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

Treesearch

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

2010-01-01

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

Regional projections of the likelihood of very large wildland fires under a changing climate in the contiguous Western United States

Treesearch

Donald McKenzie; John T. Abatzoglou; E. Natasha Stavros; Narasimhan K. Larkin

2014-01-01

Seasonal changes in the climatic potential for very large wildfires (VLWF >= 50,000 ac~20,234 ha) across the western contiguous United States are projected over the 21st century using generalized linear models and downscaled climate projections for two representative concentration pathways (RCPs). Significant (p

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

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

Testing For The Linearity of Responses To Multiple Anthropogenic Climate Forcings

NASA Astrophysics Data System (ADS)

Forest, C. E.; Stone, P. H.; Sokolov, A. P.

To test whether climate forcings are additive, we compare climate model simulations in which anthropogenic forcings are applied individually and in combination. Tests are performed with different values for climate system properties (climate sensitivity and rate of heat uptake by the deep ocean) as well as for different strengths of the net aerosol forcing, thereby testing for the dependence of linearity on these properties. The MIT 2D Land-Ocean Climate Model used in this study consists of a zonally aver- aged statistical-dynamical atmospheric model coupled to a mixed-layer Q-flux ocean model, with heat anomalies diffused into the deep ocean. Following our previous stud- ies, the anthropogenic forcings are the changes in concentrations of greenhouse gases (1860-1995), sulfate aerosol (1860-1995), and stratospheric and tropospheric ozone (1979-1995). The sulfate aerosol forcing is applied as a surface albedo change. For an aerosol forcing of -1.0 W/m2 and an effective ocean diffusitivity of 2.5 cm2/s, the nonlinearity of the response of global-mean surface temperatures to the combined forcing shows a strong dependence on climate sensitivity. The fractional change in decadal averages ([(TG + TS + TO) - TGSO]/TGSO) for the 1986-1995 period compared to pre-industrial times are 0.43, 0.90, and 1.08 with climate sensitiv- ities of 3.0, 4.5, and 6.2 C, respectively. The values of TGSO for these three cases o are 0.52, 0.62, and 0.76 C. The dependence of linearity on climate system properties, o the role of climate system feedbacks, and the implications for the detection of climate system's response to individual forcings will be presented. Details of the model and forcings can be found at http://web.mit.edu/globalchange/www/.

Testing for the linearity of responses to multiple anthropogenic climate forcings

NASA Astrophysics Data System (ADS)

Forest, C. E.; Stone, P. H.; Sokolov, A. P.

2001-12-01

To test whether climate forcings are additive, we compare climate model simulations in which anthropogenic forcings are applied individually and in combination. Tests are performed with different values for climate system properties (climate sensitivity and rate of heat uptake by the deep ocean) as well as for different strengths of the net aerosol forcing, thereby testing for the dependence of linearity on these properties. The MIT 2D Land-Ocean Climate Model used in this study consists of a zonally averaged statistical-dynamical atmospheric model coupled to a mixed-layer Q-flux ocean model, with heat anomalies diffused into the deep ocean. Following our previous studies, the anthropogenic forcings are the changes in concentrations of greenhouse gases (1860-1995), sulfate aerosol (1860-1995), and stratospheric and tropospheric ozone (1979-1995). The sulfate aerosol forcing is applied as a surface albedo change. For an aerosol forcing of -1.0 W/m2 and an effective ocean diffusitivity of 2.5 cm2/s, the nonlinearity of the response of global-mean surface temperatures to the combined forcing shows a strong dependence on climate sensitivity. The fractional change in decadal averages ([(Δ TG + Δ TS + Δ TO) - Δ TGSO ]/ Δ TGSO) for the 1986-1995 period compared to pre-industrial times are 0.43, 0.90, and 1.08 with climate sensitivities of 3.0, 4.5, and 6.2 oC, respectively. The values of Δ TGSO for these three cases are 0.52, 0.62, and 0.76 oC. The dependence of linearity on climate system properties, the role of climate system feedbacks, and the implications for the detection of climate system's response to individual forcings will be presented. Details of the model and forcings can be found at http://web.mit.edu/globalchange/www/.

Assessment of the Effect of Climate Change on Grain Yields in China

NASA Astrophysics Data System (ADS)

Chou, J.

2006-12-01

The paper elaborates the social background and research background; makes clear what the key scientific issues need to be resolved and where the difficulties are. In the research area of parasailing the grain yield change caused by climate change, massive works have been done both in the domestic and in the foreign. It is our upcoming work to evaluate how our countrywide climate change information provided by this pattern influence our economic and social development; and how to make related policies and countermeasures. the main idea in this paper is that the grain yield change is by no means the linear composition of social economy function effect and the climatic change function effect. This paper identifies the economic evaluation object, proposes one new concept - climate change output. The grain yields change affected by the social factors and the climatic change working together. Climate change influences the grain yields by the non ¨C linear function from both climate change and social factor changes, not only by climate change itself. Therefore, in my paper, the appraisal object is defined as: The social factors change based on actual social changing situations; under the two kinds of climate change situation, the invariable climate change situation and variable climate change situation; the difference of grain yield outputs is called " climate change output ", In order to solve this problem, we propose a method to analyze and imitate on the historical materials. Giving the condition that the climate is invariable, the social economic factor changes cause the grain yield change. However, this grain yield change is a tentative quantity index, not an actual quantity number. So we use the existing historical materials to exam the climate change output, based on the characteristic that social factor changes greater in year than in age, but the climate factor changes greater in age than in year. The paper proposes and establishes one economy - climate model (C-D-C model) to appraise the grain yield change caused by the climatic change. Also the preliminary test on this model has been done. In selection of the appraisal methods, we take the C-D production function model, which has been proved more mature in the economic research, as our fundamental model. Then, we introduce climate index (arid index) to the C-D model to develop one new model. This new model utilizes the climatic change factor in the economical model to appraise how the climatic change influence the grain yield change. The new way of appraise should have the better application prospect. The economy - climate model (The C-D-C model) has been applied on the eight Chinese regions that we divide; it has been proved satisfactory in its feasibility, rationality and the application prospect. So we can provide the theoretical fundamentals for policy-making under the more complex and uncertain climate change. Therefore, we open a new possible channel for the global climate change research moving toward the actual social, economic life.

Pace of shifts in climate regions increases with global temperature

NASA Astrophysics Data System (ADS)

Mahlstein, Irina; Daniel, John S.; Solomon, Susan

2013-08-01

Human-induced climate change causes significant changes in local climates, which in turn lead to changes in regional climate zones. Large shifts in the world distribution of Köppen-Geiger climate classifications by the end of this century have been projected. However, only a few studies have analysed the pace of these shifts in climate zones, and none has analysed whether the pace itself changes with increasing global mean temperature. In this study, pace refers to the rate at which climate zones change as a function of amount of global warming. Here we show that present climate projections suggest that the pace of shifting climate zones increases approximately linearly with increasing global temperature. Using the RCP8.5 emissions pathway, the pace nearly doubles by the end of this century and about 20% of all land area undergoes a change in its original climate. This implies that species will have increasingly less time to adapt to Köppen zone changes in the future, which is expected to increase the risk of extinction.

Recent trends of groundwater temperatures in Austria

NASA Astrophysics Data System (ADS)

Benz, Susanne A.; Bayer, Peter; Winkler, Gerfried; Blum, Philipp

2018-06-01

Climate change is one of if not the most pressing challenge modern society faces. Increasing temperatures are observed all over the planet and the impact of climate change on the hydrogeological cycle has long been shown. However, so far we have insufficient knowledge on the influence of atmospheric warming on shallow groundwater temperatures. While some studies analyse the implication climate change has for selected wells, large-scale studies are so far lacking. Here we focus on the combined impact of climate change in the atmosphere and local hydrogeological conditions on groundwater temperatures in 227 wells in Austria, which have in part been observed since 1964. A linear analysis finds a temperature change of +0.7 ± 0.8 K in the years from 1994 to 2013. In the same timeframe surface air temperatures in Austria increased by 0.5 ± 0.3 K, displaying a much smaller variety. However, most of the extreme changes in groundwater temperatures can be linked to local hydrogeological conditions. Correlation between groundwater temperatures and nearby surface air temperatures was additionally analysed. They vary greatly, with correlation coefficients of -0.3 in central Linz to 0.8 outside of Graz. In contrast, the correlation of nationwide groundwater temperatures and surface air temperatures is high, with a correlation coefficient of 0.83. All of these findings indicate that while atmospheric climate change can be observed in nationwide groundwater temperatures, individual wells are often primarily dominated by local hydrogeological conditions. In addition to the linear temperature trend, a step-wise model was also applied that identifies climate regime shifts, which were observed globally in the late 70s, 80s, and 90s. Hinting again at the influence of local conditions, at most 22 % of all wells show these climate regime shifts. However, we were able to identify an additional shift in 2007, which was observed by 37 % of all wells. Overall, the step-wise representation provides a slightly more accurate picture of observed temperatures than the linear trend.

Climate change impacts on projections of excess mortality at ...

EPA Pesticide Factsheets

We project the change in ozone-related mortality burden attributable to changes in climate between a historical (1995-2005) and near-future (2025-2035) time period while incorporating a non-linear and synergistic effect of ozone and temperature on mortality. We simulate air quality from climate projections varying only biogenic emissions and holding anthropogenic emissions constant, thus attributing changes in ozone only to changes in climate and independent of changes in air pollutant emissions. We estimate non-linear, spatially varying, ozone-temperature risk surfaces for 94 US urban areas using observeddata. Using the risk surfaces and climate projections we estimate daily mortality attributable to ozone exceeding 40 p.p.b. (moderate level) and 75 p.p.b. (US ozone NAAQS) for each time period. The average increases in city-specific median April-October ozone and temperature between time periods are 1.02 p.p.b. and 1.94 °F; however, the results variedby region . Increases in ozone because of climate change result in an increase in ozone mortality burden. Mortality attributed to ozone exceeding 40 p.p.b. increases by 7.7% (1 .6-14.2%). Mortality attributed to ozone exceeding 75 p.p.b. increases by 14.2% (1.628.9%). The absolute increase in excess ozone mortality is larger for changes in moderate ozone levels, reflecting the larger number of days with moderate ozone levels. In this study we evaluate changes in ozone related mortality due to changes in biogenic f

Climate-change impacts on terrestrial ecosystems and water resources at different global warming levels

NASA Astrophysics Data System (ADS)

Tanaka, A.; Takahashi, K.; Shiogama, H.; Hanasaki, N.; Masaki, Y.; Ito, A.; Noda, H.; Hijioka, Y.; Emori, S.

2016-12-01

The Paris Agreement of 2015 includes pursuing efforts to limit the increase in the global mean temperature from preindustrial levels (ΔGMT) to 1.5°C, as well as suppressing ΔGMT well below 2°C. However, how impacts of 1.5°C differ from the impacts of 2°C or greater warming is unclear, and further studies covering wider ranges of ΔGMT are required. We arranged climate-change impacts at different ΔGMT levels by employing the outputs from impact assessment simulations based on climate scenarios of five climate models and four radiative forcing scenarios. We then tested whether climate-change impacts at different ΔGMT levels in a range ΔGMT = 1.5-4°C can be derived from those at ΔGMT = 2°C by linear scaling. We assessed impacts on net primary production, CO2 emissions from biomass burning, soil erosion, and surface runoff, at global and regional scales. We found that linearity holds in most regions for net primary production, biomass burning, and surface runoff, but fails for soil erosion. In this session, we discuss at what value of ΔGMT linearity fails for both world and several regional domains.

The non-linear, interactive effects of population density and climate drive the geographical patterns of waterfowl survival

USGS Publications Warehouse

Zhao, Qing; Boomer, G. Scott; Kendall, William L.

2018-01-01

On-going climate change has major impacts on ecological processes and patterns. Understanding the impacts of climate on the geographical patterns of survival can provide insights to how population dynamics respond to climate change and provide important information for the development of appropriate conservation strategies at regional scales. It is challenging to understand the impacts of climate on survival, however, due to the fact that the non-linear relationship between survival and climate can be modified by density-dependent processes. In this study we extended the Brownie model to partition hunting and non-hunting mortalities and linked non-hunting survival to covariates. We applied this model to four decades (1972–2014) of waterfowl band-recovery, breeding population survey, and precipitation and temperature data covering multiple ecological regions to examine the non-linear, interactive effects of population density and climate on waterfowl non-hunting survival at a regional scale. Our results showed that the non-linear effect of temperature on waterfowl non-hunting survival was modified by breeding population density. The concave relationship between non-hunting survival and temperature suggested that the effects of warming on waterfowl survival might be multifaceted. Furthermore, the relationship between non-hunting survival and temperature was stronger when population density was higher, suggesting that high-density populations may be less buffered against warming than low-density populations. Our study revealed distinct relationships between waterfowl non-hunting survival and climate across and within ecological regions, highlighting the importance of considering different conservation strategies according to region-specific population and climate conditions. Our findings and associated novel modelling approach have wide implications in conservation practice.

[Effects of climate and grazing on the vegetation cover change in Xilinguole League of Inner Mongolia, North China].

PubMed

Wang, Hai-Mei; Li, Zheng-Hai; Wang, Zhen

2013-01-01

Based on the monthly temperature and precipitation data of 15 meteorological stations and the statistical data of livestock density in Xilinguole League in 1981-2007, and by using ArcGIS, this paper analyzed the spatial distribution of the climate aridity and livestock density in the League, and in combining with the ten-day data of the normalized difference vegetation index (NDVI) in 1981-2007, the driving factors of the vegetation cover change in the League were discussed. In the study period, there was a satisfactory linear regression relationship between the climate aridity and the vegetation coverage. The NDVI and the livestock density had a favorable binomial regression relationship. With the increase of NDVI, the livestock density increased first and decreased then. The vegetation coverage had a complex linear relationship with livestock density and climate aridity. The NDVI had a positive correlation with climate aridity, but a negative correlation with livestock density. Compared with livestock density, climate aridity had far greater effects on the NDVI.

