C.; Carriquiry, M.; Souza Filho, F. A.

2006-12-01

Hydroclimatological variability presents acute challenges to urban water supply providers. The impact is often most severe in developing nations where hydrologic and climate variability can be very high, water demand is unmet and increasing, and the financial resources to mitigate the social effects of that variability are limited. Furthermore, existing urban water systems face a reduced solution space, constrained by competing and conflicting interests, such as irrigation demand, recreation and hydropower production, and new (relative to system design) demands to satisfy environmental flow requirements. These constraints magnify the impacts of hydroclimatic variability and increase the vulnerability of urban areas to climate change. The high economic and social costs of structural responses to hydrologic variability, such as groundwater utilization and the construction or expansion of dams, create a need for innovative alternatives. Advances in hydrologic and climate forecasting, and the increasing sophistication and acceptance of incentive-based mechanisms for achieving economically efficient water allocation offer potential for improving the resilience of existing water systems to the challenge of variable supply. This presentation will explore the performance of a system of climate informed economic instruments designed to facilitate the reduction of hydroclimatologic variability-induced impacts on water-sensitive stakeholders. The system is comprised of bulk water option contracts between urban water suppliers and agricultural users and insurance indexed on reservoir inflows designed to cover the financial needs of the water supplier in situations where the option is likely to be exercised. Contract and insurance parameters are linked to forecasts and the evolution of seasonal precipitation and streamflow and designed for financial and political viability. A simulation of system performance is presented based on ongoing work in Metro Manila, Philippines. The system is further evaluated as an alternative strategy to infrastructure expansion for climate change adaptation in the water resources sector.

Spatial match-mismatch between juvenile fish and prey provides a mechanism for recruitment variability across contrasting climate conditions in the eastern Bering Sea.

PubMed

Siddon, Elizabeth Calvert; Kristiansen, Trond; Mueter, Franz J; Holsman, Kirstin K; Heintz, Ron A; Farley, Edward V

2013-01-01

Understanding mechanisms behind variability in early life survival of marine fishes through modeling efforts can improve predictive capabilities for recruitment success under changing climate conditions. Walleye pollock (Theragra chalcogramma) support the largest single-species commercial fishery in the United States and represent an ecologically important component of the Bering Sea ecosystem. Variability in walleye pollock growth and survival is structured in part by climate-driven bottom-up control of zooplankton composition. We used two modeling approaches, informed by observations, to understand the roles of prey quality, prey composition, and water temperature on juvenile walleye pollock growth: (1) a bioenergetics model that included local predator and prey energy densities, and (2) an individual-based model that included a mechanistic feeding component dependent on larval development and behavior, local prey densities and size, and physical oceanographic conditions. Prey composition in late-summer shifted from predominantly smaller copepod species in the warmer 2005 season to larger species in the cooler 2010 season, reflecting differences in zooplankton composition between years. In 2010, the main prey of juvenile walleye pollock were more abundant, had greater biomass, and higher mean energy density, resulting in better growth conditions. Moreover, spatial patterns in prey composition and water temperature lead to areas of enhanced growth, or growth 'hot spots', for juvenile walleye pollock and survival may be enhanced when fish overlap with these areas. This study provides evidence that a spatial mismatch between juvenile walleye pollock and growth 'hot spots' in 2005 contributed to poor recruitment while a higher degree of overlap in 2010 resulted in improved recruitment. Our results indicate that climate-driven changes in prey quality and composition can impact growth of juvenile walleye pollock, potentially severely affecting recruitment variability.

The Laminated Marca Shale: High-Frequency Climate Cycles From the Latest Cretaceous

NASA Astrophysics Data System (ADS)

Davies, A.; Kemp, A. E.; Weedon, G.; Barron, J. A.

2005-12-01

The Latest Cretaceous (Maastrichtian) Marca Shale Member, California, displays a well-preserved record of alternating terrigenous and diatomaceous laminae couplets, remarkably similar in lithology to recent laminated sediments from the Gulf of California and Santa Barbara Basin. This similarity, together with the recognition of intra- and inter-annual variability in the diatom flora, implies an annual origin for these couplets. High-resolution backscattered electron imagery has identified two sublaminae types within the varved succession; near monospecific lamina of Chaetoceros-type resting spore and of large Azpeitiopsis morenoensis. The composition and occurrence of these laminae is similar to ENSO forced intra-annual variability of diatom flora along the modern Californian margin. Relative thickness variations in terrigenous and biogenic laminae (proxies for precipitation and productivity respectively) also exhibit similar characteristics to variability in Quaternary varves from the Santa Barbara Basin, shown to be imparted by ENSO forcing. In order to track changes in the levels of bottom water oxygenation within the basin, a bioturbation index was established. Periods when bioturbation was minimal (enhanced benthic anoxia) coincide with times of greatest diatomaceous export flux and also lowest flux of detrital material. Conversely, periods of enhanced bioturbation correspond with reduced diatomaceous export flux and an increased flux of detrital material, comparable with ENSO forced variations in diatomaceous and terrigenous export flux and associated benthic oxygenation levels in Pleistocene varves off the Californian margin. Power spectra obtained from time-series analysis of the bioturbation index and laminae thickness variations exhibit strong signals within the ENSO band. This research implies that high-frequency climate perturbations are inherent components of the climate system and that ENSO-type variability was not confined to the dynamic climate system of the Quaternary, but occurred as far back as the Cretaceous. These results also add to the growing body of evidence which indicate that warm end-member climate states are not characterised by a permanent El Nino state.

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.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

How important is interannual variability in the climatic interpretation of moraine sequences?

NASA Astrophysics Data System (ADS)

Leonard, E. M.; Laabs, B. J. C.; Plummer, M. A.

2017-12-01

Mountain glaciers respond to both long-term climate and interannual forcing. Anderson et al. (2014) pointed out that kilometer-scale fluctuations in glacier length may result from interannual variability in temperature and precipitation given a "steady" climate with no long-term trends in mean or variability of temperature and precipitation. They cautioned that use of outermost moraines from the Last Glacial Maximum (LGM) as indicators of LGM climate will, because of the role of interannual forcing, result in overestimation of the magnitude of long-term temperature depression and/or precipitation enhancement. Here we assess the implications of these ideas, by examining the effect of interannual variability on glacier length and inferred magnitude of LGM climate change from present under both an assumed steady LGM climate and an LGM climate with low-magnitude, long-period variation in summer temperature and annual precipitation. We employ both the original 1-stage linear glacier model (Roe and O'Neal, 2009) used by Anderson et al. (2014) and a newer 3-stage linear model (Roe and Baker, 2014). We apply the models to two reconstructed LGM glaciers in the Colorado Sangre de Cristo Mountains. Three-stage-model results indicate that, absent long-term variations through a 7500-year-long LGM, interannual variability would result in overestimation of mean LGM temperature depression from the outermost moraine of 0.2-0.6°C. If small long-term cyclic variations of temperature (±0.5°C) and precipitation (±5%) are introduced, the overestimation of LGM temperature depression reduces to less than 0.4°C, and if slightly greater long-term variation (±1.0°C and ±10% precipitation) is introduced, the magnitude of overestimation is 0.3°C or less. Interannual variability may produce a moraine sequence that differs from the sequence that would be expected were glacier length forced only by long-term climate. With small amplitude (±0.5°C and ±5% precipitation) long-term variation, the moraine sequence expected if forced by a combination of interannual variability and long-term climate differs from that expected based on long-term climate forcing alone in 38% of model runs. With the larger amplitude long-term forcing (±1.0°C and ±10% precipitation) this difference occurs in 20% of model runs.

Assessment of impact of climate change and adaptation strategies on maize production in Uganda

NASA Astrophysics Data System (ADS)

Kikoyo, Duncan A.; Nobert, Joel

2016-06-01

Globally, various climatic studies have estimated a reduction of crop yields due to changes in surface temperature and precipitation especially for the developing countries which is heavily dependent on agriculture and lacks resources to counter the negative effects of climate change. Uganda's economy and the wellbeing of its populace depend on rain-fed agriculture which is susceptible to climate change. This study quantified the impacts of climate change and variability in Uganda and how coping strategies can enhance crop production against climate change and/or variability. The study used statistical methods to establish various climate change and variability indicators across the country, and uses the FAO AquaCrop model to simulate yields under possible future climate scenarios with and without adaptation strategies. Maize, the most widely grown crop was used for the study. Meteorological, soil and crop data were collected for various districts representing the maize growing ecological zones in the country. Based on this study, it was found that temperatures have increased by up to 1 °C across much of Uganda since the 1970s, with rates of warming around 0.3 °C per decade across the country. High altitude, low rainfall regions experience the highest level of warming, with over 0.5 °C/decade recorded in Kasese. Rainfall is variable and does not follow a specific significant increasing or decreasing trend. For both future climate scenarios, Maize yields will reduce in excess of 4.7% for the fast warming-low rainfall climates but increase on average by 3.5% for slow warming-high rainfall regions, by 2050. Improved soil fertility can improve yields by over 50% while mulching and use of surface water management practices improve yields by single digit percentages. The use of fertilizer application needs to go hand in hand with other water management strategies since more yields as a result of the improved soil fertility leads to increased water stress, especially for the dry climates.

Mitigating climate change through managing constructed-microbial communities in agriculture

DOE PAGES

Hamilton, Cyd E.; Bever, James D.; Labbe, Jessy; ...

2015-10-27

The importance of increasing crop production while reducing resource inputs and land-use change cannot be overstated especially in light of climate change and a human population growth projected to reach nine billion this century. Here, mutualistic plant microbe interactions offer a novel approach to enhance agricultural productivity while reducing environmental costs. In concert with other novel agronomic technologies and management, plant-microbial mutualisms could help increase crop production and reduce yield losses by improving resistance and/or resilience to edaphic, biologic, and climatic variability from both bottom-up and top-down perspectives.

Mitigating climate change through managing constructed-microbial communities in agriculture

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

Hamilton, Cyd E.; Bever, James D.; Labbe, Jessy

The importance of increasing crop production while reducing resource inputs and land-use change cannot be overstated especially in light of climate change and a human population growth projected to reach nine billion this century. Here, mutualistic plant microbe interactions offer a novel approach to enhance agricultural productivity while reducing environmental costs. In concert with other novel agronomic technologies and management, plant-microbial mutualisms could help increase crop production and reduce yield losses by improving resistance and/or resilience to edaphic, biologic, and climatic variability from both bottom-up and top-down perspectives.

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.

Long-term climate patterns in Alaskan surface temperature and precipitation and their biological consequences

USGS Publications Warehouse

Simpson, James J.; Hufford, Gary L.; Fleming, Michael D.; Berg, Jared S.; Ashton, J.B.

2002-01-01

Mean monthly climate maps of Alaskan surface temperature and precipitation produced by the parameter-elevation regression on independent slopes model (PRISM) were analyzed. Alaska is divided into interior and coastal zones with consistent but different climatic variability separated by a transition region; it has maximum interannual variability but low long-term mean variability. Pacific decadal oscillation (PDO)- and El Nino Southern Oscillation (ENSO)-type events influence Alaska surface temperatures weakly (1-2/spl deg/C) statewide. PDO has a stronger influence than ENSO on precipitation but its influence is largely localized to coastal central Alaska. The strongest influence of Arctic oscillation (AO) occurs in northern and interior Alaskan precipitation. Four major ecosystems are defined. A major eco-transition zone occurs between the interior boreal forest and the coastal rainforest. Variability in insolation, surface temperature, precipitation, continentality, and seasonal changes in storm track direction explain the mapped ecosystems. Lack of westward expansion of the interior boreal forest into the western shrub tundra is influenced by the coastal marine boundary layer (enhanced cloud cover, reduced insolation, cooler surface and soil temperatures).

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.

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.

A preindustrial to present record of SST from Darwin Island, Galápagos: constraining Eastern Pacific decadal variability

NASA Astrophysics Data System (ADS)

Jimenez, G.; Cole, J. E.; Vetter, L.; Thompson, D. M.; Tudhope, A. W.

2017-12-01

Climate reconstructions from sub-seasonally resolved corals have greatly enhanced our understanding of climate variability related to the El Niño-Southern Oscillation (ENSO). However, few such records exist from the Eastern Pacific, which experiences the greatest ENSO-related variance in sea surface temperature (SST). Therefore, climate patterns and mechanisms in the region remain unclear, particularly on decadal to multidecadal timescales. Here, we present a new, bimonthly-resolved δ18O-SST reconstruction from a Darwin Island coral, in the northern Galápagos archipelago. Comparison with Sr/Ca data from the same coral demonstrates that δ18O values in the core dominantly track SST, as is expected in areas with low-magnitude sea surface salinity changes such as the Galápagos. Spanning 2015 to approximately 1800 CE, our record thus represents the longest sub-seasonally resolved SST reconstruction bridging the pre-industrial era to the present day in the Eastern Pacific. This time span and resolution is ideal for identifying climatic processes on a range of timescales: the presence of modern data allows us to calibrate the record using satellite datasets, while several decades of data preceding the onset of greenhouse warming enables comparison between natural and anthropogenic climate forcings. Together with other reconstructions from the region, we use the record to establish a baseline of (ENSO-related) Eastern Pacific interannual and decadal variability and assess evidence for climate emergence and trends. Preliminary evidence suggests increased decadal variability during the latter half of the twentieth century, as well as a secular warming trend of approximately 0.1°C/decade, in agreement with other Eastern Pacific coral records. Finally, we explore the applications of coral δ13C values in reconstructing regional upwelling. Our record contributes to constraining the pre- to post-industrial climate history of the Eastern Pacific and provides insight into natural versus forced climate variability in the region.

Global warming: it's not only size that matters

NASA Astrophysics Data System (ADS)

Hegerl, Gabriele C.

2011-09-01

Observed and model simulated warming is particularly large in high latitudes, and hence the Arctic is often seen as the posterchild of vulnerability to global warming. However, Mahlstein et al (2011) point out that the signal of climate change is emerging locally from that of climate variability earliest in regions of low climate variability, based on climate model data, and in agreement with observations. This is because high latitude regions are not only regions of strong feedbacks that enhance the global warming signal, but also regions of substantial climate variability, driven by strong dynamics and enhanced by feedbacks (Hall 2004). Hence the spatial pattern of both observed warming and simulated warming for the 20th century shows strong warming in high latitudes, but this warming occurs against a backdrop of strong variability. Thus, the ratio of the warming to internal variability is not necessarily highest in the regions that warm fastest—and Mahlstein et al illustrate that it is actually the low-variability regions where the signal of local warming emerges first from that of climate variability. Thus, regions with strongest warming are neither the most important to diagnose that forcing changes climate, nor are they the regions which will necessarily experience the strongest impact. The importance of the signal-to-noise ratio has been known to the detection and attribution community, but has been buried in technical 'optimal fingerprinting' literature (e.g., Hasselmann 1979, Allen and Tett 1999), where it was used for an earlier detection of climate change by emphasizing aspects of the fingerprint of global warming associated with low variability in estimates of the observed warming. What, however, was not discussed was that the local signal-to-noise ratio is of interest also for local climate change: where temperatures emerge from the range visited by internal climate variability, it is reasonable to assume that changes in climate will also cause more impacts than temperatures that have occurred frequently due to internal climate variability. Determining when exactly temperatures enter unusual ranges may be done in many different ways (and the paper shows several, and more could be imagined), but the main result of first local emergence in low latitudes remains robust. A worrying factor is that the regions where the signal is expected to emerge first, or is already emerging are largely regions in Africa, parts of South and Central America, and the Maritime Continent; regions that are vulnerable to climate change for a variety of regions (see IPCC 2007), and regions which contribute generally little to global greenhouse gas emissions. In contrast, strong emissions of greenhouse gases occur in regions of low warming-to-variability ratio. To get even closer to the relevance of this finding for impacts, it would be interesting to place the emergence of highly unusual summer temperatures in the context not of internal variability, but in the context of variability experienced by the climate system prior to the 20th century, as, e.g. documented in palaeoclimatic reconstructions and simulated in simulations of the last millennium (see Jansen et al 2007). External forcing has moved the temperature range around more strongly for some regions and in some seasons than others. For example, while reconstructions of summer temperatures in Europe appear to show small long-term variations, winter shows deep drops in temperature in the little Ice Age and a long-term increase since then (Luterbacher et al 2004), which was at least partly caused by external forcing (Hegerl et al 2011a) and therefore 'natural variability' may be different from internal variability. A further interesting question in attempts to provide a climate-based proxy for impacts of climate change is: to what extent does the rapidity of change matter, and how does it compare to trends due to natural variability? It is reasonable to assume that fast changes impact ecosystems and society more than slow, gradual ones. Also, is it really the mean seasonal temperature that counts, or should the focus change to extremes (see Hegerl et al 2011b)? Is seasonal mean exceedance of the prior temperature envelope a good and robust measure that also reflects these other, more complex diagnostics? Lots of food for thought and research! References Allen M R and Tett S F B 1999 Checking for model consistency in optimal finger printing Clim. Dyn. 15 419-34 Hall A 2004 The role of surface albedo feedback in climate J. Clim. 17 1550-68 Hasselmann K 1979 On the signal-to-noise problem in atmospheric response studies Meteorology of Tropical Oceans ed D B Shaw (Bracknell: Royal Meteorological Society) pp 251-9 Hegerl G C, Luterbacher J, Gonzalez-Ruoco F, Tett S F B and Xoplaki E 2011a Influence of human and natural forcing on European seasonal temperatures Nature Geoscience 4 99-103 Hegerl G, Hanlon H and Beierkuhnlein C 2011b Climate science: elusive extremes Nature Geoscience 4 142-3 IPCC 2007 Climate Change 2007: Impacts, Adaption and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed M L Parry, O F Canziani, J P Palutikof, P J van der Linden and C E Hanson (Cambridge: Cambridge University Press) Jansen E et al 2007 Palaeoclimate Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change ed S Solomon et al (Cambridge: Cambridge University Press) Luterbacher J et al 2004 European seasonal and annual temperature variability, trends, and extremes since 1500 Science 303 1499-503 Mahlstein I, Knutti R, Solomon S and Portmann R W 2011 Early onset of significant local warming in low latitude countries Environ. Res. Lett. 6 034009

Temperate Mountain Forest Biodiversity under Climate Change: Compensating Negative Effects by Increasing Structural Complexity

PubMed Central

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species’ occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species’ occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change. PMID:24823495

Temperate mountain forest biodiversity under climate change: compensating negative effects by increasing structural complexity.

PubMed

Braunisch, Veronika; Coppes, Joy; Arlettaz, Raphaël; Suchant, Rudi; Zellweger, Florian; Bollmann, Kurt

2014-01-01

Species adapted to cold-climatic mountain environments are expected to face a high risk of range contractions, if not local extinctions under climate change. Yet, the populations of many endothermic species may not be primarily affected by physiological constraints, but indirectly by climate-induced changes of habitat characteristics. In mountain forests, where vertebrate species largely depend on vegetation composition and structure, deteriorating habitat suitability may thus be mitigated or even compensated by habitat management aiming at compositional and structural enhancement. We tested this possibility using four cold-adapted bird species with complementary habitat requirements as model organisms. Based on species data and environmental information collected in 300 1-km2 grid cells distributed across four mountain ranges in central Europe, we investigated (1) how species' occurrence is explained by climate, landscape, and vegetation, (2) to what extent climate change and climate-induced vegetation changes will affect habitat suitability, and (3) whether these changes could be compensated by adaptive habitat management. Species presence was modelled as a function of climate, landscape and vegetation variables under current climate; moreover, vegetation-climate relationships were assessed. The models were extrapolated to the climatic conditions of 2050, assuming the moderate IPCC-scenario A1B, and changes in species' occurrence probability were quantified. Finally, we assessed the maximum increase in occurrence probability that could be achieved by modifying one or multiple vegetation variables under altered climate conditions. Climate variables contributed significantly to explaining species occurrence, and expected climatic changes, as well as climate-induced vegetation trends, decreased the occurrence probability of all four species, particularly at the low-altitudinal margins of their distribution. These effects could be partly compensated by modifying single vegetation factors, but full compensation would only be achieved if several factors were changed in concert. The results illustrate the possibilities and limitations of adaptive species conservation management under climate change.

Growth responses of Scots pine to climatic factors on reclaimed oil shale mined land.

PubMed

Metslaid, Sandra; Stanturf, John A; Hordo, Maris; Korjus, Henn; Laarmann, Diana; Kiviste, Andres

2016-07-01

Afforestation on reclaimed mining areas has high ecological and economic importance. However, ecosystems established on post-mining substrate can become vulnerable due to climate variability. We used tree-ring data and dendrochronological techniques to study the relationship between climate variables and annual growth of Scots pine (Pinus sylvestris L.) growing on reclaimed open cast oil shale mining areas in Northeast Estonia. Chronologies for trees of different age classes (50, 40, 30) were developed. Pearson's correlation analysis between radial growth indices and monthly climate variables revealed that precipitation in June-July and higher mean temperatures in spring season enhanced radial growth of pine plantations, while higher than average temperatures in summer months inhibited wood production. Sensitivity of radial increment to climatic factors on post-mining soils was not homogenous among the studied populations. Older trees growing on more developed soils were more sensitive to precipitation deficit in summer, while growth indices of two other stand groups (young and middle-aged) were highly correlated to temperature. High mean temperatures in August were negatively related to annual wood production in all trees, while trees in the youngest stands benefited from warmer temperatures in January. As a response to thinning, mean annual basal area increment increased up to 50 %. By managing tree competition in the closed-canopy stands, through the thinning activities, tree sensitivity and response to climate could be manipulated.

Intensified impact of tropical Atlantic SST on the western North Pacific summer climate under a weakened Atlantic thermohaline circulation

NASA Astrophysics Data System (ADS)

Chen, Wei; Lee, June-Yi; Lu, Riyu; Dong, Buwen; Ha, Kyung-Ja

2015-10-01

The tropical North Atlantic (TNA) sea surface temperature (SST) has been identified as one of regulators on the boreal summer climate over the western North Pacific (WNP), in addition to SSTs in the tropical Pacific and Indian Oceans. The major physical process proposed is that the TNA warming induces a pair of cyclonic circulation anomaly over the eastern Pacific and negative precipitation anomalies over the eastern to central tropical Pacific, which in turn lead to an anticyclonic circulation anomaly over the western to central North Pacific. This study further demonstrates that the modulation of the TNA warming to the WNP summer climate anomaly tends to be intensified under background of the weakened Atlantic thermohaline circulation (THC) by using a water-hosing experiment. The results suggest that the weakened THC induces a decrease in thermocline depth over the TNA region, resulting in the enhanced sensitivity of SST variability to wind anomalies and thus intensification of the interannual variation of TNA SST. Under the weakened THC, the atmospheric responses to the TNA warming are westward shifted, enhancing the anticyclonic circulation and negative precipitation anomaly over the WNP. This study supports the recent finding that the negative phase of the Atlantic multidecadal oscillation after the late 1960s has been favourable for the strengthening of the connection between TNA SST variability and WNP summer climate and has important implications for seasonal prediction and future projection of the WNP summer climate.

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

PubMed

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

2009-10-01

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

Regional agricultural susceptibility to climate variability: A district level analysis of Maharashtra, India

NASA Astrophysics Data System (ADS)

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

2016-12-01

Climate variability (CV) has adverse impact on crop production and inadequate research carried out to assess the impact of CV on crop production has aggravated the ability of farmers to adapt (Jones et al., 2000). A better understanding of CV is required to reduce the vulnerability of farmers towards existing and future CV. Further, a wide variation in policies related to climate change exists at global level and considering the state/nation as a single unit for policy formulations may lead to under-representation of regional problems. Hence, the present work chooses to focus on CVassessment at the regional/district level of Maharashtra state in India. Here, interannual variability of wet and dry spells from year 1951-2013, are used as a measure of CV. Statistical declining trend of wet spells for (12/34) districts was observed across all the districts of Maharashtra. Districts showing highest change in wet spell pre and post 1976/77 are Beed, Latur and Osmanabad belong to Central Maharashtra Plateau zone and Western Maharashtra scarcity zone. Dry spells for (8/34) districts were found to statistically increase across all the districts of Maharashtra. Washim, Yavatmal of Vidarbha zone; and Latur, Parbhani of Amravati division belonging to Central Maharashtra Plateau zone and Central Vidarbha zone are found to reflect the large variation in their behavior pre and post 1976/77. Findings reveal that districts from the same agro-climate zones respond differently to CV, indicating significant spatial heterogeneity within the region. Trend in monsoon variability was found to be prominent after 1976/77, suggesting an enhanced role of climate change on climate variability after 1977. It necessitates separate policy formulation related to CV and agriculture for each district to bring out the solution for regional issues (socio-political, farmers, agriculturalists, economical) more clearly. Further we have attempted to link agriculture vulnerability and crop sensitivity to CV. Results signify spatial and temporal variability of different agro-ecological and climate parameters; suitable adaptation measures to famers and policy makers need to address this change. The findings can be utilized by farmers and policy makers while formulating agricultural policies and adaptation measures related to climate change.

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

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

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

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

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

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

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

PubMed

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

2015-02-01

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

Climate Variability and Oceanographic Settings Associated with Interannual Variability in the Initiation of Dinophysis acuminata Blooms

PubMed Central

Díaz, Patricio A.; Reguera, Beatriz; Ruiz-Villarreal, Manuel; Pazos, Yolanda; Velo-Suárez, Lourdes; Berger, Henrick; Sourisseau, Marc

2013-01-01

In 2012, there were exceptional blooms of D. acuminata in early spring in what appeared to be a mesoscale event affecting Western Iberia and the Bay of Biscay. The objective of this work was to identify common climatic patterns to explain the observed anomalies in two important aquaculture sites, the Galician Rías Baixas (NW Spain) and Arcachon Bay (SW France). Here, we examine climate variability through physical-biological couplings, Sea Surface Temperature (SST) anomalies and time of initiation of the upwelling season and its intensity over several decades. In 2012, the mesoscale features common to the two sites were positive anomalies in SST and unusual wind patterns. These led to an atypical predominance of upwelling in winter in the Galician Rías, and increased haline stratification associated with a southward advection of the Gironde plume in Arcachon Bay. Both scenarios promoted an early phytoplankton growth season and increased stability that enhanced D. acuminata growth. Therefore, a common climate anomaly caused exceptional blooms of D. acuminata in two distant regions through different triggering mechanisms. These results increase our capability to predict intense diarrhetic shellfish poisoning outbreaks in the early spring from observations in the preceding winter. PMID:23959151

Increasing ENSO-Driven Drought and Wildfire Risks in a Warming Climate

NASA Astrophysics Data System (ADS)

Fasullo, J.; Otto-Bliesner, B. L.; Stevenson, S.

2015-12-01

ENSO-related teleconnections occurring in the transient climate states of the 20th and 21st centuries are examined using the NCAR CESM1-CAM5 Large Ensemble (LE). A focus is given to quantifying the changing nature of related variability in a warming climate, the statistical robustness of which is enhanced by the numerous members of the LE (presently ~40). It is found that while the dynamical components of ENSO's teleconnections weaken considerably in a warming world, associated variability over land is in many cases sustained by changes in the background state, such as for rainfall due to the background rise in specific humidity. In some fields, particularly those associated with associated with thermal stress (e.g. drought and wildfire), ENSO-related variance increases dramatically. This, combined with the fact that ENSO variance itself increases in a warming climate in the LE, contributes to dramatic projected increases in ENSO-driven drought and wildfire risks in a warming world.

Forests synchronize their growth in contrasting Eurasian regions in response to climate warming.

PubMed

Shestakova, Tatiana A; Gutiérrez, Emilia; Kirdyanov, Alexander V; Camarero, Jesús Julio; Génova, Mar; Knorre, Anastasia A; Linares, Juan Carlos; Resco de Dios, Víctor; Sánchez-Salguero, Raúl; Voltas, Jordi

2016-01-19

Forests play a key role in the carbon balance of terrestrial ecosystems. One of the main uncertainties in global change predictions lies in how the spatiotemporal dynamics of forest productivity will be affected by climate warming. Here we show an increasing influence of climate on the spatial variability of tree growth during the last 120 y, ultimately leading to unprecedented temporal coherence in ring-width records over wide geographical scales (spatial synchrony). Synchrony in growth patterns across cold-constrained (central Siberia) and drought-constrained (Spain) Eurasian conifer forests have peaked in the early 21st century at subcontinental scales (∼ 1,000 km). Such enhanced synchrony is similar to that observed in trees co-occurring within a stand. In boreal forests, the combined effects of recent warming and increasing intensity of climate extremes are enhancing synchrony through an earlier start of wood formation and a stronger impact of year-to-year fluctuations of growing-season temperatures on growth. In Mediterranean forests, the impact of warming on synchrony is related mainly to an advanced onset of growth and the strengthening of drought-induced growth limitations. Spatial patterns of enhanced synchrony represent early warning signals of climate change impacts on forest ecosystems at subcontinental scales.

Forests synchronize their growth in contrasting Eurasian regions in response to climate warming

PubMed Central

Shestakova, Tatiana A.; Gutiérrez, Emilia; Kirdyanov, Alexander V.; Camarero, Jesús Julio; Génova, Mar; Knorre, Anastasia A.; Linares, Juan Carlos; Sánchez-Salguero, Raúl; Voltas, Jordi

2016-01-01

Forests play a key role in the carbon balance of terrestrial ecosystems. One of the main uncertainties in global change predictions lies in how the spatiotemporal dynamics of forest productivity will be affected by climate warming. Here we show an increasing influence of climate on the spatial variability of tree growth during the last 120 y, ultimately leading to unprecedented temporal coherence in ring-width records over wide geographical scales (spatial synchrony). Synchrony in growth patterns across cold-constrained (central Siberia) and drought-constrained (Spain) Eurasian conifer forests have peaked in the early 21st century at subcontinental scales (∼1,000 km). Such enhanced synchrony is similar to that observed in trees co-occurring within a stand. In boreal forests, the combined effects of recent warming and increasing intensity of climate extremes are enhancing synchrony through an earlier start of wood formation and a stronger impact of year-to-year fluctuations of growing-season temperatures on growth. In Mediterranean forests, the impact of warming on synchrony is related mainly to an advanced onset of growth and the strengthening of drought-induced growth limitations. Spatial patterns of enhanced synchrony represent early warning signals of climate change impacts on forest ecosystems at subcontinental scales. PMID:26729860

Winter and spring climatic conditions influence timing and synchrony of calving in reindeer.

PubMed

Paoli, Amélie; Weladji, Robert B; Holand, Øystein; Kumpula, Jouko

2018-01-01

In a context of climate change, a mismatch has been shown to occur between some species' reproductive phenology and their environment. So far, few studies have either documented temporal trends in calving phenology or assessed which climatic variables influence the calving phenology in ungulate species, yet the phenology of ungulates' births affects offspring survival and population's recruitment rate. Using a long-term dataset (45 years) of birth dates of a semi-domesticated reindeer population in Kaamanen, North Finland, we show that calving season has advanced by ~ 7 days between 1970 and 2016. Advanced birth dates were associated with lower precipitation and a reduced snow cover in April and warmer temperatures in April-May. Improved females' physical condition in late gestation due to warmer temperatures in April-May and reduced snow conditions in April probably accounted for such advance in calving date. On the other hand, a lengthening of the calving season was reported following a warmer temperature in January, a higher number of days when mean temperature exceeds 0°C in October-November and a decreasing snow cover from October to November. By affecting the inter-individual heterogeneity in the plastic response of females' calving date to better climatic conditions in fall and winter, climatic variability contributed to weaken the calving synchrony in this herd. Whether variability in climatic conditions form environmental cues for the adaptation of calving phenology by females to climate change is however uncertain, but it is likely. As such this study enhances our understanding on how reproductive phenology of ungulate species would be affected by climate change.

Winter and spring climatic conditions influence timing and synchrony of calving in reindeer

PubMed Central

Paoli, Amélie; Holand, Øystein; Kumpula, Jouko

2018-01-01

In a context of climate change, a mismatch has been shown to occur between some species’ reproductive phenology and their environment. So far, few studies have either documented temporal trends in calving phenology or assessed which climatic variables influence the calving phenology in ungulate species, yet the phenology of ungulates’ births affects offspring survival and population’s recruitment rate. Using a long-term dataset (45 years) of birth dates of a semi-domesticated reindeer population in Kaamanen, North Finland, we show that calving season has advanced by ~ 7 days between 1970 and 2016. Advanced birth dates were associated with lower precipitation and a reduced snow cover in April and warmer temperatures in April-May. Improved females’ physical condition in late gestation due to warmer temperatures in April-May and reduced snow conditions in April probably accounted for such advance in calving date. On the other hand, a lengthening of the calving season was reported following a warmer temperature in January, a higher number of days when mean temperature exceeds 0°C in October-November and a decreasing snow cover from October to November. By affecting the inter-individual heterogeneity in the plastic response of females’ calving date to better climatic conditions in fall and winter, climatic variability contributed to weaken the calving synchrony in this herd. Whether variability in climatic conditions form environmental cues for the adaptation of calving phenology by females to climate change is however uncertain, but it is likely. As such this study enhances our understanding on how reproductive phenology of ungulate species would be affected by climate change. PMID:29694410

Relationships between climate and growth of Gymnocypris selincuoensis in the Tibetan Plateau.

PubMed

Tao, Juan; Chen, Yifeng; He, Dekui; Ding, Chengzhi

2015-04-01

The consequences of climate change are becoming increasingly evident in the Tibetan Plateau, represented by glaciers retreating and lakes expanding, but the biological response to climate change by plateau-lake ecosystems is poorly known. In this study, we applied dendrochronology methods to develop a growth index chronology with otolith increment widths of Selincuo naked carp (Gymnocypris selincuoensis), which is an endemic species in Lake Selincuo (4530 m), and investigated the relationships between fish growth and climate variables (regional and global) in the last three decades. A correlation analysis and principle component regression analysis between regional climate factors and the growth index chronology indicated that the growth of G. selincuoensis was significantly and positively correlated with length of the growing season and temperature-related variables, particularly during the growing season. Most of global climate variables, which are relevant to the Asian monsoon and the midlatitude westerlies, such as El Nino Southern Oscillation Index, the Arctic Oscillation, North Atlantic Oscillation, and North America Pattern, showed negative but not significant correlations with the annual growth of Selincuo naked carp. This may have resulted from the high elevation of the Tibetan Plateau and the high mountains surrounding this area. In comparison, the Pacific Decade Oscillation (PDO) negatively affected the growth of G. selincuoensis. The reason maybe that enhancement of the PDO can lead to cold conditions in this area. Taken together, the results indicate that the Tibetan Plateau fish has been affected by global climate change, particularly during the growing season, and global climate change likely has important effects on productivity of aquatic ecosystems in this area.

The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements

NASA Astrophysics Data System (ADS)

Lucas, S. E.; Todd, J. F.; Higgins, W.

2013-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward improving their representations in numerical models and improving MJO simulation and prediction. Recent results from CVP-funded projects will be summarized in this poster.

An Integrated Multivariable Visualization Tool for Marine Sanctuary Climate Assessments

NASA Astrophysics Data System (ADS)

Shein, K. A.; Johnston, S.; Stachniewicz, J.; Duncan, B.; Cecil, D.; Ansari, S.; Urzen, M.

2012-12-01

The comprehensive development and use of ecological climate impact assessments by ecosystem managers can be limited by data access and visualization methods that require a priori knowledge about the various large and complex climate data products necessary to those impact assessments. In addition, it can be difficult to geographically and temporally integrate climate and ecological data to fully characterize climate-driven ecological impacts. To address these considerations, we have enhanced and extended the functionality of the NOAA National Climatic Data Center's Weather and Climate Toolkit (WCT). The WCT is a freely available Java-based tool designed to access and display NCDC's georeferenced climate data products (e.g., satellite, radar, and reanalysis gridded data). However, the WCT requires users already know how to obtain the data products, which products are preferred for a given variable, and which products are most relevant to their needs. Developed in cooperation with research and management customers at the Gulf of the Farallones National Marine Sanctuary, the Integrated Marine Protected Area Climate Tools (IMPACT) modification to the WCT simplifies or eliminates these requirements, while simultaneously adding core analytical functionality to the tool. Designed for use by marine ecosystem managers, WCT-IMPACT accesses a suite of data products that have been identified as relevant to marine ecosystem climate impact assessments, such as NOAA's Climate Data Records. WCT-IMPACT regularly crops these products to the geographic boundaries of each included marine protected area (MPA), and those clipped regions are processed to produce MPA-specific analytics. The tool retrieves the most appropriate data files based on the user selection of MPA, environmental variable(s), and time frame. Once the data are loaded, they may be visualized, explored, analyzed, and exported to other formats (e.g., Google KML). Multiple variables may be simultaneously visualized using a 4-panel display and compared via a variety of statistics such as difference, probability, or correlation maps.; NCDC's Weather and Climate Toolkit image of NARR-A non-convective cloud cover (%) over the Pacific Coast on June 17, 2012 at 09:00 GMT.

The impact of anthropogenic climate change on wildfire across western US forests

NASA Astrophysics Data System (ADS)

Williams, P.; Abatzoglou, J. T.

2016-12-01

Increased forest fire activity across the western United States (US) in recent decades has contributed to widespread forest mortality, carbon emissions, periods of degraded air quality, and substantial fire suppression expenditures. The increase in forest fire activity has likely been enabled by a number of factors including the legacy of fire suppression and human settlement, changes in suppression policies, natural climate variability, and human-caused climate change. We use modeled climate projections to estimate the contribution of anthropogenic climate change to observed increases in eight fuel aridity metrics and forest fire area across the western US. Anthropogenic increases in temperature and vapor pressure deficit have significantly enhanced fuel aridity across western US forests over the past several decades. Comparing observational climate records to records recalculated after removal of modeled anthropogenic trends, we find that anthropogenic climate change accounted for approximately 55% of observed increases in the eight-metric mean fuel aridity during 1979-2015 across western US forests. This implicates anthropogenic climate change as an important driver of observed increases in fuel aridity, and also highlights the importance of natural multi-decadal climate variability in influencing trends in forest fire potential on the timescales of human lives. Based on a very strong (R2 = 0.76) and mechanistically reasonable relationship between interannual variability in the eight-metric mean fuel aridity and forest-fire area in the western US, we estimate that anthropogenic increases in fuel aridity contributed to an additional 4.2 million ha (95% confidence range: 2.7-6.5 million ha) of forest fire area during 1984-2015, nearly doubling the total forest fire area expected in the absence of anthropogenic climate change. The relationship between annual forest fire area and fuel aridity is exponential and the proportion of total forest area burned in a given year has grown rapidly over the past 32 years. Natural climate variability will continue to alternate between modulating and compounding anthropogenic increases in fuel aridity, but anthropogenic climate change has emerged as a chronic driver of increased forest fire activity and should continue to do so where fuels are not limiting.

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.

Work climate, work values and professional commitment as predictors of job satisfaction in nurses.

PubMed

Caricati, Luca; Sala, Rachele La; Marletta, Giuseppe; Pelosi, Giulia; Ampollini, Monica; Fabbri, Anna; Ricchi, Alba; Scardino, Marcello; Artioli, Giovanna; Mancini, Tiziana

2014-11-01

To investigate the effect of some psychosocial variables on nurses' job satisfaction. Nurses' job satisfaction is one of the most important factors in determining individuals' intention to stay or leave a health-care organisation. Literature shows a predictive role of work climate, professional commitment and work values on job satisfaction, but their conjoint effect has rarely been considered. A cross-sectional questionnaire survey was adopted. Participants were hospital nurses and data were collected in 2011. Professional commitment and work climate positively predicted nurses' job satisfaction. The effect of intrinsic vs. extrinsic work value orientation on job satisfaction was completely mediated by professional commitment. Nurses' job satisfaction is influenced by both contextual and personal variables, in particular work climate and professional commitment. According to a more recent theoretical framework, work climate, work values and professional commitment interact with each other in determining nurses' job satisfaction. Nursing management must be careful to keep the context of work tuned to individuals' attitude and vice versa. Improving the work climate can have a positive effect on job satisfaction, but its effect may be enhanced by favouring strong professional commitment and by promoting intrinsic more than extrinsic work values. © 2013 John Wiley & Sons Ltd.

Some guidelines for helping natural resources adapt to climate change

USGS Publications Warehouse

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

2008-01-01

The changes occurring in mountain regions are an epitome of climate change. The dramatic shrinkage of major glaciers over the past century – and especially in the last 30 years – is one of several iconic images that have come to symbolize climate change. Climate creates the context for ecosystems, and climate variables strongly influence the structure, composition, and processes that characterize distinct ecosystems. Climate change, therefore, is having direct and indirect effects on species attributes, ecological interactions, and ecosystem processes. Because changes in the climate system will continue regardless of emissions mitigation, management strategies to enhance the resilience of ecosystems will become increasingly important. It is essential that management responses to climate change proceed using the best available science despite uncertainties associated with the future path of climate change, the response of ecosystems to climate effects, and the effects of management. Given these uncertainties, management adaptation will require flexibility to reflect our growing understanding of climate change impacts and management effectiveness.

PP-SWAT: A phython-based computing software for efficient multiobjective callibration of SWAT

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

El Niño-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Relative Contributions of Mean-State Shifts and ENSO-Driven Variability to Precipitation Changes in a Warming Climate

NASA Technical Reports Server (NTRS)

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; Marvel, Kate; Leung, L. Ruby; Doutriaux, Charles; Capotondi, Antonietta

2015-01-01

The El Nino-Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with Coupled General Circulation Models (CGCMs) to investigate how regional precipitation in the 21st century may be affected by changes in both ENSO-driven precipitation variability and slowly-evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of 20th century climate change. Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in 21st century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with 20th century observations and more stationary during the 21st century. Finally, the model-predicted 21st century rainfall response to cENSO is decomposed into the sum of three terms: 1) the 21st century change in the mean state of precipitation; 2) the historical precipitation response to the cENSO pattern; and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. By examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.

Mapping the Potential for Eolian Surface Activity in Grasslands of the High Plains using Landsat Images

NASA Technical Reports Server (NTRS)

Gutmann, Ethan Dain

2002-01-01

There are over 100,000 square kilometers of eolian sand dunes and sand sheets in the High Plains of the central United States. These land-forms may be unstable and may reactivate again as a result of land-use, climate change, or natural climatic variability. The main goal of this thesis was to develop a model that could be used to map an estimate of future dune activity. Multi-temporal calibrated Landsats 5 Thematic Mapper (TM) and 7 Enhanced Thematic Map per Plus (ETM+) NDVI imagery were used in conjunction with the CENTURY vegetation model to correlate vegetation cover to climatic variability. This allows the creation of a predicted vegetation map which, combined with current wind and soil data, was used to create a potential sand transport map for range land in the High Plains under drought conditions.

Climate modulates internal wave activity in the Northern South China Sea

NASA Astrophysics Data System (ADS)

DeCarlo, Thomas M.; Karnauskas, Kristopher B.; Davis, Kristen A.; Wong, George T. F.

2015-02-01

Internal waves (IWs) generated in the Luzon Strait propagate into the Northern South China Sea (NSCS), enhancing biological productivity and affecting coral reefs by modulating nutrient concentrations and temperature. Here we use a state-of-the-art ocean data assimilation system to reconstruct water column stratification in the Luzon Strait as a proxy for IW activity in the NSCS and diagnose mechanisms for its variability. Interannual variability of stratification is driven by intrusions of the Kuroshio Current into the Luzon Strait and freshwater fluxes associated with the El Niño-Southern Oscillation. Warming in the upper 100 m of the ocean caused a trend of increasing IW activity since 1900, consistent with global climate model experiments that show stratification in the Luzon Strait increases in response to radiative forcing. IW activity is expected to increase in the NSCS through the 21st century, with implications for mitigating climate change impacts on coastal ecosystems.

Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming.

PubMed

Cheng, Jun; Liu, Zhengyu; Zhang, Shaoqing; Liu, Wei; Dong, Lina; Liu, Peng; Li, Hongli

2016-03-22

Interdecadal variability of the Atlantic Meridional Overturning Circulation (AMOC-IV) plays an important role in climate variation and has significant societal impacts. Past climate reconstruction indicates that AMOC-IV has likely undergone significant changes. Despite some previous studies, responses of AMOC-IV to global warming remain unclear, in particular regarding its amplitude and time scale. In this study, we analyze the responses of AMOC-IV under various scenarios of future global warming in multiple models and find that AMOC-IV becomes weaker and shorter with enhanced global warming. From the present climate condition to the strongest future warming scenario, on average, the major period of AMOC-IV is shortened from ∼50 y to ∼20 y, and the amplitude is reduced by ∼60%. These reductions in period and amplitude of AMOC-IV are suggested to be associated with increased oceanic stratification under global warming and, in turn, the speedup of oceanic baroclinic Rossby waves.

Detection of greenhouse-gas-induced climatic change. Progress report, 1 December 1991--30 June 1994

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

Wigley, T.M.L.; Jones, P.D.

1994-07-01

In addition to changes due to variations in greenhouse gas concentrations, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the enhanced greenhouse effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics. To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas concentration changes and other factors. Analyses will be guided bymore » a variety of models, from simple energy balance climate models to ocean General Circulation Models. Appendices A--G contain the following seven papers: (A) Recent global warmth moderated by the effects of the Mount Pinatubo eruption; (B) Recent warming in global temperature series; (C) Correlation methods in fingerprint detection studies; (D) Balancing the carbon budget. Implications for projections of future carbon dioxide concentration changes; (E) A simple model for estimating methane concentration and lifetime variations; (F) Implications for climate and sea level of revised IPCC emissions scenarios; and (G) Sulfate aerosol and climatic change.« less

Hydroclimate variability in Scandinavia over the last millennium - insights from a climate model-proxy data comparison

NASA Astrophysics Data System (ADS)

Seftigen, Kristina; Goosse, Hugues; Klein, Francois; Chen, Deliang

2017-12-01

The integration of climate proxy information with general circulation model (GCM) results offers considerable potential for deriving greater understanding of the mechanisms underlying climate variability, as well as unique opportunities for out-of-sample evaluations of model performance. In this study, we combine insights from a new tree-ring hydroclimate reconstruction from Scandinavia with projections from a suite of forced transient simulations of the last millennium and historical intervals from the CMIP5 and PMIP3 archives. Model simulations and proxy reconstruction data are found to broadly agree on the modes of atmospheric variability that produce droughts-pluvials in the region. Despite these dynamical similarities, large differences between simulated and reconstructed hydroclimate time series remain. We find that the GCM-simulated multi-decadal and/or longer hydroclimate variability is systematically smaller than the proxy-based estimates, whereas the dominance of GCM-simulated high-frequency components of variability is not reflected in the proxy record. Furthermore, the paleoclimate evidence indicates in-phase coherencies between regional hydroclimate and temperature on decadal timescales, i.e., sustained wet periods have often been concurrent with warm periods and vice versa. The CMIP5-PMIP3 archive suggests, however, out-of-phase coherencies between the two variables in the last millennium. The lack of adequate understanding of mechanisms linking temperature and moisture supply on longer timescales has serious implications for attribution and prediction of regional hydroclimate changes. Our findings stress the need for further paleoclimate data-model intercomparison efforts to expand our understanding of the dynamics of hydroclimate variability and change, to enhance our ability to evaluate climate models, and to provide a more comprehensive view of future drought and pluvial risks.

Seasonal Climate Forecasts and Adoption by Agriculture

NASA Astrophysics Data System (ADS)

Garbrecht, Jurgen; Meinke, Holger; Sivakumar, Mannava V. K.; Motha, Raymond P.; Salinger, Michael J.

2005-06-01

Recent advances in atmospheric and ocean sciences and a better understanding of the global climate have led to skillful climate forecasts at seasonal to interannual timescales, even in midlatitudes. These scientific advances and forecasting capabilities have opened the door to practical applications that benefit society. The benefits include the reduction of weather/climate related risks and vulnerability, increased economic opportunities, enhanced food security, mitigation of adverse climate impacts, protection of environmental quality, and so forth. Agriculture in particular can benefit substantially from accurate long-lead seasonal climate forecasts. Indeed, agricultural production very much depends on weather, climate, and water availability, and unexpected departures from anticipated climate conditions can thwart the best laid management plans. Timely climate forecasts offer means to reduce losses in drought years, increase profitability in good years, deal more effectively with climate variability, and choose from targeted risk-management strategies. In addition to benefiting farmers, forecasts can also help marketing systems and downstream users prepare for anticipated production outcomes and associated consequences.

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.

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.

Recent trends in energy flows through the Arctic climate system

NASA Astrophysics Data System (ADS)

Mayer, Michael; Haimberger, Leo

2016-04-01

While Arctic climate change can be diagnosed in many parameters, a comprehensive assessment of long-term changes and low frequency variability in the coupled Arctic energy budget still remains challenging due to the complex physical processes involved and the lack of observations. Here we draw on strongly improved observational capabilities of the past 15 years and employ observed radiative fluxes from CERES along with state-of-the-art atmospheric as well as coupled ocean-ice reanalyses to explore recent changes in energy flows through the Arctic climate system. Various estimates of ice volume and ocean heat content trends imply that the energy imbalance of the Arctic climate system was >1 Wm-2 during the 2000-2015 period, where most of the extra heat warmed the ocean and a comparatively small fraction was used to melt sea ice. The energy imbalance was partly fed by enhanced oceanic heat transports into the Arctic, especially in the mid 2000s. Seasonal trends of net radiation show a very clear signal of the ice-albedo feedback. Stronger radiative energy input during summer means increased seasonal oceanic heat uptake and accelerated sea ice melt. In return, lower minimum sea ice extent and higher SSTs lead to enhanced heat release from the ocean during fall season. These results are consistent with modeling studies finding an enhancement of the annual cycle of surface energy exchanges in a warming Arctic. Moreover, stronger heat fluxes from the ocean to the atmosphere in fall tend to warm the arctic boundary layer and reduce meridional temperature gradients, thereby reducing atmospheric energy transports into the polar cap. Although the observed results are a robust finding, extended high-quality datasets are needed to reliably separate trends from low frequency variability.

West African warming: Investigating Temperature Trends and their relation between Precipitation Trends over West African Sahel.

NASA Astrophysics Data System (ADS)

LY, M., Jr.

2014-12-01

It is now admitted that the West African region faces a lot of constraints due to the comprehensiveness of the high climate variability and potential climate change. This is mainly due to the lack of a large number of datasets and long-term records as summarized in the in the IPCC reports. This paper aims to provide improved knowledge and evidence on current and future climate conditions, for better manage climate variability over seasons and from year to year and strengthen the capacity to adapt to future climate change. In this regards, we analyse the evolution of some extreme temperature and precipitation indices over a large area of West Africa. Prior results show a general warming trend at individual stations throughout the region during the period from 1960 to 2010, namely negative trends in the number of cool nights, and positive trends in the number of warm days and length of warm spells. Trends in rainfall-related indices are not as uniform as the ones in temperatures, rather they display marked multi-decadal variability, as expected. To refine analyses of temperature variations and their relation to precipitation we investigated on cluster analysis aimed at distinguishing different sub-regions, such as continental and coastal, and relevant seasons, such as wet, dry/cold and dry warm. This will contribute to significantly lower uncertainties by developing better and more tailored temperature and precipitation trends to inform the user communities on climate related risks, as well as enhance their resilience to food insecurity and other climate related disasters.

Interdecadal variations of ENSO around 1999/2000

NASA Astrophysics Data System (ADS)

Hu, Zeng-Zhen; Kumar, Arun; Huang, Bohua; Zhu, Jieshun; Ren, Hong-Li

2017-02-01

This paper discusses the interdecadal changes of the climate in the tropical Pacific with a focus on the corresponding changes in the characteristics of the El Niño-Southern Oscillation (ENSO). Compared with 1979-1999, the whole tropical Pacific climate system, including both the ocean and atmosphere, shifted to a lower variability regime after 1999/2000. Meanwhile, the frequency of ENSO became less regular and was closer to a white noise process. The lead time of the equatorial Pacific's subsurface ocean heat content in preceding ENSO decreased remarkably, in addition to a reduction in the maximum correlation between them. The weakening of the correlation and the shortening of the lead time pose more challenges for ENSO prediction, and is the likely reason behind the decrease in skill with respect to ENSO prediction after 2000. Coincident with the changes in tropical Pacific climate variability, the mean states of the atmospheric and oceanic components also experienced physically coherent changes. The warm anomaly of SST in the western Pacific and cold anomaly in the eastern Pacific resulted in an increased zonal SST gradient, linked to an enhancement in surface wind stress and strengthening of the Walker circulation, as well as an increase in the slope of the thermocline. These changes were consistent with an increase (a decrease) in precipitation and an enhancement (a suppression) of the deep convection in the western (eastern) equatorial Pacific. Possible connections between the mean state and ENSO variability and frequency changes in the tropical Pacific are also discussed.

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

Chavas, Daniel R.; Izaurralde, Roberto C.; Thomson, Allison M.

Increasing atmospheric greenhouse gas concentrations are expected to induce significant climate change over the next century and beyond, but the impacts on society remain highly uncertain. This work examines potential climate change impacts on the productivity of five major crops in northeastern China: canola, corn, potato, rice, and winter wheat. In addition to determining domain-wide trends, the objective is to identify vulnerable and emergent regions under future climate conditions, defined as having a greater than 10% decrease and increase in productivity, respectively. Data from the ICTP RegCM3 regional climate model for baseline (1961-1990) and future (2071-2100) periods under A2 scenariomore » conditions are used as input in the EPIC agro-ecosystem simulation model in the domain [30ºN, 108ºE] to [42ºN, 123ºE]. Simulations are performed with and without the enhanced CO2 fertilization effect. Results indicate that aggregate potential productivity (i.e. if the crop is grown everywhere) increases 6.5% for rice, 8.3% for canola, 18.6% for corn, 22.9% for potato, and 24.9% for winter wheat, although with significant spatial variability for each crop. However, absent the enhanced CO2 fertilization effect, potential productivity declines in all cases ranging from 2.5-12%. Interannual yield variability remains constant or declines in all cases except rice. Climate variables are found to be more significant drivers of simulated yield changes than changes in soil properties, except in the case of potato production in the northwest where the effects of wind erosion are more significant. Overall, in the future period corn and winter wheat benefit significantly in the North China Plain, rice remains dominant in the southeast and emerges in the northeast, potato and corn yields become viable in the northwest, and potato yields suffer in the southwest with no other crop emerging as a clear beneficiary from among those simulated in this study.« less

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.

Managed aquifer recharge with low impact development under a changing climate (Invited)

NASA Astrophysics Data System (ADS)

Gurdak, J. J.; Newcomer, M. E.; Sklar, L. S.; Nanus, L.

2013-12-01

Groundwater resources in urban environments are highly vulnerable to human pressures and climate variability and change, and many communities face water shortages and need to find alternative water supplies. Therefore, understanding how low impact development (LID) planning and best management practices (BMPs) affect recharge rates and volumes is important because of the increasing use of LID and BMPs to reduce stormwater runoff and improve surface-water quality. Some BMPs may also enhance recharge, which has often been considered a secondary management benefit. Enhancing the capacity for managed aquifer recharge with stormwater beneath LID is an important step toward the sustainable and conjunctive use of surface and groundwater resources in urban environments. This field and modeling study quantifies urban recharge rates, volumes, and efficiency beneath a BMP infiltration trench and irrigated lawn considering historical El Niño/Southern Oscillation (ENSO) variability and future climate change using simulated precipitation from the Geophysical Fluid Dynamic Laboratory (GFDL) A1F1 climate scenario. Using results from a suite of methods to measure and model recharge beneath a recently installed (2009) BMP infiltration trench, this study addresses three main questions: (1) What are the benefits of measuring recharge using in-situ methods compared to model-based and other simple estimates of recharge beneath a LID BMP? (2) What are recharge rates and volumes beneath the infiltration trench, how do they compare to an irrigated lawn that represents a non-LID source of urban recharge, and what are the important factors controlling recharge beneath the two sites? (3) How effective is the LID BMP in capturing and recharging urban stormwater considering historical ENSO variability and future climate change? We find that in-situ and modeling methods are complementary, particularly for simulating historical and future recharge scenarios, and the in-situ data are critical for accurately estimating recharge under current conditions. Recharge rates beneath the infiltration trench (1,620 to 3,710 mm yr- 1) were an order-of-magnitude greater than beneath the irrigated lawn (130 to 730 mm yr-1). Beneath the infiltration trench, recharge rates ranged from 1,390 to 5,840 mm yr-1 and averaged 3,410 mm yr-1 for El Niño years and from 1,540 to 3,330 mm yr-1 and averaged 2,430 mm yr-1 for La Niña years. We demonstrate a clear benefit for recharge and local groundwater resources using small, spatially distributed stormwater retention BMPs. This study provides the first field- and model-based estimates of recharge rates and volumes beneath BMPs considering climate variability and change, and provides practical management information regarding enhanced stormwater capture and recharge toward improved conjunctive use of water resources in urban environments.

Relationships between climate and growth of Gymnocypris selincuoensis in the Tibetan Plateau

PubMed Central

Tao, Juan; Chen, Yifeng; He, Dekui; Ding, Chengzhi

2015-01-01

The consequences of climate change are becoming increasingly evident in the Tibetan Plateau, represented by glaciers retreating and lakes expanding, but the biological response to climate change by plateau–lake ecosystems is poorly known. In this study, we applied dendrochronology methods to develop a growth index chronology with otolith increment widths of Selincuo naked carp (Gymnocypris selincuoensis), which is an endemic species in Lake Selincuo (4530 m), and investigated the relationships between fish growth and climate variables (regional and global) in the last three decades. A correlation analysis and principle component regression analysis between regional climate factors and the growth index chronology indicated that the growth of G. selincuoensis was significantly and positively correlated with length of the growing season and temperature-related variables, particularly during the growing season. Most of global climate variables, which are relevant to the Asian monsoon and the midlatitude westerlies, such as El Nino Southern Oscillation Index, the Arctic Oscillation, North Atlantic Oscillation, and North America Pattern, showed negative but not significant correlations with the annual growth of Selincuo naked carp. This may have resulted from the high elevation of the Tibetan Plateau and the high mountains surrounding this area. In comparison, the Pacific Decade Oscillation (PDO) negatively affected the growth of G. selincuoensis. The reason maybe that enhancement of the PDO can lead to cold conditions in this area. Taken together, the results indicate that the Tibetan Plateau fish has been affected by global climate change, particularly during the growing season, and global climate change likely has important effects on productivity of aquatic ecosystems in this area. PMID:25937912

Multi-scale enhancement of climate prediction over land by improving the model sensitivity to vegetation variability

NASA Astrophysics Data System (ADS)

Alessandri, A.; Catalano, F.; De Felice, M.; Hurk, B. V. D.; Doblas-Reyes, F. J.; Boussetta, S.; Balsamo, G.; Miller, P. A.

2017-12-01

Here we demonstrate, for the first time, that the implementation of a realistic representation of vegetation in Earth System Models (ESMs) can significantly improve climate simulation and prediction across multiple time-scales. The effective sub-grid vegetation fractional coverage vary seasonally and at interannual time-scales in response to leaf-canopy growth, phenology and senescence. Therefore it affects biophysical parameters such as the surface resistance to evapotranspiration, albedo, roughness lenght, and soil field capacity. To adequately represent this effect in the EC-Earth ESM, we included an exponential dependence of the vegetation cover on the Leaf Area Index.By comparing two sets of simulations performed with and without the new variable fractional-coverage parameterization, spanning from centennial (20th Century) simulations and retrospective predictions to the decadal (5-years), seasonal (2-4 months) and weather (4 days) time-scales, we show for the first time a significant multi-scale enhancement of vegetation impacts in climate simulation and prediction over land. Particularly large effects at multiple time scales are shown over boreal winter middle-to-high latitudes over Canada, West US, Eastern Europe, Russia and eastern Siberia due to the implemented time-varying shadowing effect by tree-vegetation on snow surfaces. Over Northern Hemisphere boreal forest regions the improved representation of vegetation-cover consistently correct the winter warm biases, improves the climate change sensitivity, the decadal potential predictability as well as the skill of forecasts at seasonal and weather time-scales. Significant improvements of the prediction of 2m temperature and rainfall are also shown over transitional land surface hot spots. Both the potential predictability at decadal time-scale and seasonal-forecasts skill are enhanced over Sahel, North American Great Plains, Nordeste Brazil and South East Asia, mainly related to improved performance in the surface evapotranspiration.Above results are discussed in a peer-review paper just being accepted for publication on Climate Dynamics (Alessandri et al., 2017; doi:10.1007/s00382-017-3766-y).

The GCRP Climate Health Assessment: From Scientific Literature to Climate Health Literacy

NASA Astrophysics Data System (ADS)

Crimmins, A. R.; Balbus, J. M.

2016-12-01

As noted by the new report from the US GCRP, the Impacts of Climate Change on Human Health in the United States: A Scientific Assessment, climate change is a significant threat to the health of the American people. Despite a growing awareness of the significance of climate change in general among Americans, however, recognition of the health significance of climate change is lacking. Not only are the general public and many climate scientists relatively uninformed about the myriad health implications of climate change; health professionals, including physicians and nurses, are in need of enhanced climate literacy. This presentation will provide an overview of the new GCRP Climate Health Assessment, introducing the audience to the systems thinking that underlies the assessment of health impacts, and reviewing frameworks that tie climate and earth systems phenomena to human vulnerability and health. The impacts on health through changes in temperature, precipitation, severity of weather extremes and climate variability, and alteration of ecosystems and phenology will be explored. The process of developing the assessment report will be discussed in the context of raising climate and health literacy within the federal government.

Climate change and the impact of increased rainfall variability on sediment transport and catchment scale water quality

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Willgoose, G. R.; Cohen, S.

2009-12-01

Recently there has been recognition that changing climate will affect rainfall and storm patterns with research directed to examine how the global hydrological cycle will respond to climate change. This study investigates the effect of different rainfall patterns on erosion and resultant water quality for a well studied tropical monsoonal catchment that is undisturbed by Europeans in the Northern Territory, Australia. Water quality has a large affect on a range of aquatic flora and fauna and a significant change in sediment could have impacts on the aquatic ecosystems. There have been several studies of the effect of climate change on rainfall patterns in the study area with projections indicating a significant increase in storm activity. Therefore it is important that the impact of this variability be assessed in terms of catchment hydrology, sediment transport and water quality. Here a numerical model of erosion and hydrology (CAESAR) is used to assess several different rainfall scenarios over a 1000 year modelled period. The results show that that increased rainfall amount and intensity increases sediment transport rates but predicted water quality was variable and non-linear but within the range of measured field data for the catchment and region. Therefore an assessment of sediment transport and water quality is a significant and complex issue that requires further understandings of the role of biophysical feedbacks such as vegetation as well as the role of humans in managing landscapes (i.e. controlled and uncontrolled fire). The study provides a robust methodology for assessing the impact of enhanced climate variability on sediment transport and water quality.

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

USGS Publications Warehouse

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

2009-01-01

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

Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

USDA-ARS?s Scientific Manuscript database

With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

Automated canopy estimator (ACE): Enhancing crop modelling and decision making in agriculture

USDA-ARS?s Scientific Manuscript database

The Caribbean agriculture sector is dominated by small holdings, which are overly reliant on rainfall and highly dependent on manual means of optimization. The sector is therefore very vulnerable to the vagaries of climate variability and change, with rainfall variations being of particular concern...

Soil water improvements with the long-term use of a winter rye cover crop

USDA-ARS?s Scientific Manuscript database

The Midwestern United States is projected to experience increasing rainfall variability. One approach to mitigate climate impacts is to utilize crop and soil management practices that enhance soil water storage, reducing the risks of flooding as well as drought-induced crop water stress. While some ...

Identifying the fingerprints of the anthropogenic component of land use/land cover changes on regional climate of the USA high plains

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

The majority of recent climate change studies have largely focused on detection and attribution of anthropogenic forcings of greenhouse gases, aerosols, stratospheric and tropospheric ozone. However, there is growing evidence that land cover/land use (LULC) change can significantly impact atmospheric processes from local to regional weather and climate variability. Human activities such as conversion of natural ecosystem to croplands and urban-centers, deforestation and afforestation impact biophysical properties of the land surfaces including albedo, energy balance, moisture-holding capacity of soil, and surface roughness. Alterations in these properties affect the heat and moisture exchanges between the land surface and atmospheric boundary layer, and ultimately impact the climate system. The challenge is to demonstrate that LULC changes produce a signal that can be discerned from natural climate noise. In this study, we attempt to detect the signature of anthropogenic forcing of LULC change on climate on regional scale. The signal projector investigated for detecting the signature of LULC changes on regional climate of the High Plains of the USA is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator that captures short and long-term geographical distribution of vegetation surfaces. The study develops an enhanced signal processing procedure to maximize the signal to noise ratio by introducing a pre-filtering technique of ARMA processes on the investigated climate and signal variables, before applying the optimal fingerprinting technique to detect the signals of LULC changes on observed climate, temperature, in the High Plains. The intent is to filter out as much noise as possible while still retaining the essential features of the signal by making use of the known characteristics of the noise and the anticipated signal. The study discusses the approach of identifying and suppressing the autocorrelation in optimal fingerprint analysis by applying linear transformation of ARMA processes to the analysis variables. With the assumption that natural climate variability is a near stationary process, the pre-filters are developed to generate stationary residuals. The High Plains region although impacted by droughts over the last three decades has had an increase in agricultural lands, both irrigated and non-irrigated. The study shows that for the most part of the High Plains region there is significant influence of evaporative cooling on regional climate during the summer months. As the vegetation coverage increases coupled with increased in irrigation application, the regional daytime surface energy in summer is increasingly redistributed into latent heat flux which increases the effect of evaporative cooling on summer temperatures. We included the anthropogenic forcing of CO2 on regional climate with the main purpose of surpassing the radiative heating effect of greenhouse gases from natural climate noise, to enhance the LULC signal-to-noise ratio. The warming signal due to greenhouse gas forcing is observed to be weakest in the central part of the High Plains. The results showed that the CO2 signal in the region was weak or is being surpassed by the evaporative cooling effect.

Future Changes to ENSO Temperature and Precipitation Teleconnections Under Warming

NASA Astrophysics Data System (ADS)

Perry, S.; McGregor, S.; Sen Gupta, A.; England, M. H.

2016-12-01

As the dominant mode of interannual climate variability, the El Niño-Southern Oscillation (ENSO) modulates temperature and rainfall globally, additionally contributing to weather extremes. Anthropogenic climate change has the potential to alter the strength and frequency of ENSO and may also alter ENSO-driven atmospheric teleconnections, affecting ecosystems and human activity in regions far removed from the tropical Pacific. State-of-art climate models exhibit considerable disagreement in projections of future changes in ENSO sea surface temperature variability. Despite this uncertainty, recent model studies suggest that the precipitation response to ENSO will be enhanced in the tropical Pacific under future warming, and as such the societal impacts of ENSO will increase. Here we use temperature and precipitation data from an ensemble of 41 CMIP5 models to show where ENSO teleconnections are being enhanced and dampened in a high-emission future scenario (RCP8.5) focusing on the changes that are occurring over land areas globally. Although there is some spread between the model projections, robust changes with strong ensemble agreement are found in certain locations, including amplification of teleconnections in southeast Australia, South America and the Maritime Continent. Our results suggest that in these regions future ENSO events will lead to more extreme temperature and rainfall responses.

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

Northern Hemisphere Winter Climate Response to Greenhouse Gas, Ozone, Solar and Volcanic Forcing

NASA Technical Reports Server (NTRS)

Shindell, Drew T.; Schmidt, Gavin A.; Miller, Ron L.; Rind, David; Hansen, James E. (Technical Monitor)

2001-01-01

The Goddard Institute for Space Studies (GISS) climate/middle atmosphere model has been used to study the impacts of increasing greenhouse gases, polar ozone depletion, volcanic eruptions, and solar cycle variability. We focus on the projection of the induced responses onto Northern Hemisphere winter surface climate. Changes in the model's surface climate take place largely through enhancement of existing variability patterns, with greenhouse gases, polar ozone depletion and volcanic eruptions primarily affecting the Arctic Oscillation (AO) pattern. Perturbations descend from the stratosphere to the surface in the model by altering the propagation of planetary waves coming up from the surface, in accord with observational evidence. Models lacking realistic stratospheric dynamics fail to capture these wave flux changes. The results support the conclusion that the stratosphere plays a crucial role in recent AO trends. We show that in our climate model, while ozone depletion has a significant effect, greenhouse gas forcing is the only one capable of causing the large, sustained increase in the AO observed over recent decades. This suggests that the AO trend, and a concurrent strengthening of the stratospheric vortex over the Arctic, are very likely anthropogenic in origin.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Ice sheet climate modeling: past achievements, ongoing challenges, and future endeavors

NASA Astrophysics Data System (ADS)

Lenaerts, J.

2017-12-01

Fluctuations in surface mass balance (SMB) mask out a substantial portion of contemporary Greenland and Antarctic ice sheet mass loss. That implies that we need accurate, consistent, and long-term SMB time series to isolate the mass loss signal. This in turn requires understanding of the processes driving SMB, and how they interplay. The primary controls on present-day ice sheet SMB are snowfall, which is regulated by large-scale atmospheric variability, and surface meltwater production at the ice sheet's edges, which is a complex result of atmosphere-surface interactions. Additionally, wind-driven snow redistribution and sublimation are large SMB contributors on the downslope areas of the ice sheets. Climate models provide an integrated framework to simulate all these individual ice sheet components. Recent developments in RACMO2, a regional climate model bound by atmospheric reanalyses, have focused on enhancing horizontal resolution, including blowing snow, snow albedo, and meltwater processes. Including these physics not only enhanced our understanding of the ice sheet climate system, but also enabled to obtain increasingly accurate estimates of ice sheet SMB. However, regional models are not suitable to capture the mutual interactions between ice sheet and the remainder of the global climate system in transient climates. To take that next step, global climate models are essential. In this talk, I will highlight our present work on improving ice sheet climate in the Community Earth System Model (CESM). In particular, we focus on an improved representation of polar firn, ice sheet clouds, and precipitation. For this exercise, we extensively use field observations, remote sensing data, as well as RACMO2. Next, I will highlight how CESM is used to enhance our understanding of ice sheet SMB, its drivers, and past and present changes.

Relative contributions of mean-state shifts and ENSO-driven variability to precipitation changes in a warming climate

DOE PAGES

Bonfils, Celine J. W.; Santer, Benjamin D.; Phillips, Thomas J.; ...

2015-12-18

The El Niño–Southern Oscillation (ENSO) is an important driver of regional hydroclimate variability through far-reaching teleconnections. This study uses simulations performed with coupled general circulation models (CGCMs) to investigate how regional precipitation in the twenty-first century may be affected by changes in both ENSO-driven precipitation variability and slowly evolving mean rainfall. First, a dominant, time-invariant pattern of canonical ENSO variability (cENSO) is identified in observed SST data. Next, the fidelity with which 33 state-of-the-art CGCMs represent the spatial structure and temporal variability of this pattern (as well as its associated precipitation responses) is evaluated in simulations of twentieth-century climate change.more » Possible changes in both the temporal variability of this pattern and its associated precipitation teleconnections are investigated in twenty-first-century climate projections. Models with better representation of the observed structure of the cENSO pattern produce winter rainfall teleconnection patterns that are in better accord with twentieth-century observations and more stationary during the twenty-first century. Finally, the model-predicted twenty-first-century rainfall response to cENSO is decomposed into the sum of three terms: 1) the twenty-first-century change in the mean state of precipitation, 2) the historical precipitation response to the cENSO pattern, and 3) a future enhancement in the rainfall response to cENSO, which amplifies rainfall extremes. Lastly, by examining the three terms jointly, this conceptual framework allows the identification of regions likely to experience future rainfall anomalies that are without precedent in the current climate.« less

Large-scale assessment of present day and future groundwater recharge and its sensitivity to climate variability in Europe's karst regions

NASA Astrophysics Data System (ADS)

Hartmann, A. J.; Gleeson, T. P.; Wagener, T.; Wada, Y.

2016-12-01

Karst aquifers in Europe are an important source of fresh water contributing up to half of the total drinking water supply in some countries. Karstic groundwater recharge is one of the most important components of the water balance of karst systems as it feeds the karst aquifers. Presently available large-scale hydrological models do not consider karst heterogeneity adequately. Projections of current and potential future groundwater recharge of Europe's karst aquifers are therefore unclear. In this study we compare simulations of present (1991-2010) and future (2080-2099) recharge using two different models to simulate groundwater recharge processes. One model includes karst processes (subsurface heterogeneity, lateral flow and concentrated recharge), while the other is based on the conceptual understanding of common hydrological systems (homogeneous subsurface, saturation excess overland flow). Both models are driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). To further assess sensitivity of groundwater recharge to climate variability, we calculate the elasticity of recharge rates to annual precipitation, temperature and average intensity of rainfall events, which is the median change of recharge that corresponds to the median change of these climate variables within the present and future time period, respectively. Our model comparison shows that karst regions over Europe have enhanced recharge rates with greater inter-annual variability compared to those with more homogenous subsurface properties. Furthermore, the heterogeneous representation shows stronger elasticity concerning climate variability than the homogeneous subsurface representation. This difference tends to increase towards the future. Our results suggest that water management in regions with heterogeneous subsurface can expect a higher water availability than estimated by most of the current large-scale simulations, while measures should be taken to prepare for increasingly variable groundwater recharge rates.

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.

Variability of western Amazon dry-season precipitation extremes: importance of decadal fluctuations and implications for predictability

NASA Astrophysics Data System (ADS)

Fernandes, K.; Baethgen, W.; Verchot, L. V.; Giannini, A.; Pinedo-Vasquez, M.

2014-12-01

A complete assessment of climate change projections requires understanding the combined effects of decadal variability and long-term trends and evaluating the ability of models to simulate them. The western Amazon severe droughts of the 2000s were the result of a modest drying trend enhanced by reduced moisture transport from the tropical Atlantic. Most of the WA dry-season precipitation decadal variability is attributable to decadal fluctuations of the north-south gradient (NSG) in Atlantic sea surface temperature (SST). The observed WA and NSG decadal co-variability is well reproduced in Global Climate Models (GCMs) pre-industrial control (PIC) and historical (HIST) experiments that were part of the Intergovernmental Panel on Climate Change fifth assessment report (IPCC-AR5). This suggests that unforced or natural climate variability, characteristic of the PIC simulations, determines the nature of this coupling, as the results from HIST simulations (forced with greenhouse gases (GHG) and natural and anthropogenic aerosols) are comparable in magnitude and spatial distribution. Decadal fluctuation in the NSG also determines shifts in the probability of repeated droughts and pluvials in WA, as there is a 65% chance of 3 or more years of droughts per decade when NSG>0 compared to 18% when NSG<0. The HIST and PIC model simulations also reproduce the observed shifts in probability distribution of droughts and pluvials as a function of the NSG decadal phase, suggesting there is great potential for decadal predictability based on GCMs. Persistence of the current NSG positive phase may lead to continuing above normal frequencies of western Amazon dry-season droughts.

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.

Continental-scale temperature covariance in proxy reconstructions and climate models

NASA Astrophysics Data System (ADS)

Hartl-Meier, Claudia; Büntgen, Ulf; Smerdon, Jason; Zorita, Eduardo; Krusic, Paul; Ljungqvist, Fredrik; Schneider, Lea; Esper, Jan

2017-04-01

Inter-continental temperature variability over the past millennium has been reported to be more coherent in climate model simulations than in multi-proxy-based reconstructions, a finding that undermines the representation of spatial variability in either of these approaches. We assess the covariance of summer temperatures among Northern Hemisphere continents by comparing tree-ring based temperature reconstructions with state-of-the-art climate model simulations over the past millennium. We find inter-continental temperature covariance to be larger in tree-ring-only reconstructions compared to those derived from multi-proxy networks, thus enhancing the agreement between proxy- and model-based spatial representations. A detailed comparison of simulated temperatures, however, reveals substantial spread among the models. Over the past millennium, inter-continental temperature correlations are driven by the cooling after major volcanic eruptions in 1257, 1452, 1601, and 1815. The coherence of these synchronizing events appears to be elevated in several climate simulations relative to their own covariance baselines and the proxy reconstructions, suggesting these models overestimate the amplitude of cooling in response to volcanic forcing at large spatial scales.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

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

PubMed

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

2015-06-24

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

iClimate: a climate data and analysis portal

NASA Astrophysics Data System (ADS)

Goodman, P. J.; Russell, J. L.; Merchant, N.; Miller, S. J.; Juneja, A.

2015-12-01

We will describe a new climate data and analysis portal called iClimate that facilitates direct comparisons between available climate observations and climate simulations. Modeled after the successful iPlant Collaborative Discovery Environment (www.iplantcollaborative.org) that allows plant scientists to trade and share environmental, physiological and genetic data and analyses, iClimate provides an easy-to-use platform for large-scale climate research, including the storage, sharing, automated preprocessing, analysis and high-end visualization of large and often disparate observational and model datasets. iClimate will promote data exploration and scientific discovery by providing: efficient and high-speed transfer of data from nodes around the globe (e.g. PCMDI and NASA); standardized and customized data/model metrics; efficient subsampling of datasets based on temporal period, geographical region or variable; and collaboration tools for sharing data, workflows, analysis results, and data visualizations with collaborators or with the community at large. We will present iClimate's capabilities, and demonstrate how it will simplify and enhance the ability to do basic or cutting-edge climate research by professionals, laypeople and students.

Rapid climate fluctuations over the past millennium: evidence from a lacustrine record of Basomtso Lake, southeastern Tibetan Plateau

PubMed Central

Li, Kai; Liu, Xingqi; Herzschuh, Ulrike; Wang, Yongbo

2016-01-01

Abrupt climate changes and fluctuations over short time scales are superimposed on long-term climate changes. Understanding rapid climate fluctuations at the decadal time scale over the past millennium will enhance our understanding of patterns of climate variability and aid in forecasting climate changes in the future. In this study, climate changes on the southeastern Tibetan Plateau over the past millennium were determined from a 4.82-m-long sediment core from Basomtso Lake. At the centennial time scale, the Medieval Climate Anomaly (MCA), Little Ice Age (LIA) and Current Warm Period (CWP) are distinct in the Basomtso region. Rapid climate fluctuations inferred from five episodes with higher sediment input and likely warmer conditions, as well as seven episodes with lower sediment input and likely colder conditions, were well preserved in our record. These episodes with higher and lower sediment input are characterized by abrupt climate changes and short time durations. Spectral analysis indicates that the climate variations at the centennial scale on the southeastern Tibetan Plateau are influenced by solar activity during the past millennium. PMID:27091591

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.

Data-model synthesis of grassland carbon metabolism. Quantifying direct, indirect & interactive effects of warming & elevated CO 2

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

Pendall, Elise; Ogle, Kiona; Parton, William

2016-02-29

This research project improved understanding of how climate change (elevated atmospheric CO 2, warming and altered precipitation) can affect grassland ecosystem productivity and nutrient availability. Our advanced experimental and modeling methods allowed us to test 21 specific hypotheses. We found that ecosystem changes over years of exposure to climate change can shift the plant communities and potentially make them more resilient to future climate changes. These changes in plant communities may be related to increased growth of belowground roots and enhanced nutrient uptake by some species. We also found that climate change can increase the spread of invasive and noxiousmore » weeds. These findings are important for land managers to make adaptive planning decisions for domestic livestock production in response to climate variability in semi-arid grasslands.« less

Past climates primary productivity changes in the Indian Ocean

NASA Astrophysics Data System (ADS)

Le Mézo, P. K.; Kageyama, M.; Bopp, L.; Beaufort, L.; Braconnot, P.; Bassinot, F. C.

2016-02-01

Organic climate recorders, e.g., coccolithophorids and foraminifera, are widely used to reconstruct past climate conditions, such as the Indian monsoon intensity and variability, since they are sensitive to climate-induced fluctuations of their environment. In the Indian Ocean, it is commonly accepted that a stronger summer monsoon will enhance productivity in the Arabian Sea and therefore the amount of organisms in a sediment core should reflect monsoon intensity. In this study, we use the coupled Earth System Model IPSLCM5A, which has a biogeochemical component PISCES that simulates primary production. We use 8 climate simulations of the IPSL-CM5A model, from -72kyr BP climate conditions to a preindustrial state. Our simulations have different orbital forcing (precession, obliquity and eccentricity), greenhouse gas concentrations as well as different ice sheet covers. The objective of this work is to characterize the mechanisms behind the changes in primary productivity between the different time periods. Our model shows that in climates where monsoon is enhanced (due to changes in precession) we do not necessarily see an increase in summer productivity in the Arabian Sea, and inversely. It seems that the glacial-interglacial state of the simulation is important in driving productivity changes in this region of the world. We try to explain the changes in productivity in the Arabian Sea with the local climate and then to link the changes in local climate to large scale atmospheric forcing and commonly used Indian monsoon definitions.

Late Holocene climate variability from Lake Pupuke maar, Auckland, New Zealand

NASA Astrophysics Data System (ADS)

Striewski, B.; Shulmeister, J.; Augustinus, P. C.; Soderholm, J.

2013-10-01

Spectral analyses of quasi-annual organo-diatomaceous laminae couplets in an Auckland maar lake indicate brief (sub-decadal scale) episodes with strong spectral power and long periods of weak to no spectral power between c. 1700 to c. 550 cal. yr BP. Laminae couplet thickness appears to be a function of changes in wind flow over the basin, with enhanced wind flow deepening the mixing zone and providing additional nutrients for laminae formation. Aeolian dust from Australia amplifies the wind signal. Spectral signals in the high power episodes are focused in <4 years and 6-8 years windows. These are consistent with El Niño-Southern Oscillation (ENSO) periodicity. This climate system is known to play a major role in the modern Auckland climate whereby strongly negative (positive) ENSO are associated with enhanced (diminished) SW airflow over Auckland. ENSO events interact in the modern climate and the spectral results indicate that this is the case when spectral power is strong in the laminae. These results highlight strong but intermittent ENSO activity between 600 and 1400 cal. yr BP.

A multi-model ensemble view of winter heat flux dynamics and the dipole mode in the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Liguori, Giovanni; Di Lorenzo, Emanuele; Cabos, William

2017-02-01

Changes in surface heat fluxes affect several climate processes controlling the Mediterranean climate. These include the winter formation of deep waters, which is the primary driver of the Mediterranean Sea overturning circulation. Previous studies that characterize the spatial and temporal variability of surface heat flux anomalies over the basin reveal the existence of two statistically dominant patterns of variability: a monopole of uniform sign and an east-west dipole of opposite signs. In this work, we use the 12 regional climate model ensemble from the EU-FP6 ENSEMBLES project to diagnose the large-scale atmospheric processes that control the variability of heat fluxes over the Mediterranean Sea from interannual to decadal timescales (here defined as timescales > 6 year). Our findings suggest that while the monopole structure captures variability in the winter-to-winter domain-average net heat flux, the dipole pattern tracks changes in the Mediterranean climate that are connected to the East Atlantic/Western Russia (EA/WR) atmospheric teleconnection pattern. Furthermore, while the monopole exhibits significant differences in the spatial structure across the multi-model ensemble, the dipole pattern is very robust and more clearly identifiable in the anomaly maps of individual years. A heat budget analysis of the dipole pattern reveals that changes in winds associated with the EA/WR pattern exert dominant control through both a direct effect on the latent heat flux (i.e., wind speed) and an indirect effect through specific humidity (e.g., wind advection). A simple reconstruction of the heat flux variability over the deep-water formation regions of the Gulf of Lion and the Aegean Sea reveals that the combination of the monopole and dipole time series explains over 90 % of the heat flux variance in these regions. Given the important role that surface heat flux anomalies play in deep-water formation and the regional climate, improving our knowledge on the dynamics controlling the leading modes of heat flux variability may enhance our predictability of the climate of the Mediterranean area.

Decadal climate prediction with a refined anomaly initialisation approach

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Advancing the adaptive capacity of social-ecological systems to absorb climate extremes

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja

2017-04-01

The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.

Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

NASA Astrophysics Data System (ADS)

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells D.; Lang, Megan W.; Sharifi, Amir

2018-01-01

Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2 concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085-2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of ˜ 70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha-1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.

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

ENSO modulation of tropical Indian Ocean subseasonal variability

NASA Astrophysics Data System (ADS)

Jung, Eunsil; Kirtman, Ben P.

2016-12-01

In this study, we use 30 years of retrospective climate model forecasts and observational estimates to show that El Niño/Southern Oscillation (ENSO) affects the amplitude of subseasonal variability of sea surface temperature (SST) in the southwest Indian Ocean, an important Tropical Intraseasonal Oscillation (TISO) onset region. The analysis shows that deeper background mixed-layer depths and warmer upper ocean conditions during El Niño reduce the amplitude of the subseasonal SST variability over Seychelles-Chagos Thermocline Ridge (SCTR), which may reduce SST-wind coupling and the amplitude of TISO variability. The opposite holds for La Niña where the shallower mixed-layer depth enhances SST variability over SCTR, which may increase SST-wind coupling and the amplitude of TISO variability.

Advancing water resource management in agricultural, rural, and urbanizing watersheds: Enhancing University involvement

USDA-ARS?s Scientific Manuscript database

In this research editorial we make four points relative to solving water resource issues: (1) they are complex problems and difficult to solve, (2) some progress has been made on solving these issues, (3) external non-stationary drivers such as land use changes, climate change and variability, and s...

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

USDA-ARS?s Scientific Manuscript database

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

Strong sensitivity of Pine Island ice-shelf melting to climatic variability.

PubMed

Dutrieux, Pierre; De Rydt, Jan; Jenkins, Adrian; Holland, Paul R; Ha, Ho Kyung; Lee, Sang Hoon; Steig, Eric J; Ding, Qinghua; Abrahamsen, E Povl; Schröder, Michael

2014-01-10

Pine Island Glacier has thinned and accelerated over recent decades, significantly contributing to global sea-level rise. Increased oceanic melting of its ice shelf is thought to have triggered those changes. Observations and numerical modeling reveal large fluctuations in the ocean heat available in the adjacent bay and enhanced sensitivity of ice-shelf melting to water temperatures at intermediate depth, as a seabed ridge blocks the deepest and warmest waters from reaching the thickest ice. Oceanic melting decreased by 50% between January 2010 and 2012, with ocean conditions in 2012 partly attributable to atmospheric forcing associated with a strong La Niña event. Both atmospheric variability and local ice shelf and seabed geometry play fundamental roles in determining the response of the Antarctic Ice Sheet to climate.

Surface Variability of Short-wavelength Radiation and Temperature on Exoplanets around M Dwarfs

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

Zhang, Xin; Tian, Feng; Wang, Yuwei

2017-03-10

It is a common practice to use 3D General Circulation Models (GCM) with spatial resolution of a few hundred kilometers to simulate the climate of Earth-like exoplanets. The enhanced albedo effect of clouds is especially important for exoplanets in the habitable zones around M dwarfs that likely have fixed substellar regions and substantial cloud coverage. Here, we carry out mesoscale model simulations with 3 km spatial resolution driven by the initial and boundary conditions in a 3D GCM and find that it could significantly underestimate the spatial variability of both the incident short-wavelength radiation and the temperature at planet surface.more » Our findings suggest that mesoscale models with cloud-resolving capability be considered for future studies of exoplanet climate.« less

The summer North Atlantic Oscillation (SNAO) variability on decadal to paleoclimate time scales

NASA Astrophysics Data System (ADS)

Linderholm, H. W.; Folland, C. K.; Zhang, P.; Gunnarson, B. E.; Jeong, J. H.; Ren, H.

