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.

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.

Analyzing climate variations at multiple timescales can guide Zika virus response measures.

PubMed

Muñoz, Ángel G; Thomson, Madeleine C; Goddard, Lisa; Aldighieri, Sylvain

2016-10-06

The emergence of Zika virus (ZIKV) in Latin America and the Caribbean in 2014-2016 occurred during a period of severe drought and unusually high temperatures, conditions that have been associated with the 2015-2016 El Niño event, and/or climate change; however, no quantitative assessment has been made to date. Analysis of related flaviviruses transmitted by the same vectors suggests that ZIKV dynamics are sensitive to climate seasonality and longer-term variability and trends. A better understanding of the climate conditions conducive to the 2014-2016 epidemic may permit the development of climate-informed short and long-term strategies for ZIKV prevention and control. Using a novel timescale-decomposition methodology, we demonstrate that the extreme climate anomalies observed in most parts of South America during the current epidemic are not caused exclusively by El Niño or climate change, but by a combination of climate signals acting at multiple timescales. In Brazil, the dry conditions present in 2013-2015 are primarily explained by year-to-year variability superimposed on decadal variability, but with little contribution of long-term trends. In contrast, the warm temperatures of 2014-2015 resulted from the compound effect of climate change, decadal and year-to-year climate variability. ZIKV response strategies made in Brazil during the drought concurrent with the 2015-2016 El Niño event, may require revision in light of the likely return of rainfall associated with the borderline La Niña event expected in 2016-2017. Temperatures are likely to remain warm given the importance of long term and decadal scale climate signals. The Author(s)

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

Sub-Milankovitch millennial-scale climate variability in Middle Eocene deep-marine sediments

NASA Astrophysics Data System (ADS)

Scotchman, J. I.; Pickering, K. T.; Robinson, S. A.

2009-12-01

Sub-Milankovitch millennial scale climate variability appears ubiquitous throughout the Quaternary and Pleistocene palaeoenvironmental records (e.g. McManus et al., 1999) yet the driving mechanism remains elusive. Possible mechanisms are generally linked to Quaternary-specific oceanic and cryospheric conditions (e.g. Maslin et al., 2001). An alternative external control, such as solar forcing, however, remains a compelling alternative hypothesis (e.g. Bond et al., 2001). This would imply that millennial-scale cycles are an intrinsic part of the Earth’s climatic system and not restricted to any specific period of time. Determining which of these hypotheses is correct impacts on our understanding of the climate system and its role as a driver of cyclic sedimentation during both icehouse and greenhouse climates. Here we show that Middle Eocene, laminated deep-marine sediments deposited in the Ainsa Basin, Spanish Pyrenees, contain 1,565-year (469 mm) cycles modulated by a 7,141-year (2157 mm) period. Climatic oscillations of 1,565-years recorded by element/Al ratios, are interpreted as representing climatically driven variation in sediment supply (terrigenous run-off) to the Ainsa basin. Climatic oscillations with this period are comparable to Quaternary Bond (~1,500-year), Dansgaard-Oeschger (~1,470-year) and Heinrich (~7,200-year) climatic events. Recognition of similar millennial-scale oscillations in the greenhouse climate of the Middle Eocene would appear inconsistent with an origin dependent upon Quaternary-specific conditions. Our observations lend support for pervasive millennial-scale climatic variability present throughout geologic time likely driven by an external forcing mechanism such as solar forcing. References Bond, G., Kromer, B., Beer, J., Muscheler, R., Evans, M.N., Showers, W., Hoffmann, S., Lotti-Bond, R., Hajdas, I., Bonani, G. 2001. Persistent Solar Influence on North Atlantic Climate During the Holocene. Science, 294, 2130-2136 Maslin, M., Seidov, D., Lowe, J. 2001. Synthesis of the nature and causes of rapid climate transitions during the Quaternary. In: The Oceans and rapid climate change: Past, present and future, (Seidov, D., Haupt, B. J. & Maslin, M., Eds.), AGU, Washington, D. C. McManus, J.F., Oppo, D.W. & Cullen, J.L. 1999. A 0.5-Million-Year Record of Millennial-Scale Climate Variability in the North Atlantic. Science, 283, 971-975

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

Treesearch

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

2010-01-01

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

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

USGS Publications Warehouse

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

2009-01-01

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

Climate variability risks for electricity supply

NASA Astrophysics Data System (ADS)

Kling, Harald

2017-12-01

Hydropower represents about 20% of sub-Saharan electricity, and expansion is underway. Rainfall varies year-to-year in geographical clusters, increasing the risk of climate-related electricity supply disruption in dry years.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Climate optimized planting windows for cotton in the lower Mississippi Delta region

USDA-ARS?s Scientific Manuscript database

Unique, variable summer climate of the lower Mississippi Delta region poses a critical challenge to cotton producers in deciding when to plant for optimized production. Traditional 2- to 4-year agronomic field trials conducted in this area fail to capture the effects of long-term climate variabiliti...

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

Treesearch

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

2014-01-01

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

The Effect of Vaccination Coverage and Climate on Japanese Encephalitis in Sarawak, Malaysia

PubMed Central

Impoinvil, Daniel E.; Ooi, Mong How; Diggle, Peter J.; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P.

2013-01-01

Background Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control. Methodology/principal findings Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases. Conclusions/significance This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored. PMID:23951373

Evaluating climate variability and management impacts on carbon dynamics of a temperate forest using a variety of techniques

NASA Astrophysics Data System (ADS)

Arain, M. A.

2015-12-01

Climate variability, extreme weather events, forest age and management history impacts carbon sequestration in forest ecosystems. A variety of measurement techniques such as eddy covariance, dendrochronology, automatic soil CO2 chambers and remote sensing are employed fully understand forest carbon dynamics. Here, we present carbon flux measurements from 2003-2014 in a 76-year old managed temperate pine ((-Pinus strobus L.) forest, near Lake Erie in southern Ontario, Canada. Forest was partially thinned (30% tree harvested) in 1983 and 2012. The thinning in 2012 did not significantly impact carbon fluxes as post-thinning fluxes were within the range of inter-annual variability. Mean annual post-thinning (2012-2104) gross ecosystem productivity (GEP) measure by the eddy covariance technique was 1518 ± 78 g C m-2 year-1 as compared to pre-thinning (2003-2011) GEP of 1384 ± 121 g C m-2·year-1. Over the same period, mean post-thinning net ecosystem productivity (NEP) was 185 ± 75 g C m-2 year-1 as compared to post-thinning NEP of 180 ± 70 g C m-2 year-1, indicating that pre-thinning NEP was not significantly different than post-thinning NEP. Only post-thinning mean annual ecosystem respiration (Re; 1322 ± 54 g C m-2 year-1) was higher than pre-thinning Re (1195 ± 101 g C m-2 year-1). Soil CO2 efflux measurements showed similar trends. We also evaluated the impacts of climate variability and management regime on the full life cycle of the forest using annual radial tree-ring growths from 15 trees and compared them with historical climate (temperature and precipitation) data. While the annual growth rates displayed weak correlation with long-term climatic records, the growth was generally reduced during years with extreme drought (-36% of mean annual precipitation) and extreme temperature variability (±0.6 - 1.0°C). Overall, forest was more sensitive to management regime than climate variability. It showed higher growth stress during low light condition after crown closure. When partial thinning was introduced in 1983, it responded slowly and took about 5 to 7 years to show measureable increase in its growth, despite favorable climatic conditions. This study will help to advance our understanding of carbon dynamic of forest ecosystems.

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.

Millennial- to century-scale variability in Gulf of Mexico Holocene climate records

USGS Publications Warehouse

Poore, R.Z.; Dowsett, H.J.; Verardo, S.; Quinn, T.M.

2003-01-01

Proxy records from two piston cores in the Gulf of Mexico (GOM) provide a detailed (50-100 year resolution) record of climate variability over the last 14,000 years. Long-term (millennial-scale) trends and changes are related to the transition from glacial to interglacial conditions and movement of the average position of the Intertropical Convergence Zone (ITCZ) related to orbital forcing. The ??18O of the surface-dwelling planktic foraminifer Globigerinoides ruber show negative excursions between 14 and 10.2 ka (radiocarbon years) that reflect influx of meltwater into the western GOM during melting of the Laurentide Ice Sheet. The relative abundance of the planktic foraminifer Globigerinoides sacculifer is related to transport of Caribbean water into the GOM. Maximum transport of Caribbean surface waters and moisture into the GOM associated with a northward migration of the average position of the ITCZ occurs between about 6.5 and 4.5 ka. In addition, abundance variations of G. sacculifer show century-scale variability throughout most of the Holocene. The GOM record is consistent with records from other areas, suggesting that century-scale variability is a pervasive feature of Holocene climate. The frequency of several cycles in the climate records is similar to cycles identified in proxy records of solar variability, indicating that at least some of the century-scale climate variability during the Holocene is due to external (solar) forcing.

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

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

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

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.

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.

Future warming patterns linked to today’s climate variability

DOE PAGES

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future warming patterns linked to today’s climate variability

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

Dai, Aiguo

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models’ ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21 st century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today’s climate, with areas of larger variations duringmore » 1950–1979 having more GHG-induced warming in the 21 st century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950–2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21 st century in models and in the real world. Furthermore, they support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.« less

Future Warming Patterns Linked to Today's Climate Variability.

PubMed

Dai, Aiguo

2016-01-11

The reliability of model projections of greenhouse gas (GHG)-induced future climate change is often assessed based on models' ability to simulate the current climate, but there has been little evidence that connects the two. In fact, this practice has been questioned because the GHG-induced future climate change may involve additional physical processes that are not important for the current climate. Here I show that the spatial patterns of the GHG-induced future warming in the 21(st) century is highly correlated with the patterns of the year-to-year variations of surface air temperature for today's climate, with areas of larger variations during 1950-1979 having more GHG-induced warming in the 21(st) century in all climate models. Such a relationship also exists in other climate fields such as atmospheric water vapor, and it is evident in observed temperatures from 1950-2010. The results suggest that many physical processes may work similarly in producing the year-to-year climate variations in the current climate and the GHG-induced long-term changes in the 21(st) century in models and in the real world. They support the notion that models that simulate present-day climate variability better are likely to make more reliable predictions of future climate change.

Climate Variability and Wildfires: Insights from Global Earth System Models

NASA Astrophysics Data System (ADS)

Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.

2016-12-01

Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in climate over long timescales.

Assessing the Habitat of Coccidioides posadasii, the Valley Fever Pathogen: A Study of Environmental Variables and Human Incidence Data in Arizona

NASA Astrophysics Data System (ADS)

Mann, Sarina N.

Coccidioidomycosis, or Valley Fever, is an infectious disease caused by inhalation of soil-dwelling fungus Coccidioides posadasii spores in the Lower Sonoran Life Zone (LSLZ) in Arizona. In the context of climate change, the habitat of environmentally-mediated infectious diseases, such as Valley Fever, are expected to change. Connections have been drawn between climate and Valley Fever infection. The operational scale of the organism is still unknown. Here, we use climatic variables, including precipitation, soil moisture, and temperature. We use PRISM precipitation and temperature data, and Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) as a measure of soil moisture for the entire state of Arizona, divided into 126 primary care areas (PCA). These data are analyzed and regressed with Valley Fever incidence to determine the effects of climatic variability on disease distribution and timing. This study confirms that Valley Fever occurrence is clustered in the LSLZ. Seasonal Valley Fever outbreak was found to be variable year-to-year based on climatic variability. The inconclusive regression analyses indicate that the operational scale of Coccidioides is smaller than the PCA region. All variables are related to Valley Fever infection, but one variable was not found to hold more predictive power than others.

Decadal Variability of Temperature and Salinity in the Northwest Atlantic Ocean

NASA Astrophysics Data System (ADS)

Mishonov, A. V.; Seidov, D.; Reagan, J. R.; Boyer, T.; Parsons, A. R.

2017-12-01

There are only a few regions in the World Ocean where the density of observations collected over the past 60 years is sufficient for reliable data mapping with spatial resolutions finer than one-degree. The Northwest Atlantic basin is one such regions where a spatial resolution of gridded temperature and salinity fields, comparable to those generated by eddy-resolving numerical models of ocean circulation, has recently becomes available. Using the new high-resolution Northwest Atlantic Regional Climatology, built on quarter-degree and one-tenth-degree resolution fields, we analyzed decadal variability and trends of temperature and salinity over 60 years in the Northwest Atlantic, and two 30-year ocean climates of 1955-1984 and 1985-2012 to evaluate the oceanic climate shift in this region. The 30-year climate shift is demonstrated using an innovative 3-D visualization of temperature and salinity. Spatial and temporal variability of heat accumulation found in previous research of the entire North Atlantic Ocean persists in the Northwest Atlantic Ocean. Salinity changes between two 30-year climates were also computed and are discussed.

2500 Years of European Climate Variability and Human Susceptibility

NASA Astrophysics Data System (ADS)

Büntgen, Ulf; Tegel, Willy; Nicolussi, Kurt; McCormick, Michael; Frank, David; Trouet, Valerie; Kaplan, Jed O.; Herzig, Franz; Heussner, Karl-Uwe; Wanner, Heinz; Luterbacher, Jürg; Esper, Jan

2011-02-01

Climate variations influenced the agricultural productivity, health risk, and conflict level of preindustrial societies. Discrimination between environmental and anthropogenic impacts on past civilizations, however, remains difficult because of the paucity of high-resolution paleoclimatic evidence. We present tree ring-based reconstructions of central European summer precipitation and temperature variability over the past 2500 years. Recent warming is unprecedented, but modern hydroclimatic variations may have at times been exceeded in magnitude and duration. Wet and warm summers occurred during periods of Roman and medieval prosperity. Increased climate variability from ~250 to 600 C.E. coincided with the demise of the western Roman Empire and the turmoil of the Migration Period. Such historical data may provide a basis for counteracting the recent political and fiscal reluctance to mitigate projected climate change.

A synthesis of sedimentary records of Australian environmental change during the last 2000 years

NASA Astrophysics Data System (ADS)

Tyler, J. J.; Karoly, D. J.; Gell, P.; Goodwin, I. D.

2013-12-01

Our understanding of Southern Hemispheric climate variability on multidecadal to multicentennial timescales is limited by a scarcity of quantitative, highly resolved climate records, a problem which is particularly manifest in Australia. To date there are no quantitative, annually resolved records from within continental Australia which extend further back in time than the most recent c. 300 years [Neukom and Gergis, 2012; PAGES 2k Consortium, 2013]. By contrast, a number of marine, lake, peat and speleothem sedimentary records exist, some of which span multiple millennia at sub-decadal resolution. Here we report a database of existing sedimentary records of environmental change in Australia [Freeman et al., 2011], of which 25 have sample resolutions < 100 years/sample and which span > 500 years in duration. The majority of these records are located in southeastern Australia, providing an invaluable resource with which to examine regional scale climate and environmental change. Although most of the records can not be quantitatively related to climate variability, Empirical Orthogonal Functions coupled with Monte Carlo iterative age modelling, demonstrate coherent patterns of environmental and ecological change. This coherency, as well as comparisons with a limited number of quantitative records, suggests that regional hydroclimatic changes were responsible for the observed patterns. Here, we discuss the implications of these findings with respect to Southern Hemisphere climate during the last 2000 years. In addition, we review the progress and potential of ongoing research in the region. References: Freeman, R., I. D. Goodwin, and T. Donovan (2011), Paleoclimate data synthesis and data base for the reconstruction of climate variability and impacts in NSW over the past 2000 years., Climate Futures Technical Report, 1/2011, 50 pages. Neukom, R., and J. Gergis (2012), Southern Hemisphere high-resolution palaeoclimate records of the last 2000 years, Holocene, 22(5), 501-524, doi:10.1177/0959683611427335. PAGES 2k Consortium (2013), Continental-scale temperature variability during the past two millennia, Nature Geoscience, 6, 339-346.

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

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

Fedorov, Alexey

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

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-01

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene.

PubMed

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2018-02-15

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Climate Change and ENSO Effects on Southeastern US Climate Patterns and Maize Yield.

PubMed

Mourtzinis, Spyridon; Ortiz, Brenda V; Damianidis, Damianos

2016-07-19

Climate change has a strong influence on weather patterns and significantly affects crop yields globally. El Niño Southern Oscillation (ENSO) has a strong influence on the U.S. climate and is related to agricultural production variability. ENSO effects are location-specific and in southeastern U.S. strongly connect with climate variability. When combined with climate change, the effects on growing season climate patterns and crop yields might be greater than expected. In our study, historical monthly precipitation and temperature data were coupled with non-irrigated maize yield data (33-43 years depending on the location) to show a potential yield suppression of ~15% for one °C increase in southeastern U.S. growing season maximum temperature. Yield suppression ranged between -25 and -2% among locations suppressing the southeastern U.S. average yield trend since 1981 by 17 kg ha(-1)year(-1) (~25%), mainly due to year-to-year June temperature anomalies. Yields varied among ENSO phases from 1971-2013, with greater yields observed during El Niño phase. During La Niña years, maximum June temperatures were higher than Neutral and El Niño, whereas June precipitation was lower than El Niño years. Our data highlight the importance of developing location-specific adaptation strategies quantifying both, climate change and ENSO effects on month-specific growing season climate conditions.

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

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

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

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

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Vegetation Interaction Enhances Interdecadal Climate Variability in the Sahel

NASA Technical Reports Server (NTRS)

Zeng, Ning; Neelin, J. David; Lau, William K.-M.

1999-01-01

The role of naturally varying vegetation in influencing the climate variability in the Sahel is explored in a coupled atmosphere-land-vegetation model. The Sahel rainfall variability is influenced by sea surface temperature (SST) variations in the oceans. Land-surface feedback is found to increase this variability both on interannual and interdecadal time scales. Interactive vegetation enhances the interdecadal variation significantly, but can reduce year to year variability due to a phase lag introduced by the relatively slow vegetation adjustment time. Variations in vegetation accompany the changes in rainfall, in particular, the multi-decadal drying trend from the 1950s to the 80s.

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

USGS Publications Warehouse

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

2016-01-01

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

Climate Variability Program

NASA Technical Reports Server (NTRS)

Halpern, David (Editor)

2002-01-01

The Annual Report of the Climate Variability Program briefly describes research activities of Principal Investigators who are funded by NASA's Earth Science Enterprise Research Division. The report is focused on the year 2001. Utilization of satellite observations is a singularity of research on climate science and technology at JPL (Jet Propulsion Laboratory). Research at JPL has two foci: generate new knowledge and develop new technology.

Using MERRA, AMIP II, CMIP5 Outputs to Assess Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100

NASA Astrophysics Data System (ADS)

Stackhouse, P. W.; Westberg, D. J.; Hoell, J. M., Jr.; Chandler, W.; Zhang, T.

2014-12-01

In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2emission (DOE/EIA "Annual Energy Outlook 2013"). Thus, increasing the energy efficiency of buildings is paramount to reducing energy costs and emissions. Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climates zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE (formerly known as the American Society of Hearting, Refrigeration and Air-Conditioning Engineers). A significant shortcoming of the methodology used in constructing such maps is the use of surface observations (located mainly near airports) that are unequally distributed and frequently have periods of missing data that need to be filled by various approximation schemes. This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the ASHRAE climate zone maps and then using MERRA to define the last 30 years of variability in climate zones. These results show that there is a statistically significant increase in the area covered by warmer climate zones and some tendency for a reduction of area in colder climate zones that require longer time series to confirm. Using the uncertainties of the basic surface temperature and precipitation parameters from MERRA as determined by comparison to surface measurements, we first compare patterns and variability of ASHRAE climate zones from MERRA relative to present day climate model runs from AMIP simulations to establish baseline sensitivity. Based upon these results, we assess the variability of the ASHRAE climate zones according to CMIP runs through 2100 using an ensemble analysis that classifies model output changes by percentiles. Estimates of statistical significance are then compared to original model variability during the AMIP period. This work quantifies and tests for significance the changes seen in the various US regions that represent a potential contribution by NASA to the ongoing National Climate Assessment.

Understanding the major transitions in Quaternary climate dynamics

NASA Astrophysics Data System (ADS)

Willeit, Matteo; Ganopolski, Andrey

2017-04-01

Climate dynamics over the past 3 million years was characterized by strong variability associated with glacial cycles and several distinct regime changes. The Pliocene-Pleistocene Transition (PPT), which happened around 2.7 million years ago, was characterized by the appearance of the large continental ice sheets over Northern Eurasia and North America. For two million years after the PPT climate variability was dominated by relatively symmetric 40 kyr cycles. At around 1 million years ago the dominant mode of climate variability experienced a relatively rapid transition from 40 kyr to strongly asymmetric 100 kyr cycles of larger amplitude (Mid-Pleistocene Transition). Additionally, during the past 800 kyr there are clear differences between the earlier and the later glacial cycles with the last five cycles characterized by larger magnitude of variability (Mid-Brunhes Event). Here, we use the Earth system model of intermediate complexity CLIMBER-2 to explore possible mechanisms that could explain these regime shifts. CLIMBER-2 incorporates all major components of the Earth system - atmosphere, ocean, land surface, northern hemisphere ice sheets, terrestrial biota and soil carbon, marine biogeochemistry and aeolian dust. The model was optimally tuned to reproduce climate, ice volume and CO2 variability over the last 400,000 years. Using the same model version, we performed a large set of simulations covering the entire Quaternary (3 million years) starting from identical initial conditions and using a parallelization in time technique which consists of starting the model at different times (every 100,000 years) and running each simulation for 500,000 years. The Earth's orbital variations are the only prescribed radiative forcing. Several sets of the Northern Hemisphere orography and sediment thickness representing different stages of landscape evolution during the Quaternary are prescribed as boundary conditions for the ice sheet model and volcanic CO2 outgassing is used as the external forcing for the carbon cycle to allow for different background atmospheric CO2 concentrations. We show that by varying only these two model boundary conditions and volcanic forcing the model is able to reproduce the major regime changes of Quaternary long-term climate dynamics.

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

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.

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

NASA Astrophysics Data System (ADS)

Deser, C.

2017-12-01

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

Climate 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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Detrending phenological time series improves climate-phenology analyses and reveals evidence of plasticity.

PubMed

Iler, Amy M; Inouye, David W; Schmidt, Niels M; Høye, Toke T

2017-03-01

Time series have played a critical role in documenting how phenology responds to climate change. However, regressing phenological responses against climatic predictors involves the risk of finding potentially spurious climate-phenology relationships simply because both variables also change across years. Detrending by year is a way to address this issue. Additionally, detrending isolates interannual variation in phenology and climate, so that detrended climate-phenology relationships can represent statistical evidence of phenotypic plasticity. Using two flowering phenology time series from Colorado, USA and Greenland, we detrend flowering date and two climate predictors known to be important in these ecosystems: temperature and snowmelt date. In Colorado, all climate-phenology relationships persist after detrending. In Greenland, 75% of the temperature-phenology relationships disappear after detrending (three of four species). At both sites, the relationships that persist after detrending suggest that plasticity is a major component of sensitivity of flowering phenology to climate. Finally, simulations that created different strengths of correlations among year, climate, and phenology provide broader support for our two empirical case studies. This study highlights the utility of detrending to determine whether phenology is related to a climate variable in observational data sets. Applying this as a best practice will increase our understanding of phenological responses to climatic variation and change. © 2016 by the Ecological Society of America.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan C.; Fabian, Karl; Milzer, Gesa; Giraudeau, Jacques; Knies, Jochen

2016-02-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO records are crucial to better understand its response to climate forcing factors, and assess predictability and shifts associated with ongoing climate change. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we compare geochemical measurements with instrumental data and show that primary productivity recorded in central Norwegian fjord sediments is sensitive to NAO variability. This observation is used to calibrate paleoproductivity changes to a 500-year reconstruction of winter NAO (Luterbacher et al., 2001). Conditioned on a stationary relation between our climate proxy and the NAO we establish a first high resolution NAO proxy record (NAOTFJ) from marine sediments covering the past 2800 years. The NAOTFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends. The here presented climate record shows that fjord sediments provide crucial information for an improved understanding of the linkages between atmospheric circulation, solar and oceanic forcing factors.

Climate change. Six centuries of variability and extremes in a coupled marine-terrestrial ecosystem.

PubMed

Black, Bryan A; Sydeman, William J; Frank, David C; Griffin, Daniel; Stahle, David W; García-Reyes, Marisol; Rykaczewski, Ryan R; Bograd, Steven J; Peterson, William T

2014-09-19

Reported trends in the mean and variability of coastal upwelling in eastern boundary currents have raised concerns about the future of these highly productive and biodiverse marine ecosystems. However, the instrumental records on which these estimates are based are insufficiently long to determine whether such trends exceed preindustrial limits. In the California Current, a 576-year reconstruction of climate variables associated with winter upwelling indicates that variability increased over the latter 20th century to levels equaled only twice during the past 600 years. This modern trend in variance may be unique, because it appears to be driven by an unprecedented succession of extreme, downwelling-favorable, winter climate conditions that profoundly reduce productivity for marine predators of commercial and conservation interest. Copyright © 2014, American Association for the Advancement of Science.

Has solar variability caused climate change that affected human culture?

NASA Astrophysics Data System (ADS)

Feynman, Joan

If solar variability affects human culture it most likely does so by changing the climate in which the culture operates. Variations in the solar radiative input to the Earth's atmosphere have often been suggested as a cause of such climate change on time scales from decades to tens of millennia. In the last 20 years there has been enormous progress in our knowledge of the many fields of research that impinge on this problem; the history of the solar output, the effect of solar variability on the Earth's mean climate and its regional patterns, the history of the Earth's climate and the history of mankind and human culture. This new knowledge encourages revisiting the question asked in the title of this talk. Several important historical events have been reliably related to climate change including the Little Ice Age in northern Europe and the collapse of the Classical Mayan civilization in the 9th century AD. In the first section of this paper we discus these historical events and review the evidence that they were caused by changes in the solar output. Perhaps the most important event in the history of mankind was the development of agricultural societies. This began to occur almost 12,000 years ago when the climate changed from the Pleistocene to the modern climate of the Holocene. In the second section of the paper we will discuss the suggestion ( Feynman and Ruzmaikin, 2007) that climate variability was the reason agriculture developed when it did and not before.

An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping

2015-01-01

Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.

Monthly means of selected climate variables for 1985 - 1989

NASA Technical Reports Server (NTRS)

Schubert, S.; Wu, C.-Y.; Zero, J.; Schemm, J.-K.; Park, C.-K.; Suarez, M.

1992-01-01

Meteorologists are accustomed to viewing instantaneous weather maps, since these contain the most relevant information for the task of producing short-range weather forecasts. Climatologists, on the other hand, tend to deal with long-term means, which portray the average climate. The recent emphasis on dynamical extended-range forecasting and, in particular measuring and predicting short term climate change makes it important that we become accustomed to looking at variations on monthly and longer time scales. A convenient toll for researchers to familiarize themselves with the variability which occurs in selected parameters on these time scales is provided. The format of the document was chosen to help facilitate the intercomparison of various parameters and highlight the year-to-year variability in monthly means.

Relative importance of climate changes at different time scales on net primary productivity-a case study of the Karst area of northwest Guangxi, China.

PubMed

Liu, Huiyu; Zhang, Mingyang; Lin, Zhenshan

2017-10-05

Climate changes are considered to significantly impact net primary productivity (NPP). However, there are few studies on how climate changes at multiple time scales impact NPP. With MODIS NPP product and station-based observations of sunshine duration, annual average temperature and annual precipitation, impacts of climate changes at different time scales on annual NPP, have been studied with EEMD (ensemble empirical mode decomposition) method in the Karst area of northwest Guangxi, China, during 2000-2013. Moreover, with partial least squares regression (PLSR) model, the relative importance of climatic variables for annual NPP has been explored. The results show that (1) only at quasi 3-year time scale do sunshine duration and temperature have significantly positive relations with NPP. (2) Annual precipitation has no significant relation to NPP by direct comparison, but significantly positive relation at 5-year time scale, which is because 5-year time scale is not the dominant scale of precipitation; (3) the changes of NPP may be dominated by inter-annual variabilities. (4) Multiple time scales analysis will greatly improve the performance of PLSR model for estimating NPP. The variable importance in projection (VIP) scores of sunshine duration and temperature at quasi 3-year time scale, and precipitation at quasi 5-year time scale are greater than 0.8, indicating important for NPP during 2000-2013. However, sunshine duration and temperature at quasi 3-year time scale are much more important. Our results underscore the importance of multiple time scales analysis for revealing the relations of NPP to changing climate.

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.

Sensitivity of ground - water recharge estimates to climate variability and change, Columbia Plateau, Washington

USGS Publications Warehouse

Vaccaro, John J.

1992-01-01

The sensitivity of groundwater recharge estimates was investigated for the semiarid Ellensburg basin, located on the Columbia Plateau, Washington, to historic and projected climatic regimes. Recharge was estimated for predevelopment and current (1980s) land use conditions using a daily energy-soil-water balance model. A synthetic daily weather generator was used to simulate lengthy sequences with parameters estimated from subsets of the historical record that were unusually wet and unusually dry. Comparison of recharge estimates corresponding to relatively wet and dry periods showed that recharge for predevelopment land use varies considerably within the range of climatic conditions observed in the 87-year historical observation period. Recharge variations for present land use conditions were less sensitive to the same range of historical climatic conditions because of irrigation. The estimated recharge based on the 87-year historical climatology was compared with adjustments to the historical precipitation and temperature records for the same record to reflect CO2-doubling climates as projected by general circulation models (GCMs). Two GCM scenarios were considered: an average of conditions for three different GCMs with CO2 doubling, and a most severe “maximum” case. For the average GCM scenario, predevelopment recharge increased, and current recharge decreased. Also considered was the sensitivity of recharge to the variability of climate within the historical and adjusted historical records. Predevelopment and current recharge were less and more sensitive, respectively, to the climate variability for the average GCM scenario as compared to the variability within the historical record. For the maximum GCM scenario, recharge for both predevelopment and current land use decreased, and the sensitivity to the CO2-related climate change was larger than sensitivity to the variability in the historical and adjusted historical climate records.

Climate, streamflow, and legacy effects on growth of riparian Populus angustifolia in the arid San Luis Valley, Colorado

USGS Publications Warehouse

Andersen, Douglas

2016-01-01

Knowledge of the factors affecting the vigor of desert riparian trees is important for their conservation and management. I used multiple regression to assess effects of streamflow and climate (12–14 years of data) or climate alone (up to 60 years of data) on radial growth of clonal narrowleaf cottonwood (Populus angustifolia), a foundation species in the arid, Closed Basin portion of the San Luis Valley, Colorado. I collected increment cores from trees (14–90 cm DBH) at four sites along each of Sand and Deadman creeks (total N = 85), including both perennial and ephemeral reaches. Analyses on trees <110 m from the stream channel explained 33–64% of the variation in standardized growth index (SGI) over the period having discharge measurements. Only 3 of 7 models included a streamflow variable; inclusion of prior-year conditions was common. Models for trees farther from the channel or over a deep water table explained 23–71% of SGI variability, and 4 of 5 contained a streamflow variable. Analyses using solely climate variables over longer time periods explained 17–85% of SGI variability, and 10 of 12 included a variable indexing summer precipitation. Three large, abrupt shifts in recent decades from wet to dry conditions (indexed by a seasonal Palmer Drought Severity Index) coincided with dramatically reduced radial growth. Each shift was presumably associated with branch dieback that produced a legacy effect apparent in many SGI series: uncharacteristically low SGI in the year following the shift. My results suggest trees in locations distant from the active channel rely on the regional shallow unconfined aquifer, summer rainfall, or both to meet water demands. The landscape-level differences in the water supplies sustaining these trees imply variable effects from shifts in winter-versus monsoon-related precipitation, and from climate change versus streamflow or groundwater management.

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

NASA Astrophysics Data System (ADS)

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Benveniste, Jérôme

2016-07-01

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

Does weather shape rodents? Climate related changes in morphology of two heteromyid species

NASA Astrophysics Data System (ADS)

Wolf, Mosheh; Friggens, Michael; Salazar-Bravo, Jorge

2009-01-01

Geographical variation in morphometric characters in heteromyid rodents has often correlated with climate gradients. Here, we used the long-term database of rodents trapped in the Sevilleta National Wildlife Refuge in New Mexico, USA to test whether significant annual changes in external morphometric characters are observed in a region with large variations in temperature and precipitation. We looked at the relationships between multiple temperature and precipitation variables and a number of morphological traits (body mass, body, tail, hind leg, and ear length) for two heteromyid rodents, Dipodomys merriami and Perognathus flavescens. Because these rodents can live multiple years in the wild, the climate variables for the year of the capture and the previous 2 years were included in the analyses. Using multiple linear regressions, we found that all of our morphometric traits, with the exception of tail length in D. merriami, had a significant relationship with one or more of the climate variables used. Our results demonstrate that effects of climate change on morphological traits occur over short periods, even in noninsular mammal populations. It is unclear, though, whether these changes are the result of morphological plasticity or natural selection.

Convergence of Dynamic Vegetation Net Productivity Responses to Precipitation Variability from 10 Years of MODIS EVI

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

Holocene climate and climate variability of the northern Gulf of Mexico and adjacent northern Gulf Coast: A review

USGS Publications Warehouse

Poore, Richard Z.

2008-01-01

Marine records from the northern Gulf of Mexico indicate that significant multidecadal- and century-scale variability was common during the Holocene. Mean annual sea-surface temperature (SST) during the last 1,400 years may have varied by 3°C, and excursions to cold SST coincide with reductions in solar output. Broad trends in Holocene terrestrial climate and environmental change along the eastern portion of the northern Gulf Coast are evident from existing pollen records, but the high-frequency details of climate variability are not well known. Continuous and well-dated records of climate change and climate variability in the western portion of the northern Gulf Coast are essentially lacking.Information on Holocene floods, droughts, and storm frequency along the northern Gulf Coast is limited. Records of floods may be preserved in continental shelf sediments, but establishing continuity and chronologies for sedimentary sequences on the shelf presents challenges due to sediment remobilization and redeposition during storms. Studies of past storm deposits in coastal lakes and marshes show promise for constructing records of past storm frequency. A recent summary of sea-level history of the northern Gulf Coast indicates sea level was higher than modern sea level several times during the last few thousand years.

A progressively wetter climate in southern East Africa over the past 1.3 million years.

PubMed

Johnson, T C; Werne, J P; Brown, E T; Abbott, A; Berke, M; Steinman, B A; Halbur, J; Contreras, S; Grosshuesch, S; Deino, A; Scholz, C A; Lyons, R P; Schouten, S; Damsté, J S Sinninghe

2016-09-08

African climate is generally considered to have evolved towards progressively drier conditions over the past few million years, with increased variability as glacial-interglacial change intensified worldwide. Palaeoclimate records derived mainly from northern Africa exhibit a 100,000-year (eccentricity) cycle overprinted on a pronounced 20,000-year (precession) beat, driven by orbital forcing of summer insolation, global ice volume and long-lived atmospheric greenhouse gases. Here we present a 1.3-million-year-long climate history from the Lake Malawi basin (10°-14° S in eastern Africa), which displays strong 100,000-year (eccentricity) cycles of temperature and rainfall following the Mid-Pleistocene Transition around 900,000 years ago. Interglacial periods were relatively warm and moist, while ice ages were cool and dry. The Malawi record shows limited evidence for precessional variability, which we attribute to the opposing effects of austral summer insolation and the temporal/spatial pattern of sea surface temperature in the Indian Ocean. The temperature history of the Malawi basin, at least for the past 500,000 years, strongly resembles past changes in atmospheric carbon dioxide and terrigenous dust flux in the tropical Pacific Ocean, but not in global ice volume. Climate in this sector of eastern Africa (unlike northern Africa) evolved from a predominantly arid environment with high-frequency variability to generally wetter conditions with more prolonged wet and dry intervals.

Medieval Warm Period, Little Ice Age and 20th century temperature variability from Chesapeake Bay

USGS Publications Warehouse

Cronin, T. M.; Dwyer, G.S.; Kamiya, T.; Schwede, S.; Willard, D.A.

2003-01-01

We present paleoclimate evidence for rapid (< 100 years) shifts of ~2-4oC in Chesapeake Bay (CB) temperature ~2100, 1600, 950, 650, 400 and 150 years before present (years BP) reconstructed from magnesium/calcium (Mg/Ca) paleothermometry. These include large temperature excursions during the Little Ice Age (~1400-1900 AD) and the Medieval Warm Period (~800-1300 AD) possibly related to changes in the strength of North Atlantic thermohaline circulation (THC). Evidence is presented for a long period of sustained regional and North Atlantic-wide warmth with low-amplitude temperature variability between ~450 and 1000 AD. In addition to centennial-scale temperature shifts, the existence of numerous temperature maxima between 2200 and 250 years BP (average ~70 years) suggests that multi-decadal processes typical of the North Atlantic Oscillation (NAO) are an inherent feature of late Holocene climate. However, late 19th and 20th century temperature extremes in Chesapeake Bay associated with NAO climate variability exceeded those of the prior 2000 years, including the interval 450-1000 AD, by 2-3oC, suggesting anomalous recent behavior of the climate system.

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

NASA Astrophysics Data System (ADS)

Kühl, Norbert; Moschen, Robert; Wagner, Stefanie

2010-05-01

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

Statistical link between external climate forcings and modes of ocean variability

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan; Perona, Paolo

2017-07-01

In this study we investigate statistical link between external climate forcings and modes of ocean variability on inter-annual (3-year) to centennial (100-year) timescales using de-trended semi-partial-cross-correlation analysis technique. To investigate this link we employ observations (AD 1854-1999), climate proxies (AD 1600-1999), and coupled Atmosphere-Ocean-Chemistry Climate Model simulations with SOCOL-MPIOM (AD 1600-1999). We find robust statistical evidence that Atlantic multi-decadal oscillation (AMO) has intrinsic positive correlation with solar activity in all datasets employed. The strength of the relationship between AMO and solar activity is modulated by volcanic eruptions and complex interaction among modes of ocean variability. The observational dataset reveals that El Niño southern oscillation (ENSO) has statistically significant negative intrinsic correlation with solar activity on decadal to multi-decadal timescales (16-27-year) whereas there is no evidence of a link on a typical ENSO timescale (2-7-year). In the observational dataset, the volcanic eruptions do not have a link with AMO on a typical AMO timescale (55-80-year) however the long-term datasets (proxies and SOCOL-MPIOM output) show that volcanic eruptions have intrinsic negative correlation with AMO on inter-annual to multi-decadal timescales. The Pacific decadal oscillation has no link with solar activity, however, it has positive intrinsic correlation with volcanic eruptions on multi-decadal timescales (47-54-year) in reconstruction and decadal to multi-decadal timescales (16-32-year) in climate model simulations. We also find evidence of a link between volcanic eruptions and ENSO, however, the sign of relationship is not consistent between observations/proxies and climate model simulations.

Climatic Changes in the East-European Forest-Steppe and Effects on Scots Pine Productivity

NASA Astrophysics Data System (ADS)

Matveev, S. M.; Chendev, Yu. G.; Lupo, A. R.; Hubbart, J. A.; Timashchuk, D. A.

2017-01-01

Climate change during the 20th and early 21st centuries in the transitional zone between forests and grasslands at the center of the East-European Plain (Voronezh oblast) was determined by examining climate trends and variability using tree ring radial increment data as representative of productivity. An increase in atmospheric moisture for the warm period of the year (May-September) since 1890s, and mean annual temperatures since the 1950s was identified. During the same time period, there was a marked increase in amplitude of the annual variations for temperature and precipitation. Study results revealed trends, variability in the climatic indices, and corresponding radial wood increment for the regional stands of Pinus sylvestris L. These fluctuations are consistent with 10-12-years Schwabe-Wolf, 22-years Hale, and the 32-36-years Bruckner Solar Cycles. There was an additional relationship found between high-frequency (short-period) climate fluctuations, lasting for about three years, and 70-90-years fluctuations of the moisture regime in the study region corresponding to longer cycles. The results of this study can help guide management decisions in the study region and elsewhere, especially where climate change induced alterations to the state and productivity of forest ecosystems and associated natural resource commodities are of growing concern.

Multi-year climate variability in the Southwestern United States within a context of a dynamically downscaled twentieth century reanalysis

NASA Astrophysics Data System (ADS)

Carrillo, Carlos M.; Castro, Christopher L.; Chang, Hsin-I.; Luong, Thang M.

2017-12-01

This investigation evaluates whether there is coherency in warm and cool season precipitation at the low-frequency scale that may be responsible for multi-year droughts in the US Southwest. This low-frequency climate variability at the decadal scale and longer is studied within the context of a twentieth-century reanalysis (20CR) and its dynamically-downscaled version (DD-20CR). A spectral domain matrix methods technique (Multiple-Taper-Method Singular Value Decomposition) is applied to these datasets to identify statistically significant spatiotemporal precipitation patterns for the cool (November-April) and warm (July-August) seasons. The low-frequency variability in the 20CR is evaluated by exploring global to continental-scale spatiotemporal variability in moisture flux convergence (MFC) to the occurrence of multiyear droughts and pluvials in Central America, as this region has a demonstrated anti-phase relationship in low-frequency climate variability with northern Mexico and the southwestern US By using the MFC in lieu of precipitation, this study reveals that the 20CR is able to resolve well the low-frequency, multiyear climate variability. In the context of the DD-20CR, multiyear droughts and pluvials in the southwestern US (in the early twentieth century) are significantly related to this low-frequency climate variability. The precipitation anomalies at these low-frequency timescales are in phase between the cool and warm seasons, consistent with the concept of dual-season drought as has been suggested in tree ring studies.

Quantitative Analysis of Relevant Soil, Land-use and Climate Characteristics on Landscape Degradation in Hungary

NASA Astrophysics Data System (ADS)

Kertesz, Adam; Mika, Janos; Jakab, Gergely; Palinkas, Melinda

2017-04-01

The objective of our research is to survey degradation processes acting in each micro-region of Hungary in connection with geographical and climatic characteristics. A survey of land degradation processes has been carried out at medium scale (1:50 000) to identify the affected areas of the region. Over 18,000 rectangles of Hungary have been digitally characterised for several types of land degradation. Water-flow type gully erosion and soil-loss (RUSLE, 2015: Esdac-data) are studied for dependent variables in this study. USDA textural classes, available water capacity, bulk density, clay content, coarse fragments, silt content, sand content, soil parent material, soil texture, land-use type (Corine, 2012) are used for non-climatic variables. Some of these characteristics are quantified in a non-scalable way, so the first step was to arrange these qualitative codes or pseudo-numbers into monotonous order for including them into the following multi-regression analyses. Data available from the CarpatClim Project (www.carpatclim-eu.org/pages/home) for 1961-2010 are also used in their 50 years averages is seasonal and annual resolution. The selected variables from this gridded data set are global radiation, daily mean temperature, maximum and minimum temperature, number of extreme cold days (< 20 C), precipitation, extreme wet days (>20 mm), days with utilizable precipitation (>1mm/d), potential evapotranspiration, Palmer Index (PDSI), Palfai Index (PAI), relative humidity and wind speed at 10 m height. The gully erosion processes strongly depend on the investigated non-climatic variables, mostly on parent material and slope. The group of further climatic factors is formed by winter relative humidity, wind speed and all-year round Palmer index. Besides leading role of the above non-climatic factors, additional effects of the significant climate variables are difficult to interpret. Nevertheless, the partial effects of these climate variables are combined with future climate scenarios available from GCM and RCM studies for Hungary. The real climate change effects may likely be stronger, than those obtained by this combination, due to inter-dependences between the non-climatic factors and climate variations. The study has been supported by the OTKA-K108755 project.

Vulnerability and Tradeoffs of Dairy Farmers to the Impacts of Climate Variability and Change in India

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.; R, D.

2016-12-01

In recent years climate variability has threatened the sustainability of dairy animals and dairy farming in India. The study aims at assessing the vulnerability and tradeoffs of Dairy Based Livelihoods to Climate Variability and Change in the Western Ghat ecosystem and for this purpose; data were aggregated to an overall Livelihood Vulnerability Index (LVI) to Climate Change underlying the principles of IPCC, using 28 indicators and trade-off between vulnerability and milk production was calculated. Data were collected through Participatory Rural Appraisal and personal interviews from 360 randomly selected dairy farmers of three states of Western Ghat region, complemented by thirty years of gridded weather data and livestock data. The index score of dairy based livelihoods of many regions were negative. Lanja taluka of Maharashtra has highest level of vulnerability with overall LVI value -4.17 with 48% farmers falling in highly vulnerable category. There is also significant tradeoff between milk production and components of LVI. Thus our research will provide an important basis for policy makers to develop appropriate adaptation strategies for alarming situation and decision making for farmers to minimize the risk of dairy sector to climate variability.

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.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

Unlocking the climate riddle in forested ecosystems

Treesearch

Greg C. Liknes; Christopher W. Woodall; Brian F. Walters; Sara A. Goeking

2012-01-01

Climate information is often used as a predictor in ecological studies, where temporal averages are typically based on climate normals (30-year means) or seasonal averages. While ensemble projections of future climate forecast a higher global average annual temperature, they also predict increased climate variability. It remains to be seen whether forest ecosystems...

Variability in sea ice cover and climate elicit sex specific responses in an Antarctic predator

PubMed Central

Labrousse, Sara; Sallée, Jean-Baptiste; Fraser, Alexander D.; Massom, Rob A.; Reid, Phillip; Hobbs, William; Guinet, Christophe; Harcourt, Robert; McMahon, Clive; Authier, Matthieu; Bailleul, Frédéric; Hindell, Mark A.; Charrassin, Jean-Benoit

2017-01-01

Contrasting regional changes in Southern Ocean sea ice have occurred over the last 30 years with distinct regional effects on ecosystem structure and function. Quantifying how Antarctic predators respond to such changes provides the context for predicting how climate variability/change will affect these assemblages into the future. Over an 11-year time-series, we examine how inter-annual variability in sea ice concentration and advance affect the foraging behaviour of a top Antarctic predator, the southern elephant seal. Females foraged longer in pack ice in years with greatest sea ice concentration and earliest sea ice advance, while males foraged longer in polynyas in years of lowest sea ice concentration. There was a positive relationship between near-surface meridional wind anomalies and female foraging effort, but not for males. This study reveals the complexities of foraging responses to climate forcing by a poleward migratory predator through varying sea ice property and dynamic anomalies. PMID:28233791

Variability in sea ice cover and climate elicit sex specific responses in an Antarctic predator.

PubMed

Labrousse, Sara; Sallée, Jean-Baptiste; Fraser, Alexander D; Massom, Rob A; Reid, Phillip; Hobbs, William; Guinet, Christophe; Harcourt, Robert; McMahon, Clive; Authier, Matthieu; Bailleul, Frédéric; Hindell, Mark A; Charrassin, Jean-Benoit

2017-02-24

Contrasting regional changes in Southern Ocean sea ice have occurred over the last 30 years with distinct regional effects on ecosystem structure and function. Quantifying how Antarctic predators respond to such changes provides the context for predicting how climate variability/change will affect these assemblages into the future. Over an 11-year time-series, we examine how inter-annual variability in sea ice concentration and advance affect the foraging behaviour of a top Antarctic predator, the southern elephant seal. Females foraged longer in pack ice in years with greatest sea ice concentration and earliest sea ice advance, while males foraged longer in polynyas in years of lowest sea ice concentration. There was a positive relationship between near-surface meridional wind anomalies and female foraging effort, but not for males. This study reveals the complexities of foraging responses to climate forcing by a poleward migratory predator through varying sea ice property and dynamic anomalies.