A climate-compatible approach to development practice by international humanitarian NGOs.

PubMed

Clarke, Matthew; de Cruz, Ian

2015-01-01

If current climate-change predictions prove accurate, non-linear change, including potentially catastrophic change, is possible and the environments in which international humanitarian NGOs operate will change figuratively and literally. This paper proposes that a new approach to development is required that takes changing climate into account. This 'climate-compatible approach' to development is a bleak shift from some of the current orthodox positions and will be a major challenge to international humanitarian NGOs working with the most vulnerable. However, it is necessary to address the challenges and context such NGOs face, and the need to be resilient and adaptive to these changes. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Do Quercus ilex Woodlands Undergo Abrupt Non-linear Changes in their Functional Dynamics in Response to Human Disturbance and Climatic Variation?

NASA Astrophysics Data System (ADS)

Bochet, E.; García-Fayos, P.; Molina, M. J.; Moreno de las Heras, M.; Espigares, T.; Nicolau, J. M.; Monleon, V. J.

2017-12-01

Theoretical models predict that drylands are particularly prone to suffer critical transitions with abrupt non-linear changes in their structure and functions as a result of the existing complex interactions between climatic fluctuations and human disturbances. How drylands undergo functional change has become an important issue in ecology which needs empirical data to validate theoretical models. We aim at determining the response of Mediterranean holm oak woodlands to human disturbance in three different climatic areas from Eastern Spain, under the hypothesis that semiarid and dry-transition landscapes are more prone to suffer abrupt functional changes than sub-humid ones. We used (a) remote-sensing estimations of precipitation-use-efficiency (PUE) from enhanced vegetation index (EVI) observations performed in 231 x 231 m plots of the Moderate Resolution Imaging Spectroradiometer (MODIS); (b) soil parameter (enzyme activity, organic matter) and (c) vegetation parameter (functional groups) determinations from soil sampling and vegetation surveys, respectively, performed in the same plots. We analyzed and compared the shape of the functional change (in terms of PUE, soil and vegetation parameters) in response to human disturbance intensity for our holm oak sites in the three climatic areas. Although no threshold of abrupt change is observed, important differences in the functional response of holm oak woodlands to disturbance exist between climatic conditions. Overall, semiarid and dry-transition woodlands suffer a non-linear functional decrease in terms of PUE, soil organic matter and enzyme activity with disturbance intensity. Differently, sub-humid woodlands experience a linear decrease of PUE with disturbance intensity and an increase of both soil parameters at high disturbance intensities after an important decrease at low disturbance intensities. The structural change from woody- to herbaceous-dominated landscapes in sub-humid areas explains the recovery of the functional state of the system at high disturbance intensities. This structural change in the vegetation provides resilience to sub-humid woodlands at high intensity levels where semiarid and dry-transition woodlands suffer a pronounced degradation.

Abrupt climate-independent fire regime changes

USGS Publications Warehouse

Pausas, Juli G.; Keeley, Jon E.

2014-01-01

Wildfires have played a determining role in distribution, composition and structure of many ecosystems worldwide and climatic changes are widely considered to be a major driver of future fire regime changes. However, forecasting future climatic change induced impacts on fire regimes will require a clearer understanding of other drivers of abrupt fire regime changes. Here, we focus on evidence from different environmental and temporal settings of fire regimes changes that are not directly attributed to climatic changes. We review key cases of these abrupt fire regime changes at different spatial and temporal scales, including those directly driven (i) by fauna, (ii) by invasive plant species, and (iii) by socio-economic and policy changes. All these drivers might generate non-linear effects of landscape changes in fuel structure; that is, they generate fuel changes that can cross thresholds of landscape continuity, and thus drastically change fire activity. Although climatic changes might contribute to some of these changes, there are also many instances that are not primarily linked to climatic shifts. Understanding the mechanism driving fire regime changes should contribute to our ability to better assess future fire regimes.

Drought variability in six catchments in the UK

NASA Astrophysics Data System (ADS)

Kwok-Pan, Chun; Onof, Christian; Wheater, Howard

2010-05-01

Drought is fundamentally related to consistent low precipitation levels. Changes in global and regional drought patterns are suggested by numerous recent climate change studies. However, most of the climate change adaptation measures are at a catchment scale, and the development of a framework for studying persistence in precipitation is still at an early stage. Two stochastic approaches for modelling drought severity index (DSI) are proposed to investigate possible changes in droughts in six catchments in the UK. They are the autoregressive integrated moving average (ARIMA) and the generalised linear model (GLM) approach. Results of ARIMA modelling show that mean sea level pressure and possibly the North Atlantic Oscillation (NAO) index are important climate variables for short term drought forecasts, whereas relative humidity is not a significant climate variable despite its high correlation with the DSI series. By simulating rainfall series, the generalised linear model (GLM) approach can provide the probability density function of the DSI. GLM simulations indicate that the changes in the 10th and 50th quantiles of drought events are more noticeable than in the 90th extreme droughts. The possibility of extending the GLM approach to support risk-based water management is also discussed.

Estuarine Response to River Flow and Sea-Level Rise under Future Climate Change and Human Development

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

Yang, Zhaoqing; Wang, Taiping; Voisin, Nathalie

Understanding the response of river flow and estuarine hydrodynamics to climate change, land-use/land-cover change (LULC), and sea-level rise is essential to managing water resources and stress on living organisms under these changing conditions. This paper presents a modeling study using a watershed hydrology model and an estuarine hydrodynamic model, in a one-way coupling, to investigate the estuarine hydrodynamic response to sea-level rise and change in river flow due to the effect of future climate and LULC changes in the Snohomish River estuary, Washington, USA. A set of hydrodynamic variables, including salinity intrusion points, average water depth, and salinity of themore » inundated area, were used to quantify the estuarine response to river flow and sea-level rise. Model results suggest that salinity intrusion points in the Snohomish River estuary and the average salinity of the inundated areas are a nonlinear function of river flow, although the average water depth in the inundated area is approximately linear with river flow. Future climate changes will shift salinity intrusion points further upstream under low flow conditions and further downstream under high flow conditions. In contrast, under the future LULC change scenario, the salinity intrusion point will shift downstream under both low and high flow conditions, compared to present conditions. The model results also suggest that the average water depth in the inundated areas increases linearly with sea-level rise but at a slower rate, and the average salinity in the inundated areas increases linearly with sea-level rise; however, the response of salinity intrusion points in the river to sea-level rise is strongly nonlinear.« less

Streamflow droughts in major watershed regions of the conterminous U.S.: Understanding evolution of historic patterns

NASA Astrophysics Data System (ADS)

Pournasiri Poshtiri, M.; Pal, I.

2015-12-01

Climate non-stationarity affects regional hydrological extremes. This research looks into historic patterns of streamflow drought indicators and their evolution for major watershed regions in the conterminous U.S. (CONUS). The results indicate general linear and non-linear drying trends, particularly in the last four decades, as opposed to wetting trends reported in previous studies. Regional differences in the trends are notable, and echo the local climatic changes documented in the recent National Climate Assessment (NCA). A reversal of linear trends is seen for some northern regions after 1980s. Patterns in return periods and corresponding return values of the indicators are also examined, which suggests changing risk conditions that are important for water-resources decision-making. Persistent or flash drought conditions in a river can lead to chronic or short-term water scarcity—a main driver of societal and cross-boundary conflicts. Thus, this research identifies "hotspot" locations where suitable adaptive management measures are most needed.

Analysis on the Climate Change Characteristics of Dianchi Lake Basin under the Background of Global Warming

NASA Astrophysics Data System (ADS)

Zhenyu, Yu; Luo, Yi; Yang, Kun; Qiongfei, Deng

2017-05-01

Based on the data published by the State Statistical Bureau and the weather station data, the annual mean temperature, wind speed, humidity, light duration and precipitation of Dianchi Lake in 1990 ~ 2014 were analysed. Combined with the population The results show that the climatic changes in Dianchi Lake basin are related to the climatic change in the past 25 years, and the correlation between these factors and the main climatic factors are analysed by linear regression, Mann-Kendall test, cumulative anomaly, R/S and Morlet wavelet analysis. Population, housing construction area growth and other aspects of the correlation trends and changes in the process, revealing the population expansion and housing construction area growth on the climate of the main factors of the cycle tendency of significant impact.

Understanding uncertainty in precipitation changes in a balanced perturbed-physics ensemble under multiple climate forcings

NASA Astrophysics Data System (ADS)

Millar, R.; Ingram, W.; Allen, M. R.; Lowe, J.

2013-12-01

Temperature and precipitation patterns are the climate variables with the greatest impacts on both natural and human systems. Due to the small spatial scales and the many interactions involved in the global hydrological cycle, in general circulation models (GCMs) representations of precipitation changes are subject to considerable uncertainty. Quantifying and understanding the causes of uncertainty (and identifying robust features of predictions) in both global and local precipitation change is an essential challenge of climate science. We have used the huge distributed computing capacity of the climateprediction.net citizen science project to examine parametric uncertainty in an ensemble of 20,000 perturbed-physics versions of the HadCM3 general circulation model. The ensemble has been selected to have a control climate in top-of-atmosphere energy balance [Yamazaki et al. 2013, J.G.R.]. We force this ensemble with several idealised climate-forcing scenarios including carbon dioxide step and transient profiles, solar radiation management geoengineering experiments with stratospheric aerosols, and short-lived climate forcing agents. We will present the results from several of these forcing scenarios under GCM parametric uncertainty. We examine the global mean precipitation energy budget to understand the robustness of a simple non-linear global precipitation model [Good et al. 2012, Clim. Dyn.] as a better explanation of precipitation changes in transient climate projections under GCM parametric uncertainty than a simple linear tropospheric energy balance model. We will also present work investigating robust conclusions about precipitation changes in a balanced ensemble of idealised solar radiation management scenarios [Kravitz et al. 2011, Atmos. Sci. Let.].

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

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

2012-01-01

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

Braking effect of climate and topography on global change-induced upslope forest expansion.

PubMed

Alatalo, Juha M; Ferrarini, Alessandro

2017-03-01

Forests are expected to expand into alpine areas due to global climate change. It has recently been shown that temperature alone cannot realistically explain this process and that upslope tree advance in a warmer scenario may depend on the availability of sites with adequate geomorphic/topographic characteristics. Here, we show that, besides topography (slope and aspect), climate itself can produce a braking effect on the upslope advance of subalpine forests and that tree limit is influenced by non-linear and non-monotonic contributions of the climate variables which act upon treeline upslope advance with varying relative strengths. Our results suggest that global climate change impact on the upslope advance of subalpine forests should be interpreted in a more complex way where climate can both speed up and slow down the process depending on complex patterns of contribution from each climate and non-climate variable.

Healthcare waste management during disasters and its effects on climate change: Lessons from 2010 earthquake and cholera tragedies in Haiti.

PubMed

Raila, Emilia M; Anderson, David O

2017-03-01

Despite growing effects of human activities on climate change throughout the world, and global South in particular, scientists are yet to understand how poor healthcare waste management practices in an emergency influences the climate change. This article presents new findings on climate change risks of healthcare waste disposal during and after the 2010 earthquake and cholera disasters in Haiti. The researchers analysed quantities of healthcare waste incinerated by the United Nations Mission in Haiti for 60 months (2009 to 2013). The aim was to determine the relationship between healthcare waste incinerated weights and the time of occurrence of the two disasters, and associated climate change effects, if any. Pearson product-moment correlation coefficient indicated a weak correlation between the quantities of healthcare waste disposed of and the time of occurrence of the actual emergencies (r (58) = 0.406, p = 0.001). Correspondingly, linear regression analysis indicated a relatively linear data trend (R 2 = 0.16, F (1, 58) = 11.42, P = 0.001) with fluctuating scenarios that depicted a sharp rise in 2012, and time series model showed monthly and yearly variations within 60 months. Given that the peak healthcare waste incineration occurred 2 years after the 2010 disasters, points at the need to minimise wastage on pharmaceuticals by improving logistics management. The Government of Haiti had no data on healthcare waste disposal and practised smoky open burning, thus a need for capacity building on green healthcare waste management technologies for effective climate change mitigation.

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

PubMed

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

2007-10-01

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

Sensitivity of regional forest carbon budgets to continuous and stochastic climate change pressures

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Desai, A. R.; Scheller, R. M.

2010-12-01

Climate change is expected to impact forest-atmosphere carbon budgets through three processes: 1. Increased disturbance rates, including fires, mortality due to pest outbreaks, and severe storms 2. Changes in patterns of inter-annual variability, related to increased incidence of severe droughts and defoliating insect outbreaks 3. Continuous changes in forest productivity and respiration, related to increases in mean temperature, growing season length, and CO2 fertilization While the importance of these climate change effects in future regional carbon budgets has been established, quantitative characterization of the relative sensitivity of forested landscapes to these different types of pressures is needed. We present a model- and- data-based approach to understanding the sensitivity of forested landscapes to climate change pressures. Eddy-covariance and biometric measurements from forests in the northern United States were used to constrain two forest landscape models. The first, LandNEP, uses a prescribed functional form for the evolution of net ecosystem productivity (NEP) over the age of a forested grid cell, which is reset following a disturbance event. This model was used for investigating the basic statistical properties of a simple landscape’s responses to climate change pressures. The second model, LANDIS-II, includes different tree species and models forest biomass accumulation and succession, allowing us to investigate the effects of more complex forest processes such as species change and carbon pool accumulation on landscape responses to climate change effects. We tested the sensitivity of forested landscapes to these three types of climate change pressures by applying ensemble perturbations of random disturbance rates, distribution functions of inter-annual variability, and maximum potential carbon uptake rates, in the two models. We find that landscape-scale net carbon exchange responds linearly to continuous changes in potential carbon uptake and inter-annual variability, while responses to stochastic changes are non-linear and become more important at shorter mean disturbance intervals. These results provide insight on how to better parameterize coupled carbon-climate models to more realistically simulate feedbacks between forests and the atmosphere.