2017-12-01

The summer North Atlantic Oscillation (SNAO), strongly related to the latitude of the North Atlantic and European summer storm tracks, exerts a considerable influence on European summer climate variability and extremes. Here we extend the period covered by the SNAO from July and August to June, July and August (JJA). As well as marked interannual variability, the JJA SNAO has shown a large inter-decadal change since the 1970s. Decadally averaged, there has been a change from a very positive to a rather negative SNAO phase. This change in SNAO phase is opposite in sign from that expected by a number of climate models under enhanced greenhouse forcing by the late twenty first century. It has led to noticeably wetter summers in North West Europe in the last decade. On interannual to multidecadal timescales, SNAO variability is linked to variations in North Atlantic sea surface temperature (SST): observations and models indicate an association between the Atlantic Multi-decadal Oscillation (AMO) where the cold (warm) phase of the AMO corresponds a positive (negative) phase of the SNAO. Observations also indicate a link with SST in the Gulf Stream region of the North Atlantic where, particularly on decadal time scales, SST warming may favour a more positive phase of the SNAO. Influences of Arctic climate change on North Atlantic and European atmospheric circulation may also exist, particularly reduced sea ice coverage, perhaps favouring the negative phase of the SNAO. A new tree-ring data based JJA SNAO reconstruction extending over the last millennium, as well as climate model output for the same period, enables us to examine the influence of North Atlantic SST and Arctic sea-ice coverage, as well as SNAO impacts on European summer climate, in a long-term, pre-industrial context.

A two-fold increase of carbon cycle sensitivity to tropical temperature variations.

PubMed

Wang, Xuhui; Piao, Shilong; Ciais, Philippe; Friedlingstein, Pierre; Myneni, Ranga B; Cox, Peter; Heimann, Martin; Miller, John; Peng, Shushi; Wang, Tao; Yang, Hui; Chen, Anping

2014-02-13

Earth system models project that the tropical land carbon sink will decrease in size in response to an increase in warming and drought during this century, probably causing a positive climate feedback. But available data are too limited at present to test the predicted changes in the tropical carbon balance in response to climate change. Long-term atmospheric carbon dioxide data provide a global record that integrates the interannual variability of the global carbon balance. Multiple lines of evidence demonstrate that most of this variability originates in the terrestrial biosphere. In particular, the year-to-year variations in the atmospheric carbon dioxide growth rate (CGR) are thought to be the result of fluctuations in the carbon fluxes of tropical land areas. Recently, the response of CGR to tropical climate interannual variability was used to put a constraint on the sensitivity of tropical land carbon to climate change. Here we use the long-term CGR record from Mauna Loa and the South Pole to show that the sensitivity of CGR to tropical temperature interannual variability has increased by a factor of 1.9 ± 0.3 in the past five decades. We find that this sensitivity was greater when tropical land regions experienced drier conditions. This suggests that the sensitivity of CGR to interannual temperature variations is regulated by moisture conditions, even though the direct correlation between CGR and tropical precipitation is weak. We also find that present terrestrial carbon cycle models do not capture the observed enhancement in CGR sensitivity in the past five decades. More realistic model predictions of future carbon cycle and climate feedbacks require a better understanding of the processes driving the response of tropical ecosystems to drought and warming.

Reduced interdecadal variability of Atlantic Meridional Overturning Circulation under global warming

PubMed Central

Cheng, Jun; Liu, Zhengyu; Zhang, Shaoqing; Liu, Wei; Dong, Lina; Liu, Peng; Li, Hongli

2016-01-01

Interdecadal variability of the Atlantic Meridional Overturning Circulation (AMOC-IV) plays an important role in climate variation and has significant societal impacts. Past climate reconstruction indicates that AMOC-IV has likely undergone significant changes. Despite some previous studies, responses of AMOC-IV to global warming remain unclear, in particular regarding its amplitude and time scale. In this study, we analyze the responses of AMOC-IV under various scenarios of future global warming in multiple models and find that AMOC-IV becomes weaker and shorter with enhanced global warming. From the present climate condition to the strongest future warming scenario, on average, the major period of AMOC-IV is shortened from ∼50 y to ∼20 y, and the amplitude is reduced by ∼60%. These reductions in period and amplitude of AMOC-IV are suggested to be associated with increased oceanic stratification under global warming and, in turn, the speedup of oceanic baroclinic Rossby waves. PMID:26951654

Recharge heterogeneity and high intensity rainfall events increase contamination risk for Mediterranean groundwater resources

NASA Astrophysics Data System (ADS)

Hartmann, Andreas; Jasechko, Scott; Gleeson, Tom; Wada, Yoshihide; Andreo, Bartolomé; Barberá, Juan Antonio; Brielmann, Heike; Charlier, Jean-Baptiste; Darling, George; Filippini, Maria; Garvelmann, Jakob; Goldscheider, Nico; Kralik, Martin; Kunstmann, Harald; Ladouche, Bernard; Lange, Jens; Mudarra, Matías; Francisco Martín, José; Rimmer, Alon; Sanchez, Damián; Stumpp, Christine; Wagener, Thorsten

2017-04-01

Karst develops through the dissolution of carbonate rock and results in pronounced spatiotemporal heterogeneity of hydrological processes. Karst groundwater in Europe is a major source of fresh water contributing up to half of the total drinking water supply in some countries like Austria or Slovenia. Previous work showed that karstic recharge processes enhance and alter the sensitivity of recharge to climate variability. The enhanced preferential flow from the surface to the aquifer may be followed by enhanced risk of groundwater contamination. In this study we assess the contamination risk of karst aquifers over Europe and the Mediterranean using simulated transit time distributions. Using a new type of semi-distributed model that considers the spatial heterogeneity of karst hydraulic properties, we were able to simulate karstic groundwater recharge including its heterogeneous spatiotemporal dynamics. The model is driven by gridded daily climate data from the Global Land Data Assimilation System (GLDAS). Transit time distributions are calculated using virtual tracer experiments. We evaluated our simulations by independent information on transit times derived from observed time series of water isotopes of >70 karst springs over Europe. The simulations indicate that, compared to humid, mountain and desert regions, the Mediterranean region shows a stronger risk of contamination in Europe because preferential flow processes are most pronounced given thin soil layers and the seasonal abundance of high intensity rainfall events in autumn and winter. Our modelling approach includes strong simplifications and its results cannot easily be generalized but it still highlights that the combined effects of variable climate and heterogeneous catchment properties constitute a strong risk on water quality.

Inter Annual Variability of the Acoustic Propagation in the Yellow Sea Identified from a Synoptic Monthly Gridded Database as Compared with GDEM

DTIC Science & Technology

2016-09-01

the world climate is in fact warming due to anthropogenic causes (Anderegg et al. 2010; Solomon et al. 2009). To put this in terms for this research ...2006). The present research uses a 0.5’ resolution. B. SEDIMENTS DATABASE There are four openly available sediment databases: Enhanced, Standard...DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) This research investigates the inter-annual acoustic variability in the Yellow Sea identified from

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.

Net Influence of an Internally Generated Guasi-biennial Oscillation on Modelled Stratospheric Climate and Chemistry

NASA Technical Reports Server (NTRS)

Hurwitz, Margaret M.; Oman, Luke David; Newman, Paul A.; Song, InSun

2013-01-01

A Goddard Earth Observing System Chemistry- Climate Model (GEOSCCM) simulation with strong tropical non-orographic gravity wave drag (GWD) is compared to an otherwise identical simulation with near-zero tropical non-orographic GWD. The GEOSCCM generates a quasibiennial oscillation (QBO) zonal wind signal in response to a tropical peak in GWD that resembles the zonal and climatological mean precipitation field. The modelled QBO has a frequency and amplitude that closely resembles observations. As expected, the modelled QBO improves the simulation of tropical zonal winds and enhances tropical and subtropical stratospheric variability. Also, inclusion of the QBO slows the meridional overturning circulation, resulting in a generally older stratospheric mean age of air. Slowing of the overturning circulation, changes in stratospheric temperature and enhanced subtropical mixing all affect the annual mean distributions of ozone, methane and nitrous oxide. Furthermore, the modelled QBO enhances polar stratospheric variability in winter. Because tropical zonal winds are easterly in the simulation without a QBO, there is a relative increase in tropical zonal winds in the simulation with a QBO. Extratropical differences between the simulations with and without a QBO thus reflect the westerly shift in tropical zonal winds: a relative strengthening of the polar stratospheric jet, polar stratospheric cooling and a weak reduction in Arctic lower stratospheric ozone.

CIRUN: Climate Information Responding to User Needs

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-12-01

The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.

A 13000-year, high-resolution multi-proxy record of climate variability with episodes of enhanced atmospheric dust in Western Asia: Evidence from Neor peat complex in NW Iran

NASA Astrophysics Data System (ADS)

Sharifi, O.; Pourmand, A.; Canuel, E. A.; Peterson, L. C.

2011-12-01

The regional climate over West Asia, extending between Iran and the Arabian Peninsula to the eastern Mediterranean Sea, is governed by interactions between three major synoptic systems; mid-latitude Westerlies, the Siberian Anticyclone and the Indian Ocean Summer Monsoon. In recent years, a number of paleoclimate studies have drawn potential links between episodes of abrupt climate change during the Holocene, and the rise and fall of human civilizations across the "Fertile Crescent" of West Asia. High-resolution archives of climate variability from this region, however, are scarce, and at times contradicting. For example, while pollen and planktonic data from lakes in Turkey and Iran suggest that dry, continental conditions prevailed during the early-middle Holocene, oxygen isotope records indicate that relatively wet conditions dominated during this interval over West Asia. We present interannual to decadal multi-proxy records of climate variability from a peat complex in NW Iran to reconstruct changes in moisture and atmospheric dust content during the last 13000 years. Radiocarbon dating on 20 samples from a 775-cm peat core show a nearly constant rate of accumulation (1.7 mm yr-1, R2=0.99) since 13356 ± 116 cal yr B.P. Down-core X-ray fluorescence measurements of conservative lithogenic elements (e.g., Al, Zr, Ti) as well as redox-sensitive elements (e.g., Fe, K, Rb, Zn, Cu, and Co) at 2 mm intervals reveal several periods of elevated dust input to this region since the early Holocene. Down-core variations of total organic carbon and total nitrogen co-vary closely and are inversely correlated with conservative lithogenic elements (Al, Si, Ti), indicating a potential link between climate change and accumulation of organic carbon in the Neor peat mire. Major episodes of enhanced dust deposition (13000-12000, 11700-11200, 9200-8800, 7000-6000, 4200-3200, 2800-2200 and 1500-600 cal yr B.P) are in good agreement with other proxy records that document more arid climate in Asia and eastern Mediterranean Sea during these intervals. The relationship between periods of elevated dust input and the response of civilizations in the region, such as the Akkadian and Persian Empires, can also be inferred from variation of conservative lithogenic elements since 4200 cal yr B.P. Intensive dust deposition during 4200-3200 cal yr BP, for example, coincides with similar dry conditions documented by oxygen isotope and geochemical data from Lake Van and Tecer of Turkey, the geochemical data from the Gulf of Oman and oxygen isotope records from Soreq Cave in Israel. Several significant periodicities (e.g. 750, 900, 1550 and 3000 yr) observed from wavelet analysis of refractory elements correspond with the timing of internal climate feedbacks and/or solar variability as potential modulating mechanisms for abrupt climate change in West Asia during the Holocene.

Variability in seeds: biological, ecological, and agricultural implications.

PubMed

Mitchell, Jack; Johnston, Iain G; Bassel, George W

2017-02-01

Variability is observed in biology across multiple scales, ranging from populations, individuals, and cells to the molecular components within cells. This review explores the sources and roles of this variability across these scales, focusing on seeds. From a biological perspective, the role and the impact this variability has on seed behaviour and adaptation to the environment is discussed. The consequences of seed variability on agricultural production systems, which demand uniformity, are also examined. We suggest that by understanding the basis and underlying mechanisms of variability in seeds, strategies to increase seed population uniformity can be developed, leading to enhanced agricultural production across variable climatic conditions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Variability and changes in tropospheric ozone over the western United States (1980-2010): Exploring the roles of stratosphere-to-troposphere transport and El Niño-Southern Oscillation

NASA Astrophysics Data System (ADS)

Lin, M.; Fiore, A. M.; Horowitz, L. W.; Naik, V.; Oltmans, S. J.; Levy, H.; Cooper, O. R.; Johnson, B. J.

2011-12-01

Understanding the drivers of inter-annual variability and long-term changes of tropospheric ozone is crucial for designing appropriate control policies. Advancing this knowledge will also enable process-oriented assessments of chemistry-climate models, which are needed to build confidence in their utility for projecting tropospheric ozone under future climate scenarios. We examine here the response of North American background ozone over the past 30 years (1980-2010) to changes in atmospheric circulation and chemistry, both in the stratosphere and in the troposphere, through an integrated analysis of observational records from satellite, ozonesonde and ground-based networks with the GFDL AM3 global chemistry-climate model (nudged to reanalysis winds to allow for exact space-time comparisons with the observational datasets). Comparing the model simulation with ~30 years of ozone measurements at Mauna Loa ground station (~3397 m a.s.l.) and Hilo sonde (550-450 hPa) in Hawaii, we find that mid-tropospheric ozone in the eastern Pacific extratropics is enhanced by ~5-10 ppbv (~10-20% deviations from the climatological mean) during strong El Niño events (i.e. 1982-1983, 1997-1998, 2009-2010), presumably reflecting stronger transport from the stratosphere and Asia due to the eastward extension of the Pacific storm tracks and amplified subtropical jet. The La Niña condition typically manifests in the opposite sign, with ozone decreasing north of Hawaii. Over the western U.S., however, both cyclonic and anticyclonic circulation following strong El Niño and La Niña winters, respectively, may enhance deep stratosphere-to-troposphere transport in spring. Both ozonesonde and model results sampled at Trinidad Head, California, indicate ~25% positive deviations in UT/LS ozone during the El Niño winters of 1997-1998 and 2009-2010. We find that this ENSO-related UT/LS ozone variability is also captured in satellite-derived total column ozone from TOMS and AIRS over the Northwest U.S. in May. In contrast, enhanced lower tropospheric ozone over the western U.S. during strong La Niña years (e.g. 1999) mostly reflect changes in atmospheric dynamics rather than lower stratospheric ozone. The model indicates a 0.2 ppb/yr increase in mid-tropospheric ozone over the past 25 years. We are implementing a stratospheric ozone tracer in the model to quantify the springtime stratospheric enhancement to the high tail of daily maximum 8-hour surface ozone frequency during both phases of ENSO. We expect that the associated variability should provide insights regarding potential responses to climate shifts as well as inform air quality planning and control strategies to attain the national standard.

From Past to future: the Paleoclimate Modelling Intercomparison Project's contribution to CMIP6

NASA Astrophysics Data System (ADS)

Kageyama, Masa; Braconnot, Pascale; Harrison, Sandy; Haywood, Alan; Jungclaus, Johann; Otto-Bliesner, Bette; Abe-Ouchi, Ayako

2016-04-01

Since the 1990s, PMIP has developed with the following objectives: 1/to evaluate the ability of climate models used for climate prediction in simulating well-documented past climates outside the range of present and recent climate variability; 2/to understand the mechanisms of these climate changes, in particular the role of the different climate feedbacks. To achieve these goals, PMIP has actively fostered paleo-data syntheses, multi-model analyses, including analyses of relationships between model results from past and future simulations, and model-data comparisons. For CMIP6, PMIP will focus on five past periods: - the Last Millennium (850 CE - present), to analyse natural climate variability on multidecadal or longer time-scales - the mid-Holocene, 6000 years ago, to compare model runs with paleodata for a period of warmer climate in the Northern Hemisphere, with an enhanced hydrological cycle - the Last Glacial Maximum, 21000 years ago, to evaluate the ability of climate models to represent a cold climate extreme and examine whether paleoinformation about this period can help and constrain climate sensitivity - the Last InterGlacial (~127,000 year ago), which provides a benchmark for a period of high sea-level stand - the mid-Pliocene warm period (~3.2 million years ago), which allows for the evaluation of the model's long-term response to a CO2 level analogous to the modern one. This poster will present the rationale of these "PMIP4-CMIP6" experiments. Participants are invited to come and discuss about the experimental set-up and the model output to be distributed via CMIP6. For more information and discussion of the PMIP4-CMIP6 experimental design, please visit: https://wiki.lsce.ipsl.fr/pmip3/doku.php/pmip3:cmip6:design:index

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

USGS Publications Warehouse

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

2016-01-01

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

Precipitation isoscapes for New Zealand: enhanced temporal detail using precipitation-weighted daily climatology.

PubMed

Baisden, W Troy; Keller, Elizabeth D; Van Hale, Robert; Frew, Russell D; Wassenaar, Leonard I

2016-01-01

Predictive understanding of precipitation δ(2)H and δ(18)O in New Zealand faces unique challenges, including high spatial variability in precipitation amounts, alternation between subtropical and sub-Antarctic precipitation sources, and a compressed latitudinal range of 34 to 47 °S. To map the precipitation isotope ratios across New Zealand, three years of integrated monthly precipitation samples were acquired from >50 stations. Conventional mean-annual precipitation δ(2)H and δ(18)O maps were produced by regressions using geographic and annual climate variables. Incomplete data and short-term variation in climate and precipitation sources limited the utility of this approach. We overcome these difficulties by calculating precipitation-weighted monthly climate parameters using national 5-km-gridded daily climate data. This data plus geographic variables were regressed to predict δ(2)H, δ(18)O, and d-excess at all sites. The procedure yields statistically-valid predictions of the isotope composition of precipitation (long-term average root mean square error (RMSE) for δ(18)O = 0.6 ‰; δ(2)H = 5.5 ‰); and monthly RMSE δ(18)O = 1.9 ‰, δ(2)H = 16 ‰. This approach has substantial benefits for studies that require the isotope composition of precipitation during specific time intervals, and may be further improved by comparison to daily and event-based precipitation samples as well as the use of back-trajectory calculations.

Holocene variability in the intensity of wind-gap upwelling in the tropical eastern Pacific

USGS Publications Warehouse

Toth, Lauren T.; Aronson, Richard B.; Cheng, Hai; Edwards, R. Lawrence

2015-01-01

Wind-driven upwelling in Pacific Panamá is a significant source of oceanographic variability in the tropical eastern Pacific. This upwelling system provides a critical teleconnection between the Atlantic and tropical Pacific that may impact climate variability on a global scale. Despite its importance to oceanographic circulation, ecology, and climate, little is known about the long-term stability of the Panamanian upwelling system or its interaction with climatic forcing on millennial time scales. Using a combination of radiocarbon and U-series dating of fossil corals collected in cores from five sites across Pacific Panamá, we reconstructed the local radiocarbon reservoir correction, ΔR, from ~6750 cal B.P. to present. Because the ΔR of shallow-water environments is elevated by upwelling, our data set represents a millennial-scale record of spatial and temporal variability of the Panamanian upwelling system. The general oceanographic gradient from relatively strong upwelling in the Gulf of Panamá to weak-to-absent upwelling in the Gulf of Chiriquí was present throughout our record; however, the intensity of upwelling in the Gulf of Panamá varied significantly through time. Our reconstructions suggest that upwelling in the Gulf of Panamá is weak at present; however, the middle Holocene was characterized by periods of enhanced upwelling, with the most intense upwelling occurring just after of a regional shutdown in the development of reefs at ~4100 cal B.P. Comparisons with regional climate proxies suggest that, whereas the Intertropical Convergence Zone is the primary control on modern upwelling in Pacific Panamá, the El Niño–Southern Oscillation drove the millennial-scale variability of upwelling during the Holocene.

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

Oscillations and trends of river discharge in the southern Central Andes and linkages with climate variability

NASA Astrophysics Data System (ADS)

Castino, Fabiana; Bookhagen, Bodo; Strecker, Manfred R.

2017-12-01

This study analyzes the discharge variability of small to medium drainage basins (102-104 km2) in the southern Central Andes of NW Argentina. The Hilbert-Huang Transform (HHT) was applied to evaluate non-stationary oscillatory modes of variability and trends, based on four time series of monthly-normalized discharge anomaly between 1940 and 2015. Statistically significant trends reveal increasing discharge during the past decades and document an intensification of the hydrological cycle during this period. An Ensemble Empirical Mode Decomposition (EEMD) analysis revealed that discharge variability in this region can be best described by five quasi-periodic statistically significant oscillatory modes, with mean periods varying from 1 to ∼20 y. Moreover, we show that discharge variability is most likely linked to the phases of the Pacific Decadal Oscillation (PDO) at multi-decadal timescales (∼20 y) and, to a lesser degree, to the Tropical South Atlantic SST anomaly (TSA) variability at shorter timescales (∼2-5 y). Previous studies highlighted a rapid increase in discharge in the southern Central Andes during the 1970s, inferred to have been associated with the global 1976-77 climate shift. Our results suggest that the rapid discharge increase in the NW Argentine Andes coincides with the periodic enhancement of discharge, which is mainly linked to a negative to positive transition of the PDO phase and TSA variability associated with a long-term increasing trend. We therefore suggest that variations in discharge in this region are largely driven by both natural variability and the effects of global climate change. We furthermore posit that the links between atmospheric and hydrologic processes result from a combination of forcings that operate on different spatiotemporal scales.

Examining the response of larch needle carbohydrates to climate using compound-specific δ13C and concentration analyses

NASA Astrophysics Data System (ADS)

Rinne, Katja T.; Saurer, Matthias; Kirdyanov, Alexander V.; Bryukhanova, Marina V.; Prokushkin, Anatoly S.; Churakova Sidorova, Olga V.; Siegwolf, Rolf T. W.

2016-04-01

Little is known about the dynamics of concentrations and carbon isotope ratios of individual carbohydrates in leaves in response to climatic and physiological factors. Improved knowledge of the isotopic ratio in sugars will enhance our understanding of the tree ring isotope ratio and will help to decipher environmental conditions in retrospect more reliably. Carbohydrate samples from larch (Larix gmelinii) needles of two sites in the continuous permafrost zone of Siberia with differing growth conditions were analysed with the Compound-Specific Isotope Analysis (CSIA). We compared concentrations and carbon isotope values (δ13C) of sucrose, fructose, glucose and pinitol combined with phenological data. The results for the variability of the needle carbohydrates show high dynamics with distinct seasonal characteristics between and within the studied years with a clear link to the climatic conditions, particularly vapour pressure deficit. Compound-specific differences in δ13C values as a response to climate were detected. The δ13C of pinitol, which contributes up to 50% of total soluble carbohydrates, was almost invariant during the whole growing season. Our study provides the first in-depth characterization of compound-specific needle carbohydrate isotope variability, identifies involved mechanisms and shows the potential of such results for linking tree physiological responses to different climatic conditions.

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

PubMed Central

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

2016-01-01

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

Climate change effects on beneficial plant-microorganism interactions.

PubMed

Compant, Stéphane; van der Heijden, Marcel G A; Sessitsch, Angela

2010-08-01

It is well known that beneficial plant-associated microorganisms may stimulate plant growth and enhance resistance to disease and abiotic stresses. The effects of climate change factors such as elevated CO(2), drought and warming on beneficial plant-microorganism interactions are increasingly being explored. This now makes it possible to test whether some general patterns occur and whether different groups of plant-associated microorganisms respond differently or in the same way to climate change. Here, we review the results of 135 studies investigating the effects of climate change factors on beneficial microorganisms and their interaction with host plants. The majority of studies showed that elevated CO(2) had a positive influence on the abundance of arbuscular and ectomycorrhizal fungi, whereas the effects on plant growth-promoting bacteria and endophytic fungi were more variable. In most cases, plant-associated microorganisms had a beneficial effect on plants under elevated CO(2). The effects of increased temperature on beneficial plant-associated microorganisms were more variable, positive and neutral, and negative effects were equally common and varied considerably with the study system and the temperature range investigated. Moreover, numerous studies indicated that plant growth-promoting microorganisms (both bacteria and fungi) positively affected plants subjected to drought stress. Overall, this review shows that plant-associated microorganisms are an important factor influencing the response of plants to climate change.

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

Ralph, F. M.; Prather, K. A.; Cayan, D.

The variability of precipitation and water supply along the U.S. West Coast creates major challenges to the region’s economy and environment, as evidenced by the recent California drought. This variability is strongly influenced by atmospheric rivers (AR), which deliver much of the precipitation along the U.S. West Coast and can cause flooding, and by aerosols (from local sources and transported from remote continents and oceans) that modulate clouds and precipitation. A better understanding of these processes is needed to reduce uncertainties in weather predictions and climate projections of droughts and floods, both now and under changing climate conditions.To address thesemore » gaps a group of meteorologists, hydrologists, climate scientists, atmospheric chemists, and oceanographers have created an interdisciplinary research effort, with support from multiple agencies. From 2009-2011 a series of field campaigns (CalWater 1) collected atmospheric chemistry, cloud microphysics and meteorological measurements in California and associated modeling and diagnostic studies were carried out. Based on remaining gaps, a vision was developed to extend these studies offshore over the Eastern North Pacific and to enhance land based measurements from 2014-2018 (CalWater 2). The data set and selected results from CalWater 1 are summarized here. The goals of CalWater-2, and measurements to date, are then described. CalWater is producing new findings and exploring new technologies to evaluate and improve global climate models and their regional performance and to develop tools supporting water and hydropower management. These advances also have potential to enhance hazard mitigation by improving near-term weather prediction and subseasonal and seasonal outlooks.« less

Climate Penalty on Air Quality and Human Health in China and India

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2017-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

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.

Long-term Internal Variability of the Tropical Pacific Atmosphere-Ocean System

NASA Astrophysics Data System (ADS)

Hadi Bordbar, Mohammad; Martin, Thomas; Park, Wonsun; Latif, Mojib

2016-04-01

The tropical Pacific has featured some remarkable trends during the recent decades such as an unprecedented strengthening of the Trade Winds, a strong cooling of sea surface temperatures (SST) in the eastern and central part, thereby slowing global warming and strengthening the zonal SST gradient, and highly asymmetric sea level trends with an accelerated rise relative to the global average in the western and a drop in the eastern part. These trends have been linked to an anomalously strong Pacific Walker Circulation, the major zonal atmospheric overturning cell in the tropical Pacific sector, but the origin of the strengthening is controversial. Here we address the question as to whether the recent decadal trends in the tropical Pacific atmosphere-ocean system are within the range of internal variability, as simulated in long unforced integrations of global climate models. We show that the recent trends are still within the range of long-term internal decadal variability. Further, such variability strengthens in response to enhanced greenhouse gas concentrations, which may further hinder detection of anthropogenic climate signals in that region.

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.

Influence of open vegetation fires on black carbon and ozone variability in the southern Himalayas (NCO-P, 5079 m a.s.l.).

PubMed

Putero, D; Landi, T C; Cristofanelli, P; Marinoni, A; Laj, P; Duchi, R; Calzolari, F; Verza, G P; Bonasoni, P

2014-01-01

We analysed the variability of equivalent black carbon (BC) and ozone (O3) at the global WMO/GAW station Nepal Climate Observatory-Pyramid (NCO-P, 5079 m a.s.l.) in the southern Himalayas, for evaluating the possible contribution of open vegetation fires to the variability of these short-lived climate forcers/pollutants (SLCF/SLCP) in the Himalayan region. We found that 162 days (9% of the data-set) were characterised by acute pollution events with enhanced BC and O3 in respect to the climatological values. By using satellite observations (MODIS fire products and the USGS Land Use Cover Characterization) and air mass back-trajectories, we deduced that 56% of these events were likely to be affected by emissions from open fires along the Himalayas foothills, the Indian Subcontinent and the Northern Indo-Gangetic Plain. These results suggest that open fire emissions are likely to play an important role in modulating seasonal and inter-annual BC and O3 variability over south Himalayas. Copyright © 2013 Elsevier Ltd. All rights reserved.

Influence of Climate Variability on US Regional Homicide Rates

NASA Astrophysics Data System (ADS)

Harp, R. D.; Karnauskas, K. B.

2017-12-01

Recent studies have found consistent evidence of a relationship between temperature and criminal behavior. However, despite agreement in the overall relationship, little progress has been made in distinguishing between two proposed explanatory theories. The General Affective Aggression Model (GAAM) suggests that high temperatures create periods of higher heat stress that enhance individual aggressiveness, whereas the Routine Activities Theory (RAT) theorizes that individuals are more likely to be outdoors interacting with others during periods of pleasant weather with a resulting increase in both interpersonal interactions and victim availability. Further, few studies have considered this relationship within the context of climate change in a quantitative manner. In an effort to distinguish between the two theories, and to examine the statistical relationships on a broader spatial scale than previously, we combined data from the Supplementary Homicide Report (SHR—compiled by the Federal Bureau of Investigation) and the North American Regional Reanalysis (NARR—compiled by the National Centers for Environmental Protection, a branch of the National Oceanic and Atmospheric Administration). US homicide data described by the SHR was compared with seven relevant observed climate variables (temperature, dew point, relative humidity, accumulated precipitation, accumulated snowfall, snow cover, and snow depth) provided by the NARR atmospheric reanalysis. Relationships between homicide rates and climate variables, as well as reveal regional spatial patterns will be presented and discussed, along with the implications due to future climate change. This research lays the groundwork for the refinement of estimates of an oft-overlooked climate change impact, which has previously been estimated to cause an additional 22,000 murders between 2010 and 2099, including providing important constraints for empirical models of future violent crime incidences in the face of global warming.

Subtropical Climate Variability since the Last Glacial Maximum from Speleothem Precipitation Reconstructions in Florida

NASA Astrophysics Data System (ADS)

Polk, J.; van Beynen, P.; DeLong, K. L.; Asmerom, Y.; Polyak, V. J.

2017-12-01

Teleconnections between the tropical-subtropical regions of the Americas since the Last Glacial Maximum (LGM), particularly the Mid- to Late-Holocene, and high-resolution proxy records refining climate variability over this period continue to receive increasing attention. Here, we present a high-resolution, precisely dated speleothem record spanning multiple periods of time since the LGM ( 30 ka) for the Florida peninsula. The data indicate that the amount effect plays a significant role in determining the isotopic signal of the speleothem calcite. Collectively, the records indicate distinct differences in climate in the region between the LGM, Mid-Holocene, and Late Holocene, including a progressive shift in ocean composition and precipitation isotopic values through the period, suggesting Florida's sensitivity to regional and global climatic shifts. Comparisons between speleothem δ18O values and Gulf of Mexico marine records reveal a strong connection between the Gulf region and the terrestrial subtropical climate in the Late Holocene, while the North Atlantic's influence is clear in the earlier portions of the record. Warmer sea surface temperatures correspond to enhanced evaporation, leading to more intense atmospheric convection in Florida, and thereby modulating the isotopic composition of rainfall above the cave. These regional signals in climate extend from the subtropics to the tropics, with a clear covariance between the speleothem signal and other proxy records from around the region, as well as global agreement during the LGM period with other records. These latter connections appear to be driven by changes in the mean position of the Intertropical Convergence Zone and time series analysis of the δ18O values reveals significant multidecadal periodicities in the record, which are evidenced by agreement with the AMV and other multidecadal influences (NAO and PDO) likely having varying influence throughout the period of record. The climate variability recorded in our record suggests complex responses to major and abrupt shifts during these periods, likely due to Florida's subtropical location and the influence of multiple climate forcing mechanisms in the region.

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

PubMed

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

2011-06-01

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

Japanese and Taiwanese pelagic longline fleet dynamics and the impacts of climate change in the southern Indian Ocean

NASA Astrophysics Data System (ADS)

Michael, P. E.; Wilcox, C.; Tuck, G. N.; Hobday, A. J.; Strutton, P. G.

2017-06-01

Climate change is projected to continue shifting the distribution of marine species, leading to changes in local assemblages and different interactions with human activities. With regard to fisheries, understanding the relationship between fishing fleets, target species catch per unit effort (CPUE), and the environment enhances our ability to anticipate fisher response and is an essential step towards proactive management. Here, we explore the potential impact of climate change in the southern Indian Ocean by modelling Japanese and Taiwanese pelagic longline fleet dynamics. We quantify the mean and variability of target species CPUE and the relative value and cost of fishing in different areas. Using linear mixed models, we identify fleet-specific effort allocation strategies most related to observed effort and predict the future distribution of effort and tuna catch under climate change for 2063-2068. The Japanese fleet's strategy targets high-value species and minimizes the variability in CPUE of the primary target species. Conversely, the Taiwanese strategy indicated flexible targeting of a broad range of species, fishing in areas of high and low variability in catch, and minimizing costs. The projected future mean and variability in CPUE across species suggest a slight increase in CPUE in currently high CPUE areas for most species. The corresponding effort projections suggest a slight increase in Japanese effort in the western and eastern study area, and Taiwanese effort increasing east of Madagascar. This approach provides a useful method for managers to explore the impacts of different fishing and fleet management strategies for the future.

Interannual Variability of Regional Hadley Circulation Intensity Over Western Pacific During Boreal Winter and Its Climatic Impact Over Asia-Australia Region

NASA Astrophysics Data System (ADS)

Huang, Ruping; Chen, Shangfeng; Chen, Wen; Hu, Peng

2018-01-01

This study investigates interannual variability of boreal winter regional Hadley circulation over western Pacific (WPHC) and its climatic impacts. A WPHC intensity index (WPHCI) is defined as the vertical shear of the divergent meridional winds. It shows that WPHCI correlates well with the El Niño-Southern Oscillation (ENSO). To investigate roles of the ENSO-unrelated part of WPHCI (WPHCIres), variables that are linearly related to the Niño-3 index have been removed. It reveals that meridional sea surface temperature gradient over the western Pacific plays an essential role in modulating the WPHCIres. The climatic impacts of WPHCIres are further investigated. Below-normal (above-normal) precipitation appears over south China (North Australia) when WPHCIres is stronger. This is due to the marked convergence (divergence) anomalies at the upper troposphere, divergence (convergence) at the lower troposphere, and the accompanied downward (upward) motion over south China (North Australia), which suppresses (enhances) precipitation there. In addition, a pronounced increase in surface air temperature (SAT) appears over south and central China when WPHCIres is stronger. A temperature diagnostic analysis suggests that the increase in SAT tendency over central China is primarily due to the warm zonal temperature advection and subsidence-induced adiabatic heating. In addition, the increase in SAT tendency over south China is primarily contributed by the warm meridional temperature advection. Further analysis shows that the correlation of WPHCIres with the East Asian winter monsoon (EAWM) is weak. Thus, this study may provide additional sources besides EAWM and ENSO to improve understanding of the Asia-Australia climate variability.

Simulation of Anomalous Regional Climate Events with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

1999-01-01

The stretched-grid approach provides an efficient down-scaling and consistent interactions between global and regional scales due to using one variable-resolution model for integrations. It is a workable alternative to the widely used nested-grid approach introduced over a decade ago as a pioneering step in regional climate modeling. A variable-resolution General Circulation Model (GCM) employing a stretched grid, with enhanced resolution over the US as the area of interest, is used for simulating two anomalous regional climate events, the US summer drought of 1988 and flood of 1993. The special mode of integration using a stretched-grid GCM and data assimilation system is developed that allows for imitating the nested-grid framework. The mode is useful for inter-comparison purposes and for underlining the differences between these two approaches. The 1988 and 1993 integrations are performed for the two month period starting from mid May. Regional resolutions used in most of the experiments is 60 km. The major goal and the result of the study is obtaining the efficient down-scaling over the area of interest. The monthly mean prognostic regional fields for the stretched-grid integrations are remarkably close to those of the verifying analyses. Simulated precipitation patterns are successfully verified against gauge precipitation observations. The impact of finer 40 km regional resolution is investigated for the 1993 integration and an example of recovering subregional precipitation is presented. The obtained results show that the global variable-resolution stretched-grid approach is a viable candidate for regional and subregional climate studies and applications.

Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho

2017-05-01

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.

Seasonal and interannual variability of climate and vegetation indices across the Amazon.

PubMed

Brando, Paulo M; Goetz, Scott J; Baccini, Alessandro; Nepstad, Daniel C; Beck, Pieter S A; Christman, Mary C

2010-08-17

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996-2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002-2005. Using improved enhanced vegetation index (EVI) measurements (2000-2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development.

The Challenge of Simulating the Regional Climate over Florida

NASA Astrophysics Data System (ADS)

Misra, V.; Mishra, A. K.

2015-12-01

In this study we show that the unique geography of the peninsular Florida with close proximity to strong mesoscale surface ocean currents among other factors warrants the use of relatively high resolution climate models to project Florida's hydroclimate. In the absence of such high resolution climate models we highlight the deficiencies of two relatively coarse spatial resolution CMIP5 models with respect to the warm western boundary current of the Gulf Stream. As a consequence it affects the coastal SST and the land-ocean contrast, affecting the rainy summer seasonal precipitation accumulation over peninsular Florida. We also show this through two sensitivity studies conducted with a regional coupled ocean atmosphere model with different bathymetries that dislocate and modulate the strength of the Gulf Stream that locally affects the SST in the two simulations. These studies show that a stronger and more easterly displaced Gulf Stream produces warmer coastal SST's along the Atlantic coast of Florida that enhances the precipitation over peninsular Florida relative to the other regional climate model simulation. However the regional model simulations indicate that variability of wet season rainfall variability in peninsular Florida becomes less dependent on the land-ocean contrast with a stronger Gulf Stream current.

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.

Readings from Visibility Meters: Do They Really Mean the Maximum Distance of Observing A Black Object?

NASA Astrophysics Data System (ADS)

Li, M.; Zhang, S.; Garcia-Menendez, F.; Monier, E.; Selin, N. E.

2016-12-01

Climate change, favoring more heat waves and episodes of stagnant air, may deteriorate air quality by increasing ozone and fine particulate matter (PM2.5) concentrations and high pollution episodes. This effect, termed as "climate penalty", has been quantified and explained by many earlier studies in the U.S. and Europe, but research efforts in Asian countries are limited. We evaluate the impact of climate change on air quality and human health in China and India using a modeling framework that links the Massachusetts Institute of Technology Integrated Global System Model to the Community Atmosphere Model (MIT IGSM-CAM). Future climate fields are projected under three climate scenarios including a no-policy reference scenario and two climate stabilization scenarios with 2100 total radiative forcing targets of 9.7, 4.5 and 3.7 W m-2, respectively. Each climate scenario is run for five representations of climate variability to account for the role of natural variability. Thirty-year chemical transport simulations are conducted in 1981-2010 and 2086-2115 under the three climate scenarios with fixed anthropogenic emissions at year 2000 levels. We find that 2000—2100 climate change under the no-policy reference scenario would increase ozone concentrations in eastern China and northern India by up to 5 ppb through enhancing biogenic emissions and ozone production efficiency. Ozone extreme episodes also become more frequent in these regions, while climate policies can offset most of the increase in ozone episodes. Climate change between 2000 and 2100 would slightly increase anthropogenic PM2.5 concentrations in northern China and Sichuan province, but significantly reduce anthropogenic PM2.5 concentrations in southern China and northern India, primarily due to different chemical responses of sulfate-nitrate-ammonium aerosols to climate change in these regions. Our study also suggests that the mitigation costs of climate policies can be partially offset by health benefits from reduced climate-induced air pollution in China.

Impacts Of Global/Regional Climate Changes On Environment And Health: Need For Integrated Research And Education Collaboration (Invited)

NASA Astrophysics Data System (ADS)

Tuluri, F.

2013-12-01

The realization of long term changes in climate in research community has to go beyond the comfort zone through climate literacy in academics. Higher education on climate change is the platform to bring together the otherwise disconnected factors such as effective discovery, decision making, innovation, interdisciplinary collaboration, Climate change is a complex process that may be due to natural internal processes within the climate system, or to variations in natural or anthropogenic (human-driven) external forcing. Global climate change indicates a change in either the mean state of the climate or in its variability, persisting for several decades or longer. This includes changes in average weather conditions on Earth, such as a change in average global temperature, as well as changes in how frequently regions experience heat waves, droughts, floods, storms, and other extreme weather. It is important to examine the effects of climate variations on human health and disorders in order to take preventive measures. Similarly, the influence of climate changes on animal management practices, pests and pest management systems, and high value crops such as citrus and vegetables is also equally important for investigation. New genetic agricultural varieties must be explored, and pilot studies should examine biotechnology transfer. Recent climate model improvements have resulted in an enhanced ability to simulate many aspects of climate variability and extremes. However, they are still characterized by systematic errors and limitations in accurately simulating more precisely regional climate conditions. The present situations warrant developing climate literacy on the synergistic impacts of environmental change, and improve development, testing and validation of integrated stress impacts through computer modeling. In the present study we present a detailed study of the current status on the impacts of global/regional climate changes on environment and health with a view to highlighting the need for integrated research and education collaboration at national and global level.

Regional Climate Simulation and Data Assimilation with Variable-Resolution GCMs

NASA Technical Reports Server (NTRS)

Fox-Rabinovitz, Michael S.

2002-01-01

Variable resolution GCMs using a global stretched grid (SG) with enhanced regional resolution over one or multiple areas of interest represents a viable new approach to regional climateklimate change and data assimilation studies and applications. The multiple areas of interest, at least one within each global quadrant, include the major global mountains and major global monsoonal circulations over North America, South America, India-China, and Australia. They also can include the polar domains, and the European and African regions. The SG-approach provides an efficient regional downscaling to mesoscales, and it is an ideal tool for representing consistent interactions of globaYlarge- and regionallmeso- scales while preserving the high quality of global circulation. Basically, the SG-GCM simulations are no different from those of the traditional uniform-grid GCM simulations besides using a variable-resolution grid. Several existing SG-GCMs developed by major centers and groups are briefly described. The major discussion is based on the GEOS (Goddard Earth Observing System) SG-GCM regional climate simulations.

Impacts of continental arcs on global carbon cycling and climate

NASA Astrophysics Data System (ADS)

Lee, C. T.; Jiang, H.; Carter, L.; Dasgupta, R.; Cao, W.; Lackey, J. S.; Lenardic, A.; Barnes, J.; McKenzie, R.

2017-12-01

On myr timescales, climatic variability is tied to variations in atmospheric CO2, which in turn is driven by geologic sources of CO2 and modulated by the efficiency of chemical weathering and carbonate precipitation (sinks). Long-term variability in CO2 has largely been attributed to changes in mid-ocean ridge inputs or the efficiency of global weathering. For example, the Cretaceous greenhouse is thought to be related to enhanced oceanic crust production, while the late Cenozoic icehouse is attributed to enhanced chemical weathering associated with the Himalayan orogeny. Here, we show that continental arcs may play a more important role in controlling climate, both in terms of sources and sinks. Continental arcs differ from island arcs and mid-ocean ridges in that the continental plate through which arc magmas pass may contain large amounts of sedimentary carbonate, accumulated over the history of the continent. Interaction of arc magmas with crustal carbonates via assimilation, reaction or heating can significantly add to the mantle-sourced CO2 flux. Detrital zircons and global mapping of basement rocks shows that the length of continental arcs in the Cretaceous was more than twice that in the mid-Cenozoic; maps also show many of these arcs intersected crustal carbonates. The increased length of continental arc magmatism coincided with increased oceanic spreading rates, placing convergent margins into compression, which favors continental arcs. Around 50 Ma, however, nearly all the continental arcs in Eurasia and North America terminated as India collided with Eurasia and the western Pacific rolled back, initiating the Marianas-Tonga-Kermadec intra-oceanic subduction complex and possibly leading to a decrease in global CO2 production. Meanwhile, extinct continental arcs continued to erode, resulting in regionally enhanced chemical weathering unsupported by magmatic fluxes of CO2. Continental arcs, during their magmatic lifetimes, are thus a source of CO2, driving greenhouse climates, but after they die magmatically, they remain geomorphically active and become a net CO2 sink, helping to drive climate towards cooler conditions. Tectonic oscillations that drive fluctuations in the activity of continental arcs thus may be responsible for greenhouse-icehouse oscillations in the Phanerozoic.