Application of a stochastic weather generator to assess climate change impacts in a semi-arid climate: The Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, N.; Fowler, H. J.; Blenkinsop, S.; Burton, A.; Kilsby, C. G.; Archer, D. R.; Harpham, C.; Hashmi, M. Z.

2014-09-01

Assessing local climate change impacts requires downscaling from Global Climate Model simulations. Here, a stochastic rainfall model (RainSim) combined with a rainfall conditioned weather generator (CRU WG) have been successfully applied in a semi-arid mountain climate, for part of the Upper Indus Basin (UIB), for point stations at a daily time-step to explore climate change impacts. Validation of the simulated time-series against observations (1961-1990) demonstrated the models' skill in reproducing climatological means of core variables with monthly RMSE of <2.0 mm for precipitation and ⩽0.4 °C for mean temperature and daily temperature range. This level of performance is impressive given complexity of climate processes operating in this mountainous context at the boundary between monsoonal and mid-latitude (westerly) weather systems. Of equal importance the model captures well the observed interannual variability as quantified by the first and last decile of 30-year climatic periods. Differences between a control (1961-1990) and future (2071-2100) regional climate model (RCM) time-slice experiment were then used to provide change factors which could be applied within the rainfall and weather models to produce perturbed ‘future' weather time-series. These project year-round increases in precipitation (maximum seasonal mean change:+27%, annual mean change: +18%) with increased intensity in the wettest months (February, March, April) and year-round increases in mean temperature (annual mean +4.8 °C). Climatic constraints on the productivity of natural resource-dependent systems were also assessed using relevant indices from the European Climate Assessment (ECA) and indicate potential future risk to water resources and local agriculture. However, the uniformity of projected temperature increases is in stark contrast to recent seasonally asymmetrical trends in observations, so an alternative scenario of extrapolated trends was also explored. We conclude that interannual variability in climate will continue to have the dominant impact on water resources management whichever trajectory is followed. This demonstrates the need for sophisticated downscaling methods which can evaluate changes in variability and sequencing of events to explore climate change impacts in this region.

Variability in winter climate and winter extremes reduces population growth of an alpine butterfly.

PubMed

Roland, Jens; Matter, Stephen F

2013-01-01

We examined the long-term, 15-year pattern of population change in a network of 21 Rocky Mountain populations of Parnassius smintheus butterflies in response to climatic variation. We found that winter values of the broadscale climate variable, the Pacific Decadal Oscillation (PDO) index, were a strong predictor of annual population growth, much more so than were endogenous biotic factors related to population density. The relationship between PDO and population growth was nonlinear. Populations declined in years with extreme winter PDO values, when there were either extremely warm or extremely cold sea surface temperatures in the eastern Pacific relative to that in the western Pacific. Results suggest that more variable winters, and more frequent extremely cold or warm winters, will result in more frequent decline of these populations, a pattern exacerbated by the trend for increasingly variable winters seen over the past century.

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.

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.

Region-Specific Sensitivity of Anemophilous Pollen Deposition to Temperature and Precipitation

PubMed Central

Donders, Timme H.; Hagemans, Kimberley; Dekker, Stefan C.; de Weger, Letty A.; de Klerk, Pim; Wagner-Cremer, Friederike

2014-01-01

Understanding relations between climate and pollen production is important for several societal and ecological challenges, importantly pollen forecasting for pollinosis treatment, forensic studies, global change biology, and high-resolution palaeoecological studies of past vegetation and climate fluctuations. For these purposes, we investigate the role of climate variables on annual-scale variations in pollen influx, test the regional consistency of observed patterns, and evaluate the potential to reconstruct high-frequency signals from sediment archives. A 43-year pollen-trap record from the Netherlands is used to investigate relations between annual pollen influx, climate variables (monthly and seasonal temperature and precipitation values), and the North Atlantic Oscillation climate index. Spearman rank correlation analysis shows that specifically in Alnus, Betula, Corylus, Fraxinus, Quercus and Plantago both temperature in the year prior to (T-1), as well as in the growing season (T), are highly significant factors (TApril rs between 0.30 [P<0.05[ and 0.58 [P<0.0001]; TJuli-1 rs between 0.32 [P<0.05[ and 0.56 [P<0.0001]) in the annual pollen influx of wind-pollinated plants. Total annual pollen prediction models based on multiple climate variables yield R2 between 0.38 and 0.62 (P<0.0001). The effect of precipitation is minimal. A second trapping station in the SE Netherlands, shows consistent trends and annual variability, suggesting the climate factors are regionally relevant. Summer temperature is thought to influence the formation of reproductive structures, while temperature during the flowering season influences pollen release. This study provides a first predictive model for seasonal pollen forecasting, and also aides forensic studies. Furthermore, variations in pollen accumulation rates from a sub-fossil peat deposit are comparable with the pollen trap data. This suggests that high frequency variability pollen records from natural archives reflect annual past climate variability, and can be used in palaeoecological and -climatological studies to bridge between population- and species-scale responses to climate forcing. PMID:25133631

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

PubMed

Diouf, Ibrahima; Deme, Abdoulaye; Ndione, Jacques-André; Gaye, Amadou Thierno; Rodríguez-Fonseca, Belén; Cissé, Moustapha

2013-01-01

The aim of this work, undertaken in the framework of QWeCI (Quantifying Weather and Climate Impacts on health in the developing countries) project, is to study how climate variability could influence malaria seasonal incidence. It will also assess the evolution of vector-borne diseases such as malaria by simulation analysis of climate models according to various climate scenarios for the next years. Climate variability seems to be determinant for the risk of malaria development (Freeman and Bradley, 1996 [1], Lindsay and Birley, 1996 [2], Kuhn et al., 2005 [3]). Climate can impact on the epidemiology of malaria by several mechanisms, directly, via the development rates and survival of both pathogens and vectors, and indirectly, through changes in vegetation and land surface characteristics such as the variability of breeding sites like ponds. Copyright © 2013 Académie des sciences. Published by Elsevier SAS. All rights reserved.

Indices of climate change in the Artic zone derived from radiosondes

NASA Astrophysics Data System (ADS)

Añel, J. A.; Gimeno, L.; de La Torre, L.; Nieto, R.; Tesouro, M.; Ribera, P.; García, R.; Hernández, E.

2003-04-01

The use of indices has been traditionally one of the main tools to identify climatic change. Here we present a study of the interannual variability of parameters derived from radiosonde data to study climate change in the artic zone. Trends, oscillations and the relationship with the principal climate variability mode for this region ( Northern Annular Mode) have been studied. We calculate the indices from the Upper Air Digital Files of the National Climatic Data Center (CARDS). We chose for our work the radiosonde data of stations over the studied region, with a temporal coverage of 27 years (1973-1998).

Molluscan sclerochronology on the Faroese Shelf and its potential to obtain closer insights into the climate variability of North Atlantic water masses

NASA Astrophysics Data System (ADS)

Bonitz, F. G. W.; Andersson Dahl, C.; Trofimova, T.

2016-12-01

In this study, we investigate the climate variability in the North Atlantic during the last 350 years by applying sclerochronological methods. The inflow of North Atlantic water masses into the Arctic and the Norwegian Sea is important for the climate in these regions. A better understanding of the climate variability on highly resolved time scales is needed to obtain a better fundament for climate predictions for these areas. However, highly resolved paleoclimate records are sparse in the North Atlantic and instrumental data cover only the last 50 - 150 years. Bivalve shells provide highly resolved climate archives, especially the shells of the long-lived bivalve species Arctica islandica. This widely occurring species forms annual growth increments, which can be analyzed similarly to tree rings. Climatic and oceanographic changes are recorded population-wide in the shell`s growth rate and in the isotopic composition of the shell. Hence, multi-centennial absolutely dated chronologies can be built by cross-matching live-collected and sub-fossil specimens. Our chronology building effort has led to the first multi-centennial absolutely dated chronology from the Faroese Shelf covering the time period from AD 1642 - 2013. The growth indices of the chronology anti-correlate with April - September sea surface temperatures (SST) for the last 100 years indicating favorable conditions for growth when temperatures are lower. This also suggests that the main growing season of A. islandica around the Faroe Islands occurs in this time period; a hypothesis supported by δ18O-based temperature reconstructions from growth increments representing the years 2001 - 2013. The RBAR, which is an indicator for the signal strength throughout the chronology shows an inverse relationship with Atlantic Multi-decadal Oscillation (AMO) data indicating that periods of higher AMO indexes result in a weakened signal strength in the chronology for the same time period. In conclusion, our results suggest that a combination of the growth increment variability and δ18O measurements of the growth increments can provide a tool to obtain information about the year-to-year SST variability beyond instrumental observations and the signal strength throughout the chronology may provide information about the timing of major AMO shifts.

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.

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

A virtual water network of the Roman world

NASA Astrophysics Data System (ADS)

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

2014-06-01

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

Effects of climate variability on global scale flood risk

NASA Astrophysics Data System (ADS)

Ward, P.; Dettinger, M. D.; Kummu, M.; Jongman, B.; Sperna Weiland, F.; Winsemius, H.

2013-12-01

In this contribution we demonstrate the influence of climate variability on flood risk. Globally, flooding is one of the worst natural hazards in terms of economic damages; Munich Re estimates global losses in the last decade to be in excess of $240 billion. As a result, scientifically sound estimates of flood risk at the largest scales are increasingly needed by industry (including multinational companies and the insurance industry) and policy communities. Several assessments of global scale flood risk under current and conditions have recently become available, and this year has seen the first studies assessing how flood risk may change in the future due to global change. However, the influence of climate variability on flood risk has as yet hardly been studied, despite the fact that: (a) in other fields (drought, hurricane damage, food production) this variability is as important for policy and practice as long term change; and (b) climate variability has a strong influence in peak riverflows around the world. To address this issue, this contribution illustrates the influence of ENSO-driven climate variability on flood risk, at both the globally aggregated scale and the scale of countries and large river basins. Although it exerts significant and widespread influences on flood peak discharges in many parts of the world, we show that ENSO does not have a statistically significant influence on flood risk once aggregated to global totals. At the scale of individual countries, though, strong relationships exist over large parts of the Earth's surface. For example, we find particularly strong anomalies of flood risk in El Niño or La Niña years (compared to all years) in southern Africa, parts of western Africa, Australia, parts of Central Eurasia (especially for El Niño), the western USA (especially for La Niña), and parts of South America. These findings have large implications for both decadal climate-risk projections and long-term future climate change research. We carried out the research by simulating daily river discharge using a global hydrological model (PCR-GLOBWB), forced with gridded climate reanalysis time-series. From this, we derived peak annual flood volumes for large-scale river basins globally. These were used to force a global inundation model (dynRout) to map inundation extent and depth for return periods between 2 and 1000 years, under El Niño conditions, neutral conditions, and La Niña conditions. Theses flood hazard maps were combined with global datasets on socioeconomic variables such as population and income to represent the socioeconomic exposure to flooding, and depth-damage curves to represent vulnerability.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

NASA Astrophysics Data System (ADS)

Harding, Lawrence W., Jr.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-03-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay.

PubMed

Harding, Lawrence W; Mallonee, Michael E; Perry, Elgin S; Miller, W David; Adolf, Jason E; Gallegos, Charles L; Paerl, Hans W

2016-03-30

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km(2) watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945-1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981-2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries.

Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay

PubMed Central

Harding, Jr., Lawrence W.; Mallonee, Michael E.; Perry, Elgin S.; Miller, W. David; Adolf, Jason E.; Gallegos, Charles L.; Paerl, Hans W.

2016-01-01

Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945–1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981–2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries. PMID:27026279

Climate Variability and Its Impact on Forest Hydrology on South Carolina Coastal Plain, USA

Treesearch

Zhaohua Dai; Devendra Amatya; Ge Sun; Carl Trettin; Changsheng Li; Harbin Li

2011-01-01

Understanding the changes in hydrology of coastal forested wetlands induced by climate change is fundamental for developing strategies to sustain their functions and services. This study examined 60 years of climatic observations and 30 years of hydrological data, collected at the Santee Experimental Forest (SEF) in coastal South Carolina. We also applied a physically-...

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.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events

PubMed Central

Vincenzi, Simone

2014-01-01

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an ‘extinction window’ of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the ‘extinction window’, although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. PMID:24920116

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

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

Effects of climate on numbers of northern prairie wetlands

USGS Publications Warehouse

Larson, Diane L.

1995-01-01

The amount of water held in individual wetland basins depends not only on local climate patterns but also on groundwater flow regime, soil permeability, and basin size. Most wetland basins in the northern prairies hold water in some years and are dry in others. To assess the potential effect of climate change on the number of wetland basins holding water in a given year, one must first determine how much of the variability in number of wet basins is accounted for by climatic variables. I used multiple linear regression to examine the relationship between climate variables and percentage of wet basins throughout the Prairie Pothole Region of Canada and the United States. The region was divided into three areas: parkland, Canadian grassland, and United States grassland (i.e., North Dakota and South Dakota). The models - which included variables for spring and fall temperature, yearly precipitation, the previous year's count of wet basins, and for grassland areas, the previous fall precipitation - accounted for 63 to 65% of the variation in the number of wet basins. I then explored the sensitivities of the models to changes in temperature and precipitation, as might be associated with increased greenhouse gas concentrations. Parkland wetlands are shown to be much more vulnerable to increased temperatures than are wetlands in either Canadian or United States grasslands. Sensitivity to increased precipitation did not vary geographically. These results have implications for waterfowl and other wildlife populations that depend on availability of wetlands in the parklands for breeding or during periods of drought in the southern grasslands.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

Tree- Rings Link Climate and Carbon Storage in a Northern Mixed Hardwood Forest

NASA Astrophysics Data System (ADS)

Chiriboga, A.

2007-12-01

The terrestrial biosphere is a variable sink for atmospheric carbon dioxide. It is important to understand how carbon storage in trees is affected by natural climate variability to better characterize the sink. Quantifying the sensitivity of forest carbon storage to climate will improve carbon budgets and have implications for forest management practices. Here we explore how climate variability affects the ability of a northern mixed hardwood forest in Michigan to sequester atmospheric carbon dioxide in woody tissues. This site is ideal for studies of carbon sequestration; The University of Michigan Biological Station is an Ameriflux site, and has detailed meteorological and biometric records, as well as CO2 flux data. We have produced an 82- year aspen (Populus grandidentata) tree-ring chronology for this site, and measured ring widths at several heights up the bole. These measurements were used to estimate annual wood volume, which represents carbon allocated to aboveground carbon stores. Standard dendroclimatological techniques are used to identify environmental factors (e.g. temperature or precipitation) that drive tree-ring increment variability in the past century, and therefore annual carbon storage in this forest. Preliminary results show that marker years within the tree- ring chronology correspond with years that have cold spring temperatures. This suggests that trees at this site are temperature sensitive.

Do GCM's predict the climate.... Or the low frequency weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Schertzer, D.; Varon, D.

2012-04-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500 - 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT vary in power law manners ≈ Δt**H the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale (Δt). At longer scales Δt >τw (≈ 10 days) H changes sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime. In this regime, the spectrum is a relatively flat "plateau", it's variability is low, stable, corresponding to our usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, once again H>0, so that the variability increases with scale: the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, to define "climate states" as fluctuations at scale τc and then "climate change" as the fluctuations at longer periods (Δt>τc). We show that the intermediate low frequency weather regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched so that only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by stochastic cascade models of weather, but also by control runs (i.e. without climate forcing) of GCM based climate forecasting systems including those of the Institut Pierre Simon Laplace (Paris) and the Earth Forecasting System (Hamburg). In order for these systems to go beyond simply predicting low frequency weather i.e. in order for them to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. Using statistical scaling techniques we examine the scale dependence of fluctuations from forced and unforced GCM outputs, including from the ECHO-G and EFS simulations in the Millenium climate reconstruction project and compare this with data, multiproxies and paleo data. Our general conclusion is that the models systematically underestimate the multidecadal, multicentennial scale variability.

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

PubMed Central

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

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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.

Historical floods reconstruction using NOAA 20CR global climate reanalysis over the last 150 years

NASA Astrophysics Data System (ADS)

Mathevet, T.; Brigode, P.; Jégonday, S.; Hingray, B.; Gailhard, J.; Wilhelm, B.

2017-12-01

Since several years, climatologists are producing long reanalysis for studying the variability of global climate over the last 150 years. For hydrologists, these datasets offer interesting opportunities for reconstructing historical flood events, and thus increasing the sample size used for flood frequency analysis. In this study, a streamflow reconstruction method based on the analogy of atmospheric situations (using NOAA 20CR reanalysis) for the reconstruction of climatic series and on a rainfall-runoff model for the streamflow reconstruction has been applied over different French catchments at the daily timestep. The studied catchments have been selected because of the availability of long observed streamflow series (used for quantifying the performances of the flood reconstructions) and for their different hydro-climatological regimes. Different methodologies have been tested for the reconstruction of daily climatic series over the 1851-2014 period, using geopotential heights and additional variables available within the 20CR reanalysis (relative humidity, precipitable water, etc.). Long observed climatic series have also been used when available as a reference for the climatic reconstructions. The different reconstruction methods have been finally ranked in terms of their historical flood reconstruction performances, quantified by flood types (autumn or winter floods) and atmospheric genesis (using a weather pattern classification). The obtained results indicate that using additional 20CR variables to the geopotential heights only slightly improve the flood reconstructions, while using observed climatic series improves significantly the flood reconstruction over the different catchments.

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.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Assessing How Water Type, Climate, and Landscape Position Correlate with Variability of Methane in Shallow Groundwater in the Marcellus Region

NASA Astrophysics Data System (ADS)

Campbell, A.; Lautz, L.; Hoke, G. D.

2017-12-01

Prior work shows that spatial differences in naturally-occurring methane concentrations in shallow groundwater in the Marcellus Shale region are correlated with water type (e.g. Ca-HCO3 vs Na-HCO3) and landscape position (e.g. valley vs upland). However, little is known about how naturally-occurring methane in groundwater varies through time, particularly on a seasonal or monthly time scale, and how temporal variability is related to seasonal changes in climate. Extensive development of the Marcellus shale gas play in northeastern Pennsylvania limits opportunities for measuring baseline water quality through time. In contrast, a ban on hydraulic fracturing in NY affords an opportunity for characterizing baseline temporal variability in methane concentrations. The objective of this study is to characterize temporal variability of naturally-occurring methane in shallow groundwater in the Marcellus region, and how such temporal variability is correlated to other well characteristics, such as water type, landscape position, and climatic conditions. We worked with homeowners to sample 11 domestic wells monthly in the Marcellus Shale region of NY for methane concentrations and major ions for a full year. Wells were grouped according to the primary source of methane (e.g. thermogenic vs microbial) based upon δ13C-DIC, δ13C-CH4, and δD-CH4 isotopes. The full dataset and the grouped data were analyzed to assess how well climatic conditions, water type, and landscape position correlate with variability of methane concentrations through time. These data provide information on within year and between year variability of methane, as well as spatial variability between wells, which fills a data gap and can be used to inform policy regulations.

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

Climate Variability and Ponderosa Pine Colonizations in Central Wyoming: Integrating Dendroecology and Dendroclimatology

NASA Astrophysics Data System (ADS)

Lesser, M.; Wentzel, C.; Gray, S.; Jackson, S.

2007-12-01

Many tree species are predicted to expand into new territory over the coming decades in response to changing climate. By studying tree expansions over the last several centuries we can begin to understand the mechanisms underlying these changes and anticipate their consequences for forest management. Woody-plant demographics and decadal to multidecadal climate variability are often closely linked in semi-arid regions. Integrated tree-ring analysis, combining dendroecology and dendroclimatology to document, respectively, the demographic history of the population and the climatic history of the region, can reveal ecological dynamics in response to climate variability. We studied four small, disjunct populations of Pinus ponderosa in the Bighorn Basin of north-central Wyoming. These populations are located 30 to 100 kilometers from the nearest core populations of ponderosa pine in the western Bighorn Mountains. Packrat midden studies have shown that ponderosa pine colonized the western slopes of the Bighorn Range 1500 years ago, so the disjunct populations in the basin must be younger. All trees (living and dead) at each of the four disjunct populations were mapped, cored, and then aged using tree-ring based techniques. We obtained records of hydroclimatic variability from the Bighorn Basin using four tree-ring series from Pinus flexilis (3 sites) and Pseudotsuga menziesii (1 site). The four disjunct populations were all established within the past 500 years. Initially, the populations grew slowly with low recruitment rates until the early 19th century, when they experienced one or more large recruitment pulses. These pulses coincided with extended wet periods in the climate reconstruction. However, similar wet periods before the 19th Century were not accompanied by recruitment pulses, indicating that other factors (e.g., population density, genetic variability) are also important in colonization and expansion. We are currently obtaining genetic data and carrying out population modeling to differentiate the effects of population dynamics, genetic variability, and climate variability on recruitment and expansion of these populations.

Delayed build-up of Arctic ice sheets during 400,000-year minima in insolation variability.

PubMed

Hao, Qingzhen; Wang, Luo; Oldfield, Frank; Peng, Shuzhen; Qin, Li; Song, Yang; Xu, Bing; Qiao, Yansong; Bloemendal, Jan; Guo, Zhengtang

2012-10-18

Knowledge of the past variability of climate at high northern latitudes during astronomical analogues of the present interglacial may help to inform our understanding of future climate change. Unfortunately, long-term continuous records of ice-sheet variability in the Northern Hemisphere only are scarce because records of benthic (18)O content represent an integrated signal of changes in ice volume in both polar regions. However, variations in Northern Hemisphere ice sheets influence the Siberian High (an atmospheric pressure system), so variations in the East Asian winter monsoon (EAWM)--as recorded in the aeolian dust deposits on the Chinese Loess Plateau--can serve as a useful proxy of Arctic climate variability before the ice-core record begins. Here we present an EAWM proxy record using grain-size variations in two parallel loess sections representative of sequences across the whole of the Chinese Loess Plateau over the past 900,000 years. The results show that during periods of low eccentricity and precessional variability at approximately 400,000-year intervals, the grain-size-inferred intensity of the EAWM remains weak for up to 20,000 years after the end of the interglacial episode of high summer monsoon activity and strong pedogenesis. In contrast, there is a rapid increase in the EAWM after the end of most other interglacials. We conclude that, for both the 400,000-year interglacials, the weak EAWM winds maintain a mild, non-glacial climate at high northern latitudes for much longer than expected from the conventional loess and marine oxygen isotope records. During these times, the less-severe summer insolation minima at 65° N (ref. 4) would have suppressed ice and snow accumulation, leading to a weak Siberian High and, consequently, weak EAWM winds.

Refractory periods and climate forcing in cholera dynamics.

PubMed

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

2005-08-04

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

Climate drives inter-annual variability in probability of high severity fire occurrence in the western United States

NASA Astrophysics Data System (ADS)

Keyser, Alisa; Westerling, Anthony LeRoy

2017-05-01

A long history of fire suppression in the western United States has significantly changed forest structure and ecological function, leading to increasingly uncharacteristic fires in terms of size and severity. Prior analyses of fire severity in California forests showed that time since last fire and fire weather conditions predicted fire severity very well, while a larger regional analysis showed that topography and climate were important predictors of high severity fire. There has not yet been a large-scale study that incorporates topography, vegetation and fire-year climate to determine regional scale high severity fire occurrence. We developed models to predict the probability of high severity fire occurrence for the western US. We predict high severity fire occurrence with some accuracy, and identify the relative importance of predictor classes in determining the probability of high severity fire. The inclusion of both vegetation and fire-year climate predictors was critical for model skill in identifying fires with high fractional fire severity. The inclusion of fire-year climate variables allows this model to forecast inter-annual variability in areas at future risk of high severity fire, beyond what slower-changing fuel conditions alone can accomplish. This allows for more targeted land management, including resource allocation for fuels reduction treatments to decrease the risk of high severity fire.

Predicting phenology by integrating ecology, evolution and climate science

USGS Publications Warehouse

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

2011-01-01

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

Where’s the beef? Predicting the effects of climate change on cattle production in western U.S. rangelands

Treesearch

Sue Miller; Matt Reeves; Karen Bagne; John Tanaka

2017-01-01

Cattle production capacity on western rangelands is potentially vulnerable to climate change through impacts on the amount of forage, changes in vegetation type, heat stress, and year-to-year forage variability. The researchers in this study projected climate change effects to rangelands through 2100 and compared them to a present-day baseline to estimate vulnerability...

Predicting lodgepole pine site index from climatic parameters in Alberta.

Treesearch

Robert A. Monserud; Shongming Huang; Yuqing Yang

2006-01-01

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

Climate change: The 2015 Paris Agreement thresholds and Mediterranean basin ecosystems.

PubMed

Guiot, Joel; Cramer, Wolfgang

2016-10-28

The United Nations Framework Convention on Climate Change Paris Agreement of December 2015 aims to maintain the global average warming well below 2°C above the preindustrial level. In the Mediterranean basin, recent pollen-based reconstructions of climate and ecosystem variability over the past 10,000 years provide insights regarding the implications of warming thresholds for biodiversity and land-use potential. We compare scenarios of climate-driven future change in land ecosystems with reconstructed ecosystem dynamics during the past 10,000 years. Only a 1.5°C warming scenario permits ecosystems to remain within the Holocene variability. At or above 2°C of warming, climatic change will generate Mediterranean land ecosystem changes that are unmatched in the Holocene, a period characterized by recurring precipitation deficits rather than temperature anomalies. Copyright © 2016, American Association for the Advancement of Science.

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

PubMed

Moffa-Sánchez, Paola; Hall, Ian R

2017-11-23

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

Do GCM's Predict the Climate.... Or the Low Frequency Weather?

NASA Astrophysics Data System (ADS)

Lovejoy, S.; Varon, D.; Schertzer, D. J.

2011-12-01

Over twenty-five years ago, a three-regime scaling model was proposed describing the statistical variability of the atmosphere over time scales ranging from weather scales out to ≈ 100 kyrs. Using modern in situ data reanalyses, monthly surface series (at 5ox5o), 8 "multiproxy" (yearly) series of the Northern hemisphere from 1500- 1980, and GRIP and Vostok paleotemperatures at 5.2 and ≈ 100 year resolutions (over the past 91-420 kyrs), we refine the model and show how it can be understood with the help of new developments in nonlinear dynamics, especially multifractals and cascades. In a scaling range, mean fluctuations in state variables such as temperature ΔT ≈ ΔtH the where Δt is the duration. At small (weather) scales the fluctuation exponents are generally H>0; they grow with scale. At longer scales Δt >τw (≈ 10 days) they change sign, the fluctuations decrease with scale; this is the low variability, "low frequency weather" regime the spectrum is a relatively flat "plateau", it's variability is that of the usual idea of "long term weather statistics". Finally for longer times, Δt>τc ≈ 10 - 100 years, again H>0, the variability again increases with scale. This is the true climate regime. These scaling regimes allow us to objectively define the weather as fluctuations over periods <τw, "climate states", as fluctuations at scale τc and "climate change" as the fluctuations at longer periods >τc). We show that the intermediate regime is the result of the weather regime undergoing a "dimensional transition": at temporal scales longer than the typical lifetime of planetary structures (τw), the spatial degrees of freedom are rapidly quenched, only the temporal degrees of freedom are important. This low frequency weather regime has statistical properties well reproduced not only by weather cascade models, but also by control runs (i.e. without climate forcing) of GCM's (including IPSL and ECHAM GCM's). In order for GCM's to go beyond simply predicting this low frequency weather so as to predict the climate, they need appropriate climate forcings and/ or new internal mechanisms of variability. We examine this using wavelet analyses of forced and unforced GCM outputs, including the ECHO-G simulation used in the Millenium project. For example, we find that climate scenarios with large CO2 increases do give rise to a climate regime but that Hc>1 i.e. much larger than that of natural variability which for temperatures has Hc≈0.4. In comparison, the (largely volcanic) forcing of the ECHO-G Millenium simulation is fairly realistic (Hc≈0.4), although it is not clear that this mechanism can explain the even lower frequency variability found in the paleotemperature series, nor is it clear that this is compatible with low frequency solar or orbital forcings.

High School Students' Metaphors towards "Climate" Concept According to Gender Variable

ERIC Educational Resources Information Center

Coskun, Mucahit

2010-01-01

This research was carried out to determine the metaphors of high school students towards "climate" concept according to gender variable. A total of 108 students in two high schools in Karabuk City participated in the research in 2009-2010 academic years. The data of the research were gathered from the students' completing the…

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.

Reproductive success of a keystone herbivore is more variable and responsive to climate in habitats with lower resource diversity.

PubMed

Iles, David T; Rockwell, Robert F; Koons, David N

2018-07-01

The effects of climate on wild populations are often channelled through species interactions. Population responses to climate variation can therefore differ across habitats, owing to variation in the biotic community. Theory predicts that consumer demography should be less variable and less responsive to climate in habitats with greater resource diversity. We tested these predictions using a long-term study of breeding lesser snow geese along the western coast of Hudson Bay, Manitoba, Canada. Reproductive success was measured in 22 years from 114 locations, in either coastal or inland habitat types. We used Bayesian analysis to estimate the response of reproductive success to climate in each habitat type, along with residual variation not explained by climate. We then quantified gosling diet composition in each habitat type to test the prediction that reproductive success would be less variable and more responsive to climate in habitats with lower resource diversity. Reproductive success responded positively to seasonal warmness, but this response was much stronger in inland habitats than in coastal habitats. Site- and year-level random effects were also three to five times more variable in inland habitats. Simultaneously, land cover diversity and gosling diet diversity were lower in inland habitats. Our study illustrates that spatial variation in resource diversity (and thus, species interactions) can have important effects on consumer responses to climate. In this system, climate change is expected to disproportionately increase the reproductive success of snow geese in vast inland habitats, potentially counteracting management efforts to reduce the abundance of this keystone herbivore. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

Quantifying streamflow change caused by forest disturbance at a large spatial scale: A single watershed study

NASA Astrophysics Data System (ADS)

Wei, Xiaohua; Zhang, Mingfang

2010-12-01

Climatic variability and forest disturbance are commonly recognized as two major drivers influencing streamflow change in large-scale forested watersheds. The greatest challenge in evaluating quantitative hydrological effects of forest disturbance is the removal of climatic effect on hydrology. In this paper, a method was designed to quantify respective contributions of large-scale forest disturbance and climatic variability on streamflow using the Willow River watershed (2860 km2) located in the central part of British Columbia, Canada. Long-term (>50 years) data on hydrology, climate, and timber harvesting history represented by equivalent clear-cutting area (ECA) were available to discern climatic and forestry influences on streamflow by three steps. First, effective precipitation, an integrated climatic index, was generated by subtracting evapotranspiration from precipitation. Second, modified double mass curves were developed by plotting accumulated annual streamflow against annual effective precipitation, which presented a much clearer picture of the cumulative effects of forest disturbance on streamflow following removal of climatic influence. The average annual streamflow changes that were attributed to forest disturbances and climatic variability were then estimated to be +58.7 and -72.4 mm, respectively. The positive (increasing) and negative (decreasing) values in streamflow change indicated opposite change directions, which suggest an offsetting effect between forest disturbance and climatic variability in the study watershed. Finally, a multivariate Autoregressive Integrated Moving Average (ARIMA) model was generated to establish quantitative relationships between accumulated annual streamflow deviation attributed to forest disturbances and annual ECA. The model was then used to project streamflow change under various timber harvesting scenarios. The methodology can be effectively applied to any large-scale single watershed where long-term data (>50 years) are available.

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.

What Climate Sensitivity Index Is Most Useful for Projections?

NASA Astrophysics Data System (ADS)

Grose, Michael R.; Gregory, Jonathan; Colman, Robert; Andrews, Timothy

2018-02-01

Transient climate response (TCR), transient response at 140 years (T140), and equilibrium climate sensitivity (ECS) indices are intended as benchmarks for comparing the magnitude of climate response projected by climate models. It is generally assumed that TCR or T140 would explain more variability between models than ECS for temperature change over the 21st century, since this timescale is the realm of transient climate change. Here we find that TCR explains more variability across Coupled Model Intercomparison Project phase 5 than ECS for global temperature change since preindustrial, for 50 or 100 year global trends up to the present, and for projected change under representative concentration pathways in regions of delayed warming such as the Southern Ocean. However, unexpectedly, we find that ECS correlates higher than TCR for projected change from the present in the global mean and in most regions. This higher correlation does not relate to aerosol forcing, and the physical cause requires further investigation.

Climate variability in the subarctic area for the last 2 millennia

NASA Astrophysics Data System (ADS)

Nicolle, Marie; Debret, Maxime; Massei, Nicolas; Colin, Christophe; deVernal, Anne; Divine, Dmitry; Werner, Johannes P.; Hormes, Anne; Korhola, Atte; Linderholm, Hans W.

2018-01-01

To put recent climate change in perspective, it is necessary to extend the instrumental climate records with proxy data from paleoclimate archives. Arctic climate variability for the last 2 millennia has been investigated using statistical and signal analyses from three regionally averaged records from the North Atlantic, Siberia and Alaska based on many types of proxy data archived in the Arctic 2k database v1.1.1. In the North Atlantic and Alaska, the major climatic trend is characterized by long-term cooling interrupted by recent warming that started at the beginning of the 19th century. This cooling is visible in the Siberian region at two sites, warming at the others. The cooling of the Little Ice Age (LIA) was identified from the individual series, but it is characterized by wide-range spatial and temporal expression of climate variability, in contrary to the Medieval Climate Anomaly. The LIA started at the earliest by around AD 1200 and ended at the latest in the middle of the 20th century. The widespread temporal coverage of the LIA did not show regional consistency or particular spatial distribution and did not show a relationship with archive or proxy type either. A focus on the last 2 centuries shows a recent warming characterized by a well-marked warming trend parallel with increasing greenhouse gas emissions. It also shows a multidecadal variability likely due to natural processes acting on the internal climate system on a regional scale. A ˜ 16-30-year cycle is found in Alaska and seems to be linked to the Pacific Decadal Oscillation, whereas ˜ 20-30- and ˜ 50-90-year periodicities characterize the North Atlantic climate variability, likely in relation with the Atlantic Multidecadal Oscillation. These regional features are probably linked to the sea ice cover fluctuations through ice-temperature positive feedback.

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

PubMed

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

2016-09-01

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

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela.

PubMed

Grillet, María-Eugenia; El Souki, Mayida; Laguna, Francisco; León, José Rafael

2014-01-01

We investigated the periodicity of Plasmodium vivax and P. falciparum incidence in time-series of malaria data (1990-2010) from three endemic regions in Venezuela. In particular, we determined whether disease epidemics were related to local climate variability and regional climate anomalies such as the El Niño Southern Oscillation (ENSO). Malaria periodicity was found to exhibit unique features in each studied region. Significant multi-annual cycles of 2- to about 6-year periods were identified. The inter-annual variability of malaria cases was coherent with that of SSTs (ENSO), mainly at temporal scales within the 3-6 year periods. Additionally, malaria cases were intensified approximately 1 year after an El Niño event, a pattern that highlights the role of climate inter-annual variability in the epidemic patterns. Rainfall mediated the effect of ENSO on malaria locally. Particularly, rains from the last phase of the season had a critical role in the temporal dynamics of Plasmodium. The malaria-climate relationship was complex and transient, varying in strength with the region and species. By identifying temporal cycles of malaria we have made a first step in predicting high-risk years in Venezuela. Our findings emphasize the importance of analyzing high-resolution spatial-temporal data to better understand malaria transmission dynamics. Copyright © 2013 Elsevier B.V. All rights reserved.

Regionally heterogeneous paleoenvironmental responses in the West African and South American monsoon systems on glacial to millennial timescales

NASA Astrophysics Data System (ADS)

Shanahan, T. M.; Hughen, K. A.; van Mooy, B.; Overpeck, J. T.; Baker, P. A.; Fritz, S.; Peck, J. A.; Scholz, C. A.; King, J. W.

2008-12-01

Although millennial-scale paleoenvironmental changes have been well characterized for high latitude sites, short-term climate variability in the tropics is less well understood. While the Intertropical Convergence Zone may act as an integrator of tropical climate changes, regional factors also play an important role in controlling the tropical response to climate forcing. Understanding these influences, and how they modulate the response to global climate forcing under different mean climate states is thus important for assessing how the tropics may respond to future climate change. Here, we examine new centennial-resolution records of paleoenvironmental change from isotopic and relative abundance data from molecular biomarkers in sediment cores from Lake Bosumtwi and Lake Titicaca. We assess the relative response of the West African and South American monsoon systems to millennial and suborbital-scale climate variability over the last ca. 30,000 years. While there is evidence for synchronous climate variability in the two systems, the dominant paleoenvironmental changes appear largely decoupled, highlighting the importance of regional climatology in controlling the response to climate forcing in tropical regions.

Extinction risk and eco-evolutionary dynamics in a variable environment with increasing frequency of extreme events.

PubMed

Vincenzi, Simone

2014-08-06

One of the most dramatic consequences of climate change will be the intensification and increased frequency of extreme events. I used numerical simulations to understand and predict the consequences of directional trend (i.e. mean state) and increased variability of a climate variable (e.g. temperature), increased probability of occurrence of point extreme events (e.g. floods), selection pressure and effect size of mutations on a quantitative trait determining individual fitness, as well as the their effects on the population and genetic dynamics of a population of moderate size. The interaction among climate trend, variability and probability of point extremes had a minor effect on risk of extinction, time to extinction and distribution of the trait after accounting for their independent effects. The survival chances of a population strongly and linearly decreased with increasing strength of selection, as well as with increasing climate trend and variability. Mutation amplitude had no effects on extinction risk, time to extinction or genetic adaptation to the new climate. Climate trend and strength of selection largely determined the shift of the mean phenotype in the population. The extinction or persistence of the populations in an 'extinction window' of 10 years was well predicted by a simple model including mean population size and mean genetic variance over a 10-year time frame preceding the 'extinction window', although genetic variance had a smaller role than population size in predicting contemporary risk of extinction. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Climate influence on dengue epidemics in Puerto Rico.

PubMed

Jury, Mark R

2008-10-01

The variability of the insect-borne disease dengue in Puerto Rico was studied in relation to climatic variables in the period 1979-2005. Annual and monthly reported dengue cases were compared with precipitation and temperature data. Results show that the incidence of dengue in Puerto Rico was relatively constant over time despite global warming, possibly due to the offsetting effects of declining rainfall, improving health care and little change in population. Seasonal fluctuations of dengue were driven by rainfall increases from May to November. Year-to-year variability in dengue cases was positively related to temperature, but only weakly associated with local rainfall and an index of El Nino Southern Oscillation (ENSO). Climatic conditions were mapped with respect to dengue cases and patterns in high and low years were compared. During epidemics, a low pressure system east of Florida draws warm humid air over the northwestern Caribbean. Long-term trends in past observed and future projected rainfall and temperatures were studied. Rainfall has declined slowly, but temperatures in the Caribbean are rising with the influence of global warming. Thus, dengue may increase in the future, and it will be necessary to anticipate dengue epidemics using climate forecasts, to reduce adverse health impacts.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

PubMed

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

2016-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Uncertainty in Arctic climate projections traced to variability of downwelling longwave radiation

NASA Astrophysics Data System (ADS)

Krikken, Folmer; Bintanja, Richard; Hazeleger, WIlco; van Heerwaarden, Chiel

2017-04-01

The Arctic region has warmed rapidly over the last decades, and this warming is projected to increase. The uncertainty in these projections, i.e. intermodel spread, is however very large and a clear understanding of the sources behind the spread is so far still lacking. Here we use 31 state-of-the-art global climate models to show that variability of May downwelling radiation (DLR) in the models' control climate, primarily located at the land surrounding the Arctic ocean, explains 2/3 of the intermodel spread in projected Arctic warming under the RPC85 scenario. This variability is related to the combined radiative effect of the cloud radiative forcing (CRF) and the albedo response due to snowfall, which varies strongly between the models in these regions. This mechanism dampens or enhances yearly variability of DLR in the control climate but also dampens or enhances the climate response of DLR, sea ice cover and near surface temperature.

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

USGS Publications Warehouse

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

2015-01-01

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

Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate.

PubMed

Ramos, M C; Jones, G V; Yuste, J

2015-12-01

The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27(th), bloom June 17(th), and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

Spatial and temporal variability of cv. Tempranillo phenology and grape quality within the Ribera del Duero DO (Spain) and relationships with climate

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Jones, G. V.; Yuste, J.

2015-12-01

The aim of this work was to analyze spatial phenology and grape quality variability related to the climatic characteristics within the Ribera del Duero Designation of Origin (DO). Twenty plots planted with cv. Tempranillo and distributed within the DO were analyzed for phenology from 2004 to 2013. Grape quality parameters at ripening (berry weight, sugar content, acidity and pH, and anthocyanins) were analyzed in 26 plots for the period 2003-2013. The relationships between phenology and grape parameters with different climatic variables were confirmed with a multivariate analysis. On average, bud break was April 27th, bloom June 17th, and veraison August 12th. However, phenology during the time period showed high variability, with differences between years of up to 21 days for a phenology stage. The earliest dates were observed in dry years (2005, 2006, and to a lesser degree in 2009) while the later phenology dates occurred in the wettest year of the period (2008). High correlations were found between veraison date and temperature variables as well as with precipitation-evapotranspiration recorded during the bloom-veraison period. These effects tended to be higher in the central part of the DO. Grape quality parameters also showed high variability among the dry and the wet years, and the influence of extreme temperatures on color development as well as the effect of available water on acidity were observed.

Investigating the biophysical controls on mass and energy cycling in Southwestern US ecosystems using the New Mexico Elevation Gradient of flux towers.

NASA Astrophysics Data System (ADS)

Krofcheck, D. J.; Morillas, L.; Litvak, M. E.

2014-12-01

Drylands and semi-arid ecosystems cover over 45% of the global landmass. These biomes have been shown to be extremely sensitive to changes in climate, specifically decreases in precipitation and increases in air temperature. Therefore, inter-annual variability in climate has the potential to dramatically impact the carbon budget at regional and global scales. In the Southwestern US, we are in a unique position to investigate these relationships by leveraging eight years of data from the New Mexico Elevation Gradient (NMEG), eight flux towers that span six representative biomes across the semi-arid Southwest. From C4 desert grasslands to subalpine mixed conifer forests, the NMEG flux towers use identical instrumentsand processing, and afford a unique opportunity to explore patterns in biome-specific ecosystem processes and climate sensitivity. Over the last eight years the gradient has experienced climatic variability that span from wet years to an episodic megadrought. Here we report the effects of this extreme inter-annual variability in climate on the ability of semi-arid ecosystems to cycle and store energy and carbon. We also investigated biome-specific patterns of ecosystem light and water use efficiency during a series of wet and dry years, and how these vary in response to air temperature, vapor pressure deficit, evaporative fraction, and precipitation. Our initial results suggest that significant drought reduced the maximum ecosystem assimilation of carbon most at the C4 grasslands, creosote shrublands, juniper savannas, and ponderosa pine forests, with 60%, 50%, 35%, and 50% reduction respectively, relative to a wet year. Ecosystem light use efficiency tends to show the highest maximum values at the low elevation sites as a function of water availability, with the highest annual values consistently at the middle elevation and ponderosa pine sites. Water use efficiency was strongly biome dependent with the middle elevation sites showing the highest efficiencies, and the greatest within year variability at the lower elevation sites, with strong sensitivities to vapor pressure deficit. By quantifying the biome-specific ecosystem processes and functional responses, this network provides valuable insight about how vulnerable this range of semi-arid ecosystems is to future climate scenarios.

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

PubMed

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

2016-01-01

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

Paleoecology and high-resolution paleohydrology of a kettle peatland in upper Michigan

NASA Astrophysics Data System (ADS)

Booth, Robert K.; Jackson, Stephen T.; Gray, Catherine E. D.

2004-01-01

We investigated the developmental and hydrological history of a Sphagnum-dominated, kettle peatland in Upper Michigan using testate amoebae, plant macrofossils, and pollen. Our primary objective was to determine if the paleohydrological record of the peatland represents a record of past climate variability at subcentennial to millennial time scales. To assess the role of millennial-scale climate variability on peatland paleohydrology, we compared the timing of peatland and upland vegetation changes. To investigate the role of higher-frequency climate variability on peatland paleohydrology, we used testate amoebae to reconstruct a high-resolution, hydrologic history of the peatland for the past 5100 years, and compared this record to other regional records of paleoclimate and vegetation. Comparisons revealed coherent patterns of hydrological, vegetational, and climatic changes, suggesting that peatland paleohydrology responded to climate variability at millennial to sub-centennial time scales. Although ombrotrophic peatlands have been the focus of most high-resolution peatland paleoclimate research, paleohydrological records from Sphagnum-dominated, closed-basin peatlands record high-frequency and low-magnitude climatic changes and thus represent a significant source of unexplored paleoclimate data.

The environmental context for the origins of modern human diversity: a synthesis of regional variability in African climate 150,000-30,000 years ago.

PubMed

Blome, Margaret Whiting; Cohen, Andrew S; Tryon, Christian A; Brooks, Alison S; Russell, Joellen

2012-05-01

We synthesize African paleoclimate from 150 to 30 ka (thousand years ago) using 85 diverse datasets at a regional scale, testing for coherence with North Atlantic glacial/interglacial phases and northern and southern hemisphere insolation cycles. Two major determinants of circum-African climate variability over this time period are supported by principal components analysis: North Atlantic sea surface temperature (SST) variations and local insolation maxima. North Atlantic SSTs correlated with the variability found in most circum-African SST records, whereas the variability of the majority of terrestrial temperature and precipitation records is explained by local insolation maxima, particularly at times when solar radiation was intense and highly variable (e.g., 150-75 ka). We demonstrate that climates varied with latitude, such that periods of relatively increased aridity or humidity were asynchronous across the northern, eastern, tropical and southern portions of Africa. Comparisons of the archaeological, fossil, or genetic records with generalized patterns of environmental change based solely on northern hemisphere glacial/interglacial cycles are therefore imprecise. We compare our refined climatic framework to a database of 64 radiometrically-dated paleoanthropological sites to test hypotheses of demographic response to climatic change among African hominin populations during the 150-30 ka interval. We argue that at a continental scale, population and climate changes were asynchronous and likely occurred under different regimes of climate forcing, creating alternating opportunities for migration into adjacent regions. Our results suggest little relation between large scale demographic and climate change in southern Africa during this time span, but strongly support the hypothesis of hominin occupation of the Sahara during discrete humid intervals ~135-115 ka and 105-75 ka. Hominin populations in equatorial and eastern Africa may have been buffered from the extremes of climate change by locally steep altitudinal and rainfall gradients and the complex and variable effects of increased aridity on human habitat suitability in the tropics. Our data are consistent with hominin migrations out of Africa through varying exit points from ~140-80 ka. Copyright © 2012 Elsevier Ltd. All rights reserved.

Pliocene environments

USGS Publications Warehouse

Poore, R.Z.

2007-01-01

The Pliocene spans the interval of Earth history from ca. 5.3 to 1.8 million years ago (Ma). Although details are still debated there is much evidence from continental and oceanic locations indicating that conditions from 5.3 to about 3.0 Ma were often warmer than in modern times in mid- and high latitudes and that climate variability was subdued compared to the Pleistocene. Millennial-scale early Pliocene climate records are dominated by 19–21 thousand years ago (ka) oscillations. Starting at about 3.0 Ma, a long-term trend toward climate cooling and the ice ages of the Pleistocene accelerated. Significant build-up of Northern Hemisphere ice sheets began around 2.9 Ma and climate variability as measured by the oxygen isotope record in deep-sea carbonate microfossils increased. Distinct glacial–interglacial cycles developed in the late Pliocene between 2.9 and 2.7 Ma.