Equilibrium Climate Sensitivity Obtained From Multimillennial Runs of Two GFDL Climate Models

NASA Astrophysics Data System (ADS)

Paynter, D.; Frölicher, T. L.; Horowitz, L. W.; Silvers, L. G.

2018-02-01

Equilibrium climate sensitivity (ECS), defined as the long-term change in global mean surface air temperature in response to doubling atmospheric CO2, is usually computed from short atmospheric simulations over a mixed layer ocean, or inferred using a linear regression over a short-time period of adjustment. We report the actual ECS from multimillenial simulations of two Geophysical Fluid Dynamics Laboratory (GFDL) general circulation models (GCMs), ESM2M, and CM3 of 3.3 K and 4.8 K, respectively. Both values are 1 K higher than estimates for the same models reported in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change obtained by regressing the Earth's energy imbalance against temperature. This underestimate is mainly due to changes in the climate feedback parameter (-α) within the first century after atmospheric CO2 has stabilized. For both GCMs it is possible to estimate ECS with linear regression to within 0.3 K by increasing CO2 at 1% per year to doubling and using years 51-350 after CO2 is constant. We show that changes in -α differ between the two GCMs and are strongly tied to the changes in both vertical velocity at 500 hPa (ω500) and estimated inversion strength that the GCMs experience during the progression toward the equilibrium. This suggests that while cloud physics parametrizations are important for determining the strength of -α, the substantially different atmospheric state resulting from a changed sea surface temperature pattern may be of equal importance.

Vegetation anomalies caused by antecedent precipitation in most of the world

NASA Astrophysics Data System (ADS)

Papagiannopoulou, C.; Miralles, D. G.; Dorigo, W. A.; Verhoest, N. E. C.; Depoorter, M.; Waegeman, W.

2017-07-01

Quantifying environmental controls on vegetation is critical to predict the net effect of climate change on global ecosystems and the subsequent feedback on climate. Following a non-linear Granger causality framework based on a random forest predictive model, we exploit the current wealth of multi-decadal satellite data records to uncover the main drivers of monthly vegetation variability at the global scale. Results indicate that water availability is the most dominant factor driving vegetation globally: about 61% of the vegetated surface was primarily water-limited during 1981-2010. This included semiarid climates but also transitional ecoregions. Intra-annually, temperature controls Northern Hemisphere deciduous forests during the growing season, while antecedent precipitation largely dominates vegetation dynamics during the senescence period. The uncovered dependency of global vegetation on water availability is substantially larger than previously reported. This is owed to the ability of the framework to (1) disentangle the co-linearities between radiation/temperature and precipitation, and (2) quantify non-linear impacts of climate on vegetation. Our results reveal a prolonged effect of precipitation anomalies in dry regions: due to the long memory of soil moisture and the cumulative, non-linear, response of vegetation, water-limited regions show sensitivity to the values of precipitation occurring three months earlier. Meanwhile, the impacts of temperature and radiation anomalies are more immediate and dissipate shortly, pointing to a higher resilience of vegetation to these anomalies. Despite being infrequent by definition, hydro-climatic extremes are responsible for up to 10% of the vegetation variability during the 1981-2010 period in certain areas, particularly in water-limited ecosystems. Our approach is a first step towards a quantitative comparison of the resistance and resilience signature of different ecosystems, and can be used to benchmark Earth system models in their representations of past vegetation sensitivity to changes in climate.

Learning from Non-Linear Ecosystem Dynamics Is Vital for Achieving Land Degradation Neutrality

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

Sietz, Diana; Fleskens, Luuk; Stringer, Lindsay C.

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits,despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks and the financialmore » viability of investments. These novel insights are pre-requisites for meaningful o and monitoring of progress towards Land Degradation Neutrality« less

Learning from Non-Linear Ecosystem Dynamics Is Vital for Achieving Land Degradation Neutrality

DOE PAGES

Sietz, Diana; Fleskens, Luuk; Stringer, Lindsay C.

2017-02-27

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits,despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks and the financialmore » viability of investments. These novel insights are pre-requisites for meaningful o and monitoring of progress towards Land Degradation Neutrality« less

Climate change at upper treeline: How do trees on the edge react to increasing temperatures?

NASA Astrophysics Data System (ADS)

Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof

2017-04-01

Treeline ecotones are thought to be particularly sensitive to climate warming, and an alteration of their growth conditions may have important implications for the ecosystem services they supply in mountain regions. We use a novel approach to quantify effects of a changing climate on tree growth, using case studies in the European Alps. We compiled tree-ring data from almost 600 trees of four species at treeline in three climate regions of Switzerland. Temperature loggers installed along transects provided data for a precise interpolation of temperatures experienced by the sampled trees. To assess the influence of temperature on annual growth, we used linear mixed-effects models, allowing us to quantify effect sizes and to account for between-tree growth variability. After removing biological growth trends, we isolated temporal trends of ring-width indices. Furthermore, we fitted non-linear regression models to radial growth rates of individual years with temperature and tree age as predicting covariates for a fine-scale investigation of the temperature dependency of tree growth. For all species, climate-growth linear mixed-effects models indicated strong positive responses of ring-width indices to temperature in early summer and previous year's autumn, featuring considerable between-tree variability. All species showed positive ring-width index trends at treeline but different interactions with elevation: Larix decidua exhibited a declining ring-width index trend with decreasing elevation, whereas Picea abies, Pinus cembra and Pinus mugo showed increasing and/or stable trends. Not only reflected our findings the effects of ameliorated growth conditions, they might have also revealed suspected negative and positive feedbacks of climate change on growth, and increased the knowledge about the functional form and parameterization of the temperature dependency of tree growth.

Analytically based forward and inverse models of fluvial landscape evolution during temporally continuous climatic and tectonic variations

NASA Astrophysics Data System (ADS)

Goren, Liran; Petit, Carole

2017-04-01

Fluvial channels respond to changing tectonic and climatic conditions by adjusting their patterns of erosion and relief. It is therefore expected that by examining these patterns, we can infer the tectonic and climatic conditions that shaped the channels. However, the potential interference between climatic and tectonic signals complicates this inference. Within the framework of the stream power model that describes incision rate of mountainous bedrock rivers, climate variability has two effects: it influences the erosive power of the river, causing local slope change, and it changes the fluvial response time that controls the rate at which tectonically and climatically induced slope breaks are communicated upstream. Because of this dual role, the fluvial response time during continuous climate change has so far been elusive, which hinders our understanding of environmental signal propagation and preservation in the fluvial topography. An analytic solution of the stream power model during general tectonic and climatic histories gives rise to a new definition of the fluvial response time. The analytic solution offers accurate predictions for landscape evolution that are hard to achieve with classical numerical schemes and thus can be used to validate and evaluate the accuracy of numerical landscape evolution models. The analytic solution together with the new definition of the fluvial response time allow inferring either the tectonic history or the climatic history from river long profiles by using simple linear inversion schemes. Analytic study of landscape evolution during periodic climate change reveals that high frequency (10-100 kyr) climatic oscillations with respect to the response time, such as Milankovitch cycles, are not expected to leave significant fingerprints in the upstream reaches of fluvial channels. Linear inversion schemes are applied to the Tinee river tributaries in the southern French Alps, where tributary long profiles are used to recover the incision rate history of the Tinee main trunk. Inversion results show periodic, high incision rate pulses, which are correlated with interglacial episodes. Similar incision rate histories are recovered for the past 100 kyr when assuming constant climatic conditions or periodic climatic oscillations, in agreement with theoretical predictions.

Forcing, feedbacks and climate sensitivity in CMIP5 coupled atmosphere-ocean climate models

DOE PAGES

Andrews, Timothy; Gregory, Jonathan M.; Webb, Mark J.; ...

2012-05-15

We quantify forcing and feedbacks across available CMIP5 coupled atmosphere-ocean general circulation models (AOGCMs) by analysing simulations forced by an abrupt quadrupling of atmospheric carbon dioxide concentration. This is the first application of the linear forcing-feedback regression analysis of Gregory et al. (2004) to an ensemble of AOGCMs. The range of equilibrium climate sensitivity is 2.1–4.7 K. Differences in cloud feedbacks continue to be important contributors to this range. Some models show small deviations from a linear dependence of top-of-atmosphere radiative fluxes on global surface temperature change. We show that this phenomenon largely arises from shortwave cloud radiative effects overmore » the ocean and is consistent with independent estimates of forcing using fixed sea-surface temperature methods. Moreover, we suggest that future research should focus more on understanding transient climate change, including any time-scale dependence of the forcing and/or feedback, rather than on the equilibrium response to large instantaneous forcing.« less

Energy-balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1980-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

Energy balance climate models

NASA Technical Reports Server (NTRS)

North, G. R.; Cahalan, R. F.; Coakley, J. A., Jr.

1981-01-01

An introductory survey of the global energy balance climate models is presented with an emphasis on analytical results. A sequence of increasingly complicated models involving ice cap and radiative feedback processes are solved, and the solutions and parameter sensitivities are studied. The model parameterizations are examined critically in light of many current uncertainties. A simple seasonal model is used to study the effects of changes in orbital elements on the temperature field. A linear stability theorem and a complete nonlinear stability analysis for the models are developed. Analytical solutions are also obtained for the linearized models driven by stochastic forcing elements. In this context the relation between natural fluctuation statistics and climate sensitivity is stressed.

Projection of temperature-related mortality due to cardiovascular disease in beijing under different climate change, population, and adaptation scenarios.

PubMed

Zhang, Boya; Li, Guoxing; Ma, Yue; Pan, Xiaochuan

2018-04-01

Human health faces unprecedented challenges caused by climate change. Thus, studies of the effect of temperature change on total mortality have been conducted in numerous countries. However, few of those studies focused on temperature-related mortality due to cardiovascular disease (CVD) or considered future population changes and adaptation to climate change. We present herein a projection of temperature-related mortality due to CVD under different climate change, population, and adaptation scenarios in Beijing, a megacity in China. To this end, 19 global circulation models (GCMs), 3 representative concentration pathways (RCPs), 3 socioeconomic pathways, together with generalized linear models and distributed lag non-linear models, were used to project future temperature-related CVD mortality during periods centered around the years 2050 and 2070. The number of temperature-related CVD deaths in Beijing is projected to increase by 3.5-10.2% under different RCP scenarios compared with that during the baseline period. Using the same GCM, the future daily maximum temperatures projected using the RCP2.6, RCP4.5, and RCP8.5 scenarios showed a gradually increasing trend. When population change is considered, the annual rate of increase in temperature-related CVD deaths was up to fivefold greater than that under no-population-change scenarios. The decrease in the number of cold-related deaths did not compensate for the increase in that of heat-related deaths, leading to a general increase in the number of temperature-related deaths due to CVD in Beijing. In addition, adaptation to climate change may enhance rather than ameliorate the effect of climate change, as the increase in cold-related CVD mortality greater than the decrease in heat-related CVD mortality in the adaptation scenarios will result in an increase in the total number of temperature-related CVD mortalities. Copyright © 2018 Elsevier Inc. All rights reserved.

Towards bridging the gap between climate change projections and maize producers in South Africa

NASA Astrophysics Data System (ADS)

Landman, Willem A.; Engelbrecht, Francois; Hewitson, Bruce; Malherbe, Johan; van der Merwe, Jacobus

2018-05-01

Multi-decadal regional projections of future climate change are introduced into a linear statistical model in order to produce an ensemble of austral mid-summer maximum temperature simulations for southern Africa. The statistical model uses atmospheric thickness fields from a high-resolution (0.5° × 0.5°) reanalysis-forced simulation as predictors in order to develop a linear recalibration model which represents the relationship between atmospheric thickness fields and gridded maximum temperatures across the region. The regional climate model, the conformal-cubic atmospheric model (CCAM), projects maximum temperatures increases over southern Africa to be in the order of 4 °C under low mitigation towards the end of the century or even higher. The statistical recalibration model is able to replicate these increasing temperatures, and the atmospheric thickness-maximum temperature relationship is shown to be stable under future climate conditions. Since dry land crop yields are not explicitly simulated by climate models but are sensitive to maximum temperature extremes, the effect of projected maximum temperature change on dry land crops of the Witbank maize production district of South Africa, assuming other factors remain unchanged, is then assessed by employing a statistical approach similar to the one used for maximum temperature projections.

Potential individual versus simultaneous climate change effects on soybean (C 3) and maize (C 4) crops: An agrotechnology model based study

NASA Astrophysics Data System (ADS)

Mera, Roberto J.; Niyogi, Dev; Buol, Gregory S.; Wilkerson, Gail G.; Semazzi, Fredrick H. M.