A Case Study in Caribbean Climate Change: Impacts on Crop Suitability and Small Farmer Vulnerability in St. Elizabeth, Jamaica

NASA Astrophysics Data System (ADS)

Curtis, W. R.; Gamble, D. W.; Popke, J.

2013-12-01

This paper examines some of the implications of climate change for farming in the Caribbean, through an analysis of future crop suitability and a case study of climate variability and agricultural practices in St. Elizabeth Parish, Jamaica. To assess potential changes in Caribbean agriculture, we present results from a water budget model based on a 100-year regional climate projection of temperature and precipitation for the circum-Caribbean basin. We find that future water deficits in the region are climate type-dependent. Savanna climates experience the largest annual changes, while semi-arid environments are greatly impacted in the spring. When the impacts of temperature and precipitation are considered separately, we find that predicted future warming, and the associated increase in evapotranspiration, has a slightly larger climatological effect on crop water need than predicted decreases in precipitation. To illustrate how a changing climate regime may impact agricultural practices, we present results from recent fieldwork in St. Elizabeth Parish, one of the main farming regions on the island of Jamaica. Drawing on data from farmer interviews and a recently-installed weather mesonet, we highlight the ways in which local microclimates influence farmer livelihood strategies and community-level vulnerability. Initial results suggest that farmers are experiencing greater climate variability, and that communities with Savanna and semi-arid type climates may be more susceptible to drought than communities in wetter, higher-elevation microclimates. These changes have enhanced the importance of irrigation technology and water management strategies for successful farming. In this context, we argue, large, well-capitalized farmers may be better able to manage the uncertainties associated with climate change, leading to an uneven landscape of vulnerability across the region.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Evaluation of Oceanic Surface Observation for Reproducing the Upper Ocean Structure in ECHAM5/MPI-OM

NASA Astrophysics Data System (ADS)

Luo, Hao; Zheng, Fei; Zhu, Jiang

2017-12-01

Better constraints of initial conditions from data assimilation are necessary for climate simulations and predictions, and they are particularly important for the ocean due to its long climate memory; as such, ocean data assimilation (ODA) is regarded as an effective tool for seasonal to decadal predictions. In this work, an ODA system is established for a coupled climate model (ECHAM5/MPI-OM), which can assimilate all available oceanic observations using an ensemble optimal interpolation approach. To validate and isolate the performance of different surface observations in reproducing air-sea climate variations in the model, a set of observing system simulation experiments (OSSEs) was performed over 150 model years. Generally, assimilating sea surface temperature, sea surface salinity, and sea surface height (SSH) can reasonably reproduce the climate variability and vertical structure of the upper ocean, and assimilating SSH achieves the best results compared to the true states. For the El Niño-Southern Oscillation (ENSO), assimilating different surface observations captures true aspects of ENSO well, but assimilating SSH can further enhance the accuracy of ENSO-related feedback processes in the coupled model, leading to a more reasonable ENSO evolution and air-sea interaction over the tropical Pacific. For ocean heat content, there are still limitations in reproducing the long time-scale variability in the North Atlantic, even if SSH has been taken into consideration. These results demonstrate the effectiveness of assimilating surface observations in capturing the interannual signal and, to some extent, the decadal signal but still highlight the necessity of assimilating profile data to reproduce specific decadal variability.

Global Crop Yields, Climatic Trends and Technology Enhancement

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Khanbilvardi, R.; Kogan, F.

2016-12-01

During the last decades the global agricultural production has soared up and technology enhancement is still making positive contribution to yield growth. However, continuing population, water crisis, deforestation and climate change threaten the global food security. Attempts to predict food availability in the future around the world can be partly understood from the impact of changes to date. A new multilevel model for yield prediction at the country scale using climate covariates and technology trend is presented in this paper. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling and/or clustering to automatically group and reduce estimation uncertainties. El Niño Southern Oscillation (ENSO), Palmer Drought Severity Index (PDSI), Geopotential height (GPH), historical CO2 level and time-trend as a relatively reliable approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2007. Results show that these indicators can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications.

Limited evidence for CO2 -related growth enhancement in northern Rocky Mountain lodgepole pine populations across climate gradients.

PubMed

Reed, Charlotte C; Ballantyne, Ashley P; Cooper, Leila Annie; Sala, Anna

2018-04-15

Forests sequester large amounts of carbon annually and are integral in buffering against effects of global change. Increasing atmospheric CO 2 may enhance photosynthesis and/or decrease stomatal conductance (g s ) thereby enhancing intrinsic water-use efficiency (iWUE), having potential indirect and direct benefits to tree growth. While increasing iWUE has been observed in most trees globally, enhanced growth is not ubiquitous, possibly due to concurrent climatic constraints on growth. To investigate our incomplete understanding of interactions between climate and CO 2 and their impacts on tree physiology and growth, we used an environmental gradient approach. We combined dendrochronology with carbon isotope analysis (δ 13 C) to assess the covariation of basal area increment (BAI) and iWUE over time in lodgepole pine. Trees were sampled at 18 sites spanning two climatically distinct elevation transects on the lee and windward sides of the Continental Divide, encompassing the majority of lodgepole pine's northern Rocky Mountain elevational range. We analyzed BAI and iWUE from 1950 to 2015, and explored correlations with monthly climate variables. As expected, iWUE increased at all sites. However, concurrent growth trends depended on site climatic water deficit (CWD). Significant growth increases occurred only at the driest sites, where increases in iWUE were strongest, while growth decreases were greatest at sites where CWD has been historically lowest. Late summer drought of the previous year negatively affected growth across sites. These results suggest that increasing iWUE, if strong enough, may indirectly benefit growth at drier sites by effectively extending the growing season via reductions in g s . Strong growth decreases at high elevation windward sites may reflect increasing water stress as a result of decreasing snowpack, which was not offset by greater iWUE. Our results imply that increasing iWUE driven by decreasing g s may benefit tree growth in limited scenarios, having implications for future carbon uptake potential of semiarid ecosystems. © 2018 John Wiley & Sons Ltd.

Winter climate limits subantarctic low forest growth and establishment.

PubMed

Harsch, Melanie A; McGlone, Matt S; Wilmshurst, Janet M

2014-01-01

Campbell Island, an isolated island 600 km south of New Zealand mainland (52 °S, 169 °E) is oceanic (Conrad Index of Continentality  =  -5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6 °C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally.

Winter Climate Limits Subantarctic Low Forest Growth and Establishment

PubMed Central

Harsch, Melanie A.; McGlone, Matt S.; Wilmshurst, Janet M.

2014-01-01

Campbell Island, an isolated island 600 km south of New Zealand mainland (52°S, 169°E) is oceanic (Conrad Index of Continentality  = −5) with small differences between mean summer and winter temperatures. Previous work established the unexpected result that a mean annual climate warming of c. 0.6°C since the 1940's has not led to upward movement of the forest limit. Here we explore the relative importance of summer and winter climatic conditions on growth and age-class structure of the treeline forming species, Dracophyllum longifolium and Dracophyllum scoparium over the second half of the 20th century. The relationship between climate and growth and establishment were evaluated using standard dendroecological methods and local climate data from a meteorological station on the island. Growth and establishment were correlated against climate variables and further evaluated within hierarchical regression models to take into account the effect of plot level variables. Winter climatic conditions exerted a greater effect on growth and establishment than summer climatic conditions. Establishment is maximized under warm (mean winter temperatures >7 °C), dry winters (total winter precipitation <400 mm). Growth, on the other hand, is adversely affected by wide winter temperature ranges and increased rainfall. The contrasting effect of winter warmth on growth and establishment suggests that winter temperature affects growth and establishment through differing mechanisms. We propose that milder winters enhance survival of seedlings and, therefore, recruitment, but increases metabolic stress on established plants, resulting in lower growth rates. Future winter warming may therefore have complex effects on plant growth and establishment globally. PMID:24691026

Impacts of Climate Change on Surface Ozone and Intercontinental Ozone Pollution: A Multi-Model Study

NASA Technical Reports Server (NTRS)

Doherty, R. M.; Wild, O.; Shindell, D. T.; Zeng, G.; MacKenzie, I. A.; Collins, W. J.; Fiore, A. M.; Stevenson, D. S.; Dentener, F. J.; Schultz, M. G.;

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Environmental drivers of mesozooplankton biomass variability in the North Pacific Subtropical Gyre

NASA Astrophysics Data System (ADS)

Valencia, Bellineth; Landry, Michael R.; Décima, Moira; Hannides, Cecelia C. S.

2016-12-01

The environmental drivers of zooplankton variability are poorly explored for the central subtropical Pacific, where a direct bottom-up food-web connection is suggested by increasing trends in primary production and mesozooplankton biomass at station ALOHA (A Long-term Oligotrophic Habitat Assessment) over the past 20 years (1994-2013). Here we use generalized additive models (GAMs) to investigate how these trends relate to the major modes of North Pacific climate variability. A GAM based on monthly mean data explains 43% of the temporal variability in mesozooplankton biomass with significant influences from primary productivity (PP), sea surface temperature (SST), North Pacific Gyre Oscillation (NPGO), and El Niño. This result mainly reflects the seasonal plankton cycle at station ALOHA, in which increasing light and SST lead to enhanced nitrogen fixation, productivity, and zooplankton biomass during summertime. Based on annual mean data, GAMs for two variables suggest that PP and 3-4 year lagged NPGO individually account for 40% of zooplankton variability. The full annual mean GAM explains 70% of variability of zooplankton biomass with significant influences from PP, 4 year lagged NPGO, and 4 year lagged Pacific Decadal Oscillation (PDO). The NPGO affects wind stress, sea surface height, and subtropical gyre circulation and has been linked to mideuphotic zone anomalies in salinity and PP at station ALOHA. Our study broadens the known impact of this climate mode on plankton dynamics in the North Pacific. While lagged transport effects are also evident for subtropical waters, our study highlights a strong coupling between zooplankton fluctuations and PP, which differs from the transport-dominated climate influences that have been found for North Pacific boundary currents.

Enhancement of phytoplankton chlorophyll by submesoscale frontal dynamics in the North Pacific Subtropical Gyre.

PubMed

Liu, Xiao; Levine, Naomi M

2016-02-28

Subtropical gyres contribute significantly to global ocean productivity. As the climate warms, the strength of these gyres as a biological carbon pump is predicted to diminish due to increased stratification and depleted surface nutrients. We present results suggesting that the impact of submesoscale physics on phytoplankton in the oligotrophic ocean is substantial and may either compensate or exacerbate future changes in carbon cycling. A new statistical tool was developed to quantify surface patchiness from sea surface temperatures. Chlorophyll concentrations in the North Pacific Subtropical Gyre were shown to be enhanced by submesoscale frontal dynamics with an average increase of 38% (maximum of 83%) during late winter. The magnitude of this enhancement is comparable to the observed decline in chlorophyll due to a warming of ~1.1°C. These results highlight the need for an improved understanding of fine-scale physical variability in order to predict the response of marine ecosystems to projected climate changes.

Enhancement of phytoplankton chlorophyll by submesoscale frontal dynamics in the North Pacific Subtropical Gyre

NASA Astrophysics Data System (ADS)

Liu, Xiao; Levine, Naomi M.

2016-02-01

Subtropical gyres contribute significantly to global ocean productivity. As the climate warms, the strength of these gyres as a biological carbon pump is predicted to diminish due to increased stratification and depleted surface nutrients. We present results suggesting that the impact of submesoscale physics on phytoplankton in the oligotrophic ocean is substantial and may either compensate or exacerbate future changes in carbon cycling. A new statistical tool was developed to quantify surface patchiness from sea surface temperatures. Chlorophyll concentrations in the North Pacific Subtropical Gyre were shown to be enhanced by submesoscale frontal dynamics with an average increase of 38% (maximum of 83%) during late winter. The magnitude of this enhancement is comparable to the observed decline in chlorophyll due to a warming of ~1.1°C. These results highlight the need for an improved understanding of fine-scale physical variability in order to predict the response of marine ecosystems to projected climate changes.

Impact of Climate Change on Siberian High and Wintertime Air Pollution in China in Past Two Decades

NASA Astrophysics Data System (ADS)

Zhao, Shuyu; Feng, Tian; Tie, Xuexi; Long, Xin; Li, Guohui; Cao, Junji; Zhou, Weijian; An, Zhisheng

2018-02-01

China has suffered severe air pollutions during wintertime as national industrialization and urbanization have been increasingly developed in the past decades. Recent studies suggest that climate change has important impacts on extreme haze events in northern China. This study uses reanalysis datasets to analyze the trend and variability of Siberian High (SiH) intensity, and its relationship with the Arctic temperature and sea ice cover (SIC) in past two decades. The results show that Arctic is warming accompanied by a rapid decline of SIC, while Eurasia is cooling and SiH intensity is gradually enhancing. The statistics illustrates that the SiH has a significantly positive correlation to the temperature (R = 0.70), and a significant anticorrelation to the SIC (R = -0.69), and this is because the warming Arctic and the reducing SIC enhanced the SiH. The enhanced SiH leads to strengthened northerly winds in the North China Plain (NCP). The WRF-Chem model calculation reveals the strengthened northerly winds during the stronger SiH period in January 2016 produce a significant decrease in PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) concentrations by 100-200 µg m-3 than that during the weaker one in January 2013. A sensitivity calculation figures out the reduction of PM2.5 concentrations due to a decrease of 50% in emissions is comparable to changes from the weak SiH condition to the strong SiH condition, suggesting that extreme climate variability in the past few years could have an equivalent impact as a consequence of a large emission reduction on wintertime air pollution in the NCP.

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.

Climate-agriculture interactions and needs for policy making

NASA Astrophysics Data System (ADS)

Phillips, J. G.

2010-12-01

Research exploring climate change interactions with agriculture has evolved from simplistic “delta T” simulation experiments with crop models to work highlighting the importance of climate variability and extreme events, which characterized the negative impacts possible if no adaptation occurred. There soon followed consideration of socioeconomic factors allowing for adaptive strategies that are likely to mitigate the worst case outcomes originally projected. At the same time, improved understanding of biophysical feedbacks has led to a greater recognition of the role that agriculture plays in modifying climate, with a great deal of attention recently paid to strategies to enhance carbon sequestration in agricultural systems. Advances in models of biogeochemical cycling applied to agronomic systems have allowed for new insights into greenhouse gas emissions and sinks associated with current, conventional farming systems. Yet this work is still relatively simplistic in that it seldom addresses interactions between climate dynamics, adoption of mitigation strategies, and feedbacks to the climate system and the surrounding environment. In order for agricultural policy to be developed that provides incentives for appropriate adaptation and mitigation strategies over the next 50 years, a systems approach needs to be utilized that addresses feedbacks and interactions at field, farm and regional scales in a broader environmental context. Interactions between carbon and climate constraints on the one hand, and environmental impacts related to water, nutrient runoff, and pest control all imply a transformation of farming practices that is as of yet not well defined. Little attention has been paid to studying the implications of “alternative” farming strategies such as organic systems, intensive rotational grazing of livestock, or increases in the perennial component of farmscapes, all of which may be necessary responses to energy and other environmental constraints over the coming century, interacting with a changing climate. Examples of interactions that need further exploration include the degree to which increases in soil organic matter to enhance carbon sequestration will improve system resilience and help mitigate the effects of an increase in climate variability, and how we can optimize the role of below-ground microbial communities in methane and nitrous-oxide emissions and sinks as well as in nutrient cycling and plant-water relations. These and other key areas where agroecosystem research is needed to advance policy will be discussed.

Comparative analyses of hydrological responses of two adjacent watersheds to climate variability and change using the SWAT model

USGS Publications Warehouse

Lee, Sangchul; Yeo, In-Young; Sadeghi, Ali M.; McCarty, Gregory W.; Hively, Wells; Lang, Megan W.; Sharifi, Amir

2018-01-01

Water quality problems in the Chesapeake Bay Watershed (CBW) are expected to be exacerbated by climate variability and change. However, climate impacts on agricultural lands and resultant nutrient loads into surface water resources are largely unknown. This study evaluated the impacts of climate variability and change on two adjacent watersheds in the Coastal Plain of the CBW, using the Soil and Water Assessment Tool (SWAT) model. We prepared six climate sensitivity scenarios to assess the individual impacts of variations in CO2concentration (590 and 850 ppm), precipitation increase (11 and 21 %), and temperature increase (2.9 and 5.0 °C), based on regional general circulation model (GCM) projections. Further, we considered the ensemble of five GCM projections (2085–2098) under the Representative Concentration Pathway (RCP) 8.5 scenario to evaluate simultaneous changes in CO2, precipitation, and temperature. Using SWAT model simulations from 2001 to 2014 as a baseline scenario, predicted hydrologic outputs (water and nitrate budgets) and crop growth were analyzed. Compared to the baseline scenario, a precipitation increase of 21 % and elevated CO2 concentration of 850 ppm significantly increased streamflow and nitrate loads by 50 and 52 %, respectively, while a temperature increase of 5.0 °C reduced streamflow and nitrate loads by 12 and 13 %, respectively. Crop biomass increased with elevated CO2 concentrations due to enhanced radiation- and water-use efficiency, while it decreased with precipitation and temperature increases. Over the GCM ensemble mean, annual streamflow and nitrate loads showed an increase of  ∼  70 % relative to the baseline scenario, due to elevated CO2 concentrations and precipitation increase. Different hydrological responses to climate change were observed from the two watersheds, due to contrasting land use and soil characteristics. The watershed with a larger percent of croplands demonstrated a greater increased rate of 5.2 kg N ha−1 in nitrate yield relative to the watershed with a lower percent of croplands as a result of increased export of nitrate derived from fertilizer. The watershed dominated by poorly drained soils showed increased nitrate removal due do enhanced denitrification compared to the watershed dominated by well-drained soils. Our findings suggest that increased implementation of conservation practices would be necessary for this region to mitigate increased nitrate loads associated with predicted changes in future climate.

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

PubMed

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

2014-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

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

Palaeoclimatic insights into future climate challenges.

PubMed

Alley, Richard B

2003-09-15

Palaeoclimatic data document a sensitive climate system subject to large and perhaps difficult-to-predict abrupt changes. These data suggest that neither the sensitivity nor the variability of the climate are fully captured in some climate-change projections, such as the Intergovernmental Panel on Climate Change (IPCC) Summary for Policymakers. Because larger, faster and less-expected climate changes can cause more problems for economies and ecosystems, the palaeoclimatic data suggest the hypothesis that the future may be more challenging than anticipated in ongoing policy making. Large changes have occurred repeatedly with little net forcing. Increasing carbon dioxide concentration appears to have globalized deglacial warming, with climate sensitivity near the upper end of values from general circulation models (GCMs) used to project human-enhanced greenhouse warming; data from the warm Cretaceous period suggest a similarly high climate sensitivity to CO(2). Abrupt climate changes of the most recent glacial-interglacial cycle occurred during warm as well as cold times, linked especially to changing North Atlantic freshwater fluxes. GCMs typically project greenhouse-gas-induced North Atlantic freshening and circulation changes with notable but not extreme consequences; however, such models often underestimate the magnitude, speed or extent of past changes. Targeted research to assess model uncertainties would help to test these hypotheses.

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...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer L.; Collins, Katherine M.; Tucker, Compton J.; Pak, Edwin W.; Britch, Seth C.; Eastman, James Ronald; Pinzon, Jorge E.; Russell, Kevin L.

2011-01-01

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Extremes in rainfall (drought and flood) during the period 2004 - 2009 have privileged different disease vectors. Chikungunya outbreaks occurred during the severe drought from late 2004 to 2006 over coastal East Africa and the western Indian Ocean islands and in the later years India and Southeast Asia. The chikungunya pandemic was caused by a Central/East African genotype that appears to have been precipitated and then enhanced by global-scale and regional climate conditions in these regions. Outbreaks of Rift Valley fever occurred following excessive rainfall period from late 2006 to late 2007 in East Africa and Sudan, and then in 2008 - 2009 in Southern Africa. The shift in the outbreak patterns of Rift Valley fever from East Africa to Southern Africa followed a transition of the El Nino/Southern Oscillation (ENSO) phenomena from the warm El Nino phase (2006-2007) to the cold La Nina phase (2007-2009) and associated patterns of variability in the greater Indian Ocean basin that result in the displacement of the centres of above normal rainfall from Eastern to Southern Africa. Understanding the background patterns of climate variability both at global and regional scale and their impacts on ecological drivers of vector borne-diseases is critical in long-range planning of appropriate response and mitigation measures.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed

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

2015-12-04

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

Reconstructing Hydrologic Variability in Southwestern North America Using Speleothem Proxies and Precipitation Isotopes from California

NASA Astrophysics Data System (ADS)

McCabe-Glynn, Staryl

Precipitation in southwestern North America has exhibited significant natural variability over the past few thousand years. This variability has been attributed to sea surface temperature regimes in the Pacific and Atlantic oceans, and to the attendant shifts in atmospheric circulation patterns. In particular, decadal variability in the North Pacific has influenced precipitation in this region during the twentieth century, but links to earlier droughts and pluvials are unclear. Here I assess these links using delta18 O measurements from a speleothem from southern California that spans AD 854-- 2007. I show that variations in the oxygen isotopes of the speleothem correlate to sea surface temperatures in the Kuroshio Extension region of the North Pacific, which affect the atmospheric trajectory and isotopic composition of moisture reaching the study site. Interpreting our speleothem data as a record of sea surface temperatures in the Kuroshio Extension, I find a strong 22-year periodicity, suggesting a persistent solar influence on North Pacific decadal variability. A comparison with tree-ring records of precipitation during the past millennium shows that some droughts occurred during periods of warmth in the Kuroshio Extension, similar to the instrumental record. However, other droughts did not and instead were likely influenced by other factors. The carbon isotope record indicates drier conditions are associated with higher delta13C values and may be a suitable proxy for reconstructing past drought variability. More research is needed to determine the controls on trace element concentrations. Finally, I find a significant increase in sea surface temperature variability over the past 150 years, which may reflect an influence of greenhouse gas concentrations on variability in the North Pacific. While drought is a common feature of climate in this region, most climate models also project extreme precipitation events to increase in frequency and severity because the climate changes largely due to increased water vapor content in a warmer atmosphere. I also utilize precipitation data and isotopic analysis from precipitation samples collected weekly from near the cave site at Giant Forest, Sequoia National Park, California, from 2001 to 2011, to analyze climate mode patterns during extreme precipitation events and to construct an isotopic data base of precipitation samples. Composite maps indicate extreme precipitation weeks consist of a weaker Aleutian Low, coupled with a deep low pressure cell located northwest of California and enhanced subtropical moisture. I find extreme precipitation weeks occur more often during the La Nina phase and less during the positive Eastern Pacific (EP) phase or during the Central Pacific (CP) neutral phase at our site. Analyses of climate mode patterns and precipitation amounts indicate that when the negative Arctic Oscillation (AO), negative and neutral Pacific North American pattern (PNA), and positive Southern Oscillation Index (SOI) (La Nina) are in sync, the maximum amount of precipitation anomalies are distributed along the Western US. Additionally, the central or eastern Pacific location of El Nino Southern Oscillation sea surface temperature anomalies can further enhance predictive capabilities of the landfall location of extreme precipitation.

Interaction between climate, volcanism, and isostatic rebound in Southeast Alaska during the last deglaciation

USGS Publications Warehouse

Praetorius, Summer; Mix, Alan; Jensen, Britta; Froese, Duane; Milne, Glenn A.; Wolhowe, Matthew; Addison, Jason A.; Prahl, Fred

2016-01-01

Observations of enhanced volcanic frequency during the last deglaciation have led to the hypothesis that ice unloading in glaciated volcanic terrains can promote volcanism through decompression melting in the shallow mantle or a reduction in crustal magma storage time. However, a direct link between regional climate change, isostatic adjustment, and the initiation of volcanism remains to be demonstrated due to the difficulty of obtaining high-resolution well-dated records that capture short-term climate and volcanic variability traced to a particular source region. Here we present an exceptionally resolved record of 19 tephra layers paired with foraminiferal oxygen isotopes and alkenone paleotemperatures from marine sediment cores along the Southeast Alaska margin spanning the last deglacial transition. Major element compositions of the tephras indicate a predominant source from the nearby Mt. Edgecumbe Volcanic Field (MEVF). We constrain the timing of this regional eruptive sequence to 14.6–13.1 ka. The sudden increase in volcanic activity from the MEVF coincides with the onset of Bølling–Allerød interstadial warmth, the disappearance of ice-rafted detritus, and rapid vertical land motion associated with modeled regional isostatic rebound in response to glacier retreat. These data support the hypothesis that regional deglaciation can rapidly trigger volcanic activity. Rapid sea surface temperature fluctuations and an increase in local salinity (i.e., δ18Osw) variability are associated with the interval of intense volcanic activity, consistent with a two-way interaction between climate and volcanism in which rapid volcanic response to ice unloading may in turn enhance short-term melting of the glaciers, plausibly via albedo effects on glacier ablation zones.

Solar Radiation and Climate Experiment (SORCE) Satellite

NASA Technical Reports Server (NTRS)

2003-01-01

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

Perceptions of motivational climate and teachers' strategies to sustain discipline as predictors of intrinsic motivation in physical education.

PubMed

Gutiérrez, Melchor; Ruiz, Luis-Miguel; López, Esther

2010-11-01

This study examined the relationship among pupils' perceptions of the motivational climate, pupils' perceptions of teachers' strategies to maintain discipline and pupils' intrinsic motivation in physical education. A sample of 2189 Spanish adolescents, ages 13 to 17 years, completed Spanish versions of the EPCM, SSDS, and IMI. Confirmatory factor analyses were carried out to confirm the factorial validity of the scales. Then, the relationship among the variables was explored through Structural Equation Modelling. The most important predictors of pupils' intrinsic motivation were the perceived mastery climate, and perceived teachers' emphasis on intrinsic reasons to maintain discipline. Perceived performance climate and perceived teachers' strategies to maintain discipline based on introjected reasons and indifference, predicted pupils' tension-pressure. Results are discussed in the context of theoretical propositions of self-determination theory and practical issues of enhancing adolescents' motivation in physical education.

Growing Land-Sea Temperature Contrast and the Intensification of Arctic Cyclones

NASA Astrophysics Data System (ADS)

Day, Jonathan J.; Hodges, Kevin I.

2018-04-01

Cyclones play an important role in the coupled dynamics of the Arctic climate system on a range of time scales. Modeling studies suggest that storminess will increase in Arctic summer due to enhanced land-sea thermal contrast along the Arctic coastline, in a region known as the Arctic Frontal Zone (AFZ). However, the climate models used in these studies are poor at reproducing the present-day Arctic summer cyclone climatology and so their projections of Arctic cyclones and related quantities, such as sea ice, may not be reliable. In this study we perform composite analysis of Arctic cyclone statistics using AFZ variability as an analog for climate change. High AFZ years are characterized both by increased cyclone frequency and dynamical intensity, compared to low years. Importantly, the size of the response in this analog suggests that General Circulation Models may underestimate the response of Arctic cyclones to climate change, given a similar change in baroclinicity.

Recent Climate and Ice-Sheet Changes in West Antarctica Compared with the Past 2,000 Years

NASA Technical Reports Server (NTRS)

Steig, Eric J.; Ding, Qinghua; White, James W.; Kuttel, Marcel; Rupper, Summer B.; Neumann, Thomas Allen; Neff, Peter D.; Gallant, Ailie J. E.; Mayewski, Paul A.; Taylor, Kendrick C.;

A reference time scale for Site U1385 (Shackleton Site) on the SW Iberian Margin

NASA Astrophysics Data System (ADS)

Hodell, D.; Lourens, L.; Crowhurst, S.; Konijnendijk, T.; Tjallingii, R.; Jiménez-Espejo, F.; Skinner, L.; Tzedakis, P. C.; Abrantes, Fatima; Acton, Gary D.; Alvarez Zarikian, Carlos A.; Bahr, André; Balestra, Barbara; Barranco, Estefanìa Llave; Carrara, Gabriela; Ducassou, Emmanuelle; Flood, Roger D.; Flores, José-Abel; Furota, Satoshi; Grimalt, Joan; Grunert, Patrick; Hernández-Molina, Javier; Kim, Jin Kyoung; Krissek, Lawrence A.; Kuroda, Junichiro; Li, Baohua; Lofi, Johanna; Margari, Vasiliki; Martrat, Belen; Miller, Madeline D.; Nanayama, Futoshi; Nishida, Naohisa; Richter, Carl; Rodrigues, Teresa; Rodríguez-Tovar, Francisco J.; Roque, Ana Cristina Freixo; Sanchez Goñi, Maria F.; Sierro Sánchez, Francisco J.; Singh, Arun D.; Sloss, Craig R.; Stow, Dorrik A. V.; Takashimizu, Yasuhiro; Tzanova, Alexandrina; Voelker, Antje; Xuan, Chuang; Williams, Trevor

2015-10-01

We produced a composite depth scale and chronology for Site U1385 on the SW Iberian Margin. Using log(Ca/Ti) measured by core scanning XRF at 1-cm resolution in all holes, a composite section was constructed to 166.5 meter composite depth (mcd) that corrects for stretching and squeezing in each core. Oxygen isotopes of benthic foraminifera were correlated to a stacked δ18O reference signal (LR04) to produce an oxygen isotope stratigraphy and age model. Variations in sediment color contain very strong precession signals at Site U1385, and the amplitude modulation of these cycles provides a powerful tool for developing an orbitally-tuned age model. We tuned the U1385 record by correlating peaks in L* to the local summer insolation maxima at 37°N. The benthic δ18O record of Site U1385, when placed on the tuned age model, generally agrees with other time scales within their respective chronologic uncertainties. The age model is transferred to down-core data to produce a continuous time series of log(Ca/Ti) that reflect relative changes of biogenic carbonate and detrital sediment. Biogenic carbonate increases during interglacial and interstadial climate states and decreases during glacial and stadial periods. Much of the variance in the log(Ca/Ti) is explained by a linear combination of orbital frequencies (precession, tilt and eccentricity), whereas the residual signal reflects suborbital climate variability. The strong correlation between suborbital log(Ca/Ti) variability and Greenland temperature over the last glacial cycle at Site U1385 suggests that this signal can be used as a proxy for millennial-scale climate variability over the past 1.5 Ma. Millennial climate variability, as expressed by log(Ca/Ti) at Site U1385, was a persistent feature of glacial climates over the past 1.5 Ma, including glacial periods of the early Pleistocene ('41-kyr world') when boundary conditions differed significantly from those of the late Pleistocene ('100-kyr world'). Suborbital variability was suppressed during interglacial stages and enhanced during glacial periods, especially when benthic δ18O surpassed 3.3-3.5‰. Each glacial inception was marked by appearance of strong millennial variability and each deglaciation was preceded by a terminal stadial event. Suborbital variability may be a symptomatic feature of glacial climate or, alternatively, may play a more active role in the inception and/or termination of glacial cycles.

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.

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

PubMed Central

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Modelling spatial and temporal variability of hydrologic impacts under climate changes over the Nenjiang River Basin, China

NASA Astrophysics Data System (ADS)

Chen, Hao; Zhang, Wanchang

2017-10-01

The Variable Infiltration Capacity (VIC) hydrologic model was adopted for investigating spatial and temporal variability of hydrologic impacts of climate change over the Nenjiang River Basin (NRB) based on a set of gridded forcing dataset at 1/12th degree resolution from 1970 to 2013. Basin-scale changes in the input forcing data and the simulated hydrological variables of the NRB, as well as station-scale changes in discharges for three major hydrometric stations were examined, which suggested that the model was performed fairly satisfactory in reproducing the observed discharges, meanwhile, the snow cover and evapotranspiration in temporal and spatial patterns were simulated reasonably corresponded to the remotely sensed ones. Wetland maps produced by multi-sources satellite images covering the entire basin between 1978 and 2008 were also utilized for investigating the responses and feedbacks of hydrological regimes on wetland dynamics. Results revealed that significant decreasing trends appeared in annual, spring and autumn streamflow demonstrated strong affection of precipitation and temperature changes over the study watershed, and the effects of climate change on the runoff reduction varied in the sub-basin area over different time scales. The proportion of evapotranspiration to precipitation characterized several severe fluctuations in droughts and floods took place in the region, which implied the enhanced sensitiveness and vulnerability of hydrologic regimes to changing environment of the region. Furthermore, it was found that the different types of wetlands undergone quite unique variation features with the varied hydro-meteorological conditions over the region, such as precipitation, evapotranspiration and soil moisture. This study provided effective scientific basis for water resource managers to develop effective eco-environment management plans and strategies that address the consequences of climate changes.

Efficacy of Radiative Transfer Model Across Space, Time and Hydro-climates

NASA Astrophysics Data System (ADS)

Mohanty, B.; Neelam, M.

2017-12-01

The efficiency of radiative transfer model for better soil moisture retrievals is not yet clearly understood over natural systems with great variability and heterogeneity with respect to soil, land cover, topography, precipitation etc. However, this knowledge is important to direct and strategize future research direction and field campaigns. In this work, we present global sensitivity analysis (GSA) technique to study the influence of heterogeneity and uncertainties on radiative transfer model (RTM) and to quantify climate-soil-vegetation interactions. A framework is proposed to understand soil moisture mechanisms underlying these interactions, and influence of these interactions on soil moisture retrieval accuracy. Soil moisture dynamics is observed to play a key role in variability of these interactions, i.e., it enhances both mean and variance of soil-vegetation coupling. The analysis is conducted for different support scales (Point Scale, 800 m, 1.6 km, 3.2 km, 6.4 km, 12.8 km, and 36 km), seasonality (time), hydro-climates, aggregation (scaling) methods and across Level I and Level II ecoregions of contiguous USA (CONUS). For undisturbed natural environments such as SGP'97 (Oklahoma, USA) and SMEX04 (Arizona, USA), the sensitivity of TB to land surface variables remain nearly uniform and are not influenced by extent, support scales or averaging method. On the contrary, for anthropogenically-manipulated environments such as SMEX02 (Iowa, USA) and SMAPVEX12 (Winnipeg, Canada), the sensitivity to variables are highly influenced by the distribution of land surface heterogeneity and upscaling methods. The climate-soil-vegetation interactions analyzed across all ecoregions are presented through a probability distribution function (PDF). The intensity of these interactions are categorized accordingly to yield "hotspots", where the RTM model fails to retrieve soil moisture. A ecoregion specific scaling function is proposed for these hotspots to rectify RTM for retrieving soil moisture.

Crop diversification and livelihoods of smallholder farmers in Zimbabwe: adaptive management for environmental change.

PubMed

Makate, Clifton; Wang, Rongchang; Makate, Marshall; Mango, Nelson

2016-01-01

This paper demonstrates how crop diversification impacts on two outcomes of climate smart agriculture; increased productivity (legume and cereal crop productivity) and enhanced resilience (household income, food security, and nutrition) in rural Zimbabwe. Using data from over 500 smallholder farmers, we jointly estimate crop diversification and each of the outcome variables within a conditional (recursive) mixed process framework that corrects for selectivity bias arising due to the voluntary nature of crop diversification. We find that crop diversification depends on the land size, farming experience, asset wealth, location, access to agricultural extension services, information on output prices, low transportation costs and general information access. Our results also indicate that an increase in the rate of adoption improves crop productivity, income, food security and nutrition at household level. Overall, our results are indicative of the importance of crop diversification as a viable climate smart agriculture practice that significantly enhances crop productivity and consequently resilience in rural smallholder farming systems. We, therefore, recommend wider adoption of diversified cropping systems notably those currently less diversified for greater adaptation to the ever-changing climate.

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

Seasonal and interannual variability of climate and vegetation indices across the Amazon

PubMed Central

Brando, Paulo M.; Goetz, Scott J.; Baccini, Alessandro; Nepstad, Daniel C.; Beck, Pieter S. A.; Christman, Mary C.

2010-01-01

Drought exerts a strong influence on tropical forest metabolism, carbon stocks, and ultimately the flux of carbon to the atmosphere. Satellite-based studies have suggested that Amazon forests green up during droughts because of increased sunlight, whereas field studies have reported increased tree mortality during severe droughts. In an effort to reconcile these apparently conflicting findings, we conducted an analysis of climate data, field measurements, and improved satellite-based measures of forest photosynthetic activity. Wet-season precipitation and plant-available water (PAW) decreased over the Amazon Basin from 1996−2005, and photosynthetically active radiation (PAR) and air dryness (expressed as vapor pressure deficit, VPD) increased from 2002–2005. Using improved enhanced vegetation index (EVI) measurements (2000–2008), we show that gross primary productivity (expressed as EVI) declined with VPD and PAW in regions of sparse canopy cover across a wide range of environments for each year of the study. In densely forested areas, no climatic variable adequately explained the Basin-wide interannual variability of EVI. Based on a site-specific study, we show that monthly EVI was relatively insensitive to leaf area index (LAI) but correlated positively with leaf flushing and PAR measured in the field. These findings suggest that production of new leaves, even when unaccompanied by associated changes in LAI, could play an important role in Basin-wide interannual EVI variability. Because EVI variability was greatest in regions of lower PAW, we hypothesize that drought could increase EVI by synchronizing leaf flushing via its effects on leaf bud development. PMID:20679201

Decadal-timescale changes of the Atlantic overturning circulation and climate in a coupled climate model with a hybrid-coordinate ocean component

NASA Astrophysics Data System (ADS)

Persechino, A.; Marsh, R.; Sinha, B.; Megann, A. P.; Blaker, A. T.; New, A. L.

2012-08-01

A wide range of statistical tools is used to investigate the decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) and associated key variables in a climate model (CHIME, Coupled Hadley-Isopycnic Model Experiment), which features a novel ocean component. CHIME is as similar as possible to the 3rd Hadley Centre Coupled Model (HadCM3) with the important exception that its ocean component is based on a hybrid vertical coordinate. Power spectral analysis reveals enhanced AMOC variability for periods in the range 15-30 years. Strong AMOC conditions are associated with: (1) a Sea Surface Temperature (SST) anomaly pattern reminiscent of the Atlantic Multi-decadal Oscillation (AMO) response, but associated with variations in a northern tropical-subtropical gradient; (2) a Surface Air Temperature anomaly pattern closely linked to SST; (3) a positive North Atlantic Oscillation (NAO)-like pattern; (4) a northward shift of the Intertropical Convergence Zone. The primary mode of AMOC variability is associated with decadal changes in the Labrador Sea and the Greenland Iceland Norwegian (GIN) Seas, in both cases linked to the tropical activity about 15 years earlier. These decadal changes are controlled by the low-frequency NAO that may be associated with a rapid atmospheric teleconnection from the tropics to the extratropics. Poleward advection of salinity anomalies in the mixed layer also leads to AMOC changes that are linked to processes in the Labrador Sea. A secondary mode of AMOC variability is associated with interannual changes in the Labrador and GIN Seas, through the impact of the NAO on local surface density.

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

USGS Publications Warehouse

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

2013-01-01

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

Enhanced groundwater recharge rates and altered recharge sensitivity to climate variability through subsurface heterogeneity

PubMed Central

Hartmann, Andreas; Gleeson, Tom; Wagener, Thorsten

2017-01-01

Our environment is heterogeneous. In hydrological sciences, the heterogeneity of subsurface properties, such as hydraulic conductivities or porosities, exerts an important control on water balance. This notably includes groundwater recharge, which is an important variable for efficient and sustainable groundwater resources management. Current large-scale hydrological models do not adequately consider this subsurface heterogeneity. Here we show that regions with strong subsurface heterogeneity have enhanced present and future recharge rates due to a different sensitivity of recharge to climate variability compared with regions with homogeneous subsurface properties. Our study domain comprises the carbonate rock regions of Europe, Northern Africa, and the Middle East, which cover ∼25% of the total land area. We compare the simulations of two large-scale hydrological models, one of them accounting for subsurface heterogeneity. Carbonate rock regions strongly exhibit “karstification,” which is known to produce particularly strong subsurface heterogeneity. Aquifers from these regions contribute up to half of the drinking water supply for some European countries. Our results suggest that water management for these regions cannot rely on most of the presently available projections of groundwater recharge because spatially variable storages and spatial concentration of recharge result in actual recharge rates that are up to four times larger for present conditions and changes up to five times larger for potential future conditions than previously estimated. These differences in recharge rates for strongly heterogeneous regions suggest a need for groundwater management strategies that are adapted to the fast transit of water from the surface to the aquifers. PMID:28242703

Enhanced Groundwater Recharge Rates and Altered Recharge Sensitivity to Climate Variability Through Subsurface Heterogeneity

NASA Technical Reports Server (NTRS)

Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten

2017-01-01

Our environment is heterogeneous. In hydrological sciences, the heterogeneity of subsurface properties, such as hydraulic conductivities or porosities, exerts an important control on water balance. This notably includes groundwater recharge, which is an important variable for efficient and sustainable groundwater resources management. Current large-scale hydrological models do not adequately consider this subsurface heterogeneity. Here we show that regions with strong subsurface heterogeneity have enhanced present and future recharge rates due to a different sensitivity of recharge to climate variability compared with regions with homogeneous subsurface properties. Our study domain comprises the carbonate rock regions of Europe, Northern Africa, and the Middle East, which cover 25 of the total land area. We compare the simulations of two large-scale hydrological models, one of them accounting for subsurface heterogeneity. Carbonate rock regions strongly exhibit karstification, which is known to produce particularly strong subsurface heterogeneity. Aquifers from these regions contribute up to half of the drinking water supply for some European countries. Our results suggest that water management for these regions cannot rely on most of the presently available projections of groundwater recharge because spatially variable storages and spatial concentration of recharge result in actual recharge rates that are up to four times larger for present conditions and changes up to five times larger for potential future conditions than previously estimated. These differences in recharge rates for strongly heterogeneous regions suggest a need for groundwater management strategies that are adapted to the fast transit of water from the surface to the aquifers.

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

Perception, experience, and indigenous knowledge of climate change and variability: the case of Accra, a sub-Saharan African city

USGS Publications Warehouse

Codjoe, Samuel N.A.; Owusu, George; Burkett, Virginia

2014-01-01

Several recent international assessments have concluded that climate change has the potential to reverse the modest economic gains achieved in many developing countries over the past decade. The phenomenon of climate change threatens to worsen poverty or burden populations with additional hardships, especially in poor societies with weak infrastructure and economic well-being. The importance of the perceptions, experiences, and knowledge of indigenous peoples has gained prominence in discussions of climate change and adaptation in developing countries and among international development organizations. Efforts to evaluate the role of indigenous knowledge in adaptation planning, however, have largely focused on rural people and their agricultural livelihoods. This paper presents the results of a study that examines perceptions, experiences, and indigenous knowledge relating to climate change and variability in three communities of metropolitan Accra, which is the capital of Ghana. The study design is based on a three-part conceptual framework and interview process involving risk mapping, mental models, and individual stressor cognition. Most of the residents interviewed in the three communities of urban Accra attributed climate change to the combination of deforestation and the burning of firewood and rubbish. None of the residents associated climate change with fossil fuel emissions from developed countries. Numerous potential adaptation strategies were suggested by the residents, many of which have been used effectively during past drought and flood events. Results suggest that ethnic residential clustering as well as strong community bonds in metropolitan Accra have allowed various groups and long-settled communities to engage in the sharing and transmission of knowledge of weather patterns and trends. Understanding and building upon indigenous knowledge may enhance the design, acceptance, and implementation of climate change adaptation strategies in Accra and urban regions of other developing nations.