Norwegian fjord sediments reveal NAO related winter temperature and precipitation changes of the past 2800 years

NASA Astrophysics Data System (ADS)

Faust, Johan; Fabian, Karl; Giraudeau, Jacques; Knies, Jochen

2016-04-01

The North Atlantic Oscillation (NAO) is the leading mode of atmospheric circulation variability in the North Atlantic region. Associated shifts of storm tracks, precipitation and temperature patterns affect energy supply and demand, fisheries and agricultural, as well as marine and terrestrial ecological dynamics. Long-term NAO reconstructions are crucial to better understand NAO variability in its response to climate forcing factors, and assess predictability and possible shifts associated with ongoing climate change. Fjord deposits have a great potential for providing high-resolution sedimentary records that reflect local terrestrial and marine processes and, therefore, offer unique opportunities for the investigation of sedimentological and geochemical climatically induced processes. A recent study of instrumental time series revealed NAO as main factor for a strong relation between winter temperature, precipitation and river discharge in central Norway over the past 50 years. Here we use the gained knowledge to establish the first high resolution NAO proxy record from marine sediments. By comparing geochemical measurements from a short sediment core with instrumental data we show that marine primary productivity proxies are sensitive to NAO changes. Conditioned on a stationary relation between our climate proxy and the NAO we establish the first high resolution NAO proxy record (NAO-TFJ) from marine sediments covering the past 2,800 years. The NAO-TFJ shows distinct co-variability with climate changes over Greenland, solar activity and Northern Hemisphere glacier dynamics as well as climatically associated paleo-demographic trends.

Increasing importance of precipitation variability on global livestock grazing lands

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan

NASA Astrophysics Data System (ADS)

Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Liu, Junguo; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Khan, Muhammad Imran

2018-02-01

The northern part of Hindukush Mountains has a perplexing environment due to the influence of adjacent mountains of Himalaya, Karakoram, and Tibetan Plateau. Although reliable evidences of climate change are available; however, a clear knowledge of snow cover dynamics in the context of climate change is missing for this region. In this study, we used various remotely sensed (TRMM precipitation product, while MODIS temperature and snow cover products) and gauge-based datasets to quantify the spatiotemporal variability of climatic variables and their turn effects over the snow cover area (SCA) and river discharge in the Swat watershed, northern Hindukush Mountains, Pakistan. The Mann-Kendall method and Sen's slope estimator were used to estimate the trends in SCA and hydro-climatic variables, at 5% significant level (P = 0.05). Results show that the winter and springs temperatures have increased (at the rate of 0.079 and 0.059 °C year-1, respectively), while decreasing in the summer and autumn (at the rate of 0.049 and 0.070 °C year-1, respectively). Basin-wide increasing tendency of precipitation was identified with a highest increasing rate of 3.563 mm year-1 in the spring season. A decreasing trend in the winter SCA (at the rate of -0.275% year-1) and increasing trends in other seasons were identified. An increasing tendency of river discharge on annual and seasonal scales was also witnessed. The seasonal variations in discharge showed significant positive and negative relationships with temperature and SCA, respectively. We conclude that the future variations in the temperature and SCA in the higher altitudes of the Swat watershed could substantially affect the seasonality of the river discharge. Moreover, it implies that the effect of ongoing global warming on the SCA in the snowmelt-dominated river basins needs to be considered for sustainable regional planning and management of water resources, hydropower production, and downstream irrigation scheduling.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

PubMed Central

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478

Local variability mediates vulnerability of trout populations to land use and climate change

USGS Publications Warehouse

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

PubMed

Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

Development and application of downscaled hydroclimatic predictor variables for use in climate vulnerability and assessment studies

USGS Publications Warehouse

Thorne, James; Boynton, Ryan; Flint, Lorraine; Flint, Alan; N'goc Le, Thuy

2012-01-01

This paper outlines the production of 270-meter grid-scale maps for 14 climate and derivative hydrologic variables for a region that encompasses the State of California and all the streams that flow into it. The paper describes the Basin Characterization Model (BCM), a map-based, mechanistic model used to process the hydrological variables. Three historic and three future time periods of 30 years (1911–1940, 1941–1970, 1971–2000, 2010–2039, 2040–2069, and 2070–2099) were developed that summarize 180 years of monthly historic and future climate values. These comprise a standardized set of fine-scale climate data that were shared with 14 research groups, including the U.S. National Park Service and several University of California groups as part of this project. We present three analyses done with the outputs from the Basin Characterization Model: trends in hydrologic variables over baseline, the most recent 30-year period; a calibration and validation effort that uses measured discharge values from 139 streamgages and compares those to Basin Characterization Model-derived projections of discharge for the same basins; and an assessment of the trends of specific hydrological variables that links historical trend to projected future change under four future climate projections. Overall, increases in potential evapotranspiration dominate other influences in future hydrologic cycles. Increased potential evapotranspiration drives decreasing runoff even under forecasts with increased precipitation, and drives increased climatic water deficit, which may lead to conversion of dominant vegetation types across large parts of the study region as well as have implications for rain-fed agriculture. The potential evapotranspiration is driven by air temperatures, and the Basin Characterization Model permits it to be integrated with a water balance model that can be derived for landscapes and summarized by watershed. These results show the utility of using a process-based model with modules representing different hydrological pathways that can be inter-linked.

Cold Regime Interannual Variability of Primary and Secondary Producer Community Composition in the Southeastern Bering Sea

PubMed Central

Stauffer, Beth A.; Miksis-Olds, Jennifer; Goes, Joaquim I.

2015-01-01

Variability of hydrographic conditions and primary and secondary productivity between cold and warm climatic regimes in the Bering Sea has been the subject of much study in recent years, while interannual variability within a single regime and across multiple trophic levels has been less well-documented. Measurements from an instrumented mooring on the southeastern shelf of the Bering Sea were analyzed for the spring-to-summer transitions within the cold regime years of 2009–2012 to investigate the interannual variability of hydrographic conditions, primary producer biomass, and acoustically-derived secondary producer and consumer abundance and community structure. Hydrographic conditions in 2012 were significantly different than in 2009, 2010, and 2011, driven largely by increased ice extent and thickness, later ice retreat, and earlier stratification of the water column. Primary producer biomass was more tightly coupled to hydrographic conditions in 2012 than in 2009 or 2011, and shallow and mid-column phytoplankton blooms tended to occur independent of one another. There was a high degree of variability in the relationships between different classes of secondary producers and hydrographic conditions, evidence of significant intra-consumer interactions, and trade-offs between different consumer size classes in each year. Phytoplankton blooms stimulated different populations of secondary producers in each year, and summer consumer populations appeared to determine dominant populations in the subsequent spring. Overall, primary producers and secondary producers were more tightly coupled to each other and to hydrographic conditions in the coldest year compared to the warmer years. The highly variable nature of the interactions between the atmospherically-driven hydrographic environment, primary and secondary producers, and within food webs underscores the need to revisit how climatic regimes within the Bering Sea are defined and predicted to function given changing climate scenarios. PMID:26110822

Cold Regime interannual variability of primary and secondary producer community composition in the southeastern Bering Sea.

PubMed

Stauffer, Beth A; Miksis-Olds, Jennifer; Goes, Joaquim I

2015-01-01

Variability of hydrographic conditions and primary and secondary productivity between cold and warm climatic regimes in the Bering Sea has been the subject of much study in recent years, while interannual variability within a single regime and across multiple trophic levels has been less well-documented. Measurements from an instrumented mooring on the southeastern shelf of the Bering Sea were analyzed for the spring-to-summer transitions within the cold regime years of 2009-2012 to investigate the interannual variability of hydrographic conditions, primary producer biomass, and acoustically-derived secondary producer and consumer abundance and community structure. Hydrographic conditions in 2012 were significantly different than in 2009, 2010, and 2011, driven largely by increased ice extent and thickness, later ice retreat, and earlier stratification of the water column. Primary producer biomass was more tightly coupled to hydrographic conditions in 2012 than in 2009 or 2011, and shallow and mid-column phytoplankton blooms tended to occur independent of one another. There was a high degree of variability in the relationships between different classes of secondary producers and hydrographic conditions, evidence of significant intra-consumer interactions, and trade-offs between different consumer size classes in each year. Phytoplankton blooms stimulated different populations of secondary producers in each year, and summer consumer populations appeared to determine dominant populations in the subsequent spring. Overall, primary producers and secondary producers were more tightly coupled to each other and to hydrographic conditions in the coldest year compared to the warmer years. The highly variable nature of the interactions between the atmospherically-driven hydrographic environment, primary and secondary producers, and within food webs underscores the need to revisit how climatic regimes within the Bering Sea are defined and predicted to function given changing climate scenarios.

Climate change is likely to worsen the public health threat of diarrheal disease in Botswana.

PubMed

Alexander, Kathleen A; Carzolio, Marcos; Goodin, Douglas; Vance, Eric

2013-03-26

Diarrheal disease is an important health challenge, accounting for the majority of childhood deaths globally. Climate change is expected to increase the global burden of diarrheal disease but little is known regarding climate drivers, particularly in Africa. Using health data from Botswana spanning a 30-year period (1974-2003), we evaluated monthly reports of diarrheal disease among patients presenting to Botswana health facilities and compared this to climatic variables. Diarrheal case incidence presents with a bimodal cyclical pattern with peaks in March (ANOVA p < 0.001) and October (ANOVA p < 0.001) in the wet and dry season, respectively. There is a strong positive autocorrelation (p < 0.001) in the number of reported diarrhea cases at the one-month lag level. Climatic variables (rainfall, minimum temperature, and vapor pressure) predicted seasonal diarrheal with a one-month lag in variables (p < 0.001). Diarrheal case incidence was highest in the dry season after accounting for other variables, exhibiting on average a 20% increase over the yearly mean (p < 0.001). Our analysis suggests that forecasted climate change increases in temperature and decreases in precipitation may increase dry season diarrheal disease incidence with hot, dry conditions starting earlier and lasting longer. Diarrheal disease incidence in the wet season is likely to decline. Our results identify significant health-climate interactions, highlighting the need for an escalated public health focus on controlling diarrheal disease in Botswana. Study findings have application to other arid countries in Africa where diarrheal disease is a persistent public health problem.

Climate Change is Likely to Worsen the Public Health Threat of Diarrheal Disease in Botswana

PubMed Central

Alexander, Kathleen A.; Carzolio, Marcos; Goodin, Douglas; Vance, Eric

2013-01-01

Diarrheal disease is an important health challenge, accounting for the majority of childhood deaths globally. Climate change is expected to increase the global burden of diarrheal disease but little is known regarding climate drivers, particularly in Africa. Using health data from Botswana spanning a 30-year period (1974–2003), we evaluated monthly reports of diarrheal disease among patients presenting to Botswana health facilities and compared this to climatic variables. Diarrheal case incidence presents with a bimodal cyclical pattern with peaks in March (ANOVA p < 0.001) and October (ANOVA p < 0.001) in the wet and dry season, respectively. There is a strong positive autocorrelation (p < 0.001) in the number of reported diarrhea cases at the one-month lag level. Climatic variables (rainfall, minimum temperature, and vapor pressure) predicted seasonal diarrheal with a one-month lag in variables (p < 0.001). Diarrheal case incidence was highest in the dry season after accounting for other variables, exhibiting on average a 20% increase over the yearly mean (p < 0.001). Our analysis suggests that forecasted climate change increases in temperature and decreases in precipitation may increase dry season diarrheal disease incidence with hot, dry conditions starting earlier and lasting longer. Diarrheal disease incidence in the wet season is likely to decline. Our results identify significant health-climate interactions, highlighting the need for an escalated public health focus on controlling diarrheal disease in Botswana. Study findings have application to other arid countries in Africa where diarrheal disease is a persistent public health problem. PMID:23531489

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

PubMed

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

2018-01-10

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

Integrating inter- and intra-annual tree-ring width, carbon isotopes and anatomy: responses to climate variability in a temperate oak forest

NASA Astrophysics Data System (ADS)

Granda, Elena; Bazot, Stéphane; Fresneau, Chantal; Boura, Anaïs; Faccioni, Georgia; Damesin, Claire

2015-04-01

While many forests are experiencing strong tree declines due to climate change in temperate ecosystems, others nearby to those declining show no apparent signs of decline. This could be due to particular microsite conditions or, for instance, to a higher plasticity of given traits that allow a better performance under stressful conditions. We studied oak functional mechanisms (Quercus petraea) leading to the apparently healthy status of the forest and their relation to the observed climatic variability. This study was conducted in the Barbeau Forest (northern France), where cores from mature trees were collected. Three types of functional traits (secondary growth, physiological variables - δ13C and derived Δ13C and iWUE- and several anatomical ones -e.g. vessel area, density-) were recorded for each ring for the 1991-2011 period, distinguishing EW from LW in all measured traits. Among the three types of functional traits, those related to growth experienced the highest variability both between years and between individuals, followed by anatomical and physiological ones. Secondary growth maintained a constant trend during the study period. Instead, ring, EW and LW δ13C slightly declined from 1991 to 2011. Additional intra-ring δ13C analyses allowed for a more detailed understanding of the seasonal dynamics within each year. In particular, the year 2007 (an especially favorable climatic year during the growing season) showed the lowest δ13C values during the EW-LW transition for the whole study period. Inter-annual anatomical traits varied in their responses, but in general, no temporal trends were found. The results from structural equation modeling (SEM) showed direct relationships of seasonal climate and growth, as well as indirect relationships mediated by anatomical and physiological traits. We further discuss the implications of these results on future forest responses to ongoing climate changes.

Does the weather influence public opinion about climate change?

NASA Astrophysics Data System (ADS)

Donner, S. D.; McDaniel, J.

2010-12-01

Public opinion in North America about the science of anthropogenic climate change and the motivation for policy action has been variable over the past twenty years. The trends in public opinion over time have been attributed the general lack of pressing public concern about climate change to a range of political, economic and psychological factors. One driving force behind the variability in polling data from year to year may be the weather itself. The difference between what we “expect” - the climate - and what we “get” - the weather - can be a major source of confusion and obfuscation in the public discourse about climate change. For example, reaction to moderate global temperatures in 2007 and 2008 may have helped prompt the spread of a “global cooling” meme in the public and the news media. At the same time, a decrease in the belief in the science of climate change and the need for action has been noted in opinion polls. This study analyzes the relationship between public opinion about climate change and the weather in the U.S. since the mid-1980s using historical polling data from several major organizations (e.g. Gallup, Pew, Harris Interactive, ABC News), historical monthly air temperature (NCDC) and a survey of opinion articles from major U.S. newspapers (Washington Post, New York Times, Wall Street Journal, Houston Chronicle, USA Today). Seasonal and annual monthly temperature anomalies for the northeastern U.S and the continental U.S are compared with available national opinion data for three general categories of questions: i) Is the climate warming?, ii) Is the observed warming due to human activity?, and iii) Are you concerned about climate change? The variability in temperature and public opinion over time is also compared with the variability in the fraction of opinion articles in the newspapers (n ~ 7000) which express general agreement or disagreement with IPCC Summary for Policymakers consensus statements on climate change (“most of the observed increase in global average temperature is very likely to be due to the observed increase in anthropogenic greenhouse gas concentrations”). The results reveal a possible link between opinion leaders, particularly in the northeastern U.S, public confusion about the difference between weather and climate, and the evolution of U.S. public opinion about climate change.

Landscape structure and climate influences on hydrologic response

NASA Astrophysics Data System (ADS)

Nippgen, Fabian; McGlynn, Brian L.; Marshall, Lucy A.; Emanuel, Ryan E.

2011-12-01

Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfall-runoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.

Inability of CMIP5 Climate Models to Simulate Recent Multi-decadal Climate Change in the Tropical Pacific.

NASA Astrophysics Data System (ADS)

Power, S.; Delage, F.; Kociuba, G.; Wang, G.; Smith, I.

2017-12-01

Observed 15-year surface temperature trends beginning 1998 or later have attracted a great deal of interest because of an apparent slowdown in the rate of global warming, and contrasts between climate model simulations and observations of such trends. Many studies have addressed the statistical significance of these relatively short trends, whether they indicate a possible bias in models and the implications for global warming generally. Here we analyse historical and projected changes in 38 CMIP5 climate models. All of the models simulate multi-decadal warming in the Pacific over the past half-century that exceeds observed values. This stark difference cannot be fully explained by observed, internal multi-decadal climate variability, even if allowance is made for an apparent tendency for models to underestimate internal multi-decadal variability in the Pacific. We also show that CMIP5 models are not able to simulate the magnitude of the strengthening of the Walker Circulation over the past thirty years. Some of the reasons for these major shortcomings in the ability of models to simulate multi-decadal variability in the Pacific, and the impact these findings have on our confidence in global 21st century projections, will be discussed.

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

Did Climate Change Cause the 2012-2014 California Drought?

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

US Climate Variability and Predictability Project

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

Patterson, Mike

The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less

US Climate Variability and Predictability (CLIVAR) Project- Final Report

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

Patterson, Mike

The US CLIVAR Project Office administers the US CLIVAR Program with its mission to advance understanding and prediction of climate variability and change across timescales with an emphasis on the role of the ocean and its interaction with other elements of the Earth system. The Project Office promotes and facilitates scientific collaboration within the US and international climate and Earth science communities, addressing priority topics from subseasonal to centennial climate variability and change; the global energy imbalance; the ocean’s role in climate, water, and carbon cycles; climate and weather extremes; and polar climate changes. This project provides essential one-year supportmore » of the Project Office, enabling the participation of US scientists in the meetings of the US CLIVAR bodies that guide scientific planning and implementation, including the scientific steering committee that establishes program goals and evaluates progress of activities to address them, the science team of funded investigators studying the ocean overturning circulation in the Atlantic, and two working groups tackling the priority research topics of Arctic change influence on midlatitude climate and weather extremes and the decadal-scale widening of the tropical belt.« less

Individual-scale inference to anticipate climate-change vulnerability of biodiversity.

PubMed

Clark, James S; Bell, David M; Kwit, Matthew; Stine, Anne; Vierra, Ben; Zhu, Kai

2012-01-19

Anticipating how biodiversity will respond to climate change is challenged by the fact that climate variables affect individuals in competition with others, but interest lies at the scale of species and landscapes. By omitting the individual scale, models cannot accommodate the processes that determine future biodiversity. We demonstrate how individual-scale inference can be applied to the problem of anticipating vulnerability of species to climate. The approach places climate vulnerability in the context of competition for light and soil moisture. Sensitivities to climate and competition interactions aggregated from the individual tree scale provide estimates of which species are vulnerable to which variables in different habitats. Vulnerability is explored in terms of specific demographic responses (growth, fecundity and survival) and in terms of the synthetic response (the combination of demographic rates), termed climate tracking. These indices quantify risks for individuals in the context of their competitive environments. However, by aggregating in specific ways (over individuals, years, and other input variables), we provide ways to summarize and rank species in terms of their risks from climate change.

Timing and climate forcing of volcanic eruptions for the past 2,500 years.

PubMed

Sigl, M; Winstrup, M; McConnell, J R; Welten, K C; Plunkett, G; Ludlow, F; Büntgen, U; Caffee, M; Chellman, N; Dahl-Jensen, D; Fischer, H; Kipfstuhl, S; Kostick, C; Maselli, O J; Mekhaldi, F; Mulvaney, R; Muscheler, R; Pasteris, D R; Pilcher, J R; Salzer, M; Schüpbach, S; Steffensen, J P; Vinther, B M; Woodruff, T E

2015-07-30

Volcanic eruptions contribute to climate variability, but quantifying these contributions has been limited by inconsistencies in the timing of atmospheric volcanic aerosol loading determined from ice cores and subsequent cooling from climate proxies such as tree rings. Here we resolve these inconsistencies and show that large eruptions in the tropics and high latitudes were primary drivers of interannual-to-decadal temperature variability in the Northern Hemisphere during the past 2,500 years. Our results are based on new records of atmospheric aerosol loading developed from high-resolution, multi-parameter measurements from an array of Greenland and Antarctic ice cores as well as distinctive age markers to constrain chronologies. Overall, cooling was proportional to the magnitude of volcanic forcing and persisted for up to ten years after some of the largest eruptive episodes. Our revised timescale more firmly implicates volcanic eruptions as catalysts in the major sixth-century pandemics, famines, and socioeconomic disruptions in Eurasia and Mesoamerica while allowing multi-millennium quantification of climate response to volcanic forcing.

Timing and climate forcing of volcanic eruptions for the past 2,500 years

NASA Astrophysics Data System (ADS)

Sigl, M.; Winstrup, M.; McConnell, J. R.; Welten, K. C.; Plunkett, G.; Ludlow, F.; Büntgen, U.; Caffee, M.; Chellman, N.; Dahl-Jensen, D.; Fischer, H.; Kipfstuhl, S.; Kostick, C.; Maselli, O. J.; Mekhaldi, F.; Mulvaney, R.; Muscheler, R.; Pasteris, D. R.; Pilcher, J. R.; Salzer, M.; Schüpbach, S.; Steffensen, J. P.; Vinther, B. M.; Woodruff, T. E.

2015-07-01

Volcanic eruptions contribute to climate variability, but quantifying these contributions has been limited by inconsistencies in the timing of atmospheric volcanic aerosol loading determined from ice cores and subsequent cooling from climate proxies such as tree rings. Here we resolve these inconsistencies and show that large eruptions in the tropics and high latitudes were primary drivers of interannual-to-decadal temperature variability in the Northern Hemisphere during the past 2,500 years. Our results are based on new records of atmospheric aerosol loading developed from high-resolution, multi-parameter measurements from an array of Greenland and Antarctic ice cores as well as distinctive age markers to constrain chronologies. Overall, cooling was proportional to the magnitude of volcanic forcing and persisted for up to ten years after some of the largest eruptive episodes. Our revised timescale more firmly implicates volcanic eruptions as catalysts in the major sixth-century pandemics, famines, and socioeconomic disruptions in Eurasia and Mesoamerica while allowing multi-millennium quantification of climate response to volcanic forcing.

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.

Adaptation with climate uncertainty: An examination of agricultural land use in the United States

USGS Publications Warehouse

Mu, Jianhong E.; McCarl, Bruce A.; Sleeter, Benjamin M.; Abatzoglou, John T.; Zhang, Hongliang

2018-01-01

This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important as that of inter-annual climate variability. Projecting into the future, we find projected climate change will lead to an expansion in crop land share across the northern and interior western United States with decreases in the south. We also find that grazing land share increases in southern regions and Inland Pacific Northwest and declines in the northern areas. However, the extent to which the adaptation potential would be is dependent on the climate model, emission scenario and time horizon under consideration.

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD

PubMed Central

Lorenz, David J.; Nieto-Lugilde, Diego; Blois, Jessica L.; Fitzpatrick, Matthew C.; Williams, John W.

2016-01-01

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950–2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850–2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity. PMID:27377537

Downscaled and debiased climate simulations for North America from 21,000 years ago to 2100AD.

PubMed

Lorenz, David J; Nieto-Lugilde, Diego; Blois, Jessica L; Fitzpatrick, Matthew C; Williams, John W

2016-07-05

Increasingly, ecological modellers are integrating paleodata with future projections to understand climate-driven biodiversity dynamics from the past through the current century. Climate simulations from earth system models are necessary to this effort, but must be debiased and downscaled before they can be used by ecological models. Downscaling methods and observational baselines vary among researchers, which produces confounding biases among downscaled climate simulations. We present unified datasets of debiased and downscaled climate simulations for North America from 21 ka BP to 2100AD, at 0.5° spatial resolution. Temporal resolution is decadal averages of monthly data until 1950AD, average climates for 1950-2005 AD, and monthly data from 2010 to 2100AD, with decadal averages also provided. This downscaling includes two transient paleoclimatic simulations and 12 climate models for the IPCC AR5 (CMIP5) historical (1850-2005), RCP4.5, and RCP8.5 21st-century scenarios. Climate variables include primary variables and derived bioclimatic variables. These datasets provide a common set of climate simulations suitable for seamlessly modelling the effects of past and future climate change on species distributions and diversity.

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

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

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

Multi-annual modes in the 20th century temperature variability in reanalyses and CMIP5 models

NASA Astrophysics Data System (ADS)

Järvinen, Heikki; Seitola, Teija; Silén, Johan; Räisänen, Jouni

2016-11-01

A performance expectation is that Earth system models simulate well the climate mean state and the climate variability. To test this expectation, we decompose two 20th century reanalysis data sets and 12 CMIP5 model simulations for the years 1901-2005 of the monthly mean near-surface air temperature using randomised multi-channel singular spectrum analysis (RMSSA). Due to the relatively short time span, we concentrate on the representation of multi-annual variability which the RMSSA method effectively captures as separate and mutually orthogonal spatio-temporal components. This decomposition is a unique way to separate statistically significant quasi-periodic oscillations from one another in high-dimensional data sets.The main results are as follows. First, the total spectra for the two reanalysis data sets are remarkably similar in all timescales, except that the spectral power in ERA-20C is systematically slightly higher than in 20CR. Apart from the slow components related to multi-decadal periodicities, ENSO oscillations with approximately 3.5- and 5-year periods are the most prominent forms of variability in both reanalyses. In 20CR, these are relatively slightly more pronounced than in ERA-20C. Since about the 1970s, the amplitudes of the 3.5- and 5-year oscillations have increased, presumably due to some combination of forced climate change, intrinsic low-frequency climate variability, or change in global observing network. Second, none of the 12 coupled climate models closely reproduce all aspects of the reanalysis spectra, although some models represent many aspects well. For instance, the GFDL-ESM2M model has two nicely separated ENSO periods although they are relatively too prominent as compared with the reanalyses. There is an extensive Supplement and YouTube videos to illustrate the multi-annual variability of the data sets.

Synchronous multi-decadal climate variability of the whole Pacific areas revealed in tree rings since 1567

NASA Astrophysics Data System (ADS)

Fang, Keyan; Cook, Edward; Guo, Zhengtang; Chen, Deliang; Ou, Tinghai; Zhao, Yan

2018-02-01

Oceanic and atmospheric patterns play a crucial role in modulating climate variability from interannual to multi-decadal timescales by causing large-scale co-varying climate changes. The brevity of the existing instrumental records hinders the ability to recognize climate patterns before the industrial era, which can be alleviated using proxies. Unfortunately, proxy based reconstructions of oceanic and atmospheric modes of the past millennia often have modest agreements with each other before the instrumental period, raising questions about the robustness of the reconstructions. To ensure the stability of climate signals in proxy data through time, we first identified tree-ring datasets from distant regions containing coherent variations in Asia and North America, and then interpreted their climate information. We found that the multi-decadal covarying climate patterns of the middle and high latitudinal regions around the northern Pacific Ocean agreed quite well with the climate reconstructions of the tropical and southern Pacific areas. This indicates a synchronous variability at the multi-decadal timescale of the past 430 years for the entire Pacific Ocean. This pattern is closely linked to the dominant mode of the Pacific sea surface temperature (SST) after removing the warming trend. This Pacific multi-decadal SST variability resembles the Interdecadal Pacific Oscillation.

Climatic and geologic controls on the piezometry of the Querença-Silves karst aquifer, Algarve (Portugal)

NASA Astrophysics Data System (ADS)

Neves, Maria C.; Costa, Luis; Monteiro, José P.

2016-06-01

Karst aquifers in semi-arid regions, like Querença-Silves (Portugal), are particularly vulnerable to climate variability. For the first time in this region, the temporal structure of a groundwater-level time series (1985-2010) was explored using the continuous wavelet transform. The investigation focused on a set of four piezometers, two at each side of the S. Marcos-Quarteira fault, to demonstrate how each of the two sectors of the aquifer respond to climate-induced patterns. Singular spectral analysis applied to an extended set of piezometers enabled identification of several quasi-periodic modes of variability, with periods of 6.5, 4.3, 3.2 and 2.6 years, which can be explained by low-frequency climate patterns. The geologic forcing accounts for ~15 % of the differential variability between the eastern and western sectors of the aquifer. The western sector displays spatially homogenous piezometric variations, large memory effects and low-pass filtering characteristics, which are consistent with relatively large and uniform values of water storage capacity and transmissivity properties. In this sector, the 6.5-year mode of variability accounts for ~70 % of the total variance of the groundwater levels. The eastern sector shows larger spatial and temporal heterogeneity, is more reactive to short-term variations, and is less influenced by the low-frequency components related to climate patterns.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

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.

ENSO in a warming world: interannual climate variability in the early Miocene Southern Hemisphere

NASA Astrophysics Data System (ADS)

Fox, Bethany; Wilson, Gary; Lee, Daphne

2016-04-01

The El Niño - Southern Oscillation (ENSO) is the dominant source of interannual variability in the modern-day climate system. ENSO is a quasi-periodic cycle with a recurrence interval of 2-8 years. A major question in modern climatology is how ENSO will respond to increased climatic warmth. ENSO-like (2-8 year) cycles have been detected in many palaeoclimate records for the Holocene. However, the temporal resolution of pre-Quaternary palaeoclimate archives is generally too coarse to investigate ENSO-scale variability. We present a 100-kyr record of ENSO-like variability during the second half of the Oligocene/Miocene Mi-1 event, a period of increasing global temperatures and Antarctic deglaciation (~23.032-2.93 Ma). This record is drawn from an annually laminated lacustrine diatomite from southern New Zealand, a region strongly affected by ENSO in the present day. The diatomite consists of seasonal alternations of light (diatom bloom) and dark (low diatom productivity) layers. Each light-dark couplet represents one year's sedimentation. Light-dark couplet thickness is characterised by ENSO-scale variability. We use high-resolution (sub-annual) measurements of colour spectra to detect couplet thickness variability. Wavelet analysis indicates that absolute values are modulated by orbital cycles. However, when orbital effects are taken into account, ENSO-like variability occurs throughout the entire depositional period, with no clear increase or reduction in relation to Antarctic deglaciation and increasing global warmth.

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.

Rates of change in climatic niches in plant and animal populations are much slower than projected climate change

PubMed Central

Jezkova, Tereza

2016-01-01

Climate change may soon threaten much of global biodiversity. A critical question is: can species undergo niche shifts of sufficient speed and magnitude to persist within their current geographic ranges? Here, we analyse niche shifts among populations within 56 plant and animal species using time-calibrated trees from phylogeographic studies. Across 266 phylogeographic groups analysed, rates of niche change were much slower than rates of projected climate change (mean difference > 200 000-fold for temperature variables). Furthermore, the absolute niche divergence among populations was typically lower than the magnitude of projected climate change over the next approximately 55 years for relevant variables, suggesting the amount of change needed to persist may often be too great, even if these niche shifts were instantaneous. Rates were broadly similar between plants and animals, but especially rapid in some arthropods, birds and mammals. Rates for temperature variables were lower at lower latitudes, further suggesting that tropical species may be especially vulnerable to climate change. PMID:27881748

Rates of change in climatic niches in plant and animal populations are much slower than projected climate change.

PubMed

Jezkova, Tereza; Wiens, John J

2016-11-30

Climate change may soon threaten much of global biodiversity. A critical question is: can species undergo niche shifts of sufficient speed and magnitude to persist within their current geographic ranges? Here, we analyse niche shifts among populations within 56 plant and animal species using time-calibrated trees from phylogeographic studies. Across 266 phylogeographic groups analysed, rates of niche change were much slower than rates of projected climate change (mean difference > 200 000-fold for temperature variables). Furthermore, the absolute niche divergence among populations was typically lower than the magnitude of projected climate change over the next approximately 55 years for relevant variables, suggesting the amount of change needed to persist may often be too great, even if these niche shifts were instantaneous. Rates were broadly similar between plants and animals, but especially rapid in some arthropods, birds and mammals. Rates for temperature variables were lower at lower latitudes, further suggesting that tropical species may be especially vulnerable to climate change. © 2016 The Author(s).

El-Niño/Southern Oscillation (ENSO) influences on monthly NO 3 load and concentration, stream flow and precipitation in the Little River Watershed, Tifton, Georgia (GA)

NASA Astrophysics Data System (ADS)

Keener, V. W.; Feyereisen, G. W.; Lall, U.; Jones, J. W.; Bosch, D. D.; Lowrance, R.

2010-02-01

SummaryAs climate variability increases, it is becoming increasingly critical to find predictable patterns that can still be identified despite overall uncertainty. The El-Niño/Southern Oscillation is the best known pattern. Its global effects on weather, hydrology, ecology and human health have been well documented. Climate variability manifested through ENSO has strong effects in the southeast United States, seen in precipitation and stream flow data. However, climate variability may also affect water quality in nutrient concentrations and loads, and have impacts on ecosystems, health, and food availability in the southeast. In this research, we establish a teleconnection between ENSO and the Little River Watershed (LRW), GA., as seen in a shared 3-7 year mode of variability for precipitation, stream flow, and nutrient load time series. Univariate wavelet analysis of the NINO 3.4 index of sea surface temperature (SST) and of precipitation, stream flow, NO 3 concentration and load time series from the watershed was used to identify common signals. Shared 3-7 year modes of variability were seen in all variables, most strongly in precipitation, stream flow and nutrient load in strong El Niño years. The significance of shared 3-7 year periodicity over red noise with 95% confidence in SST and precipitation, stream flow, and NO 3 load time series was confirmed through cross-wavelet and wavelet-coherence transforms, in which common high power and co-variance were computed for each set of data. The strongest 3-7 year shared power was seen in SST and stream flow data, while the strongest co-variance was seen in SST and NO 3 load data. The strongest cross-correlation was seen as a positive value between the NINO 3.4 and NO 3 load with a three-month lag. The teleconnection seen in the LRW between the NINO 3.4 index and precipitation, stream flow, and NO 3 load can be utilized in a model to predict monthly nutrient loads based on short-term climate variability, facilitating management in high risk seasons.

Old World megadroughts and pluvials during the Common Era.

PubMed

Cook, Edward R; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R; Büntgen, Ulf; Frank, David; Krusic, Paul J; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian

2015-11-01

Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other "Old World" climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the "Old World Drought Atlas" (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability.

Old World megadroughts and pluvials during the Common Era

PubMed Central

Cook, Edward R.; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R.; Büntgen, Ulf; Frank, David; Krusic, Paul J.; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M.; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian

2015-01-01

Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability. PMID:26601136

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

USGS Publications Warehouse

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke; Korhonen, Johanna; Yasuyuki Aono,

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

PubMed Central

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke A.; Korhonen, Johanna; Aono, Yasuyuki

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality. PMID:27113125

Detection and Attribution of Temperature Trends in the Presence of Natural Variability

NASA Astrophysics Data System (ADS)

Wallace, J. M.

2014-12-01

The fingerprint of human-induced global warming stands out clearly above the noise In the time series of global-mean temperature, but not local temperature. At extratropical latitudes over land the standard error of 50-year linear temperature trends at a fixed point is as large as the cumulative rise in global-mean temperature over the past century. Much of the samping variability in local temperature trends is "dynamically-induced", i.e., attributable to the fact that the seasonally-varying mean circulation varies substantially from one year to the next and anomalous circulation patterns are generally accompanied by anomalous temperature patterns. In the presence of such large sampling variability it is virtually impossible to identify the spatial signature of greenhouse warming based on observational data or to partition observed local temperature trends into natural and human-induced components. It follows that previous IPCC assessments, which have focused on the deterministic signature of human-induced climate change, are inherently limited as to what they can tell us about the attribution of the past record of local temperature change or about how much the temperature at a particular place is likely to rise in the next few decades in response to global warming. To obtain more informative assessments of regional and local climate variability and change it will be necessary to take a probabilistic approach. Just as the use of the ensembles has contributed to more informative extended range weather predictions, large ensembles of climate model simulations can provide a statistical context for interpreting observed climate change and for framing projections of future climate. For some purposes, statistics relating to the interannual variability in the historical record can serve as a surrogate for statistics relating to the diversity of climate change scenarios in large ensembles.

2000 Years of Drought Variability in Inner Asia from Tree Rings

NASA Astrophysics Data System (ADS)

Hessl, A. E.; Pederson, N.; Anchukaitis, K. J.; Leland, C.; Byambasuren, O.; Nachin, B.; Andreu-Hayles, L.

2015-12-01

Understanding connections between climate, ecosystems, and society during historical and modern climatic transitions requires annual resolution records with high fidelity climate signals. In semi-arid regions, high temperatures are projected to increase the frequency, duration, and severity of droughts in coming decades. Between 1996-2014, Mongolia experienced an extended drought that coincided with a transition away from pastoralism as thousands of families lost their herds and migrated to informal urban settlements. Because Mongolia's climate is highly variable, it is difficult to place recent climatic extremes and associated social and ecological change in context without long records of climatic variability. Here we ask: how extreme was the 21st century drought in the last 2000 years? We present two 2000 year long tree-ring reconstructions of warm-season drought, derived from live and dead Siberian pine (Pinus sibirica) trees from two lava flows in central Mongolia. Trees growing on the lava today are stunted and widely spaced, occurring on microsites with little to no soil development. These trees are water-stressed and their radial growth is correlated with both soil water availability (scPDSI) and grassland productivity (Normalized Difference Vegetation Index (NDVI)). To contextualize the severity of recent droughts and to explore potential forcing factors, we compare recent drought persistence to the distribution of events in the past and perform long control runs of GFDL climate model. Our reconstructions, calibrated and validated on instrumental June-August scPDSI (1959-2009) account for >55% of the variability in the regional scPDSI when >70% of the annual rainfall occurs. Our tree-ring data combined with existing reconstructions of temperature, meteorological data, and model results suggest that the early 21st century drought was the hottest and one of the most persistent droughts in the last 2000 years. These dry conditions were occurred with reductions in NPP of grasslands and loss of lake area. Our results are consistent with model projections of warming in Inner Asia but suggest that future warming may overwhelm increases in precipitation leading to similar "heat droughts", with potentially severe ecological and social consequences for Mongolia.

Current Climate Variability & Change

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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

PubMed

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

2016-08-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Quantifying the Hydrologic Effect of Climate Variability in the Lower Colorado Basin

NASA Astrophysics Data System (ADS)

Switanek, M.; Troch, P. A.

2007-12-01

Regional climate patterns are driven in large part by ocean states and associated atmospheric circulations, but modified through feedbacks from land surface conditions. The latter defines the climate elasticity of a river basin. Many regions that lie between semi-arid and semi-humid zones with seasonal rainfall, for instance, experience prolonged periods of wet and dry spells. Understanding the triggers that bring a river basin from one state (e.g. wet period of late 90s in the Colorado basin) abruptly to another state (multi-year drought initiated in 2001 to present) is what motivates the present study. Our research methodology investigates the causes of regional climate variability and its effect on hydrologic response. By correlating, using different monthly time lags, sea surface temperatures (SST) and sea level pressures (SLP) with basin averaged precipitation and surface temperature, we determine the most influential regions of the Pacific Ocean on lower Colorado climate variability. Using the most correlated data for each month, we derive precipitation and temperature distributions under similar conditions to that of the El Niño Southern Oscillation (ENSO). We compare the distributions of the climatic data, given ENSO constraints on SST and SLP, to the distributions considering non-ENSO years. Finally, we use observed stream flows and climatic data to determine the basin's climate elasticity. This allows us to quantitatively translate the predicted regional climate effects of ENSO on hydrologic response. Our presentation will use data for the Little Colorado as an example to demonstrate the procedure and produce preliminary results.

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.

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Climate SPHINX: High-resolution present-day and future climate simulations with an improved representation of small-scale variability

NASA Astrophysics Data System (ADS)

Davini, Paolo; von Hardenberg, Jost; Corti, Susanna; Subramanian, Aneesh; Weisheimer, Antje; Christensen, Hannah; Juricke, Stephan; Palmer, Tim

2016-04-01

The PRACE Climate SPHINX project investigates the sensitivity of climate simulations to model resolution and stochastic parameterization. The EC-Earth Earth-System Model is used to explore the impact of stochastic physics in 30-years climate integrations as a function of model resolution (from 80km up to 16km for the atmosphere). The experiments include more than 70 simulations in both a historical scenario (1979-2008) and a climate change projection (2039-2068), using RCP8.5 CMIP5 forcing. A total amount of 20 million core hours will be used at end of the project (March 2016) and about 150 TBytes of post-processed data will be available to the climate community. Preliminary results show a clear improvement in the representation of climate variability over the Euro-Atlantic following resolution increase. More specifically, the well-known atmospheric blocking negative bias over Europe is definitely resolved. High resolution runs also show improved fidelity in representation of tropical variability - such as the MJO and its propagation - over the low resolution simulations. It is shown that including stochastic parameterization in the low resolution runs help to improve some of the aspects of the MJO propagation further. These findings show the importance of representing the impact of small scale processes on the large scale climate variability either explicitly (with high resolution simulations) or stochastically (in low resolution simulations).

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

PubMed Central

Taylor, P. H.; Gibson, R.

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Modeling the impact of climate variability on diarrhea-associated diseases in Taiwan (1996-2007).

PubMed

Chou, Wei-Chun; Wu, Jiunn-Lin; Wang, Yu-Chun; Huang, Hsin; Sung, Fung-Chang; Chuang, Chun-Yu

2010-12-01

Diarrhea is an important public health problem in Taiwan. Climatic changes and an increase in extreme weather events (extreme heat, drought or rainfalls) have been strongly linked to the incidence of diarrhea-associated disease. This study investigated and quantified the relationship between climate variations and diarrhea-associated morbidity in subtropical Taiwan. Specifically, this study analyzed the local climatic variables and the number of diarrhea-associated infection cases from 1996 to 2007. This study applied a climate variation-guided Poisson regression model to predict the dynamics of diarrhea-associated morbidity. The proposed model allows for climate factors (relative humidity, maximum temperature and the numbers of extreme rainfall), autoregression, long-term trends and seasonality, and a lag-time effect. Results indicated that the maximum temperature and extreme rainfall days were strongly related to diarrhea-associated morbidity. The impact of maximum temperature on diarrhea-associated morbidity appeared primarily among children (0-14years) and older adults (40-64years), and had less of an effect on adults (15-39years). Otherwise, relative humidity and extreme rainfall days significantly contributed to the diarrhea-associated morbidity in adult. This suggested that children and older adults were the most susceptible to diarrhea-associated morbidity caused by climatic variation. Because climatic variation contributed to diarrhea morbidity in Taiwan, it is necessary to develop an early warning system based on the climatic variation information for disease control management. Copyright © 2010 Elsevier B.V. All rights reserved.

Climatic change by cloudiness linked to the spatial variability of sea surface temperatures

NASA Technical Reports Server (NTRS)

Otterman, J.

1975-01-01

An active role in modifying the earth's climate is suggested for low cloudiness over the circumarctic oceans. Such cloudiness, linked to the spatial differences in ocean surface temperatures, was studied. The temporal variations from year to year of ocean temperature patterns can be pronounced and therefore, the low cloudiness over this region should also show strong temporal variations, affecting the albedo of the earth and therefore the climate. Photographs are included.

Understanding north-western Mediterranean climate variability: a multi-proxy and multi-sequence approach based on wavelet analysis.

NASA Astrophysics Data System (ADS)

Azuara, Julien; Lebreton, Vincent; Jalali, Bassem; Sicre, Marie-Alexandrine; Sabatier, Pierre; Dezileau, Laurent; Peyron, Odile; Frigola, Jaime; Combourieu-Nebout, Nathalie

2017-04-01

Forcings and physical mechanisms underlying Holocene climate variability still remain poorly understood. Comparison of different paleoclimatic reconstructions using spectral analysis allows to investigate their common periodicities and helps to understand the causes of past climate changes. Wavelet analysis applied on several proxy time series from the Atlantic domain already revealed the first key-issues on the origin of Holocene climate variability. However the differences in duration, resolution and variance between the time-series are important issues for comparing paleoclimatic sequences in the frequency domain. This work compiles 7 paleoclimatic proxy records from 4 time-series from the north-western Mediterranean all ranging from 7000 to 1000 yrs cal BP: -pollen and clay mineral contents from the lagoonal sediment core PB06 recovered in southern France, -Sea Surface Temperatures (SST) derived from alkenones, concentration of terrestrial alkanes and their average chain length (ACL) from core KSGC-31_GolHo-1B recovered in the Gulf of Lion inner-shelf, - δ18O record from speleothems recovered in the Asiul Cave in north-western Spain, -grain size record from the deep basin sediment drift core MD99-2343 north of Minorca island. A comparison of their frequency content is proposed using wavelet analysis and cluster analysis of wavelet power spectra. Common cyclicities are assessed using cross-wavelet analysis. In addition, a new algorithm is used in order to propagate the age model errors within wavelet power spectra. Results are consistents with a non-stationnary Holocene climate variability. The Halstatt cycles (2000-2500 years) depicted in many proxies (ACL, errestrial alkanes and SSTs) demonstrate solar activity influence in the north-western Mediterranean climate. Cluster analysis shows that pollen and ACL proxies, both indicating changes in aridity, are clearly distinct from other proxies and share significant common periodicities around 1000 and 600 years, since the mid-Holocene. The 1000 years period is also evidenced in terrestrial alkanes and Minorca sediment drift grain size, which respectively indicate changes in the Rhône hydrology and changes in the north-western Mediterranean deep water formation. These findings suggests that an original climate driver influences the Gulf of Lion area. Finally, both clay mineral content from PB06, indicative of past storminess and δ18O record from the north western Iberia, related to precipitations, record the well known 1500 years period since the middle Holocene. The presence of this period, widely encountered in the Atlantic, highlights the link between the north-western Mediterranean and the Atlantic climate variability.

Mars dust storms - Interannual variability and chaos

NASA Technical Reports Server (NTRS)

Ingersoll, Andrew P.; Lyons, James R.

1993-01-01

The hypothesis is that the global climate system, consisting of atmospheric dust interacting with the circulation, produces its own interannual variability when forced at the annual frequency. The model has two time-dependent variables representing the amount of atmospheric dust in the northern and southern hemispheres, respectively. Absorption of sunlight by the dust drives a cross-equatorial Hadley cell that brings more dust into the heated hemisphere. The circulation decays when the dust storm covers the globe. Interannual variability manifests itself either as a periodic solution in which the period is a multiple of the Martian year, or as an aperiodic (chaotic) solution that never repeats. Both kinds of solution are found in the model, lending support to the idea that interannual variability is an intrinsic property of the global climate system. The next step is to develop a hierarchy of dust-circulation models capable of being integrated for many years.