2006-11-01

Landuse/landcover change induced effects on regional weather and climate patterns and the associated plant response or agricultural productivity are coupled processes. Some of the basic responses to climate change can be detected via changes in radiation ( R), precipitation ( P), and temperature ( T). Past studies indicate that each of these three variables can affect LCLUC response and the agricultural productivity. This study seeks to address the following question: What is the effect of individual versus simultaneous changes in R, P, and T on plant response such as crop yields in a C 3 and a C 4 plant? This question is addressed by conducting model experiments for soybean (C 3) and maize (C 4) crops using the DSSAT: Decision Support System for Agrotechnology Transfer, CROPGRO (soybean), and CERES-Maize (maize) models. These models were configured over an agricultural experiment station in Clayton, NC [35.65°N, 78.5°W]. Observed weather and field conditions corresponding to 1998 were used as the control. In the first set of experiments, the CROPGRO (soybean) and CERES-Maize (maize) responses to individual changes in R and P (25%, 50%, 75%, 150%) and T (± 1, ± 2 °C) with respect to control were studied. In the second set, R, P, and T were simultaneously changed by 50%, 150%, and ± 2 °C, and the interactions and direct effects of individual versus simultaneous variable changes were analyzed. For the model setting and the prescribed environmental changes, results from the first set of experiments indicate: (i) precipitation changes were most sensitive and directly affected yield and water loss due to evapotranspiration; (ii) radiation changes had a non-linear effect and were not as prominent as precipitation changes; (iii) temperature had a limited impact and the response was non-linear; (iv) soybeans and maize responded differently for R, P, and T, with maize being more sensitive. The results from the second set of experiments indicate that simultaneous change analyses do not necessarily agree with those from individual changes, particularly for temperature changes. Our analysis indicates that for the changing climate, precipitation (hydrological), temperature, and radiative feedbacks show a non-linear effect on yield. Study results also indicate that for studying the feedback between the land surface and the atmospheric changes, (i) there is a need for performing simultaneous parameter changes in the response assessment of cropping patterns and crop yield based on ensembles of projected climate change, and (ii) C 3 crops are generally considered more sensitive than C 4; however, the temperature-radiation related changes shown in this study also effected significant changes in C 4 crops. Future studies assessing LCLUC impacts, including those from agricultural cropping patterns and other LCULC-climate couplings, should advance beyond the sensitivity mode and consider multivariable, ensemble approaches to identify the vulnerability and feedbacks in estimating climate-related impacts.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

Seasonal climate change patterns due to cumulative CO2 emissions

NASA Astrophysics Data System (ADS)

Partanen, Antti-Ilari; Leduc, Martin; Damon Matthews, H.

2017-07-01

Cumulative CO2 emissions are near linearly related to both global and regional changes in annual-mean surface temperature. These relationships are known as the transient climate response to cumulative CO2 emissions (TCRE) and the regional TCRE (RTCRE), and have been shown to remain approximately constant over a wide range of cumulative emissions. Here, we assessed how well this relationship holds for seasonal patterns of temperature change, as well as for annual-mean and seasonal precipitation patterns. We analyzed an idealized scenario with CO2 concentration growing at an annual rate of 1% using data from 12 Earth system models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). Seasonal RTCRE values for temperature varied considerably, with the highest seasonal variation evident in the Arctic, where RTCRE was about 5.5 °C per Tt C for boreal winter and about 2.0 °C per Tt C for boreal summer. Also the precipitation response in the Arctic during boreal winter was stronger than during other seasons. We found that emission-normalized seasonal patterns of temperature change were relatively robust with respect to time, though they were sub-linear with respect to emissions particularly near the Arctic. Moreover, RTCRE patterns for precipitation could not be quantified robustly due to the large internal variability of precipitation. Our results suggest that cumulative CO2 emissions are a useful metric to predict regional and seasonal changes in precipitation and temperature. This extension of the TCRE framework to seasonal and regional climate change is helpful for communicating the link between emissions and climate change to policy-makers and the general public, and is well-suited for impact studies that could make use of estimated regional-scale climate changes that are consistent with the carbon budgets associated with global temperature targets.

Reconciling inconsistencies in precipitation-productivity relationships: implications for climate change.

PubMed

Knapp, Alan K; Ciais, Philippe; Smith, Melinda D

2017-04-01

Contents 41 I. 41 II. 42 III. 43 IV. 44 V. 45 Acknowledgements 46 References 46 SUMMARY: Precipitation (PPT) is a primary climatic determinant of plant growth and aboveground net primary production (ANPP) over much of the globe. Thus, PPT-ANPP relationships are important both ecologically and to land-atmosphere models that couple terrestrial vegetation to the global carbon cycle. Empirical PPT-ANPP relationships derived from long-term site-based data are almost always portrayed as linear, but recent evidence has accumulated that is inconsistent with an underlying linear relationship. We review, and then reconcile, these inconsistencies with a nonlinear model that incorporates observed asymmetries in PPT-ANPP relationships. Although data are currently lacking for parameterization, this new model highlights research needs that, when met, will improve our understanding of carbon cycle dynamics, as well as forecasts of ecosystem responses to climate change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Bird population trends are linearly affected by climate change along species thermal ranges.

PubMed

Jiguet, Frédéric; Devictor, Vincent; Ottvall, Richard; Van Turnhout, Chris; Van der Jeugd, Henk; Lindström, Ake

2010-12-07

Beyond the effects of temperature increase on local population trends and on species distribution shifts, how populations of a given species are affected by climate change along a species range is still unclear. We tested whether and how species responses to climate change are related to the populations locations within the species thermal range. We compared the average 20 year growth rates of 62 terrestrial breeding birds in three European countries along the latitudinal gradient of the species ranges. After controlling for factors already reported to affect bird population trends (habitat specialization, migration distance and body mass), we found that populations breeding close to the species thermal maximum have lower growth rates than those in other parts of the thermal range, while those breeding close to the species thermal minimum have higher growth rates. These results were maintained even after having controlled for the effect of latitude per se. Therefore, the results cannot solely be explained by latitudinal clines linked to the geographical structure in local spring warming. Indeed, we found that populations are not just responding to changes in temperature at the hottest and coolest parts of the species range, but that they show a linear graded response across their European thermal range. We thus provide insights into how populations respond to climate changes. We suggest that projections of future species distributions, and also management options and conservation assessments, cannot be based on the assumption of a uniform response to climate change across a species range or at range edges only.

Meteorological Modes of Variability for Fine Particulate Matter (PM2.5) Air Quality in the United States: Implications for PM2.5 Sensitivity to Climate Change

EPA Science Inventory

We applied a multiple linear regression model to understand the relationships of PM_2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM_2.5 to climate change. We used 2004-2008 PM_2.5 observations fro...

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

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

PubMed

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

2017-01-15

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

Simulating the dynamics of linear forests in great plains agroecosystems under changing climates

Treesearch

Qinfeng Guo; J. Brandle; Michele Schoeneberger; D. Buettner

2004-01-01

Most forest growth models are not suitable for the highly fragmented, linear (or linearly shaped) forests in the Great Plains agroecosystems (e.g., windbreaks, riparian forest buffers), where such forests are a minor but ecologically important component of the land mosaics. This study used SEEI)SCAPE, a recently modified gap model designed for cultivated land mosaics...

Non-linear responses of glaciated prairie wetlands to climate warming

USGS Publications Warehouse

Johnson, W. Carter; Werner, Brett; Guntenspergen, Glenn R.

2016-01-01

The response of ecosystems to climate warming is likely to include threshold events when small changes in key environmental drivers produce large changes in an ecosystem. Wetlands of the Prairie Pothole Region (PPR) are especially sensitive to climate variability, yet the possibility that functional changes may occur more rapidly with warming than expected has not been examined or modeled. The productivity and biodiversity of these wetlands are strongly controlled by the speed and completeness of a vegetation cover cycle driven by the wet and dry extremes of climate. Two thresholds involving duration and depth of standing water must be exceeded every few decades or so to complete the cycle and to produce highly functional wetlands. Model experiments at 19 weather stations employing incremental warming scenarios determined that wetland function across most of the PPR would be diminished beyond a climate warming of about 1.5–2.0 °C, a critical temperature threshold range identified in other climate change studies.

Contributions to Future Stratospheric Climate Change: An Idealized Chemistry-Climate Model Sensitivity Study

NASA Technical Reports Server (NTRS)

Hurwitz, M. M.; Braesicke, P.; Pyle, J. A.

2010-01-01

Within the framework of an idealized model sensitivity study, three of the main contributors to future stratospheric climate change are evaluated: increases in greenhouse gas concentrations, ozone recovery, and changing sea surface temperatures (SSTs). These three contributors are explored in combination and separately, to test the interactions between ozone and climate; the linearity of their contributions to stratospheric climate change is also assessed. In a simplified chemistry-climate model, stratospheric global mean temperature is most sensitive to CO2 doubling, followed by ozone depletion, then by increased SSTs. At polar latitudes, the Northern Hemisphere (NH) stratosphere is more sensitive to changes in CO2, SSTs and O3 than is the Southern Hemisphere (SH); the opposing responses to ozone depletion under low or high background CO2 concentrations, as seen with present-day SSTs, are much weaker and are not statistically significant under enhanced SSTs. Consistent with previous studies, the strength of the Brewer-Dobson circulation is found to increase in an idealized future climate; SSTs contribute most to this increase in the upper troposphere/lower stratosphere (UT/LS) region, while CO2 and ozone changes contribute most in the stratosphere and mesosphere.

Assessing response of sediment load variation to climate change and human activities with six different approaches.

PubMed

Zhao, Guangju; Mu, Xingmin; Jiao, Juying; Gao, Peng; Sun, Wenyi; Li, Erhui; Wei, Yanhong; Huang, Jiacong

2018-05-23

Understanding the relative contributions of climate change and human activities to variations in sediment load is of great importance for regional soil, and river basin management. Considerable studies have investigated spatial-temporal variation of sediment load within the Loess Plateau; however, contradictory findings exist among methods used. This study systematically reviewed six quantitative methods: simple linear regression, double mass curve, sediment identity factor analysis, dam-sedimentation based method, the Sediment Delivery Distributed (SEDD) model, and the Soil Water Assessment Tool (SWAT) model. The calculation procedures and merits for each method were systematically explained. A case study in the Huangfuchuan watershed on the northern Loess Plateau has been undertaken. The results showed that sediment load had been reduced by 70.5% during the changing period from 1990 to 2012 compared to that of the baseline period from 1955 to 1989. Human activities accounted for an average of 93.6 ± 4.1% of the total decline in sediment load, whereas climate change contributed 6.4 ± 4.1%. Five methods produced similar estimates, but the linear regression yielded relatively different results. The results of this study provide a good reference for assessing the effects of climate change and human activities on sediment load variation by using different methods. Copyright © 2018. Published by Elsevier B.V.

Awareness of Climate Change and the Dietary Choices of Young Adults in Finland: A Population-Based Cross-Sectional Study

PubMed Central

Korkala, Essi A. E.; Hugg, Timo T.; Jaakkola, Jouni J. K.

2014-01-01

Climate change is a major public health threat that is exacerbated by food production. Food items differ substantially in the amount of greenhouse gases their production generates and therefore individuals, if willing, can mitigate climate change through dietary choices. We conducted a population-based cross-sectional study to assess if the understanding of climate change, concern over climate change or socio-economic characteristics are reflected in the frequencies of climate-friendly food choices. The study population comprised 1623 young adults in Finland who returned a self-administered questionnaire (response rate 64.0%). We constructed a Climate-Friendly Diet Score (CFDS) ranging theoretically from −14 to 14 based on the consumption of 14 food items. A higher CFDS indicated a climate-friendlier diet. Multivariate linear regression analyses on the determinants of CFDS revealed that medium concern raised CFDS on average by 0.51 points (95% confidence interval (CI) 0.03, 0.98) and high concern by 1.30 points (95% CI 0.80, 1.80) compared to low concern. Understanding had no effect on CFDS on its own. Female gender raised CFDS by 1.92 (95% CI 1.59, 2.25). Unemployment decreased CFDS by 0.92 (95% CI −1.68, −0.15). Separate analyses of genders revealed that high concern over climate change brought about a greater increase in CFDS in females than in males. Good understanding of climate change was weakly connected to climate-friendly diet among females only. Our results indicate that increasing awareness of climate change could lead to increased consumption of climate-friendly food, reduction in GHG emissions, and thus climate change mitigation. PMID:24824363

Chicken barn climate and hazardous volatile compounds control using simple linear regression and PID

NASA Astrophysics Data System (ADS)

Abdullah, A. H.; Bakar, M. A. A.; Shukor, S. A. A.; Saad, F. S. A.; Kamis, M. S.; Mustafa, M. H.; Khalid, N. S.

2016-07-01

The hazardous volatile compounds from chicken manure in chicken barn are potentially to be a health threat to the farm animals and workers. Ammonia (NH3) and hydrogen sulphide (H2S) produced in chicken barn are influenced by climate changes. The Electronic Nose (e-nose) is used for the barn's air, temperature and humidity data sampling. Simple Linear Regression is used to identify the correlation between temperature-humidity, humidity-ammonia and ammonia-hydrogen sulphide. MATLAB Simulink software was used for the sample data analysis using PID controller. Results shows that the performance of PID controller using the Ziegler-Nichols technique can improve the system controller to control climate in chicken barn.

Climate-Induced Boreal Forest Change: Predictions versus Current Observations

NASA Technical Reports Server (NTRS)

Soja, Amber J.; Tchebakova, Nadezda M.; French, Nancy H. F.; Flannigan, Michael D.; Shugart, Herman H.; Stocks, Brian J.; Sukhinin, Anatoly I.; Parfenova, E. I.; Chapin, F. Stuart, III; Stackhouse, Paul W., Jr.