Role of the Indonesian Throughflow in controlling regional mean climate and rainfall variability

NASA Astrophysics Data System (ADS)

England, Matthew H.; Santoso, Agus; Phipps, Steven; Ummenhofer, Caroline

2017-04-01

The role of the Indonesian Throughflow (ITF) in controlling regional mean climate and rainfall is examined using a coupled ocean-atmosphere general circulation model. Experiments employing both a closed and open ITF are equilibrated to steady state and then 200 years of natural climatic variability is assessed within each model run, with a particular focus on the Indian Ocean region. Opening of the ITF results in a mean Pacific-to-Indian throughflow of 21 Sv (1 Sv = 106 m3 sec-1), which advects warm west Pacific waters into the east Indian Ocean. This warm signature is propagated westward by the mean ocean flow, however it never reaches the west Indian Ocean, as an ocean-atmosphere feedback in the tropics generates a weakened trade wind field that is reminiscent of the negative phase of the Indian Ocean Dipole (IOD). This is in marked contrast to the Indian Ocean response to an open ITF when examined in ocean-only model experiments; which sees a strengthening of both the Indian Ocean South Equatorial Current and the Agulhas Current. The coupled feedback in contrast leads to cooler conditions over the west Indian Ocean, and an anomalous zonal atmospheric pressure gradient that enhances the advection of warm moist air toward south Asia and Australia. This leaves the African continent significantly drier, and much of Australia and southern Asia significantly wetter, in response to the opening of the ITF. Given the substantial interannual variability that the ITF exhibits in the present-day climate system, and the restriction of the ITF gateway in past climate eras, this could have important implications for understanding past and present regional rainfall patterns around the Indian Ocean and over neighbouring land-masses.

Understanding the Influence of Climate Forecasts on Farmer Decisions as Planned Behavior

NASA Astrophysics Data System (ADS)

Artikov, Ikrom; Hoffman, Stacey J.; Lynne, Gary D.; Pytlik Zillig, Lisa M.; Hu, Qi; Tomkins, Alan J.; Hubbard, Kenneth G.; Hayes, Michael J.; Waltman, William

2006-09-01

Results of a set of four regression models applied to recent survey data of farmers in eastern Nebraska suggest the causes that drive farmer intentions of using weather and climate information and forecasts in farming decisions. The model results quantify the relative importance of attitude, social norm, perceived behavioral control, and financial capability in explaining the influence of climate-conditions information and short-term and long-term forecasts on agronomic, crop insurance, and crop marketing decisions. Attitude, serving as a proxy for the utility gained from the use of such information, had the most profound positive influence on the outcome of all the decisions, followed by norms. The norms in the community, as a proxy for the utility gained from allowing oneself to be influenced by others, played a larger role in agronomic decisions than in insurance or marketing decisions. In addition, the interaction of controllability (accuracy, availability, reliability, timeliness of weather and climate information), self-efficacy (farmer ability and understanding), and general preference for control was shown to be a substantive cause. Yet control variables also have an economic side: The farm-sales variable as a measure of financial ability and motivation intensified and clarified the role of control while also enhancing the statistical robustness of the attitude and norms variables in better clarifying how they drive the influence. Overall, the integrated model of planned behavior from social psychology and derived demand from economics, that is, the “planned demand model,” is more powerful than models based on either of these approaches alone. Taken together, these results suggest that the “human dimension” needs to be better recognized so as to improve effective use of climate and weather forecasts and information for farming decision making.

A High-Resolution Biogenic Silica Record From Lake Titicaca, Peru-Bolivia: South American Millennial-Scale Climate Variability From 18-60 Kya

NASA Astrophysics Data System (ADS)

Ekdahl, E. J.; Fritz, S. C.; Stevens, L. R.; Baker, P. A.; Seltzer, G. O.

2004-12-01

Sediments recovered from a deep basin in Lake Titicaca, Peru-Boliva, were analyzed for biogenic silica (BSi) content by extraction of freeze dried sediments in 1% sodium carbonate. Sediments were dated using an age model developed from multiple 14C dates on bulk sediments. The BSi record shows distinct fluctuations in concentration and accumulation rate from 18 to 60 kya. Multi-taper method spectral analysis reveals a significant millennial-scale component to these fluctuations centered at 1370 years. High BSi accumulation rates correlate with enhanced benthic diatom preservation, suggesting that the BSi record is related to variations in lake water level. Modern-day Lake Titicaca lake level and precipitation are strongly related to northern equatorial Atlantic sea surface temperatures, with cooler SSTs related to wetter conditions. Subsequently, the spectral behavior of the GRIP ice core δ 18O record was investigated in order to estimate coherency and linkages between North Atlantic and tropical South American climate. GRIP data exhibit a significant 1370-year spectral peak which comprises approximately 26% of the total variability in the record. Despite a high degree of coherency between millennial-scale periodicities in Lake Titicaca BSi and GRIP δ 18O records, the Lake Titicaca silica record does not show longer term cooling cycles characteristic of D-O cycles found in the GRIP record. Rather, the Lake Titicaca record is highly periodic and more similar in nature to several Antarctic climate proxy records. These results suggest that while South American tropical climate varies in phase with North Atlantic climate, additional forcing mechanisms are manifest in the region which may include tropical Pacific and Southern Ocean variability.

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.

The Footprint of the Inter-decadal Pacific Oscillation in Indian Ocean Sea Surface Temperatures

NASA Astrophysics Data System (ADS)

Dong, Lu; Zhou, Tianjun; Dai, Aiguo; Song, Fengfei; Wu, Bo; Chen, Xiaolong

2016-02-01

Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871-2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcings account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. The decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.

The Footprint of the Inter-decadal Pacific Oscillation in Indian Ocean Sea Surface Temperatures.

PubMed

Dong, Lu; Zhou, Tianjun; Dai, Aiguo; Song, Fengfei; Wu, Bo; Chen, Xiaolong

2016-02-17

Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871-2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcings account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO's cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. The decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

Projected Impact of Climate Change on Hydrological Regimes in the Philippines

PubMed Central

Kanamaru, Hideki; Keesstra, Saskia; Maroulis, Jerry; David, Carlos Primo C.; Ritsema, Coen J.

2016-01-01

The Philippines is one of the most vulnerable countries in the world to the potential impacts of climate change. To fully understand these potential impacts, especially on future hydrological regimes and water resources (2010-2050), 24 river basins located in the major agricultural provinces throughout the Philippines were assessed. Calibrated using existing historical interpolated climate data, the STREAM model was used to assess future river flows derived from three global climate models (BCM2, CNCM3 and MPEH5) under two plausible scenarios (A1B and A2) and then compared with baseline scenarios (20th century). Results predict a general increase in water availability for most parts of the country. For the A1B scenario, CNCM3 and MPEH5 models predict an overall increase in river flows and river flow variability for most basins, with higher flow magnitudes and flow variability, while an increase in peak flow return periods is predicted for the middle and southern parts of the country during the wet season. However, in the north, the prognosis is for an increase in peak flow return periods for both wet and dry seasons. These findings suggest a general increase in water availability for agriculture, however, there is also the increased threat of flooding and enhanced soil erosion throughout the country. PMID:27749908

Project Ukko - Design of a climate service visualisation interface for seasonal wind forecasts

NASA Astrophysics Data System (ADS)

Hemment, Drew; Stefaner, Moritz; Makri, Stephann; Buontempo, Carlo; Christel, Isadora; Torralba-Fernandez, Veronica; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco; de Matos, Paula; Dykes, Jason

2016-04-01

Project Ukko is a prototype climate service to visually communicate probabilistic seasonal wind forecasts for the energy sector. In Project Ukko, an interactive visualisation enhances the accessibility and readability to the latests advances in seasonal wind speed predictions developed as part of the RESILIENCE prototype of the EUPORIAS (EC FP7) project. Climate services provide made-to-measure climate information, tailored to the specific requirements of different users and industries. In the wind energy sector, understanding of wind conditions in the next few months has high economic value, for instance, for the energy traders. Current energy practices use retrospective climatology, but access to reliable seasonal predictions based in the recent advances in global climate models has potential to improve their resilience to climate variability and change. Despite their potential benefits, a barrier to the development of commercially viable services is the complexity of the probabilistic forecast information, and the challenge of communicating complex and uncertain information to decision makers in industry. Project Ukko consists of an interactive climate service interface for wind energy users to explore probabilistic wind speed predictions for the coming season. This interface enables fast visual detection and exploration of interesting features and regions likely to experience unusual changes in wind speed in the coming months.The aim is not only to support users to better understand the future variability in wind power resources, but also to bridge the gap between practitioners' traditional approach and the advanced prediction systems developed by the climate science community. Project Ukko is presented as a case study of cross-disciplinary collaboration between climate science and design, for the development of climate services that are useful, usable and effective for industry users. The presentation will reflect on the challenge of developing a climate service for industry users in the wind energy sector, the background to this challenge, our approach, and the evaluation of the visualisation interface.

Underestimated interannual variability of East Asian summer rainfall under climate change

NASA Astrophysics Data System (ADS)

Ren, Yongjian; Song, Lianchun; Xiao, Ying; Du, Liangmin

2018-02-01

This study evaluates the performance of climate models in simulating the climatological mean and interannual variability of East Asian summer rainfall (EASR) using Coupled Model Intercomparison Project Phase 5 (CMIP5). Compared to the observation, the interannual variability of EASR during 1979-2005 is underestimated by the CMIP5 with a range of 0.86 16.08%. Based on bias correction of CMIP5 simulations with historical data, the reliability of future projections will be enhanced. The corrected EASR under representative concentration pathways (RCPs) 4.5 and 8.5 increases by 5.6 and 7.5% during 2081-2100 relative to the baseline of 1986-2005, respectively. After correction, the areas with both negative and positive anomalies decrease, which are mainly located in the South China Sea and central China, and southern China and west of the Philippines, separately. In comparison to the baseline, the interannual variability of EASR increases by 20.8% under RCP4.5 but 26.2% under RCP8.5 in 2006-2100, which is underestimated by 10.7 and 11.1% under both RCPs in the original CMIP5 simulation. Compared with the mean precipitation, the interannual variability of EASR is notably larger under global warming. Thus, the probabilities of floods and droughts may increase in the future.

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.

Modelling the Response of Energy, Water and CO2 Fluxes Over Forests to Climate Variability

NASA Astrophysics Data System (ADS)

Ju, W.; Chen, J.; Liu, J.; Chen, B.

2004-05-01

Understanding the response of energy, water and CO2 fluxes of terrestrial ecosystems to climate variability at various temporal scales is of interest to climate change research. To simulate carbon (C) and water dynamics and their interactions at the continental scale with high temporal and spatial resolutions, the remote sensing driven BEPS (Boreal Ecosystem Productivity Simulator) model was updated to couple with the soil model of CENTURY and a newly developed biophysical model. This coupled model separates the whole canopy into two layers. For the top layer, the leaf-level conductance is scaled up to canopy level using a sunlit and shaded leaf separation approach. Fluxes of water, and CO{2} are simulated as the sums of those from sunlit and shaded leaves separately. This new approach allows for close coupling in modeling these fluxes. The whole profile of soil under a seasonal snowpack is split into four layers for estimating soil moisture and temperature. Long-term means of the vegetation productivity and climate are employed to initialize the carbon pools for the computation of heterotrophic respiration. Validated against tower data at four forested sites, this model is able to describe these fluxes and their response to climate variability. The model captures over 55% of year-round half/one hourly variances of these fluxes. The highest agreement of model results with tower data was achieved for CO2 flux at Southern Old Aspen (SOA) (R2>0.85 and RMSE<2.37 μ mol C m-2 s-1, N=17520). However, the model slightly overestimates the diurnal amplitude of sensible heat flux in winter and sometimes underestimates that of CO2 flux in the growing season. Model simulations suggest that C uptakes of forests are controlled by climate variability and the response of C cycle to climate depends on forest type. For SOA, the annual NPP (Net Primary Productivity) is more sensitive to temperature than to precipitation. This forest usually has higher NPP in warm years than in cool years. Interannual variability of heterotrophic respiration, however, is strongly related to precipitation. The soil releases more CO2 in wet years than in dry years. Warm and relatively dry climate enhances the C uptake in this forest stand. Compared with SOA, a temperate deciduous forest in the southern part of the temperate deciduous forest biome in eastern United States responds to climate variability differently. High temperature and low precipitation in the growing season reduces NPP and consequently NEP (Net Ecosystem Productivity). In warm years, the Southern Old Jack Pine forest uptakes less C than in cool years. The modeled heterotrophic respiration and NEP are very sensitive to soil moisture and the empirical equation used to describe the effect of soil moisture on decomposition. This suggests that hydrological modelling is critical in C budget estimation. Next step, this model will be validated against more tower data and used for upscaling from site to region.

Economic costs of extratropical storms under climate change: An application of FUND

NASA Astrophysics Data System (ADS)

Narita, D.; Tol, R.; Anthoff, D.

2009-12-01

Extratropical cyclones have attracted some attention in climate policy circles as a possible significant damage factor of climate change. This study conducts an assessment of economic impacts of increased storm activities under climate change with the integrated assessment model FUND 3.5. FUND is a model that calculates damages of climate change for 16 regions by making use of exogenous scenarios of socioeconomic variables (for details of our estimation approach, see our working paper whose URL is indicated below). Our estimation shows that in the base case, the direct economic damage of enhanced storms due to climate change amounts to $2.8 billion globally (approximately 38% of the total economic loss of storms at present) at the year 2100, while the ratio to the world GDP is 0.0009%. The regional results (Figure 1) indicate that the economic effect of extratropical storms with climate change would have relatively minor importance for the US (USA): The enhanced extratropical storm damage (less than 0.001% of GDP for the base case) is one order of magnitude lower than the tropical cyclone damage (roughly 0.01% GDP) calculated by the same version of FUND. In the regions without strong tropical cyclone influence, such as Western Europe (WEU) and Australia and New Zealand (ANZ), the extratropical storms might have some more significance as a possible damage factor of climate change. Especially for the latter, the direct economic damage could amount to more than 0.006% of GDP. Still, the impact is small relative to the income growth expected in these regions. Figure 1. Increased direct economic loss at the year 2100 for selected regions (results are shown for the three different baselines: the years 1986-2005, 1976-2005, and 1996-2005). US - USA; Canada - CAN; Western Europe - WEU; Australia and New Zealand - ANZ.

Middle Miocene climate cooling linked to intensification of eastern equatorial Pacific upwelling

NASA Astrophysics Data System (ADS)

Holbourn, A. E.; Kuhnt, W.; Lyle, M. W.; Schneider, L. J.; Romero, O. E.; Andersen, N.

2013-12-01

During the middle Miocene, Earth's climate transitioned from a relatively warm phase (Miocene climatic optimum, ~17-15 Ma) into a colder mode with re-establishment of permanent ice sheets on Antarctica. Carbon sequestration and atmospheric CO2 drawdown through increased terrigenous and/or marine productivity have been proposed as the main drivers of this fundamental transition. However, comparatively little is known about the processes initially sustaining global warmth and about the chain of climate events that reversed this trend and promoted ice growth on Antarctica after ~15 Ma. We integrate high-resolution (1-3 kyr) benthic stable isotope data with XRF-scanner derived biogenic silica and carbonate accumulation estimates in an exceptionally well-preserved sedimentary archive to reconstruct variations in eastern equatorial Pacific upwelling and to investigate temporal linkages between high- and low-latitude climate change over the interval 16-13 Ma. Our records show that the climatic optimum (16.8-14.7 Ma) was characterized by high amplitude climate variations, marked by intense perturbations of the carbon cycle. Episodes of peak warmth at (southern hemisphere) insolation maxima coincided with transient shoaling of the carbonate compensation depth and enhanced carbonate dissolution in the deep ocean. A switch to obliquity-paced climate variability after 14.7 Ma concurred with a general improvement in carbonate preservation and the onset of stepwise global cooling, culminating with extensive ice growth over Antarctica at ~13.8 Ma (Mi3 event). We find that two massive increases in opal accumulation at ~14.0 and ~13.8 Ma occurred just before and during the final and most prominent cooling step, supporting the hypothesis that increased primary productivity due to enhancement of the eastern equatorial Pacific cold tongue contributed to CO2 drawdown and promoted global cooling.

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.

Does safety climate moderate the influence of staffing adequacy and work conditions on nurse injuries?

PubMed

Mark, Barbara A; Hughes, Linda C; Belyea, Michael; Chang, Yunkyung; Hofmann, David; Jones, Cheryl B; Bacon, Cynthia T

2007-01-01

Hospital nurses have one of the highest work-related injury rates in the United States. Yet, approaches to improving employee safety have generally focused on attempts to modify individual behavior through enforced compliance with safety rules and mandatory participation in safety training. We examined a theoretical model that investigated the impact on nurse injuries (back injuries and needlesticks) of critical structural variables (staffing adequacy, work engagement, and work conditions) and further tested whether safety climate moderated these effects. A longitudinal, non-experimental, organizational study, conducted in 281 medical-surgical units in 143 general acute care hospitals in the United States. Work engagement and work conditions were positively related to safety climate, but not directly to nurse back injuries or needlesticks. Safety climate moderated the relationship between work engagement and needlesticks, while safety climate moderated the effect of work conditions on both needlesticks and back injuries, although in unexpected ways. DISCUSSION AND IMPACT ON INDUSTRY: Our findings suggest that positive work engagement and work conditions contribute to enhanced safety climate and can reduce nurse injuries.

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.

Global agricultural intensification during climate change: a role for genomics.

PubMed

Abberton, Michael; Batley, Jacqueline; Bentley, Alison; Bryant, John; Cai, Hongwei; Cockram, James; de Oliveira, Antonio Costa; Cseke, Leland J; Dempewolf, Hannes; De Pace, Ciro; Edwards, David; Gepts, Paul; Greenland, Andy; Hall, Anthony E; Henry, Robert; Hori, Kiyosumi; Howe, Glenn Thomas; Hughes, Stephen; Humphreys, Mike; Lightfoot, David; Marshall, Athole; Mayes, Sean; Nguyen, Henry T; Ogbonnaya, Francis C; Ortiz, Rodomiro; Paterson, Andrew H; Tuberosa, Roberto; Valliyodan, Babu; Varshney, Rajeev K; Yano, Masahiro

2016-04-01

Agriculture is now facing the 'perfect storm' of climate change, increasing costs of fertilizer and rising food demands from a larger and wealthier human population. These factors point to a global food deficit unless the efficiency and resilience of crop production is increased. The intensification of agriculture has focused on improving production under optimized conditions, with significant agronomic inputs. Furthermore, the intensive cultivation of a limited number of crops has drastically narrowed the number of plant species humans rely on. A new agricultural paradigm is required, reducing dependence on high inputs and increasing crop diversity, yield stability and environmental resilience. Genomics offers unprecedented opportunities to increase crop yield, quality and stability of production through advanced breeding strategies, enhancing the resilience of major crops to climate variability, and increasing the productivity and range of minor crops to diversify the food supply. Here we review the state of the art of genomic-assisted breeding for the most important staples that feed the world, and how to use and adapt such genomic tools to accelerate development of both major and minor crops with desired traits that enhance adaptation to, or mitigate the effects of climate change. © 2015 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Accelerated warming of the Southern Ocean and its impacts on the hydrological cycle and sea ice.

PubMed

Liu, Jiping; Curry, Judith A

2010-08-24

The observed sea surface temperature in the Southern Ocean shows a substantial warming trend for the second half of the 20th century. Associated with the warming, there has been an enhanced atmospheric hydrological cycle in the Southern Ocean that results in an increase of the Antarctic sea ice for the past three decades through the reduced upward ocean heat transport and increased snowfall. The simulated sea surface temperature variability from two global coupled climate models for the second half of the 20th century is dominated by natural internal variability associated with the Antarctic Oscillation, suggesting that the models' internal variability is too strong, leading to a response to anthropogenic forcing that is too weak. With increased loading of greenhouse gases in the atmosphere through the 21st century, the models show an accelerated warming in the Southern Ocean, and indicate that anthropogenic forcing exceeds natural internal variability. The increased heating from below (ocean) and above (atmosphere) and increased liquid precipitation associated with the enhanced hydrological cycle results in a projected decline of the Antarctic sea ice.

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.

Understanding the Seasonal Greenness Trends and Controls in South Asia Using Satellite Based Observations

NASA Astrophysics Data System (ADS)

Sarmah, S.; Jia, G.; Zhang, A.; Singha, M.

2017-12-01

South Asia (SA) is one of the most remarkable regions in changing vegetation greenness along with its major expansion of agricultural activity, especially irrigated farming. However, SA is predicted to be a vulnerable agricultural regions to future climate changes. The influence of monsoon climate on the seasonal trends and anomalies of vegetation greenness are not well understood in the region which can provide valuable information about climate-ecosystem interaction. This study analyzed the spatio-temporal patterns of seasonal vegetation trends and variability using satellite vegetation indices (VI) including AVHRR Normalized Difference Vegetation Index (NDVI) (1982-2013) and MODIS Enhanced Vegetation Index (EVI) (2000-2013) in summer monsoon (SM) (June-Sept) and winter monsoon (WM) (Dec-Apr) seasons among irrigated cropland (IC), rainfed cropland (RC) and natural vegetation (NV). Seasonal VI variations with climatic factors (precipitation and temperature) and LULC changes have been investigated to identify the forcings behind the vegetation trends and variability. We found that major greening occurred in the last three decades due to the increase in IC productivity noticeably in WM, however, recent (2000-2013) greening trends were lower than the previous decades (1982-1999) in both the IC and RC indicating the stresses on them. The browning trends, mainly concentrated in NV areas were prominent during WM and rigorous since 2000, confirmed from the moderate resolution EVI and LULC datasets. Winter time maximal temperature had been increasing tremendously whereas precipitation trend was not significant over SA. Both the climate variability and LULC changes had integrated effects on the vegetation changes in NV areas specifically in hilly regions. However, LULC impact was intensified since 2000, mostly in north east India. This study also revealed a distinct seasonal variation in spatial distribution of correlation between VI's and climate anomalies over SA. Concluding, so far SA has managed to get a decent productivity over croplands due to the advanced cultivation techniques which likely to be at risk under future warming climate. Also NV areas of SA are in constant threat from the anthropogenic activities and climate changes.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Assessing 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

Tropical Atlantic Impacts on the Decadal Climate Variability of the Tropical Ocean and Atmosphere.

NASA Astrophysics Data System (ADS)

Li, X.; Xie, S. P.; Gille, S. T.; Yoo, C.

2015-12-01

Previous studies revealed atmospheric bridges between the tropical Pacific, Atlantic, and Indian Ocean. In particular, several recent works indicate that the Atlantic sea surface temperature (SST) may contribute to the climate variability over the equatorial Pacific. Inspired by these studies, our work aims at investigating the impact of the tropical Atlantic on the entire tropical climate system, and uncovering the physical dynamics under these tropical teleconnections. We first performed a 'pacemaker' simulation by restoring the satellite era tropical Atlantic SST changes in a fully coupled model - the CESM1. Results reveal that the Atlantic warming heats the Indo-Western Pacific and cools the Eastern Pacific, enhances the Walker circulation and drives the subsurface Pacific to a La Niña mode, contributing to 60-70% of the above tropical changes in the past 30 years. The same pan-tropical teleconnections have been validated by the statistics of observations and 106 CMIP5 control simulations. We then used a hierarchy of atmospheric and oceanic models with different complexities, to single out the roles of atmospheric dynamics, atmosphere-ocean fluxes, and oceanic dynamics in these teleconnections. With these simulations we established a two-step mechanism as shown in the schematic figure: 1) Atlantic warming generates an atmospheric deep convection and induces easterly wind anomalies over the Indo-Western Pacific in the form of Kelvin waves, and westerly wind anomalies over the eastern equatorial Pacific as Rossby waves, in line with Gill's solution. This circulation changes warms the Indo-Western Pacific and cools the Eastern Pacific with the wind-evaporation-SST effect, forming a temperature gradient over the Indo-Pacific basins. 2) The temperature gradient further generates a secondary atmospheric deep convection, which reinforces the easterly wind anomalies over the equatorial Pacific and enhances the Walker circulation, triggering the Pacific to a La Niña mode with Bjerknes ocean dynamical feedback. This mechanism contributes to the understanding of the global decadal climate variability and predictability. In particular, Atlantic contributes to the Eastern Pacific cooling, which is considered as an important source of the recent global warming hiatus.

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.

The past, present and future of African dust.

PubMed

Evan, Amato T; Flamant, Cyrille; Gaetani, Marco; Guichard, Françoise

2016-03-24

African dust emission and transport exhibits variability on diurnal to decadal timescales and is known to influence processes such as Amazon productivity, Atlantic climate modes, regional atmospheric composition and radiative balance and precipitation in the Sahel. To elucidate the role of African dust in the climate system, it is necessary to understand the factors governing its emission and transport. However, African dust is correlated with seemingly disparate atmospheric phenomena, including the El Niño/Southern Oscillation, the North Atlantic Oscillation, the meridional position of the intertropical convergence zone, Sahelian rainfall and surface temperatures over the Sahara Desert, all of which obfuscate the connection between dust and climate. Here we show that the surface wind field responsible for most of the variability in North African dust emission reflects the topography of the Sahara, owing to orographic acceleration of the surface flow. As such, the correlations between dust and various climate phenomena probably arise from the projection of the winds associated with these phenomena onto an orographically controlled pattern of wind variability. A 161-year time series of dust from 1851 to 2011, created by projecting this wind field pattern onto surface winds from a historical reanalysis, suggests that the highest concentrations of dust occurred from the 1910s to the 1940s and the 1970s to the 1980s, and that there have been three periods of persistent anomalously low dust concentrations--in the 1860s, 1950s and 2000s. Projections of the wind pattern onto climate models give a statistically significant downward trend in African dust emission and transport as greenhouse gas concentrations increase over the twenty-first century, potentially associated with a slow-down of the tropical circulation. Such a dust feedback, which is not represented in climate models, may be of benefit to human and ecosystem health in West Africa via improved air quality and increased rainfall. This feedback may also enhance warming of the tropical North Atlantic, which would make the basin more suitable for hurricane formation and growth.

Lake Challa (Kenya/Tanzania) sediments, a varved climate archive of environmental variability in equatorial East Africa of the last 25.000 years

NASA Astrophysics Data System (ADS)

Wolff, C.; Haug, G.; Plessen, B.; Kristen, I.; Verschuren, D.; Participants, C.

2008-12-01

Recently, an increasing number of climate records from low-latitude regions underscore the importance of tropical atmospheric processes in the global climate system. Nevertheless, the regional synchrony of temperature and humidity variations, as well as teleconnecting mechanisms between high and low latitudes are still poorly understood. The EuroCLIMATE project CHALLACEA aims to provide a continuous high- resolution multi-proxy record of temperature and moisture-balance variability in equatorial East Africa from the Last Glacial Maximum (25 ka BP) to the present. Lake Challa is a crater lake located about 40 km east of Mt. Kilimanjaro at an altitude of 880 m a.s.l. It is a freshwater lake whose water column is stratified during most of the year. It is fed by subsurface inflow which derives mainly from percolation of precipitation falling in the montane forest zone higher up the mountain. Within the lake form lacustrine deposits which predominantly consist of autochthonous components (carbonate, biogenic silica, organic matter). The present study focuses on microfacies analyses and isotope measurements. Fine laminations are preserved over wide parts of a 22 m long sediment profile. Microfacies analyses reveal that the light/dark couplets represent true calcite varves. The darker layers contain organic matter and endogenic calcite. Sediment trap studies show that these layers form during the warm season (Nov to Mar) when water temperatures are high and the lake is biological productive. The light layers consist predominantly of diatom frustules. They accumulate in the sediment trap between June and October. By counting and measuring the thickness of the varves on thin sections, we establish a varve record that currently covers the last 1500 years. Stable isotope analyses on bulk carbonates will complement this record and give further insights into the hydrological variability of the region and enhance our knowledge of climate change in the highly sensitive climate region of the Mt. Kilimanjaro area.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

A Multi-sensor Approach to Identify Crop Sensitivity Related to Climate Variability in Central India

NASA Astrophysics Data System (ADS)

Mondal, P.; DeFries, R. S.; Jain, M.; Robertson, A. W.; Galford, G. L.; Small, C.

2012-12-01

Agriculture is a primary source of livelihood for over 70% of India's population, with staple crops (e.g. winter wheat) playing a pivotal role in satisfying an ever-increasing food-demand of a growing population. Agricultural yield in India has been reported to be highly correlated with the timing and total amount of monsoon rainfall and/or temperature depending on crop type. With expected change in future climate (temperature and precipitation), significant fluctuations in crop yields are projected for near future. To date, little work has identified the sensitivity of cropping intensity, or the number of crops planted in a given year, to climate variability. The objective of this study is to shed light on relative importance of different climate parameters through a statistical analysis of inter-annual variations in cropping intensity at a regional scale, which may help identify adaptive strategies in response to future climate anomalies. Our study focuses on a highly human-modified landscape in central India, and uses a multi-sensor approach to determine the sensitivity of agriculture to climate variability. First, we assembled the 16-day time-series of 250m Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), and applied a spline function-based smoothing algorithm to develop maps of monsoon and winter crops in Central India for a decadal time-span. A hierarchical model involving moderate resolution Landsat (30m) data was used to estimate the heterogeneity of the spectral signature within the MODIS dataset (250m). We then compared the season-specific cropping patterns with spatio-temporal variability in climate parameters derived from the Tropical Rainfall Measuring Mission (TRMM) data. Initial data indicates that the existence of a monsoon crop has moderate to strong correlation with wet season end date (ρ = .522), wet season length (ρ = .522), and the number of rainy days during wet season (ρ = .829). Existence of a winter crop, however, has a moderately strong correlation with wet season start date (ρ = .577). In addition, winter crop yield (ton/ha) has a moderate correlation with wet season end date (ρ = .624), number of rainy days during the wet season (ρ = .492), and during the dry season (ρ = .410). Future work will assess which other factors influence cropping intensity (e.g. access to irrigation among many other), since a complex interplay of bio-physical and socio-economic factors governs the decision-making at the farm-level, ultimately leading to inter-annual variability in cropping intensity and/or yield.

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.

Atlantic Induced Pan-tropical Climate Variability in the Upper-ocean and Atmosphere

NASA Astrophysics Data System (ADS)

Li, X.; Xie, S. P.; Gille, S. T.; Yoo, C.

2016-02-01

During the last three decades, tropical sea surface temperature (SST) exhibited dipole-like trends, with warming over the tropical Atlantic and Indo-Western Pacific but cooling over the Eastern Pacific. The Eastern Pacific cooling has recently been identified as a driver of the global warming hiatus. Previous studies revealed atmospheric bridges between the tropical Pacific, Atlantic, and Indian Ocean, which could potentially contribute to this zonally asymmetric SST pattern. However, the mechanisms and the interactions between these teleconnections remain unclear. To investigate these questions, we performed a `pacemaker' simulation by restoring the tropical Atlantic SST changes in a state-of-the-art climate model - the CESM1. Results show that the Atlantic plays a key role in initiating the tropical-wide teleconnections, and the Atlantic-induced anomalies contribute 55%-75% of the total tropical SST and circulation changes during the satellite era. A hierarchy of oceanic and atmospheric models are then used to investigate the physical mechanisms of these teleconnections: the Atlantic warming enhances atmospheric deep convection, drives easterly wind anomalies over the Indo-Western Pacific through the Kelvin wave, and westerly anomalies over the eastern Pacific as Rossby waves, in line with Gill's solution (Fig1a). These wind changes induce an Indo-Western Pacific warming via the wind-evaporation-SST effect, and this warming intensifies the La Niña-type response in the upper Pacific Ocean by enhancing the easterly trade winds and through the Bjerknes ocean-dynamical processes (Fig1b). The teleconnection finally develops into a tropical-wide SST dipole pattern with an enhanced trade wind and Walker circulation, similar as the observed changes during the satellite era. This mechanism reveals that the tropical ocean basins are more tightly connected than previously thought, and the Atlantic plays a key role in the tropical climate pattern formation and further the global warming hiatus. The tropical Atlantic warming is likely due to radiative forcing and Atlantic meridional overturning circulation (AMOC). Our study suggests that the AMOC may force the decadal variability of the tropical ocean and atmosphere, and thus contributes to the decadal predictability of the global climate.

Constraining Carbonaceous Aerosol Climate Forcing by Bridging Laboratory, Field and Modeling Studies

NASA Astrophysics Data System (ADS)

Dubey, M. K.; Aiken, A. C.; Liu, S.; Saleh, R.; Cappa, C. D.; Williams, L. R.; Donahue, N. M.; Gorkowski, K.; Ng, N. L.; Mazzoleni, C.; China, S.; Sharma, N.; Yokelson, R. J.; Allan, J. D.; Liu, D.

2014-12-01

Biomass and fossil fuel combustion emits black (BC) and brown carbon (BrC) aerosols that absorb sunlight to warm climate and organic carbon (OC) aerosols that scatter sunlight to cool climate. The net forcing depends strongly on the composition, mixing state and transformations of these carbonaceous aerosols. Complexities from large variability of fuel types, combustion conditions and aging processes have confounded their treatment in models. We analyse recent laboratory and field measurements to uncover fundamental mechanism that control the chemical, optical and microphysical properties of carbonaceous aerosols that are elaborated below: Wavelength dependence of absorption and the single scattering albedo (ω) of fresh biomass burning aerosols produced from many fuels during FLAME-4 was analysed to determine the factors that control the variability in ω. Results show that ω varies strongly with fire-integrated modified combustion efficiency (MCEFI)—higher MCEFI results in lower ω values and greater spectral dependence of ω (Liu et al GRL 2014). A parameterization of ω as a function of MCEFI for fresh BB aerosols is derived from the laboratory data and is evaluated by field data, including BBOP. Our laboratory studies also demonstrate that BrC production correlates with BC indicating that that they are produced by a common mechanism that is driven by MCEFI (Saleh et al NGeo 2014). We show that BrC absorption is concentrated in the extremely low volatility component that favours long-range transport. We observe substantial absorption enhancement for internally mixed BC from diesel and wood combustion near London during ClearFlo. While the absorption enhancement is due to BC particles coated by co-emitted OC in urban regions, it increases with photochemical age in rural areas and is simulated by core-shell models. We measure BrC absorption that is concentrated in the extremely low volatility components and attribute it to wood burning. Our results support enhanced light absorption by internally mixed BC parameterizations in models and identify mixed biomass and fossil combustion regions where this effect is large. We unify the treatment of carbonaceous aerosol components and their interactions to simplify and verify their representation in climate models, and re-evaluate their direct radiative forcing.

Airborne Particles: What We Have Learned About Their Role in Climate from Remote Sensing, and Prospects for Future Advances

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2013-01-01

Desert dust, wildfire smoke, volcanic ash, biogenic and urban pollution particles, all affect the regional-scale climate of Earth in places and at times; some have global-scale impacts on the column radiation balance, cloud properties, atmospheric stability structure, and circulation patterns. Remote sensing has played a central role in identifying the sources and transports of airborne particles, mapping their three-dimensional distribution and variability, quantifying their amount, and constraining aerosol air mass type. The measurements obtained from remote sensing have strengths and limitations, and their value for characterizing Earths environment is enhanced immensely when they are combined with direct, in situ observations, and used to constrain aerosol transport and climate models. A similar approach has been taken to study the role particles play in determining the climate of Mars, though based on far fewer observations. This presentation will focus what we have learned from remote sensing about the impacts aerosol have on Earths climate; a few points about how aerosols affect the climate of Mars will also be introduced, in the context of how we might assess aerosol-climate impacts more generally on other worlds.

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.

The Upstream and Downstream impact of Milankovitch cycles in continental nonmarine sedimentary records

NASA Astrophysics Data System (ADS)

Valero, Luis; Garcés, Miguel; Huerta, Pedro; Cabrera, Lluís

2016-04-01

Discerning the effects of climate in the stratigraphic record is crucial for the comprehension of past climate changes. The signature of climate in sedimentary sequences is often assessed by the identification of Milankovitch cycles, as they can be recognized due to their (quasi) periodic behaviour. The integration of diverse stratigraphic disciplines is required in order to understand the different processes involved in the expression of the orbital cycles in the sedimentary records. New advances in Stratigraphy disclose the different variables that affect the sedimentation along the sediment routing systems. These variables can be summarized as the relationship between accommodation and sediment supply (AS/SS), because they account for the shifts of the total mass balance of a basin. Based in these indicators we propose a synthetic model for the understanding of the expression of climate in continental basins. Sedimentation in internally drained lake basins is particularly sensitive to net precipitation/evaporation variations. Rapid base level oscillations modify the AS/SS ratio sufficiently as to mask possible sediment flux variations associated to the changing discharge. On the other hand, basins lacking a central lacustrine system do not experience climatically-driven accommodation changes, and thus are more sensitive to archive sediment pulses. Small basins lacking carbonate facies are the ideal candidates to archive the impact of orbital forcing in the landscapes, as their small-scale sediment transfer systems are unable to buffer the upstream signal. Sedimentation models that include the relationship between accommodation and sediment supply, the effects of density and type of vegetation, and its coupled response with climate are needed to enhance their reliability.

A hydro-meteorological model chain to assess the influence of natural variability and impacts of climate change on extreme events and propose optimal water management

NASA Astrophysics Data System (ADS)

von Trentini, F.; Willkofer, F.; Wood, R. R.; Schmid, F. J.; Ludwig, R.

2017-12-01

The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. Therefore, a hydro-meteorological model chain is applied. It employs high performance computing capacity of the Leibniz Supercomputing Centre facility SuperMUC to dynamically downscale 50 members of the Global Circulation Model CanESM2 over European and Eastern North American domains using the Canadian Regional Climate Model (RCM) CRCM5. Over Europe, the unique single model ensemble is conjointly analyzed with the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change in the dynamics of extreme events. Furthermore, these 50 members of a single RCM will enhance extreme value statistics (extreme return periods) by exploiting the available 1500 model years for the reference period from 1981 to 2010. Hence, the RCM output is applied to drive the process based, fully distributed, and deterministic hydrological model WaSiM in high temporal (3h) and spatial (500m) resolution. WaSiM and the large ensemble are further used to derive a variety of hydro-meteorological patterns leading to severe flood events. A tool for virtual perfect prediction shall provide a combination of optimal lead time and management strategy to mitigate certain flood events following these patterns.

Changing Conditions in the Arctic: An Analysis of 45 years of Tropospheric Ozone Measurements at Barrow Observatory

NASA Astrophysics Data System (ADS)

McClure-Begley, A.; Petropavlovskikh, I. V.; Crepinsek, S.; Jefferson, A.; Emmons, L. K.; Oltmans, S. J.

2017-12-01

In order to understand the impact of climate on local bio-systems, understanding the changes to the atmospheric composition and processes in the Arctic boundary layer and free troposphere is imperative. In the Arctic, many conditions influence tropospheric ozone variability such as: seasonal halogen caused depletion events, long range transport of pollutants from mid-northern latitudes, compounds released from wildfires, and different meteorological conditions. The Barrow station in Utqiagvik, Alaska has collected continuous measurements of ground-level ozone since 1973. This unique long-term time series allows for analysis of the influence of a rapidly changing climate on ozone conditions in this region. Specifically, this study analyzes the frequency of enhanced ozone episodes over time and provides in depth analysis of periods of positive deviations from the expected conditions. To discern the contribution of different pollutant sources to observed ozone variability, co-located measurements of aerosols, carbon monoxide, and meteorological conditions are used. In addition, the NCAR Mozart-4/MOPITT Chemical Forecast model and NOAA Hysplit back-trajectory analysis provide information on transport patterns to the Arctic and confirmation of the emission sources that influenced the observed conditions. These anthropogenic influences on ozone variability in and below the boundary layer are essential for developing an understanding of the interaction of climate change and the bio-systems in the Arctic.

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

Disentangling the role of Natural Variability and Climate Change in the aggravation of Droughts in central Chile

NASA Astrophysics Data System (ADS)

Garreaud, R. D.; Boisier, J. P.; Rondanelli, R. F.

2016-12-01

Among other climate extreme events, droughts (annual rainfall deficit larger than 25%) have punctuated the hydro-climate history of central Chile (30-40°S) with profoundly negative effects on physical (e.g., water storage depletion), ecological (e.g., increase in forest fires) and human systems (e.g., major distress in rural communities). In this presentation we show that intense but short-lived (1 or 2 years long) droughts are associated with anticyclonic (cyclonic) anomalies over the subtropical south Pacific (Amudsen sea), reduced synoptic-scale variability in that area and weakening of the westerly winds impinging the west coast of South America. These large-scale anomalies often occurs in connection with the cold phase of ENSO (La Niña events). Of particular interest is an uninterrupted rainfall deficit since 2010 to date, referred to as the central Chile mega-drought (MD) in virtue of its unprecedented character in term of duration, spatial extent and coincidence with warm air temperatures. The protracted MD shares some of the climate features of the historical events but for the prevalence of near-neutral ENSO years with the exception of 2010 (La Niña) and 2015 (intense El Niño). Thus, we use a suite of fully-coupled and SST-forced climate simulations to disentangle natural and anthropogenic contributions to current mega drought as well as to shed light in the physical link between global climate change and rainfall deficit in central Chile drought. It turns out that anthropogenic climate change accounts for about a third of the drought as it forces SAM towards its positive polarity. The later enhances a dipole of geopotential height over the South Pacific that is conducive to dry conditions in central Chile.

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.

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.

Climate sensitivity of DSSAT under different agriculture practice scenarios in China

NASA Astrophysics Data System (ADS)

Xia, L.; Robock, A.

2014-12-01

Crop yields are sensitive to both agricultural practice and climate changes. Under different agricultural practice scenarios, crop yield may have different climate sensitivities. Since it is important to understand how future climate changes affect agriculture productivity and what the potential adaptation strategies would be to compensate for possible negative impacts on crop production, we performed experiments to study climate sensitivity under different agricultural practice scenarios for rice, maize and wheat in the top four production provinces in China using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The agricultural practice scenarios include four categories: different amounts of nitrogen fertilizer or no nitrogen stress; irrigation turned on or off, or no water stress; all possible seeds in the DSSAT cultivar data base; and different planting dates. For the climate sensitivity test, the control climate is from 1998 to 2007, and we individually modify four climate variables: daily maximum and minimum temperature by +2 °C and -2 °C, daily precipitation by +20% and -20%, and daily solar radiation by + 20% and -20%. With more nitrogen fertilizer applied, crops are more sensitive to temperature changes as well as precipitation changes because of their release from nitrogen limitation. With irrigation turned on, crop yield sensitivity to temperature decreases in most of the regions depending on the amount of the local precipitation, since more water is available and soil temperature varies less with higher soil moisture. Those results indicate that there could be possible agriculture adaptation strategies under certain future climate scenarios. For example, increasing nitrogen fertilizer usage by a certain amount might compensate for the negative impact on crop yield from climate changes. However, since crops are more sensitive to climate changes when there is more nitrogen fertilizer applied, if the climate changes are unfavorable to crop yields, increasing nitrogen fertilizer usage at certain levels might enhance the negative climate change impact. Enhanced nitrogen fertilizer use might have additional negative impacts on climate because of nitrogen emissions to the atmosphere, but those effects were not studied here.

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.

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

USGS Publications Warehouse

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

2009-01-01

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

Effects on asthma and respiratory allergy of Climate change and air pollution.