Incorporating palaeoclimate data into water security planning and decision making - a case study from southeast Queensland, Australia

NASA Astrophysics Data System (ADS)

Kiem, Anthony; Vance, Tessa; Tozer, Carly; Roberts, Jason

2017-04-01

Decision makers in the water sector need to deal with existing hydroclimatic variability and uncertainty about future changes to climate and catchment conditions. Identifying solutions for hydroclimatic risk adaptation strategies that are both optimal and robust in the presence of variability and uncertainty presents a difficult challenge. A major reason for this challenge is the fact that the instrumental record in Australia is short ( 60-130 years) and fails to encompass enough climate variability to allow the calculation of robust statistics around the baseline risk of extreme events (e.g. multi-year droughts, decadal periods with clustering of major flood events). This climate variability is documented pre-1900 in palaeoclimate records from sources such as corals, tree-rings, freshwater and marine sediments. Despite being remote from Queensland, a high resolution and highly correlated palaeoclimate record from the Law Dome ice cores in Antarctica (Vance et al. 2015) is also now available and has identified eight mega-droughts (lasting from 5-39 years) during 1000-2009 AD. Most importantly, the palaeoclimate information confirms that the post-1900 instrumental period (i.e. the period on which all water resources infrastructure, policy, operation rules and strategies is based) does not capture the full range of variability that has occurred. Other work also clearly shows that, out to 2050 at least, impacts associated with natural variability significantly exceed even the worst-case climate change scenarios (i.e. obtained from Global Climate Models run under the highest emission scenarios). This presentation will demonstrate how the Law Dome ice cores from Antarctica have been used to produce a highly accurate, 1000 year, annual and seasonal resolution, hydroclimate reconstruction (i.e. precipitation and streamflow) for the southeast Queensland region of Australia. We will then show how the palaeoclimate data has been incorporated into the South East Queensland Regional Stochastic Model (SEQRSM) of catchment hydrology to (a) demonstrate the utility of a palaeoclimate proxy approach in producing more robust estimates of hydroclimatic risk under climate variability and change; (b) gain improved insights into the characteristics (e.g. location, duration, frequency, magnitude, spatial extent, sequencing) of hydroclimate extremes for water security planning and (c) deliver optimised solutions for hydroclimatic risk adaptation strategies to water managers (e.g. optimal and sustainable supply of water to meet current and future urban requirements and also to nearby catchments to support irrigation for dairy, vegetable and forage crops).

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.

Drought, multi-seasonal climate, and wildfire in northern New Mexico

USGS Publications Warehouse

Margolis, Ellis; Woodhouse, Connie A.; Swetnam, Thomas W.

2017-01-01

Wildfire is increasingly a concern in the USA, where 10 million acres burned in 2015. Climate is a primary driver of wildfire, and understanding fire-climate relationships is crucial for informing fire management and modeling the effects of climate change on fire. In the southwestern USA, fire-climate relationships have been informed by tree-ring data that extend centuries prior to the onset of fire exclusion in the late 1800s. Variability in cool-season precipitation has been linked to fire occurrence, but the effects of the summer North American monsoon on fire are less understood, as are the effects of climate on fire seasonality. We use a new set of reconstructions for cool-season (October–April) and monsoon-season (July–August) moisture conditions along with a large new fire scar dataset to examine relationships between multi-seasonal climate variability, fire extent, and fire seasonality in the Jemez Mountains, New Mexico (1599–1899 CE). Results suggest that large fires burning in all seasons are strongly influenced by the current year cool-season moisture, but fires burning mid-summer to fall are also influenced by monsoon moisture. Wet conditions several years prior to the fire year during the cool season, and to a lesser extent during the monsoon season, are also important for spring through late-summer fires. Persistent cool-season drought longer than 3 years may inhibit fires due to the lack of moisture to replenish surface fuels. This suggests that fuels may become increasingly limiting for fire occurrence in semi-arid regions that are projected to become drier with climate change.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Impacts of Changing Climate on Agricultural Variability: Implications for Smallholder Farmers in India

NASA Astrophysics Data System (ADS)

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

2013-12-01

Agriculture is the largest employment sector in India, where food productivity, and thus food security, is highly dependent on seasonal rainfall and temperature. Projected increase in temperature, along with less frequent but intense rainfall events, will have a negative impact on crop productivity in India in the coming decades. These changes, along with continued ground water depletion, could have serious implications for Indian smallholder farmers, who are among some of the most vulnerable communities to climatic and economic changes. Hence baseline information on agricultural sensitivity to climate variability is important for strategies and policies that promote adaptation to climate variability. This study examines how cropping patterns in different agro-ecological zones in India respond to variations in precipitation and temperature. We specifically examine: a) which climate variables most influence crop cover for monsoon and winter crops? and b) how does the sensitivity of crop cover to climate variability vary in different agro-ecological regions with diverse socio-economic factors? We use remote sensing data (2000-01 - 2012-13) for cropping patterns (developed using MODIS satellite data), climate parameters (derived from MODIS and TRMM satellite data) and agricultural census data. We initially assessed the importance of these climate variables in two agro-ecoregions: a predominantly groundwater irrigated, cash crop region in western India, and a region in central India primarily comprised of rain-fed or surface water irrigated subsistence crops. Seasonal crop cover anomaly varied between -25% and 25% of the 13-year mean in these two regions. Predominantly climate-dependent region in central India showed high anomalies up to 200% of the 13-year crop cover mean, especially during winter season. Winter daytime mean temperature is overwhelmingly the most important climate variable for winter crops irrespective of the varied biophysical and socio-economic conditions across the study regions. Despite access to groundwater irrigation, crop cover in the western Indian study region showed substantial fluctuations during monsoon, probably due to changing planting strategies. This region is less sensitive to precipitation compared to the central Indian study region with predominantly climate-dependent irrigation from surface water. In western Indian study region a greater number of rainy days, increased intensity of rainfall, and cooler daytime and nighttime temperatures lead to increased crop cover during monsoon season, compared to in the central Indian study region where monsoon timing and amount of total rainfall are the most important factors of crop cover. Our findings indicate that different regions respond differently to climate, since socio-economic factors, such as irrigation access, market influences, demography, and policies play critical role in agricultural production. In the wake of projected precipitation and temperature changes, better access to irrigation and heat-tolerant high-yielding crop varieties will be crucial for future food production.

Climate change but not unemployment explains the changing suicidality in Thessaloniki Greece (2000-2012).

PubMed

Fountoulakis, Konstantinos N; Savopoulos, Christos; Zannis, Prodromos; Apostolopoulou, Martha; Fountoukidis, Ilias; Kakaletsis, Nikolaos; Kanellos, Ilias; Dimellis, Dimos; Hyphantis, Thomas; Tsikerdekis, Athanasios; Pompili, Maurizio; Hatzitolios, Apostolos I

2016-03-15

Recently there was a debate concerning the etiology behind attempts and completed suicides. The aim of the current study was to search for possible correlations between the rates of attempted and completed suicide and climate variables and regional unemployment per year in the county of Thessaloniki, Macedonia, northern Greece, for the years 2000-12. The regional rates of suicide and attempted suicide as well as regional unemployment were available from previous publications of the authors. The climate variables were calculated from the daily E-OBS gridded dataset which is based on observational data Only the male suicide rates correlate significantly with high mean annual temperature but not with unemployment. The multiple linear regression analysis results suggest that temperature is the only variable that determines male suicides and explains 51% of their variance. Unemployment fails to contribute significantly to the model. There seems to be a seasonal distribution for attempts with mean rates being higher for the period from May to October and the rates clearly correlate with temperature. The highest mean rates were observed during May and August and the lowest during December and February. Multiple linear regression analysis suggests that temperature also determines the female attempts rate although the explained variable is significant but very low (3-5%) Climate variables and specifically high temperature correlate both with suicide and attempted suicide rates but with a different way between males and females. The climate effect was stronger than the effect of unemployment. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

ENSO-driven climate variability promotes periodic major outbreaks of dengue in Venezuela.

PubMed

Vincenti-Gonzalez, M F; Tami, A; Lizarazo, E F; Grillet, M E

2018-04-10

Dengue is a mosquito-borne viral disease of global impact. In Venezuela, dengue has emerged as one of the most important public health problems of urban areas with frequent epidemics since 2001. The long-term pattern of this disease has involved not only a general upward trend in cases but also a dramatic increase in the size and frequency of epidemic outbreaks. By assuming that climate variability has a relevant influence on these changes in time, we quantified the periodicity of dengue incidence in time-series of data from two northern regions of Venezuela. Disease cycles of 1 and 3-4 years (p < 0.05) were detected. We determined that dengue cycles corresponded with local climate and the El Niño Southern Oscillation (ENSO) variation at both seasonal and inter-annual scales (every 2-3 years). Dengue incidence peaks were more prevalent during the warmer and dryer years of El Niño confirming that ENSO is a regional climatic driver of such long-term periodicity through local changes in temperature and rainfall. Our findings support the evidence of the effect of climate on dengue dynamics and advocate the incorporation of climate information in the surveillance and prediction of this arboviral disease in Venezuela.

Contrasting growth forecasts across the geographical range of Scots pine due to altitudinal and latitudinal differences in climatic sensitivity.

PubMed

Matías, Luis; Linares, Juan C; Sánchez-Miranda, Ángela; Jump, Alistair S

2017-10-01

Ongoing changes in global climate are altering ecological conditions for many species. The consequences of such changes are typically most evident at the edge of a species' geographical distribution, where differences in growth or population dynamics may result in range expansions or contractions. Understanding population responses to different climatic drivers along wide latitudinal and altitudinal gradients is necessary in order to gain a better understanding of plant responses to ongoing increases in global temperature and drought severity. We selected Scots pine (Pinus sylvestris L.) as a model species to explore growth responses to climatic variability (seasonal temperature and precipitation) over the last century through dendrochronological methods. We developed linear models based on age, climate and previous growth to forecast growth trends up to year 2100 using climatic predictions. Populations were located at the treeline across a latitudinal gradient covering the northern, central and southernmost populations and across an altitudinal gradient at the southern edge of the distribution (treeline, medium and lower elevations). Radial growth was maximal at medium altitude and treeline of the southernmost populations. Temperature was the main factor controlling growth variability along the gradients, although the timing and strength of climatic variables affecting growth shifted with latitude and altitude. Predictive models forecast a general increase in Scots pine growth at treeline across the latitudinal distribution, with southern populations increasing growth up to year 2050, when it stabilizes. The highest responsiveness appeared at central latitude, and moderate growth increase is projected at the northern limit. Contrastingly, the model forecasted growth declines at lowland-southern populations, suggesting an upslope range displacement over the coming decades. Our results give insight into the geographical responses of tree species to climate change and demonstrate the importance of incorporating biogeographical variability into predictive models for an accurate prediction of species dynamics as climate changes. © 2017 John Wiley & Sons Ltd.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

Characterization of climate uncertainty at regional scales over near-term planning horizons (0-30 years) is crucial for climate adaptation. Climate internal variability (CIV) dominates climate uncertainty over decadal prediction horizons at stakeholders' scales (regional to local). In the literature, CIV has been characterized indirectly using projections of climate change from multi-model ensembles (MME) instead of directly using projections from multiple initial condition ensembles (MICE), primarily because adequate number of initial condition (IC) runs were not available for any climate model. Nevertheless, the recent availability of significant number of IC runs from one climate model allows for the first time to characterize CIV directly from climate model projections and perform a sensitivity analysis to study the dominance of CIV compared to model response variability (MRV). Here, we measure relative agreement (a dimensionless number with values ranging between 0 and 1, inclusive; a high value indicates less variability and vice versa) among MME and MICE and find that CIV is lower than MRV for all projection time horizons and spatial resolutions for precipitation and temperature. However, CIV exhibits greater dominance over MRV for seasonal and annual mean precipitation at higher latitudes where signals of climate change are expected to emerge sooner. Furthermore, precipitation exhibits large uncertainties and a rapid decline in relative agreement from global to continental, regional, or local scales for MICE compared to MME. The fractional contribution of uncertainty due to CIV is invariant for precipitation and decreases for temperature as lead time progresses towards the end of the century.

Harvesting Atlantic Cod under Climate Variability

NASA Astrophysics Data System (ADS)

Oremus, K. L.

2016-12-01

Previous literature links the growth of a fishery to climate variability. This study uses an age-structured bioeconomic model to compare optimal harvest in the Gulf of Maine Atlantic cod fishery under a variable climate versus a static climate. The optimal harvest path depends on the relationship between fishery growth and the interest rate, with higher interest rates dictating greater harvests now at the cost of long-term stock sustainability. Given the time horizon of a single generation of fishermen under assumptions of a static climate, the model finds that the economically optimal management strategy is to harvest the entire stock in the short term and allow the fishery to collapse. However, if the biological growth of the fishery is assumed to vary with climate conditions, such as the North Atlantic Oscillation, there will always be pulses of high growth in the stock. During some of these high-growth years, the growth of the stock and its economic yield can exceed the growth rate of the economy even under high interest rates. This implies that it is not economically optimal to exhaust the New England cod fishery if NAO is included in the biological growth function. This finding may have theoretical implications for the management of other renewable yet exhaustible resources whose growth rates are subject to climate variability.

Dynamic response of airborne infections to climate change: predictions for varicella

NASA Astrophysics Data System (ADS)

Baker, R.; Mahmud, A. S.; Metcalf, C. J. E.

2017-12-01

Characterizing how climate change will alter the burden of infectious diseases has clear applications for public health policy. Despite our uniquely detailed understanding of the transmission process for directly transmitted infections, the impact of climate variables on these infections remains understudied. We develop a novel methodology for estimating the causal relationship between climate and directly transmitted infections, which combines an epidemiological model of disease transmission with panel regression techniques. Our method allows us to move beyond correlational approaches to studying the link between climate and infectious diseases. Further, we can generate semi-mechanistic projections of incidence across climate scenarios. We illustrate our approach using 30 years of reported cases of varicella, a common airborne childhood infection, across 32 states in Mexico. We find significantly increased varicella transmission in drier conditions. We use this to map potential changes in the magnitude and variability of varicella incidence in Mexico as a result of projected changes in future climate conditions. Our results indicate that the predicted decrease in humidity in Mexico towards the end of the century will increase incidence of varicella, all else equal, and that these changes in incidence will be non-uniform across the year.

Climate Change Impact Assessment in Pacific North West Using Copula based Coupling of Temperature and Precipitation variables

NASA Astrophysics Data System (ADS)

Qin, Y.; Rana, A.; Moradkhani, H.

2014-12-01

The multi downscaled-scenario products allow us to better assess the uncertainty of the changes/variations of precipitation and temperature in the current and future periods. Joint Probability distribution functions (PDFs), of both the climatic variables, might help better understand the interdependence of the two, and thus in-turn help in accessing the future with confidence. Using the joint distribution of temperature and precipitation is also of significant importance in hydrological applications and climate change studies. In the present study, we have used multi-modelled statistically downscaled-scenario ensemble of precipitation and temperature variables using 2 different statistically downscaled climate dataset. The datasets used are, 10 Global Climate Models (GCMs) downscaled products from CMIP5 daily dataset, namely, those from the Bias Correction and Spatial Downscaling (BCSD) technique generated at Portland State University and from the Multivariate Adaptive Constructed Analogs (MACA) technique, generated at University of Idaho, leading to 2 ensemble time series from 20 GCM products. Thereafter the ensemble PDFs of both precipitation and temperature is evaluated for summer, winter, and yearly periods for all the 10 sub-basins across Columbia River Basin (CRB). Eventually, Copula is applied to establish the joint distribution of two variables enabling users to model the joint behavior of the variables with any level of correlation and dependency. Moreover, the probabilistic distribution helps remove the limitations on marginal distributions of variables in question. The joint distribution is then used to estimate the change trends of the joint precipitation and temperature in the current and future, along with estimation of the probabilities of the given change. Results have indicated towards varied change trends of the joint distribution of, summer, winter, and yearly time scale, respectively in all 10 sub-basins. Probabilities of changes, as estimated by the joint precipitation and temperature, will provide useful information/insights for hydrological and climate change predictions.

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

NASA Astrophysics Data System (ADS)

Walker, A. E.; Derksen, C.

2008-12-01

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

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.

The variability of runoff and soil erosion in the Brazilian Cerrado biome due to the potential land use and climate changes

NASA Astrophysics Data System (ADS)

Alexandre Ayach Anache, Jamil; Wendland, Edson; Malacarne Pinheiro Rosalem, Lívia; Srivastava, Anurag; Flanagan, Dennis

2017-04-01

Changes in land use and climate can influence runoff and soil loss, threatening soil and water conservation in the Cerrado biome in Brazil. Due to the lack of long term observed data for runoff and soil erosion in Brazil, the adoption of a process-based model was necessary, representing the variability of both variables in a continuous simulation approach. Thus, we aimed to calibrate WEPP (Water Erosion Prediction Project) model for different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane) under subtropical conditions inside the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change scenarios. We performed the model calibration using a 4-year dataset of observed runoff and soil loss in four different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane). The WEPP model components (climate, topography, soil, and management) were calibrated according to field data. However, soil and management were optimized according to each land use using a parameter estimation tool. The observations were conducted between 2012 and 2015 in experimental plots (5 m width, 20 m length, 9% slope gradient, 3 replicates per treatment). The simulations were done using the calibrated WEPP model components, but changing the 4-year observed climate file by a 100-year dataset created with CLIGEN (weather generator) based on regional climate statistics. Afterwards, using MarkSim DSSAT Weather File Generator, runoff and soil loss were simulated using future climate scenarios for 2030, 2060, and 2090. To analyze the data, we used non-parametric statistics as data do not follow normal distribution. The results show that WEPP model had an acceptable performance for the considered conditions. In addition, both land use and climate can influence on runoff and soil loss rates. Potential climate changes which consider the increase of rainfall intensities and depths in the studied region may increase the variability and rates for runoff and soil erosion. However, the climate did not change the differences and similarities between the rates of the four analyzed land uses. The runoff behavior is distinct for all land uses, but for soil loss we found similarities between pasture and undisturbed Cerrado, suggesting that soil sustainability could be reached when the management follows conservation principles.

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.

Impact of Climate Variability on Maize Production in Pakistan using Remote Sensing and Machine Learning

NASA Astrophysics Data System (ADS)

Richetti, J.; Ahmad, I.; Aristizabal, F.; Judge, J.

2017-12-01

Determining maize agricultural production under climate variability is valuable to policy makers in Pakistan since maize is the third most produced crop by area after wheat and rice. This study aims to predict the maize production under climate variability. Two-hundred ground truth points of both maize and non-maize land covers were collected from the Faisalabad district during the growing seasons of 2015 and 2016. Landsat-8 images taken in second week of May which correspond spatially and temporally to the local, peak growing season for maize were gathered. For classifying the region training data was constructed for a variety of machine learning algorithms by sampling the second, third, and fourth bands of the Landsat-8 imagery at these reference locations. Cross validation was used for parameter tuning as well as estimating the generalized performances. All the classifiers resulted in overall accuracies of greater than 90% for both years and a support vector machine with a radial basis kernel recorded the maximum accuracy of 97%. The tuned models were used to determine the spatial distribution of maize fields for both growing seasons in the Faisalabad district using parallel processing to improve computation time. The overall classified maize growing area represented 12% difference than that reported by the Crop Reporting Service (CRS) of Punjab Pakistan for both 2015 and 2016. For the agricultural production normalized difference vegetation index from Landsat-8 and climate indicators from ground stations will be used as inputs in a variety of machine learning regression algorithms. The expected results will be compared to actual yield from 64 commercial farms. To verify the impact of climate variability in the maize agricultural production historical climate data from previous 30 years will be used in the developed model to asses the impact of climate variability on the maize production.

An Attempt To Estimate The Contribution Of Variability Of Wetland Extent On The Variability Of The Atmospheric Methane Growth Rate In The Years 1993-2000.

NASA Astrophysics Data System (ADS)

Ringeval, B.; de Noblet-Ducoudre, N.; Prigent, C.; Bousquet, P.

2006-12-01

The atmospheric methane growth rate presents lots of seasonal and year-to-year variations. Large uncertainties still exist in the relative part of differents sources and sinks on these variations. We have considered, in this study, the main natural sources of methane and the supposed main variable source, i.e. wetlands, and tried to simulate the variations of their emissions considering the variability of the wetland extent and of the climate. For this study, we use the methane emission model of Walter et al. (2001) and the quantification of the flooded areas for the years 1993-2000 obtained with a suite of satellite observations by Prigent et al. (2001). The data necessary to the Walter's model are obtained with simulation of a dynamic global vegetation model ORCHIDEE (Krinner et al. (2005)) constrained by the NCC climate data (Ngo-Duc et al. (2005)) and after imposing a water-saturated soil to approach productivity of wetlands. We calculate global annual methane emissions from wetlands to be 400 Tg per year, that is higher than previous results obtained with fixed wetland extent. Simulations are realised to estimate the part of variability in the emissions explained by the variability of the wetland extent. It seems that the year-to-year emission variability is mainly explained by the interannual variability of wetland extent. The seasonnal variability is explained for 75% in the tropics and only for 40% in the north of 30°N by variability of wetlands extend. Finally, we compare results with a top-down approach of Bousquet et al.(2006).

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Paleoenvironmental and Paleoclimate Changes Since 21,000 Cal Years BP in the Northeastern part of Brazil Inferred From Sediment Records in Lagoa do Caco (Maranhao State, Brazil)

NASA Astrophysics Data System (ADS)

Sifeddine, A.; Meyers, P. A.; Gustavo, A.; Spadano Albuquerque, A. L.; Turcq, B.; Campbello Cordeiro, R.; Abrao, J. J.

2004-12-01

Two cores from Caco Lake, Maranhao State (North Brazil) record different histories of sediment accumulation on the margin and center of the lake that reflect changes in lake level. Seismic profiles, mineralogy and organic geochemical studies, backed by radiocarbon dating, reveal variable climatic and environmental conditions over the last 21 Cal Kyr BP. During the Last Glacial Maximum, regional climate was predominantly dry but was interrupted by short humid phases as reflected by a succession of very thin layers of sand and organic matter. The late glacial climate was relatively wet and included two rapid lake-level increases accompanied by forest expansion. The two wet phases were separated by a phase where the lake level remained stable and the forest changes were marked by the development of cool "Podocarpus" forest. These humid climate periods differed significantly from present warm tropical conditions.. The Holocene period is characterized by progressive increase of lake level, which reaches his maximum at around 7,000 Cal years BP. The period between 4,000 Cal years BP and the present shows high variability in lake level. Comparing with other South American and African records, we conclude that Late Glacial humid conditions were controlled by intensification of the ITCZ or shifts of its position, resulting in southeasterly trade wind variations and in interconnection between northern South America and the Atlantic tropical ocean-atmosphere system. The climatic variability during the Holocene is probably the result of sub-Milankovitch solar cycles and regional responses to these global forcings that are related to Atlantic and Pacific variability and their interconnections.

Acute childhood asthma in Galway city from 1985-2005: relationship to air pollution and climate.

PubMed

Loftus, A; Loftus, B G; Muircheartaigh, I O; Newell, J; Scarrott, C; Jennings, S

2014-01-01

We examine the relationship of air pollution and climatic variables to asthma admission rates of children in Galway city over a 21 year period. Paediatric asthma admissions were recorded from 1985-2005, and admission rates per thousand calculated for pre-school (1-4 years), school aged (5-14 years) and all children (1-14 years) on a monthly and annual basis. These data were compared to average monthly and annual climatic variables (rainfall, humidity, sunshine, wind speed and temperature) and black smoke levels for the city. Simple correlation and Poisson Generalized Additive Models (GAM) were used. Admission rates each month are significantly correlated with smoke levels (p = 0.007). Poisson GAM also shows a relationship between admissions and pollution (p = 0.07). Annual smoke levels impact more on admission rates of preschoolers (p = 0.04) than school age children (p = 0.10). These data suggest that air pollution is an important factor in the epidemiology of acute childhood asthma.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Climate Variability and Inter-Provincial Migration in South America, 1970-2011

PubMed Central

Thiede, Brian; Gray, Clark; Mueller, Valerie

2016-01-01

We examine the effect of climate variability on human migration in South America. Our analyses draw on over 21 million observations of adults aged 15-40 from 25 censuses conducted in eight South American countries. Addressing limitations associated with methodological diversity among prior studies, we apply a common analytic approach and uniform definitions of migration and climate across all countries. We estimate the effects of climate variability on migration overall and also investigate heterogeneity across sex, age, and socioeconomic groups, across countries, and across historical climate conditions. We also disaggregate migration by the rural/urban status of destination. We find that exposure to monthly temperature shocks has the most consistent effects on migration relative to monthly rainfall shocks and gradual changes in climate over multi-year periods. We also find evidence of heterogeneity across demographic groups and countries. Analyses that disaggregate migration by the rural/urban status of destination suggest that much of the climate-related inter-province migration is directed toward urban areas. Overall, our results underscore the complexity of environment-migration linkages and challenge simplistic narratives that envision a linear and monolithic migratory response to changing climates. PMID:28413264

Climate Variability and Inter-Provincial Migration in South America, 1970-2011.

PubMed

Thiede, Brian; Gray, Clark; Mueller, Valerie

2016-11-01

We examine the effect of climate variability on human migration in South America. Our analyses draw on over 21 million observations of adults aged 15-40 from 25 censuses conducted in eight South American countries. Addressing limitations associated with methodological diversity among prior studies, we apply a common analytic approach and uniform definitions of migration and climate across all countries. We estimate the effects of climate variability on migration overall and also investigate heterogeneity across sex, age, and socioeconomic groups, across countries, and across historical climate conditions. We also disaggregate migration by the rural/urban status of destination. We find that exposure to monthly temperature shocks has the most consistent effects on migration relative to monthly rainfall shocks and gradual changes in climate over multi-year periods. We also find evidence of heterogeneity across demographic groups and countries. Analyses that disaggregate migration by the rural/urban status of destination suggest that much of the climate-related inter-province migration is directed toward urban areas. Overall, our results underscore the complexity of environment-migration linkages and challenge simplistic narratives that envision a linear and monolithic migratory response to changing climates.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis.

PubMed

Adeola, Abiodun M; Botai, Joel O; Rautenbach, Hannes; Adisa, Omolola M; Ncongwane, Katlego P; Botai, Christina M; Adebayo-Ojo, Temitope C

2017-11-08

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease's transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998-2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables' and malaria cases' time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature ( R ² = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention.

Contribution of increasing CO2 and climate to carbon storage by ecosystems in the United States.

PubMed

Schimel, D; Melillo, J; Tian, H; McGuire, A D; Kicklighter, D; Kittel, T; Rosenbloom, N; Running, S; Thornton, P; Ojima, D; Parton, W; Kelly, R; Sykes, M; Neilson, R; Rizzo, B

2000-03-17

The effects of increasing carbon dioxide (CO2) and climate on net carbon storage in terrestrial ecosystems of the conterminous United States for the period 1895-1993 were modeled with new, detailed historical climate information. For the period 1980-1993, results from an ensemble of three models agree within 25%, simulating a land carbon sink from CO2 and climate effects of 0.08 gigaton of carbon per year. The best estimates of the total sink from inventory data are about three times larger, suggesting that processes such as regrowth on abandoned agricultural land or in forests harvested before 1980 have effects as large as or larger than the direct effects of CO2 and climate. The modeled sink varies by about 100% from year to year as a result of climate variability.

Contribution of increasing CO2 and climate to carbon storage by ecosystems in the United States

USGS Publications Warehouse

Schimel, D.; Melillo, J.; Tian, H.; McGuire, A.D.; Kicklighter, D.; Kittel, T.; Rosenbloom, N.; Running, S.; Thornton, P.; Ojima, D.; Parton, W.; Kelly, R.; Sykes, M.; Neilson, R.; Rizzo, B.

2000-01-01

The effects of increasing carbon dioxide (CO2) and climate on net carbon storage in terrestrial ecosystems of the conterminous United States for the period 1895-1993 were modeled with new, detailed historical climate information. For the period 1980-1993, results from an ensemble of three models agree within 25%, simulating a land carbon sink from CO2 and climate effects of 0.08 gigaton of carbon per year. The best estimates of the total sink from inventory data are about three times larger, suggesting that processes such as regrowth on abandoned agricultural land or in forests harvested before 1980 have effects as large as or larger than the direct effects of CO2 and climate. The modeled sink varies by about 100% from year to year as a result of climate variability.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

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

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

Crime Seasonality: Examining the Temporal Fluctuations of Property Crime in Cities With Varying Climates.

PubMed

Linning, Shannon J; Andresen, Martin A; Brantingham, Paul J

2017-12-01

This study investigates whether crime patterns fluctuate periodically throughout the year using data containing different property crime types in two Canadian cities with differing climates. Using police report data, a series of ordinary least squares (OLS; Vancouver, British Columbia) and negative binomial (Ottawa, Ontario) regressions were employed to examine the corresponding temporal patterns of property crime in Vancouver (2003-2013) and Ottawa (2006-2008). Moreover, both aggregate and disaggregate models were run to examine whether different weather and temporal variables had a distinctive impact on particular offences. Overall, results suggest that cities that experience greater variations in weather throughout the year have more distinct increases of property offences in the summer months and that different climate variables affect certain crime types, thus advocating for disaggregate analysis in the future.

Climate variability and extremes, interacting with nitrogen storage, amplify eutrophication risk

USGS Publications Warehouse

Lee, Minjin; Shevliakova, Elena; Malyshev, Sergey; Milly, P.C.D.; Jaffe, Peter R.

2016-01-01

Despite 30 years of basin-wide nutrient-reduction efforts, severe hypoxia continues to be observed in the Chesapeake Bay. Here we demonstrate the critical influence of climate variability, interacting with accumulated nitrogen (N) over multidecades, on Susquehanna River dissolved nitrogen (DN) loads, known precursors of the hypoxia in the Bay. We used the process model LM3-TAN (Terrestrial and Aquatic Nitrogen), which is capable of capturing both seasonal and decadal-to-century changes in vegetation-soil-river N storage, and produced nine scenarios of DN-load distributions under different short-term scenarios of climate variability and extremes. We illustrate that after 1 to 3 yearlong dry spells, the likelihood of exceeding a threshold DN load (56 kt yr−1) increases by 40 to 65% due to flushing of N accumulated throughout the dry spells and altered microbial processes. Our analyses suggest that possible future increases in climate variability/extremes—specifically, high precipitation occurring after multiyear dry spells—could likely lead to high DN-load anomalies and hypoxia.

Assessing the Dynamic Effects of Climate on Individual Tree Growth Across Time and Space

NASA Astrophysics Data System (ADS)

Itter, M.; Finley, A. O.; D'Amato, A. W.; Foster, J. R.; Bradford, J. B.

2015-12-01

The relationship between climate variability and an ecosystem process, such as forest growth, is frequently not fixed over time, but changes due to complex interactions between unobserved ecological factors and the process of interest. Climate data and forecasts are frequently spatially and temporally misaligned with ecological observations making inference regarding the effects of climate on ecosystem processes particularly challenging. Here we develop a Bayesian dynamic hierarchical model for annual tree growth increment that allows the effects of climate to evolve over time, applies climate data at a spatial-temporal scale consistent with observations, and controls for individual-level variability commonly encountered in ecological datasets. The model is applied to individual tree data from northern Minnesota using a modified Thornthwaite-type water balance model to transform PRISM temperature and precipitation estimates to physiologically relevant values of actual and potential evapotranspiration (AET, PET), and climatic water deficit. Model results indicate that mean tree growth is most sensitive to AET during the growing season and PET and minimum temperature in the spring prior to growth. The effects of these variables on tree growth, however, are not stationary with significant effects observed in only a subset of years during the 111-year study period. Importantly, significant effects of climate do not result from anomalous climate observations, but follow from large growth deviations unexplained by tree age and size, and time since forest disturbance. Results differ markedly from alternative models that assume the effects of climate are stationary over time or apply climate estimates at the individual scale. Forecasts of future tree growth as a function of climate follow directly from the dynamic hierarchical model allowing for assessment of forest change. Current work is focused on extending the model framework to include regional climate and ecosystem effects for application to a larger tree growth dataset spanning a latitudinal gradient within the US from Maine to Florida.

Two centuries of observed atmospheric variability and change over the North Sea region

NASA Astrophysics Data System (ADS)

Stendel, Martin; van den Besselaar, Else; Hannachi, Abdel; Kent, Elizabeth; Lefebvre, Christiana; van Oldenborgh, Geert Jan; Rosenhagen, Gudrun; Schenk, Frederik; van der Schrier, Gerard

2015-04-01

Situated in northwestern Europe, the North Sea region is under influence of air masses from subtropical to arctic origin, and thus exhibits significant natural climate variability. As the land areas surrounding the North Sea are densely populated, climate change is an important issue in terms of e.g. coastal protection, fishery and trade. This study is part of the NOSCCA initiative (North Sea Region Climate Change Assessment) and presents observed variability and changes in atmospheric parameters during the last roughly 200 years. Circulation patterns show considerable decadal variability. In recent decades, a northward shift of storm tracks and increased cyclonic activity has been observed. There is also an indication of increased persistence of weather types. The wind climate is dominated by large multidecadal variability, and no robust long-term trends can be identified in the available datasets. There is a clear positive trend in near-surface temperatures, in particular during spring and winter. Over the region as a whole, no clear long-term precipitation trends are visible, although regional indications exist for an increased risk of extreme precipitation events.

Spatio-temporal variability of NDVI-precipitation over southernmost South America: possible linkages between climate signals and epidemics

NASA Astrophysics Data System (ADS)

Tourre, Y. M.; Jarlan, L.; Lacaux, J.-P.; Rotela, C. H.; Lafaye, M.

2008-10-01

Climate-environment variability affects the rates of incidence of vector-borne and zoonotic diseases and is possibly associated with epidemics outbreaks. Over southernmost South America the joint spatio-temporal evolution of climate-environment is analyzed for the 1982-2004 period. Detailed mapping of normalized difference vegetation index (NDVI) and rainfall variability are then compared to zones with preliminary epidemiological reports. A significant quasi-biennial signal (2.2- to 2.4-year periods, or QB) for joint NDVI-rainfall variability is revealed. From rotated EOFs, dominant NDVI patterns are partitioned according to their lead frequencies: (1) the 'QB group' (2.1-to 3-year periods) includes six modes over southern Brazil, Uruguay, northern-central Argentina (two modes), the southern Paraguay-northern Argentina border, and the Santa Cruz Province; (2) the QB1 (2.4- to 3-year periods) + quasi-quadrennial (QQ) mode over the Misiones Province; and (3) the QB2 (2.1- to 2.5-year periods) + QQ + inter-annual (IA) (3- to 7-year periods) two modes over south-eastern Argentina. Modes within the 'QB group' are positively correlated with global climate signals and SST. The Uruguayan mode is correlated with global ENSO (8-month lag) whilst the southern Entre-Rios/northern Buenos Aires provinces are correlated with central equatorial Pacific SSTs (3-month lag). The Santa Cruz (Patagonia) Province is most correlated with the Pacific South America (PSA) index and SST patterns (3-month lag) along the Antarctica circumpolar current. The spatial distribution of lead NDVI modes includes the Formosa, Misiones, Chaco and Buenos Aires provinces among others, known for being prone to vector-borne epidemics such as dengue fever, malaria, leishmaniasis (American cutaneous leishmaniasis or ACL), hantivirus, chagas and Argentine hemorrhagic fever (AHF). Some provinces also correspond to regions where lead NDVI PCs' modes are associated with high-frequency climate signals such as the quasi-biennial oscillation in northwest Argentina. The joint preliminary results (climate-environment-public health reports) presented here for the first time are meant: (1) to contribute to a better understanding of climate-environment-epidemics process-based and modeling studies and (2) to facilitate, in the long run, the implementation of local and regional health early warning systems (HEWS) over southernmost South America. The latter is becoming crucial with ever-increasing migration, urban sprawl (re-emergence of dengue fever epidemics since the late 1990s), all embedded in a climate change context.

Fluctuations in Tree Ring Cellulose d18O during the Little Ice Age Correlate with Solar Activity

NASA Astrophysics Data System (ADS)

Yamaguchi, Y. T.; Yokoyama, Y.; Miyahara, H.; Nakatsuka, T.

2008-12-01

The Maunder Minimum (AD1645-1715), when sunspots became exceedingly rare, is known to coincide with the coldest period during the Little Ice Age. This is a useful period to investigate possible linkage between solar activity and climate because variation in solar activity was different from that of today. The solar cycle length was longer (14 and 28 years) than that of today (11 and 22 years) hence any climate archives that have similar periodic changes could be separated from other internal climate forcing. We have reported that Greenland temperature variations coincided with decadal-scale variability in solar activity during the Maunder Minimum (Miyahara et al. 2008). Here we report interannual and intra-annual relative humidity (RH) variations in central Japan during that period, using tree ring cellulose d18O in a 382-year-old Japanese cedar tree (Cryptomeria japonica). The isotopic composition of tree rings can be a powerful tool to study the relationship between solar activity and climate, because we can directly compare solar activity (D14C) and climate (d18O) with little dating error. The climate proxy obtained using tree ring cellulose d18O is correlated both negatively and positively with RH and d18O in precipitation, respectively. Since d18O in precipitation is negatively correlated with the amount of precipitation in the monsoon area, tree ring cellulose d18O can be a reliable proxy for past RH and/or amount of precipitation in the area of the interest. Tree ring cellulose d18O of the cedar tree during AD1938-1998 in fact correlates significantly with the mean RH in June in central Japan. Tree ring d18O inferred RH variability during the Maunder Minimum shows distinct high RH spikes with an approximate 14-year quasiperiodicity. All nine solar minima during AD1640-1756 deduced from tree ring D14C coincided with high RH spikes, and seven of which coincided within 1-year. Interannual RH variations also coincided with Greenland temperature during this period. These results suggest that weakening of solar activity at solar minima caused distinct hemispheric scale climate change during the Maunder Minimum. We discuss the mechanism in which the solar activity variation caused the climate change, based on intra-annual RH variability and further data analysis of interannual RH variability. H. Miyahara et al., Earth Planet. Sci. Lett. 272, 1-2, 290-295 (2008).

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

The surface warming has been widespread over the entire globe. Central Europe, including Poland, is not an exception. Global temperature increases are accompanied by changes in other climatic variables. Climate change in Poland manifests itself also as change in annual sums of precipitation. They have been slightly growing but, what is more important, seasonal and monthly distributions of precipitation have been also changing. The most visible increases have been observed during colder half-year, especially in March. A decreasing contribution of summer precipitation total (June-August) to the annual total is observed. Climate projections for Poland predict further warming and continuation of already observed changes in the quantity of precipitation as well as its spatial and seasonal distribution.

Analysis of morpho-agronomic and climatic variables in successive agricultural years provides novel information regarding the phenological cycle of Jatropha in conditions of the Brazilian cerrado.

PubMed

Domiciano, Gisele P; Alves, Alexandre A; Laviola, Bruno G; Albrecht, Julio C

2014-12-01

Phenological studies can provide information that enables the understanding of the dynamics of plants and how these dynamics are related to the biotic and abiotic environment. In order to study the phenological phases of Jatropha during two agricultural years, agronomic and climatic variables, such as temperature and rainfall, were evaluated. Data for each variable in each year and each genotype were subjected to analysis of variance (ANOVA) and the differences were tested at 5% probability by F test. In addition, the correlation of growth behavior and reproductive development of two Jatropha accessions (CNPAE-102 and CNPAE-169) as a function of time elapsed after the start of the phenological cycle with climatic variables were analyzed through Pearson's correlation. It was found that: (i) the resuming of plant growth by producing new branches and flowers of both genotypes coincides with the start of the rainy season, (ii) the flowering may be related to the increase in temperature and rainfall; (iii) the number of inflorescences per plant and number of female flowers determine the number of green fruits, (iv) the environmental changes are responsible for the delimitation of phenophases; and finally that (v) the responses to phenological changes are genotype-dependent.

Transient nature of late Pleistocene climate variability.

PubMed

Crowley, Thomas J; Hyde, William T

2008-11-13

Climate in the early Pleistocene varied with a period of 41 kyr and was related to variations in Earth's obliquity. About 900 kyr ago, variability increased and oscillated primarily at a period of approximately 100 kyr, suggesting that the link was then with the eccentricity of Earth's orbit. This transition has often been attributed to a nonlinear response to small changes in external boundary conditions. Here we propose that increasing variablility within the past million years may indicate that the climate system was approaching a second climate bifurcation point, after which it would transition again to a new stable state characterized by permanent mid-latitude Northern Hemisphere glaciation. From this perspective the past million years can be viewed as a transient interval in the evolution of Earth's climate. We support our hypothesis using a coupled energy-balance/ice-sheet model, which furthermore predicts that the future transition would involve a large expansion of the Eurasian ice sheet. The process responsible for the abrupt change seems to be the albedo discontinuity at the snow-ice edge. The best-fit model run, which explains almost 60% of the variance in global ice volume during the past 400 kyr, predicts a rapid transition in the geologically near future to the proposed glacial state. Should it be attained, this state would be more 'symmetric' than the present climate, with comparable areas of ice/sea-ice cover in each hemisphere, and would represent the culmination of 50 million years of evolution from bipolar nonglacial climates to bipolar glacial climates.

Evidence for a possible modern and mid-Holocene solar influence on climate from Lake Titicaca, South America

NASA Astrophysics Data System (ADS)

Theissen, K. M.; Dunbar, R. B.

2005-12-01

In tropical regions, there are few paleoclimate archives with the necessary resolution to investigate climate variability at interannual-to-decadal timescales prior to the onset of the instrumental record. Interannual variability associated with the El Niño Southern Oscillation (ENSO) is well documented in the instrumental record and the importance of the precessional forcing of millennial variability has been established in studies of tropical paleoclimate records. In contrast, decade-to-century variability is still poorly understood. Here, we examine interannual to decadal variability in the northern Altiplano of South America using digital image analysis of a floating interval of varved sediments of middle Holocene age (~6160-6310 yr BP) from Lake Titicaca. Multi-taper method (MTM) and wavelet frequency-domain analyses were performed on a time series generated from a gray-scaled digital image of the mm-thick laminations. Our results indicate significant power at a decadal periodicity (10-12 years) associated with the Schwabe cycle of solar activity. Frequency-domain analysis also indicates power at 2-2.5 year periodicities associated with ENSO. Similarly, spectral analysis of a 75 year instrumental record of Titicaca lake level shows significant power at both solar and ENSO periodicities. Although both of the examined records are short, our results imply that during both the mid-Holocene and modern times, solar and ENSO variability may have contributed to high frequency climate fluctuations over the northern Altiplano. We suspect that solar influence on large-scale atmospheric circulation features may account for the decadal variability in the mid-Holocene and present-day water balance of the Altiplano.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

PubMed

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-02-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling

PubMed Central

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-01-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631

Variations in the perceptions of peer and coach motivational climate.

PubMed

Vazou, Spiridoula

2010-06-01

This study examined (a) variations in the perceptions of peer- and coach-generated motivational climate within and between teams and (b) individual- and group-level factors that can account for these variations. Participants were 483 athletes between 12 and 16 years old. The results showed that perceptions of both peer- and coach-generated climate varied as a function of group-level variables, namely team success, coach's gender (except for peer ego-involving climate), and team type (only for coach ego-involving climate). Perceptions of peer- and coach-generated climate also varied as a function of individual-level variables, namely athletes' task and ego orientations, gender, and age (only for coach task-involving and peer ego-involving climate). Moreover, within-team variations in perceptions of peer- and coach-generated climate as a function of task and ego orientation levels were identified. Identifying and controlling the factors that influence perceptions of peer- and coach-generated climate may be important in strengthening task-involving motivational cues.

The East Asian Jet Stream and Asian-Pacific-American Climate

NASA Technical Reports Server (NTRS)

Yang, Song; Lau, K.-M.; Kim, K.-M.

2000-01-01

The upper-tropospheric westerly jet stream over subtropical East Asia and western Pacific, often referred to as East Asian Jet (EAJ), is an important atmospheric circulation system in the Asian-Pacific-American (APA) region during winter. It is characterized by variabilities on a wide range of time scales and exerts a strong impact on the weather and climate of the region. On the synoptic scale, the jet stream is closely linked to many phenomena such as cyclogenesis, frontogenesis, blocking, storm track activity, and the development of other atmospheric disturbances. On the seasonal time scale, the variation of the EAJ determines many characteristics of the seasonal transition of the atmospheric circulation especially over East Asia. The variabilities of the EAJ on these time scales have been relatively well documented. It has also been understood since decades ago that the interannual. variability of the EAJ is associated with many climate signals in the APA region. These signals include the persistent anomalies of the East Asian winter monsoon and the changes in diabatic heating and in the Hadley circulation. However, many questions remain for the year-to-year variabilities of the EAJ and their relation to the APA climate. For example, what is the relationship between the EAJ and El Nino/Southern Oscillation (ENSO)? Will the EAJ and ENSO play different roles in modulating the APA climate? How is the jet stream linked to the non-ENSO-related sea surface temperature (SST) anomalies and to the Pacific/North American (PNA) teleconnection pattern?

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

PubMed

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

2010-04-01

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

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.

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.

Climate-based statistical regression models for crop yield forecasting of coffee in humid tropical Kerala, India

NASA Astrophysics Data System (ADS)

Jayakumar, M.; Rajavel, M.; Surendran, U.

2016-12-01

A study on the variability of coffee yield of both Coffea arabica and Coffea canephora as influenced by climate parameters (rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH)) was undertaken at Regional Coffee Research Station, Chundale, Wayanad, Kerala State, India. The result on the coffee yield data of 30 years (1980 to 2009) revealed that the yield of coffee is fluctuating with the variations in climatic parameters. Among the species, productivity was higher for C. canephora coffee than C. arabica in most of the years. Maximum yield of C. canephora (2040 kg ha-1) was recorded in 2003-2004 and there was declining trend of yield noticed in the recent years. Similarly, the maximum yield of C. arabica (1745 kg ha-1) was recorded in 1988-1989 and decreased yield was noticed in the subsequent years till 1997-1998 due to year to year variability in climate. The highest correlation coefficient was found between the yield of C. arabica coffee and maximum temperature during January (0.7) and between C. arabica coffee yield and RH during July (0.4). Yield of C. canephora coffee had highest correlation with maximum temperature, RH and rainfall during February. Statistical regression model between selected climatic parameters and yield of C. arabica and C. canephora coffee was developed to forecast the yield of coffee in Wayanad district in Kerala. The model was validated for years 2010, 2011, and 2012 with the coffee yield data obtained during the years and the prediction was found to be good.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

Savanna landscapes are globally extensive and highly sensitive to climate change, yet the physical processes and climate phenomena which affect them remain poorly understood and therefore poorly represented in climate models. Both human populations and natural ecosystems are highly susceptible to precipitation variation in these regions due to the effects on water and food availability and atmosphere-biosphere energy fluxes. Here we quantify the relationship between climate phenomena and historical rainfall variability in Australian savannas and, in particular, how these relationships changed across a strong rainfall gradient, namely the North Australian Tropical Transect (NATT). Climate phenomena were described by 16 relevant climate indices and correlated against precipitation from 1900 to 2010 to determine the relative importance of each climate index on seasonal, annual and decadal timescales. Precipitation trends, climate index trends and wet season characteristics have also been investigated using linear statistical methods. In general, climate index-rainfall correlations were stronger in the north of the NATT where annual rainfall variability was lower and a high proportion of rainfall fell during the wet season. This is consistent with a decreased influence of the Indian-Australian monsoon from the north to the south. Seasonal variation was most strongly correlated with the Australian Monsoon Index, whereas yearly variability was related to a greater number of climate indices, predominately the Tasman Sea and Indonesian sea surface temperature indices (both of which experienced a linear increase over the duration of the study) and the El Niño-Southern Oscillation indices. These findings highlight the importance of understanding the climatic processes driving variability and, subsequently, the importance of understanding the relationships between rainfall and climatic phenomena in the Northern Territory in order to project future rainfall patterns in the region.

Late Holocene sea level variability and Atlantic Meridional Overturning Circulation

USGS Publications Warehouse

Cronin, Thomas M.; Farmer, Jesse R.; Marzen, R. E.; Thomas, E.; Varekamp, J.C.