2007-01-01

For about three decades, there have been many predictions of the potential ecological response in boreal regions to the currently warmer conditions. In essence, a widespread, naturally occurring experiment has been conducted over time. In this paper, we describe previously modeled predictions of ecological change in boreal Alaska, Canada and Russia, and then we investigate potential evidence of current climate-induced change. For instance, ecological models have suggested that warming will induce the northern and upslope migration of the treeline and an alteration in the current mosaic structure of boreal forests. We present evidence of the migration of keystone ecosystems in the upland and lowland treeline of mountainous regions across southern Siberia. Ecological models have also predicted a moisture-stress-related dieback in white spruce trees in Alaska, and current investigations show that as temperatures increase, white spruce tree growth is declining. Additionally, it was suggested that increases in infestation and wildfire disturbance would be catalysts that precipitate the alteration of the current mosaic forest composition. In Siberia, five of the last seven years have resulted in extreme fire seasons, and extreme fire years have also been more frequent in both Alaska and Canada. In addition, Alaska has experienced extreme and geographically expansive multi-year outbreaks of the spruce beetle, which had been previously limited by the cold, moist environment. We suggest that there is substantial evidence throughout the circumboreal region to conclude that the biosphere within the boreal terrestrial environment has already responded to the transient effects of climate change. Additionally, temperature increases and warming-induced change are progressing faster than had been predicted in some regions, suggesting a potential non-linear rapid response to changes in climate, as opposed to the predicted slow linear response to climate change.

The rise and fall of infectious disease in a warmer world

USGS Publications Warehouse

Lafferty, Kevin D.; Mordecai, Erin A.

2016-01-01

Now-outdated estimates proposed that climate change should have increased the number of people at risk of malaria, yet malaria and several other infectious diseases have declined. Although some diseases have increased as the climate has warmed, evidence for widespread climate-driven disease expansion has not materialized, despite increased research attention. Biological responses to warming depend on the non-linear relationships between physiological performance and temperature, called the thermal response curve. This leads performance to rise and fall with temperature. Under climate change, host species and their associated parasites face extinction if they cannot either thermoregulate or adapt by shifting phenology or geographic range. Climate change might also affect disease transmission through increases or decreases in host susceptibility and infective stage (and vector) production, longevity, and pathology. Many other factors drive disease transmission, especially economics, and some change in time along with temperature, making it hard to distinguish whether temperature drives disease or just correlates with disease drivers. Although it is difficult to predict how climate change will affect infectious disease, an ecological approach can help meet the challenge.

The climate response to five trillion tonnes of carbon

NASA Astrophysics Data System (ADS)

Tokarska, Katarzyna B.; Gillett, Nathan P.; Weaver, Andrew J.; Arora, Vivek K.; Eby, Michael

2016-09-01

Concrete actions to curtail greenhouse gas emissions have so far been limited on a global scale, and therefore the ultimate magnitude of climate change in the absence of further mitigation is an important consideration for climate policy. Estimates of fossil fuel reserves and resources are highly uncertain, and the amount used under a business-as-usual scenario would depend on prevailing economic and technological conditions. In the absence of global mitigation actions, five trillion tonnes of carbon (5 EgC), corresponding to the lower end of the range of estimates of the total fossil fuel resource, is often cited as an estimate of total cumulative emissions. An approximately linear relationship between global warming and cumulative CO2 emissions is known to hold up to 2 EgC emissions on decadal to centennial timescales; however, in some simple climate models the predicted warming at higher cumulative emissions is less than that predicted by such a linear relationship. Here, using simulations from four comprehensive Earth system models, we demonstrate that CO2-attributable warming continues to increase approximately linearly up to 5 EgC emissions. These models simulate, in response to 5 EgC of CO2 emissions, global mean warming of 6.4-9.5 °C, mean Arctic warming of 14.7-19.5 °C, and mean regional precipitation increases by more than a factor of four. These results indicate that the unregulated exploitation of the fossil fuel resource could ultimately result in considerably more profound climate changes than previously suggested.

Assessing NARCCAP climate model effects using spatial confidence regions.

PubMed

French, Joshua P; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.

Regional Climate Sensitivity- and Historical-Based Projections to 2100

NASA Astrophysics Data System (ADS)

Hébert, Raphaël.; Lovejoy, Shaun

2018-05-01

Reliable climate projections at the regional scale are needed in order to evaluate climate change impacts and inform policy. We develop an alternative method for projections based on the transient climate sensitivity (TCS), which relies on a linear relationship between the forced temperature response and the strongly increasing anthropogenic forcing. The TCS is evaluated at the regional scale (5° by 5°), and projections are made accordingly to 2100 using the high and low Representative Concentration Pathways emission scenarios. We find that there are large spatial discrepancies between the regional TCS from 5 historical data sets and 32 global climate model (GCM) historical runs and furthermore that the global mean GCM TCS is about 15% too high. Given that the GCM Representative Concentration Pathway scenario runs are mostly linear with respect to their (inadequate) TCS, we conclude that historical methods of regional projection are better suited given that they are directly calibrated on the real world (historical) climate.

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

Treesearch

Seth J. Wenger; Nicholas A. Som; Daniel C. Dauwalter; Daniel J. Isaak; Helen M. Neville; Charles H. Luce; Jason B. Dunham; Michael K. Young; Kurt D. Fausch; Bruce E. Rieman

2013-01-01

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing...

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming

USGS Publications Warehouse

Euskirchen, E.S.; McGuire, A.D.; Chapin, F.S.

2007-01-01

The warming associated with changes in snow cover in northern high-latitude terrestrial regions represents an important energy feedback to the climate system. Here, we simulate snow cover-climate feedbacks (i.e. changes in snow cover on atmospheric heating) across the Pan-arctic over two distinct warming periods during the 20th century, 1910-1940 and 1970-2000. We offer evidence that increases in snow cover-climate feedbacks during 1970-2000 were nearly three times larger than during 1910-1940 because the recent snow-cover change occurred in spring, when radiation load is highest, rather than in autumn. Based on linear regression analysis, we also detected a greater sensitivity of snow cover-climate feedbacks to temperature trends during the more recent time period. Pan-arctic vegetation types differed substantially in snow cover-climate feedbacks. Those with a high seasonal contrast in albedo, such as tundra, showed much larger changes in atmospheric heating than did those with a low seasonal contrast in albedo, such as forests, even if the changes in snow-cover duration were similar across the vegetation types. These changes in energy exchange warrant careful consideration in studies of climate change, particularly with respect to associated shifts in vegetation between forests, grasslands, and tundra. ?? 2007 Blackwell Publishing Ltd.

Functional linear models to test for differences in prairie wetland hydraulic gradients

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

Shifts in water availability mediate plant-pollinator interactions.

PubMed

Gallagher, M Kate; Campbell, Diane R

2017-07-01

Altered precipitation patterns associated with anthropogenic climate change are expected to have many effects on plants and insect pollinators, but it is unknown if effects on pollination are mediated by changes in water availability. We tested the hypothesis that impacts of climate on plant-pollinator interactions operate through changes in water availability, and specifically that such effects occur through alteration of floral attractants. We manipulated water availability in two naturally occurring Mertensia ciliata (Boraginaceae) populations using water addition, water reduction and control plots and measured effects on vegetative and floral traits, pollinator visitation and seed set. While most floral trait values, including corolla size and nectar, increased linearly with increasing water availability, in this bumblebee-pollinated species, pollinator visitation peaked at intermediate water levels. Visitation also peaked at an intermediate corolla length, while its relationship to corolla width varied across sites. Seed set, however, increased linearly with water. These results demonstrate the potential for changes in water availability to impact plant-pollinator interactions through pollinator responses to differences in floral attractants, and that the effects of water on pollinator visitation can be nonlinear. Plant responses to changes in resource availability may be an important mechanism by which climate change will affect species interactions. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

Nonlinear flowering responses to climate: are species approaching their limits of phenological change?

PubMed

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

2013-08-19

Many alpine and subalpine plant species exhibit phenological advancements in association with earlier snowmelt. While the phenology of some plant species does not advance beyond a threshold snowmelt date, the prevalence of such threshold phenological responses within plant communities is largely unknown. We therefore examined the shape of flowering phenology responses (linear versus nonlinear) to climate using two long-term datasets from plant communities in snow-dominated environments: Gothic, CO, USA (1974-2011) and Zackenberg, Greenland (1996-2011). For a total of 64 species, we determined whether a linear or nonlinear regression model best explained interannual variation in flowering phenology in response to increasing temperatures and advancing snowmelt dates. The most common nonlinear trend was for species to flower earlier as snowmelt advanced, with either no change or a slower rate of change when snowmelt was early (average 20% of cases). By contrast, some species advanced their flowering at a faster rate over the warmest temperatures relative to cooler temperatures (average 5% of cases). Thus, some species seem to be approaching their limits of phenological change in response to snowmelt but not temperature. Such phenological thresholds could either be a result of minimum springtime photoperiod cues for flowering or a slower rate of adaptive change in flowering time relative to changing climatic conditions.

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.

Convergence and contrast in the community structure of Bacteria, Fungi and Archaea along a tropical elevation-climate gradient.

PubMed

Peay, Kabir G; von Sperber, Christian; Cardarelli, Emily; Toju, Hirokazu; Francis, Christopher A; Chadwick, Oliver A; Vitousek, Peter M

2017-05-01

Changes in species richness along climatological gradients have been instrumental in developing theories about the general drivers of biodiversity. Previous studies on microbial communities along climate gradients on mountainsides have revealed positive, negative and neutral richness trends. We examined changes in richness and composition of Fungi, Bacteria and Archaea in soil along a 50-1000 m elevation, 280-3280 mm/yr precipitation gradient in Hawai'i. Soil properties and their drivers are exceptionally well understood along this gradient. All three microbial groups responded strongly to the gradient, with community ordinations being similar along axes of environmental conditions (pH, rainfall) and resource availability (nitrogen, phosphorus). However, the form of the richness-climate relationship varied between Fungi (positive linear), Bacteria (unimodal) and Archaea (negative linear). These differences were related to resource-ecology and limiting conditions for each group, with fungal richness increasing most strongly with soil carbon, ammonia-oxidizing Archaea increasing with nitrogen mineralization rate, and Bacteria increasing with both carbon and pH. Reponses to the gradient became increasingly variable at finer taxonomic scales and within any taxonomic group most individual OTUs occurred in narrow climate-elevation ranges. These results show that microbial responses to climate gradients are heterogeneous due to complexity of underlying environmental changes and the diverse ecologies of microbial taxa. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Sensitivity of Regulated Flow Regimes to Climate Change in the Western United States

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

Zhou, Tian; Voisin, Nathalie; Leng, Guoyong

Water management activities or flow regulations modify water fluxes at the land surface and affect water resources in space and time. We hypothesize that flow regulations change the sensitivity of river flow to climate change with respect to unmanaged water resources. Quantifying these changes in sensitivity could help elucidate the impacts of water management at different spatiotemporal scales and inform climate adaptation decisions. In this study, we compared the emergence of significant changes in natural and regulated river flow regimes across the Western United States from simulations driven by multiple climate models and scenarios. We find that significant climate change-inducedmore » alterations in natural flow do not cascade linearly through water management activities. At the annual time scale, 50% of the Hydrologic Unit Code 4 (HUC4) sub-basins over the Western U.S. regions tend to have regulated flow regime more sensitive to the climate change than natural flow regime. Seasonality analyses show that the sensitivity varies remarkably across the seasons. We also find that the sensitivity is related to the level of water management. For 35% of the HUC4 sub-basins with the highest level of water management, the summer and winter flows tend to show a heightened sensitivity to climate change due to the complexity of joint reservoir operations. We further demonstrate that the impacts of considering water management in models are comparable to those that arises from uncertainties across climate models and emission scenarios. This prompts further climate adaptation studies research about nonlinearity effects of climate change through water management activities.« less

Weighting climate model projections using observational constraints.

PubMed

Gillett, Nathan P

2015-11-13

Projected climate change integrates the net response to multiple climate feedbacks. Whereas existing long-term climate change projections are typically based on unweighted individual climate model simulations, as observed climate change intensifies it is increasingly becoming possible to constrain the net response to feedbacks and hence projected warming directly from observed climate change. One approach scales simulated future warming based on a fit to observations over the historical period, but this approach is only accurate for near-term projections and for scenarios of continuously increasing radiative forcing. For this reason, the recent Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) included such observationally constrained projections in its assessment of warming to 2035, but used raw model projections of longer term warming to 2100. Here a simple approach to weighting model projections based on an observational constraint is proposed which does not assume a linear relationship between past and future changes. This approach is used to weight model projections of warming in 2081-2100 relative to 1986-2005 under the Representative Concentration Pathway 4.5 forcing scenario, based on an observationally constrained estimate of the Transient Climate Response derived from a detection and attribution analysis. The resulting observationally constrained 5-95% warming range of 0.8-2.5 K is somewhat lower than the unweighted range of 1.1-2.6 K reported in the IPCC AR5. © 2015 The Authors.

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

DOE PAGES

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; ...

2017-01-01

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6.

NASA Technical Reports Server (NTRS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Helene; Douville, Herve; Good, Peter; Kay, Jennifer E.;

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

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

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro

Our primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud–climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. But, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions Howmore » does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO 2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO 2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO 2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions. How well do clouds and other relevant variables simulated by models agree with observations?What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?Which models have the most credible representations of processes relevant to the simulation of clouds?How do clouds and their changes interact with other elements of the climate system?« less

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

PubMed

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

2013-01-01

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

Satellite orbit and data sampling requirements

NASA Technical Reports Server (NTRS)

Rossow, William

1993-01-01

Climate forcings and feedbacks vary over a wide range of time and space scales. The operation of non-linear feedbacks can couple variations at widely separated time and space scales and cause climatological phenomena to be intermittent. Consequently, monitoring of global, decadal changes in climate requires global observations that cover the whole range of space-time scales and are continuous over several decades. The sampling of smaller space-time scales must have sufficient statistical accuracy to measure the small changes in the forcings and feedbacks anticipated in the next few decades, while continuity of measurements is crucial for unambiguous interpretation of climate change. Shorter records of monthly and regional (500-1000 km) measurements with similar accuracies can also provide valuable information about climate processes, when 'natural experiments' such as large volcanic eruptions or El Ninos occur. In this section existing satellite datasets and climate model simulations are used to test the satellite orbits and sampling required to achieve accurate measurements of changes in forcings and feedbacks at monthly frequency and 1000 km (regional) scale.