PubMed

D'Amato, Gennaro; Vitale, Carolina; De Martino, Annamaria; Viegi, Giovanni; Lanza, Maurizia; Molino, Antonio; Sanduzzi, Alessandro; Vatrella, Alessandro; Annesi-Maesano, Isabella; D'Amato, Maria

2015-01-01

The major changes to our world are those involving the atmosphere and the climate, including global warming induced by anthropogenic factors, with impact on the biosphere and human environment. Studies on the effects of climate changes on respiratory allergy are still lacking and current knowledge is provided by epidemiological and experimental studies on the relationship between allergic respiratory diseases, asthma and environmental factors, like meteorological variables, airborne allergens and air pollution. Epidemiologic studies have demonstrated that urbanization, high levels of vehicle emissions and westernized lifestyle are correlated with an increased frequency of respiratory allergy, mainly in people who live in urban areas in comparison with people living in rural areas. However, it is not easy to evaluate the impact of climate changes and air pollution on the prevalence of asthma in general and on the timing of asthma exacerbations, although the global rise in asthma prevalence and severity could be also considered an effect of air pollution and climate changes. Since airborne allergens and air pollutants are frequently increased contemporaneously in the atmosphere, enhanced IgE-mediated response to aeroallergens and enhanced airway inflammation could account for the increasing frequency of respiratory allergy and asthma in atopic subjects in the last five decades. Pollen allergy is frequently used to study the interrelationship between air pollution and respiratory allergic diseases such as rhinitis and bronchial asthma. Climatic factors (temperature, wind speed, humidity, thunderstorms, etc) can affect both components (biological and chemical) of this interaction. Scientific societies should be involved in advocacy activities, such as those realized by the Global Alliance against chronic Respiratory Diseases (GARD).

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.

A high-resolution speleothem record of western equatorial Pacific rainfall: Implications for Holocene ENSO evolution

NASA Astrophysics Data System (ADS)

Chen, Sang; Hoffmann, Sharon S.; Lund, David C.; Cobb, Kim M.; Emile-Geay, Julien; Adkins, Jess F.

2016-05-01

The El Niño-Southern Oscillation (ENSO) is the primary driver of interannual climate variability in the tropics and subtropics. Despite substantial progress in understanding ocean-atmosphere feedbacks that drive ENSO today, relatively little is known about its behavior on centennial and longer timescales. Paleoclimate records from lakes, corals, molluscs and deep-sea sediments generally suggest that ENSO variability was weaker during the mid-Holocene (4-6 kyr BP) than the late Holocene (0-4 kyr BP). However, discrepancies amongst the records preclude a clear timeline of Holocene ENSO evolution and therefore the attribution of ENSO variability to specific climate forcing mechanisms. Here we present δ18 O results from a U-Th dated speleothem in Malaysian Borneo sampled at sub-annual resolution. The δ18 O of Borneo rainfall is a robust proxy of regional convective intensity and precipitation amount, both of which are directly influenced by ENSO activity. Our estimates of stalagmite δ18 O variance at ENSO periods (2-7 yr) show a significant reduction in interannual variability during the mid-Holocene (3240-3380 and 5160-5230 yr BP) relative to both the late Holocene (2390-2590 yr BP) and early Holocene (6590-6730 yr BP). The Borneo results are therefore inconsistent with lacustrine records of ENSO from the eastern equatorial Pacific that show little or no ENSO variance during the early Holocene. Instead, our results support coral, mollusc and foraminiferal records from the central and eastern equatorial Pacific that show a mid-Holocene minimum in ENSO variance. Reduced mid-Holocene interannual δ18 O variability in Borneo coincides with an overall minimum in mean δ18 O from 3.5 to 5.5 kyr BP. Persistent warm pool convection would tend to enhance the Walker circulation during the mid-Holocene, which likely contributed to reduced ENSO variance during this period. This finding implies that both convective intensity and interannual variability in Borneo are driven by coupled air-sea dynamics that are sensitive to precessional insolation forcing. Isolating the exact mechanisms that drive long-term ENSO evolution will require additional high-resolution paleoclimatic reconstructions and further investigation of Holocene tropical climate evolution using coupled climate models.

Deglacial diatom production in the tropical North Atlantic driven by enhanced silicic acid supply

NASA Astrophysics Data System (ADS)

Hendry, Katharine R.; Gong, Xun; Knorr, Gregor; Pike, Jennifer; Hall, Ian R.

2016-03-01

Major shifts in ocean circulation are thought to be responsible for abrupt changes in temperature and atmospheric CO2 during the last deglaciation, linked to variability in meridional heat transport and deep ocean carbon storage. There is also widespread evidence for shifts in biological production during these times of deglacial CO2 rise, including enhanced diatom production in regions such as the tropical Atlantic. However, it remains unclear as to whether this diatom production was driven by enhanced wind-driven upwelling or density-driven vertical mixing, or by elevated thermocline concentrations of silicic acid supplied to the surface at a constant rate. Here, we demonstrate that silicic acid supply at depth in the NE Atlantic was enhanced during the abrupt climate events of the deglaciation. We use marine sediment archives to show that an increase in diatom production during abrupt climate shifts could only occur in regions of the NE Atlantic where the deep supply of silicic acid could reach the surface. The associated changes are indicative of enhanced regional wind-driven upwelling and/or weakened stratification due to circulation changes during phases of weakened Atlantic meridional overturning. Globally near-synchronous pulses of diatom production and enhanced thermocline concentrations of silicic acid suggest that widespread deglacial surface-driven breakdown of stratification, linked to changes in atmospheric circulation, had major consequences for biological productivity and carbon cycling.

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China

PubMed Central

Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

2015-01-01

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983–1999 and 2000–2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6–11.0% and 19.5–92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming. PMID:26336098

Responses of Crop Water Use Efficiency to Climate Change and Agronomic Measures in the Semiarid Area of Northern China.

PubMed

Zhang, Jingting; Ren, Wei; An, Pingli; Pan, Zhihua; Wang, Liwei; Dong, Zhiqiang; He, Di; Yang, Jia; Pan, Shufen; Tian, Hanqin

2015-01-01

It has long been concerned how crop water use efficiency (WUE) responds to climate change. Most of existing researches have emphasized the impact of single climate factor but have paid less attention to the effect of developed agronomic measures on crop WUE. Based on the long-term field observations/experiments data, we investigated the changing responses of crop WUE to climate variables (temperature and precipitation) and agronomic practices (fertilization and cropping patterns) in the semi-arid area of northern China (SAC) during two periods, 1983-1999 and 2000-2010 (drier and warmer). Our results suggest that crop WUE was an intrinsical system sensitive to climate change and agronomic measures. Crops tend to reach the maximum WUE (WUEmax) in warm-dry environment while reach the stable minimum WUE (WUEmin) in warm-wet environment, with a difference between WUEmax and WUEmin ranging from 29.0%-55.5%. Changes in temperature and precipitation in the past three decades jointly enhanced crop WUE by 8.1%-30.6%. Elevated fertilizer and rotation cropping would increase crop WUE by 5.6-11.0% and 19.5-92.9%, respectively. These results indicate crop has the resilience by adjusting WUE, which is not only able to respond to subsequent periods of favorable water balance but also to tolerate the drought stress, and reasonable agronomic practices could enhance this resilience. However, this capacity would break down under impact of climate changes and unconscionable agronomic practices (e.g. excessive N/P/K fertilizer or traditional continuous cropping). Based on the findings in this study, a conceptual crop WUE model is constructed to indicate the threshold of crop resilience, which could help the farmer develop appropriate strategies in adapting the adverse impacts of climate warming.

Responses of tropical root crops to climate change: implications for Pacific food security

NASA Astrophysics Data System (ADS)

Gleadow, R.; Webber, B.; Macness, N.; Lisson, S.; Nauluvula, P.; Hargraves, J.; Crimp, S. J.

2013-12-01

Cassava and taro are an important source of calories in many parts of the developing world and hold much promise for meeting the need for food security in equatorial regions. Communities in the Pacific Island countries reliant on agriculture-based livelihood systems have been identified as particularly at risk from climate change, due to likely increases in crop failure, new patterns of pests and diseases, lack of appropriate seed and plant material, loss of livestock and potential loss of arable land. Recent shortfalls in agricultural production resulting from changing export markets, commodity prices, climatic variation, and population growth and urbanisation, have contributed further to regional food insecurity concerns. Cassava and taro contain herbivore defense chemicals that are detrimental to human health (cyanogenic glucosides and calcium oxalate). Unprocessed cassava can cause acute cyanide intoxication, paralysis and even death, especially during droughts. A number of activities are already underway in the Pacific region to identify ways to ameliorate existing climate risk and enhance current agricultural production. Whilst these activities are important to ensure long-term agricultural sustainability, there remains a significant degree of uncertainty as to how effective these strategies may be in the face of a changing and increasingly variable future climate. We present our current understanding of the impact of climate change on key Pacific production systems - specifically those based on the staple root crops, taro and cassava. This includes (1) Our understanding of the responses of cassava and taro crops to existing environmental drivers (climate, soil and nutrient interactions); (2) The responses of cassava and taro crops to enhanced CO2 conditions; and (3) Efforts to model productivity responses (within the APSIM framework) and results for locations in the Pacific.

Distant Influence of Kuroshio Eddies on North Pacific Weather Patterns?

PubMed Central

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

2015-01-01

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

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

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Moderation, mediation - or even both? School climate and the association between peer and adolescent alcohol use.

PubMed

Tomczyk, Samuel; Isensee, Barbara; Hanewinkel, Reiner

2015-12-01

Ample studies discuss the enhancing effects of peer drinking on student alcohol use. In addition, there is vast research on school climate impact on student alcohol use. Though these two areas are intertwined for most young adolescents, it is heretofore not completely clear, in what way these characteristics functionally interact and affect drinking behavior. In a longitudinal study, we analyzed a sample of 2490 German adolescents (Mage=13.32, SD=0.57, range=8-13) from 5th (fall 2010) to 8th (fall 2013) grade. We discerned mediating (class climate) and moderating (school organization variables) functions of school on the association between peer and adolescent alcohol use, and finally combined them in direct effect moderated mediation models for a variety of outcomes (lifetime alcohol use, frequency and amount of drinking, binge drinking), adjusting for possible confounders. Class climate mediated a small significant part of the association between peer and adolescent alcohol use (1.8-2.4%), with the exception of lifetime drinking. Student-teacher ratio and percentage of at-risk students significantly moderated the peer-adolescent association, with the latter having an enhancing and the first having a buffering effect. School life serves as an important context of adolescent development and as such, seems to have direct and indirect effects on behavior and health. Future research should pay attention to differentiating effects of school climate and include both forms of operationalization when analyzing school effects on student behavior. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development of a drought forecasting model for the Asia-Pacific region using remote sensing and climate data: Focusing on Indonesia

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Kim, Gayoung; Im, Jungho

2017-04-01

Three regions of Indonesia with different rainfall characteristics were chosen to develop drought forecast models based on machine learning. The 6-month Standardized Precipitation Index (SPI6) was selected as the target variable. The models' forecast skill was compared to the skill of long-range climate forecast models in terms of drought accuracy and regression mean absolute error (MAE). Indonesian droughts are known to be related to El Nino Southern Oscillation (ENSO) variability despite of regional differences as well as monsoon, local sea surface temperature (SST), other large-scale atmosphere-ocean interactions such as Indian Ocean Dipole (IOD) and Southern Pacific Convergence Zone (SPCZ), and local factors including topography and elevation. Machine learning models are thus to enhance drought forecast skill by combining local and remote SST and remote sensing information reflecting initial drought conditions to the long-range climate forecast model results. A total of 126 machine learning models were developed for the three regions of West Java (JB), West Sumatra (SB), and Gorontalo (GO) and six long-range climate forecast models of MSC_CanCM3, MSC_CanCM4, NCEP, NASA, PNU, POAMA as well as one climatology model based on remote sensing precipitation data, and 1 to 6-month lead times. When compared the results between the machine learning models and the long-range climate forecast models, West Java and Gorontalo regions showed similar characteristics in terms of drought accuracy. Drought accuracy of the long-range climate forecast models were generally higher than the machine learning models with short lead times but the opposite appeared for longer lead times. For West Sumatra, however, the machine learning models and the long-range climate forecast models showed similar drought accuracy. The machine learning models showed smaller regression errors for all three regions especially with longer lead times. Among the three regions, the machine learning models developed for Gorontalo showed the highest drought accuracy and the lowest regression error. West Java showed higher drought accuracy compared to West Sumatra, while West Sumatra showed lower regression error compared to West Java. The lower error in West Sumatra may be because of the smaller sample size used for training and evaluation for the region. Regional differences of forecast skill are determined by the effect of ENSO and the following forecast skill of the long-range climate forecast models. While shown somewhat high in West Sumatra, relative importance of remote sensing variables was mostly low in most cases. High importance of the variables based on long-range climate forecast models indicates that the forecast skill of the machine learning models are mostly determined by the forecast skill of the climate models.

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.

Estimation of water storage changes in small endorheic lakes in Burabay National Nature Park (Northern Kazakhstan, Central Asia); the effect of climate change and anthropogenic influences

NASA Astrophysics Data System (ADS)

Yapiyev, Vadim; Sagintayev, Zhanay; Verhoef, Anne; Samarkhanov, Kanat; Jumassultanova, Saltanat

2017-04-01

Both climate change and anthropogenic activities contribute to deterioration of terrestrial water resources and ecosystems worldwide. It has been observed in recent decades that water-limited steppe regions of Central Asia are among ecosystems found to exhibit enhanced responses to climate variability. In fact, the largest share of worldwide net loss of permanent water extent is geographically concentrated in the Central Asia and Middle East regions attributed to both climate variability/change and human activities impacts. We used a digital elevation model, digitized bathymetry maps and high resolution Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia, for the period 2000-2016. Based on the analysis of long-term climatic data from meteorological stations, hydrometeorological network observations as well as regional climate model projections we evaluate the impacts of past thirty years and future climatic conditions on the water balance of BNNP lake catchments. The anthropogenic water consumption was estimated based on data collected at a local water supply company and regulation authorities. One the one hand historical in-situ observations and future climate projections do not show a significant change in precipitation in BNNP. On the other hand both observations and the model demonstrate steadily rising air temperatures in the area. It is concluded that the long-term decline in water levels for most of these lakes can be largely attributed to climate change (but only via changes in air temperature, causing evaporation to exceed precipitation) and not to direct anthropogenic influences such as increased water withdrawals. In addition, the two largest lakes, showing the highest historical water level decline, do not have sufficient water drainage basin area to sustain water levels under increased evaporation rates.

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.

Meteorological factors affecting dengue incidence in Davao, Philippines.

PubMed

Iguchi, Jesavel A; Seposo, Xerxes T; Honda, Yasushi

2018-05-15

Dengue fever is a major public health concern in the Philippines, and has been a significant cause of hospitalizations and deaths among young children. Previous literature links climate change to dengue, and with increasingly unpredictable changing climate patterns, there is a need to understand how these meteorological variables affect dengue incidence in a highly endemic area. Weekly dengue incidences (2011-2015) in Davao Region, Philippines were obtained from the Department of Health. Same period of weekly local meteorological variables were obtained from the National Climatic Data Center (NCDC) and the National Oceanic and Atmospheric Administration (NOAA). Wavelet coherence analysis was used to determine the presence of non-stationary relationships, while a quasi-Poisson regression combined with distributed lag nonlinear model (DLNM) was used to analyze the association between meteorological variables and dengue incidences. Significant periodicity was detected in the 7 to 14-week band between the year 2011-2012 and a 26-week periodicity from the year 2013-2014. Overall cumulative risks were particularly high for rainfall at 32 mm (RR: 1.67, 95% CI: 1.07-2.62), while risks were observed to increase with increasing dew point. On the other hand, lower average temperature of 26 °C has resulted to an increased RR of dengue (RR: 1.96, 95% CI: 0.47-8.15) while higher temperature from 27 °C to 31 °C has lower RR. The observed possible threshold levels of these meteorological variables can be integrated into an early warning system to enhance dengue prediction for better vector control and management in the future.

[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.

Visualisation and communication of probabilistic climate forecasts to renewable-energy policy makers

NASA Astrophysics Data System (ADS)

Steffen, Sophie; Lowe, Rachel; Davis, Melanie; Doblas-Reyes, Francisco J.; Rodó, Xavier

2014-05-01

Despite the strong dependence on weather and climate variability of the renewable-energy industry, and the existence of several initiatives towards demonstrating the added benefits of integrating probabilistic forecasts into energy decision-making processes, weather and climate forecasts are still under-utilised within the sector. Improved communication is fundamental to stimulate the use of climate forecast information within decision-making processes, in order to adapt to a highly climate dependent renewable-energy industry. This work focuses on improving the visualisation of climate forecast information, paying special attention to seasonal time scales. This activity is central to enhance climate services for renewable energy and to optimise the usefulness and usability of inherently complex climate information. In the realm of the Global Framework for Climate Services (GFCS) initiative, and subsequent European projects: Seasonal-to-Decadal Climate Prediction for the Improvement of European Climate Service (SPECS) and the European Provision of Regional Impacts Assessment in Seasonal and Decadal Timescales (EUPORIAS), this paper investigates the visualisation and communication of seasonal forecasts with regards to their usefulness and usability, to enable the development of a European climate service. The target end user is the group of renewable-energy policy makers, who are central to enhance climate services for the energy industry. The overall objective is to promote the wide-range dissemination and exchange of actionable climate information based on seasonal forecasts from Global Producing Centres (GPCs). It examines the existing main barriers and deficits. Examples of probabilistic climate forecasts from different GPC's are used to make a catalogue of current approaches, to assess their advantages and limitations and, finally, to recommend better alternatives. Interviews have been conducted with renewable-energy stakeholders to receive feedback for the improvement of existing visualisation techniques of forecasts. The overall aim is to establish a communication protocol for the visualisation of probabilistic climate forecasts, which does not currently exist. GPCs show their own probabilistic forecasts with limited consistency in their communication across different centres, which complicates the understanding for the end user. The recommended communication protocol for both the visualisation and description of climate forecasts can help to introduce a standard format and message to end users from several climate-sensitive sectors, such as energy, tourism, agriculture and health.

Enhanced Arctic Amplification Began at the Mid-Brunhes Event ~400,000 years ago.

PubMed

Cronin, T M; Dwyer, G S; Caverly, E K; Farmer, J; DeNinno, L H; Rodriguez-Lazaro, J; Gemery, L

2017-11-03

Arctic Ocean temperatures influence ecosystems, sea ice, species diversity, biogeochemical cycling, seafloor methane stability, deep-sea circulation, and CO 2 cycling. Today's Arctic Ocean and surrounding regions are undergoing climatic changes often attributed to "Arctic amplification" - that is, amplified warming in Arctic regions due to sea-ice loss and other processes, relative to global mean temperature. However, the long-term evolution of Arctic amplification is poorly constrained due to lack of continuous sediment proxy records of Arctic Ocean temperature, sea ice cover and circulation. Here we present reconstructions of Arctic Ocean intermediate depth water (AIW) temperatures and sea-ice cover spanning the last ~ 1.5 million years (Ma) of orbitally-paced glacial/interglacial cycles (GIC). Using Mg/Ca paleothermometry of the ostracode Krithe and sea-ice planktic and benthic indicator species, we suggest that the Mid-Brunhes Event (MBE), a major climate transition ~ 400-350 ka, involved fundamental changes in AIW temperature and sea-ice variability. Enhanced Arctic amplification at the MBE suggests a major climate threshold was reached at ~ 400 ka involving Atlantic Meridional Overturning Circulation (AMOC), inflowing warm Atlantic Layer water, ice sheet, sea-ice and ice-shelf feedbacks, and sensitivity to higher post-MBE interglacial CO 2 concentrations.

The dynamics of climate-induced deglacial ice stream acceleration

NASA Astrophysics Data System (ADS)

Robel, A.; Tziperman, E.

2015-12-01

Geological observations indicate that ice streams were a significant contributor to ice flow in the Laurentide Ice Sheet during the Last Glacial Maximum. Conceptual and simple model studies have also argued that the gradual development of ice streams increases the sensitivity of large ice sheets to weak climate forcing. In this study, we use an idealized configuration of the Parallel Ice Sheet Model to explore the role of ice streams in rapid deglaciation. In a growing ice sheet, ice streams develop gradually as the bed warms and the margin expands outward onto the continental shelf. Then, a weak change in equilibrium line altitude commensurate with Milankovitch forcing results in a rapid deglacial response, as ice stream acceleration leads to enhanced calving and surface melting at low elevations. We explain the dynamical mechanism that drives this ice stream acceleration and its broader applicability as a feedback for enhancing ice sheet decay in response to climate forcing. We show how our idealized ice sheet simulations match geomorphological observations of deglacial ice stream variability and previous model-data analyses. We conclude with observations on the potential for interaction between ice streams and other feedback mechanisms within the earth system.

Holocene climate aridification trend and human impact interrupted by millennial- and centennial-scale climate fluctuations from a new sedimentary record from Padul (Sierra Nevada, southern Iberian Peninsula)

NASA Astrophysics Data System (ADS)

Ramos-Román, María J.; Jiménez-Moreno, Gonzalo; Camuera, Jon; García-Alix, Antonio; Anderson, R. Scott; Jiménez-Espejo, Francisco J.; Carrión, José S.

2018-01-01

Holocene centennial-scale paleoenvironmental variability has been described in a multiproxy analysis (i.e., lithology, geochemistry, macrofossil, and microfossil analyses) of a paleoecological record from the Padul Basin in Sierra Nevada, southern Iberian Peninsula. This sequence covers a relevant time interval hitherto unreported in the studies of the Padul sedimentary sequence. The ˜ 4700-year record has preserved proxies of climate variability, with vegetation, lake levels, and sedimentological change during the Holocene in one of the most unique and southernmost wetlands in Europe. The progressive middle and late Holocene trend toward arid conditions identified by numerous authors in the western Mediterranean region, mostly related to a decrease in summer insolation, is also documented in this record; here it is also superimposed by centennial-scale variability in humidity. In turn, this record shows centennial-scale climate oscillations in temperature that correlate with well-known climatic events during the late Holocene in the western Mediterranean region, synchronous with variability in solar and atmospheric dynamics. The multiproxy Padul record first shows a transition from a relatively humid middle Holocene in the western Mediterranean region to more aridity from ˜ 4700 to ˜ 2800 cal yr BP. A relatively warm and humid period occurred between ˜ 2600 and ˜ 1600 cal yr BP, coinciding with persistent negative North Atlantic Oscillation (NAO) conditions and the historic Iberian-Roman Humid Period. Enhanced arid conditions, co-occurring with overall positive NAO conditions and increasing solar activity, are observed between ˜ 1550 and ˜ 450 cal yr BP (˜ 400 to ˜ 1400 CE) and colder and warmer conditions occurred during the Dark Ages and Medieval Climate Anomaly (MCA), respectively. Slightly wetter conditions took place during the end of the MCA and the first part of the Little Ice Age, which could be related to a change towards negative NAO conditions and minima in solar activity. Time series analysis performed from local (Botryococcus and total organic carbon) and regional (Mediterranean forest) signals helped us determining the relationship between southern Iberian climate evolution, atmospheric and oceanic dynamics, and solar activity. Our multiproxy record shows little evidence of human impact in the area until ˜ 1550 cal yr BP, when evidence of agriculture and livestock grazing occurs. Therefore, climate is the main forcing mechanism controlling environmental change in the area until relatively recently.

Reconstruction of Past Mediterranean Climate

NASA Astrophysics Data System (ADS)

García-Herrera, Ricardo; Luterbacher, Jürg; Lionello, Piero; Gonzáles-Rouco, Fidel; Ribera, Pedro; Rodó, Xavier; Kull, Christoph; Zerefos, Christos

2007-02-01

First MEDCLIVAR Workshop on Reconstruction of Past Mediterranean Climate; Pablo de Olavide University, Carmona, Spain, 8-11 November 2006; Mediterranean Climate Variability and Predictability (MEDCLIVAR; http://www.medclivar.eu) is a program that coordinates and promotes research on different aspects of Mediterranean climate. The main MEDCLIVAR goals include the reconstruction of past climate, describing patterns and mechanisms characterizing climate space-time variability, extremes at different time and space scales, coupled climate model/empirical reconstruction comparisons, seasonal forecasting, and the identification of the forcings responsible for the observed changes. The program has been endorsed by CLIVAR (Climate Variability and Predictability project) and is funded by the European Science Foundation.

Climate change and pastoralism: impacts, consequences and adaptation.

PubMed

Herrero, M; Addison, J; Bedelian, C; Carabine, E; Havlík, P; Henderson, B; Van De Steeg, J; Thornton, P K

2016-11-01

The authors discuss the main climate change impacts on pastoralist societies, including those on rangelands, livestock and other natural resources, and their extended repercussions on food security, incomes and vulnerability. The impacts of climate change on the rangelands of the globe and on the vulnerability of the people who inhabit them will be severe and diverse, and will require multiple, simultaneous responses. In higher latitudes, the removal of temperature constraints might increase pasture production and livestock productivity, but in tropical arid lands, the impacts are highly location specific, but mostly negative. The authors outline several adaptation options, ranging from implementing new technical practices and diversifying income sources to finding institutional support and introducing new market mechanisms, all of which are pivotal for enhancing the capacity of pastoralists to adapt to climate variability and change. Due to the dynamism of all the changes affecting pastoral societies, strategies that lock pastoral societies into specified development pathways could be maladaptive. Flexible and evolving combinations of practices and policies are the key to successful pastoral adaptation.

Early onset of industrial-era warming across the oceans and continents.

PubMed

Abram, Nerilie J; McGregor, Helen V; Tierney, Jessica E; Evans, Michael N; McKay, Nicholas P; Kaufman, Darrell S

2016-08-25

The evolution of industrial-era warming across the continents and oceans provides a context for future climate change and is important for determining climate sensitivity and the processes that control regional warming. Here we use post-ad 1500 palaeoclimate records to show that sustained industrial-era warming of the tropical oceans first developed during the mid-nineteenth century and was nearly synchronous with Northern Hemisphere continental warming. The early onset of sustained, significant warming in palaeoclimate records and model simulations suggests that greenhouse forcing of industrial-era warming commenced as early as the mid-nineteenth century and included an enhanced equatorial ocean response mechanism. The development of Southern Hemisphere warming is delayed in reconstructions, but this apparent delay is not reproduced in climate simulations. Our findings imply that instrumental records are too short to comprehensively assess anthropogenic climate change and that, in some regions, about 180 years of industrial-era warming has already caused surface temperatures to emerge above pre-industrial values, even when taking natural variability into account.

Climate forecasts in disaster management: Red Cross flood operations in West Africa, 2008.

PubMed

Braman, Lisette Martine; van Aalst, Maarten Krispijn; Mason, Simon J; Suarez, Pablo; Ait-Chellouche, Youcef; Tall, Arame

2013-01-01

In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors. © 2013 The Author(s). Journal compilation © Overseas Development Institute, 2013.

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.

Towards a Local-Scale Climate Service for Colombian Agriculture: Findings and Future Perspectives

NASA Astrophysics Data System (ADS)

Ramirez-Villegas, J.; Prager, S.; Llanos, L.; Agudelo, D.; Esquivel, A.; Sotelo, S.; Guevara, E.; Howland, F. C.; Munoz, A.; Rodriguez, J.; Ordonez, L.; Fernandes, K.

2017-12-01

Globally, interannual climate variability explains roughly a third of the yield variation for major crops. In Colombia, interannual climate variations and specially those driven by ENSO can disrupt production, lower farmers' incomes and increase market prices for both urban and rural consumers alike. Farmers in Colombia, however, often plan for the cropping season based on the immediately prior year's experience, which is unlikely to result in successful crops under high climate variability events. Critical decisions for avoiding total investment loss or to ensure successful harvests, including issues related to planting date, what variety to plant, or whether to plant, are made, at best, intuitively. Here, we demonstrate that the combination of better data, skillful seasonal climate forecasts, calibrated crop models, and a web-based climate services platform tailored to users' needs can prove successful in establishing a sustained climate service for agriculture. Rainfall predictability analyses indicate that statistical seasonal climate forecasts are skillful enough for issuing forecasts reliably in virtually all areas, with dry periods generally showing greater predictability than wet periods. Importantly, we find that a better specification of predictor regions significantly enhances seasonal forecast skill. Rice and maize crop models capture well the growth and development of rice and maize crops in experimental settings, and ably simulate historical (1980-2014) variations in productivity. With skillful climate and crop models, we developed a climate services platform that produces seasonal climate forecasts, and connects these with crop models. A usability study of the forecast platform revealed that, from a population of ca. 200 farmers and professionals, roughly two thirds correctly interpreted information and felt both confident and encouraged to use the platform. Nevertheless, capacity strengthening on key agro-climatology concepts was highlighted by farmers as a crucial need. Challenges also arose in certain zones due to limited access to electricity, computers or Internet. Based on our results, we conclude that for a climate service to be truly sustainable, well-calibrated and skillful models are as critical as the co-creation of the service itself with the stakeholder community.

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

PubMed

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

2017-06-01

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

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.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-02-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Discriminating low frequency components from long range persistent fluctuations in daily atmospheric temperature variability

NASA Astrophysics Data System (ADS)

Lanfredi, M.; Simoniello, T.; Cuomo, V.; Macchiato, M.

2009-07-01

This study originated from recent results reported in literature, which support the existence of long-range (power-law) persistence in atmospheric temperature fluctuations on monthly and inter-annual scales. We investigated the results of Detrended Fluctuation Analysis (DFA) carried out on twenty-two historical daily time series recorded in Europe in order to evaluate the reliability of such findings in depth. More detailed inspections emphasized systematic deviations from power-law and high statistical confidence for functional form misspecification. Rigorous analyses did not support scale-free correlation as an operative concept for Climate modelling, as instead suggested in literature. In order to understand the physical implications of our results better, we designed a bivariate Markov process, parameterised on the basis of the atmospheric observational data by introducing a slow dummy variable. The time series generated by this model, analysed both in time and frequency domains, tallied with the real ones very well. They accounted for both the deceptive scaling found in literature and the correlation details enhanced by our analysis. Our results seem to evidence the presence of slow fluctuations from another climatic sub-system such as ocean, which inflates temperature variance up to several months. They advise more precise re-analyses of temperature time series before suggesting dynamical paradigms useful for Climate modelling and for the assessment of Climate Change.

Frost and leaf-size gradients in forests: global patterns and experimental evidence.

PubMed

Lusk, Christopher H; Clearwater, Michael J; Laughlin, Daniel C; Harrison, Sandy P; Prentice, Iain Colin; Nordenstahl, Marisa; Smith, Benjamin

2018-05-16

Explanations of leaf size variation commonly focus on water availability, yet leaf size also varies with latitude and elevation in environments where water is not strongly limiting. We provide the first conclusive test of a prediction of leaf energy balance theory that may explain this pattern: large leaves are more vulnerable to night-time chilling, because their thick boundary layers impede convective exchange with the surrounding air. Seedlings of 15 New Zealand evergreens spanning 12-fold variation in leaf width were exposed to clear night skies, and leaf temperatures were measured with thermocouples. We then used a global dataset to assess several climate variables as predictors of leaf size in forest assemblages. Leaf minus air temperature was strongly correlated with leaf width, ranging from -0.9 to -3.2°C in the smallest- and largest-leaved species, respectively. Mean annual temperature and frost-free period were good predictors of evergreen angiosperm leaf size in forest assemblages, but no climate variable predicted deciduous leaf size. Although winter deciduousness makes large leaves possible in strongly seasonal climates, large-leaved evergreens are largely confined to frost-free climates because of their susceptibility to radiative cooling. Evergreen leaf size data can therefore be used to enhance vegetation models, and to infer palaeotemperatures from fossil leaf assemblages. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.

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

Van Aalst, M.

Climate change is already taking place, and further changes are inevitable. Developing countries, and particularly the poorest people in these countries, are most at risk. The impacts result not only from gradual changes in temperature and sea level but also, in particular, from increased climate variability and extremes, including more intense floods, droughts, and storms. These changes are already having major impacts on the economic performance of developing countries and on the lives and livelihoods of millions of poor people around the world. Climate change thus directly affects the World Bank Group's mission of eradicating poverty. It also puts atmore » risk many projects in a wide range of sectors, including infrastructure, agriculture, human health, water resources, and environment. The risks include physical threats to the investments, potential underperformance, and the possibility that projects will indirectly contribute to rising vulnerability by, for example, triggering investment and settlement in high-risk areas. The way to address these concerns is not to separate climate change adaptation from other priorities but to integrate comprehensive climate risk management into development planning, programs, and projects. While there is a great need to heighten awareness of climate risk in Bank work, a large body of experience on climate risk management is already available, in analytical work, in country dialogues, and in a growing number of investment projects. This operational experience highlights the general ingredients for successful integration of climate risk management into the mainstream development agenda: getting the right sectoral departments and senior policy makers involved; incorporating risk management into economic planning; engaging a wide range of nongovernmental actors (businesses, nongovernmental organizations, communities, and so on); giving attention to regulatory issues; and choosing strategies that will pay off immediately under current climate conditions. There are several ways in which the World Bank Group can continue helping its clients better manage climate risks to poverty reduction and sustainable development: Integrating climate risk management into the project cycle, by adopting early risk identification (for instance by applying a quick and simple risk-screening tool) and following up throughout the design process if necessary. Integrating climate risk management into country and sector dialogues, especially in countries and sectors that are particularly vulnerable. Enhancing internal support for and coordination of climate risk management by, for example, expanding analytical work and capacity for cross-support by the Global Climate Change Team and the Hazard Management Unit of the World Bank and by actively developing climate risk management activities within regional departments. Supporting the establishment of proper financing mechanisms for adaptation, using, for example, the Investment Framework for Clean Energy and Development. New funding mechanisms created under the United Nations Framework Convention on Climate Change (UNFCCC) and being made operational by the Global Environment Facility (GEF), as well as the Kyoto Protocol, should be used to leverage maximum adaptation results within the Bank's broad range of development activities and investments. By enhancing climate risk management, the World Bank Group will be able to address the growing risks from climate change and, at the same time, make current development investments more resilient to climate variability and extreme weather events. In that way, climate risk management will not only guard the Bank's investments in a changing climate but will also improve the impact of development efforts right now.« less

Asynchronous North Atlantic iceberg discharges during the last glacial period explained through ocean circulation changes

NASA Astrophysics Data System (ADS)

Montoya, M.; Banderas, R.; Alvarez-Solas, J.; Robinson, A.

2017-12-01

Heinrich events (HEs) are episodes of increased ice-rafted debris (IRD) deposition in the North Atlantic Ocean that took place during stadials of the last glacial period, and are interpreted as massive iceberg discharges from the Laurentide Ice Sheet (LIS). IRD originating from the Fennoscandian ice sheet (FIS) accompany HEs during stadials, but enhanced calving has also been reported, however, during interstadials. While a number of mechanisms have been proposed to explain HEs involving the LIS, the role of the FIS during these events has not received much attention from a modeling perspective. Thus, a consistent explanation for the asynchronous occurrence of enhanced IRD throughout the North Atlantic is lacking. Here we investigate the response of the FIS to millennial-scale climate variability during the last glacial period. We use a hybrid three-dimensional thermomechanical ice-sheet model forced offline through a novel perturbative approach accounting for a more realistic treatment of millennial-scale climatic variability, including both the atmospheric and the oceanic components. Our results show that the FIS responds with enhanced iceberg discharges in phase with interstadial warmings in the North Atlantic. Separating the atmospheric and oceanic effects demonstrates the major role of the ocean in controlling the dynamics of the FIS on millennial timescales. While the atmospheric forcing alone is only able to produce modest iceberg discharges (< 0.02 Sv), the warmer oceanic surface waters lead to much higher rates of iceberg surges (ca. 0.1 Sv) as a result of relatively high basal melting rates within the margins of the ice sheet through the reactivation of ice streams in the northeastern (NE) part of the ice sheet. Together with previous work our results provide a consistent explanation for the asynchronous response of the LIS and the FIS to glacial abrupt climate changes. Finally, they support the notion that the FIS is a likely candidate to produce iceberg discharges during interstadials as suggested by IRD in the region.

Irrigation as an Historical Climate Forcing

NASA Technical Reports Server (NTRS)

Cook, Benjamin I.; Shukla, Sonali P.; Puma, Michael J.; Nazarenko, Larissa S.

2014-01-01

Irrigation is the single largest anthropogenic water use, a modification of the land surface that significantly affects surface energy budgets, the water cycle, and climate. Irrigation, however, is typically not included in standard historical general circulation model (GCM) simulations along with other anthropogenic and natural forcings. To investigate the importance of irrigation as an anthropogenic climate forcing, we conduct two 5-member ensemble GCM experiments. Both are setup identical to the historical forced (anthropogenic plus natural) scenario used in version 5 of the Coupled Model Intercomparison Project, but in one experiment we also add water to the land surface using a dataset of historically estimated irrigation rates. Irrigation has a negligible effect on the global average radiative balance at the top of the atmosphere, but causes significant cooling of global average surface air temperatures over land and dampens regional warming trends. This cooling is regionally focused and is especially strong in Western North America, the Mediterranean, the Middle East, and Asia. Irrigation enhances cloud cover and precipitation in these same regions, except for summer in parts of Monsoon Asia, where irrigation causes a reduction in monsoon season precipitation. Irrigation cools the surface, reducing upward fluxes of longwave radiation (increasing net longwave), and increases cloud cover, enhancing shortwave reflection (reducing net shortwave). The relative magnitude of these two processes causes regional increases (northern India) or decreases (Central Asia, China) in energy availability at the surface and top of the atmosphere. Despite these changes in net radiation, however, climate responses are due primarily to larger magnitude shifts in the Bowen ratio from sensible to latent heating. Irrigation impacts on temperature, precipitation, and other climate variables are regionally significant, even while other anthropogenic forcings (anthropogenic aerosols, greenhouse gases, etc.) dominate the long term climate evolution in the simulations. To better constrain the magnitude and uncertainties of irrigation-forced climate anomalies, irrigation should therefore be considered as another important anthropogenic climate forcing in the next generation of historical climate simulations and multimodel assessments.

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.

The footprint of the inter-decadal Pacific oscillation in Indian Ocean sea surface temperatures

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

Dong, Lu; Zhou, Tianjun; Dai, Aiguo

Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871–2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcingsmore » account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. As a result, the decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.« less

The footprint of the inter-decadal Pacific oscillation in Indian Ocean sea surface temperatures

DOE PAGES

Dong, Lu; Zhou, Tianjun; Dai, Aiguo; ...

2016-02-17

Superimposed on a pronounced warming trend, the Indian Ocean (IO) sea surface temperatures (SSTs) also show considerable decadal variations that can cause regional climate oscillations around the IO. However, the mechanisms of the IO decadal variability remain unclear. Here we perform numerical experiments using a state-of-the-art, fully coupled climate model in which the external forcings with or without the observed SSTs in the tropical eastern Pacific Ocean (TEP) are applied for 1871–2012. Both the observed timing and magnitude of the IO decadal variations are well reproduced in those experiments with the TEP SSTs prescribed to observations. Although the external forcingsmore » account for most of the warming trend, the decadal variability in IO SSTs is dominated by internal variability that is induced by the TEP SSTs, especially the Inter-decadal Pacific Oscillation (IPO). The IPO weakens (enhances) the warming of the external forcings by about 50% over the IO during IPO’s cold (warm) phase, which contributes about 10% to the recent global warming hiatus since 1999. As a result, the decadal variability in IO SSTs is modulated by the IPO-induced atmospheric adjustment through changing surface heat fluxes, sea surface height and thermocline depth.« less

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

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....

Ionosphere variability during the 2009 SSW: Influence of the lunar semidiurnal tide and mechanisms producing electron density variability

NASA Astrophysics Data System (ADS)

Pedatella, N. M.; Liu, H.-L.; Sassi, F.; Lei, J.; Chau, J. L.; Zhang, X.

2014-05-01

To investigate ionosphere variability during the 2009 sudden stratosphere warming (SSW), we present simulation results that combine the Whole Atmosphere Community Climate Model Extended version and the thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM). The simulations reveal notable enhancements in both the migrating semidiurnal solar (SW2) and lunar (M2) tides during the SSW. The SW2 and M2 amplitudes reach ˜50 m s-1 and ˜40 m s-1, respectively, in zonal wind at E region altitudes. The dramatic increase in the M2 at these altitudes influences the dynamo generation of electric fields, and the importance of the M2 on the ionosphere variability during the 2009 SSW is demonstrated by comparing simulations with and without the M2. TIME-GCM simulations that incorporate the M2 are found to be in good agreement with Jicamarca Incoherent Scatter Radar vertical plasma drifts and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations of the maximum F region electron density. The agreement with observations is worse if the M2 is not included in the simulation, demonstrating that the lunar tide is an important contributor to the ionosphere variability during the 2009 SSW. We additionally investigate sources of the F region electron density variability during the SSW. The primary driver of the electron density variability is changes in electric fields. Changes in meridional neutral winds and thermosphere composition are found to also contribute to the electron density variability during the 2009 SSW. The electron density variability for the 2009 SSW is therefore not solely due to variability in electric fields as previously thought.

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.

The role of Amundsen-Bellingshausen Sea anticyclonic circulation in forcing marine air intrusions into West Antarctica

NASA Astrophysics Data System (ADS)

Emanuelsson, B. Daniel; Bertler, Nancy A. N.; Neff, Peter D.; Renwick, James A.; Markle, Bradley R.; Baisden, W. Troy; Keller, Elizabeth D.

2018-01-01

Persistent positive 500-hPa geopotential height anomalies from the ECMWF ERA-Interim reanalysis are used to quantify Amundsen-Bellingshausen Sea (ABS) anticyclonic event occurrences associated with precipitation in West Antarctica (WA). We demonstrate that multi-day (minimum 3-day duration) anticyclones play a key role in the ABS by dynamically inducing meridional transport, which is associated with heat and moisture advection into WA. This affects surface climate variability and trends, precipitation rates and thus WA ice sheet surface mass balance. We show that the snow accumulation record from the Roosevelt Island Climate Evolution (RICE) ice core reflects interannual variability of blocking and geopotential height conditions in the ABS/Ross Sea region. Furthermore, our analysis shows that larger precipitation events are related to enhanced anticyclonic circulation and meridional winds, which cause pronounced dipole patterns in air temperature anomalies and sea ice concentrations between the eastern Ross Sea and the Bellingshausen Sea/Weddell Sea, as well as between the eastern and western Ross Sea.

On the discrepancy between observed and CMIP5 multi-model simulated Barents Sea winter sea ice decline

NASA Astrophysics Data System (ADS)

Li, Dawei; Zhang, Rong; Knutson, Thomas R.

2017-04-01

This study aims to understand the relative roles of external forcing versus internal climate variability in causing the observed Barents Sea winter sea ice extent (SIE) decline since 1979. We identify major discrepancies in the spatial patterns of winter Northern Hemisphere sea ice concentration trends over the satellite period between observations and CMIP5 multi-model mean externally forced response. The CMIP5 externally forced decline in Barents Sea winter SIE is much weaker than that observed. Across CMIP5 ensemble members, March Barents Sea SIE trends have little correlation with global mean surface air temperature trends, but are strongly anti-correlated with trends in Atlantic heat transport across the Barents Sea Opening (BSO). Further comparison with control simulations from coupled climate models suggests that enhanced Atlantic heat transport across the BSO associated with regional internal variability may have played a leading role in the observed decline in winter Barents Sea SIE since 1979.

Reduced cooling following future volcanic eruptions

NASA Astrophysics Data System (ADS)

Hopcroft, Peter O.; Kandlbauer, Jessy; Valdes, Paul J.; Sparks, R. Stephen J.