2014-01-01

Pre-twentieth century sea level (SL) variability remains poorly understood due to limits of tide gauge records, low temporal resolution of tidal marsh records, and regional anomalies caused by dynamic ocean processes, notably multidecadal changes in Atlantic Meridional Overturning Circulation (AMOC). We examined SL and AMOC variability along the eastern United States over the last 2000 years, using a SL curve constructed from proxy sea surface temperature (SST) records from Chesapeake Bay, and twentieth century SL-sea surface temperature (SST) relations derived from tide gauges and instrumental SST. The SL curve shows multidecadal-scale variability (20–30 years) during the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA), as well as the twentieth century. During these SL oscillations, short-term rates ranged from 2 to 4 mm yr−1, roughly similar to those of the last few decades. These oscillations likely represent internal modes of climate variability related to AMOC variability and originating at high latitudes, although the exact mechanisms remain unclear. Results imply that dynamic ocean changes, in addition to thermosteric, glacio-eustatic, or glacio-isostatic processes are an inherent part of SL variability in coastal regions, even during millennial-scale climate oscillations such as the MCA and LIA and should be factored into efforts that use tide gauges and tidal marsh sediments to understand global sea level rise.

Synchronous centennial-scale variability in abundance of remote sardine populations in the Pacific

NASA Astrophysics Data System (ADS)

Kuwae, M.; Takashige, S.; Yamamoto, M.; Sagawa, T.; Takeoka, H.

2012-12-01

A number of studies have identified evidence for connections between Pacific climate decadal variability and variations in Pacific marine ecosystems which are typically shown in abundance of remote sardine and anchovy species off Japan, California, Peru, and Chile as well as Alaska salmon species. The variations in climate indices and abundance of sardine and anchovy species most likely have 50-70 year cycles and therefore these natural perturbations in climates and Pacific ecosystems should be considered for developing predictive models of fisheries productions and the managements. Despite the importance of natural perturbations for long-term predictions, one issue, whether synchronous centennial-variations in remote Pacific fisheries productions in response to climate variability exists in the past, has not been questioned, because there has never been long-term reconstructed time series in the western North Pacific. Here we present well preserved, fossil fish scale-based abundance record of Japanese sardine over the last 1100 years reconstructed from a seasonal anoxic basin in the western Seto Inland Sea near their spawning areas in the western North Pacific. A comparison of our record with other previous records clearly showed centennial-scale variations in abundance of sardine species off Japan, California, and Chile, characterized by centennial-scale alternations between low abundance regimes and high abundance regimes in which multidecadal fluctuations with large amplitudes occurred once or several times. High abundance regimes from 1450 to 1650 AD and after 1800 AD and a low abundance regime from 1650 to 1800 AD corresponded to low frequency patterns of PDO index reconstructed from tree-ring records in North America. This indicates that connections between Pacific climate variability and variations in Pacific marine ecosystems exist not only on multidecadal timescales but on centennial timescales. Three to four hundred-yr periodicity of the Pacific climate-ecosystem dynamics suggests possibility of a change into a century-long, low sardine abundance regime in the next 100 years.

Tropical Pacific climate variability over the last 6000 years as recorded in Bainbridge Crater Lake, Galápagos

NASA Astrophysics Data System (ADS)

Thompson, Diane M.; Conroy, Jessica L.; Collins, Aaron; Hlohowskyj, Stephan R.; Overpeck, Jonathan T.; Riedinger-Whitmore, Melanie; Cole, Julia E.; Bush, Mark B.; Whitney, H.; Corley, Timothy L.; Kannan, Miriam Steinitz

2017-08-01

Finely laminated sediments within Bainbridge Crater Lake, Galápagos, provide a record of El Niño-Southern Oscillation (ENSO) events over the Holocene. Despite the importance of this sediment record, hypotheses for how climate variability is preserved in the lake sediments have not been tested. Here we present results of long-term monitoring of the local climate and limnology and a revised interpretation of the sediment record. Brown-green, organic-rich, siliciclastic laminae reflect warm, wet conditions typical of El Niño events, whereas carbonate and gypsum precipitate during cool, dry La Niña events and persistent dry periods, respectively. Applying this new interpretation, we find that ENSO events of both phases were generally less frequent during the mid-Holocene ( 6100-4000 calendar years B.P.) relative to the last 1500 calendar years. Abundant carbonate laminations between 3500 and 3000 calendar years B.P. imply that conditions in the Galápagos region were cool and dry during this period when the tropical Pacific E-W sea surface temperature (SST) gradient likely strengthened. The frequency of El Niño and La Niña events then intensified dramatically around 1750-2000 calendar years B.P., consistent with a weaker SST gradient and an increased frequency of ENSO events in other regional records. This strong interannual variability persisted until 700 calendar years B.P., when ENSO-related variability at the lake decreased as the SST gradient strengthened. Persistent, dry conditions then dominated between 300 and 50 calendar years B.P. (A.D. 1650-1900, ± 100 years), whereas wetter conditions and frequent El Niño events dominated in the most recent century.

A global perspective on Glacial- to Interglacial variability change

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Münch, Thomas; Ho, Sze Ling; Laepple, Thomas

2017-04-01

Changes in climate variability are more important for society than changes in the mean state alone. While we will be facing a large-scale shift of the mean climate in the future, its implications for climate variability are not well constrained. Here we quantify changes in temperature variability as climate shifted from the Last Glacial cold to the Holocene warm period. Greenland ice core oxygen isotope records provide evidence of this climatic shift, and are used as reference datasets in many palaeoclimate studies worldwide. A striking feature in these records is pronounced millennial variability in the Glacial, and a distinct reduction in variance in the Holocene. We present quantitative estimates of the change in variability on 500- to 1500-year timescales based on a global compilation of high-resolution proxy records for temperature which span both the Glacial and the Holocene. The estimates are derived based on power spectral analysis, and corrected using estimates of the proxy signal-to-noise ratios. We show that, on a global scale, variability at the Glacial maximum is five times higher than during the Holocene, with a possible range of 3-10 times. The spatial pattern of the variability change is latitude-dependent. While the tropics show no changes in variability, mid-latitude changes are higher. A slight overall reduction in variability in the centennial to millennial range is found in Antarctica. The variability decrease in the Greenland ice core oxygen isotope records is larger than in any other proxy dataset. These results therefore contradict the view of a globally quiescent Holocene following the instable Glacial, and imply that, in terms of centennial to millennial temperature variability, the two states may be more similar than previously thought.

Quantifying the effects of climate variability and human activities on runoff for Kaidu River Basin in arid region of northwest China

NASA Astrophysics Data System (ADS)

Chen, Zhongsheng; Chen, Yaning; Li, Baofu

2013-02-01

Much attention has recently been focused on the effects that climate variability and human activities have had on runoff. In this study, data from the Kaidu River Basin in the arid region of northwest China were analyzed to investigate changes in annual runoff during the period of 1960-2009. The nonparametric Mann-Kendall test and the Mann-Kendall-Sneyers test were used to identify trend and step change point in the annual runoff. It was found that the basin had a significant increasing trend in annual runoff. Step change point in annual runoff was identified in the basin, which occurred in the year around 1993 dividing the long-term runoff series into a natural period (1960-1993) and a human-induced period (1994-2009). Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In 1994-2009, climate variability was the main factor that increased runoff with contribution of 90.5 %, while the increasing percentage due to human activities only accounted for 9.5 %, showing that runoff in the Kaidu River Basin is more sensitive to climate variability than human activities. This study quantitatively distinguishes the effects between climate variability and human activities on runoff, which can do duty for a reference for regional water resources assessment and management.

Millennial-scale variability to 735 ka: High-resolution climate records from Santa Barbara Basin, CA

NASA Astrophysics Data System (ADS)

White, Sarah M.; Hill, Tessa M.; Kennett, James P.; Behl, Richard J.; Nicholson, Craig

2013-06-01

Determining the ultimate cause and effect of millennial-scale climate variability remains an outstanding problem in paleoceanography, partly due to the lack of high-resolution records predating the last glaciation. Recent cores from Santa Barbara Basin provide 2500-5700 year "windows" of climate with 10-50 year resolution. Ages for three cores, determined by seismic stratigraphic correlation, oxygen isotope stratigraphy, and biostratigraphy, date to 293 ka (MIS 8), 450 ka (MIS 12), and 735 ka (MIS 18). These records sample the Late Pleistocene, during which the 100 kyr cycle strengthened and the magnitude of glacial-interglacial cyclicity increased. Thus, these records provide a test of the dependence of millennial-scale behavior on variations in glacial-interglacial cyclicity. The stable isotopic (δ18O) composition of planktonic foraminifera shows millennial-scale variability in all three intervals, with similar characteristics (duration, cyclicity) to those previously documented during MIS 3 at this site. Stadial G. bulloides δ18O values are 2.75-1.75‰ (average 2.25‰) and interstadial values are 1.75-0.5‰ (average 1‰), with rapid (decadal-scale) interstadial and stadial initiations of 1-2‰, as in MIS 3. Interstadials lasted 250-1600 years and occurred every 650-1900 years. Stadial paleotemperatures were 3.5-9.5°C and interstadial paleotemperatures were 7.5-13°C. Upwelling, evidenced by planktonic foraminiferal assemblages and δ13C, increased during interstadials, similar to MIS 3; high productivity during some stadials was reminiscent of the Last Glacial Maximum. This study builds upon previous records in showing that millennial-scale shifts were an inherent feature of Northern Hemisphere glacial climates since 735 ka, and they remained remarkably constant in the details of their amplitude, cyclicity, and temperature variability.

Setting in evidence of the new climatic tendency in Algeria by the analysis of the main variables of the climate : Survey of the chronological sets on more of 50 years.

NASA Astrophysics Data System (ADS)

Zeineddine, N.

2009-09-01

Setting in evidence of the new climatic tendency in Algeria by the analysis of the main variables of the climate : Survey of the chronological sets on more of 50 years. In the present conditions of the global climatic changes, North Africa and Maghreb, observe these last years of the distresses without precedent. This new tendency expresses itself by a rise of the temperatures confirmed in several countries. In the same way to this rise, one also notes an intensification of the climatic cycles (more and more humid humid periods, more and more dry dry periods). So, after the long droughts observed in the years four - twenty and ninety, the a lot more humid period bootjack is noted in the whole region. These phases are punctuated however sometimes of stern droughts, that been the case in 2000 to Morocco and in Algeria. The humid phases are as for them more and more frequent and are characterized henceforth by very intense rainy episodes. Repeatedly, serious floodings touched these countries. In 2002 in Algeria, it is the capital that has been touched, the districts of Bab - El Wadi was heavily damaged. In the valley of the Soummam, the town of Bejaïa was the theater of important phenomena of urban flooding in 2007. In the Algerian Sahara, heavy rains provoked the rise in the water level of the wadi M' Zab and the submersion of the city of Ghardaïa. All as Algeria, Tunisia has also been touched by these phenomena. The city of Tunis knew a tragic episode thus in 2007. To the west extreme of North Africa in 2002, Morocco has been hit by important floodings that made 35 deaths.. Progressively, the climatic conditions become unusual. The signs of the changes prove to be even more meaningful with the records of rain for the agricultural year 2008 / 2009 in the under region from the Maghreb (Morocco - Algeria). Qualified of exceptional and historic, rains have generously supplied the watertables, carrying the water security margin to close to two years in drinking water and in water intended to the irrigation. The replenishment of the dams is also he without precedent and add up to close to 80% in Morocco and to 72% in Algeria. Through the survey of the Algerian example, I will try to raise the new climatic tendency that characterizes this region. The analysis of rain and the other climatic variables, (temperature, number of rain days and number of storm days) aims to make appear the main fluctuations and the general tendency that marked more of fifty years of measure, to a national and regional scale. This analysis will be able to confirm thus or will be able to invalidate the return toward conditions more hot and more humid with more intense rains. The used methodology will be based on the treatment of chronological sets long-term (of the order of 30 years). The statistical behavior of the sets will permit to compare the respective evolutions of the different variable. Key - Words : Climatic tendency, humid phase, intense rain, climatic warming up,

Bidecadal North Atlantic ocean circulation variability controlled by timing of volcanic eruptions.

PubMed

Swingedouw, Didier; Ortega, Pablo; Mignot, Juliette; Guilyardi, Eric; Masson-Delmotte, Valérie; Butler, Paul G; Khodri, Myriam; Séférian, Roland

2015-03-30

While bidecadal climate variability has been evidenced in several North Atlantic paleoclimate records, its drivers remain poorly understood. Here we show that the subset of CMIP5 historical climate simulations that produce such bidecadal variability exhibits a robust synchronization, with a maximum in Atlantic Meridional Overturning Circulation (AMOC) 15 years after the 1963 Agung eruption. The mechanisms at play involve salinity advection from the Arctic and explain the timing of Great Salinity Anomalies observed in the 1970s and the 1990s. Simulations, as well as Greenland and Iceland paleoclimate records, indicate that coherent bidecadal cycles were excited following five Agung-like volcanic eruptions of the last millennium. Climate simulations and a conceptual model reveal that destructive interference caused by the Pinatubo 1991 eruption may have damped the observed decreasing trend of the AMOC in the 2000s. Our results imply a long-lasting climatic impact and predictability following the next Agung-like eruption.

Using Scaling to Understand, Model and Predict Global Scale Anthropogenic and Natural Climate Change

NASA Astrophysics Data System (ADS)

Lovejoy, S.; del Rio Amador, L.

2014-12-01

The atmosphere is variable over twenty orders of magnitude in time (≈10-3 to 1017 s) and almost all of the variance is in the spectral "background" which we show can be divided into five scaling regimes: weather, macroweather, climate, macroclimate and megaclimate. We illustrate this with instrumental and paleo data. Based the signs of the fluctuation exponent H, we argue that while the weather is "what you get" (H>0: fluctuations increasing with scale), that it is macroweather (H<0: fluctuations decreasing with scale) - not climate - "that you expect". The conventional framework that treats the background as close to white noise and focuses on quasi-periodic variability assumes a spectrum that is in error by a factor of a quadrillion (≈ 1015). Using this scaling framework, we can quantify the natural variability, distinguish it from anthropogenic variability, test various statistical hypotheses and make stochastic climate forecasts. For example, we estimate the probability that the warming is simply a giant century long natural fluctuation is less than 1%, most likely less than 0.1% and estimate return periods for natural warming events of different strengths and durations, including the slow down ("pause") in the warming since 1998. The return period for the pause was found to be 20-50 years i.e. not very unusual; however it immediately follows a 6 year "pre-pause" warming event of almost the same magnitude with a similar return period (30 - 40 years). To improve on these unconditional estimates, we can use scaling models to exploit the long range memory of the climate process to make accurate stochastic forecasts of the climate including the pause. We illustrate stochastic forecasts on monthly and annual scale series of global and northern hemisphere surface temperatures. We obtain forecast skill nearly as high as the theoretical (scaling) predictability limits allow: for example, using hindcasts we find that at 10 year forecast horizons we can still explain ≈ 15% of the anomaly variance. These scaling hindcasts have comparable - or smaller - RMS errors than existing GCM's. We discuss how these be further improved by going beyond time series forecasts to space-time.

Climate as a driver of continent-wide irruptions in boreal seed-eating birds (Invited)

NASA Astrophysics Data System (ADS)

Strong, C.; Zuckerberg, B.; Betancourt, J. L.

2013-12-01

Boreal seed-eating birds regularly breed and overwinter throughout Canada and Alaska, but every few years these species demonstrate impressive irruptive migrations out of the boreal forest and into more southerly regions. It is thought that irruptive migrations are inversely dependent on a circumboreally synchronized pattern of seed crop fluctuations in boreal trees; seed-eating boreal birds stay in the north when food is plentiful, but sojourn south when food is scarce. Because both seed production and bird irruptions are characterized by periodicity ranging from biennial to decadal cycles, there is a strong possibility that these ecological phenomena are driven by climate variability. Using over twenty years of data from Project FeederWatch (a national citizen science project), we found that 'super irruptions' are correlated with continent-wide irruptive events in pine siskin population, and that these irruptions are associated with multi-decadal climate variability of Pacific origin. We also investigate how climate variability may influence the distribution of boreal bird species across different regions of North America during winter, and evaluate results in the context of limited banding data to assess possible geographic pathways of irruptions.

Demands, skill discretion, decision authority and social climate at work as determinants of major depression in a 3-year follow-up study.

PubMed

Fandiño-Losada, Andrés; Forsell, Yvonne; Lundberg, Ingvar

2013-07-01

The psychosocial work environment may be a determinant of the development and course of depressive disorders, but the literature shows inconsistent findings. Thus, the aim of this study is to determine longitudinal effects of the job demands-control-support model (JDCSM) variables on the occurrence of major depression among working men and women from the general population. The sample comprised 4,710 working women and men living in Stockholm, who answered the same questionnaire twice, 3 years apart, who were not depressed during the first wave and had the same job in both waves. The questionnaire included JDCSM variables (demands, skill discretion, decision authority and social climate) and other co-variables (income, education, occupational group, social support, help and small children at home, living with an adult and depressive symptoms at time 1; and negative life events at time 2). Multiple logistic regressions were run to calculate odds ratios of having major depression at time 2, after adjustment for other JDCSM variables and co-variables. Among women, inadequate work social climate was the only significant risk indicator for major depression. Surprisingly, among men, high job demands and low skill discretion appeared as protective factors against major depression. The results showed a strong relationship between inadequate social climate and major depression among women, while there were no certain effects for the remaining exposure variables. Among men, few cases of major depression hampered well-founded conclusions regarding our findings of low job demands and high skill discretion as related to major depression.

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.

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

USGS Publications Warehouse

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

1999-01-01

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

Long-Term and Seasonal Dynamics of Dengue in Iquitos, Peru

PubMed Central

Stoddard, Steven T.; Wearing, Helen J.; Reiner, Robert C.; Morrison, Amy C.; Astete, Helvio; Vilcarromero, Stalin; Alvarez, Carlos; Ramal-Asayag, Cesar; Sihuincha, Moises; Rocha, Claudio; Halsey, Eric S.; Scott, Thomas W.; Kochel, Tadeusz J.; Forshey, Brett M.

2014-01-01

Introduction Long-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world's population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data. Methods We studied 10 years (2000–2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases. Findings Transmission was dominated by single serotypes, first DENV-3 (2001–2007) then DENV-4 (2008–2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season. Conclusions Dengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos. PMID:25033412

Implications of climate variability for monitoring the effectiveness of global mercury policy

NASA Astrophysics Data System (ADS)

Giang, A.; Monier, E.; Couzo, E. A.; Pike-thackray, C.; Selin, N. E.

2016-12-01

We investigate how climate variability affects ability to detect policy-related anthropogenic changes in mercury emissions in wet deposition monitoring data using earth system and atmospheric chemistry modeling. The Minamata Convention, a multilateral environmental agreement that aims to protect human health and the environment from anthropogenic emissions and releases of mercury, includes provisions for monitoring treaty effectiveness. Because meteorology can affect mercury chemistry and transport, internal variability is an important contributor to uncertainty in how effective policy may be in reducing the amount of mercury entering ecosystems through wet deposition. We simulate mercury chemistry using the GEOS-Chem global transport model to assess the influence of meteorology in the context of other uncertainties in mercury cycling and policy. In these simulations, we find that interannual variability in meteorology may be a dominant contributor to the spatial pattern and magnitude of historical regional wet deposition trends. To further assess the influence of climate variability in the GEOS-Chem mercury simulation, we use a 5-member ensemble of meteorological fields from the MIT Integrated Global System Model under present and future climate. Each member involves randomly initialized 20 year simulations centered around 2000 and 2050 (under a no-policy and a climate stabilization scenario). Building on previous efforts to understand climate-air quality interactions for ground-level O3 and particulate matter, we estimate from the ensemble the range of trends in mercury wet deposition given natural variability, and, to extend our previous results on regions that are sensitive to near-source vs. remote anthropogenic signals, we identify geographic regions where mercury wet deposition is most sensitive to this variability. We discuss how an improved understanding of natural variability can inform the Conference of Parties on monitoring strategy and policy ambition.

From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)

NASA Astrophysics Data System (ADS)

Brücher, Tim; Latif, Mojib

2017-04-01

We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).

Low-resolution Australasian palaeoclimate records of the last 2000 years

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Modelling the biophysical and socio-economic potential of Sustainable Land Management (SLM) in the Cabo Verde drylands: The PESERA-DESMICE approach.

NASA Astrophysics Data System (ADS)

Baptista, Isaurinda; Irvine, Brian; Fleskens, Luuk; Geissen, Violette; Ritsema, Coen

2015-04-01

Rainfall variability, the occurrence of extreme drought and historic land management practice have been recognised as contributing to serious environmental impact in Cabo Verde. Investment in conservation measures has become visible throughout the landscape. Despite this the biophysical and socioeconomic impacts of the conservation measures have been poorly assessed and documented. As such a concerted approach based on the DESIRE project continues to consult stackholders and carry out field trials for selected conservation technologies. Recent field trials have demonstrated the potential of conservation technologies but have also demonstrated that yield variability between sites and between years is significant. This variability appears to be driven by soil and rainfall characteristics However, where detailed field studies have only run for a limited period they have not as yet encountered the full range of climatic variability; thus a modelling approach is considered to capture a greater range of climatic conditions. The PESERA-DESMICE model is adopted which considers the biophysical and social economic benefits of the conservation technologies against a local baseline condition. PESERA is adopted as climate is implicitly considered in the model and, where appropriate, in-situ conservation measures are considered as an annual input to the soil. The DESMICE component of the model considers the suitability of the conservation measures and their costs and benefits in terms of environmental conditions and market access. Historic rainfall statistics are calculated from field measurements in the Ribeira Seca catchment. These statistics are used to generate a series of 50 year rainfall realisations to capture a fuller range of the climatic conditions. Each realisation provides a unique time-series of rainfall and through modelling can provide a simulated time-series of crop yield. Additional realisations and model simulations add to an envelope of the potential crop yield and cost-benefit relations. The development of such envelopes help express the agricultural risk associated with climate variability and the potential of the conservation measures to absorb the risk. Thus, highlighting the uncertainty of a given crop yield being achieved in any particular year. Such information that can directly inform or influence the adoption of conservation measures under the climatic variability of the Cabo Verde drylands.

Country-Specific Effects of Climate Variability on Human Migration.

PubMed

Gray, Clark; Wise, Erika

2016-04-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe.

Medium term hurricane catastrophe models: a validation experiment

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Seasonal prediction for hydro-meteorological variables in the Korean Peninsula: Links with atmospheric teleconnections

NASA Astrophysics Data System (ADS)

Yoon, S.

2016-12-01

This study analyzes nonlinear behavior links with atmospheric teleconnections between hydrologic variables and climate indices using statistical models over the Korean Peninsula (KP). The ocean-related major climate factors such as the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) mode in the Tropical Ocean (TO) region were used to analyze the atmospheric teleconnections by principal component analysis (PCA) and a singular spectrum analysis (SSA). The nonlinear lag time correlations between climate indices and hydrological variables are calculated by the Mutual Information (MI) techniques. Results show that teleconnection based nonlinear correlation coefficients (CCs) were higher than linear CCs, ENSO shows a few months of lag time correlation with IOD, which has a direct influence on rainfall and streamflow anomalies in the KP. The precipitation and streamflow in KP shows a significant increasing and decreasing tendency during warm pool (WP) and cold tongue (CT) El Niño decaying years, respectively, while the La Niña year shows slightly above normal conditions. IOD events show significantly decreasing and increasing long-term normal conditions during positive and negative years, respectively. A better understanding of the relationship between climate indices and streamflow can help policy makers prepare for possible options in river discharge pattern changes. Furthermore, these results provide useful information for water managers and end-users to support long-range water resources prediction and water-related management plan.

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.

Regional Climate and Streamflow Projections in North America Under IPCC CMIP5 Scenarios

NASA Astrophysics Data System (ADS)

Chang, H. I.; Castro, C. L.; Troch, P. A. A.; Mukherjee, R.

2014-12-01

The Colorado River system is the predominant source of water supply for the Southwest U.S. and is already fully allocated, making the region's environmental and economic health particularly sensitive to annual and multi-year streamflow variability. Observed streamflow declines in the Colorado Basin in recent years are likely due to synergistic combination of anthropogenic global warming and natural climate variability, which are creating an overall warmer and more extreme climate. IPCC assessment reports have projected warmer and drier conditions in arid to semi-arid regions (e.g. Solomon et al. 2007). The NAM-related precipitation contributes to substantial Colorado streamflows. Recent climate change studies for the Southwest U.S. region project a dire future, with chronic drought, and substantially reduced Colorado River flows. These regional effects reflect the general observation that climate is being more extreme globally, with areas climatologically favored to be wet getting wetter and areas favored to be dry getting drier (Wang et al. 2012). Multi-scale downscaling modeling experiments are designed using recent IPCC AR5 global climate projections, which incorporate regional climate and hydrologic modeling components. The Weather Research and Forecasting model (WRF) has been selected as the main regional modeling tool; the Variable Infiltration Capacity model (VIC) will be used to generate streamflow projections for the Colorado River Basin. The WRF domain is set up to follow the CORDEX-North America guideline with 25km grid spacing, and VIC model is individually calibrated for upper and lower Colorado River basins in 1/8° resolution. The multi-scale climate and hydrology study aims to characterize how the combination of climate change and natural climate variability is changing cool and warm season precipitation. Further, to preserve the downscaled RCM sensitivity and maintain a reasonable climatology mean based on observed record, a new bias correction technique is applied when using the RCM climatology to the streamflow model. Of specific interest is how major droughts associated with La Niña-like conditions may worsen in the future, as these are the times when the Colorado River system is most critically stressed and would define the "worst case" scenario for water resource planning.

IODP Site 1476: 7.5 Million Year Record of Southeast African Climate

NASA Astrophysics Data System (ADS)

Cantu, K.; Norris, R. D.

2017-12-01

The primary focus of IODP Expedition 361 was Southeast African Climate. Site 1476 in the northern Mozambique Channel yielded a sediment record going back roughly 7.6 million years, a time frame particularly interesting due to its relevance to hominid evolution. Previous paleoclimate studies from the region have included lake sediments and soil carbonate isotopes, which have been interpreted as showing a long-term trend toward increasing aridity. Lake Malawi records from the last 1.3 million years show a change during the Mid-Pleistocene Transition (MPT) from high frequency variability and generally lower lake levels to higher amplitude variability and higher lake levels punctuated by long, severe droughts resulting in extreme and long-lasting low-stands. Site 1476 cores were scanned using X-Ray Fluorescence (XRF), which gives semi-quantitative elemental abundances. Elemental abundance ratios are used as proxies for a variety of climate-related signals, such as changes in weathering rates, the nature of terrigenous material, and grain size. Looking at the site's Fe/Ca, K/Ca, and Rb/Zr ratios, the period of 4.5 to about 1.5 million years ago shows higher terrigenous flux, higher clay flux, and a smaller grain size respectively than most of the previous 3 million years, followed by a steep decline before the MPT, before transitioning to a pattern of high amplitude oscillations post-MPT. These higher amplitude oscillations seem to correspond to Lake Malawi low stands in the post-MPT period, suggesting that the higher flux of terrigenous material to site 1476 is due to higher aridity resulting in lower vegetative cover. This data also point to high climate variability in the last million years, likely contributing to the evolution and ecological adaptability of our species.

Landsat Surface Reflectance Climate Data Records

USGS Publications Warehouse

,

2014-01-01

Landsat Surface Reflectance Climate Data Records (CDRs) are high level Landsat data products that support land surface change studies. Climate Data Records, as defined by the National Research Council, are a time series of measurements with sufficient length, consistency, and continuity to identify climate variability and change. The U.S. Geological Survey (USGS) is using the valuable 40-year Landsat archive to create CDRs that can be used to document changes to Earth’s terrestrial environment.

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

DTIC Science & Technology

2007-04-01

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

Temperature Anomalies from the AIRS Product in Giovanni for the Climate Community

NASA Technical Reports Server (NTRS)

Ding, Feng; Hearty, Thomas J.; Wei, Jennifer; Theobald, Michael; Vollmer, Bruce; Seiler, Edward; Meyer, David

2018-01-01

The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Relating annual increments of the endangered Blanding's turtle plastron growth to climate

PubMed Central

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-01-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration. PMID:24963390

Relating annual increments of the endangered Blanding's turtle plastron growth to climate.

PubMed

Richard, Monik G; Laroque, Colin P; Herman, Thomas B

2014-05-01

This research is the first published study to report a relationship between climate variables and plastron growth increments of turtles, in this case the endangered Nova Scotia Blanding's turtle (Emydoidea blandingii). We used techniques and software common to the discipline of dendrochronology to successfully cross-date our growth increment data series, to detrend and average our series of 80 immature Blanding's turtles into one common chronology, and to seek correlations between the chronology and environmental temperature and precipitation variables. Our cross-dated chronology had a series intercorrelation of 0.441 (above 99% confidence interval), an average mean sensitivity of 0.293, and an average unfiltered autocorrelation of 0.377. Our master chronology represented increments from 1975 to 2007 (33 years), with index values ranging from a low of 0.688 in 2006 to a high of 1.303 in 1977. Univariate climate response function analysis on mean monthly air temperature and precipitation values revealed a positive correlation with the previous year's May temperature and current year's August temperature; a negative correlation with the previous year's October temperature; and no significant correlation with precipitation. These techniques for determining growth increment response to environmental variables should be applicable to other turtle species and merit further exploration.

Global characteristics of stream flow seasonality and variability

USGS Publications Warehouse

Dettinger, M.D.; Diaz, Henry F.

2000-01-01

Monthly stream flow series from 1345 sites around the world are used to characterize geographic differences in the seasonality and year-to-year variability of stream flow. Stream flow seasonality varies regionally, depending on the timing of maximum precipitation, evapotranspiration, and contributions from snow and ice. Lags between peaks of precipitation and stream flow vary smoothly from long delays in high-latitude and mountainous regions to short delays in the warmest sectors. Stream flow is most variable from year to year in dry regions of the southwest United States and Mexico, the Sahel, and southern continents, and it varies more (relatively) than precipitation in the same regions. Tropical rivers have the steadiest flows. El Nin??o variations are correlated with stream flow in many parts of the Americas, Europe, and Australia. Many stream flow series from North America, Europe, and the Tropics reflect North Pacific climate, whereas series from the eastern United States, Europe, and tropical South America and Africa reflect North Atlantic climate variations.

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

NASA Technical Reports Server (NTRS)

2012-01-01

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

The seasonal response of the Held-Suarez climate model to prescribed ocean temperature anomalies. I - Results of decadal integrations

NASA Technical Reports Server (NTRS)

Phillips, T. J.; Semtner, A. J., Jr.

1984-01-01

Anomalies in ocean surface temperature have been identified as possible causes of variations in the climate of particular seasons or as a source of interannual climatic variability, and attempts have been made to forecast seasonal climate by using ocean temperatures as predictor variables. However, the seasonal atmospheric response to ocean temperature anomalies has not yet been systematically investigated with nonlinear models. The present investigation is concerned with ten-year integrations involving a model of intermediate complexity, the Held-Suarez climate model. The calculations have been performed to investigate the changes in seasonal climate which result from a fixed anomaly imposed on a seasonally varying, global ocean temperature field. Part I of the paper provides a report on the results of these decadal integrations. Attention is given to model properties, the experimental design, and the anomaly experiments.

Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon.

PubMed

Preisler, Haiganoush K; Hicke, Jeffrey A; Ager, Alan A; Hayes, Jane L

2012-11-01

Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process models that simulate climate suitability for mountain pine beetle outbreaks have advanced our understanding of beetle population dynamics; however, there are few studies that have assessed their accuracy across multiple outbreaks or at larger spatial scales. This study used the observed number of trees killed by mountain pine beetles per square kilometer in Oregon and Washington, USA, over the past three decades to quantify and assess the influence of climate and weather variables on beetle activity over longer time periods and larger scales than previously studied. Influences of temperature and precipitation in addition to process model output variables were assessed at annual and climatological time scales. The statistical analysis showed that new attacks are more likely to occur at locations with climatological mean August temperatures >15 degrees C. After controlling for beetle pressure, the variables with the largest effect on the odds of an outbreak exceeding a certain size were minimum winter temperature (positive relationship) and drought conditions in current and previous years. Precipitation levels in the year prior to the outbreak had a positive effect, possibly an indication of the influence of this driver on brood size. Two-year cumulative precipitation had a negative effect, a possible indication of the influence of drought on tree stress. Among the process model variables, cold tolerance was the strongest indicator of an outbreak increasing to epidemic size. A weather suitability index developed from the regression analysis indicated a 2.5x increase in the odds of outbreak at locations with highly suitable weather vs. locations with low suitability. The models were useful for estimating expected amounts of damage (total area with outbreaks) and for quantifying the contribution of climate to total damage. Overall, the results confirm the importance of climate and weather on the spatial expansion of bark beetle outbreaks over time.

Association between Climatic Variables and Malaria Incidence: A Study in Kokrajhar District of Assam, India

PubMed Central

Nath, Dilip C.; Mwchahary, Dimacha Dwibrang

2013-01-01

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with z malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models. PMID:23283041

Association between climatic variables and malaria incidence: a study in Kokrajhar district of Assam, India.

PubMed

Nath, Dilip C; Mwchahary, Dimacha Dwibrang

2012-11-11

A favorable climatic condition for transmission of malaria prevails in Kokrajhar district throughout the year. A sizeable part of the district is covered by forest due to which dissimilar dynamics of malaria transmission emerge in forest and non-forest areas. Observed malaria incidence rates of forest area, non-forest area and the whole district over the period 2001-2010 were considered for analyzing temporal correlation between malaria incidence and climatic variables. Associations between the two were examined by Pearson correlation analysis. Cross-correlation tests were performed between pre-whitened series of climatic variable and malaria series. Linear regressions were used to obtain linear relationships between climatic factors and malaria incidence, while weighted least squares regression was used to construct models for explaining and estimating malaria incidence rates. Annual concentration of malaria incidence was analyzed by Markham technique by obtaining seasonal index. Forest area and non-forest area have distinguishable malaria seasons. Relative humidity was positively correlated with forest malaria incidence, while temperature series were negatively correlated with non-forest malaria incidence. There was higher seasonality of concentration of malaria in the forest area than non-forest area. Significant correlation between annual changes in malaria cases in forest area and temperature was observed (coeff=0.689, p=0.040). Separate reliable models constructed for forecasting malaria incidence rates based on the combined influence of climatic variables on malaria incidence in different areas of the district were able to explain substantial percentage of observed variability in the incidence rates (R2adj=45.4%, 50.6%, 47.2%; p< .001 for all). There is an intricate association between climatic variables and malaria incidence of the district. Climatic variables influence malaria incidence in forest area and non-forest area in different ways. Rainfall plays a primary role in characterizing malaria incidences in the district. Malaria parasites in the district had adapted to a relative humidity condition higher than the normal range for transmission in India. Instead of individual influence of the climatic variables, their combined influence was utilizable for construction of models.

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.;

Revealing climate modes in steric sea levels: lessons learned from satellite geodesy, objective analyses and ocean reanalyses

NASA Astrophysics Data System (ADS)

Pfeffer, J.; Tregoning, P.; Purcell, A. P.

2017-12-01

Due to increased greenhouse gases emissions, the oceans are accumulating heat. In response to the ocean circulation and atmospheric forcing, the heat is irregularly redistributed within the oceans, causing sea level to rise at variable rates in space and time. These rates of steric expansion are extremely difficult to assess because of the sparsity of in-situ hydrographic observations available within the course of the 20th century. We compare here three methods to reconstruct the steric sea levels over the past 13, 25 and 58 years based on satellite geodesy, objective analyses and ocean reanalyses. The interannual to decadal variability of each dataset is explored with a model merging six climate indices representative of the natural variability of the ocean and climate system. Consistent regional patterns are identified for the Pacific Decadal Oscillation (PDO) and El Niño Southern Oscillation (ENSO) in all datasets at all timescales. Despite the short time coverage (13 years), the combination of satellite geodetic data (altimetry and GRACE) also reveals significant steric responses to the North Pacific Gyre Oscillation (NPGO), Indian Dipole (IOD) and Indian ocean basinwide (IOBM) mode. The richer information content in the ocean reanalyses allows us to recover the regional fingerprints of the PDO, ENSO, NPGO, IOD and IOBM, but also of the Atlantic Multidecadal Oscillation (AMO) acting over longer time scales (40 to 60 years). Therefore, ocean reanalyses, coupled with climate mode analyses, constitute innovative and promising tools to investigate the mechanisms triggering the variability of sea level rise over the past decades.

Untangling the causes a decadal-scale drought: a case study in southeast Australia.

NASA Astrophysics Data System (ADS)

Lewis, Sophie; Gallant, Ailie

2017-04-01

Prolonged droughts on the order of multiple years to a decade have recently afflicted many parts of highly populated regions around the globe, for example, the southwest United States and southeast Australia. However, the causes of these droughts remain unclear. A significant contribution from natural decadal-scale climate variability is likely, but there is also conflicting evidence of any contribution from anthropogenic climate change. This work aims to untangle the causes of a 13-year drought in southeast Australia spanning 1997-2009. A suite of historical and control simulations from fully coupled GCMs contained in the CMIP5 archive are employed, and the potential contributions of random climate variability, SST forcing and anthropogenic forcing to the drought are examined. It is likely that random, decadal-scale variability played a significant role in producing the prolonged rainfall deficits across southeast Australia. These were reinforced by several years with El Niño-like conditions, which commonly induce drought in the region, and a lack of La Niña conditions, which are more likely to bring rain. Evidence of contribution of anthropogenic forcing to the drought is limited

Annually resolved ice core records of tropical climate variability over the past ~1800 years.

PubMed

Thompson, L G; Mosley-Thompson, E; Davis, M E; Zagorodnov, V S; Howat, I M; Mikhalenko, V N; Lin, P-N

2013-05-24

Ice cores from low latitudes can provide a wealth of unique information about past climate in the tropics, but they are difficult to recover and few exist. Here, we report annually resolved ice core records from the Quelccaya ice cap (5670 meters above sea level) in Peru that extend back ~1800 years and provide a high-resolution record of climate variability there. Oxygen isotopic ratios (δ(18)O) are linked to sea surface temperatures in the tropical eastern Pacific, whereas concentrations of ammonium and nitrate document the dominant role played by the migration of the Intertropical Convergence Zone in the region of the tropical Andes. Quelccaya continues to retreat and thin. Radiocarbon dates on wetland plants exposed along its retreating margins indicate that it has not been smaller for at least six millennia.

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.

Addressing Air, Land & Water Nitrogen Issues under Changing Climate Trends & Variability

EPA Science Inventory

The climate of western U.S. dairy producing states is anticipated to change significantly over the next 50 to 75 years. A multimedia modeling system based upon the “nitrogen cascade” concept has been configured to address three aspects of sustainability (environmenta...

Unstable relationships between tree ring δ18O and climate variables over southwestern China: possible impacts from increasing central Pacific SSTs

NASA Astrophysics Data System (ADS)

An, Wenling; Liu, Xiaohong; Hou, Shugui; Zeng, Xiaomin; Sun, Weizhen; Wang, Wenzhi; Wang, Yu; Xu, Guobao; Ren, Jiawen

2018-05-01

In this study, we investigated the potential influence of central and eastern Pacific sea surface temperatures (SSTs) on the unstable relationship between earlywood δ18O and climatic factors in the southwestern China from 1902 to 2005. The results show that the strength of the climate signals recorded in the earlywood δ18O series has declined since the late 1970s. This reduction in signal strength may have been caused by the changes in the local hydroclimate, which is associated with the increasing SSTs in the central Pacific Ocean over recent decades. Alongside these increasing SSTs in the central Pacific, southwestern China has experienced more droughts, as well as more severe droughts through the late spring and early summer during the central Pacific (CP) El Niño years than during the eastern Pacific (EP) El Niño years in recent decades. This increased drought frequency may have weakened the response of earlywood δ18O to climate variables.

RICE ice core: Black Carbon reflects climate variability at Roosevelt Island, West Antarctica

NASA Astrophysics Data System (ADS)

Ellis, Aja; Edwards, Ross; Bertler, Nancy; Winton, Holly; Goodwin, Ian; Neff, Peter; Tuohy, Andrea; Proemse, Bernadette; Hogan, Chad; Feiteng, Wang

2015-04-01

The Roosevelt Island Climate Evolution (RICE) project successfully drilled a deep ice core from Roosevelt Island during the 2011/2012 and 2012/2013 seasons. Located in the Ross Ice Shelf in West Antarctica, the site is an ideal location for investigating climate variability and the past stability of the Ross Ice Shelf. Black carbon (BC) aerosols are emitted by both biomass burning and fossil fuels, and BC particles emitted in the southern hemisphere are transported in the atmosphere and preserved in Antarctic ice. The past record of BC is expected to be sensitive to climate variability, as it is modulated by both emissions and transport. To investigate BC variability over the past 200 years, we developed a BC record from two overlapping ice cores (~1850-2012) and a high-resolution snow pit spanning 2010-2012 (cal. yr). Consistent results are found between the snow pit profiles and ice core records. Distinct decadal trends are found with respect to BC particle size, and the record indicates a steady rise in BC particle size over the last 100 years. Differences in emission sources and conditions may be a possible explanation for changes in BC size. These records also show a significant increase in BC concentration over the past decade with concentrations rising over 1.5 ppb (1.5*10^-9 ng/g), suggesting a fundamental shift in BC deposition to the site.

Attribution of declining Western U.S. Snowpack to human effects

USGS Publications Warehouse

Pierce, D.W.; Barnett, T.P.; Hidalgo, H.G.; Das, T.; Bonfils, Celine; Santer, B.D.; Bala, G.; Dettinger, M.D.; Cayan, D.R.; Mirin, A.; Wood, A.W.; Nozawa, T.

2008-01-01

Observations show snowpack has declined across much of the western United States over the period 1950-99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D-A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean-atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D-A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols. ?? 2008 American Meteorological Society.

A comparative modeling analysis of multiscale temporal variability of rainfall in Australia

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

The effects of long-term natural climate variability and human-induced climate change on rainfall variability have become the focus of much concern and recent research efforts. In this paper, we present the results of a comparative analysis of observed multiscale temporal variability of rainfall in the Perth, Newcastle, and Darwin regions of Australia. This empirical and stochastic modeling analysis explores multiscale rainfall variability, i.e., ranging from short to long term, including within-storm patterns, and intra-annual, interannual, and interdecadal variabilities, using data taken from each of these regions. The analyses investigated how storm durations, interstorm periods, and average storm rainfall intensities differ for different climate states and demonstrated significant differences in this regard between the three selected regions. In Perth, the average storm intensity is stronger during La Niña years than during El Niño years, whereas in Newcastle and Darwin storm duration is longer during La Niña years. Increase of either storm duration or average storm intensity is the cause of higher average annual rainfall during La Niña years as compared to El Niño years. On the other hand, within-storm variability does not differ significantly between different ENSO states in all three locations. In the case of long-term rainfall variability, the statistical analyses indicated that in Newcastle the long-term rainfall pattern reflects the variability of the Interdecadal Pacific Oscillation (IPO) index, whereas in Perth and Darwin the long-term variability exhibits a step change in average annual rainfall (up in Darwin and down in Perth) which occurred around 1970. The step changes in Perth and Darwin and the switch in IPO states in Newcastle manifested differently in the three study regions in terms of changes in the annual number of rainy days or the average daily rainfall intensity or both. On the basis of these empirical data analyses, a stochastic rainfall time series model was developed that incorporates the entire range of multiscale variabilities observed in each region, including within-storm, intra-annual, interannual, and interdecadal variability. Such ability to characterize, model, and synthetically generate realistic time series of rainfall intensities is essential for addressing many hydrological problems, including estimation of flood and drought frequencies, pesticide risk assessment, and landslide frequencies.

Environmental variability and the transmission of haemorrhagic fever with renal syndrome in Changsha, People's Republic of China.

PubMed

Xiao, H; Gao, L D; Li, X J; Lin, X L; Dai, X Y; Zhu, P J; Chen, B Y; Zhang, X X; Zhao, J; Tian, H Y

2013-09-01

The transmission of haemorrhagic fever with renal syndrome (HFRS) is influenced by climatic, reservoir and environmental variables. The epidemiology of the disease was studied over a 6-year period in Changsha. Variables relating to climate, environment, rodent host distribution and disease occurrence were collected monthly and analysed using a time-series adjusted Poisson regression model. It was found that the density of the rodent host and multivariate El Niño Southern Oscillation index had the greatest effect on the transmission of HFRS with lags of 2–6 months. However, a number of climatic and environmental factors played important roles in affecting the density and transmission potential of the rodent host population. It was concluded that the measurement of a number of these variables could be used in disease surveillance to give useful advance warning of potential disease epidemics.

Tropical rainforests dominate multi-decadal variability of the global carbon cycle

NASA Astrophysics Data System (ADS)

Zhang, X.; Wang, Y. P.; Peng, S.; Rayner, P. J.; Silver, J.; Ciais, P.; Piao, S.; Zhu, Z.; Lu, X.; Zheng, X.

2017-12-01

Recent studies find that inter-annual variability of global atmosphere-to-land CO2 uptake (NBP) is dominated by semi-arid ecosystems. However, the NBP variations at decadal to multi-decadal timescales are still not known. By developing a basic theory for the role of net primary production (NPP) and heterotrophic respiration (Rh) on NBP and applying it to 100-year simulations of terrestrial ecosystem models forced by observational climate, we find that tropical rainforests dominate the multi-decadal variability of global NBP (48%) rather than the semi-arid lands (35%). The NBP variation at inter-annual timescales is almost 90% contributed by NPP, but across longer timescales is progressively controlled by Rh that constitutes the response from the NPP-derived soil carbon input (40%) and the response of soil carbon turnover rates to climate variability (60%). The NBP variations of tropical rainforests is modulated by the ENSO and the PDO through their significant influences on temperature and precipitation at timescales of 2.5-7 and 25-50 years, respectively. This study highlights the importance of tropical rainforests on the multi-decadal variability of global carbon cycle, suggesting that we need to carefully differentiate the effect of NBP long-term fluctuations associated with ocean-related climate modes on the long-term trend in land sink.

Atlas of climatic controls of wildfire in the western United States

USGS Publications Warehouse

Hostetler, S.W.; Bartlein, P.J.; Holman, J.O.

2006-01-01

Wildfire behavior depends on several factors including ecologic characteristics, near-term and antecedent climatic conditions,fuel availability and moisture level, weather, and sources of ignition (lightning or human). The variability and interplay of these factors over many spatial and temporal scales present an ongoing challenge to our ability to forecast a given wildfire season. Here we focus on one aspect of wildfire in the western US through a retrospective analysis of wildfire (starts and area burned) and climate over monthly time scales. We consider prefire conditions up to a year preceding fire outbreaks. For our analysis, we used daily and monthly wildfire records and a combination of observed and model-simulated atmospheric and surface climate data. The focus of this report is on monthly wildfire and climate for the period 1980-2000. Although a longer fire record is desirable, the 21-year record is the longest currently available and it is sufficient for the purpose of a first-order regional analysis. We present the main results in the form of a wildfire-climate atlas for 8 subregions of the West that can be used by resource managers to assess current wildfire conditions relative to high, normal, and low fire years in the historical record. Our results clearly demonstrate the link between wildfire conditions and a small set of climatic variables, and our methodology is a framework for providing near-real-time assessments of current wildfire conditions in the West.