Changes in extremes due to half a degree warming in observations and models

NASA Astrophysics Data System (ADS)

Fischer, E. M.; Schleussner, C. F.; Pfleiderer, P.

2017-12-01

Assessing the climate impacts of half-a-degree warming increments is high on the post-Paris science agenda. Discriminating those effects is particularly challenging for climate extremes such as heavy precipitation and heat extremes for which model uncertainties are generally large, and for which internal variability is so important that it can easily offset or strongly amplify the forced local changes induced by half a degree warming. Despite these challenges we provide evidence for large-scale changes in the intensity and frequency of climate extremes due to half a degree warming. We first assess the difference in extreme climate indicators in observational data for the 1960s and 1970s versus the recent past, two periods differ by half a degree. We identify distinct differences for the global and continental-scale occurrence of heat and heavy precipitation extremes. We show that those observed changes in heavy precipitation and heat extremes broadly agree with simulated historical differences and are informative for the projected differences between 1.5 and 2°C warming despite different radiative forcings. We therefore argue that evidence from the observational record can inform the debate about discernible climate impacts in the light of model uncertainty by providing a conservative estimate of the implications of 0.5°C warming. A limitation of using the observational record arises from potential non-linearities in the response of climate extremes to a certain level of warming. We test for potential non-linearities in the response of heat and heavy precipitation extremes in a large ensemble of transient climate simulations. We further quantify differences between a time-window approach in a coupled model large ensemble vs. time-slice experiments using prescribed SST experiments performed in the context of the HAPPI-MIP project. Thereby we provide different lines of evidence that half a degree warming leads to substantial changes in the expected occurrence of heat and heavy precipitation extremes.

Effect of Climate Change on Soil Temperature in Swedish Boreal Forests

PubMed Central

Jungqvist, Gunnar; Oni, Stephen K.; Teutschbein, Claudia; Futter, Martyn N.

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions. PMID:24747938

Effect of climate change on soil temperature in Swedish boreal forests.

PubMed

Jungqvist, Gunnar; Oni, Stephen K; Teutschbein, Claudia; Futter, Martyn N

2014-01-01

Complex non-linear relationships exist between air and soil temperature responses to climate change. Despite its influence on hydrological and biogeochemical processes, soil temperature has received less attention in climate impact studies. Here we present and apply an empirical soil temperature model to four forest sites along a climatic gradient of Sweden. Future air and soil temperature were projected using an ensemble of regional climate models. Annual average air and soil temperatures were projected to increase, but complex dynamics were projected on a seasonal scale. Future changes in winter soil temperature were strongly dependent on projected snow cover. At the northernmost site, winter soil temperatures changed very little due to insulating effects of snow cover but southern sites with little or no snow cover showed the largest projected winter soil warming. Projected soil warming was greatest in the spring (up to 4°C) in the north, suggesting earlier snowmelt, extension of growing season length and possible northward shifts in the boreal biome. This showed that the projected effects of climate change on soil temperature in snow dominated regions are complex and general assumptions of future soil temperature responses to climate change based on air temperature alone are inadequate and should be avoided in boreal regions.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

The role of climatic variables in winter cereal yields: a retrospective analysis.

PubMed

Luo, Qunying; Wen, Li

2015-02-01

This study examined the effects of observed climate including [CO2] on winter cereal [winter wheat (Triticum aestivum), barley (Hordeum vulgare) and oat (Avena sativa)] yields by adopting robust statistical analysis/modelling approaches (i.e. autoregressive fractionally integrated moving average, generalised addition model) based on long time series of historical climate data and cereal yield data at three locations (Moree, Dubbo and Wagga Wagga) in New South Wales, Australia. Research results show that (1) growing season rainfall was significantly, positively and non-linearly correlated with crop yield at all locations considered; (2) [CO2] was significantly, positively and non-linearly correlated with crop yields in all cases except wheat and barley yields at Wagga Wagga; (3) growing season maximum temperature was significantly, negatively and non-linearly correlated with crop yields at Dubbo and Moree (except for barley); and (4) radiation was only significantly correlated with oat yield at Wagga Wagga. This information will help to identify appropriate management adaptation options in dealing with the risk and in taking the opportunities of climate change.

Do Quercus ilex woodlands undergo abrupt non-linear functional changes in response to human disturbance along a climatic gradient?

NASA Astrophysics Data System (ADS)

Bochet, Esther; García-Fayos, Patricio; José Molina, Maria; Moreno de las Heras, Mariano; Espigares, Tíscar; Nicolau, Jose Manuel; Monleon, Vicente

2017-04-01

Theoretical models predict that drylands are particularly prone to suffer critical transitions with abrupt non-linear changes in their structure and functions as a result of the existing complex interactions between climatic fluctuations and human disturbances. However, so far, few studies provide empirical data to validate these models. We aim at determining how holm oak (Quercus ilex) woodlands undergo changes in their functions in response to human disturbance along an aridity gradient (from semi-arid to sub-humid conditions), in eastern Spain. For that purpose, we used (a) remote-sensing estimations of precipitation-use-efficiency (PUE) from enhanced vegetation index (EVI) observations performed in 231x231 m plots of the Moderate Resolution Imaging Spectroradiometer (MODIS); (b) biological and chemical soil parameter determinations (extracellular soil enzyme activity, soil respiration, nutrient cycling processes) from soil sampled in the same plots; (c) vegetation parameter determinations (ratio of functional groups) from vegetation surveys performed in the same plots. We analyzed and compared the shape of the functional change (in terms of PUE and soil and vegetation parameters) in response to human disturbance intensity for our holm oak sites along the aridity gradient. Overall, our results evidenced important differences in the shape of the functional change in response to human disturbance between climatic conditions. Semi-arid areas experienced a more accelerated non-linear decrease with an increasing disturbance intensity than sub-humid ones. The proportion of functional groups (herbaceous vs. woody cover) played a relevant role in the shape of the functional response of the holm oak sites to human disturbance.

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

PubMed Central

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

2013-01-01

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

Thermohaline circulation and its box models simulation

NASA Astrophysics Data System (ADS)

Bazyura, Kateryna; Polonsky, Alexander; Sannikov, Viktor

2014-05-01

Ocean Thermochaline circulation (THC) is the part of large-scale World Ocean circulation and one of the main climate system components. It is generated by global meridional density gradients, which are controlled by surface heat and freshwater fluxes. THC regulates climate variability on different timescales (from decades to thousands years) [Stocker (2000), Clark (2002)]. Study of paleoclimatic evidences of abrupt and dramatic changes in ocean-atmosphere system in the past (such as, Dansgaard-Oeschger and Heinrich events or Younger Dryas, see e.g., [Rahmstorf (2002), Alley & Clark(1999)]) shows that these events are connected with THC regimes. At different times during last 120,000 years, three THC modes have prevailed in the Atlantic. They can be labeled as stadial, interstadial and Heinrich modes or as cold, warm and off mode. THC collapse (or thermohaline catastrophe) can be one of the consequences of global warming (including modern anthropogenic climate changes occurring at the moment). The ideas underlying different box-model studies, possibility of thermochaline catastrophe in present and past are discussed in this presentation. Response of generalized four box model of North Atlantic thermohaline circulation [developing the model of Griffies & Tzippermann (1995)] on periodic, stochastic and linear forcing is studied in details. To estimate climatic parameters of the box model we used monthly salinity and temperature data of ECMWF operational Ocean Reanalysis System 3 (ORA-S3) and data from atmospheric NCEP/NCAR reanalysis on precipitation, and heat fluxes for 1959-2011. Mean values, amplitude of seasonal cycle, amplitudes and periods of typical interdecadal oscillations, white noise level, linear trend coefficients and their significance level were estimated for every hydrophysical parameter. In response to intense freshwater or heat forcing, THC regime can change resulting in thermohaline catastrophe. We analyze relevant thresholds of external forcing in cases of using linear and nonlinear seawater state equation. In the frame of four-box model it is shown that: 1) The occurrence of the thermohaline catastrophe, which is likely happened at Younger Dryas period or developed as Heinrich events in the past, is improbable in modern climate epoch. 2) Choice of nonlinear seawater equitation of state leads to stabilization of warm mode of THC, which corresponds to modern climate state. 3) Typical white noise in heat and freshwater fluxes leads to generation of multidecadal oscillations of volume transport. Time-scale of these oscillations coincides with Atlantic Multidecadal oscillation periodicity. So, it is shown that that recent climate is characterized by quasi-periodical stable multidecadal THC warm regime. Stocker, T. F., 2000: Past and future reorganisations in the climate system. Quat. Sci.Rev, Vol. 19, P.301-319. Clark U., 2002: The role of the thermohaline circulation in abrupt climate change. Nature. Vol. 415, P.863-869. Rahmstorf S., 2002: Ocean circulation and climate during the past 120000 years. Nature. Vol. 419, P.207-214. Alley, R. B. & Clark, P. U., 1999: The deglaciation of the Northern Hemisphere: a global perspective. Annu.Rev. Earth Planet. Sci. Vol. 27, P.149-182. Griffies S.M., Tziperman E., 1995: A linear thermohaline oscillator driven by stochastic atmospheric forcing. Journal of Climate. Vol. 8. P. 2440-2453.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

Soares dos Santos, T.; Mendes, D.; Rodrigues Torres, R.

2016-01-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANNs) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon; northeastern Brazil; and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model output and observed monthly precipitation. We used general circulation model (GCM) experiments for the 20th century (RCP historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANNs significantly outperform the MLR downscaling of monthly precipitation variability.

Artificial neural networks and multiple linear regression model using principal components to estimate rainfall over South America

NASA Astrophysics Data System (ADS)

dos Santos, T. S.; Mendes, D.; Torres, R. R.

2015-08-01

Several studies have been devoted to dynamic and statistical downscaling for analysis of both climate variability and climate change. This paper introduces an application of artificial neural networks (ANN) and multiple linear regression (MLR) by principal components to estimate rainfall in South America. This method is proposed for downscaling monthly precipitation time series over South America for three regions: the Amazon, Northeastern Brazil and the La Plata Basin, which is one of the regions of the planet that will be most affected by the climate change projected for the end of the 21st century. The downscaling models were developed and validated using CMIP5 model out- put and observed monthly precipitation. We used GCMs experiments for the 20th century (RCP Historical; 1970-1999) and two scenarios (RCP 2.6 and 8.5; 2070-2100). The model test results indicate that the ANN significantly outperforms the MLR downscaling of monthly precipitation variability.

Towards a threshold climate for emergency lower respiratory hospital admissions.

PubMed

Islam, Muhammad Saiful; Chaussalet, Thierry J; Koizumi, Naoru

2017-02-01

Identification of 'cut-points' or thresholds of climate factors would play a crucial role in alerting risks of climate change and providing guidance to policymakers. This study investigated a 'Climate Threshold' for emergency hospital admissions of chronic lower respiratory diseases by using a distributed lag non-linear model (DLNM). We analysed a unique longitudinal dataset (10 years, 2000-2009) on emergency hospital admissions, climate, and pollution factors for the Greater London. Our study extends existing work on this topic by considering non-linearity, lag effects between climate factors and disease exposure within the DLNM model considering B-spline as smoothing technique. The final model also considered natural cubic splines of time since exposure and 'day of the week' as confounding factors. The results of DLNM indicated a significant improvement in model fitting compared to a typical GLM model. The final model identified the thresholds of several climate factors including: high temperature (≥27°C), low relative humidity (≤ 40%), high Pm10 level (≥70-µg/m 3 ), low wind speed (≤ 2 knots) and high rainfall (≥30mm). Beyond the threshold values, a significantly higher number of emergency admissions due to lower respiratory problems would be expected within the following 2-3 days after the climate shift in the Greater London. The approach will be useful to initiate 'region and disease specific' climate mitigation plans. It will help identify spatial hot spots and the most sensitive areas and population due to climate change, and will eventually lead towards a diversified health warning system tailored to specific climate zones and populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Assessing NARCCAP climate model effects using spatial confidence regions

PubMed Central

French, Joshua P.; McGinnis, Seth; Schwartzman, Armin

2017-01-01

We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference. PMID:28936474

Sink or Swim: Adapting to the Hydrologic Impacts of Climate Change

NASA Astrophysics Data System (ADS)

Gleick, P. H.

2014-12-01

Climate changes lead to a wide range of societal and environmental impacts; indeed, strong evidence has accrued that such impacts are already occurring, as summarized by the newest National Climate Assessment and other analyses. Among the most important will be alterations in the hydrologic cycle, changes in water supply and demand, and impacts on existing water-related infrastructure. Because of the complexity of our water systems, adaptation responses will be equally complex. This problem has made it difficult for water managers and planners to develop and implement adaptation strategies. This talk will address three ways to think about water-related adaptation approaches to climate change: (1) strategies that are already being implemented to address population and economic changes without climate change; (2) whether these first-line strategies are appropriate for additional impacts that might result from climatic changes; and (3) new approaches that might be necessary for new, non-linear, or threshold impacts. An effort will also be made to differentiate between adaptation strategies that influence the hydrologic cycle directly (e.g., cloud seeding), those that influence supply management (e.g., construction of additional reservoirs or water-distribution systems), and those that affect water demand (e.g., removal of outdoor landscaping, installation of efficient irrigation systems).