2017-11-01

Volcanic eruptions are an important influence on decadal to centennial climate variability. Large eruptions lead to the formation of a stratospheric sulphate aerosol layer which can cause short-term global cooling. This response is modulated by feedback processes in the earth system, but the influence from future warming has not been assessed before. Using earth system model simulations we find that the eruption-induced cooling is significantly weaker in the future state. This is predominantly due to an increase in planetary albedo caused by increased tropospheric aerosol loading with a contribution from associated changes in cloud properties. The increased albedo of the troposphere reduces the effective volcanic aerosol radiative forcing. Reduced sea-ice coverage and hence feedbacks also contribute over high-latitudes, and an enhanced winter warming signal emerges in the future eruption ensemble. These findings show that the eruption response is a complex function of the environmental conditions, which has implications for the role of eruptions in climate variability in the future and potentially in the past.

Mid Pleistocene foraminiferal mass extinction coupled with phytoplankton evolution

PubMed Central

Kender, Sev; McClymont, Erin L.; Elmore, Aurora C.; Emanuele, Dario; Leng, Melanie J.; Elderfield, Henry

2016-01-01

Understanding the interaction between climate and biotic evolution is crucial for deciphering the sensitivity of life. An enigmatic mass extinction occurred in the deep oceans during the Mid Pleistocene, with a loss of over 100 species (20%) of sea floor calcareous foraminifera. An evolutionarily conservative group, benthic foraminifera often comprise >50% of eukaryote biomass on the deep-ocean floor. Here we test extinction hypotheses (temperature, corrosiveness and productivity) in the Tasman Sea, using geochemistry and micropalaeontology, and find evidence from several globally distributed sites that the extinction was caused by a change in phytoplankton food source. Coccolithophore evolution may have enhanced the seasonal ‘bloom' nature of primary productivity and fundamentally shifted it towards a more intra-annually variable state at ∼0.8 Ma. Our results highlight intra-annual variability as a potential new consideration for Mid Pleistocene global biogeochemical climate models, and imply that deep-sea biota may be sensitive to future changes in productivity. PMID:27311937

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.

An enhanced archive facilitating climate impacts analysis

USGS Publications Warehouse

Maurer, E.P.; Brekke, L.; Pruitt, T.; Thrasher, B.; Long, J.; Duffy, P.; Dettinger, M.; Cayan, D.; Arnold, J.

2014-01-01

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrologi- cal variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_ cmip_projections).

North Atlantic summers have warmed more than winters since 1353, and the response of marine zooplankton.

PubMed

Kamenos, Nicholas A

2010-12-28

Modeling and measurements show that Atlantic marine temperatures are rising; however, the low temporal resolution of models and restricted spatial resolution of measurements (i) mask regional details critical for determining the rate and extent of climate variability, and (ii) prevent robust determination of climatic impacts on marine ecosystems. To address both issues for the North East Atlantic, a fortnightly resolution marine climate record from 1353-2006 was constructed for shallow inshore waters and compared to changes in marine zooplankton abundance. For the first time summer marine temperatures are shown to have increased nearly twice as much as winter temperatures since 1353. Additional climatic instability began in 1700 characterized by ∼5-65 year climate oscillations that appear to be a recent phenomenon. Enhanced summer-specific warming reduced the abundance of the copepod Calanus finmarchicus, a key food item of cod, and led to significantly lower projected abundances by 2040 than at present. The faster increase of summer marine temperatures has implications for climate projections and affects abundance, and thus biomass, near the base of the marine food web with potentially significant feedback effects for marine food security.

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.

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.

Observed Land Impacts on Clouds, Water Vapor, and Rainfall at Continental Scales

NASA Technical Reports Server (NTRS)

Jin, Menglin; King, Michael D.

2005-01-01

How do the continents affect large-scale hydrological cycles? How important can one continent be to the climate system? To address these questions, 4-years of National Aeronautics and Space Administration (NASA) Terra Moderate Resolution Imaging Spectroradiometer (MODIS) observations, Tropical Rainfall Measuring Mission (TRMM) observations, and the Global Precipitation Climatology Project (GPCP) global precipitation analysis, were used to assess the land impacts on clouds, rainfall, and water vapor at continental scales. At these scales, the observations illustrate that continents are integrated regions that enhance the seasonality of atmospheric and surface hydrological parameters. Specifically, the continents of Eurasia and North America enhance the seasonality of cloud optical thickness, cirrus fraction, rainfall, and water vapor. Over land, both liquid water and ice cloud effective radii are smaller than over oceans primarily because land has more aerosol particles. In addition, different continents have similar impacts on hydrological variables in terms of seasonality, but differ in magnitude. For example, in winter, North America and Eurasia increase cloud optical thickness to 17.5 and 16, respectively, while in summer, Eurasia has much smaller cloud optical thicknesses than North America. Such different land impacts are determined by each continent s geographical condition, land cover, and land use. These new understandings help further address the land-ocean contrasts on global climate, help validate global climate model simulated land-atmosphere interactions, and help interpret climate change over land.

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.

Enhanced precipitation variability decreases grass- and increases shrub-productivity

PubMed Central

Gherardi, Laureano A.; Sala, Osvaldo E.

2015-01-01

Although projections of precipitation change indicate increases in variability, most studies of impacts of climate change on ecosystems focused on effects of changes in amount of precipitation, overlooking precipitation variability effects, especially at the interannual scale. Here, we present results from a 6-y field experiment, where we applied sequences of wet and dry years, increasing interannual precipitation coefficient of variation while maintaining a precipitation amount constant. Increased precipitation variability significantly reduced ecosystem primary production. Dominant plant-functional types showed opposite responses: perennial-grass productivity decreased by 81%, whereas shrub productivity increased by 67%. This pattern was explained by different nonlinear responses to precipitation. Grass productivity presented a saturating response to precipitation where dry years had a larger negative effect than the positive effects of wet years. In contrast, shrubs showed an increasing response to precipitation that resulted in an increase in average productivity with increasing precipitation variability. In addition, the effects of precipitation variation increased through time. We argue that the differential responses of grasses and shrubs to precipitation variability and the amplification of this phenomenon through time result from contrasting root distributions of grasses and shrubs and competitive interactions among plant types, confirmed by structural equation analysis. Under drought conditions, grasses reduce their abundance and their ability to absorb water that then is transferred to deep soil layers that are exclusively explored by shrubs. Our work addresses an understudied dimension of climate change that might lead to widespread shrub encroachment reducing the provisioning of ecosystem services to society. PMID:26417095

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

NASA Astrophysics Data System (ADS)

Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

2011-08-01

During the past decades, human water use more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water scarcity considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which is subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes and reservoirs by means of the global hydrological model PCR-GLOBWB. The results show a drastic increase in the global population living under water-stressed conditions (i.e., moderate to high water stress) due to the growing water demand, primarily for irrigation, which more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27 % of the global population were under water-stressed conditions for 1960. This number increased to 2.6 billion or 43 % for 2000. Our results indicate that increased water demand is the decisive factor for the heightened water stress, enhancing the intensity of water stress up to 200 %, while climate variability is often the main determinant of onsets for extreme events, i.e. major droughts. However, our results also suggest that in several emerging and developing economies (e.g., India, Turkey, Romania and Cuba) some of the past observed droughts were anthropogenically driven due to increased water demand rather than being climate-induced. In those countries, it can be seen that human water consumption is a major factor contributing to the high intensity of major drought events.

Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability

NASA Astrophysics Data System (ADS)

Wada, Y.; van Beek, L. P. H.; Bierkens, M. F. P.

2011-12-01

During the past decades, human water use has more than doubled, yet available freshwater resources are finite. As a result, water scarcity has been prevalent in various regions of the world. Here, we present the first global assessment of past development of water stress considering not only climate variability but also growing water demand, desalinated water use and non-renewable groundwater abstraction over the period 1960-2001 at a spatial resolution of 0.5°. Agricultural water demand is estimated based on past extents of irrigated areas and livestock densities. We approximate past economic development based on GDP, energy and household consumption and electricity production, which are subsequently used together with population numbers to estimate industrial and domestic water demand. Climate variability is expressed by simulated blue water availability defined by freshwater in rivers, lakes, wetlands and reservoirs by means of the global hydrological model PCR-GLOBWB. We thus define blue water stress by comparing blue water availability with corresponding net total blue water demand by means of the commonly used, Water Scarcity Index. The results show a drastic increase in the global population living under water-stressed conditions (i.e. moderate to high water stress) due to growing water demand, primarily for irrigation, which has more than doubled from 1708/818 to 3708/1832 km3 yr-1 (gross/net) over the period 1960-2000. We estimate that 800 million people or 27% of the global population were living under water-stressed conditions for 1960. This number is eventually increased to 2.6 billion or 43% for 2000. Our results indicate that increased water demand is a decisive factor for heightened water stress in various regions such as India and North China, enhancing the intensity of water stress up to 200%, while climate variability is often a main determinant of extreme events. However, our results also suggest that in several emerging and developing economies (e.g. India, Turkey, Romania and Cuba) some of past extreme events were anthropogenically driven due to increased water demand rather than being climate-induced.

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Burned forests impact water supplies.

PubMed

Hallema, Dennis W; Sun, Ge; Caldwell, Peter V; Norman, Steven P; Cohen, Erika C; Liu, Yongqiang; Bladon, Kevin D; McNulty, Steven G

2018-04-10

Wildland fire impacts on surface freshwater resources have not previously been measured, nor factored into regional water management strategies. But, large wildland fires are increasing and raise concerns about fire impacts on potable water. Here we synthesize long-term records of wildland fire, climate, and river flow for 168 locations across the United States. We show that annual river flow changed in 32 locations, where more than 19% of the basin area was burned. Wildland fires enhanced annual river flow in the western regions with a warm temperate or humid continental climate. Wildland fires increased annual river flow most in the semi-arid Lower Colorado region, in spite of frequent droughts in this region. In contrast, prescribed burns in the subtropical Southeast did not significantly alter river flow. These extremely variable outcomes offer new insights into the potential role of wildfire and prescribed fire in regional water resource management, under a changing climate.

Regional climate impacts of a possible future grand solar minimum.

PubMed

Ineson, Sarah; Maycock, Amanda C; Gray, Lesley J; Scaife, Adam A; Dunstone, Nick J; Harder, Jerald W; Knight, Jeff R; Lockwood, Mike; Manners, James C; Wood, Richard A

2015-06-23

Any reduction in global mean near-surface temperature due to a future decline in solar activity is likely to be a small fraction of projected anthropogenic warming. However, variability in ultraviolet solar irradiance is linked to modulation of the Arctic and North Atlantic Oscillations, suggesting the potential for larger regional surface climate effects. Here, we explore possible impacts through two experiments designed to bracket uncertainty in ultraviolet irradiance in a scenario in which future solar activity decreases to Maunder Minimum-like conditions by 2050. Both experiments show regional structure in the wintertime response, resembling the North Atlantic Oscillation, with enhanced relative cooling over northern Eurasia and the eastern United States. For a high-end decline in solar ultraviolet irradiance, the impact on winter northern European surface temperatures over the late twenty-first century could be a significant fraction of the difference in climate change between plausible AR5 scenarios of greenhouse gas concentrations.

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

Holocene environmental changes inferred from biological and sedimentological proxies in a high elevation Great Basin lake in the northern Ruby Mountains, Nevada, USA

USGS Publications Warehouse

Wahl, David B.; Starratt, Scott W.; Anderson, Lysanna; Kusler, Jennifer E.; Fuller, Christopher C.; Addison, Jason A.; Wan, Elmira

2015-01-01

Multi-proxy analyses were conducted on a sediment core from Favre Lake, a high elevation cirque lake in the northern Ruby Mountains, Nevada, and provide a ca. 7600 year record of local and regional environmental change. Data indicate that lake levels were lower from 7600-5750 cal yr BP, when local climate was warmer and/or drier than today. Effective moisture increased after 5750 cal yr BP and remained relatively wet, and possibly cooler, until ca. 3750 cal yr BP. Results indicate generally dry conditions but also enhanced climatic variability from 3750-1750 cal yr BP, after which effective moisture increased. The timing of major changes in the Favre Lake proxy data are roughly coeval and in phase with those recorded in several paleoclimate studies across the Great Basin, suggesting regional climatic controls on local conditions and similar responses at high and low altitudes.

Modelling Climate/Global Change and Assessing Environmental Risks for Siberia

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Impact of Stochastic Parameterization Schemes on Coupled and Uncoupled Climate Simulations with the Community Earth System Model

NASA Astrophysics Data System (ADS)

Christensen, H. M.; Berner, J.; Coleman, D.; Palmer, T.

2015-12-01

Stochastic parameterizations have been used for more than a decade in atmospheric models to represent the variability of unresolved sub-grid processes. They have a beneficial effect on the spread and mean state of medium- and extended-range forecasts (Buizza et al. 1999, Palmer et al. 2009). There is also increasing evidence that stochastic parameterization of unresolved processes could be beneficial for the climate of an atmospheric model through noise enhanced variability, noise-induced drift (Berner et al. 2008), and by enabling the climate simulator to explore other flow regimes (Christensen et al. 2015; Dawson and Palmer 2015). We present results showing the impact of including the Stochastically Perturbed Parameterization Tendencies scheme (SPPT) in coupled runs of the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 4 (CAM4) with historical forcing. The SPPT scheme accounts for uncertainty in the CAM physical parameterization schemes, including the convection scheme, by perturbing the parametrised temperature, moisture and wind tendencies with a multiplicative noise term. SPPT results in a large improvement in the variability of the CAM4 modeled climate. In particular, SPPT results in a significant improvement to the representation of the El Nino-Southern Oscillation in CAM4, improving the power spectrum, as well as both the inter- and intra-annual variability of tropical pacific sea surface temperatures. References: Berner, J., Doblas-Reyes, F. J., Palmer, T. N., Shutts, G. J., & Weisheimer, A., 2008. Phil. Trans. R. Soc A, 366, 2559-2577 Buizza, R., Miller, M. and Palmer, T. N., 1999. Q.J.R. Meteorol. Soc., 125, 2887-2908. Christensen, H. M., I. M. Moroz & T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2239-9 Dawson, A. and T. N. Palmer, 2015. Clim. Dynam., doi: 10.1007/s00382-014-2238-x Palmer, T.N., R. Buizza, F. Doblas-Reyes, et al., 2009, ECMWF technical memorandum 598.

Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

NASA Astrophysics Data System (ADS)

Visser, H.; Molenaar, J.

1995-05-01

The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of the model is rather poor, and possible explanations are discussed.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting models, as confirmed by AIC, BIC, and MAPE.

Multi-proxy palaeoclimate reconstructions from peatlands in southern South America

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Assessment of projected climate change in the Carpathian Region using the Holdridge life zone system

NASA Astrophysics Data System (ADS)

Szelepcsényi, Zoltán; Breuer, Hajnalka; Kis, Anna; Pongrácz, Rita; Sümegi, Pál

2018-01-01

In this paper, expected changes in the spatial and altitudinal distribution patterns of Holdridge life zone (HLZ) types are analysed to assess the possible ecological impacts of future climate change for the Carpathian Region, by using 11 bias-corrected regional climate model simulations of temperature and precipitation. The distribution patterns of HLZ types are characterized by the relative extent, the mean centre and the altitudinal range. According to the applied projections, the following conclusions can be drawn: (a) the altitudinal ranges are likely to expand in the future, (b) the lower and upper altitudinal limits as well as the altitudinal midpoints may move to higher altitudes, (c) a northward shift is expected for most HLZ types and (d) the magnitudes of these shifts can even be multiples of those observed in the last century. Related to the northward shifts, the HLZ types warm temperate thorn steppe and subtropical dry forest can also appear in the southern segment of the target area. However, a large uncertainty in the estimated changes of precipitation patterns was indicated by the following: (a) the expected change in the coverage of the HLZ type cool temperate steppe is extremely uncertain because there is no consensus among the projections even in terms of the sign of the change (high inter-model variability) and (b) a significant trend in the westward/eastward shift is simulated just for some HLZ types (high temporal variability). Finally, it is important to emphasize that the uncertainty of our results is further enhanced by the fact that some important aspects (e.g. seasonality of climate variables, direct CO2 effect, etc.) cannot be considered in the estimating process.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States

USGS Publications Warehouse

Pourmokhtarian, Afshin; Driscoll, Charles T.; Campbell, John L.; Hayhoe, Katharine; Stoner, Anne M. K.; Adams, Mary Beth; Burns, Douglas; Fernandez, Ivan; Mitchell, Myron J.; Shanley, James B.

2017-01-01

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere–ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO2effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change.

Annual climate variation modifies nitrogen induced carbon accumulation of Pinus sylvestris forests.

PubMed

Lim, Hyungwoo; Oren, Ram; Linder, Sune; From, Fredrik; Nordin, Annika; Fahlvik, Nils; Lundmark, Tomas; Näsholm, Torgny

2017-09-01

We report results from long-term simulated external nitrogen (N) input experiments in three northern Pinus sylvestris forests, two of moderately high and one of moderately low productivity, assessing effects on annual net primary production (NPP) of woody mass and its interannual variation in response to variability in weather conditions. A sigmoidal response of wood NPP to external N inputs was observed in the both higher and lower productivity stands, reaching a maximum of ~65% enhancement regardless of the native site productivity, saturating at an external N input of 4-5 g N·m -2 ·yr -1 . The rate of increase in wood NPP and the N response efficiency (RE N , increase in wood NPP per external N input) were maximized at an external N input of ~3 g N·m -2 ·yr -1 , regardless of site productivity. The maximum RE N was greater in the higher productivity than the lower productivity stand (~20 vs. ~14 g C/g N). The N-induced enhancement of wood NPP and its RE N were, however, markedly contingent on climatic variables. In both of the higher and lower productivity stands, wood NPP increased with growing season precipitation (P), but only up to ~400 mm. The sensitivity of the response to P increased with increasing external N inputs. Increasing growing season temperature (T) somewhat increased the N-induced drought effect, whereas decreasing T reduced the drought effect. These responses of wood NPP infused a large temporal variation to RE N , making the use of a fixed value unadvisable. Based on these results, we suggest that regional climate conditions and future climate scenarios should be considered when modeling carbon sequestration in response to N deposition in boreal P. sylvestris, and possibly other forests. © 2017 by the Ecological Society of America.

Modeled ecohydrological responses to climate change at seven small watersheds in the northeastern United States.

PubMed

Pourmokhtarian, Afshin; Driscoll, Charles T; Campbell, John L; Hayhoe, Katharine; Stoner, Anne M K; Adams, Mary Beth; Burns, Douglas; Fernandez, Ivan; Mitchell, Myron J; Shanley, James B

2017-02-01

A cross-site analysis was conducted on seven diverse, forested watersheds in the northeastern United States to evaluate hydrological responses (evapotranspiration, soil moisture, seasonal and annual streamflow, and water stress) to projections of future climate. We used output from four atmosphere-ocean general circulation models (AOGCMs; CCSM4, HadGEM2-CC, MIROC5, and MRI-CGCM3) included in Phase 5 of the Coupled Model Intercomparison Project, coupled with two Representative Concentration Pathways (RCP 8.5 and 4.5). The coarse resolution AOGCMs outputs were statistically downscaled using an asynchronous regional regression model to provide finer resolution future climate projections as inputs to the deterministic dynamic ecosystem model PnET-BGC. Simulation results indicated that projected warmer temperatures and longer growing seasons in the northeastern United States are anticipated to increase evapotranspiration across all sites, although invoking CO 2 effects on vegetation (growth enhancement and increases in water use efficiency (WUE)) diminish this response. The model showed enhanced evapotranspiration resulted in drier growing season conditions across all sites and all scenarios in the future. Spruce-fir conifer forests have a lower optimum temperature for photosynthesis, making them more susceptible to temperature stress than more tolerant hardwood species, potentially giving hardwoods a competitive advantage in the future. However, some hardwood forests are projected to experience seasonal water stress, despite anticipated increases in precipitation, due to the higher temperatures, earlier loss of snow packs, longer growing seasons, and associated water deficits. Considering future CO 2 effects on WUE in the model alleviated water stress across all sites. Modeled streamflow responses were highly variable, with some sites showing significant increases in annual water yield, while others showed decreases. This variability in streamflow responses poses a challenge to water resource management in the northeastern United States. Our analyses suggest that dominant vegetation type and soil type are important attributes in determining future hydrological responses to climate change. © 2016 John Wiley & Sons Ltd.

Solar forcing of Gulf of California climate during the past 2000 yr suggested by diatoms and silicoflagellates

USGS Publications Warehouse

Barron, John A.; Bukry, David

2007-01-01

Cores BAM80 E-17 (27.9° N) and NH01-26 (24.3° N) contain longer-duration cycles of diatoms and silicoflagellates. The early part of Medieval Climate Anomaly (∼ A.D. 900 to 1200) is characterized by two periods of reduced productivity (warmer SST) with an intervening high productivity (cool) interval centered at ∼ A.D. 1050. Reduced productivity and higher SST also characterize the record of the last ∼ 100 to 200 yr in these cores. Solar variability appears to be driving productivity cycles, as intervals of increased radiocarbon production (sunspot minima) correlate with intervals of enhanced productivity. It is proposed that increased winter cooling of the atmosphere above southwest U.S. during sunspot minima causes intensification of the northwest winds that blow down the Gulf during the late fall to early spring, leading to intensified overturn of surface waters and enhanced productivity.

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.

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

PubMed

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

2018-03-30

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate Signal Detection in Wine Quality Using Gridded vs. Station Data in North-East Hungary

NASA Astrophysics Data System (ADS)

Mika, Janos; Razsi, Andras; Gal, Lajos

2017-04-01

The grapevine is one of the oldest cultivated plants. Today's viticultural regions for quality wine production are located in relatively narrow geographical and therefore climatic niches. Our target area, the Matra Region in NE Hungary is fairly close to the edge of optimal wine production concerning its climate conditions. Fifty year (1961-2010) wine and quality (natural sugar content, in weight % of must) data are analysed and compared to parallel climate variables. Two sets of station-based monthly temperature, sunshine duration and precipitation data, taken from neighbouring stations, Eger-Kőlyuktető (1961-2010) and Kompolt (1976-2006) are used in 132 combinations, together with daily grid-point data provided by the CarpatClim Project (www.carpatclim-eu.org/pages/home). By now it is clear that (1) wine quality, is in significant negative correlation with the annual precipitation and in positive correlation with temperature and sunshine duration. (2) Applying a wide combination of monthly data we obtain even stronger correlations (higher significance according to t-tests) even from the station-based data, but it is difficult to select and optimum model from the many proper combinations differing in performance over the test sample just slightly. (3) The interpolated site-specific areal averages from the grid-point data provide even better results and stronger differences between the best models and the few other candidates. (4) Further improvement of statistical signal detection capacity of the above climate variables by using 5-day averages, point at the strong vulnerability of wine quality on climate anomalies of some key phenological phases of the investigated grapevine-mixes. Enhanced spatial and temporal resolution provides much better fit to the observed wine quality data. The study has been supported by the OTKA-113209 national project.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Estimating the effects of potential climate and land use changes on hydrologic processes of a large agriculture dominated watershed

NASA Astrophysics Data System (ADS)

Neupane, Ram P.; Kumar, Sandeep

2015-10-01

Land use and climate are two major components that directly influence catchment hydrologic processes, and therefore better understanding of their effects is crucial for future land use planning and water resources management. We applied Soil and Water Assessment Tool (SWAT) to assess the effects of potential land use change and climate variability on hydrologic processes of large agriculture dominated Big Sioux River (BSR) watershed located in North Central region of USA. Future climate change scenarios were simulated using average output of temperature and precipitation data derived from Special Report on Emission Scenarios (SRES) (B1, A1B, and A2) for end-21st century. Land use change was modeled spatially based on historic long-term pattern of agricultural transformation in the basin, and included the expansion of corn (Zea mays L.) cultivation by 2, 5, and 10%. We estimated higher surface runoff in all land use scenarios with maximum increase of 4% while expanding 10% corn cultivation in the basin. Annual stream discharge was estimated higher with maximum increase of 72% in SRES-B1 attributed from higher groundwater contribution of 152% in the same scenario. We assessed increased precipitation during spring season but the summer precipitation decreased substantially in all climate change scenarios. Similar to decreased summer precipitation, discharge of the BSR also decreased potentially affecting agricultural production due to reduced future water availability during crop growing season in the basin. However, combined effects of potential land use change with climate variability enhanced for higher annual discharge of the BSR. Therefore, these estimations can be crucial for implications of future land use planning and water resources management of the basin.

Violence and Disorder, School Climate, and PBIS: The Relationship among School Climate, Student Outcomes, and the Use of Positive Behavioral Interventions and Supports

ERIC Educational Resources Information Center

Eacho, Thomas Christopher

2013-01-01

The primary purpose of this study was to examine the relationship between school climate and student outcome variables. The secondary purpose was to examine the relationship between the use of Positive Behavioral Interventions and Supports (PBIS) and the same student outcome variables. Variables depicting student perceptions of school climate,…

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2016-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

Effects of climatic factors and ecosystem responses on the inter-annual variability of evapotranspiration in a coniferous plantation in subtropical China.

PubMed

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003-2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003-2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May-June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation.

Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China

PubMed Central

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610

Climate variability modulates western US ozone air quality in spring via deep stratospheric intrusions

PubMed Central

Lin, Meiyun; Fiore, Arlene M.; Horowitz, Larry W.; Langford, Andrew O.; Oltmans, Samuel J.; Tarasick, David; Rieder, Harald E.

2015-01-01

Evidence suggests deep stratospheric intrusions can elevate western US surface ozone to unhealthy levels during spring. These intrusions can be classified as ‘exceptional events', which are not counted towards non-attainment determinations. Understanding the factors driving the year-to-year variability of these intrusions is thus relevant for effective implementation of the US ozone air quality standard. Here we use observations and model simulations to link these events to modes of climate variability. We show more frequent late spring stratospheric intrusions when the polar jet meanders towards the western United States, such as occurs following strong La Niña winters (Niño3.4<−1.0 °C). While El Niño leads to enhancements of upper tropospheric ozone, we find this influence does not reach surface air. Fewer and weaker intrusion events follow in the two springs after the 1991 volcanic eruption of Mt. Pinatubo. The linkage between La Niña and western US stratospheric intrusions can be exploited to provide a few months of lead time during which preparations could be made to deploy targeted measurements aimed at identifying these exceptional events. PMID:25964012

An energy balance model exploration of the impacts of interactions between surface albedo, cloud cover and water vapor on polar amplification

NASA Astrophysics Data System (ADS)

Södergren, A. Helena; McDonald, Adrian J.; Bodeker, Gregory E.

2017-11-01

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes.

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

PubMed

Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

2017-03-01

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans. © 2016 John Wiley & Sons Ltd.

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

USGS Publications Warehouse

Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

2017-01-01

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Projection of future runoff change using climate elasticity method derived from Budyko framework in major basins across China

NASA Astrophysics Data System (ADS)

Xing, Wanqiu; Wang, Weiguang; Zou, Shan; Deng, Chao

2018-03-01

This study established a climate elasticity method based on Budyko hypothesis and enhanced it by selecting the most effective Budyko-type formula to strengthen the runoff change prediction reliability. The spatiotemporal variations in hydrologic variables (i.e., runoff, precipitation and potential evaporation) during historical period were revealed first and the climate elasticities of runoff were investigated. The proposed climate elasticity method was also applied to project the spatiotemporal variations in future runoff and its key influencing factors in 35 watersheds across China. Wherein, the future climate series were retrieved by consulting the historical series, informed by four global climate models (GCMs) under representative concentration pathways from phase five of the Coupled Model Intercomparison Project. Wang-Tang equation was selected as the optimal Budyko-type equation for its best ability in reproducing the runoff change (with a coefficient of determination and mean absolute error of 0.998 and 1.36 mm, respectively). Observed runoff presents significant decreasing trends in the northern and increasing trends in the southern regions of China, and generally its change is identified to be more sensitive to climatic variables in Hai River Basin and lower Yellow River Basin. Compared to the runoff during the reference period, positive change rates in the north and negative change rates in the south of China in the mid-21st century can be practically generalized from the majority of GCMs projections. This maybe resulted from the increasing precipitation, especially in parts of northern basins. Meanwhile, GCMs project a consistently upward trend in potential evaporation although significant decreasing trends occur in the majority of catchments for the historical period. The results indicate that climate change will possibly bring some changes to the water resources over China in the mid-21st century and some countermeasures of water resources planning and management should be taken.

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.

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

Climate change enhances the mobilisation of naturally occurring metals in high altitude environments.

PubMed

Zaharescu, Dragos G; Hooda, Peter S; Burghelea, Carmen I; Polyakov, Viktor; Palanca-Soler, Antonio

2016-08-01

Manmade climate change has expressed a plethora of complex effects on Earth's biogeochemical compartments. Climate change may also affect the mobilisation of natural metal sources, with potential ecological consequences beyond mountains' geographical limits; however, this question has remained largely unexplored. We investigated this by analysing a number of key climatic factors in relationship with trace metal accumulation in the sediment core of a Pyrenean lake. The sediment metal contents showed increasing accumulation trend over time, and their levels varied in step with recent climate change. The findings further revealed that a rise in the elevation of freezing level, a general increase in the frequency of drier periods, changes in the frequency of winter freezing days and a reducing snow cover since the early 1980s, together are responsible for the observed variability and augmented accumulation of trace metals. Our results provide clear evidence of increased mobilisation of natural metal sources - an overlooked effect of climate change on the environment. With further alterations in climate equilibrium predicted over the ensuing decades, it is likely that mountain catchments in metamorphic areas may become significant sources of trace metals, with potentially harmful consequences for the wider environment. Copyright © 2016 Elsevier B.V. All rights reserved.

Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

NASA Astrophysics Data System (ADS)

Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

2016-02-01

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

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

Atmospheric teleconnections between the Arctic and the Baltic Sea regions

NASA Astrophysics Data System (ADS)

Jakobson, L.; Jakobson, E.

2017-12-01

The observed enhanced warming of the Arctic, referred to as the AA, is expected to be related to further changes that impact mid-latitudes and the rest of the world. Our aim is to clarify how the climatic parameters in the Baltic Sea and Arctic regions are associated. Knowledge of such connections helps to define regions in the Arctic that could be with higher extent associated with the Baltic Sea region climate change. We used monthly mean reanalysis data from NCEP-CFSR and ERA-Interim. The strongest teleconnections between the same parameter (temperature, SLP, specific humidity, wind speed) at the Baltic Sea region and the Arctic are found in winter, but they are clearly affected by the Arctic Oscillation (AO) index. After removal of the AO index variability, correlations in winter were everywhere below ±0.5, while in other seasons there remained regions with strong (|R|>0.5, p<0.002) correlations. Strong correlations are also present between different climate variables at the Baltic Sea region and different regions of the Arctic. Temperature from 1000 to 500 hPa level at the Baltic Sea region have a strong negative correlation with the Greenland sector (the region between 20 - 80W and 55 - 80N) during all seasons except summer. The positive temperature anomaly of mild winter at the Greenland sector shifts towards east during the next seasons, reaching to Scandinavia/Baltic Sea region in summer. The Greenland sector is the region which gives the most significant correlations with the climatic parameters (temperature, wind speed, specific humidity, SLP) of the Baltic Sea region. These relationships can be explained by the AO index variability only in winter. In other seasons there has to be other influencing factors. The results of this study are valuable for selecting regions in the Arctic that have statistically the largest effect on climate in the Baltic Sea region.

Climate variability in SE Europe since 1450 AD based on a varved sediment record from Etoliko Lagoon (Western Greece)

NASA Astrophysics Data System (ADS)

Koutsodendris, Andreas; Brauer, Achim; Reed, Jane M.; Plessen, Birgit; Friedrich, Oliver; Hennrich, Barbara; Zacharias, Ierotheos; Pross, Jörg

2017-03-01

To achieve deeper understanding of climate variability during the last millennium in SE Europe, we report new sedimentological and paleoecological data from Etoliko Lagoon, Western Greece. The record represents the southernmost annually laminated (i.e., varved) archive from the Balkan Peninsula spanning the Little Ice Age, allowing insights into critical time intervals of climate instability such as during the Maunder and Dalton solar minima. After developing a continuous, ca. 500-year-long varve chronology, high-resolution μ-XRF counts, stable-isotope data measured on ostracod shells, palynological (including pollen and dinoflagellate cysts), and diatom data are used to decipher the season-specific climate and ecosystem evolution at Etoliko Lagoon since 1450 AD. Our results show that the Etoliko varve record became more sensitive to climate change from 1740 AD onwards. We attribute this shift to the enhancement of primary productivity within the lagoon, which is documented by an up to threefold increase in varve thickness. This marked change in the lagoon's ecosystem was caused by: (i) increased terrestrial input of nutrients, (ii) a closer connection to the sea and human eutrophication particularly from 1850 AD onwards, and (iii) increasing summer temperatures. Integration of our data with those of previously published paleolake sediment records, tree-ring-based precipitation reconstructions, simulations of atmospheric circulation and instrumental precipitation data suggests that wet conditions in winter prevailed during 1740-1790 AD, whereas dry winters marked the periods 1790-1830 AD (Dalton Minimum) and 1830-1930 AD, the latter being sporadically interrupted by wet winters. This variability in precipitation can be explained by shifts in the large-scale atmospheric circulation patterns over the European continent that affected the Balkan Peninsula (e.g., North Atlantic Oscillation). The transition between dry and wet phases at Etoliko points to longitudinal shifts of the precipitation pattern in the Balkan Peninsula during the Little Ice Age.

Long-term dynamics of a floodplain shallow lake in the Pantanal wetland: Is it all about climate?

PubMed

Silio-Calzada, Ana; Barquín, José; Huszar, Vera L M; Mazzeo, Nestor; Méndez, Fernando; Álvarez-Martínez, Jose Manuel

2017-12-15

Hydrological variability over seasonal and multi-annual timescales strongly shapes the ecological structure and functioning of floodplain ecosystems. The current IPCC climate scenario foresees an increase in the frequency of extreme events. This, in conjunction with other anthropogenic disturbances (e.g., river regulation or land-use changes) poses a serious threat to the natural functioning of these ecosystems. In this study we aimed to i) evaluate the long-term variability of the flooded area of the third largest floodplain lake in the Brazilian Pantanal using remote sensing techniques, and ii) analyze the possible factors influencing this variability. Changes in open-water and riparian floodplain-wetland vegetation areas were mapped by applying an ad hoc-developed remote-sensing method (including a newly developed normalized water index, NWI) to 221 Landsat-Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images, acquired between 1984 and 2011. Added to the lake's natural swing between riparian floodplain-wetland vegetation expansion and retraction, our analyses revealed large interannual changes, grouped into three main periods within the studied time interval. Moreover, our results indicate that this floodplain-lake system is losing open-water area, paired with an increase in riparian floodplain-wetland vegetation. The system's long-term dynamics are not all climate related, but are the result of a combination of drivers. The start of the Manso dam's operation upstream of the studied system, and the subsequent river regulation because of the dam operation, coupled with climatic oscillation appear to be responsible for the observed changes. However, other factors which were not considered in this study might also be important in this process and contributing to the reduction of the system's resilience to droughts (e.g., land-use changes). This study illustrates the serious conservation risks that the Pantanal faces in the near future, given the current climate-change scenario and the accumulation of dam building projects in this region. Copyright © 2017 Elsevier B.V. All rights reserved.

Separating the Effects of Tropical Atlantic and Pacific SST-driven Climate Variability on Amazon Carbon Exchange

NASA Astrophysics Data System (ADS)

Liptak, J.; Keppel-Aleks, G.

2016-12-01

Amazon forests store an estimated 25% percent of global terrestrial carbon per year1, 2, but the responses of Amazon carbon uptake to climate change is highly uncertain. One source of this uncertainty is tropical sea surface temperature variability driven by teleconnections. El Nino-Southern Oscillation (ENSO) is a key driver of year-to-year Amazon carbon exchange, with associated temperature and precipitation changes favoring net carbon storage in La Nina years, and net carbon release during El Nino years3. To determine how Amazon climate and terrestrial carbon fluxes react to ENSO alone and in concert with other SST-driven teleconnections such as the Atlantic Multidecadal Oscillation (AMO), we force the atmosphere (CAM5) and land (CLM4) components of the CESM(BGC) with prescribed monthly SSTs over the period 1950—2014 in a Historical control simulation. We then run an experiment (PAC) with time-varying SSTs applied only to the tropical equatorial Pacific Ocean, and repeating SST seasonal cycle climatologies elsewhere. Limiting SST variability to the equatorial Pacific indicates that other processes enhance ENSO-driven Amazon climate anomalies. Compared to the Historical control simulation, warming, drying and terrestrial carbon loss over the Amazon during El Nino periods are lower in the PAC simulation, especially prior to 1990 during the cool phase of the AMO. Cooling, moistening, and net carbon uptake during La Nina periods are also reduced in the PAC simulation, but differences are greater after 1990 during the warm phase of the AMO. By quantifying the relationships among climate drivers and carbon fluxes in the Historical and PAC simulations, we both assess the sensitivity of these relationships to the magnitude of ENSO forcing and quantify how other teleconnections affect ENSO-driven Amazon climate feedbacks. We expect that these results will help us improve hypotheses for how Atlantic and Pacific climate trends will affect future Amazon carbon carbon cycling. Pan, Y. et al. A large and persistent carbon sink in the world's forests. Science 333, 988-993 (2011) Brienen, Roel J. W. et al. Long-term decline of the Amazon carbon sink. Nature 519, 344-348 (2015) Botta, A. et al. Long-term variations of climate and carbon fluxes over the Amazon basin. Geophys. Res. Lett. 29 (2002)

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.

Climate Change and Air Pollution: Effects on Respiratory Allergy

PubMed Central

Pawankar, Ruby; Vitale, Carolina; Lanza, Maurizia; Molino, Antonio; Stanziola, Anna; Sanduzzi, Alessandro; Vatrella, Alessandro; D'Amato, Maria

2016-01-01

A body of evidence suggests that major changes involving the atmosphere and the climate, including global warming induced by anthropogenic factors, have impact on the biosphere and human environment. Studies on the effects of climate change on respiratory allergy are still lacking and current knowledge is provided by epidemiological and experimental studies on the relationship between allergic respiratory diseases, asthma and environmental factors, such as meteorological variables, airborne allergens, and air pollution. Urbanization with its high levels of vehicle emissions, and a westernized lifestyle are linked to the rising frequency of respiratory allergic diseases and bronchial asthma observed over recent decades in most industrialized countries. However, it is not easy to evaluate the impact of climate changes and air pollution on the prevalence of asthma in the general population and on the timing of asthma exacerbations, although the global rise in asthma prevalence and severity could also be an effect of air pollution and climate change. Since airborne allergens and air pollutants are frequently increased contemporaneously in the atmosphere, an enhanced IgE-mediated response to aeroallergens and enhanced airway inflammation could account for the increasing frequency of respiratory allergy and asthma in atopic subjects in the last 5 decades. Pollen allergy is frequently used to study the relationship between air pollution and respiratory allergic diseases, such as rhinitis and bronchial asthma. Epidemiologic studies have demonstrated that urbanization, high levels of vehicle emissions, and westernized lifestyle are correlated with an increased frequency of respiratory allergy prevalently in people who live in urban areas in comparison with people living in rural areas. Climatic factors (temperature, wind speed, humidity, thunderstorms, etc.) can affect both components (biological and chemical) of this interaction. PMID:27334776

Variation characteristics and influences of climate factors on aridity index and its association with AO and ENSO in northern China from 1961 to 2012

NASA Astrophysics Data System (ADS)

Zhang, Kexin; Qian, Xiaoqing; Liu, Puxing; Xu, Yihong; Cao, Liguo; Hao, Yongpei; Dai, Shengpei

2017-10-01

Analyses of the variation characteristics for aridity index (AI) can further enhance the understanding of climate change and have effect on hydrology and agriculture. In this paper, based on the data of 283 standard meteorological stations, the temporal-spatial variations and the influences of climate factors on AI were investigated and the relationship between AI and two climate indices (the Arctic Oscillation (AO); El Nino-Southern Oscillation (ENSO)) were also assessed in northern China (NC) during the period from 1961 to 2012. The results revealed that the annual mean AI decreased at the rate of -0.031 per decade in the past 52 years and the trend was statistically significant at the 0.01 level. The Mann-Kendall (M-K) test presented that the percentages of stations with positive trends and negative trends for AI were 10 and 81.9 % (22.6 % statistically significant), respectively. Spatially, in the western part of 100° E, the extremely dry area declined and the climate tended to become wet obviously. In the eastern part of 100° E, dry area moved toward the east and the south, which resulted in the enhancement of semiarid area and the shrinkage of subhumid area. The contributions of sunshine duration and precipitation to the decline of AI are more than those of other meteorological variables in NC. Moreover, the average temperature has risen significantly and AI decreased in NC, which indicated the existence of "paradox." Relationship between climate indices (AO and ENSO) and AI demonstrated that the influence of ENSO on AI overweight the AO on AI in NC.

Public perceptions about climate change mitigation in British Columbia's forest sector

PubMed Central

Hagerman, Shannon; Kozak, Robert; Hoberg, George

2018-01-01

The role of forest management in mitigating climate change is a central concern for the Canadian province of British Columbia. The successful implementation of forest management activities to achieve climate change mitigation in British Columbia will be strongly influenced by public support or opposition. While we now have increasingly clear ideas of the management opportunities associated with forest mitigation and some insight into public support for climate change mitigation in the context of sustainable forest management, very little is known with respect to the levels and basis of public support for potential forest management strategies to mitigate climate change. This paper, by describing the results of a web-based survey, documents levels of public support for the implementation of eight forest carbon mitigation strategies in British Columbia’s forest sector, and examines and quantifies the influence of the factors that shape this support. Overall, respondents ascribed a high level of importance to forest carbon mitigation and supported all of the eight proposed strategies, indicating that the British Columbia public is inclined to consider alternative practices in managing forests and wood products to mitigate climate change. That said, we found differences in levels of support for the mitigation strategies. In general, we found greater levels of support for a rehabilitation strategy (e.g. reforestation of unproductive forest land), and to a lesser extent for conservation strategies (e.g. old growth conservation, reduced harvest) over enhanced forest management strategies (e.g. improved harvesting and silvicultural techniques). We also highlighted multiple variables within the British Columbia population that appear to play a role in predicting levels of support for conservation and/or enhanced forest management strategies, including environmental values, risk perception, trust in groups of actors, prioritized objectives of forest management and socio-demographic factors. PMID:29684041

Climate Change and Air Pollution: Effects on Respiratory Allergy.

PubMed

D'Amato, Gennaro; Pawankar, Ruby; Vitale, Carolina; Lanza, Maurizia; Molino, Antonio; Stanziola, Anna; Sanduzzi, Alessandro; Vatrella, Alessandro; D'Amato, Maria

2016-09-01

A body of evidence suggests that major changes involving the atmosphere and the climate, including global warming induced by anthropogenic factors, have impact on the biosphere and human environment. Studies on the effects of climate change on respiratory allergy are still lacking and current knowledge is provided by epidemiological and experimental studies on the relationship between allergic respiratory diseases, asthma and environmental factors, such as meteorological variables, airborne allergens, and air pollution. Urbanization with its high levels of vehicle emissions, and a westernized lifestyle are linked to the rising frequency of respiratory allergic diseases and bronchial asthma observed over recent decades in most industrialized countries. However, it is not easy to evaluate the impact of climate changes and air pollution on the prevalence of asthma in the general population and on the timing of asthma exacerbations, although the global rise in asthma prevalence and severity could also be an effect of air pollution and climate change. Since airborne allergens and air pollutants are frequently increased contemporaneously in the atmosphere, an enhanced IgE-mediated response to aeroallergens and enhanced airway inflammation could account for the increasing frequency of respiratory allergy and asthma in atopic subjects in the last 5 decades. Pollen allergy is frequently used to study the relationship between air pollution and respiratory allergic diseases, such as rhinitis and bronchial asthma. Epidemiologic studies have demonstrated that urbanization, high levels of vehicle emissions, and westernized lifestyle are correlated with an increased frequency of respiratory allergy prevalently in people who live in urban areas in comparison with people living in rural areas. Climatic factors (temperature, wind speed, humidity, thunderstorms, etc.) can affect both components (biological and chemical) of this interaction.