US Drought-Heat Wave Relationships in Past Versus Current Climates

NASA Astrophysics Data System (ADS)

Cheng, L.; Hoerling, M. P.; Eischeid, J.; Liu, Z.

2017-12-01

This study explores the relationship between droughts and heat waves over various regions of the contiguous United States that are distinguished by so-called energy-limited versus water-limited climatologies. We first examine the regional sensitivity of heat waves to soil moisture variability under 19th century climate conditions, and then compare to sensitivities under current climate that has been subjected to human-induced change. Our approach involves application of the conditional statistical framework of vine copula. Vine copula is known for its flexibility in reproducing various dependence structures exhibited by climate variables. Here we highlight its feature for evaluating the importance of conditional relationships between variables and processes that capture underlying physical factors involved in their interdependence during drought/heat waves. Of particular interest is identifying changes in coupling strength between heat waves and land surface conditions that may yield more extreme events as a result of land surface feedbacks. We diagnose two equilibrium experiments a coupled climate model (CESM1), one subjected to Year-1850 external forcing and the other to Year-2000 radiative forcing. We calculate joint heat wave/drought relationships for each climate state, and also calculate their change as a result of external radiative forcing changes across this 150-yr period. Our results reveal no material change in the dependency between heat waves and droughts, aside from small increases in coupling strength over the Great Plains. Overall, hot U.S. summer droughts of 1850-vintage do not become hotter in the current climate -- aside from the warming contribution of long-term climate change, in CESM1. The detectability of changes in hotter droughts as a consequence of anthropogenic forced changes in this single effect, i.e. coupling strength between soil moisture and hot summer temperature, is judged to be low at this time.

Regionally synchronous fires in interior British Columbia, Canada, driven by interannual climate variability and weakly associated with large-scale climate patterns between AD 1600-1900

NASA Astrophysics Data System (ADS)

Harvey, J. E.; Smith, D. J.

2016-12-01

We investigated the influence of climate variability on forest fire occurrence in west central British Columbia (BC), Canada, between AD 1600 and 1900. Fire history was reconstructed at 8 sites in the Cariboo-Chilcotin region and we identified 46 local (fires that affected 1 site) and 16 moderate (fires that affected 2 sites) fires. Preexisting fire history data collected from nearby sites was incorporated to identify 17 regionally synchronous fire years (fires that affected ³ 3 sites). Interannual and multidecadal relationships between fire occurrence and the Palmer Drought Severity Index (PDSI), El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and the Pacific North American (PNA) pattern were examined, in addition to the effects of phase interactions between ENSO and PDO. We examined multiple reconstructions of PDO and ENSO and utilized three methodological approaches to characterize climate-fire relationships. We found that the influence of interannual climate expressed as PDSI, increasingly synchronized the occurrence of of fires from local to regional fires. Regional fires were associated with anomalously dry, warm conditions in the year of the fire and in years preceding the fire. We also identified an association between local fires and antecedent moisture conditions, where wetter and cooler conditions persisted 2-3 years prior to fire. This finding suggests that moisture-driven fine fuel development and proximity to grasslands could function as key determinants of local (small-scale) fire history parameters. The relationships we identified between regional fires and ENSO, PDO and PNA suggest that large-scale patterns of climate variability exert a weak and/or inconsistent influence over fire activity in west central BC between AD 1600-1900. The strongest relationships between regional fires and large-scale climate patterns were identified when ENSO and PDO were both in positive phases. We also documented a relationship between regional fires and positive years of the PNA pattern. Our findings suggest that long-term fire planning using predictions of large scale climate patterns may be limited in west central BC, however, the consideration of additive phases of ENSO and PDO, and the PNA pattern, may be effective and has been suggested by others in the inland Pacific Northwest.

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)

Recruitment success of different fish stocks in the North Sea in relation to climate variability

NASA Astrophysics Data System (ADS)

Dippner, Joachim W.

1997-09-01

Long-term data of year class strengths of different commercially harvested fish stocks based on a virtual population analysis (VPA) are available from ICES. The anomalies of these long-term data sets of year class strength are analyzed using Empirical Orthogonal Functions (EOFs) and are related to climate variability: the anomalies of the sea surface temperature (SST) in the northern North Sea and the North Atlantic Oscillation (NAO) index. A Canonical Correlation Analysis (CCA) between the leading eigenmodes is performed. The results suggest that the variability in the fish recruitment of western mackerel and three gadoids, namely North Sea cod, North Sea saithe, and North Sea whiting is highly correlated to the variability of the North Sea SST which is directly influenced by the NAO. For North Sea haddock and herring no meaningful correlation exists to North Sea SST and NAO. The results allow the conclusion that is seems possible to predict long-term changes in the fish recruitment from climate change scenarios for North Sea cod, North Sea saithe and western mackerel. Furthermore, the results indicate the possibility of recruitment failure for North Sea cod, North Sea whiting, and western mackerel in the case of global warming.

Intraseasonal and Interannual Variability of Mars Present Climate

NASA Astrophysics Data System (ADS)

Hollingsworth, Jeffery L.; Bridger, Alison F. C.; Haberle, Robert M.

1996-01-01

This is a Final Report for a Joint Research Interchange (JRI) between NASA Ames Research Center and San Jose State University, Department of Meteorology. The focus of this JRI has been to investigate the nature of intraseasonal and interannual variability of Mars'present climate. We have applied a three-dimensional climate model based on the full hydrostatic primitive equations to determine the spatial, but primarily, the temporal structures of the planet's large-scale circulation as it evolves during a given seasonal advance, and, over multi-annual cycles. The particular climate model applies simplified physical parameterizations and is computationally efficient. It could thus easily be integrated in a perpetual season or advancing season configuration, as well as over many Mars years. We have assessed both high and low-frequency components of the circulation (i.e., motions having periods of Omicron(2-10 days) or greater than Omicron(10 days), respectively). Results from this investigation have explored the basic issue whether Mars' climate system is naturally 'chaotic' associated with nonlinear interactions of the large-scale circulation-regardless of any allowance for year-to-year variations in external forcing mechanisms. Titles of papers presented at scientific conferences and a manuscript to be submitted to the scientific literature are provided. An overview of a areas for further investigation is also presented.

Modelling climate change and malaria transmission.

PubMed

Parham, Paul E; Michael, Edwin

2010-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Long-term variability and environmental control of the carbon cycle in an oak-dominated temperate forest

Treesearch

Jing Xie; Jiquan Chen; Ge Sun; Housen Chu; Asko Noormets; Zutao Ouyang; Ranjeet John; Shiqiang Wan; Wenbin Guan

2014-01-01

Our understanding of the long-term carbon (C) cycle of temperate deciduous forests and its sensitivity to climate variability is limited due to the large temporal dynamics of C fluxes. The goal of the study was to quantify the effects of environmental variables on the C balance in a 70-year-old mixed-oak woodland forest over a 7-year period in northwest Ohio, USA. The...

Evaluating the ClimEx Single Model Large Ensemble in Comparison with EURO-CORDEX Results of Seasonal Means and Extreme Precipitation Indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Brisette, F.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several extreme indicators like R95pTOT, RX5day and others are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

The Great Plains low-level jet in 1.5C and 2C HAPPI simulations: Implications for changes in extreme climate events

NASA Astrophysics Data System (ADS)

Weaver, S. J.; Barcikowska, M. J.

2017-12-01

Global temperature targets have become the cornerstone for global climate policy discussions. Given the goal of the Paris Accord to limit the rise in global mean temperature to well below 2.0oC above pre-industrial levels, and pursue efforts toward the more ambitious 1.5oC goal, there is increasing focus in the climate science community on what the relative changes in regional climate extremes may be for these two scenarios. Despite the successes of major climate science modeling efforts, there is still a significant information gap regarding the regional and seasonal changes in some climate extremes over the U.S. as a function of these global mean temperature targets.During the spring and summer, large amounts of heat and moisture are transported northward into the central and eastern U.S. by the Great Plains Low-Level Jet (GPLLJ) - an atmospheric river which dominates the subcontinental scale climate variability during the warm half of the year. Accordingly, the GPLLJ and its vast spatiotemporal variability is highly influential over several types of extreme climate anomalies east of the Rocky Mountains, including, drought and pluvial events, tornadic activity, and the evolution of central U.S warming hole. Changes in the GPLLJ and its variability are probed from the perspective of several hundred climate realizations afforded by the availability of climate model experiments from the Half a degree additional warming, Prognosis, and Projected Impacts (HAPPI) effort - a suite of multi-model ensemble AMIP simulations forced by 1.5oC and 2oC levels of global warming. The multimodel analysis focuses on the variable magnitude of the seasonal changes in the mean GPLLJ and shifts in the extremes of the prominent modes of GPLLJ variability - both of which have implications for the future shifts in extreme climate events over the Great Plains, Midwest, and southeast regions of the U.S.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

PubMed

Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B

2017-06-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics

USGS Publications Warehouse

Itter, Malcolm S.; Finley, Andrew O.; D'Amato, Anthony W.; Foster, Jane R.; Bradford, John B.

2017-01-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics—changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands.

Climate variability during the Medieval Climate Anomaly and Little Ice Age based on ostracod faunas and shell geochemistry from Biscayne Bay, Florida: Chapter 14

USGS Publications Warehouse

Cronin, Thomas M.; Wingard, G. Lynn; Dwyer, Gary S.; Swart, Peter K.; Willard, Debra A.; Albietz, Jessica

2012-01-01

An 800-year-long environmental history of Biscayne Bay, Florida, is reconstructed from ostracod faunal and shell geochemical (oxygen, carbon isotopes, Mg/Ca ratios) studies of sediment cores from three mudbanks in the central and southern parts of the bay. Using calibrations derived from analyses of modern Biscayne and Florida Bay ostracods, palaeosalinity oscillations associated with changes in precipitation were identified. These oscillations reflect multidecadal- and centennial-scale climate variability associated with the Atlantic Multidecadal Oscillation during the late Medieval Climate Anomaly (MCA) and the Little Ice Age (LIA). Evidence suggests wetter regional climate during the MCA and drier conditions during the LIA. In addition, twentieth century anthropogenic modifications to Everglades hydrology influenced bay circulation and/or processes controlling carbon isotopic composition.

Future of endemic flora of biodiversity hotspots in India.

PubMed

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.

Future of Endemic Flora of Biodiversity Hotspots in India

PubMed Central

Chitale, Vishwas Sudhir; Behera, Mukund Dev; Roy, Partha Sarthi

2014-01-01

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models. PMID:25501852

A 12-year (1987-1998) Ensemble Simulation of the US Climate with a Variable Resolution Stretched Grid GCM

NASA Technical Reports Server (NTRS)

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

2002-01-01

The variable-resolution stretched-grid (SG) GEOS (Goddard Earth Observing System) GCM has been used for limited ensemble integrations with a relatively coarse, 60 to 100 km, regional resolution over the U.S. The experiments have been run for the 12-year period, 1987-1998, that includes the recent ENSO cycles. Initial conditions 1-2 days apart are used for ensemble members. The goal of the experiments is analyzing the long-term SG-GCM ensemble integrations in terms of their potential in reducing the uncertainties of regional climate simulation while producing realistic mesoscales. The ensemble integration results are analyzed for both prognostic and diagnostic fields. A special attention is devoted to analyzing the variability of precipitation over the U.S. The internal variability of the SG-GCM has been assessed. The ensemble means appear to be closer to the verifying analyses than the individual ensemble members. The ensemble means capture realistic mesoscale patterns, especially those of induced by orography. Two ENSO cycles have been analyzed in terms their impact on the U.S. climate, especially on precipitation. The ability of the SG-GCM simulations to produce regional climate anomalies has been confirmed. However, the optimal size of the ensembles depending on fine regional resolution used, is still to be determined. The SG-GCM ensemble simulations are performed as a preparation or a preliminary stage for the international SGMIP (Stretched-Grid Model Intercomparison Project) that is under way with participation of the major centers and groups employing the SG-approach for regional climate modeling.

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

NASA Astrophysics Data System (ADS)

Dhakal, S.; Ojha, S.

2017-12-01

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

An analysis of the decadal variability of Carbon fluxes in three evergreen European forests through modelling

NASA Astrophysics Data System (ADS)

Delpierre, N.; Dufrêne, E.

2009-04-01

With several sites measuring mass and energy turbulent fluxes for more than ten years, the CarboEurope database appears as a valuable resource for addressing the question of the determinism of the interannual variability of carbon (C) and water balances in forests ecosystems. Apart from major climate-driven anomalies during the anomalous 2003 summer and 2007 spring, little is known about the factors driving interannual variability (IAV) of the C balance in forest ecosystems. We used the CASTANEA process-based model to simulate the C and W fluxes and balances of three European evergreen forests for the 2000-2007 period (FRPue Quercus ilex, 44°N; DETha Picea abies, 51°N; FIHyy Pinus sylvestris, 62°N). The model fairly reproduced the day-to-day variability of measured fluxes, accounting for 70-81%, 77-91% and 59-90% of the daily variance of measured NEP, GPP and TER, respectively. However, the model was challenged in representing the IAV of fluxes integrated on an annual time scale. It reproduced ca. 80% of the interannual variance of measured GPP, but no significant relationship could be established between annual measured and modelled NEP or TER. Accordingly, CASTANEA appeared as a suitable tool for disentangling the influence of climate and biological processes on GPP at mutiple time scales. We show that climate and biological processes relative influences on the modelled GPP vary from year to year in European evergreen forests. Water-stress related and phenological processes (i.e. release of the winter thermal constraint on photosynthesis in evergreens) appear as primary drivers for the particular 2003 and 2007 years, respectively, but the relative influence of other climatic factors widely varies for less remarkable years at all sites. We discuss shortcomings of the method, as related to the influence of compensating errors in the simulated fluxes, and assess the causes of the model poor ability to represent the IAV of the annual sums of NEP and TER.

Climatic Variables and Malaria Morbidity in Mutale Local Municipality, South Africa: A 19-Year Data Analysis

PubMed Central

Botai, Joel O.; Rautenbach, Hannes; Ncongwane, Katlego P.; Botai, Christina M.

2017-01-01

The north-eastern parts of South Africa, comprising the Limpopo Province, have recorded a sudden rise in the rate of malaria morbidity and mortality in the 2017 malaria season. The epidemiological profiles of malaria, as well as other vector-borne diseases, are strongly associated with climate and environmental conditions. A retrospective understanding of the relationship between climate and the occurrence of malaria may provide insight into the dynamics of the disease’s transmission and its persistence in the north-eastern region. In this paper, the association between climatic variables and the occurrence of malaria was studied in the Mutale local municipality in South Africa over a period of 19-year. Time series analysis was conducted on monthly climatic variables and monthly malaria cases in the Mutale municipality for the period of 1998–2017. Spearman correlation analysis was performed and the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was developed. Microsoft Excel was used for data cleaning, and statistical software R was used to analyse the data and develop the model. Results show that both climatic variables’ and malaria cases’ time series exhibited seasonal patterns, showing a number of peaks and fluctuations. Spearman correlation analysis indicated that monthly total rainfall, mean minimum temperature, mean maximum temperature, mean average temperature, and mean relative humidity were significantly and positively correlated with monthly malaria cases in the study area. Regression analysis showed that monthly total rainfall and monthly mean minimum temperature (R2 = 0.65), at a two-month lagged effect, are the most significant climatic predictors of malaria transmission in Mutale local municipality. A SARIMA (2,1,2) (1,1,1) model fitted with only malaria cases has a prediction performance of about 51%, and the SARIMAX (2,1,2) (1,1,1) model with climatic variables as exogenous factors has a prediction performance of about 72% in malaria cases. The model gives a close comparison between the predicted and observed number of malaria cases, hence indicating that the model provides an acceptable fit to predict the number of malaria cases in the municipality. To sum up, the association between the climatic variables and malaria cases provides clues to better understand the dynamics of malaria transmission. The lagged effect detected in this study can help in adequate planning for malaria intervention. PMID:29117114

Impact of Climate Change on Food Security in Kenya

NASA Astrophysics Data System (ADS)

Yator, J. J.

2016-12-01

This study sought to address the existing gap on the impact of climate change on food security in support of policy measures to avert famine catastrophes. Fixed and random effects regressions for crop food security were estimated. The study simulated the expected impact of future climate change on food insecurity based on the Representative Concentration Pathways scenario (RCPs). The study makes use of county-level yields estimates (beans, maize, millet and sorghum) and daily climate data (1971 to 2010). Climate variability affects food security irrespective of how food security is defined. Rainfall during October-November-December (OND), as well as during March-April-May (MAM) exhibit an inverted U-shaped relationship with most food crops; the effects are most pronounced for maize and sorghum. Beans and Millet are found to be largely unresponsive to climate variability and also to time-invariant factors. OND rains and fall and summer temperature exhibit a U-shaped relationship with yields for most crops, while MAM rains temperature exhibits an inverted U-shaped relationship. However, winter temperatures exhibit a hill-shaped relationship with most crops. Project future climate change scenarios on crop productivity show that climate change will adversely affect food security, with up to 69% decline in yields by the year 2100. Climate variables have a non-linear relationship with food insecurity. Temperature exhibits an inverted U-shaped relationship with food insecurity, suggesting that increased temperatures will increase crop food insecurity. However, maize and millet, benefit from increased summer and winter temperatures. The simulated effects of different climate change scenarios on food insecurity suggest that adverse climate change will increase food insecurity in Kenya. The largest increases in food insecurity are predicted for the RCP 8.5Wm2, compared to RCP 4.5Wm2. Climate change is likely to have the greatest effects on maize insecurity, which is likely to increase by between 8.56% and 21% by the year 2100. There exists a need for policies that safeguard agriculture against the adverse effects of climate change to alleviate food insecurity in Kenya. Therefore, it is important that climate change mitigation is given much more priority in policy planning and also implementation.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

Horton, Radley M.

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

Impact of climate variability and anthropogenic activity on streamflow in the Three Rivers Headwater Region, Tibetan Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, Chong; Li, Daiqing; Gao, Yanni; Liu, Wenfeng; Zhang, Linbo

2017-07-01

Under the impacts of climate variability and human activities, there is violent fluctuation for streamflow in the large basins in China. Therefore, it is crucial to separate the impacts of climate variability and human activities on streamflow fluctuation for better water resources planning and management. In this study, the Three Rivers Headwater Region (TRHR) was chosen as the study area. Long-term hydrological data for the TRHR were collected in order to investigate the changes in annual runoff during the period of 1956-2012. The nonparametric Mann-Kendall test, moving t test, Pettitt test, Mann-Kendall-Sneyers test, and the cumulative anomaly curve were used to identify trends and change points in the hydro-meteorological variables. Change point in runoff was identified in the three basins, which respectively occurred around the years 1989 and 1993, dividing the long-term runoff series into a natural period and a human-induced period. Then, the hydrologic sensitivity analysis method was employed to evaluate the effects of climate variability and human activities on mean annual runoff for the human-induced period based on precipitation and potential evapotranspiration. In the human-induced period, climate variability was the main factor that increased (reduced) runoff in LRB and YARB (YRB) with contribution of more than 90 %, while the increasing (decreasing) percentage due to human activities only accounted for less than 10 %, showing that runoff in the TRHR is more sensitive to climate variability than human activities. The intra-annual distribution of runoff shifted gradually from a double peak pattern to a single peak pattern, which was mainly influenced by atmospheric circulation in the summer and autumn. The inter-annual variation in runoff was jointly controlled by the East Asian monsoon, the westerly, and Tibetan Plateau monsoons.

The cumulative effects of forest disturbance and climate variability on baseflow in a large forested watershed

NASA Astrophysics Data System (ADS)

Li, Q.; Wei, A.; Giles-Hansen, K.; Zhang, M.; Liu, W.

2016-12-01

Assessing how forest disturbance and climate change affect baseflow or groundwater discharge is critical for understanding water resource supply and protecting aquatic functions. Previous studies have mainly evaluated the effects of forest disturbance on streamflow, with rare attention on baseflow, particularly in large watersheds. However, studying this topic is challenging as it requires explicit inclusion of climate into assessment due to their interactions at any large watersheds. In this study, we used Upper Similkameen River watershed (USR) (1810 km2), located in the southern interior of British Columbia, Canada to examine how forest disturbance and climate variability affect baseflow. The conductivity mass balance method was first used for baseflow separation, and the modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to annual baseflow. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were about 85.2 ± 21.5 mm year-1 and 0.22 ± 0.05 for the study period of 1954-2013, respectively. The forest disturbance increased the annual baseflow of 18.4 mm, while climate variability decreased 19.4 mm. In addition, forest disturbance also shifted the baseflow regime with increasing of the spring baseflow and decreasing of the summer baseflow. We conclude that forest disturbance significantly altered the baseflow magnitudes and patterns, and its role in annual baseflow was equal to that caused by climate variability in the study watershed despite their opposite changing directions. The implications of our results are discussed in the context of future forest disturbance (or land cover changes) and climate changes.

Why and How the Dairy Farmers of India are Vulnerable to the Impacts of Climate Variability and Change?

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.

2017-12-01

Climate change and variability has added many atrociousness to India's food security challenges and the relationship between the asset components of farmers and climate change is always complex. In India, dairy farming substantially contributes towards the food security and always plays a supportive role to agriculture from the adversities. This study provides an overview of the socio economic and livelihood vulnerability of small holder dairy farmers of India to climate change and variability in three dimensions — sensitivity, exposure and adaptive capacity by combining 70 indicators and 12 major components. The livelihood and socio economic vulnerability of dairy farmers to climate change and variability is assessed at taluka level in India through detailed house hold level data of livelihoods of Western Ghats region of India collected by several levels of survey and through Participatory Rural Appraisal (PRA) techniques from selected farmers complemented by thirty years of gridded weather data and other secondary data sources. The index score of dairy based livelihoods of Maharashtra was highly negative compared to other states with about 50 percent of farmers having high level of vulnerability with significant tradeoff between milk productivity and health, food, natural disasters-climate variability components. It finds that ensuring food security in the scenario of climate change will be a dreadful challenge and recommends identification of different potential options depending on local contexts at grass root level, the adoption of sustainable agricultural practices, focusing on improving the adaptive capacity component, provision of livelihood security, preparing the extensionists of Krishi Vigyan Kendras (KVKs)- universities to deal with the risks through extensive training programmes, long-term relief measures in the event of natural disasters, workshops on climate science and communication and promoting farmer centric extension system.

Seeing the climate through the trees: observing climate and forestry impacts on streamflow using a 60-year record

Treesearch

T. P. Burt; N. J. K. Howden; J. J. McDonnell; J. A. Jones; G. R. Hancock

2014-01-01

Paired watershed experiments involving the removal or manipulation of forest cover in one of the watersheds have been conducted for more than a century to quantify the impact of forestry operations on streamflow. Because climate variability is expected to be large, forestry treatment effects would be undetectable without the treatment–control comparison. New...

Population viability of Pediocactus brady (Cactaceae) in a changing climate

USGS Publications Warehouse

Shryock, Daniel F.; Esque, Todd C.; Huges, Lee

2014-01-01

• Conclusions: Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events.

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

PubMed

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

2013-01-01

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

A reconstruction of global hydroclimate and dynamical variables over the Common Era.

PubMed

Steiger, Nathan J; Smerdon, Jason E; Cook, Edward R; Cook, Benjamin I

2018-05-22

Hydroclimate extremes critically affect human and natural systems, but there remain many unanswered questions about their causes and how to interpret their dynamics in the past and in climate change projections. These uncertainties are due, in part, to the lack of long-term, spatially resolved hydroclimate reconstructions and information on the underlying physical drivers for many regions. Here we present the first global reconstructions of hydroclimate and associated climate dynamical variables over the past two thousand years. We use a data assimilation approach tailored to reconstruct hydroclimate that optimally combines 2,978 paleoclimate proxy-data time series with the physical constraints of an atmosphere-ocean climate model. The global reconstructions are annually or seasonally resolved and include two spatiotemporal drought indices, near-surface air temperature, an index of North Atlantic variability, the location of the intertropical convergence zone, and monthly Niño indices. This database, called the Paleo Hydrodynamics Data Assimilation product (PHYDA), will provide a critical new platform for investigating the causes of past climate variability and extremes, while informing interpretations of future hydroclimate projections.

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

PubMed

Quintero, Ignacio; Wiens, John J

2013-08-01

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

Solar Forced Dansgaard/Oeschger Events?

NASA Technical Reports Server (NTRS)

Muscheler, R.; Beer, J.

2006-01-01

Climate records for the last ice age (which ended 11,500 years ago) show enormous climate fluctuations in the North Atlantic region - the so-called Dansgaard/Oeschger events. During these events air temperatures in Greenland changed on the order of 10 degrees Celsius within a few decades. These changes were attributed to shifts in ocean circulation which influences the warm water supply from lower latitudes to the North Atlantic region. Interestingly, the rapid warmings tend to recur approximately every 1500 years or multiples thereof. This has led researchers to speculate about an external cause for these changes with the variable Sun being one possible candidate. Support for this hypothesis came from climate reconstructions, which suggested that the Sun influenced the climate in the North Atlantic region on these time scales during the last approximately 12,000 years of relatively stable Holocene climate. However, Be-10 measurements in ice cores do not indicate that the Sun caused or triggered the Dansgaard/Oeschger events. Depending on the solar magnetic shielding more or less Be-10 is produced in the Earth's atmosphere. Therefore, 10Be can be used as a proxy for solar activity changes. Since Be-10 can be measured in ice cores, it is possible to compare the variable solar forcing directly with the climate record from the same ice core. This removes any uncertainties in the relative dating, and the solar-climate link can be reliably studied. Notwithstanding that some Dansgaard/Oeschger warmings could be related to increased solar activity, there is no indication that this is the case for all of the Dansgaard/Oeschger events. Therefore, during the last ice age the Be-10 and ice core climate data do not indicate a persistent solar influence on North Atlantic climate.

Climate Change Impacts on Migration in the Vulnerable Countries

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Effects of changing climate on European stream invertebrate communities: A long-term data analysis.

PubMed

Jourdan, Jonas; O'Hara, Robert B; Bottarin, Roberta; Huttunen, Kaisa-Leena; Kuemmerlen, Mathias; Monteith, Don; Muotka, Timo; Ozoliņš, Dāvis; Paavola, Riku; Pilotto, Francesca; Springe, Gunta; Skuja, Agnija; Sundermann, Andrea; Tonkin, Jonathan D; Haase, Peter

2018-04-15

Long-term observations on riverine benthic invertebrate communities enable assessments of the potential impacts of global change on stream ecosystems. Besides increasing average temperatures, many studies predict greater temperature extremes and intense precipitation events as a consequence of climate change. In this study we examined long-term observation data (10-32years) of 26 streams and rivers from four ecoregions in the European Long-Term Ecological Research (LTER) network, to investigate invertebrate community responses to changing climatic conditions. We used functional trait and multi-taxonomic analyses and combined examinations of general long-term changes in communities with detailed analyses of the impact of different climatic drivers (i.e., various temperature and precipitation variables) by focusing on the response of communities to climatic conditions of the previous year. Taxa and ecoregions differed substantially in their response to climate change conditions. We did not observe any trend of changes in total taxonomic richness or overall abundance over time or with increasing temperatures, which reflects a compensatory turnover in the composition of communities; sensitive Plecoptera decreased in response to warmer years and Ephemeroptera increased in northern regions. Invasive species increased with an increasing number of extreme days which also caused an apparent upstream community movement. The observed changes in functional feeding group diversity indicate that climate change may be associated with changes in trophic interactions within aquatic food webs. These findings highlight the vulnerability of riverine ecosystems to climate change and emphasize the need to further explore the interactive effects of climate change variables with other local stressors to develop appropriate conservation measures. Copyright © 2017 Elsevier B.V. All rights reserved.

Farmers' perception and adaptation practice to climate variability and change: a case study of the Vea catchment in Ghana.

PubMed

Limantol, Andrew Manoba; Keith, Bruce Edward; Azabre, Bismark Atiayure; Lennartz, Bernd

2016-01-01

Rain-fed agriculture remains the source of employment for a majority of Ghana's population, particularly in northern Ghana where annual rainfall is low. The purpose of this study is to examine farmers' perceptions and adaptation practices to climate change and variability in accordance with actual recorded weather data of the Vea catchment in Upper East Region of northern Ghana during the time interval from 1972 to 2012. Climatic data over 41-years (1972-2012) from four stations in vicinity of the catchment was evaluated to identify actual weather outcomes. A survey questionnaire targeting farmers with at least 30-years of farming experience in the area was administered in six of the eleven agricultural enumeration areas in the catchment covering 305 km(2). Of the 466 farmers interviewed, 79 % utilized rain-fed practices while 21 % utilized some form of irrigation. Results indicate that nearly 90 % of the farmers interviewed believe that temperature increased over the past 30-years, while over 94 % of the farmers believe that amount of rainfall, duration, intensity and rainy days has decreased. Nearly 96 % of the farmers believe that their farms are extremely vulnerable to decreased rainfall, droughts and changed timing of rainfall events. Climatic data of the catchment indicates a rising trend in temperature but no long-term changes in annual and monthly rainfall, thereby possibly increasing levels of evapotranspiration. While no statistical differences were found between rain-fed and irrigation agricultural types regarding receipt of external support, their approaches to climatic change adaptation do differ. Patently, 94 and 90 % of farmers relying on rain-fed and irrigation strategies respectively receive some form of support, primarily via extension services. Farmers using rain-fed practices adjust to climate variability by varying crop types via rotation without fertilizer while farmers employing irrigation practices are more likely to offset climate variability with a greater use of fertilizer application. The Vea catchment faces rising temperature and evapotranspiration trends. Farmers are aware of these climatic changes and are adapting strategies to cope with the effects but require support. Adequate extension services and irrigation facilities are needed to assist farmers in order to sustain their livelihoods on the long run.

High resolution climate scenarios for snowmelt modelling in small alpine catchments

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources

NASA Astrophysics Data System (ADS)

Feng, Dapeng; Zheng, Yi; Mao, Yixin; Zhang, Aijing; Wu, Bin; Li, Jinguo; Tian, Yong; Wu, Xin

2018-02-01

Water resources in coastal areas can be profoundly influenced by both climate change and human activities. These climatic and human impacts are usually intertwined and difficult to isolate. This study developed an integrated model-based approach for detection and attribution of climatic and human impacts and applied this approach to the Luanhe Plain, a typical coastal area in northern China. An integrated surface water-groundwater model was developed for the study area using GSFLOW (coupled groundwater and surface-water flow). Model calibration and validation were performed for background years between 1975 and 2000. The variation in water resources between the 1980s and 1990s was then quantitatively attributed to climate variability, groundwater pumping and changes in upstream inflow. Climate scenarios for future years (2075-2100) were also developed by downscaling the projections in CMIP5. Potential water resource responses to climate change, as well as their uncertainty, were then investigated through integrated modeling. The study results demonstrated the feasibility and value of the integrated modeling-based analysis for water resource management in areas with complex surface water-groundwater interaction. Specific findings for the Luanhe Plain included the following: (1) During the historical period, upstream inflow had the most significant impact on river outflow to the sea, followed by climate variability, whereas groundwater pumping was the least influential. (2) The increase in groundwater pumping had a dominant influence on the decline in groundwater change, followed by climate variability. (3) Synergetic and counteractive effects among different impacting factors, while identified, were not significant, which implied that the interaction among different factors was not very strong in this case. (4) It is highly probable that future climate change will accelerate groundwater depletion in the study area, implying that strict regulations for groundwater pumping are imperative for adaptation.

Physically-based distributed mass balance modeling of a tropical glacier: An application to backward modeling of past climate

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Winkler, M.; Kaser, G.

2009-04-01

The use of spatially distributed (2-D) mass balance models has increased in recent years, but mostly focuses on extratropical glacier surfaces. Here we present the first application of a process-based 2-D model to an African glacier: Kersten Glacier on Kilimanjaro. Multi-year data from an automatic weather station (AWS) at 5873 m a.s.l. (500 hPa) serve to force the model. Validation variables comprise surface temperature, surface height change, snow depth, and incoming radiation - all of which indicate a good model performance. Analyses of the interannual variability in the most significant total mass budget terms (surface accumulation, melt, and sublimation), as well as in the related energy fluxes, exhibit a strong link to atmospheric moisture of a particular year. This is because net shortwave radiation (a result of both cloudiness and surface albedo) is the most variable energy flux on monthly to annual time scales. Internal accumulation (refreezing of melt water), however, shows a time lag and is strongest after a very wet year. Due to the limited validation data at lower elevations, we also perform a detailed sensitivity study by varying 17 model parameters - which yields a total mass loss estimate of 522 +/- 105 kg/m2/year under present climate conditions. Moreover, the verified model allows us to perform backward modeling of the last maximum extent of Kersten Glacier in the 1880s, which is indicated by a well preserved terminal moraine. This step reveals decreases in precipitation (30-45%), water vapor pressure (0.1-0.3 hPa) and cloud cover (2-4 percentage units) as the most likely local climate change between late 19th century and present. Thus, the study also demonstrates how 2-D modeling can help reconstruct past climate for a remote place prior to the availability of measurements. In our case these findings have great relevance for the debate of surface versus mid-tropospheric climate change in the tropics.

Accounting for multiple climate components when estimating climate change exposure and velocity

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

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

High resolution geochemical proxy record of the last 600yr in a speleothem from the northwest Iberian Peninsula

NASA Astrophysics Data System (ADS)

Iglesias González, Miguel; Pisonero, Jorge; Cheng, Hai; Edwards, R. Lawrence; Stoll, Heather

2017-04-01

In meteorology and climatology, the instrumental period is the period where we have measured directly by instrumentation, different meteorological data along the surface which allow us to determinate the evolution of the climate during the last 150 years over the world. At the beginning, the density of this data were very low, so we have to wait until the last 75-100 years to have a good network in most of the parts of the surface. This time period is very small if we want to analyze the relationship between geochemical and instrumental variability in any speleothem. So a very high resolution data is needed to determinate the connection between both of them in the instrumental period, to try to determinate de evolution of climate in the last 600 years. Here we present a high resolution speleothem record from a cave located in the middle of the Cantabrian Mountains without any anthropologic influence and with no CO2 seasonal variability. This 600yr stalagmite, dated with U/Th method with a growth rate from 100 to 200 micrometers/yr calculated with Bchron model, provide us accurate information of the climate conditions near the cave. Trace elements are analyzed at 8 micrometers intervals by Laser Ablation ICP-MS which resolves even monthly resolution during the last 600 years with special attention with Sr, Mg, Al and Si. This data, without seasonal variability and with the presence of a river inside the cave, give us very valuable information about the extreme flood events inside the cave during the whole period, which is related with the precipitations and the snow fusion events outside the cave. We identify more extremely flood events during the Little Ice Age than in the last 100yr. As well, we have trace elements data with spatial resolution of 0.2mm analyzed with ICP-AES which allow us to compare the geochemical variability with both technics. We also analyze stable isotope d13C and d18O with a spatial resolution of 0.2mm, so we are able to identify variations and all possible correlations between them, trace elements and instrumental records from the different weather stations located near the cave. We use instrumental data, and the statistical correlation between our proxy and them, to calibrate and analyze the variability along the 600yr which provide us a lot of information about the climate variability. In spite of the significate global warming during the last 25 years, we have less variability during this period than along the transition between the Medieval Warm Period and the Little Ice Age. We also analyze this variability along the 600 years with wavelet analysis, with special attention in the instrumental period. With this mathematical method, we can identify several cycles both in trace elements and stable isotopes at special scales compatible with the decadal and multidecadal variability with a value similar to very important climate index like AMO.

Quantifying climatic variability in monsoonal northern China over the last 2200 years and its role in driving Chinese dynastic changes

NASA Astrophysics Data System (ADS)

Li, Jianyong; Dodson, John; Yan, Hong; Zhang, David D.; Zhang, Xiaojian; Xu, Qinghai; Lee, Harry F.; Pei, Qing; Cheng, Bo; Li, Chunhai; Ni, Jian; Sun, Aizhi; Lu, Fengyan; Zong, Yongqiang

2017-03-01

Our understanding on the spatial-temporal patterns of climatic variability over the last few millennia in the East Asian monsoon-dominated northern China (NC), and its role at a macro-scale in affecting the prosperity and depression of Chinese dynasties is limited. Quantitative high-resolution, regionally-synthesized palaeoclimatic reconstructions as well as simulations, and numerical analyses of their relationships with various fine-scale, numerical agro-ecological, social-economic, and geo-political historical records during the period of China's history, are presented here for NC. We utilize pollen data together with climate modeling to reconstruct and simulate decadal- to centennial-scale variations in precipitation or temperature for NC during the last 2200 years (-200-2000 AD). We find an overall cyclic-pattern (wet/warm or dry/cold) in the precipitation and temperature anomalies on centennial- to millennial-scale that can be likely considered as a representative for the entire NC by comparison with other related climatic records. We suggest that solar activity may play a key role in driving the climatic fluctuations in NC during the last 22 centuries, with its quasi ∼100, 50, 23, or 22-year periodicity clearly identified in our climatic reconstructions. We employ variation partitioning and redundancy analysis to quantify the independent effects of climatic factors on accounting for the total variation of 17 fine-grained numerical Chinese historical records. We quantitatively illustrate that precipitation (67.4%) may have been more important than temperature (32.5%) in causing the overall agro-ecological and macro-geopolitical shifts in imperial China with NC as the central ruling region and an agricultural heartland over the last 2200 years.

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

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.

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.

The GISS global climate-middle atmosphere model. II - Model variability due to interactions between planetary waves, the mean circulation and gravity wave drag

NASA Technical Reports Server (NTRS)

Rind, D.; Suozzo, R.; Balachandran, N. K.

1988-01-01

The variability which arises in the GISS Global Climate-Middle Atmosphere Model on two time scales is reviewed: interannual standard deviations, derived from the five-year control run, and intraseasonal variability as exemplified by statospheric warnings. The model's extratropical variability for both mean fields and eddy statistics appears reasonable when compared with observations, while the tropical wind variability near the stratopause may be excessive possibly, due to inertial oscillations. Both wave 1 and wave 2 warmings develop, with connections to tropospheric forcing. Variability on both time scales results from a complex set of interactions among planetary waves, the mean circulation, and gravity wave drag. Specific examples of these interactions are presented, which imply that variability in gravity wave forcing and drag may be an important component of the variability of the middle atmosphere.

Past crops yield dynamics reconstruction from tree-ring chronologies in the forest-steppe zone based on low- and high-frequency components

NASA Astrophysics Data System (ADS)

Babushkina, Elena A.; Belokopytova, Liliana V.; Shah, Santosh K.; Zhirnova, Dina F.

2018-05-01

Interrelations of the yield variability of the main crops (wheat, barley, and oats) with hydrothermal regime and growth of conifer trees ( Pinus sylvestris and Larix sibirica) in forest-steppes were investigated in Khakassia, South Siberia. An attempt has been made to understand the role and mechanisms of climatic impact on plants productivity. It was found that amongst variables describing moisture supply, wetness index had maximum impact. Strength of climatic response and correlations with tree growth are different for rain-fed and irrigated crops yield. Separated high-frequency variability components of yield and tree-ring width have more pronounced relationships between each other and with climatic variables than their chronologies per se. Corresponding low-frequency variability components are strongly correlated with maxima observed after 1- to 5-year time shift of tree-ring width. Results of analysis allowed us to develop original approach of crops yield dynamics reconstruction on the base of high-frequency variability component of the growth of pine and low-frequency one of larch.

Accessing the Gulf of Maine’s Climate Change Data Through Webtools

EPA Science Inventory

Climate variables have been measured in the Gulf of Maine and its watersheds for over one hundred years and long-standing time series are available at many different institutes. However, today’s managers looking for a quick answer to scientific questions rarely have the tim...

A 2700-year record of ENSO and PDO variability from the Californian margin based on coccolithophore assemblages and calcification

NASA Astrophysics Data System (ADS)

Beaufort, Luc; Grelaud, Michaël

2017-12-01

The El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) account for a large part of modern climate variability. Over the last decades, understanding of these modes of climate variability has increased but prediction in the context of global warming has proven difficult because of the lack of pertinent and reproducible paleodata. Here, we infer the dynamics of these oscillations from fossil assemblage and calcification state of coccolithophore in the Californian margin because El Niño has a strong impact on phytoplankton ecology and PDO on the upwelling intensity and hence on the ocean chemistry. Intense Californian upwelling brings water rich in CO2 and poor in carbonate ions and coccolithophores secrete lower calcified coccoliths. Seasonally laminated sediments of the Santa Barbara Basin are used to document ENSO variability and PDO index for the last 2700 years at a temporal resolution of 3 years. The records present the same characteristics as other PDO or ENSO records from the same area spanning the last centuries. We are therefore confident on the value produced here for the last 2.7 millennia. The records show important centennial variability that is equivalent to solar cycles.

Coral based-ENSO/IOD related climate variability in Indonesia: a review

NASA Astrophysics Data System (ADS)

Yudawati Cahyarini, Sri; Henrizan, Marfasran

2018-02-01

Indonesia is located in the prominent site to study climate variability as it lies between Pacific and Indian Ocean. It has consequences to the regional climate in Indonesia that its climate variability is influenced by the climate events in the Pacific oceans (e.g. ENSO) and in the Indian ocean (e.g. IOD), and monsoon as well as Indonesian Throughflow (ITF). Northwestern monsoon causes rainfall in the region of Indonesia, while reversely Southwestern monsoon causes dry season around Indonesia. The ENSO warm phase called El Nino causes several droughts in Indonesian region, reversely the La Nina causes flooding in some regions in Indonesia. However, the impact of ENSO in Indonesia is different from one place to the others. Having better understanding on the climate phenomenon and its impact to the region requires long time series climate data. Paleoclimate study which provides climate data back into hundreds to thousands even to million years overcome this requirement. Coral Sr/Ca can provide information on past sea surface temperature (SST) and paired Sr/Ca and δ18O may be used to reconstruct variations in the precipitation balance (salinity) at monthly to annual interannual resolution. Several climate studies based on coral geochemical records in Indonesia show that coral Sr/Ca and δ18O from Indonesian records SST and salinity respectively. Coral Sr/Ca from inshore Seribu islands complex shows more air temperature rather than SST. Modern coral from Timor shows the impact of ENSO and IOD to the saliniy and SST is different at Timor sea. This result should be taken into account when interpreting Paleoclimate records over Indonesia. Timor coral also shows more pronounced low frequency SST variability compared to the SST reanalysis (model). The longer data of low frequency variability will improve the understanding of warming trend in this climatically important region.

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

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

Hu, Aixue; Meehl, Gerald; Stammer, Detlef

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

Role of Perturbing Ocean Initial Condition in Simulated Regional Sea Level Change

DOE PAGES

Hu, Aixue; Meehl, Gerald; Stammer, Detlef; ...

2017-06-05

Multiple lines of observational evidence indicate that the global climate has been getting warmer since the early 20th century. This warmer climate has led to a global mean sea level rise of about 18 cm during the 20th century, and over 6 cm for the first 15 years of the 21st century. Regionally the sea level rise is not uniform due in large part to internal climate variability. To better serve the community, the uncertainties of predicting/projecting regional sea level changes associated with internal climate variability need to be quantified. Previous research on this topic has used single-model large ensemblesmore » with perturbed atmospheric initial conditions (ICs). Here we compare uncertainties associated with perturbing ICs in just the atmosphere and just the ocean using a state-of-the-art coupled climate model. We find that by perturbing the oceanic ICs, the uncertainties in regional sea level changes increase compared to those with perturbed atmospheric ICs. In order for us to better assess the full spectrum of the impacts of such internal climate variability on regional and global sea level rise, approaches that involve perturbing both atmospheric and oceanic initial conditions are thus necessary.« less

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.

Influence of long-range atmospheric transport pathways and climate teleconnection patterns on the variability of surface 210Pb and 7Be concentrations in southwestern Europe.

PubMed

Grossi, C; Ballester, J; Serrano, I; Galmarini, S; Camacho, A; Curcoll, R; Morguí, J A; Rodò, X; Duch, M A

2016-12-01

The variability of the atmospheric concentration of the 7 Be and 210 Pb radionuclides is strongly linked to the origin of air masses, the strength of their sources and the processes of wet and dry deposition. It has been shown how these processes and their variability are strongly affected by climate change. Thus, a deeper knowledge of the relationship between the atmospheric radionuclides variability measured close to the ground and these atmospheric processes could help in the analysis of climate scenarios. In the present study, we analyze the atmospheric variability of a 14-year time series of 7 Be and 210 Pb in a Mediterranean coastal city using a synergy of different indicators and tools such as: the local meteorological conditions, global and regional climate indexes and a lagrangian atmospheric transport model. We particularly focus on the relationships between the main pathways of air masses and sun spots occurrence, the variability of the local relative humidity and temperature conditions, and the main modes of regional climate variability, such as the North Atlantic Oscillation (NAO) and the Western Mediterranean Oscillation (WeMO). The variability of the observed atmospheric concentrations of both 7 Be and 210 Pb radionuclides was found to be mainly positively associated to the local climate conditions of temperature and to the pathways of air masses arriving at the station. Measured radionuclide concentrations significantly increase when air masses travel at low tropospheric levels from central Europe and the western part of the Iberian Peninsula, while low concentrations are associated with westerly air masses. We found a significant negative correlation between the WeMO index and the atmospheric variability of both radionuclides and no significant association was observed for the NAO index. Copyright © 2016 Elsevier Ltd. All rights reserved.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

Selection of meteorological conditions to apply in an Ecotron facility

NASA Astrophysics Data System (ADS)

Leemans, Vincent; De Cruz, Lesley; Dumont, Benjamin; Hamdi, Rafiq; Delaplace, Pierre; Heinesh, Bernard; Garré, Sarah; Verheggen, François; Theodorakopoulos, Nicolas; Longdoz, Bernard

2017-04-01

This presentation aims to propose a generic method to produce meteorological input data that is useful for climate research infrastructures such as an Ecotron, where researchers will face the need to generate representative actual or future climatic conditions. Depending on the experimental objectives and the research purposes, typical conditions or more extreme values such as dry or wet climatic scenarios might be requested. Four variables were considered here, the near-surface air temperature, the near-surface relative humidity, the cloud cover and precipitation. The meteorological datasets, among which a specific meteorological year can be picked up, are produced by the ALARO-0 model from the RMIB (Royal Meteorological Institute of Belgium). Two future climate scenarios (RCP 4.5 and 8.5) and two time periods (2041-2070 and 2071-2100) were used as well as a historical run of the model (1981-2010) which is used as a reference. When the data from a historical run were compared to the observed historical data, biases were noticed. A linear correction was proposed for all the variables except for precipitation, for which a non-linear correction (using a power function) was chosen to maintain a zero-precipitation occurrences. These transformations were able to remove most of the differences between the observed and historical run of the model for the means and for the standard deviations. For the relative humidity, because of non-linearities, only one half of the average bias was corrected and a different path might have to be chosen. For the selection of a meteorological year, a position and a dispersion parameter have been proposed to characterise each meteorological year for each variable. For precipitation, a third parameter quantifying the importance of dry and wet periods has been defined. In order to select a specific climate, for each of these nine parameters the experimenter should provide a percentile and a weight to prioritize the importance of each variable in the process of a global climate selection. The proposed algorithm computed the weighted distance for each year between the parameters and the point representing the position of the percentile in the nine-dimensional space. The five closest values were then selected and represented in different graphs. The proposed method is able to provide a decision aid in the selection of the meteorological conditions to be generated within an Ecotron. However, with a limited number of years available in each case (thirty years for each RCP and each time period), there is no perfect match and the ultimate trade-off will be the responsibility of the researcher. For typical years, close to the median, the relative frequency is higher and the trade-off is more easy than for more extreme years where the relative frequency is low.