Changes in ENSO amplitude under climate warming and cooling

NASA Astrophysics Data System (ADS)

Wang, Yingying; Luo, Yiyong; Lu, Jian; Liu, Fukai

2018-05-01

The response of ENSO amplitude to climate warming and cooling is investigated using the Community Earth System Model (CESM), in which the warming and cooling scenarios are designed by adding heat fluxes of equal amplitude but opposite sign onto the ocean surface, respectively. Results show that the warming induces an increase of the ENSO amplitude but the cooling gives rise to a decrease of the ENSO amplitude, and these changes are robust in statistics. A mixed layer heat budget analysis finds that the increasing (decreasing) SST tendency under climate warming (cooling) is mainly due to an enhancement (weakening) of dynamical feedback processes over the equatorial Pacific, including zonal advective (ZA) feedback, meridional advective (MA) feedback, thermocline (TH) feedback, and Ekman (EK) feedback. As the climate warms, a wind anomaly of the same magnitude across the equatorial Pacific can induce a stronger zonal current change in the east (i.e., a stronger ZA feedback), which in turn produces a greater weakening of upwelling (i.e., a stronger EK feedback) and thus a larger thermocline change (i.e., a stronger TH feedback). In response to the climate warming, in addition, the MA feedback is also strengthened due to an enhancement of the meridional SST gradient around the equator resulting from a weakening of the subtropical cells (STCs). It should be noted that the weakened STCs itself has a negative contribution to the change of the MA feedback which, however, appears to be secondary. And vice versa for the cooling case. Bjerknes linear stability (BJ) index is also evaluated for the linear stability of ENSO, with remarkably larger (smaller) BJ index found for the warming (cooling) case.

Water resources sensitivity to the isolated effects of land use, water demand and climate change under 2 degree global warming

NASA Astrophysics Data System (ADS)

Bisselink, Berny; Bernhard, Jeroen; de Roo, Ad

2017-04-01

One of the key impacts of global change are the future water resources. These water resources are influenced by changes in land use (LU), water demand (WD) and climate change. Recent developments in scenario modelling opened new opportunities for an integrated assessment. However, for identifying water resource management strategies it is helpful to focus on the isolated effects of possible changes in LU, WD and climate that may occur in the near future. In this work, we quantify the isolated contribution of LU, WD and climate to the integrated total water resources assuming a linear model behavior. An ensemble of five EURO-CORDEX RCP8.5 climate projections for the 31-year periods centered on the year of exceeding the global-mean temperature of 2 degree is used to drive the fully distributed hydrological model LISFLOOD for multiple river catchments in Europe. The JRC's Land Use Modelling Platform LUISA was used to obtain a detailed pan-European reference land use scenario until 2050. Water demand is estimated based on socio-economic (GDP, population estimates etc.), land use and climate projections as well. For each climate projection, four model runs have been performed including an integrated (LU, WD and climate) simulation and other three simulations to isolate the effect of LU, WD and climate. Changes relative to the baseline in terms of water resources indicators of the ensemble means of the 2 degree warming period and their associated uncertainties will reveal the integrated and isolated effect of LU, WD and climate change on water resources.

Testing a multi-malaria-model ensemble against 30 years of data in the Kenyan highlands

PubMed Central

2014-01-01

Background Multi-model ensembles could overcome challenges resulting from uncertainties in models’ initial conditions, parameterization and structural imperfections. They could also quantify in a probabilistic way uncertainties in future climatic conditions and their impacts. Methods A four-malaria-model ensemble was implemented to assess the impact of long-term changes in climatic conditions on Plasmodium falciparum malaria morbidity observed in Kericho, in the highlands of Western Kenya, over the period 1979–2009. Input data included quality controlled temperature and rainfall records gathered at a nearby weather station over the historical periods 1979–2009 and 1980–2009, respectively. Simulations included models’ sensitivities to changes in sets of parameters and analysis of non-linear changes in the mean duration of host’s infectivity to vectors due to increased resistance to anti-malarial drugs. Results The ensemble explained from 32 to 38% of the variance of the observed P. falciparum malaria incidence. Obtained R2-values were above the results achieved with individual model simulation outputs. Up to 18.6% of the variance of malaria incidence could be attributed to the +0.19 to +0.25°C per decade significant long-term linear trend in near-surface air temperatures. On top of this 18.6%, at least 6% of the variance of malaria incidence could be related to the increased resistance to anti-malarial drugs. Ensemble simulations also suggest that climatic conditions have likely been less favourable to malaria transmission in Kericho in recent years. Conclusions Long-term changes in climatic conditions and non-linear changes in the mean duration of host’s infectivity are synergistically driving the increasing incidence of P. falciparum malaria in the Kenyan highlands. User-friendly, online-downloadable, open source mathematical tools, such as the one presented here, could improve decision-making processes of local and regional health authorities. PMID:24885824

Seasonal climate change patterns due to cumulative CO 2 emissions

DOE PAGES

Partanen, Antti-Ilari; Leduc, Martin; Matthews, H. Damon

2017-06-28

Cumulative CO 2 emissions are near linearly related to both global and regional changes in annual-mean surface temperature. These relationships are known as the transient climate response to cumulative CO 2 emissions (TCRE) and the regional TCRE (RTCRE), and have been shown to remain approximately constant over a wide range of cumulative emissions. Here, we assessed how well this relationship holds for seasonal patterns of temperature change, as well as for annual-mean and seasonal precipitation patterns. We analyzed an idealized scenario with CO 2 concentration growing at an annual rate of 1% using data from 12 Earth system models frommore » the Coupled Model Intercomparison Project Phase 5 (CMIP5). Seasonal RTCRE values for temperature varied considerably, with the highest seasonal variation evident in the Arctic, where RTCRE was about 5.5 °C per Tt C for boreal winter and about 2.0 °C per Tt C for boreal summer. Also the precipitation response in the Arctic during boreal winter was stronger than during other seasons. We found that emission-normalized seasonal patterns of temperature change were relatively robust with respect to time, though they were sub-linear with respect to emissions particularly near the Arctic. Moreover, RTCRE patterns for precipitation could not be quantified robustly due to the large internal variability of precipitation. Here, our results suggest that cumulative CO 2 emissions are a useful metric to predict regional and seasonal changes in precipitation and temperature. This extension of the TCRE framework to seasonal and regional climate change is helpful for communicating the link between emissions and climate change to policy-makers and the general public, and is well-suited for impact studies that could make use of estimated regional-scale climate changes that are consistent with the carbon budgets associated with global temperature targets.« less

Seasonal climate change patterns due to cumulative CO 2 emissions

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

Partanen, Antti-Ilari; Leduc, Martin; Matthews, H. Damon

Cumulative CO 2 emissions are near linearly related to both global and regional changes in annual-mean surface temperature. These relationships are known as the transient climate response to cumulative CO 2 emissions (TCRE) and the regional TCRE (RTCRE), and have been shown to remain approximately constant over a wide range of cumulative emissions. Here, we assessed how well this relationship holds for seasonal patterns of temperature change, as well as for annual-mean and seasonal precipitation patterns. We analyzed an idealized scenario with CO 2 concentration growing at an annual rate of 1% using data from 12 Earth system models frommore » the Coupled Model Intercomparison Project Phase 5 (CMIP5). Seasonal RTCRE values for temperature varied considerably, with the highest seasonal variation evident in the Arctic, where RTCRE was about 5.5 °C per Tt C for boreal winter and about 2.0 °C per Tt C for boreal summer. Also the precipitation response in the Arctic during boreal winter was stronger than during other seasons. We found that emission-normalized seasonal patterns of temperature change were relatively robust with respect to time, though they were sub-linear with respect to emissions particularly near the Arctic. Moreover, RTCRE patterns for precipitation could not be quantified robustly due to the large internal variability of precipitation. Here, our results suggest that cumulative CO 2 emissions are a useful metric to predict regional and seasonal changes in precipitation and temperature. This extension of the TCRE framework to seasonal and regional climate change is helpful for communicating the link between emissions and climate change to policy-makers and the general public, and is well-suited for impact studies that could make use of estimated regional-scale climate changes that are consistent with the carbon budgets associated with global temperature targets.« less

A global assessment of climate-water quality relationships in large rivers: an elasticity perspective.

PubMed

Jiang, Jiping; Sharma, Ashish; Sivakumar, Bellie; Wang, Peng

2014-01-15

To uncover climate-water quality relationships in large rivers on a global scale, the present study investigates the climate elasticity of river water quality (CEWQ) using long-term monthly records observed at 14 large rivers. Temperature and precipitation elasticities of 12 water quality parameters, highlighted by N- and P-nutrients, are assessed. General observations on elasticity values show the usefulness of this approach to describe the magnitude of stream water quality responses to climate change, which improves that of simple statistical correlation. Sensitivity type, intensity and variability rank of CEWQ are reported and specific characteristics and mechanism of elasticity of nutrient parameters are also revealed. Among them, the performance of ammonia, total phosphorus-air temperature models, and nitrite, orthophosphorus-precipitation models are the best. Spatial and temporal assessment shows that precipitation elasticity is more variable in space than temperature elasticity and that seasonal variation is more evident for precipitation elasticity than for temperature elasticity. Moreover, both anthropogenic activities and environmental factors are found to impact CEWQ for select variables. The major relationships that can be inferred include: (1) human population has a strong linear correlation with temperature elasticity of turbidity and total phosphorus; and (2) latitude has a strong linear correlation with precipitation elasticity of turbidity and N nutrients. As this work improves our understanding of the relation between climate factors and surface water quality, it is potentially helpful for investigating the effect of climate change on water quality in large rivers, such as on the long-term change of nutrient concentrations. © 2013.

The economic impact of climate change on Kenyan crop agriculture: A Ricardian approach

NASA Astrophysics Data System (ADS)

Kabubo-Mariara, Jane; Karanja, Fredrick K.

2007-06-01

This paper measures the economic impact of climate on crops in Kenya. We use cross-sectional data on climate, hydrological, soil and household level data for a sample of 816 households. We estimate a seasonal Ricardian model to assess the impact of climate on net crop revenue per acre. The results show that climate affects crop productivity. There is a non-linear relationship between temperature and revenue on one hand and between precipitation and revenue on the other. Estimated marginal impacts suggest that global warming is harmful for crop productivity. Predictions from global circulation models confirm that global warming will have a substantial impact on net crop revenue in Kenya. The results also show that the temperature component of global warming is much more important than precipitation. Findings call for monitoring of climate change and dissemination of information to farmers to encourage adaptations to climate change. Improved management and conservation of available water resources, water harvesting and recycling of wastewater could generate water for irrigation purposes especially in the arid and semi-arid areas.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Uncertainties associated with quantifying climate change impacts on human health: a case study for diarrhea.

PubMed

Kolstad, Erik W; Johansson, Kjell Arne

2011-03-01

Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8-11% (with SDs of 3-5%) by 2010-2039 and 22-29% (SDs of 9-12%) by 2070-2099. Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate-health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health.

Effects of local adaptation and interspecific competition on species' responses to climate change.

PubMed

Bocedi, Greta; Atkins, Katherine E; Liao, Jishan; Henry, Roslyn C; Travis, Justin M J; Hellmann, Jessica J

2013-09-01

Local adaptation and species interactions have been shown to affect geographic ranges; therefore, we need models of climate impact that include both factors. To identify possible dynamics of species when including these factors, we ran simulations of two competing species using an individual-based, coupled map-lattice model using a linear climatic gradient that varies across latitude and is warmed over time. Reproductive success is governed by an individual's adaptation to local climate as well as its location relative to global constraints. In exploratory experiments varying the strength of adaptation and competition, competition reduces genetic diversity and slows range change, although the two species can coexist in the absence of climate change and shift in the absence of competitors. We also found that one species can drive the other to extinction, sometimes long after climate change ends. Weak selection on local adaptation and poor dispersal ability also caused surfing of cooler-adapted phenotypes from the expanding margin backwards, causing loss of warmer-adapted phenotypes. Finally, geographic ranges can become disjointed, losing centrally-adapted genotypes. These initial results suggest that the interplay between local adaptation and interspecific competition can significantly influence species' responses to climate change, in a way that demands future research. © 2013 New York Academy of Sciences.

Test Plan for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; Hair, Jason; McAndrew, Brendan; Daw, Adrian; Jennings, Donald; Rabin, Douglas

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe high-accuracy, long-term climate change trends and to use decadal change observations as the most critical method to determine the accuracy of climate change. One of the major objectives of CLARREO is to advance the accuracy of SI traceable absolute calibration at infrared and reflected solar wavelengths. This advance is required to reach the on-orbit absolute accuracy required to allow climate change observations to survive data gaps while remaining sufficiently accurate to observe climate change to within the uncertainty of the limit of natural variability. While these capabilities exist at NIST in the laboratory, there is a need to demonstrate that it can move successfully from NIST to NASA and/or instrument vendor capabilities for future spaceborne instruments. The current work describes the test plan for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches , alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result of efforts with the SOLARIS CDS will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections. The CLARREO mission addresses the need to observe high-accuracy, long-term climate change trends and advance the accuracy of SI traceable absolute calibration. The current work describes the test plan for the SOLARIS which is the calibration demonstration system for the reflected solar portion of CLARREO. SOLARIS provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The end result will be an SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climate-quality data collections.

Secondary calcification and dissolution respond differently to future ocean conditions

NASA Astrophysics Data System (ADS)

Silbiger, N. J.; Donahue, M. J.