Public perceptions about climate change mitigation in British Columbia's forest sector.

PubMed

Peterson St-Laurent, Guillaume; Hagerman, Shannon; Kozak, Robert; Hoberg, George

2018-01-01

The role of forest management in mitigating climate change is a central concern for the Canadian province of British Columbia. The successful implementation of forest management activities to achieve climate change mitigation in British Columbia will be strongly influenced by public support or opposition. While we now have increasingly clear ideas of the management opportunities associated with forest mitigation and some insight into public support for climate change mitigation in the context of sustainable forest management, very little is known with respect to the levels and basis of public support for potential forest management strategies to mitigate climate change. This paper, by describing the results of a web-based survey, documents levels of public support for the implementation of eight forest carbon mitigation strategies in British Columbia's forest sector, and examines and quantifies the influence of the factors that shape this support. Overall, respondents ascribed a high level of importance to forest carbon mitigation and supported all of the eight proposed strategies, indicating that the British Columbia public is inclined to consider alternative practices in managing forests and wood products to mitigate climate change. That said, we found differences in levels of support for the mitigation strategies. In general, we found greater levels of support for a rehabilitation strategy (e.g. reforestation of unproductive forest land), and to a lesser extent for conservation strategies (e.g. old growth conservation, reduced harvest) over enhanced forest management strategies (e.g. improved harvesting and silvicultural techniques). We also highlighted multiple variables within the British Columbia population that appear to play a role in predicting levels of support for conservation and/or enhanced forest management strategies, including environmental values, risk perception, trust in groups of actors, prioritized objectives of forest management and socio-demographic factors.

Functional adjustments of xylem anatomy to climatic variability: insights from long-term Ilex aquifolium tree-ring series.

PubMed

Rita, Angelo; Cherubini, Paolo; Leonardi, Stefano; Todaro, Luigi; Borghetti, Marco

2015-08-01

The present study assessed the effects of climatic conditions on radial growth and functional anatomical traits, including ring width, vessel size, vessel frequency and derived variables, i.e., potential hydraulic conductivity and xylem vulnerability to cavitation in Ilex aquifolium L. trees using long-term tree-ring time series obtained at two climatically contrasting sites, one mesic site in Switzerland (CH) and one drought-prone site in Italy (ITA). Relationships were explored by examining different xylem traits, and point pattern analysis was applied to investigate vessel clustering. We also used generalized additive models and bootstrap correlation functions to describe temperature and precipitation effects. Results indicated modified radial growth and xylem anatomy in trees over the last century; in particular, vessel frequency increased markedly at both sites in recent years, and all xylem traits examined, with the exception of xylem cavitation vulnerability, were higher at the CH mesic compared with the ITA drought site. A significant vessel clustering was observed at the ITA site, which could contribute to an enhanced tolerance to drought-induced embolism. Flat and negative relationships between vessel size and ring width were observed, suggesting carbon was not allocated to radial growth under conditions which favored stem water conduction. Finally, in most cases results indicated that climatic conditions influenced functional anatomical traits more substantially than tree radial growth, suggesting a crucial role of functional xylem anatomy in plant acclimation to future climatic conditions. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

Global synthesis of groundwater recharge in semiarid and arid regions

NASA Astrophysics Data System (ADS)

Scanlon, Bridget R.; Keese, Kelley E.; Flint, Alan L.; Flint, Lorraine E.; Gaye, Cheikh B.; Edmunds, W. Michael; Simmers, Ian

2006-10-01

Global synthesis of the findings from 140 recharge study areas in semiarid and arid regions provides important information on recharge rates, controls, and processes, which are critical for sustainable water development. Water resource evaluation, dryland salinity assessment (Australia), and radioactive waste disposal (US) are among the primary goals of many of these recharge studies. The chloride mass balance (CMB) technique is widely used to estimate recharge. Average recharge rates estimated over large areas (40-374 000 km2) range from 0.2 to 35 mm year-1, representing 0.1-5% of long-term average annual precipitation. Extreme local variability in recharge, with rates up to 720 m year-1, results from focussed recharge beneath ephemeral streams and lakes and preferential flow mostly in fractured systems. System response to climate variability and land use/land cover (LU/LC) changes is archived in unsaturated zone tracer profiles and in groundwater level fluctuations. Inter-annual climate variability related to El Niño Southern Oscillation (ENSO) results in up to three times higher recharge in regions within the SW US during periods of frequent El Niños (1977-1998) relative to periods dominated by La Niñas (1941-1957). Enhanced recharge related to ENSO is also documented in Argentina. Climate variability at decadal to century scales recorded in chloride profiles in Africa results in recharge rates of 30 mm year-1 during the Sahel drought (1970-1986) to 150 mm year-1 during non-drought periods. Variations in climate at millennial scales in the SW US changed systems from recharge during the Pleistocene glacial period (10 000 years ago) to discharge during the Holocene semiarid period. LU/LC changes such as deforestation in Australia increased recharge up to about 2 orders of magnitude. Changes from natural grassland and shrublands to dryland (rain-fed) agriculture altered systems from discharge (evapotranspiration, ET) to recharge in the SW US. The impact of LU change was much greater than climate variability in Niger (Africa), where replacement of savanna by crops increased recharge by about an order of magnitude even during severe droughts. Sensitivity of recharge to LU/LC changes suggests that recharge may be controlled through management of LU. In irrigated areas, recharge varies from 10 to 485 mm year-1, representing 1-25% of irrigation plus precipitation. However, irrigation pumpage in groundwater-fed irrigated areas greatly exceeds recharge rates, resulting in groundwater mining. Increased recharge related to cultivation has mobilized salts that accumulated in the unsaturated zone over millennia, resulting in widespread groundwater and surface water contamination, particularly in Australia. The synthesis of recharge rates provided in this study contains valuable information for developing sustainable groundwater resource programmes within the context of climate variability and LU/LC change.

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

Arctic sea ice area in CMIP3 and CMIP5 climate model ensembles - variability and change

NASA Astrophysics Data System (ADS)

Semenov, V. A.; Martin, T.; Behrens, L. K.; Latif, M.

2015-02-01

The shrinking Arctic sea ice cover observed during the last decades is probably the clearest manifestation of ongoing climate change. While climate models in general reproduce the sea ice retreat in the Arctic during the 20th century and simulate further sea ice area loss during the 21st century in response to anthropogenic forcing, the models suffer from large biases and the model results exhibit considerable spread. The last generation of climate models from World Climate Research Programme Coupled Model Intercomparison Project Phase 5 (CMIP5), when compared to the previous CMIP3 model ensemble and considering the whole Arctic, were found to be more consistent with the observed changes in sea ice extent during the recent decades. Some CMIP5 models project strongly accelerated (non-linear) sea ice loss during the first half of the 21st century. Here, complementary to previous studies, we compare results from CMIP3 and CMIP5 with respect to regional Arctic sea ice change. We focus on September and March sea ice. Sea ice area (SIA) variability, sea ice concentration (SIC) variability, and characteristics of the SIA seasonal cycle and interannual variability have been analysed for the whole Arctic, termed Entire Arctic, Central Arctic and Barents Sea. Further, the sensitivity of SIA changes to changes in Northern Hemisphere (NH) averaged temperature is investigated and several important dynamical links between SIA and natural climate variability involving the Atlantic Meridional Overturning Circulation (AMOC), North Atlantic Oscillation (NAO) and sea level pressure gradient (SLPG) in the western Barents Sea opening serving as an index of oceanic inflow to the Barents Sea are studied. The CMIP3 and CMIP5 models not only simulate a coherent decline of the Arctic SIA but also depict consistent changes in the SIA seasonal cycle and in the aforementioned dynamical links. The spatial patterns of SIC variability improve in the CMIP5 ensemble, particularly in summer. Both CMIP ensembles depict a significant link between the SIA and NH temperature changes. Our analysis suggests that, on average, the sensitivity of SIA to external forcing is enhanced in the CMIP5 models. The Arctic SIA variability response to anthropogenic forcing is different in CMIP3 and CMIP5. While the CMIP3 models simulate increased variability in March and September, the CMIP5 ensemble shows the opposite tendency. A noticeable improvement in the simulation of summer SIA by the CMIP5 models is often accompanied by worse results for winter SIA characteristics. The relation between SIA and mean AMOC changes is opposite in September and March, with March SIA changes being positively correlated with AMOC slowing. Finally, both CMIP ensembles demonstrate an ability to capture, at least qualitatively, important dynamical links of SIA to decadal variability of the AMOC, NAO and SLPG. SIA in the Barents Sea is strongly overestimated by the majority of the CMIP3 and CMIP5 models, and projected SIA changes are characterized by a large spread giving rise to high uncertainty.

Advances in desertification and climate change research: Are they accessible for application to enhance adaptive capacity?

NASA Astrophysics Data System (ADS)

Seely, M.; Dirkx, E.; Hager, C.; Klintenberg, P.; Roberts, C.; von Oertzen, D.

2008-12-01

Sustainable living in arid lands is the goal of many, including local residents, policy-makers and scientists. Research into desertification and climate change has the potential to significantly enhance livelihoods of resident people. It also has the potential to contribute to their capacity for risk reduction, improved natural resources management and adaptation to climatic and other changes in multi-stressor systems. This potential is not frequently realised. To effectively ensure that scientific insights and contemporary technologies are applied, active involvement of and feedback from those who apply and use the benefits offered by science and technology are required. Scientists and technologists have to address the diverse, mainly non-technical, aspects required to understand and cope with endemic climate variability, desertification and climate change. They need to appropriately tailor their approaches to disseminate results, and communicate their findings in a way that can be understood and readily implemented by policy-makers, politicians and communities. At the same time, they must learn from experiences gained through implementation by users at all levels. The challenges of making the necessary connections between the combinatory effects of desertification and climate change and their effective application are explored and tested. It was found that several key factors contribute to making the necessary connections to facilitate application on all levels of research advances. These include translation, information dissemination, communication, communication platforms, boundary organisations and leadership contributing to knowledge, motivation and capacity. The purpose of this paper is to assess research experiences from integrated land and water resource management, the application of renewable energy and energy efficiency, and local-level monitoring of natural resources and their application to the challenges of desertification and climate change. The conclusion of this assessment is the identification and description of a common framework that can be applied to address the challenges of desertification and climate change.

Seasonal predictions of equatorial Atlantic SST in a low-resolution CGCM with surface heat flux correction

NASA Astrophysics Data System (ADS)

Dippe, Tina; Greatbatch, Richard; Ding, Hui

2016-04-01

The dominant mode of interannual variability in tropical Atlantic sea surface temperatures (SSTs) is the Atlantic Niño or Zonal Mode. Akin to the El Niño-Southern Oscillation in the Pacific sector, it is able to impact the climate both of the adjacent equatorial African continent and remote regions. Due to heavy biases in the mean state climate of the equatorial-to-subtropical Atlantic, however, most state-of-the-art coupled global climate models (CGCMs) are unable to realistically simulate equatorial Atlantic variability. In this study, the Kiel Climate Model (KCM) is used to investigate the impact of a simple bias alleviation technique on the predictability of equatorial Atlantic SSTs. Two sets of seasonal forecasting experiments are performed: An experiment using the standard KCM (STD), and an experiment with additional surface heat flux correction (FLX) that efficiently removes the SST bias from simulations. Initial conditions for both experiments are generated by the KCM run in partially coupled mode, a simple assimilation technique that forces the KCM with observed wind stress anomalies and preserves SST as a fully prognostic variable. Seasonal predictions for both sets of experiments are run four times yearly for 1981-2012. Results: Heat flux correction substantially improves the simulated variability in the initialization runs for boreal summer and fall (June-October). In boreal spring (March-May), however, neither the initialization runs of the STD or FLX-experiments are able to capture the observed variability. FLX-predictions show no consistent enhancement of skill relative to the predictions of the STD experiment over the course of the year. The skill of persistence forecasts is hardly beat by either of the two experiments in any season, limiting the usefulness of the few forecasts that show significant skill. However, FLX-forecasts initialized in May recover skill in July and August, the peak season of the Atlantic Niño (anomaly correlation coefficients of about 0.3). Further study is necessary to determine the mechanism that drives this potentially useful recovery.

A south equatorial African precipitation dipole and the associated atmospheric circulation

NASA Astrophysics Data System (ADS)

Dezfuli, A. K.; Zaitchik, B.; Gnanadesikan, A.

2013-12-01

South Equatorial Africa (SEA) is a climatically diverse region that includes a dramatic topographic and vegetation contrast between the lowland, humid Congo basin to the west and the East African Plateau to the east. Due to lack of conventional weather data and a tendency for researchers to treat East and western Africa as separate regions, dynamics of the atmospheric water cycle across SEA have received relatively little attention, particularly at subseasonal timescales. Both western and eastern sectors of SEA are affected by large-scale drivers of the water cycle associated with Atlantic variability (western sector), Indian Ocean variability (eastern sector) and Pacific variability (both sectors). However, a specific characteristic of SEA is strong heterogeneity in interannual rainfall variability that cannot be explained by large-scale climatic phenomena. For this reason, this study examines regional climate dynamics on daily time-scale with a focus on the role that the abrupt topographic contrast between the lowland Congo and the East African highlands plays in driving rainfall behavior on short timescales. Analysis of daily precipitation data during November-March reveals a zonally-oriented dipole mode over SEA that explains the leading pattern of weather-scale precipitation variability in the region. The separating longitude of the two poles is coincident with the zonal variation of topography. An anomalous counter-clockwise atmospheric circulation associated with the dipole mode appears over the entire SEA. The circulation is triggered by its low-level westerly component, which is in turn generated by an interhemispheric pressure gradient. These enhanced westerlies hit the East African highlands and produce topographically-driven low-level convergence and convection that further intensifies the circulation. Recent studies have shown that under climate change the position and intensity of subtropical highs in both hemispheres and the intensity of precipitation over equatorial Africa are projected to change. Both of these trends have implications for the manner in which large-scale dynamics will interact with regional topography, affecting the intensity and frequency of the dipole mode characterized in this study and the occurrence of extreme wet and dry spells in the region.

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

Enhancing Famine Early Warning Systems with Improved Forecasts, Satellite Observations and Hydrologic Simulations

NASA Astrophysics Data System (ADS)

Funk, C. C.; Verdin, J.; Thiaw, W. M.; Hoell, A.; Korecha, D.; McNally, A.; Shukla, S.; Arsenault, K. R.; Magadzire, T.; Novella, N.; Peters-Lidard, C. D.; Robjohn, M.; Pomposi, C.; Galu, G.; Rowland, J.; Budde, M. E.; Landsfeld, M. F.; Harrison, L.; Davenport, F.; Husak, G. J.; Endalkachew, E.

2017-12-01

Drought early warning science, in support of famine prevention, is a rapidly advancing field that is helping to save lives and livelihoods. In 2015-2017, a series of extreme droughts afflicted Ethiopia, Southern Africa, Eastern Africa in OND and Eastern Africa in MAM, pushing more than 50 million people into severe food insecurity. Improved drought forecasts and monitoring tools, however, helped motivate and target large and effective humanitarian responses. Here we describe new science being developed by a long-established early warning system - the USAID Famine Early Warning Systems Network (FEWS NET). FEWS NET is a leading provider of early warning and analysis on food insecurity. FEWS NET research is advancing rapidly on several fronts, providing better climate forecasts and more effective drought monitoring tools that are being used to support enhanced famine early warning. We explore the philosophy and science underlying these successes, suggesting that a modal view of climate change can support enhanced seasonal prediction. Under this modal perspective, warming of the tropical oceans may interact with natural modes of variability, like the El Niño-Southern Oscillation, to enhance Indo-Pacific sea surface temperature gradients during both El Niño and La Niña-like climate states. Using empirical data and climate change simulations, we suggest that a sequence of droughts may commence in northern Ethiopia and Southern Africa with the advent of a moderate-to-strong El Niño, and then continue with La Niña/West Pacific related droughts in equatorial eastern East Africa. Scientifically, we show that a new hybrid statistical-dynamic precipitation forecast system, the FEWS NET Integrated Forecast System (FIFS), based on reformulations of the Global Ensemble Forecast System weather forecasts and National Multi-Model Ensemble (NMME) seasonal climate predictions, can effectively anticipate recent East and Southern African drought events. Using cross-validation, we evaluate FIFS' skill and compare it to the NMME and the International Research Institute forecasts. Our study concludes with an overview of the satellite observations provided by FEWS NET partners at NOAA, NASA, USGS, and UC Santa Barbara, and the assimilation of these products within the FEWS NET Land Data Assimilation System (FLDAS).

Increased nitrogen export from eastern North America to the Atlantic Ocean due to climatic and anthropogenic changes during 1901-2008

NASA Astrophysics Data System (ADS)

Yang, Qichun; Tian, Hanqin; Friedrichs, Marjorie A. M.; Hopkinson, Charles S.; Lu, Chaoqun; Najjar, Raymond G.

2015-06-01

We used a process-based land model, Dynamic Land Ecosystem Model 2.0, to examine how climatic and anthropogenic changes affected riverine fluxes of ammonium (NH4+), nitrate (NO3-), dissolved organic nitrogen (DON), and particulate organic nitrogen (PON) from eastern North America, especially the drainage areas of the Gulf of Maine (GOM), Mid-Atlantic Bight (MAB), and South Atlantic Bight (SAB) during 1901-2008. Model simulations indicated that annual fluxes of NH4+, NO3-, DON, and PON from the study area during 1980-2008 were 0.019 ± 0.003 (mean ± 1 standard deviation) Tg N yr-1, 0.18 ± 0.035 Tg N yr-1, 0.10 ± 0.016 Tg N yr-1, and 0.043 ± 0.008 Tg N yr-1, respectively. NH4+, NO3-, and DON exports increased while PON export decreased from 1901 to 2008. Nitrogen export demonstrated substantial spatial variability across the study area. Increased NH4+ export mainly occurred around major cities in the MAB. NO3- export increased in most parts of the MAB but decreased in parts of the GOM. Enhanced DON export was mainly distributed in the GOM and the SAB. PON export increased in coastal areas of the SAB and northern parts of the GOM but decreased in the Piedmont areas and the eastern parts of the MAB. Climate was the primary reason for interannual variability in nitrogen export; fertilizer use and nitrogen deposition tended to enhance the export of all nitrogen species; livestock farming and sewage discharge were also responsible for the increases in NH4+ and NO3- fluxes; and land cover change (especially reforestation of former agricultural land) reduced the export of the four nitrogen species.

Atlantic Meridional Overturning Circulation Influence on North Atlantic Sector Surface Air Temperature and its Predictability in the Kiel Climate Model

NASA Astrophysics Data System (ADS)

Latif, M.

2017-12-01

We investigate the influence of the Atlantic Meridional Overturning Circulation (AMOC) on the North Atlantic sector surface air temperature (SAT) in two multi-millennial control integrations of the Kiel Climate Model (KCM). One model version employs a freshwater flux correction over the North Atlantic, while the other does not. A clear influence of the AMOC on North Atlantic sector SAT only is simulated in the corrected model that depicts much reduced upper ocean salinity and temperature biases in comparison to the uncorrected model. Further, the model with much reduced biases depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector relative to the uncorrected model. The enhanced SAT predictability in the corrected model is due to a stronger and more variable AMOC and its enhanced influence on North Atlantic sea surface temperature (SST). Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SST and exhibit a smaller SAT predictability over the North Atlantic sector.

High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

NASA Astrophysics Data System (ADS)

Haarsma, Reindert J.; Roberts, Malcolm J.; Vidale, Pier Luigi; Senior, Catherine A.; Bellucci, Alessio; Bao, Qing; Chang, Ping; Corti, Susanna; Fučkar, Neven S.; Guemas, Virginie; von Hardenberg, Jost; Hazeleger, Wilco; Kodama, Chihiro; Koenigk, Torben; Leung, L. Ruby; Lu, Jian; Luo, Jing-Jia; Mao, Jiafu; Mizielinski, Matthew S.; Mizuta, Ryo; Nobre, Paulo; Satoh, Masaki; Scoccimarro, Enrico; Semmler, Tido; Small, Justin; von Storch, Jin-Song

2016-11-01

Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, "what are the origins and consequences of systematic model biases?", but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

Downscaling climate information for local disease mapping.

PubMed

Bernardi, M; Gommes, R; Grieser, J

2006-06-01

The study of the impacts of climate on human health requires the interdisciplinary efforts of health professionals, climatologists, biologists, and social scientists to analyze the relationships among physical, biological, ecological, and social systems. As the disease dynamics respond to variations in regional and local climate, climate variability affects every region of the world and the diseases are not necessarily limited to specific regions, so that vectors may become endemic in other regions. Climate data at local level are thus essential to evaluate the dynamics of vector-borne disease through health-climate models and most of the times the climatological databases are not adequate. Climate data at high spatial resolution can be derived by statistical downscaling using historical observations but the method is limited by the availability of historical data at local level. Since the 90s', the statistical interpolation of climate data has been an important priority of the Agrometeorology Group of the Food and Agriculture Organization of the United Nations (FAO), as they are required for agricultural planning and operational activities at the local level. Since 1995, date of the first FAO spatial interpolation software for climate data, more advanced applications have been developed such as SEDI (Satellite Enhanced Data Interpolation) for the downscaling of climate data, LOCCLIM (Local Climate Estimator) and the NEW_LOCCLIM in collaboration with the Deutscher Wetterdienst (German Weather Service) to estimate climatic conditions at locations for which no observations are available. In parallel, an important effort has been made to improve the FAO climate database including at present more than 30,000 stations worldwide and expanding the database from developing countries coverage to global coverage.

An interdecadal climate dipole between Northeast Asia and Antarctica over the past five centuries

NASA Astrophysics Data System (ADS)

Fang, Keyan; Chen, Deliang; Guo, Zhengtang; Zhao, Yan; Frank, David; He, Maosheng; Zhou, Feifei; Shi, Feng; Seppä, Heikki; Zhang, Peng; Neukom, Raphael

2018-03-01

Climate models emphasize the need to investigate inter-hemispheric climatic interactions. However, these models often underestimate the inter-hemispheric differences in climate change. With the wide application of reanalysis data since 1948, we identified a dipole pattern between the geopotential heights (GPHs) in Northeast Asia and Antarctica on the interdecadal scale in boreal summer. This Northeast Asia/Antarctica (NAA) dipole pattern is not conspicuous on the interannual scale, probably in that the interannual inter-hemispheric climate interaction is masked by strong interannual signals in the tropics associated with the El Niño-Southern Oscillation (ENSO). Unfortunately, the instrumental records are not sufficiently long-lasting to detect the interdecadal variability of the NAA. We thus reconstructed GPHs since 1565, making using the proxy records mostly from tree rings in Northeast Asia and ice cores from Antarctica. The strength of the NAA is time-varying and it is most conspicuous in the eighteenth century and after the late twentieth century. The strength of the NAA matches well with the variations of the solar radiation and tends to increase in along with its enhancement. In boreal summer, enhanced heating associated with high solar radiation in the Northern Hemisphere drives more air masses from the South to the North. This inter-hemispheric interaction is particularly strong in East Asia as a result of the Asian summer monsoon. Northeast Asia and Antarctica appear to be the key regions responsible for inter-hemispheric interactions on the interdecadal scale in boreal summer since they are respectively located at the front and the end of this inter-hemispheric trajectory.

Assessing cover crop management under actual and climate change conditions.

PubMed

Alonso-Ayuso, María; Quemada, Miguel; Vanclooster, Marnik; Ruiz-Ramos, Margarita; Rodriguez, Alfredo; Gabriel, José Luis

2018-04-15

The termination date is recognized as a key management factor to enhance cover crops for multiple benefits and to avoid competition with the following cash crop. However, the optimum date depends on annual meteorological conditions, and climate variability induces uncertainty in a decision that needs to be taken every year. One of the most important cover crop benefits is reducing nitrate leaching, a major concern for irrigated agricultural systems and highly affected by the termination date. This study aimed to determine the effects of cover crops and their termination date on the water and N balances of an irrigated Mediterranean agroecosystem under present and future climate conditions. For that purpose, two field experiments were used for inverse calibration and validation of the WAVE model (Water and Agrochemicals in the soil and Vadose Environment), based on continuous soil water content data, soil nitrogen content and crop measurements. The calibrated and validated model was subsequently used in advanced scenario analysis under present and climate change conditions. Under present conditions, a late termination date increased cover crop biomass and subsequently soil water and N depletion. Hence, preemptive competition risk with the main crop was enhanced, but a reduction of nitrate leaching also occurred. The hypothetical planting date of the following cash crop was also an important tool to reduce preemptive competition. Under climate change conditions, the simulations showed that the termination date will be even more important to reduce preemptive competition and nitrate leaching. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

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.

Beyond Climate Scenarios: Advancing from Changes in the Mean to a Better Understanding of Physical Processes to Enhance Stakeholder Engagement

NASA Astrophysics Data System (ADS)

Yates, D. N.; Kaatz, L.; Ammann, C. M.

2017-12-01

Great strides have been made within the climate sciences community to make Global Climate Model (GCM) output and their results as meaningful as possible to the broad community of stakeholders that might benefit from this information. Regardless of these good intentions, the fact remains that most data from GCMs are viewed as being highly uncertain and thus not actionable for water resources planning. The most common use of GCM data is informing projected future climate by use of a mean change, primarily for temperature, given the generally greater confidence in this variable. In contrast, precipitation is viewed as highly uncertain, primarily because it has not validated well against observed precipitation climatologies at local and regional levels. Simple perturbations to historical mean temperature and precipitation sequences are not as complex as using direct GCM outputs and have fewer analytical requirements. Mean climate change information can still give valuable information to water managers, providing meaningful insights and sign posts into future vulnerabilities and is an approach that is arguably deemed more actionable. These temperature and precipitation sign posts can be monitored and used as indicators when certain actions become necessary and/or until there are improvements in actionable climate science information. Recent advances in regional climate modeling (RCM), particularly those run at very high resolution and are cloud resolving, show promise in advancing our understanding of the interaction among climate variables at the regional level. Thus, in addition to exploring how changes in the mean climate (e.g. 2oC warming) might impact a water system, this bottom-up approach makes use of carefully constructed regional climate experiments that are conducted, for example, under conditions of a warmer atmosphere that can hold more moisture. One can then explore what happens to, for example, rain-snow partitioning at various elevations across a snow dominated basin, what happens to coastal rainfall intensities when ocean temperatures are warmer in the early spring, or how might the daily temperature differential (tmin/max) change?

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.

Process connectivity reveals ecohydrologic sensitivity to drought and rainfall pulses

NASA Astrophysics Data System (ADS)

Goodwell, A. E.; Kumar, P.

2017-12-01

Ecohydrologic fluxes within atmosphere, canopy and soil systems exhibit complex and joint variability. This complexity arises from direct and indirect forcing and feedback interactions that can cause fluctuations to propagate between water, energy, and nutrient fluxes at various time scales. When an ecosystem is perturbed in the form of a single storm event, an accumulating drought, or changes in climate and land cover, this aspect of joint variability may dictate responsiveness and resilience of the entire system. A characterization of the time-dependent and multivariate connectivity between processes, fluxes, and states is necessary to identify and understand these aspects of ecohydrologic systems. We construct Temporal Information Partitioning Networks (TIPNets), based on information theory measures, to identify time-dependencies between variables measured at flux towers along elevation and climate gradients in relation to their responses to moisture-related perturbations. Along a flux tower transect in the Reynolds Creek Critical Zone Observatory (CZO) in Idaho, we detect a significant network response to a large 2015 dry season rainfall event that enhances microbial respiration and latent heat fluxes. At a transect in the Southern Sierra CZO in California, we explore network properties in relation to drought responses from 2011 to 2015. We find that both high and low elevation sites exhibit decreased connectivity between atmospheric and soil variables and latent heat fluxes, but the higher elevation site is less sensitive to this altered connectivity in terms of average monthly heat fluxes. Through a novel approach to gage the responsiveness of ecosystem fluxes to shifts in connectivity, this study aids our understanding of ecohydrologic sensitivity to short-term rainfall events and longer term droughts. This study is relevant to ecosystem resilience under a changing climate, and can lead to a greater understanding of shifting behaviors in many types of complex systems.

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...

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.

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.

Assessing climate adaptation options and uncertainties for cereal systems in West Africa

NASA Astrophysics Data System (ADS)

Guan, K.; Sultan, B.; Biasutti, M.; Lobell, D. B.

2015-12-01

The already fragile agriculture production system in West Africa faces further challenges in meeting food security in the coming decades, primarily due to a fast increasing population and risks of climate change. Successful adaptation of agriculture should not only benefit in the current climate but should also reduce negative (or enhance positive) impacts for climate change. Assessment of various possible adaptation options and their uncertainties provides key information for prioritizing adaptation investments. Here, based on the several robust aspects of climate projections in this region (i.e. temperature increases and rainfall pattern shifts), we use two well-validated crop models (i.e. APSIM and SARRA-H) and an ensemble of downscaled climate forcing to assess five possible and realistic adaptation options (late sowing, intensification, thermal time increase, water harvesting and increased resilience to heat stress) in West Africa for the staple crop production of sorghum. We adopt a new assessment framework to account for both the impacts of adaptation options in current climate and their ability to reduce impacts of future climate change, and also consider changes in both mean yield and its variability. Our results reveal that most proposed "adaptation options" are not more beneficial in the future than in the current climate, i.e. not really reduce the climate change impacts. Increased temperature resilience during grain number formation period is the main adaptation that emerges. We also find that changing from the traditional to modern cultivar, and later sowing in West Sahel appear to be robust adaptations.

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.

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.

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.

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.

Processes Understanding of Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Prömmel, Kerstin; Cubasch, Ulrich

2016-04-01

The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program "MiKlip II - Decadal Climate Predictions" (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.

Retrievals of aerosol optical depth and Angström exponent from ground-based Sun-photometer data of Singapore.

PubMed

Salinas, Santo V; Chew, Boon N; Liew, Soo C

2009-03-10

The role of aerosols in climate and climate change is one of the factors that is least understood at the present. Aerosols' direct interaction with solar radiation is a well understood mechanism that affects Earth's net radiative forcing. However, quantifying its magnitude is more problematic because of the temporal and spatial variability of aerosol particles. To enhance our understanding of the radiative effects of aerosols on the global climate, Singapore has joined the AERONET (Aerosol Robotic Network) worldwide network by contributing ground-based direct Sun measurements performed by means of a multiwavelength Sun-photometer instrument. Data are collected on an hourly basis, then are uploaded to be fully screened and quality assured by AERONET. We use a one year data record (level 1.5/2.0) of measured columnar atmospheric optical depth, spanning from November 2006 to October 2007, to study the monthly and seasonal variability of the aerosol optical depth and the Angström exponent. We performed independent retrievals of these parameters (aerosol optical depth and Angström exponent) by using the photometer's six available bands covering the near-UV to near-IR (380-1080 nm). As a validation, our independent retrievals were compared with AERONET 1.5/2.0 level direct Sun product.

Biodiversity enhances reef fish biomass and resistance to climate change.

PubMed

Duffy, J Emmett; Lefcheck, Jonathan S; Stuart-Smith, Rick D; Navarrete, Sergio A; Edgar, Graham J

2016-05-31

Fishes are the most diverse group of vertebrates, play key functional roles in aquatic ecosystems, and provide protein for a billion people, especially in the developing world. Those functions are compromised by mounting pressures on marine biodiversity and ecosystems. Because of its economic and food value, fish biomass production provides an unusually direct link from biodiversity to critical ecosystem services. We used the Reef Life Survey's global database of 4,556 standardized fish surveys to test the importance of biodiversity to fish production relative to 25 environmental drivers. Temperature, biodiversity, and human influence together explained 47% of the global variation in reef fish biomass among sites. Fish species richness and functional diversity were among the strongest predictors of fish biomass, particularly for the large-bodied species and carnivores preferred by fishers, and these biodiversity effects were robust to potentially confounding influences of sample abundance, scale, and environmental correlations. Warmer temperatures increased biomass directly, presumably by raising metabolism, and indirectly by increasing diversity, whereas temperature variability reduced biomass. Importantly, diversity and climate interact, with biomass of diverse communities less affected by rising and variable temperatures than species-poor communities. Biodiversity thus buffers global fish biomass from climate change, and conservation of marine biodiversity can stabilize fish production in a changing ocean.

Mitigating Harmful Cyanobacterial Blooms in a Human- and Climatically-Impacted World

PubMed Central

Paerl, Hans W.

2014-01-01

Bloom-forming harmful cyanobacteria (CyanoHABs) are harmful from environmental, ecological and human health perspectives by outcompeting beneficial phytoplankton, creating low oxygen conditions (hypoxia, anoxia), and by producing cyanotoxins. Cyanobacterial genera exhibit optimal growth rates and bloom potentials at relatively high water temperatures; hence, global warming plays a key role in their expansion and persistence. CyanoHABs are regulated by synergistic effects of nutrient (nitrogen:N and phosphorus:P) supplies, light, temperature, vertical stratification, water residence times, and biotic interactions. In most instances, nutrient control strategies should focus on reducing both N and P inputs. Strategies based on physical, chemical (nutrient) and biological manipulations can be effective in reducing CyanoHABs; however, these strategies are largely confined to relatively small systems, and some are prone to ecological and environmental drawbacks, including enhancing release of cyanotoxins, disruption of planktonic and benthic communities and fisheries habitat. All strategies should consider and be adaptive to climatic variability and change in order to be effective for long-term control of CyanoHABs. Rising temperatures and greater hydrologic variability will increase growth rates and alter critical nutrient thresholds for CyanoHAB development; thus, nutrient reductions for bloom control may need to be more aggressively pursued in response to climatic changes globally. PMID:25517134

Biodiversity enhances reef fish biomass and resistance to climate change

PubMed Central

Duffy, J. Emmett; Lefcheck, Jonathan S.; Navarrete, Sergio A.; Edgar, Graham J.

2016-01-01

Fishes are the most diverse group of vertebrates, play key functional roles in aquatic ecosystems, and provide protein for a billion people, especially in the developing world. Those functions are compromised by mounting pressures on marine biodiversity and ecosystems. Because of its economic and food value, fish biomass production provides an unusually direct link from biodiversity to critical ecosystem services. We used the Reef Life Survey’s global database of 4,556 standardized fish surveys to test the importance of biodiversity to fish production relative to 25 environmental drivers. Temperature, biodiversity, and human influence together explained 47% of the global variation in reef fish biomass among sites. Fish species richness and functional diversity were among the strongest predictors of fish biomass, particularly for the large-bodied species and carnivores preferred by fishers, and these biodiversity effects were robust to potentially confounding influences of sample abundance, scale, and environmental correlations. Warmer temperatures increased biomass directly, presumably by raising metabolism, and indirectly by increasing diversity, whereas temperature variability reduced biomass. Importantly, diversity and climate interact, with biomass of diverse communities less affected by rising and variable temperatures than species-poor communities. Biodiversity thus buffers global fish biomass from climate change, and conservation of marine biodiversity can stabilize fish production in a changing ocean. PMID:27185921

The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

PubMed

Synodinos, Alexis D; Tietjen, Britta; Lohmann, Dirk; Jeltsch, Florian

2018-01-21

Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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.

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.

Ecosystem Disturbance Effects on Land Surface Temperature, Forest Carbon Stocks, and Primary Productivity in the Western United States

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A.; Holden, Z. A.; Landguth, E.

2015-12-01

Disturbance plays an important role in the structure, composition, and nutrient cycling of forest ecosystems. Climate change is resulting in an increase in disturbance frequency and intensity, making it critical that we quantify the physical and chemical impacts of disturbances on forests. The impacts of disturbance are thought to vary widely depending on disturbance type, location, and climate. More specifically, fires, insect infestations, and other types of disturbances differ in their timing, extent, and intensity making it difficult to assess the true impact of disturbances on local energy budgets and carbon cycling. Here, we provide a regional analysis of the impacts of fire, insect attack, and other disturbances on land surface temperature (LST), carbon stocks, and gross primary productivity (GPP). Using disturbances detected with MODIS Enhanced Vegetation Index (EVI) time series between 2002 and 2012, we find that the impacts of disturbance on LST, carbon stocks, and GPP vary widely according to local climate, vegetation, and disturbance type and intensity. Fires resulted in the most distinct impacts on all response variables. Forest responses to insect epidemics were more varied in their magnitude and timing. The results of this study provide an important estimation of the variability of climate and ecosystem responses to disturbance across a large and heterogeneous landscape. With disturbance projected to increase in both frequency and intensity around the globe in the coming years, this information is vitally important to effectively manage forests into the future.

Temporal dynamics of direct N2O fluxes from agro-ecosystems in cold climates: importance of year-round measurements in multiple cropping systems

NASA Astrophysics Data System (ADS)

Wagner-Riddle, C.; Tenuta, M.

2014-12-01

Soil N2O fluxes (direct emissions) are highly variable in time and space due to soil, weather and management drivers. In cold climates, freeze/thaw cycles and short growing seasons can enhance soil N2O production contributing to the temporal variability of fluxes. Year-round measurements of N2O fluxes in multiple cropping systems are needed to decrease the uncertainty of annual emission estimates and to devise mitigation practices for emission reduction in cold climates. We have deployed a micrometeorological flux-gradient approach coupled to a tunable diode laser absorption spectroscopy system at two long-term sites in Canada: Elora, Ontario (2000-2014) and Glenlea, Manitoba (2006-2014). Quasi-simultaneous half-hourly flux measurements on four 4-ha fields within a level and aerodynamically homogeneous landscape were obtained allowing for comparison of crop type and/or management practices within and between years. Annual crops such as corn, soybeans, wheat, and barley received typical inorganic fertilizer and/or manure applications, and best management practices such as timing of application and reduced tillage were studied. Perennial grass-alfalfa hayfields were compared to annual crops during selected time periods. Here we synthesize the long-term datasets from these two sites, and quantify the overall contribution of non-growing season (mainly freeze/thaw cycles) and growing season (mainly nitrogen application) to annual emission totals. Uncertainties of regional estimates for cold-climates will be assessed using these long-term datasets.

How Will Climate Change Impact Cholera Outbreaks?

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

North Tropical Atlantic Climate Variability and Model Biases

NASA Astrophysics Data System (ADS)

Yang, Y.

2017-12-01

Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Surfing wave climate variability

NASA Astrophysics Data System (ADS)

Espejo, Antonio; Losada, Iñigo J.; Méndez, Fernando J.

2014-10-01

International surfing destinations are highly dependent on specific combinations of wind-wave formation, thermal conditions and local bathymetry. Surf quality depends on a vast number of geophysical variables, and analyses of surf quality require the consideration of the seasonal, interannual and long-term variability of surf conditions on a global scale. A multivariable standardized index based on expert judgment is proposed for this purpose. This index makes it possible to analyze surf conditions objectively over a global domain. A summary of global surf resources based on a new index integrating existing wave, wind, tides and sea surface temperature databases is presented. According to general atmospheric circulation and swell propagation patterns, results show that west-facing low to middle-latitude coasts are more suitable for surfing, especially those in the Southern Hemisphere. Month-to-month analysis reveals strong seasonal variations in the occurrence of surfable events, enhancing the frequency of such events in the North Atlantic and the North Pacific. Interannual variability was investigated by comparing occurrence values with global and regional modes of low-frequency climate variability such as El Niño and the North Atlantic Oscillation, revealing their strong influence at both the global and the regional scale. Results of the long-term trends demonstrate an increase in the probability of surfable events on west-facing coasts around the world in recent years. The resulting maps provide useful information for surfers, the surf tourism industry and surf-related coastal planners and stakeholders.

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...

Seasonal timing of first rain storms affects rare plant population dynamics

USGS Publications Warehouse

Levine, J.M.; McEachern, A.K.; Cowan, C.

2011-01-01

A major challenge in forecasting the ecological consequences of climate change is understanding the relative importance of changes to mean conditions vs. changes to discrete climatic events, such as storms, frosts, or droughts. Here we show that the first major storm of the growing season strongly influences the population dynamics of three rare and endangered annual plant species in a coastal California (USA) ecosystem. In a field experiment we used moisture barriers and water addition to manipulate the timing and temperature associated with first major rains of the season. The three focal species showed two- to fivefold variation in per capita population growth rates between the different storm treatments, comparable to variation found in a prior experiment imposing eightfold differences in season-long precipitation. Variation in germination was a major demographic driver of how two of three species responded to the first rains. For one of these species, the timing of the storm was the most critical determinant of its germination, while the other showed enhanced germination with colder storm temperatures. The role of temperature was further supported by laboratory trials showing enhanced germination in cooler treatments. Our work suggests that, because of species-specific cues for demographic transitions such as germination, changes to discrete climate events may be as, if not more, important than changes to season-long variables.

Seasonal timing of first rain storms affects rare plant population dynamics.

PubMed

Levine, Jonathan M; McEachern, A Kathryn; Cowan, Clark

2011-12-01

A major challenge in forecasting the ecological consequences of climate change is understanding the relative importance of changes to mean conditions vs. changes to discrete climatic events, such as storms, frosts, or droughts. Here we show that the first major storm of the growing season strongly influences the population dynamics of three rare and endangered annual plant species in a coastal California (USA) ecosystem. In a field experiment we used moisture barriers and water addition to manipulate the timing and temperature associated with first major rains of the season. The three focal species showed two- to fivefold variation in per capita population growth rates between the different storm treatments, comparable to variation found in a prior experiment imposing eightfold differences in season-long precipitation. Variation in germination was a major demographic driver of how two of three species responded to the first rains. For one of these species, the timing of the storm was the most critical determinant of its germination, while the other showed enhanced germination with colder storm temperatures. The role of temperature was further supported by laboratory trials showing enhanced germination in cooler treatments. Our work suggests that, because of species-specific cues for demographic transitions such as germination, changes to discrete climate events may be as, if not more, important than changes to season-long variables.

Enhanced Arctic amplification began at the Mid-Brunhes Event 430,000 years ago

USGS Publications Warehouse

Cronin, Thomas M.; Dwyer, Gary S.; Caverly, Emma; Farmer, Jesse; DeNinno, Lauren H.; Rodriguez-Lazaro, Julio; Gemery, Laura

2017-01-01

Arctic Ocean temperatures influence ecosystems, sea ice, species diversity, biogeochemical cycling, seafloor methane stability, deep-sea circulation, and CO2 cycling. Today's Arctic Ocean and surrounding regions are undergoing climatic changes often attributed to "Arctic amplification" - that is, amplified warming in Arctic regions due to sea-ice loss and other processes, relative to global mean temperature. However, the long-term evolution of Arctic amplification is poorly constrained due to lack of continuous sediment proxy records of Arctic Ocean temperature, sea ice cover and circulation. Here we present reconstructions of Arctic Ocean intermediate depth water (AIW) temperatures and sea-ice cover spanning the last ~ 1.5 million years (Ma) of orbitally-paced glacial/interglacial cycles (GIC). Using Mg/Ca paleothermometry of the ostracode Krithe and sea-ice planktic and benthic indicator species, we suggest that the Mid-Brunhes Event (MBE), a major climate transition ~ 400-350 ka, involved fundamental changes in AIW temperature and sea-ice variability. Enhanced Arctic amplification at the MBE suggests a major climate threshold was reached at ~ 400 ka involving Atlantic Meridional Overturning Circulation (AMOC), inflowing warm Atlantic Layer water, ice sheet, sea-ice and ice-shelf feedbacks, and sensitivity to higher post-MBE interglacial CO2 concentrations.