Effect of year-to-year variability of leaf area index on variable infiltration capacity model performance and simulation of streamflow during drought

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2014-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrologic model performance and the simulation of streamflow during drought using the variable infiltration capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) observed monthly LAI dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the percentage deviation of the simulated monthly streamflow using the observed monthly LAI from simulated streamflow using long-term mean monthly LAI was computed. The VIC model predicted monthly streamflow in the selected sub-catchments with model efficiencies ranging from 61.5 to 95.9% during calibration (1982-1997) and 59 to 92.4% during validation (1998-2012). Our results suggest systematic improvements from 4 to 25% in the Nash-Sutcliffe efficiency in pasture dominated catchments when the VIC model was calibrated with the observed monthly LAI instead of the long-term mean monthly LAI. There was limited systematic improvement in tree dominated catchments. The results also suggest that the model overestimation or underestimation of streamflow during wet and dry periods can be reduced to some extent by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

The effect of year-to-year variability of leaf area index on Variable Infiltration Capacity model performance and simulation of runoff

NASA Astrophysics Data System (ADS)

Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

2015-09-01

This study assessed the effect of using observed monthly leaf area index (LAI) on hydrological model performance and the simulation of runoff using the Variable Infiltration Capacity (VIC) hydrological model in the Goulburn-Broken catchment of Australia, which has heterogeneous vegetation, soil and climate zones. VIC was calibrated with both observed monthly LAI and long-term mean monthly LAI, which were derived from the Global Land Surface Satellite (GLASS) leaf area index dataset covering the period from 1982 to 2012. The model performance under wet and dry climates for the two different LAI inputs was assessed using three criteria, the classical Nash-Sutcliffe efficiency, the logarithm transformed flow Nash-Sutcliffe efficiency and the percentage bias. Finally, the deviation of the simulated monthly runoff using the observed monthly LAI from simulated runoff using long-term mean monthly LAI was computed. The VIC model predicted monthly runoff in the selected sub-catchments with model efficiencies ranging from 61.5% to 95.9% during calibration (1982-1997) and 59% to 92.4% during validation (1998-2012). Our results suggest systematic improvements, from 4% to 25% in Nash-Sutcliffe efficiency, in sparsely forested sub-catchments when the VIC model was calibrated with observed monthly LAI instead of long-term mean monthly LAI. There was limited systematic improvement in tree dominated sub-catchments. The results also suggest that the model overestimation or underestimation of runoff during wet and dry periods can be reduced to 25 mm and 35 mm respectively by including the year-to-year variability of LAI in the model, thus reflecting the responses of vegetation to fluctuations in climate and other factors. Hence, the year-to-year variability in LAI should not be neglected; rather it should be included in model calibration as well as simulation of monthly water balance.

Drought and deluge: Effects of recent climate variability on groundwater levels in eastern Arkansas

USGS Publications Warehouse

Czarnecki, John B.; Schrader, T.P.

2013-01-01

Arkansas experienced wide extremes in climate variability during the period of 2005 to 2010, recording the largest annual precipitation ever recorded in the State (100.05 inches) in 2009. Many weather stations across the State reported between 80 to 90 inches of rainfall in 2009. For comparison, the average annual precipitation in Little Rock, Arkansas, for the period 1878 to 2010 was 47.1 inches. In contrast, 2005 and 2010 were the 7th and 14th driest years on record in Little Rock with 34.55 and 36.52 inches, respectively; both tied as the hottest years ever recorded in Arkansas. The wettest year on record in Little Rock (2009) was interspersed within these dry years, with a total of 81.79 inches. Fifteen weather stations within the State ranked 2009 as the wettest year on record. Extremes in annual precipitation rates may lead to greater variability in groundwater recharge rates and water use, particularly in the agricultural areas in eastern Arkansas that rely heavily on groundwater produced from the Mississippi River Valley alluvial aquifer (hereafter referred to as the alluvial aquifer). How does this variability affect the groundwater system and water use therein? Are the effects of this variability discernable in measured water levels in wells? Czarnecki and Schrader examined these questions and provided some insights, the results of which are presented here.

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.

PubMed

Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi

2014-07-01

Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.

Rain, temperature, and child-adolescent height among Native Amazonians in Bolivia.

PubMed

Godoy, R; Goodman, E; Reyes-Garcia, V; Eisenberg, D T A; Leonard, W R; Huanca, T; McDade, T W; Tanner, S; Jha, N

2008-01-01

Global climate change and recent studies on early-life origins of well-being suggest that climate events early in life might affect health later in life. The study tested hypotheses about the association between the level and variability of rain and temperature early in life on the height of children and adolescents in a foraging-farming society of native Amazonians in Bolivia (Tsimane'). Measurements were taken for 525 children aged 2-12 and 218 adolescents aged 13-23 in 13 villages in 2005. Log of standing height was regressed on mean annual level and mean intra-annual monthly coefficient of variation (CV) of rain and mean annual level of temperature during gestation, birth year, and ages 2-4. Controls include age, quinquennium and season of birth, parent's attributes, and dummy variables for surveyors and villages. Climate variables were only related with the height of boys age 2-12. The level and CV of rain during birth year and the CV of rain and level of temperature during ages 2-4 were associated with taller stature. There were no secular changes in temperature (1973-2005) or rain (1943-2005). The height of young females and males is well protected from climate events, but protection works less well for boys ages 2-12.

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

PubMed

Milfont, Taciano L

2012-06-01

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

Eastern South African hydroclimate over the past 270,000 years

NASA Astrophysics Data System (ADS)

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J. C.; Hall, Ian R.

2015-12-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years.

PubMed

Simon, Margit H; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J C; Hall, Ian R

2015-12-21

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years

PubMed Central

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J.C.; Hall, Ian R.

2015-01-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique. PMID:26686943

Country-Specific Effects of Climate Variability on Human Migration

PubMed Central

Gray, Clark; Wise, Erika

2016-01-01

Involuntary human migration is among the social outcomes of greatest concern in the current era of global climate change. Responding to this concern, a growing number of studies have investigated the consequences of short to medium-term climate variability for human migration using demographic and econometric approaches. These studies have provided important insights, but at the same time have been significantly limited by lack of expertise in the use of climate data, access to cross-national data on migration, and attention to model specification. To address these limitations, we link data on internal and international migration over a 6-year period from 9,812 origin households in Kenya, Uganda, Nigeria, Burkina Faso and Senegal to high-resolution gridded climate data from both station and satellite sources. Analyses of these data using several plausible specifications reveal that climate variability has country-specific effects on migration: Migration tends to increase with temperature anomalies in Uganda, tends to decrease with temperature anomalies in Kenya and Burkina Faso, and shows no consistent relationship with temperature in Nigeria and Senegal. Consistent with previous studies, precipitation shows weak and inconsistent relationships with migration across countries. These results challenge generalizing narratives that foresee a consistent migratory response to climate change across the globe. PMID:27092012

Flexible stocking strategies for adapting to climatic variability

USDA-ARS?s Scientific Manuscript database

As a result of precipitation-induced variability on forage production, ranchers have difficulty matching animal demand with forage availability in their operations. Flexible stocking strategies could more effectively use extra forage in highly productive years and limit risk of overgrazing during dr...

Extreme storm surge and wind wave climate scenario simulations at the Venetian littoral

NASA Astrophysics Data System (ADS)

Lionello, P.; Galati, M. B.; Elvini, E.

Scenario climate projections for extreme marine storms producing storm surges and wind waves are very important for the northern flat coast of the Adriatic Sea, where the area at risk includes a unique cultural and environmental heritage, and important economic activities. This study uses a shallow water model and a spectral wave model for computing the storm surge and the wind wave field, respectively, from the sea level pressure and wind fields that have been computed by the RegCM regional climate model. Simulations cover the period 1961-1990 for the present climate (control simulations) and the period 2071-2100 for the A2 and B2 scenarios. Generalized Extreme Value analysis is used for estimating values for the 10 and 100 year return times. The adequacy of these modeling tools for a reliable estimation of the climate change signal, without needing further downscaling is shown. However, this study has mainly a methodological value, because issues such as interdecadal variability and intermodel variability cannot be addressed, since the analysis is based on single model 30-year long simulations. The control simulation looks reasonably accurate for extreme value analysis, though it overestimates/underestimates the frequency of high/low surge and wind wave events with respect to observations. Scenario simulations suggest higher frequency of intense storms for the B2 scenario, but not for the A2. Likely, these differences are not the effect of climate change, but of climate multidecadal variability. Extreme storms are stronger in future scenarios, but differences are not statistically significant. Therefore this study does not provide convincing evidence for more stormy conditions in future scenarios.

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

DOE PAGES

Berryman, E. M.; Barnard, H. R.; Adams, H. R.; ...

2015-02-10

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

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

Berryman, E. M.; Barnard, H. R.; Adams, H. R.

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. In this paper, we quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important formore » dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Finally, soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.« less

Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

USGS Publications Warehouse

Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D.

2015-01-01

Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.

El Niño Helps Spread Bartonellosis Epidemics in Peru

NASA Astrophysics Data System (ADS)

Zhou, Jiayu; Lau, William K.-M.; Masuoka, Fenny M.; Andre, Richard G.; Chamberlin, Judith; Lawyer, Phillip; Laughlin, Larry W.

The consequences of climate variability on human health, especially for poor and medically underserved populations, have received much attention in recent years. Some of the most severe health hazards induced by climate variability are epidemics of vector-borne infectious diseases. Entomologic studies have shown that insect vectors that transmit diseases, such as malaria, yellow fever, dengue, etc., are sensitive to temperature, humidity wind, and rainfall patterns, and therefore, their abundance is potentially influenced by climate variability. Because of its geographical location, the climate of tropical South America is strongly influenced by El Niño. The episodic outbreaks of various diseases in this region have been linked to the El Niño cycles. Yet, according to a report of the World Health Organization [1999], early results from South American epidemiological studies, which were based on the aggregated national disease data irrespective of the regional meteorological impacts, found no consistent correlation between the El Niño effect with the epidemics of malaria and yellow fever.

A decade of sea level rise slowed by climate-driven hydrology.

PubMed

Reager, J T; Gardner, A S; Famiglietti, J S; Wiese, D N; Eicker, A; Lo, M-H

2016-02-12

Climate-driven changes in land water storage and their contributions to sea level rise have been absent from Intergovernmental Panel on Climate Change sea level budgets owing to observational challenges. Recent advances in satellite measurement of time-variable gravity combined with reconciled global glacier loss estimates enable a disaggregation of continental land mass changes and a quantification of this term. We found that between 2002 and 2014, climate variability resulted in an additional 3200 ± 900 gigatons of water being stored on land. This gain partially offset water losses from ice sheets, glaciers, and groundwater pumping, slowing the rate of sea level rise by 0.71 ± 0.20 millimeters per year. These findings highlight the importance of climate-driven changes in hydrology when assigning attribution to decadal changes in sea level. Copyright © 2016, American Association for the Advancement of Science.

Skillful prediction of northern climate provided by the ocean

NASA Astrophysics Data System (ADS)

Årthun, Marius; Eldevik, Tor; Viste, Ellen; Drange, Helge; Furevik, Tore; Johnson, Helen L.; Keenlyside, Noel S.

2017-06-01

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981-2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

A global model of malaria climate sensitivity: comparing malaria response to historic climate data based on simulation and officially reported malaria incidence.

PubMed

Edlund, Stefan; Davis, Matthew; Douglas, Judith V; Kershenbaum, Arik; Waraporn, Narongrit; Lessler, Justin; Kaufman, James H

2012-09-18

The role of the Anopheles vector in malaria transmission and the effect of climate on Anopheles populations are well established. Models of the impact of climate change on the global malaria burden now have access to high-resolution climate data, but malaria surveillance data tends to be less precise, making model calibration problematic. Measurement of malaria response to fluctuations in climate variables offers a way to address these difficulties. Given the demonstrated sensitivity of malaria transmission to vector capacity, this work tests response functions to fluctuations in land surface temperature and precipitation. This study of regional sensitivity of malaria incidence to year-to-year climate variations used an extended Macdonald Ross compartmental disease model (to compute malaria incidence) built on top of a global Anopheles vector capacity model (based on 10 years of satellite climate data). The predicted incidence was compared with estimates from the World Health Organization and the Malaria Atlas. The models and denominator data used are freely available through the Eclipse Foundation's Spatiotemporal Epidemiological Modeller (STEM). Although the absolute scale factor relating reported malaria to absolute incidence is uncertain, there is a positive correlation between predicted and reported year-to-year variation in malaria burden with an averaged root mean square (RMS) error of 25% comparing normalized incidence across 86 countries. Based on this, the proposed measure of sensitivity of malaria to variations in climate variables indicates locations where malaria is most likely to increase or decrease in response to specific climate factors. Bootstrapping measures the increased uncertainty in predicting malaria sensitivity when reporting is restricted to national level and an annual basis. Results indicate a potential 20x improvement in accuracy if data were available at the level ISO 3166-2 national subdivisions and with monthly time sampling. The high spatial resolution possible with state-of-the-art numerical models can identify regions most likely to require intervention due to climate changes. Higher-resolution surveillance data can provide a better understanding of how climate fluctuations affect malaria incidence and improve predictions. An open-source modelling framework, such as STEM, can be a valuable tool for the scientific community and provide a collaborative platform for developing such models.

Changing forest water yields in response to climate warming: results from long-term experimental watershed sites across North America

Treesearch

Irena F. Creed; Adam T. Spargo; Julia A. Jones; Jim M. Buttle; Mary B. Adams; Fred D. Beall; Eric G. Booth; John L. Campbell; Dave Clow; Kelly Elder; Mark B. Green; Nancy B. Grimm; Chelcy Miniat; Patricia Ramlal; Amartya Saha; Stephen Sebestyen; Dave Spittlehouse; Shannon Sterling; Mark W. Williams; Rita Winkler; Huaxia Yao

2014-01-01

Climate warming is projected to affect forest water yields but the effects are expected to vary.We investigated how forest type and age affect water yield resilience to climate warming. To answer this question, we examined the variability in historical water yields at long-term experimental catchments across Canada and the United States over 5-year cool and warm...

Impacts of climatic change and fishing on Pacific salmon abundance over the past 300 years.

PubMed

Finney, B P; Gregory-Eaves, I; Sweetman, J; Douglas, M S; Smol, J P

2000-10-27

The effects of climate variability on Pacific salmon abundance are uncertain because historical records are short and are complicated by commercial harvesting and habitat alteration. We use lake sediment records of delta15N and biological indicators to reconstruct sockeye salmon abundance in the Bristol Bay and Kodiak Island regions of Alaska over the past 300 years. Marked shifts in populations occurred over decades during this period, and some pronounced changes appear to be related to climatic change. Variations in salmon returns due to climate or harvesting can have strong impacts on sockeye nursery lake productivity in systems where adult salmon carcasses are important nutrient sources.

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

PubMed

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

2014-11-01

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

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Impacts of climate variability and human colonization on the vegetation of the Galápagos Islands.

PubMed

Restrepo, Alejandra; Colinvaux, Paul; Bush, Mark; Correa-Metrio, Alexander; Conroy, Jessica; Gardener, Mark R; Jaramillo, Patricia; Steinitz-Kannan, Miriam; Overpeck, Jonathan

2012-08-01

A high-resolution (2-9 year sampling interval) fossil pollen record from the Galápagos Islands, which spans the last 2690 years, reveals considerable ecosystem stability. Vegetation changes associated with independently derived histories of El Niño Southern Oscillation variability provided evidence of shifts in the relative abundance of individual species rather than immigration or extinction. Droughts associated with the Medieval Climate Anomaly induced rapid ecological change that was followed by a reversion to the previous state. The paleoecological data suggested nonneutral responses to climatic forcing in this ecosystem prior to the period of human influence. Human impacts on the islands are evident in the record. A marked decline in long-term codominants of the pollen record, Alternanthera and Acalypha, produced a flora without modern analogue before 1930. Intensified animal husbandry after ca. 1930 may have induced the local extinction of Acalypha and Alternanthera. Reductions in populations of grazing animals in the 1970s and 1980s did not result in the return of the native flora, but in invasions by exotic species. After ca. 1970 the trajectory of habitat change accelerated, continuously moving the ecosystem away from the observed range of variability in the previous 2690 years toward a novel ecosystem. The last 40 years of the record also suggest unprecedented transport of lowland pollen to the uplands, consistent with intensified convection and warmer wet seasons.

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

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

Yang, Qichun; Tian, Hanqin; Li, Xia

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE PAGES

Yang, Qichun; Tian, Hanqin; Li, Xia; ...

2014-08-08

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Climate warming alters effects of management on population viability of threatened species: results from a 30-year experimental study on a rare orchid.

PubMed

Sletvold, Nina; Dahlgren, Johan P; Oien, Dag-Inge; Moen, Asbjørn; Ehrlén, Johan

2013-09-01

Climate change is expected to influence the viability of populations both directly and indirectly, via species interactions. The effects of large-scale climate change are also likely to interact with local habitat conditions. Management actions designed to preserve threatened species therefore need to adapt both to the prevailing climate and local conditions. Yet, few studies have separated the direct and indirect effects of climatic variables on the viability of local populations and discussed the implications for optimal management. We used 30 years of demographic data to estimate the simultaneous effects of management practice and among-year variation in four climatic variables on individual survival, growth and fecundity in one coastal and one inland population of the perennial orchid Dactylorhiza lapponica in Norway. Current management, mowing, is expected to reduce competitive interactions. Statistical models of how climate and management practice influenced vital rates were incorporated into matrix population models to quantify effects on population growth rate. Effects of climate differed between mown and control plots in both populations. In particular, population growth rate increased more strongly with summer temperature in mown plots than in control plots. Population growth rate declined with spring temperature in the inland population, and with precipitation in the coastal population, and the decline was stronger in control plots in both populations. These results illustrate that both direct and indirect effects of climate change are important for population viability and that net effects depend both on local abiotic conditions and on biotic conditions in terms of management practice and intensity of competition. The results also show that effects of management practices influencing competitive interactions can strongly depend on climatic factors. We conclude that interactions between climate and management should be considered to reliably predict future population viability and optimize conservation actions. © 2013 John Wiley & Sons Ltd.

Analysis of monthly, winter, and annual temperatures in Zagreb, Croatia, from 1864 to 2010: the 7.7-year cycle and the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Sen, Asok K.; Ogrin, Darko

2016-02-01

Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity.

Meteorological influences on the interannual variability of meningitis incidence in northwest Nigeria.

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Monaghan, Andrew; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Leckebusch, Gregor

2013-04-01

Northwest Nigeria is a region with high risk of bacterial meningitis. Since the first documented epidemic of meningitis in Nigeria in 1905, the disease has been endemic in the northern part of the country, with epidemics occurring regularly. In this study we examine the influence of climate on the interannual variability of meningitis incidence and epidemics. Monthly aggregate counts of clinically confirmed hospital-reported cases of meningitis were collected in northwest Nigeria for the 22-year period spanning 1990-2011. Several generalized linear statistical models were fit to the monthly meningitis counts, including generalized additive models. Explanatory variables included monthly records of temperatures, humidity, rainfall, wind speed, sunshine and dustiness from weather stations nearest to the hospitals, and a time series of polysaccharide vaccination efficacy. The effects of other confounding factors -- i.e., mainly non-climatic factors for which records were not available -- were estimated as a smooth, monthly-varying function of time in the generalized additive models. Results reveal that the most important explanatory climatic variables are mean maximum monthly temperature, relative humidity and dustiness. Accounting for confounding factors (e.g., social processes) in the generalized additive models explains more of the year-to-year variation of meningococcal disease compared to those generalized linear models that do not account for such factors. Promising results from several models that included only explanatory variables that preceded the meningitis case data by 1-month suggest there may be potential for prediction of meningitis in northwest Nigeria to aid decision makers on this time scale.

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

NASA Astrophysics Data System (ADS)

Wolfe, Brent

2013-04-01

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

Climatic change controls productivity variation in global grasslands

PubMed Central

Gao, Qingzhu; Zhu, Wenquan; Schwartz, Mark W.; Ganjurjav, Hasbagan; Wan, Yunfan; Qin, Xiaobo; Ma, Xin; Williamson, Matthew A.; Li, Yue

2016-01-01

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms. PMID:27243565

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, David A.; Helfrich, J. V. K.; Moore, B.; Vorosmarty, C.J.

1998-01-01

The Amazon Basin contains almost one-half of the world's undisturbed tropical evergreen forest as well as large areas of tropical savanna. The forests account for about 10 per cent of the world's terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems, and short-term field measurements suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Nino episodes in recent decades. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage. Here we use a transient process-based biogeochemical model of terrestrial ecosystems to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Nino years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation in the Amazon Basin in the early 1990s. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Using dry and wet year hydroclimatic extremes to guide future hydrologic projections

NASA Astrophysics Data System (ADS)

Oni, Stephen; Futter, Martyn; Ledesma, Jose; Teutschbein, Claudia; Buttle, Jim; Laudon, Hjalmar

2016-07-01

There are growing numbers of studies on climate change impacts on forest hydrology, but limited attempts have been made to use current hydroclimatic variabilities to constrain projections of future climatic conditions. Here we used historical wet and dry years as a proxy for expected future extreme conditions in a boreal catchment. We showed that runoff could be underestimated by at least 35 % when dry year parameterizations were used for wet year conditions. Uncertainty analysis showed that behavioural parameter sets from wet and dry years separated mainly on precipitation-related parameters and to a lesser extent on parameters related to landscape processes, while uncertainties inherent in climate models (as opposed to differences in calibration or performance metrics) appeared to drive the overall uncertainty in runoff projections under dry and wet hydroclimatic conditions. Hydrologic model calibration for climate impact studies could be based on years that closely approximate anticipated conditions to better constrain uncertainty in projecting extreme conditions in boreal and temperate regions.

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

NASA Astrophysics Data System (ADS)

Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these sequences allowing identification of growth periods with different magnitudes and durations anywhere in the time series. Results show that the highest absolute variability in peak greenness occurred in cropped areas while the highest relative variability (coefficient of variation) occurred in interior Australia particularly around Lake Eyre, the center of a closed drainage basin in the dry interior of the continent. Across the desert interior, the timing of the green-up onset and the peak greenness was correlated with the landfall of cyclones and the inland penetration and strength of the north Australian summer monsoon (represented by TRMM data). The variability of Australian land surface phenology magnitude and timing was found to be strongly correlated with the swings between La Nina and El Nino events. The information on vegetation dynamics represented here is critical for land surface, fuel accumulation, agricultural production, and permanent ecosystem change modeling in relation to climate trends. A unique research opportunity is provided by recent climate variability: in 2010 a persistent El Nino has given way to a strong two-year La Nina breaking a decade long drought that was followed by record-breaking rainfall across most of the continent and extensive flooding followed by sustained greening.

Interannual variability: a crucial component of space use at the territory level.

PubMed

Uboni, Alessia; Vucetich, John A; Stahler, Daniel R; Smith, Douglas W

2015-01-01

Interannual variability in space use and how that variation is influenced by density-dependent and density-independent factors are important processes in population ecology. Nevertheless, interannual variability has been neglected by the majority of space use studies. We assessed that variation for wolves living in 15 different packs within Yellowstone National Park during a 13-year period (1996-2008). We estimated utilization distributions to quantify the intensity of space use within each pack's territory each year in summer and winter. Then, we used the volume of intersection index (VI) to quantify the extent to which space use varied from year to year. This index accounts for both the area of overlap and differences in the intensity of use throughout a territory and ranges between 0 and 1. The mean VI index was 0.49, and varied considerably, with approximately 20% of observations (n = 230) being <0.3 or >0.7. In summer, 42% of the variation was attributable to differences between packs. These differences can be attributable to learned behaviors and had never been thought to have such an influence on space use. In winter, 34% of the variation in overlap between years was attributable to interannual differences in precipitation and pack size. This result reveals the strong influence of climate on predator space use and underlies the importance of understanding how climatic factors are going to affect predator populations in the occurrence of climate change. We did not find any significant association between overlap and variables representing density-dependent processes (elk and wolf densities) or intraspecific competition (ratio of wolves to elk). This last result poses a challenge to the classic view of predator-prey systems. On a small spatial scale, predator space use may be driven by factors other than prey distribution.

Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling

NASA Astrophysics Data System (ADS)

Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.

2012-04-01

The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).

A Coral-based Reconstruction of Interannual Climate Variability at Vanuatu during the Medieval Climate Anomaly (950-1250 CE)

NASA Astrophysics Data System (ADS)

Lawman, A. E.; Quinn, T. M.; Partin, J. W.; Taylor, F. W.; Thirumalai, K.; WU, C. C.; Shen, C. C.

2016-12-01

The Medieval Climate Anomaly (MCA: 950-1250 CE) is identified as a period during the last 2 millennia with Northern Hemisphere surface temperatures similar to the present. However, our understanding of tropical climate variability during the MCA is poorly constrained due to a lack of proxy records. We investigate the El Niño-Southern Oscillation (ENSO), the leading mode of global interannual variability, during the MCA using geochemical records developed from well preserved fossilized corals from the tropical southwest Pacific (Tasmaloum, Vanuatu; 15° 37' S, 166° 54.5' E). We use paired coral Sr/Ca and δ18O measurements to reconstruct sea surface temperature (SST) and the δ18O of seawater (a proxy for salinity) variability associated with ENSO. We present Sr/Ca and δ18O data from a 1.68-m-long Porites lutea coral head collected from Tasmaloum, Vanuatu. An absolute U/Th date of 1127.1 ± 2.7 CE indicates that the selected coral lived during the MCA. Preliminary assessment of >65 years of monthly resolved Sr/Ca data yields a mean value of 8.937 ± 0.120 mmol/mol (2σ, n = 757), and an average seasonal cycle of 0.156 ± 0.009 mmol/mol or 2.7 ± 0.1°C based on modern Sr/Ca-SST calibrations. We find that the magnitude and variability of the SST seasonal cycle is comparable to gridded and in situ SST datasets for Vanuatu as well as a published, modern 165 year-long coral record from Sabine Bank, Vanuatu, located 90 km to the SW of Tasmaloum. Applying a 2-8 year band pass filter to the Sr/Ca time series, we identify 8 El Niño and 3 La Niña events based on Sr/Ca (SST) anomalies. Preliminary assessment of >45 years of paired δ18O measurements yields a mean value of -4.67 ± 0.43‰ (2σ, n = 373). We also identify ENSO activity in the 2-8 year band pass filtered data. We expect to develop a 120-year record of paired coral Sr/Ca and δ18O measurements when data acquisition is complete, which will be used to investigate the frequency and magnitude of ENSO events during the MCA.

A new large initial condition ensemble to assess avoided impacts in a climate mitigation scenario

NASA Astrophysics Data System (ADS)

Sanderson, B. M.; Tebaldi, C.; Knutti, R.; Oleson, K. W.

2014-12-01

It has recently been demonstrated that when considering timescales of up to 50 years, natural variability may play an equal role to anthropogenic forcing on subcontinental trends for a variety of climate indicators. Thus, for many questions assessing climate impacts on such time and spatial scales, it has become clear that a significant number of ensemble members may be required to produce robust statistics (and especially so for extreme events). However, large ensemble experiments to date have considered the role of variability in a single scenario, leaving uncertain the relationship between the forced climate trajectory and the variability about that path. To address this issue, we present a new, publicly available, 15 member initial condition ensemble of 21st century climate projections for the RCP 4.5 scenario using the CESM1.1 Earth System Model, which we propose as a companion project to the existing 40 member CESM large ensemble which uses the higher greenhouse gas emission future of RCP8.5. This provides a valuable data set for assessing what societal and ecological impacts might be avoided through a moderate mitigation strategy in contrast to a fossil fuel intensive future. We present some early analyses of these combined ensembles to assess to what degree the climate variability can be considered to combine linearly with the underlying forced response. In regions where there is no detectable relationship between the mean state and the variability about the mean trajectory, then linear assumptions can be trivially exploited to utilize a single ensemble or control simulation to characterize the variability in any scenario of interest. We highlight regions where there is a detectable nonlinearity in extreme event frequency, how far in the future they will be manifested and propose mechanisms to account for these effects.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Impacts of climate variability and extreme events on soil hydrological processes

NASA Astrophysics Data System (ADS)

Ramos, M. C.; Mulligan, M.

2003-04-01

The Mediterranean climate (dry subhumid), characterised by a high variability, produces in many situations an insufficient water supply to support stable agriculture. Not only is there insufficient rainfall, but its occurrence is also highly variable between years, during the year, and spatially, during a single rainfall event. One of the main climatic characteristics affecting the vulnerability of the Mediterranean region is the high intensity rainfalls which fall after a very dry summer and the high degree of climatic fluctuation in the short and long term, especially in rainfall quantity. In addition, the rainwater penetration and storage of water in the soil are conditioned by the soil characteristics, in some cases modified by changes in land use and with new management practices. The aim of this study was to evaluate the impact of this high variability, from year to year and through the year, on soil hydrological processes, in fields resulted of the mechanisation works in vineyards in a Mediterranean environment. The PATTERNlight model, a simplified two-dimensional version of the hydrological and growth PATTERN model (Mulligan, 1996) is used here to simulate the water balance for three situations: normal, wet and dry years. Ssignificant differences in soil moisture and recharge were observed under vine culture from year to year, giving rise very often, to critical situations for the development of the crops. The distribution of the rainfall through the year together with the intensity of the recorded rainfalls is much very significant for soil hydrology than the total annual rainfall. Very low soil moisture conditions are raised when spring rainfall is scarce, which contribute to exhaustion of profile soil water over the summer, especially if the antecedent soil moisture is low. This low soil moisture has a significant effect on the development of the vine crop. The simulations of leaf and root biomass carried out with the PATTERNLIGHT model indicate the differences in the development of the leaf biomass between wet and dry conditions, especially with dry springs. Wet conditions favour the development of root and leaf biomass in a significant way. Mulligan, M., 1996. Modelling the hydrology of vegetation competition in a degrade semiarid environment. PhD Theses. Department of Geography, King's College London, University of London.

Solar-terrestrial influences on weather and climate; Proceedings of the Symposium, Ohio State University, Columbus, Ohio, August 24-28, 1978

NASA Technical Reports Server (NTRS)

Mccormac, B. M. (Editor); Seliga, T. A.

1979-01-01

The book contains most of the invited papers and contributions presented at the symposium/workshop on solar-terrestrial influences on weather and climate. Four main issues dominate the activities of the symposium: whether solar variability relationships to weather and climate is a fundamental scientific question to which answers may have important implications for long-term weather and climate prediction; the sun-weather relationships; other potential solar influences on weather including the 11-year sunspot cycle, the 27-day solar rotation, and special solar events such as flares and coronal holes; and the development of practical use of solar variability as a tool for weather and climatic forecasting, other than through empirical approaches. Attention is given to correlation topics; solar influences on global circulation and climate models; lower and upper atmospheric coupling, including electricity; planetary motions and other indirect factors; experimental approaches to sun-weather relationships; and the role of minor atmospheric constituents.

The impacts of climatologically-driven megadrought, past and future, on semi-arid watersheds and the water resource system they support in central Arizona, USA.

NASA Astrophysics Data System (ADS)

Murphy, K. W.; Ellis, A. W.

2017-12-01

The sustainability of water resource systems in the western United States has previously been brought into question by drought concerns and how it will be influenced by future climate change. Although decadal droughts are observed in instrumental records, the data are typically too short and the droughts too few to render the range of hydroclimatic variability that might impact modern water resource systems in the future. Natural modes of variability are not well represented in climate models, which limits the applicability of their downscaled projections in a region of interest since drought risk would be understated. Paleoclimate data have provided evidence of megadroughts from centuries ago whose hydrologic manifestations of climate variability could readily reoccur again in the future. These can be applied to research into watershed hydrologic response and resource system resilience - past, present, and future. A 645-year tree ring reconstruction of stream flow for the Salt and Verde River watersheds in central Arizona has revealed several drought periods, some more severe than seen in the 129-year instrumental record, including a late 16th century megadrought which affected large portions of the United States. This research study translated the tree ring record into net basin water supply which drives a reservoir operations simulation model to assess how the resource system performs under such severe drought. Regional climate change scenarios were developed from the observation that watershed climate sensitivity has been twice the global warming response. These were applied to the watersheds' temperature sensitivities and precipitation elasticities (reported at AGU2014) to obtain detailed renditions of hydrologic response should megadrought reoccur in a future climate. This provided one of the first rigorous projections of surface water supply under future climate change that amplifies the impact of megadrought arising from modes of climate variability often seen in the western United States. The implications to a large reservoir system serving 40% of water demand in the metropolitan Phoenix, Arizona area is reported which enables decision making for future adaptation planning.

Reducing the Uncertainty in Atlantic Meridional Overturning Circulation Projections Using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Olson, R.; An, S. I.

2016-12-01

Atlantic Meridional Overturning Circulation (AMOC) in the ocean might slow down in the future, which can lead to a host of climatic effects in North Atlantic and throughout the world. Despite improvements in climate models and availability of new observations, AMOC projections remain uncertain. Here we constrain CMIP5 multi-model ensemble output with observations of a recently developed AMOC index to provide improved Bayesian predictions of future AMOC. Specifically, we first calculate yearly AMOC index loosely based on Rahmstorf et al. (2015) for years 1880—2004 for both observations, and the CMIP5 models for which relevant output is available. We then assign a weight to each model based on a Bayesian Model Averaging method that accounts for differential model skill in terms of both mean state and variability. We include the temporal autocorrelation in climate model errors, and account for the uncertainty in the parameters of our statistical model. We use the weights to provide future weighted projections of AMOC, and compare them to un-weighted ones. Our projections use bootstrapping to account for uncertainty in internal AMOC variability. We also perform spectral and other statistical analyses to show that AMOC index variability, both in models and in observations, is consistent with red noise. Our results improve on and complement previous work by using a new ensemble of climate models, a different observational metric, and an improved Bayesian weighting method that accounts for differential model skill at reproducing internal variability. Reference: Rahmstorf, S., Box, J. E., Feulner, G., Mann, M. E., Robinson, A., Rutherford, S., & Schaffernicht, E. J. (2015). Exceptional twentieth-century slowdown in atlantic ocean overturning circulation. Nature Climate Change, 5(5), 475-480. doi:10.1038/nclimate2554

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.

Range-wide reproductive consequences of ocean climate variability for the seabird Cassin's Auklet.

PubMed

Wolf, Shaye G; Sydeman, William J; Hipfner, J Mark; Abraham, Christine L; Tershy, Bernie R; Croll, Donald A

2009-03-01

We examine how ocean climate variability influences the reproductive phenology and demography of the seabird Cassin's Auklet (Ptychoramphus aleuticus) across approximately 2500 km of its breeding range in the oceanographically dynamic California Current System along the west coast of North America. Specifically, we determine the extent to which ocean climate conditions and Cassin's Auklet timing of breeding and breeding success covary across populations in British Columbia, central California, and northern Mexico over six years (2000-2005) and test whether auklet timing of breeding and breeding success are similarly related to local and large-scale ocean climate indices across populations. Local ocean foraging environments ranged from seasonally variable, high-productivity environments in the north to aseasonal, low-productivity environments to the south, but covaried similarly due to the synchronizing effects of large-scale climate processes. Auklet timing of breeding in the southern population did not covary with populations to the north and was not significantly related to local oceanographic conditions, in contrast to northern populations, where timing of breeding appears to be influenced by oceanographic cues that signal peaks in prey availability. Annual breeding success covaried similarly across populations and was consistently related to local ocean climate conditions across this system. Overall, local ocean climate indices, particularly sea surface height, better explained timing of breeding and breeding success than a large-scale climate index by better representing heterogeneity in physical processes important to auklets and their prey. The significant, consistent relationships we detected between Cassin's Auklet breeding success and ocean climate conditions across widely spaced populations indicate that Cassin's Auklets are susceptible to climate change across the California Current System, especially by the strengthening of climate processes that synchronize oceanographic conditions. Auklet populations in the northern and central regions of this ecosystem may be more sensitive to changes in the timing and variability of ocean climate conditions since they appear to time breeding to take advantage of seasonal productivity peaks.

Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era

NASA Astrophysics Data System (ADS)

Parkes, Ben; Defrance, Dimitri; Sultan, Benjamin; Ciais, Philippe; Wang, Xuhui

2018-02-01

The ability of a region to feed itself in the upcoming decades is an important issue. The West African population is expected to increase significantly in the next 30 years. The responses of crops to short-term climate change is critical to the population and the decision makers tasked with food security. This leads to three questions: how will crop yields change in the near future? What influence will climate change have on crop failures? Which adaptation methods should be employed to ameliorate undesirable changes? An ensemble of near-term climate projections are used to simulate maize, millet and sorghum in West Africa in the recent historic period (1986-2005) and a near-term future when global temperatures are 1.5 K above pre-industrial levels to assess the change in yield, yield variability and crop failure rate. Four crop models were used to simulate maize, millet and sorghum in West Africa in the historic and future climates. Across the majority of West Africa the maize, millet and sorghum yields are shown to fall. In the regions where yields increase, the variability also increases. This increase in variability increases the likelihood of crop failures, which are defined as yield negative anomalies beyond 1 standard deviation during the historic period. The increasing variability increases the frequency of crop failures across West Africa. The return time of crop failures falls from 8.8, 9.7 and 10.1 years to 5.2, 6.3 and 5.8 years for maize, millet and sorghum respectively. The adoption of heat-resistant cultivars and the use of captured rainwater have been investigated using one crop model as an idealized sensitivity test. The generalized doption of a cultivar resistant to high-temperature stress during flowering is shown to be more beneficial than using rainwater harvesting.

Effects of climate change on phenology in two French LTER (Alps and Brittany) for the period 1998-2009

NASA Astrophysics Data System (ADS)

Perrimond, B.; Bigot, S.; Quénol, H.; Spielgelberger, T.; Baudry, J.

2012-04-01

Climate and vegetation are linked all over the world. In this study, we work on a seasonal weather classification based on air temperature and precipitation to deduce a link with different phenological stage (greening up, senescence, ...) over a 12 year period (1998-2009) for two different domains in France (Alps and Brittany). In temperate land, the main climatic variable with a potential effect on vegetation is the mean temperature followed by the rainfall deficit. A better understanding in season and their climatic characteristic is need to establish link between climate and phenology; so a weather classification is proposed based on empirical orthogonal functions and ascending hierarchical classification on atmospheric variables. This classification allows us to exhibit the inter-annual and intra-seasonal climatic spatiotemporal variability for both experimental site. Relationships between climate and phenology consist in a comparison between advance and delay in phenological stage and weather type issue from the classification. Experiment field are two french Long Term Ecological Research (LTER). The first one (LTER 'Alps' ) have mountain characteristics about 1000 to 4780 m ASL, ~65% of forest occupation ; the second one (LTER Armorique) is an Atlantic coastal landscape, 0-360 m ASL, ~70% of agricultural field. Climatic data are SAFRAN-France reanalysis which are developed to run SVAT model and come from the French meteorological service 'Météo-France'. All atmospheric variable needed to run a hydrological model are available (air temperature, rainfall/snowfall, wind speed, relative humidity, incoming/outcoming radiation) at a 8-8 km2 space resolution and with a daily time resolution. The phenological data are extracted from SPOT-VGT product 1-1 km2 space resolution and 10 days time resolution) by time series analysis process. Such of study is particularly important to understand relationships between environmental and ecological variables and it will allow to better predict ecological reaction under climate change constraint.

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.

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

PubMed

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

2018-04-03

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

The climate of the Common Era off the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Abrantes, Fátima; Rodrigues, Teresa; Rufino, Marta; Salgueiro, Emília; Oliveira, Dulce; Gomes, Sandra; Oliveira, Paulo; Costa, Ana; Mil-Homens, Mário; Drago, Teresa; Naughton, Filipa

2017-12-01

The Mediterranean region is a climate hot spot, sensitive not only to global warming but also to water availability. In this work we document major temperature and precipitation changes in the Iberian Peninsula and margin during the last 2000 years and propose an interplay of the North Atlantic internal variability with the three atmospheric circulation modes (ACMs), (North Atlantic Oscillation (NAO), east atlantic (EA) and Scandinavia (SCAND)) to explain the detected climate variability. We present reconstructions of sea surface temperature (SST derived from alkenones) and on-land precipitation (estimated from higher plant n-alkanes and pollen data) in sedimentary sequences recovered along the Iberian Margin between the south of Portugal (Algarve) and the northwest of Spain (Galiza) (36 to 42° N). A clear long-term cooling trend, from 0 CE to the beginning of the 20th century, emerges in all SST records and is considered to be a reflection of the decrease in the Northern Hemisphere summer insolation that began after the Holocene optimum. Multi-decadal/centennial SST variability follows other records from Spain, Europe and the Northern Hemisphere. Warm SSTs throughout the first 1300 years encompass the Roman period (RP), the Dark Ages (DA) and the Medieval Climate Anomaly (MCA). A cooling initiated at 1300 CE leads to 4 centuries of colder SSTs contemporary with the Little Ice Age (LIA), while a climate warming at 1800 CE marks the beginning of the modern/Industrial Era. Novel results include two distinct phases in the MCA: an early period (900-1100 years) characterized by intense precipitation/flooding and warm winters but a cooler spring-fall season attributed to the interplay of internal oceanic variability with a positive phase in the three modes of atmospheric circulation (NAO, EA and SCAND). The late MCA is marked by cooler and relatively drier winters and a warmer spring-fall season consistent with a shift to a negative mode of the SCAND. The Industrial Era reveals a clear difference between the NW Iberia and the Algarve records. While off NW Iberia variability is low, the Algarve shows large-amplitude decadal variability with an inverse relationship between SST and river input. Such conditions suggest a shift in the EA mode, from negative between 1900 and 1970 CE to positive after 1970, while NAO and SCAND remain in a positive phase. The particularly noticeable rise in SST at the Algarve site by the mid-20th century (±1970), provides evidence for a regional response to the ongoing climate warming. The reported findings have implications for decadal-scale predictions of future climate change in the Iberian Peninsula.

Does an understanding of ecosystems responses to rainfall pulses improve predictions of responses of drylands to climate change?

USDA-ARS?s Scientific Manuscript database

Drylands will experience more intense and frequent droughts and floods. Ten-year field experiments manipulating the amount and variability of precipitation suggest that we cannot predict responses of drylands to climate change based on pulse experimentation. Long-term drought experiments showed no e...

Spatial and temporal variability in minimum temperature trends in the western U.S. sagebrush steppe

USDA-ARS?s Scientific Manuscript database

Climate is a major driver of ecosystem dynamics. In recent years there has been considerable interest in future climate change and potential impacts on ecosystems and management options. In this paper, we analyzed minimum monthly temperature (T min) for ten rural locations in the western sagebrush...

Holocene climates and connections between the San Francisco Bay Estuary and its watershed: A review

USGS Publications Warehouse

Malamud-Roam, F.; Dettinger, M.; Ingram, B. Lynn; Hughes, Malcolm K.; Florsheim, Joan

2007-01-01

This review of paleoclimate records reveals a gradual warming and drying in California from about 10,000 years to about 4,000 years before present. During this period, the current Bay and Delta were inundated by rising sea level so that by 4,000 years ago the Bay and Delta had taken on much of their present shape and extent. Between about 4,000 and 2,000 years ago, cooler and wetter conditions prevailed in the watershed, lowering salinity in the Estuary and altering local ecosystems. Those wetter conditions gave way to increasing aridity during the past 2,000 years, a general trend punctuated by occasional prolonged and severe droughts and occasional unusually wet, cool periods. California’s climate since A.D. 1850 has been unusually stable and benign, compared to climate variations during the previous 2,000 or more years. Thus, climate variations in California’s future may be even more (perhaps much more) challenging than those of the past 100 years. To improve our understanding of these past examples of climate variability in California, and of the linkages between watershed climate and estuarine responses, greater emphases on paleoclimate records in and around the Estuary, improved temporal resolutions in several record types, and linked watershed-estuary paleo-modeling capabilities are needed. 

Detrital events and hydroclimate variability in the Romanian Carpathians during the mid-to-late Holocene

NASA Astrophysics Data System (ADS)

Longman, Jack; Ersek, Vasile; Veres, Daniel; Salzmann, Ulrich

2017-07-01

The Romanian Carpathians are located at the confluence of three major atmospheric pressure fields: the North Atlantic, the Mediterranean and the Siberian. Despite its importance for understanding past human impact and climate change, high-resolution palaeoenvironmental reconstructions of Holocene hydroclimate variability, and in particular records of extreme precipitation events in the area, are rare. Here we present a 7500-year-long high-resolution record of past climatic change and human impact recorded in a peatbog from the Southern Carpathians, integrating palynological, geochemical and sedimentological proxies. Natural climate fluctuations appear to be dominant until 4500 years before present (yr BP), followed by increasing importance of human impact. Sedimentological and geochemical analyses document regular minerogenic deposition within the bog, linked to periods of high precipitation. Such minerogenic depositional events began 4000 yr BP, with increased depositional rates during the Medieval Warm Period (MWP), the Little Ice Age (LIA) and during periods of societal upheaval (e.g. the Roman conquest of Dacia). The timing of minerogenic events appears to indicate a teleconnection between major shifts in North Atlantic Oscillation (NAO) and hydroclimate variability in southeastern Europe, with increased minerogenic deposition correlating to low NAO index values. By linking the minerogenic deposition to precipitation variability, we state that this link persists throughout the mid-to-late Holocene.

eVolv2k: A new ice core-based volcanic forcing reconstruction for the past 2000 years

NASA Astrophysics Data System (ADS)

Toohey, Matthew; Sigl, Michael

2016-04-01

Radiative forcing resulting from stratospheric aerosols produced by major volcanic eruptions is a dominant driver of climate variability in the Earth's past. The ability of climate model simulations to accurately recreate past climate is tied directly to the accuracy of the volcanic forcing timeseries used in the simulations. We present here a new volcanic forcing reconstruction, based on newly updated ice core composites from Antarctica and Greenland. Ice core records are translated into stratospheric aerosol properties for use in climate models through the Easy Volcanic Aerosol (EVA) module, which provides an analytic representation of volcanic stratospheric aerosol forcing based on available observations and aerosol model results, prescribing the aerosol's radiative properties and primary modes of spatial and temporal variability. The evolv2k volcanic forcing dataset covers the past 2000 years, and has been provided for use in the Paleo-Modeling Intercomparison Project (PMIP), and VolMIP experiments within CMIP6. Here, we describe the construction of the eVolv2k data set, compare with prior forcing sets, and show initial simulation results.

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

Can unforced radiative variability explain the "hiatus"?

NASA Astrophysics Data System (ADS)

Donohoe, A.

2016-02-01

The paradox of the "hiatus" is characterized as a decade long period over which global mean surface temperature remained relatively constant even though greenhouse forcing forcing is believed to have been positive and increasing. Explanations of the hiatus have focused on two primary lines of thought: 1. There was a net radiative imbalance at the top of atmosphere (TOA) but this energy input was stored in the ocean without increasing surface temperature or 2. There was no radiative imbalance at the TOA because the greenhouse forcing was offset by other climate forcings. Here, we explore a third hypothesis: that there was no TOA radiative imbalance over the decade due to unforced, natural modes of radiative variability that are unrelated to global mean temperature. Is it possible that the Earth could emit enough radiation to offset greenhouse forcing without increasing its temperature due to internal modes of climate variability? Global mean TOA energy imbalance is estimated to be 0.65 W m-2 as determined from the long term change in ocean heat content - where the majority of the energy imbalance is stored. Therefore, in order to offset this TOA energy imbalance natural modes of radiative variability with amplitudes of order 0.5 W m-2 at the decadal timescale are required. We demonstrate that unforced coupled climate models have global mean radiative variability of the required magnitude (2 standard deviations of 0.57 W m-2 in the inter-model mean) and that the vast majority (>90%) of this variability is unrelated to surface temperature radiative feedbacks. However, much of this variability is at shorter (monthly and annual) timescales and does not persist from year to year making the possibility of a decade long natural interruption of the energy accumulation in the climate system unlikely due to natural radiative variability alone given the magnitude of the greenhouse forcing on Earth. Comparison to observed satellite data suggest the models capture the magnitude (2 sigma = 0.61 W m-2) and mechanisms of internal radiative variability but we cannot exclude the possibility of low frequency modes of variability with significant magnitude given the limited length of the satellite record.

Downscaling GCM Output with Genetic Programming Model

NASA Astrophysics Data System (ADS)

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

2004-05-01

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

Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012.

PubMed

Kamigaki, Taro; Chaw, Liling; Tan, Alvin G; Tamaki, Raita; Alday, Portia P; Javier, Jenaline B; Olveda, Remigio M; Oshitani, Hitoshi; Tallo, Veronica L

2016-01-01

The seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. We investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan. Wavelet analysis and the dynamic linear regression model were applied. Climate variables used in the analysis included mean temperature, relative and specific humidity, precipitation, and number of rainy days. The Akaike Information Criterion estimated in each model was used to test the improvement of fit in comparison with the baseline model. At all three study sites, annual seasonal peaks were observed in influenza A and RSV; peaks were unclear for influenza B. Ranges of climate variables at the two Philippine sites were narrower and mean variables were significantly different among the three sites. Whereas all climate variables except the number of rainy days improved model fit to the local trend model, their contributions were modest. Mean temperature and specific humidity were positively associated with influenza and RSV at the Philippine sites and negatively associated with influenza A in Okinawa. Precipitation also improved model fit for influenza and RSV at both Philippine sites, except for the influenza A model in the Eastern Visayas. Annual seasonal peaks were observed for influenza A and RSV but were less clear for influenza B at all three study sites. Including additional data from subsequent more years would help to ascertain these findings. Annual amplitude and variation in climate variables are more important than their absolute values for determining their effect on the seasonality of influenza and RSV.

Advances of NOAA Training Program in Climate Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.

2012-12-01

Since 2002, NOAA's National Weather Service (NWS) Climate Services Division (CSD) has offered numerous training opportunities to NWS staff. After eight-years of development, the training program offers three instructor-led courses and roughly 25 online (distance learning) modules covering various climate topics, such as: climate data and observations, climate variability and change, and NWS national / local climate products (tools, skill, and interpretation). Leveraging climate information and expertise available at all NOAA line offices and partners allows for the delivery of the most advanced knowledge and is a very critical aspect of the training program. The emerging NOAA Climate Service (NCS) requires a well-trained, climate-literate workforce at the local level capable of delivering NOAA's climate products and services as well as providing climate-sensitive decision support. NWS Weather Forecast Offices and River Forecast Centers presently serve as local outlets for the NCS climate services. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-sound messages and amiable communication techniques are important in developing an engaged dialog between the climate service providers and users. Several pilot projects have been conducted by the NWS CSD this past year that apply the program's training lessons and expertise to specialized external user group training. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring instructions to the potential applications for each group of users. Training technical users identified the following critical issues: (1) knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) leveraging partnership with climate services providers; and, (3) applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

Training NOAA Staff on Effective Communication Methods with Local Climate Users

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Mayes, B.

2011-12-01

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

Disentangling the response of streamflow to forest management and climate

NASA Astrophysics Data System (ADS)

Dymond, S.; Miniat, C.; Bladon, K. D.; Keppeler, E.; Caldwell, P. V.

2016-12-01

Paired watershed studies have showcased the relationships between forests, management, and streamflow. However, classical analyses of paired-watershed studies have done little to disentangle the effects of management from overarching climatic signals, potentially masking the interaction between management and climate. Such approaches may confound our understanding of how forest management impacts streamflow. Here we use a 50-year record of streamflow and climate data from the Caspar Creek Experimental Watersheds (CCEW), California, USA to separate the effects of forest management and climate on streamflow. CCEW has two treatment watersheds that have been harvested in the past 50 years. We used a nonlinear mixed model to combine the pre-treatment relationship between streamflow and climate and the post-treatment relationship via an interaction between climate and management into one equation. Our results show that precipitation and potential evapotranspiration alone can account for >95% of the variability in pre-treatment streamflow. Including management scenarios into the model explained most of the variability in streamflow (R2 > 0.98). While forest harvesting altered streamflow in both of our modeled watersheds, removing 66% of the vegetation via selection logging using a tractor yarding system over the entire watershed had a more substantial impact on streamflow than clearcutting small portions of a watershed using cable-yarding. These results suggest that forest harvesting may result in differing impacts on streamflow and highlights the need to incorporate climate into streamflow analyses of paired-watershed studies.

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2016-02-01

The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

Decadal climate variability and the spatial organization of deep hydrological drought

NASA Astrophysics Data System (ADS)

Barros, Ana P.; Hodes, Jared L.; Arulraj, Malarvizhi

2017-10-01

Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (< 6 years) space-time modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

Sensitivity of Catchment Transit Times to Rainfall Variability Under Present and Future Climates

NASA Astrophysics Data System (ADS)

Wilusz, Daniel C.; Harman, Ciaran J.; Ball, William P.

2017-12-01

Hydrologists have a relatively good understanding of how rainfall variability shapes the catchment hydrograph, a reflection of the celerity of hydraulic head propagation. Much less is known about the influence of rainfall variability on catchment transit times, a reflection of water velocities that control solute transport. This work uses catchment-scale lumped parameter models to decompose the relationship between rainfall variability and an important metric of transit times, the time-varying fraction of young water (<90 days old) in streams (FYW). A coupled rainfall-runoff model and rank StorAge Selection (rSAS) transit time model were calibrated to extensive hydrometric and environmental tracer data from neighboring headwater catchments in Plynlimon, Wales from 1999 to 2008. At both sites, the mean annual FYW increased more than 13 percentage points from the driest to the wettest year. Yearly mean rainfall explained most between-year variation, but certain signatures of rainfall pattern were also associated with higher FYW including: more clustered storms, more negatively skewed storms, and higher covariance between daily rainfall and discharge. We show that these signatures are symptomatic of an "inverse storage effect" that may be common among watersheds. Looking to the future, changes in rainfall due to projected climate change caused an up to 19 percentage point increase in simulated mean winter FYW and similarly large decreases in the mean summer FYW. Thus, climate change could seasonally alter the ages of water in streams at these sites, with concomitant impacts on water quality.

Time series of Essential Climate Variables from Satellite Data

NASA Astrophysics Data System (ADS)

Werscheck, M.

2010-09-01

Climate change is a fact. We need to know how the climate system will develop in future and how this will affect workaday life. To do this we need climate models for prediction of the future on all time scales, and models to assess the impact of the prediction results to the various sectors of social and economic life. With this knowledge we can take measures to mitigate the causes and adapt to changes. Prerequisite for this is a careful and thorough monitoring of the climate systems. Satellite data are an increasing & valuable source of information to observe the climate system. For many decades now satellite data are available to derive information about our planet earth. EUMETSAT is the European Organisation in charge of the exploitation of satellite data for meteorology and (since the year 2000) climatology. Within the EUMETSAT Satellite Application Facility (SAF) Network, comprising 8 initiatives to derive geophysical parameters from satellite, the Satellite Application Facility on Climate Monitoring (CM SAF) is especially dedicated to provide climate relevant information from satellite data. Many products as e.g. water vapour, radiation at surface and top of atmosphere, cloud properties are available, some of these for more then 2 decades. Just recently the European Space Agency (ESA) launched the Climate Change Initiative (CCI) to derive Essential Climate Variables (ECVs) from satellite data, including e.g. cloud properties, aerosol, ozone, sea surface temperature etc.. The presentation will give an overview on some relevant European activities to derive Essential Climate Variables from satellite data and the links to Global Climate Observing System (GCOS), the Global Satellite Intercalibration System (GSICS) as well as the Sustained Co-ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE CM).

Fine scale climatic and soil variability effects on plant species cover along the Front Range of Colorado, USA

NASA Astrophysics Data System (ADS)

Cumming, William Frank Preston

Fine scale studies are rarely performed to address landscape level responses to microclimatic variability. Is it the timing, distribution, and magnitude of soil temperature and moisture that affects what species emerge each season and, in turn, their resilience to fluctuations in microclimate. For this dissertation research, I evaluated the response of vegetation change to microclimatic variability within two communities over a three year period (2009-2012) utilizing 25 meter transects at two locations along the Front Range of Colorado near Boulder, CO and Golden, CO respectively. To assess microclimatic variability, spatial and temporal autocorrelation analyses were performed with soil temperature and moisture. Species cover was assessed along several line transects and correlated with microclimatic variability. Spatial and temporal autocorrelograms are useful tools in identifying the degree of dependency of soil temperature and moisture on the distance and time between pairs of measurements. With this analysis I found that a meter spatial resolution and two-hour measurements are sufficient to capture the fine scale variability in soil properties throughout the year. By comparing this to in situ measurements of soil properties and species percent cover I found that there are several plant functional types and/or species origin in particular that are more sensitive to variations in temperature and moisture than others. When all seasons, locations, correlations, and regional climate are looked at, it is the month of March that stands out in terms of significance. Additionally, of all of the vegetation types represented at these two sites C4, C3, native, non-native, and forb species seem to be the most sensitive to fluctuations in soil temperature, moisture, and regional climate in the spring season. The steady decline in percent species cover the study period and subsequent decrease in percent species cover and size at both locations may indicate that certain are unable to respond to continually higher temperatures and lower moisture availability that is inevitable with future climatic variability.

Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

NASA Astrophysics Data System (ADS)

Jaeger, K. L.

2017-12-01

The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the landscape that may be resilient or sensitive to drought conditions, allowing for targeted management efforts to protect critical reaches.

Regional regression equations for estimation of natural streamflow statistics in Colorado

USGS Publications Warehouse

Capesius, Joseph P.; Stephens, Verlin C.

2009-01-01

The U.S. Geological Survey (USGS), in cooperation with the Colorado Water Conservation Board and the Colorado Department of Transportation, developed regional regression equations for estimation of various streamflow statistics that are representative of natural streamflow conditions at ungaged sites in Colorado. The equations define the statistical relations between streamflow statistics (response variables) and basin and climatic characteristics (predictor variables). The equations were developed using generalized least-squares and weighted least-squares multilinear regression reliant on logarithmic variable transformation. Streamflow statistics were derived from at least 10 years of streamflow data through about 2007 from selected USGS streamflow-gaging stations in the study area that are representative of natural-flow conditions. Basin and climatic characteristics used for equation development are drainage area, mean watershed elevation, mean watershed slope, percentage of drainage area above 7,500 feet of elevation, mean annual precipitation, and 6-hour, 100-year precipitation. For each of five hydrologic regions in Colorado, peak-streamflow equations that are based on peak-streamflow data from selected stations are presented for the 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year instantaneous-peak streamflows. For four of the five hydrologic regions, equations based on daily-mean streamflow data from selected stations are presented for 7-day minimum 2-, 10-, and 50-year streamflows and for 7-day maximum 2-, 10-, and 50-year streamflows. Other equations presented for the same four hydrologic regions include those for estimation of annual- and monthly-mean streamflow and streamflow-duration statistics for exceedances of 10, 25, 50, 75, and 90 percent. All equations are reported along with salient diagnostic statistics, ranges of basin and climatic characteristics on which each equation is based, and commentary of potential bias, which is not otherwise removed by log-transformation of the variables of the equations from interpretation of residual plots. The predictor-variable ranges can be used to assess equation applicability for ungaged sites in Colorado.

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.

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

USGS Publications Warehouse

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

2011-01-01

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

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.

The ARGO Project: Global Ocean Observations for Understanding and Prediction of Climate Variability. Report for Calendar Year 2004

DTIC Science & Technology

2004-01-01

international Argo practices. Data appropriate for research applications and for comparison with climate change models are not available for several...global ocean heat and fresh water storage and the detection and attribution of climate change . These presentations can be accessed at http...stresses on ocean ecosystems have serious consequences, and sometimes dramatic ones, such as coral reef bleaching . In the future, the impacts of a

Cross-biome transplants of plant litter show decomposition models extend to a broader climatic range but lose predictability at the decadal time scale

Treesearch

William S. Currie; Mark E. Harmon; Ingrid C. Burke; Stephen C. Hart; William J. Parton; Whendee L. Silver

2009-01-01

We analyzed results from 10-year long field incubations of foliar and fine root litter from the Long-term lntersite Decomposition Experiment Team (LIDET) study. We tested whether a variety of climate and litter quality variables could be used to develop regression models of decomposition parameters across wide ranges in litter quality and climate and whether these...

Dynamical adjustment of Scandinavian glacier mass-balance time series

NASA Astrophysics Data System (ADS)

Bonan, D.; Christian, J. E.; Christianson, K. A.

2017-12-01

Glacier mass wastage is often cited as one of the most visible manifestations of anthropogenic climate change. Annual glacier mass-balance is related to local climate and atmospheric circulation, as it is defined as the yearly sum of accumulation and ablation—processes that are strongly influenced by year-to-year fluctuations in precipitation and temperature. Glacier response to a climatic trend can, however, be masked by internal variability in atmospheric circulation, and by non-climatic factors (such as topographic control, wind deposition, and incident solar radiation). Thus, unambiguous attribution of a negative glacier mass-balance trend to anthropogenic forcing remains challenging. Maritime glacier mass-balance records may be especially difficult to interpret due to the high winter balances from decadal-scale climate oscillations and the relatively short time series. Here we examine the influence of climate and atmospheric circulation variability on 14 Norwegian glaciers that span 20° of latitude, from southern Norway to Svalbard. We use dynamical adjustment—a statistical method based on partial least squares regression—to identify the components of variability within the mass-balance records that are associated with the time-varying sea level pressure (SLP) and sea surface temperature (SST) fields. We find that 30-50% of the variance in the winter mass-balance records of the glaciers in southern Norway is explained by using sea level pressure as a predictor. The leading SLP predictor pattern mimics the spatial signature of the North Atlantic Oscillation (NAO), indicating that winter balance is strongly influenced by the NAO. Moreover, the adjusted mass-balance records indicate a geographic trend: the southern Norwegian glaciers have significant negative trends in the summer balance that remain negative after adjustment, while the more northern glaciers have negative winter balance trends that only become significant after adjustment. We look into anthropogenic warming to explain the trends after dynamical adjustment.

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.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

Climatically induced interannual variability in aboveground production in forest-tundra and northern taiga of central Siberia.

PubMed

Knorre, Anastasia A; Kirdyanov, Alexander V; Vaganov, Eugene A

2006-02-01

To investigate the variability of primary production of boreal forest ecosystems under the current climatic changes, we compared the dynamics of annual increments and productivity of the main components of plant community (trees, shrubs, mosses) at three sites in the north of Siberia (Russia). Annual radial growth of trees and shrubs was mostly defined by summer temperature regime (positive correlation), but climatic response of woody plants was species specific and depends on local conditions. Dynamics of annual increments of mosses were opposite to tree growth. The difference in climatic response of the different vegetation components of the forest ecosystems indicates that these components seem to be adapted to use climatic conditions during the short and severe northern summer, and decreasing in annual production of one component is usually combined with the increase of other component productivity. Average productivity in the northern forest ecosystems varies from 0.05 to 0.14 t ha(-1) year(-1) for trees, from 0.05 to 0.18 t ha(-1) year(-1) for shrubs and from 0.54 to 0.66 t ha(-1) year(-1) for mosses. Higher values of tree productivity combined with lower annual moss productivity were found in sites in northern taiga in comparison with forest-tundra. Different tendencies in the productivity of the dominant species from each vegetation level (trees, shrubs, mosses) were indicated for the last 10 years studied (1990-1999): while productivity of mosses is increasing, productivity of trees is decreasing, but there is no obvious trend in the productivity of shrubs. Our results show that in the long term, the main contribution to changes in annual biomass productivity in forest-tundra and northern taiga ecosystems under the predicted climatic changes will be determined by living ground cover.

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.

Climatic effects on breeding grounds are more important drivers of breeding phenology in migrant birds than carry-over effects from wintering grounds.

PubMed

Ockendon, Nancy; Leech, Dave; Pearce-Higgins, James W

2013-01-01

Long-distance migrants may be particularly vulnerable to climate change on both wintering and breeding grounds. However, the relative importance of climatic variables at different stages of the annual cycle is poorly understood, even in well-studied Palaearctic migrant species. Using a national dataset spanning 46 years, we investigate the impact of wintering ground precipitation and breeding ground temperature on breeding phenology and clutch size of 19 UK migrants. Although both spring temperature and arid zone precipitation were significantly correlated with laying date, the former accounted for 3.5 times more inter-annual variation. Neither climate variable strongly affected clutch size. Thus, although carry-over effects had some impact, they were weaker drivers of reproductive traits than conditions on the breeding grounds.

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

NASA Technical Reports Server (NTRS)

Barsugli, Joseph J.; Guentchev, Galina; Horton, Radley M.; Wood, Andrew; Mearns, Lindo O.; Liang, Xin-Zhong; Winkler, Julia A.; Dixon, Keith; Hayhoe, Katharine; Rood, Richard B.;

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.

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

NASA Astrophysics Data System (ADS)

Xu, M.; Hoffman, F. M.

2016-12-01

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

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

USGS Publications Warehouse

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

2008-01-01

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

Climatic and socio-economic fire drivers in the Mediterranean basin at a century scale: Analysis and modelling based on historical fire statistics and dynamic global vegetation models (DGVMs)

NASA Astrophysics Data System (ADS)

Mouillot, F.; Koutsias, N.; Conedera, M.; Pezzatti, B.; Madoui, A.; Belhadj Kheder, C.

2017-12-01

Wildfire is the main disturbance affecting Mediterranean ecosystems, with implications on biogeochemical cycles, biosphere/atmosphere interactions, air quality, biodiversity, and socio-ecosystems sustainability. The fire/climate relationship is time-scale dependent and may additionally vary according to concurrent changes climatic, environmental (e.g. land use), and fire management processes (e.g. fire prevention and control strategies). To date, however, most studies focus on a decadal scale only, being fire statistics ore remote sensing data usually available for a few decades only. Long-term fire data may allow for a better caption of the slow-varying human and climate constrains and for testing the consistency of the fire/climate relationship on the mid-time to better apprehend global change effects on fire risks. Dynamic Global Vegetation Models (DGVMs) associated with process-based fire models have been recently developed to capture both the direct role of climate on fire hazard and the indirect role of changes in vegetation and human population, to simulate biosphere/atmosphere interactions including fire emissions. Their ability to accurately reproduce observed fire patterns is still under investigation regarding seasonality, extreme events or temporal trend to identify potential misrepresentations of processes. We used a unique long-term fire reconstruction (from 1880 to 2016) of yearly burned area along a North/South and East/West environmental gradient across the Mediterranean Basin (southern Switzerland, Greece, Algeria, Tunisia) to capture the climatic and socio economic drivers of extreme fire years by linking yearly burned area with selected climate indices derived from historical climate databases and socio-economic variables. We additionally compared the actual historical reconstructed fire history with the yearly burned area simulated by a panel of DGVMS (FIREMIP initiative) driven by daily CRU climate data at 0.5° resolution across the Mediterranean basin. We will present and discuss the key processes driving interannual fire hazard along the 20th century, and analysed how DGVMs capture this interannual variability.

Using CHIRPS Rainfall Dataset to detect rainfall trends in West Africa

NASA Astrophysics Data System (ADS)

Blakeley, S. L.; Husak, G. J.

2016-12-01

In West Africa, agriculture is often rain-fed, subjecting agricultural productivity and food availability to climate variability. Agricultural conditions will change as warming temperatures increase evaporative demand, and with a growing population dependent on the food supply, farmers will become more reliant on improved adaptation strategies. Development of such adaptation strategies will need to consider West African rainfall trends to remain relevant in a changing climate. Here, using the CHIRPS rainfall product (provided by the Climate Hazards Group at UC Santa Barbara), I examine trends in West African rainfall variability. My analysis will focus on seasonal rainfall totals, the structure of the rainy season, and the distribution of rainfall. I then use farmer-identified drought years to take an in-depth analysis of intra-seasonal rainfall irregularities. I will also examine other datasets such as potential evapotranspiration (PET) data, other remotely sensed rainfall data, rain gauge data in specific locations, and remotely sensed vegetation data. Farmer bad year data will also be used to isolate "bad" year markers in these additional datasets to provide benchmarks for identification in the future of problematic rainy seasons.

Current temporal trends in moth abundance are counter to predicted effects of climate change in an assemblage of subarctic forest moths.

PubMed

Hunter, Mark D; Kozlov, Mikhail V; Itämies, Juhani; Pulliainen, Erkki; Bäck, Jaana; Kyrö, Ella-Maria; Niemelä, Pekka

2014-06-01

Changes in climate are influencing the distribution and abundance of the world's biota, with significant consequences for biological diversity and ecosystem processes. Recent work has raised concern that populations of moths and butterflies (Lepidoptera) may be particularly susceptible to population declines under environmental change. Moreover, effects of climate change may be especially pronounced in high latitude ecosystems. Here, we examine population dynamics in an assemblage of subarctic forest moths in Finnish Lapland to assess current trajectories of population change. Moth counts were made continuously over a period of 32 years using light traps. From 456 species recorded, 80 were sufficiently abundant for detailed analyses of their population dynamics. Climate records indicated rapid increases in temperature and winter precipitation at our study site during the sampling period. However, 90% of moth populations were stable (57%) or increasing (33%) over the same period of study. Nonetheless, current population trends do not appear to reflect positive responses to climate change. Rather, time-series models illustrated that the per capita rates of change of moth species were more frequently associated negatively than positively with climate change variables, even as their populations were increasing. For example, the per capita rates of change of 35% of microlepidoptera were associated negatively with climate change variables. Moth life-history traits were not generally strong predictors of current population change or associations with climate change variables. However, 60% of moth species that fed as larvae on resources other than living vascular plants (e.g. litter, lichen, mosses) were associated negatively with climate change variables in time-series models, suggesting that such species may be particularly vulnerable to climate change. Overall, populations of subarctic forest moths in Finland are performing better than expected, and their populations appear buffered at present from potential deleterious effects of climate change by other ecological forces. © 2014 John Wiley & Sons Ltd.

Revealing The Impact Of Climate Variability On The Wind Resource Using Data Mining Techniques

NASA Astrophysics Data System (ADS)

Clifton, A.; Lundquist, J. K.

2011-12-01

Wind turbines harvest energy from the wind. Winds at heights where industrial-scale turbines operate, up to 200 m above ground, experience a complex interaction between the atmosphere and the Earth's surface. Previous studies for a variety of locations have shown that the wind resource varies over time. In some locations, this variability can be related to large-scale climate oscillations as revealed in climate indices such as the El-Nino-Southern Oscillation (ENSO). These indices can be used to quantify climate change in the past, and can also be extracted from models of future climate. Understanding the correlation between climate indices and wind resources therefore allows us to understand how climate change may influence wind energy production. We present a new methodology for assessing relevant climate modes of oscillation at a given site in order to quantify future wind resource variability. We demonstrate the method on a 14-year record of 10-minute averaged wind speed and wind direction data from several levels of an 80m tower at the National Renewable Energy Laboratory (NREL) National Wind Technology Center near Boulder, Colorado. Data mining techniques (based on k-means clustering) identify 4 major groups of wind speed and direction. After removing annual means, each cluster was compared to a series of climate indices, including the Arctic Oscillation (AO) and Multivariate ENSO Index (MEI). Statistically significant relationships emerge between individual clusters and climate indices. At this location, this result is consistent with the MEI's relationship with other meteorological parameters, such as precipitation, in the Rocky Mountain Region. The presentation will illustrate these relationships between wind resource at this location and other relevant climate indices, and suggest how these relationships can provide a foundation for quantifying the potential future variability of wind energy production at this site and others.

Vegetation change, malnutrition and violence in the Horn of Africa

NASA Astrophysics Data System (ADS)

Rowhani, P.; Degomme, O.; Linderman, M.; Guha-Sapir, D.; Lambin, E.

2008-12-01

In certain circumstances, climate change in association with a broad range of social factors may increase the risk of famines and subsequently, violent conflict. The impacts of climate change on society will be experienced both through changes in mean conditions over long time periods and through increases in extreme events. Recent studies have shown the historical effects of long term climate change on societies and the importance of short term climatic triggers on armed conflict. However, most of these studies are at the state level ignoring local conditions. Here we use detailed information extracted from wide-swath satellite data (MODIS) to analyze the impact of climate variability change on malnutrition and violent conflict. More specifically, we perform multivariate logistic regression analysis in order to explain the geographical distribution of malnutrition and conflict in the Horn of Africa on a sub-national level. This region, constituted by several unstable and poor states, has been affected by droughts, floods, famines, and violence in the past few years. Three commonly used nutrition and mortality indicators are used to characterize the health situation (CE-DAT database). To map violence we use the georeferenced Armed Conflicts dataset developed by the Center for the Study of Civil War. Explanatory variables include several socio-economic variables and environmental variables characterizing land degradation, vegetation activity, and interannual variability in land-surface conditions. First results show that interannual variability in land-surface conditions is associated with malnutrition but not with armed conflict. Furthermore, land degradation seems not to be associated with either malnutrition or armed conflict.

Precision diet formulation to improve performance and profitability across various climates: Modeling the implications of increasing the formulation frequency of dairy cattle diets.

PubMed

White, Robin R; Capper, Judith L

2014-03-01

The objective of this study was to use a precision nutrition model to simulate the relationship between diet formulation frequency and dairy cattle performance across various climates. Agricultural Modeling and Training Systems (AMTS) CattlePro diet-balancing software (Cornell Research Foundation, Ithaca, NY) was used to compare 3 diet formulation frequencies (weekly, monthly, or seasonal) and 3 levels of climate variability (hot, cold, or variable). Predicted daily milk yield (MY), metabolizable energy (ME) balance, and dry matter intake (DMI) were recorded for each frequency-variability combination. Economic analysis was conducted to calculate the predicted revenue over feed and labor costs. Diet formulation frequency affected ME balance and MY but did not affect DMI. Climate variability affected ME balance and DMI but not MY. The interaction between climate variability and formulation frequency did not affect ME balance, MY, or DMI. Formulating diets more frequently increased MY, DMI, and ME balance. Economic analysis showed that formulating diets weekly rather than seasonally could improve returns over variable costs by $25,000 per year for a moderate-sized (300-cow) operation. To achieve this increase in returns, an entire feeding system margin of error of <1% was required. Formulating monthly, rather than seasonally, may be a more feasible alternative as this requires a margin of error of only 2.5% for the entire feeding system. Feeding systems with a low margin of error must be developed to better take advantage of the benefits of precision nutrition. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ocean angular momentum signals in a climate model and implications for Earth rotation

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Rajamony, J.; Gregory, J. M.

2002-03-01

Estimates of ocean angular momentum (OAM) provide an integrated measure of variability in ocean circulation and mass fields and can be directly related to observed changes in Earth rotation. We use output from a climate model to calculate 240 years of 3-monthly OAM values (two equatorial terms L1 and L2, related to polar motion or wobble, and axial term L3, related to length of day variations) representing the period 1860-2100. Control and forced runs permit the study of the effects of natural and anthropogenically forced climate variability on OAM. All OAM components exhibit a clear annual cycle, with large decadal modulations in amplitude, and also longer period fluctuations, all associated with natural climate variability in the model. Anthropogenically induced signals, inferred from the differences between forced and control runs, include an upward trend in L3, related to inhomogeneous ocean warming and increases in the transport of the Antarctic Circumpolar Current, and a significantly weaker seasonal cycle in L2 in the second half of the record, related primarily to changes in seasonal bottom pressure variability in the Southern Ocean and North Pacific. Variability in mass fields is in general more important to OAM signals than changes in circulation at the seasonal and longer periods analyzed. Relation of OAM signals to changes in surface atmospheric forcing are discussed. The important role of the oceans as an excitation source for the annual, Chandler and Markowitz wobbles, is confirmed. Natural climate variability in OAM and related excitation is likely to measurably affect the Earth rotation, but anthropogenically induced effects are comparatively weak.

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

Toward a Unified Representation of Atmospheric Convection in Variable-Resolution Climate Models

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

Walko, Robert

2016-11-07

The purpose of this project was to improve the representation of convection in atmospheric weather and climate models that employ computational grids with spatially-variable resolution. Specifically, our work targeted models whose grids are fine enough over selected regions that convection is resolved explicitly, while over other regions the grid is coarser and convection is represented as a subgrid-scale process. The working criterion for a successful scheme for representing convection over this range of grid resolution was that identical convective environments must produce very similar convective responses (i.e., the same precipitation amount, rate, and timing, and the same modification of themore » atmospheric profile) regardless of grid scale. The need for such a convective scheme has increased in recent years as more global weather and climate models have adopted variable resolution meshes that are often extended into the range of resolving convection in selected locations.« less

Evaluating the ClimEx Single Model large ensemble in comparison with EURO-CORDEX results of heatwave and drought indicators

NASA Astrophysics Data System (ADS)

von Trentini, F.; Schmid, F. J.; Braun, M.; Frigon, A.; Leduc, M.; Martel, J. L.; Willkofer, F.; Wood, R. R.; Ludwig, R.

2017-12-01

Meteorological extreme events seem to become more frequent in the present and future, and a seperation of natural climate variability and a clear climate change effect on these extreme events gains more and more interest. Since there is only one realisation of historical events, natural variability in terms of very long timeseries for a robust statistical analysis is not possible with observation data. A new single model large ensemble (SMLE), developed for the ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) is supposed to overcome this lack of data by downscaling 50 members of the CanESM2 (RCP 8.5) with the Canadian CRCM5 regional model (using the EURO-CORDEX grid specifications) for timeseries of 1950-2099 each, resulting in 7500 years of simulated climate. This allows for a better probabilistic analysis of rare and extreme events than any preceding dataset. Besides seasonal sums, several indicators concerning heatwave frequency, duration and mean temperature a well as number and maximum length of dry periods (cons. days <1mm) are calculated for the ClimEx ensemble and several EURO-CORDEX runs. This enables us to investigate the interaction between natural variability (as it appears in the CanESM2-CRCM5 members) and a climate change signal of those members for past, present and future conditions. Adding the EURO-CORDEX results to this, we can also assess the role of internal model variability (or natural variability) in climate change simulations. A first comparison shows similar magnitudes of variability of climate change signals between the ClimEx large ensemble and the CORDEX runs for some indicators, while for most indicators the spread of the SMLE is smaller than the spread of different CORDEX models.

Compounding nonlinearities in the climate and wildfire system contribute to high uncertainty in estimates of future burned area in the western United State

NASA Astrophysics Data System (ADS)

Williams, P.

2015-12-01

Ecological studies are increasingly recognizing the importance of atmospheric vapor-pressure deficit (VPD) as a driver of forest drought stress and disturbance processes such as wildfire. Because of the nonlinear Clausius-Clapeyron relationship between temperature and saturation vapor pressure, small variations in temperature can have large impacts on VPD, and therefore drought, particularly in warm, dry areas and particularly during the warm season. It is also clear that VPD and drought affect forest fire nonlinearly, as incremental drying leads to increasingly large burned areas. Forest fire is also affected by fuel amount and connectivity, which are promoted by vegetation growth in previous years, which is in turn promoted by lack of drought, highlighting the importance of nuances in the sequencing of natural interannual climate variations in modulating the impacts of drought on wildfire. The many factors affecting forest fire, and the nonlinearities embedded within the climate and wildfire systems, cause interannual variability in forest-fire area and frequency to be wildly variable and strongly affected by internal climate variability. In addition, warming over the past century has produced a background increase in forest fire frequency and area in many regions. In this talk I focus on the western United States and will explore whether the relationships between internal climate variability on forest fire area have been amplified by the effects of warming as a result of the compounding nonlinearities described above. I will then explore what this means for future burned area in the western United States and make the case that uncertainties in the future global greenhouse gas emissions trajectory, model projections of mean temperatures, model projections of precipitation, and model projections of natural climate variability translate to very large uncertainties in the effects of future climate variability on forest fire area in the United States and globally.

Seasonal and inter-annual variability of the net ecosystem CO2 exchange of a temperate mountain grassland: effects of climate and management.

PubMed

Wohlfahrt, Georg; Hammerle, Albin; Haslwanter, Alois; Bahn, Michael; Tappeiner, Ulrike; Cernusca, Alexander

2008-04-27

The role and relative importance of climate and cutting for the seasonal and inter-annual variability of the net ecosystem CO 2 (NEE) of a temperate mountain grassland was investigated. Eddy covariance CO 2 flux data and associated measurements of the green area index and the major environmental driving forces acquired during 2001-2006 at the study site Neustift (Austria) were analyzed. Driven by three cutting events per year which kept the investigated grassland in a stage of vigorous growth, the seasonal variability of NEE was primarily modulated by gross primary productivity (GPP). The role of environmental parameters in modulating the seasonal variability of NEE was obscured by the strong response of GPP to changes in the amount of green area, as well as the cutting-mediated decoupling of phenological development and the seasonal course of climate drivers. None of the climate and management metrics examined was able to explain the inter-annual variability of annual NEE. This is thought to result from (1) a high covariance between GPP and ecosystem respiration (R eco ) at the annual time scale which results in a comparatively small inter-annual variation of NEE, (2) compensating effects between carbon exchange during and outside the management period, and (3) changes in the biotic response to rather than the climate variables per se. GPP was more important in modulating inter-annual variations in NEE in spring and before the first and second cut, while R eco explained a larger fraction of the inter-annual variability of NEE during the remaining, in particular the post-cut, periods.

Potential impacts of climate variability on dengue hemorrhagic fever in Honduras, 2010.

PubMed

Zambrano, L I; Sevilla, C; Reyes-García, S Z; Sierra, M; Kafati, R; Rodriguez-Morales, A J; Mattar, S

2012-12-01

Climate change and variability are affecting human health and disease direct or indirectly through many mechanisms. Dengue is one of those diseases that is strongly influenced by climate variability; however its study in Central America has been poorly approached. In this study, we assessed potential associations between macroclimatic and microclimatic variation and dengue hemorrhagic fever (DHF) cases in the main hospital of Honduras during 2010. In this year, 3,353 cases of DHF were reported in the Hospital Escuela, Tegucigalpa. Climatic periods marked a difference of 158% in the mean incidence of cases, from El Niño weeks (-99% of cases below the mean incidence) to La Niña months (+59% of cases above it) (p<0.01). Linear regression showed significantly higher dengue incidence with lower values of Oceanic Niño Index (p=0.0097), higher rain probability (p=0.0149), accumulated rain (p=0.0443) and higher relative humidity (p=0.0292). At a multiple linear regression model using those variables, ONI values shown to be the most important and significant factor found to be associated with the monthly occurrence of DHF cases (r²=0.649; βstandardized=-0.836; p=0.01). As has been shown herein, climate variability is an important element influencing the dengue epidemiology in Honduras. However, it is necessary to extend these studies in this and other countries in the Central America region, because these models can be applied for surveillance as well as for prediction of dengue.

The Modulated Annual Cycle: An Alternative Reference Frame for Climate Anomalies

NASA Astrophysics Data System (ADS)

Wu, Z.

2007-12-01

In climate science, an anomaly is the deviation of a quantity from its annual cycle (AC). There are many ways to define annual cycle. Traditionally, the annual cycle is taken to be an exact repetition of itself year after year. This stationary annual cycle may not reflect well the intrinsic nonlinearity of the climate system, especially under external forcing. In this study, we have reexamined the reference frame for anomalies by reexamining the annual cycle. We propose an alternative reference frame, the modulated annual cycle (MAC) that allows the annual cycle to change from year to year, for defining anomalies. In order for this alternative reference frame to be useful, we need to be able to define the instantaneous annual cycle. We therefore also introduce a new method to extract the MAC from climatic data. In the presence of an MAC, modulated in both amplitude and frequency, we can then define an alternative version of an anomaly, this time with respect to the instantaneous MAC rather than a permanent and unchanging AC. Based on this alternative definition of anomalies, we reexamine some familiar physical processes: in particular, the sea surface temperature (SST) reemergence and the ENSO phase locking to the annual cycle. We find that the re-emergence mechanism may be alternatively interpreted as an explanation of the change of the annual cycle instead of the interannual to interdecadal persistence of SST anomalies. We also find that the ENSO phase locking can largely be attributed to the residual annual cycle (the difference of the MAC and the corresponding traditional annual cycle) contained in the traditional anomaly, and, therefore, can be alternatively interpreted as a part of the annual cycle phase locked to the annual cycle itself. Two additional examples are also presented of the implications of using a MAC against which to define anomalies. We show that using MAC as a reference framework for anomaly can bypass the difficulty brought by concepts such as "decadal variability of summer (or winter) climate" for understanding the low-frequency variability of the climate system. We also point out the drawbacks related to the stationary assumption in previous studies of extreme weather and climate and propose instead the appropriateness of choosing a non-stationary framework to study extreme weather and climate events. The concept of an amplitude and frequency modulated annual cycle, a method to extract it, and its implications for the interpretation of physical processes, all may contribute potentially to a more consistent and fruitful way of examining past and future climate variability and change.

Projections of Future Summer Weather in Seoul and Their Impacts on Urban Agriculture

NASA Astrophysics Data System (ADS)

Kim, S. O.; Kim, J. H.; Yun, J. I.

2015-12-01

Climate departure from the past variability was projected to start in 2042 for Seoul. In order to understand the implication of climate departure in Seoul for urban agriculture, we evaluated the daily temperature for the June-September period from 2041 to 2070, which were projected by the RCP8.5 climate scenario. These data were analyzed with respect to climate extremes and their effects on growth of hot pepper (Capsicum annuum), one of the major crops in urban farming. The mean daily maximum and minimum temperatures in 2041-2070 approached to the 90th percentile in the past 30 years (1951- 1980). However, the frequency of extreme events such as heat waves and tropical nights appeared to exceed the past variability. While the departure of mean temperature might begin in or after 2040, the climate departure in the sense of extreme weather events seems already in progress. When the climate scenario data were applied to the growth and development of hot pepper, the departures of both planting date and harvest date are expected to follow those of temperature. However, the maximum duration for hot pepper cultivation, which is the number of days between the first planting and the last harvest, seems to have already deviated from the past variability.

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

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

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

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

PubMed

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

2016-12-28

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

Rainfall variability and drought characteristics in two agro-climatic zones: An assessment of climate change challenges in Africa.

PubMed

Ayanlade, Ayansina; Radeny, Maren; Morton, John F; Muchaba, Tabitha

2018-07-15

This paper examines drought characteristics as an evidence of climate change in two agro-climatic zones of Nigeria and farmers' climate change perceptions of impacts and adaptation strategies. The results show high spatial and temporal rainfall variability for the stations. Consequently, there are several anomalies in rainfall in recent years but much more in the locations around the Guinea savanna. The inter-station and seasonality statistics reveal less variable and wetter early growing seasons and late growing seasons in the Rainforest zone, and more variable and drier growing seasons in other stations. The probability (p) of dry spells exceeding 3, 5 and 10 consecutive days is very high with 0.62≤p≥0.8 in all the stations, though, the p-values for 10day spells drop below 0.6 in Ibadan and Osogbo. The results further show that rainfall is much more reliable from the month of May until July with the coefficient of variance for rainy days <0.30, but less reliable in the months of March, August and October (CV-RD>0.30), though CV-RD appears higher in the month of August for all the stations. It is apparent that farmers' perceptions of drought fundamentally mirror climatic patterns from historical weather data. The study concludes that the adaptation facilities and equipment, hybrids of crops and animals are to be provided to farmers, at a subsidized price by the government, for them to cope with the current condition of climate change. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Motew, M.; Kucharik, C. J.

2011-12-01

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

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Emergent constraint on equilibrium climate sensitivity from global temperature variability.

PubMed

Cox, Peter M; Huntingford, Chris; Williamson, Mark S

2018-01-17

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO 2 ) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO 2 . Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the 'likely' range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC 'likely' range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Using an improved understanding of current climate variability to develop increased drought resilience in UK irrigated agriculture

NASA Astrophysics Data System (ADS)

Holman, I.; Rey Vicario, D.

2016-12-01

Improving community preparedness for climate change can be supported by developing resilience to past events, focused on those changes of particular relevance (such as floods and droughts). However, communities' perceptions of impacts and risk can be influenced by an incomplete appreciation of historical baseline climate variability. This can arise from a number of factors including individual's age, access to long term data records and availability of local knowledge. For example, the most significant recent drought in the UK occurred in 1976/77 but does it represent the worst drought that did occur (or could have occurred) without climate change? We focus on the east of England where most irrigated agriculture is located and where many local farmers interviewed were either not in business then or have an incomplete memory of the impacts of the drought. This paper describes a comparison of an annual agroclimatic indicator closely linked to irrigation demand (maximum Potential Soil Moisture Deficit) calculated from three sources of long term observational and simulated historical weather data with recent data. These long term datasets include gridded measured / calculated datasets of precipitation and reference evapotranspiration; a dynamically downscaled 20th Century Re-analysis dataset, and two Regional Climate Model ensemble datasets (FutureFlows and the MaRIUS event set) which each provide between 110 and 3000 years of baseline weather. The comparison shows that the long term datasets provide a wider characterisation of current climate variability and affect the perception of current drought frequency and severity. The paper will show that using a more comprehensive understanding of current climate variability and drought risk as a basis for adapting irrigated systems to droughts can provide substantial increased resilience to (uncertain) climate change.

Emergent constraint on equilibrium climate sensitivity from global temperature variability

NASA Astrophysics Data System (ADS)

Cox, Peter M.; Huntingford, Chris; Williamson, Mark S.

2018-01-01

Equilibrium climate sensitivity (ECS) remains one of the most important unknowns in climate change science. ECS is defined as the global mean warming that would occur if the atmospheric carbon dioxide (CO2) concentration were instantly doubled and the climate were then brought to equilibrium with that new level of CO2. Despite its rather idealized definition, ECS has continuing relevance for international climate change agreements, which are often framed in terms of stabilization of global warming relative to the pre-industrial climate. However, the ‘likely’ range of ECS as stated by the Intergovernmental Panel on Climate Change (IPCC) has remained at 1.5-4.5 degrees Celsius for more than 25 years. The possibility of a value of ECS towards the upper end of this range reduces the feasibility of avoiding 2 degrees Celsius of global warming, as required by the Paris Agreement. Here we present a new emergent constraint on ECS that yields a central estimate of 2.8 degrees Celsius with 66 per cent confidence limits (equivalent to the IPCC ‘likely’ range) of 2.2-3.4 degrees Celsius. Our approach is to focus on the variability of temperature about long-term historical warming, rather than on the warming trend itself. We use an ensemble of climate models to define an emergent relationship between ECS and a theoretically informed metric of global temperature variability. This metric of variability can also be calculated from observational records of global warming, which enables tighter constraints to be placed on ECS, reducing the probability of ECS being less than 1.5 degrees Celsius to less than 3 per cent, and the probability of ECS exceeding 4.5 degrees Celsius to less than 1 per cent.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Assessing the Effects of Climate Variability on Orange Yield in Florida to Reduce Production Forecast Errors

NASA Astrophysics Data System (ADS)

Concha Larrauri, P.

2015-12-01

Orange production in Florida has experienced a decline over the past decade. Hurricanes in 2004 and 2005 greatly affected production, almost to the same degree as strong freezes that occurred in the 1980's. The spread of the citrus greening disease after the hurricanes has also contributed to a reduction in orange production in Florida. The occurrence of hurricanes and diseases cannot easily be predicted but the additional effects of climate on orange yield can be studied and incorporated into existing production forecasts that are based on physical surveys, such as the October Citrus forecast issued every year by the USDA. Specific climate variables ocurring before and after the October forecast is issued can have impacts on flowering, orange drop rates, growth, and maturation, and can contribute to the forecast error. Here we present a methodology to incorporate local climate variables to predict the USDA's orange production forecast error, and we study the local effects of climate on yield in different counties in Florida. This information can aid farmers to gain an insight on what is to be expected during the orange production cycle, and can help supply chain managers to better plan their strategy.

300 Years of East African Climate Variability from Oxygen Isotopes in a Kenya Coral

NASA Astrophysics Data System (ADS)

Dunbar, R.

2003-04-01

Instrumental records of climate variability from the western Indian Ocean are relatively scarce and short. Here I present a monthly resolution stable isotopic record acquired from a large living coral head (Porites) from the Malindi Marine Reserve, Kenya (3^oS, 40^oE). The annual chronology is precise and is based on exceptionally clear high and low density growth band couplets. The record extends from 1696 to 1996 A.D., making it the longest coral climate record from the Indian Ocean and one of the longest available worldwide. We have analyzed the uppermost portion of the coral colony in triplicate, using 3 separate cores. This upper section, used for calibration purposes, also provides estimates of signal fidelity and noise in the climate recording system internal to the colony. Coral δ18O at this site primarily records SST; linear regression of monthly coral δ18O vs. SST yields a slope of -0.26 ppm δ18O per ^oC, and δ18O explains ˜57% of the SST variance. Additional isotopic variability may result from changes in seawater δ18O due to local runoff or regional evaporation/precipitation balance, but these changes are likely to be small because local rainfall δ18O is not strongly depleted relative to seawater and salinity gradients are small. The coral record indicates a clear warming trend of about 1.5^oC that accelerates in the latest 20th century, superimposed on strong decadal variability that persists throughout the record. In fact, δ18O values in the 1990's exceed the 300 year envelope (they are lower) and correspond with apparently unprecedented coral bleaching in coastal East Africa. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. In general, East African SST and rainfall are better correlated with Pacific ENSO indicators than with the Indian Monsoon at all periods (inter-annual through multi-decadal) but the correlation weakens after 1975. One dramatic new result we report here is a strong indication of a major cool and dry period from 1750--1820 A.D. This is the single largest multi-decadal anomaly of the past 300 years and correlates perfectly in time with the historically and anecdotally defined Lapanarat Drought. Our results indicate a strong link between multi-decadal tropical cold SST anomalies And far-reaching continental droughts in East Africa. Causes and links to other climate recording systems will be explored. Interannual-decadal SST variations are strongly coherent with ENSO indices and other ENSO-sensitive coral records on decadal and interannual time scales. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. Previous work has argued that this component likely reflects a monsoonal influence. However, decadal variance in both Malindi and Seychelles (Charles et al. 1997) coral records is more strongly coherent with ENSO indices than with the India or East Africa rain indices. The coherency of both coral records with Pacific indicators suggests instead that Indian Ocean variability reflects decadal ENSO-like variability originating in the Pacific. These records don't correlate significantly with the Pacific Decadal Oscillation implying a dominant role for the tropical Pacific (as opposed to extra-tropical regions) as a source of regional decadal variability in the western Indian Ocean. This work confirms that the tropical Pacific can act as an agent of decadal climate variability over a very large spatial scale.