2015-01-01

Climate change threatens both the accretion and erosion processes that sustain coral reefs. Secondary calcification, bioerosion, and reef dissolution are integral to the structural complexity and long-term persistence of coral reefs, yet these processes have received less research attention than reef accretion by corals. In this study, we use climate scenarios from RCP 8.5 to examine the combined effects of rising ocean acidity and sea surface temperature (SST) on both secondary calcification and dissolution rates of a natural coral rubble community using a flow-through aquarium system. We found that secondary reef calcification and dissolution responded differently to the combined effect of pCO2 and temperature. Calcification had a non-linear response to the combined effect of pCO2 and temperature: the highest calcification rate occurred slightly above ambient conditions and the lowest calcification rate was in the highest temperature-pCO2 condition. In contrast, dissolution increased linearly with temperature-pCO2 . The rubble community switched from net calcification to net dissolution at +271 μatm pCO2 and 0.75 °C above ambient conditions, suggesting that rubble reefs may shift from net calcification to net dissolution before the end of the century. Our results indicate that (i) dissolution may be more sensitive to climate change than calcification and (ii) that calcification and dissolution have different functional responses to climate stressors; this highlights the need to study the effects of climate stressors on both calcification and dissolution to predict future changes in coral reefs.

Secondary calcification and dissolution respond differently to future ocean conditions

NASA Astrophysics Data System (ADS)

Silbiger, N. J.; Donahue, M. J.

2014-09-01

Climate change threatens both the accretion and erosion processes that sustain coral reefs. Secondary calcification, bioerosion, and reef dissolution are integral to the structural complexity and long-term persistence of coral reefs, yet these processes have received less research attention than reef accretion by corals. In this study, we use climate scenarios from RCP8.5 to examine the combined effects of rising ocean acidity and SST on both secondary calcification and dissolution rates of a natural coral rubble community using a flow-through aquarium system. We found that secondary reef calcification and dissolution responded differently to the combined effect of pCO2 and temperature. Calcification had a non-linear response to the combined effect of pCO2-temperature: the highest calcification rate occurred slightly above ambient conditions and the lowest calcification rate was in the highest pCO2-temperature condition. In contrast, dissolution increased linearly with pCO2-temperature. The rubble community switched from net calcification to net dissolution at +272 μatm pCO2 and 0.84 °C above ambient conditions, suggesting that rubble reefs may shift from net calcification to net dissolution before the end of the century. Our results indicate that dissolution may be more sensitive to climate change than calcification, and that calcification and dissolution have different functional responses to climate stressors, highlighting the need to study the effects of climate stressors on both calcification and dissolution to predict future changes in coral reefs.

Integrating solar energy and climate research into science education

NASA Astrophysics Data System (ADS)

Betts, Alan K.; Hamilton, James; Ligon, Sam; Mahar, Ann Marie

2016-01-01

This paper analyzes multi-year records of solar flux and climate data from two solar power sites in Vermont. We show the inter-annual differences of temperature, wind, panel solar flux, electrical power production, and cloud cover. Power production has a linear relation to a dimensionless measure of the transmission of sunlight through the cloud field. The difference between panel and air temperatures reaches 24°C with high solar flux and low wind speed. High panel temperatures that occur in summer with low wind speeds and clear skies can reduce power production by as much as 13%. The intercomparison of two sites 63 km apart shows that while temperature is highly correlated on daily (R2=0.98) and hourly (R2=0.94) timescales, the correlation of panel solar flux drops markedly from daily (R2=0.86) to hourly (R2=0.63) timescales. Minimum temperatures change little with cloud cover, but the diurnal temperature range shows a nearly linear increase with falling cloud cover to 16°C under nearly clear skies, similar to results from the Canadian Prairies. The availability of these new solar and climate datasets allows local student groups, a Rutland High School team here, to explore the coupled relationships between climate, clouds, and renewable power production. As our society makes major changes in our energy infrastructure in response to climate change, it is important that we accelerate the technical education of high school students using real-world data.

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.

Public perceptions of climate change and extreme weather events

NASA Astrophysics Data System (ADS)

Bruine de Bruin, W.; Dessai, S.; Morgan, G.; Taylor, A.; Wong-Parodi, G.

2013-12-01

Climate experts face a serious communication challenge. Public debate about climate change continues, even though at the same time people seem to complain about extreme weather events becoming increasingly common. As compared to the abstract concept of ';climate change,' (changes in) extreme weather events are indeed easier to perceive, more vivid, and personally relevant. Public perception research in different countries has suggested that people commonly expect that climate change will lead to increases in temperature, and that unseasonably warm weather is likely to be interpreted as evidence of climate change. However, relatively little is known about whether public concerns about climate change may also be driven by changes in other types of extreme weather events, such as exceptional amounts of precipitation or flooding. We therefore examined how perceptions of and personal experiences with changes in these specific weather events are related to public concerns about climate change. In this presentation, we will discuss findings from two large public perception surveys conducted in flood-prone Pittsburgh, Pennsylvania (US) and with a national sample in the UK, where extreme flooding has recently occurred across the country. Participants completed questions about their perceptions of and experiences with specific extreme weather events, and their beliefs about climate change. We then conducted linear regressions to predict individual differences in climate-change beliefs, using perceptions of and experiences with specific extreme weather events as predictors, while controlling for demographic characteristics. The US study found that people (a) perceive flood chances to be increasing over the decades, (b) believe climate change to play a role in increases in future flood chances, and (c) would interpret future increases in flooding as evidence for climate change. The UK study found that (a) UK residents are more likely to perceive increases in ';wet' events such as flooding and heavy rainfall than in ';hot' events such as heatwaves, (b) perceptions of these ';wet' weather events are more strongly associated with climate-change beliefs than were extremely ';hot' weather events, and (c) personal experiences with the negative consequences of specific extreme weather events are associated with stronger climate-change beliefs. Hence, which specific weather events people interpret as evidence of climate change may depend on their personal perceptions and experiences - which may not involve the temperature increases that are commonly the focus of climate-change communications. Overall, these findings suggest that climate experts should consider focusing their public communications on extreme weather events that are relevant to their intended audience. We will discuss strategies for designing and evaluating communications about climate change and adaptation.

The Cloud Feedback Model Intercomparison Project (CFMIP) contribution to CMIP6

NASA Astrophysics Data System (ADS)

Webb, Mark J.; Andrews, Timothy; Bodas-Salcedo, Alejandro; Bony, Sandrine; Bretherton, Christopher S.; Chadwick, Robin; Chepfer, Hélène; Douville, Hervé; Good, Peter; Kay, Jennifer E.; Klein, Stephen A.; Marchand, Roger; Medeiros, Brian; Pier Siebesma, A.; Skinner, Christopher B.; Stevens, Bjorn; Tselioudis, George; Tsushima, Yoko; Watanabe, Masahiro

2017-01-01

The primary objective of CFMIP is to inform future assessments of cloud feedbacks through improved understanding of cloud-climate feedback mechanisms and better evaluation of cloud processes and cloud feedbacks in climate models. However, the CFMIP approach is also increasingly being used to understand other aspects of climate change, and so a second objective has now been introduced, to improve understanding of circulation, regional-scale precipitation, and non-linear changes. CFMIP is supporting ongoing model inter-comparison activities by coordinating a hierarchy of targeted experiments for CMIP6, along with a set of cloud-related output diagnostics. CFMIP contributes primarily to addressing the CMIP6 questions How does the Earth system respond to forcing? and What are the origins and consequences of systematic model biases? and supports the activities of the WCRP Grand Challenge on Clouds, Circulation and Climate Sensitivity.A compact set of Tier 1 experiments is proposed for CMIP6 to address this question: (1) what are the physical mechanisms underlying the range of cloud feedbacks and cloud adjustments predicted by climate models, and which models have the most credible cloud feedbacks? Additional Tier 2 experiments are proposed to address the following questions. (2) Are cloud feedbacks consistent for climate cooling and warming, and if not, why? (3) How do cloud-radiative effects impact the structure, the strength and the variability of the general atmospheric circulation in present and future climates? (4) How do responses in the climate system due to changes in solar forcing differ from changes due to CO2, and is the response sensitive to the sign of the forcing? (5) To what extent is regional climate change per CO2 doubling state-dependent (non-linear), and why? (6) Are climate feedbacks during the 20th century different to those acting on long-term climate change and climate sensitivity? (7) How do regional climate responses (e.g. in precipitation) and their uncertainties in coupled models arise from the combination of different aspects of CO2 forcing and sea surface warming?CFMIP also proposes a number of additional model outputs in the CMIP DECK, CMIP6 Historical and CMIP6 CFMIP experiments, including COSP simulator outputs and process diagnostics to address the following questions.

1. How well do clouds and other relevant variables simulated by models agree with observations?

2. What physical processes and mechanisms are important for a credible simulation of clouds, cloud feedbacks and cloud adjustments in climate models?

3. Which models have the most credible representations of processes relevant to the simulation of clouds?

4. How do clouds and their changes interact with other elements of the climate system?

The effects of climate change on harp seals (Pagophilus groenlandicus).

PubMed

Johnston, David W; Bowers, Matthew T; Friedlaender, Ari S; Lavigne, David M

2012-01-01

Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data.

The Effects of Climate Change on Harp Seals (Pagophilus groenlandicus)

PubMed Central

Johnston, David W.; Bowers, Matthew T.; Friedlaender, Ari S.; Lavigne, David M.

2012-01-01

Harp seals (Pagophilus groenlandicus) have evolved life history strategies to exploit seasonal sea ice as a breeding platform. As such, individuals are prepared to deal with fluctuations in the quantity and quality of ice in their breeding areas. It remains unclear, however, how shifts in climate may affect seal populations. The present study assesses the effects of climate change on harp seals through three linked analyses. First, we tested the effects of short-term climate variability on young-of-the year harp seal mortality using a linear regression of sea ice cover in the Gulf of St. Lawrence against stranding rates of dead harp seals in the region during 1992 to 2010. A similar regression of stranding rates and North Atlantic Oscillation (NAO) index values was also conducted. These analyses revealed negative correlations between both ice cover and NAO conditions and seal mortality, indicating that lighter ice cover and lower NAO values result in higher mortality. A retrospective cross-correlation analysis of NAO conditions and sea ice cover from 1978 to 2011 revealed that NAO-related changes in sea ice may have contributed to the depletion of seals on the east coast of Canada during 1950 to 1972, and to their recovery during 1973 to 2000. This historical retrospective also reveals opposite links between neonatal mortality in harp seals in the Northeast Atlantic and NAO phase. Finally, an assessment of the long-term trends in sea ice cover in the breeding regions of harp seals across the entire North Atlantic during 1979 through 2011 using multiple linear regression models and mixed effects linear regression models revealed that sea ice cover in all harp seal breeding regions has been declining by as much as 6 percent per decade over the time series of available satellite data. PMID:22238591

Forecasting the effects of land use scenarios on farmland birds reveal a potential mitigation of climate change impacts.

PubMed

Princé, Karine; Lorrillière, Romain; Barbet-Massin, Morgane; Léger, François; Jiguet, Frédéric

2015-01-01

Climate and land use changes are key drivers of current biodiversity trends, but interactions between these drivers are poorly modeled, even though they could amplify or mitigate negative impacts of climate change. Here, we attempt to predict the impacts of different agricultural change scenarios on common breeding birds within farmland included in the potential future climatic suitable areas for these species. We used the Special Report on Emissions Scenarios (SRES) to integrate likely changes in species climatic suitability, based on species distribution models, and changes in area of farmland, based on the IMAGE model, inside future climatic suitable areas. We also developed six farmland cover scenarios, based on expert opinion, which cover a wide spectrum of potential changes in livestock farming and cropping patterns by 2050. We ran generalized linear mixed models to calibrate the effects of farmland cover and climate change on bird specific abundance within 386 small agricultural regions. We used model outputs to predict potential changes in bird populations on the basis of predicted changes in regional farmland cover, in area of farmland and in species climatic suitability. We then examined the species sensitivity according to their habitat requirements. A scenario based on extensification of agricultural systems (i.e., low-intensity agriculture) showed the greatest potential to reduce reverse current declines in breeding birds. To meet ecological requirements of a larger number of species, agricultural policies accounting for regional disparities and landscape structure appear more efficient than global policies uniformly implemented at national scale. Interestingly, we also found evidence that farmland cover changes can mitigate the negative effect of climate change. Here, we confirm that there is a potential for countering negative effects of climate change by adaptive management of landscape. We argue that such studies will help inform sustainable agricultural policies for the future.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections.

PubMed

Junk, J; Ulber, B; Vidal, S; Eickermann, M

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Assessing climate change impacts on the rape stem weevil, Ceutorhynchus napi Gyll., based on bias- and non-bias-corrected regional climate change projections

NASA Astrophysics Data System (ADS)

Junk, J.; Ulber, B.; Vidal, S.; Eickermann, M.

2015-11-01

Agricultural production is directly affected by projected increases in air temperature and changes in precipitation. A multi-model ensemble of regional climate change projections indicated shifts towards higher air temperatures and changing precipitation patterns during the summer and winter seasons up to the year 2100 for the region of Goettingen (Lower Saxony, Germany). A second major controlling factor of the agricultural production is the infestation level by pests. Based on long-term field surveys and meteorological observations, a calibration of an existing model describing the migration of the pest insect Ceutorhynchus napi was possible. To assess the impacts of climate on pests under projected changing environmental conditions, we combined the results of regional climate models with the phenological model to describe the crop invasion of this species. In order to reduce systematic differences between the output of the regional climate models and observational data sets, two different bias correction methods were applied: a linear correction for air temperature and a quantile mapping approach for precipitation. Only the results derived from the bias-corrected output of the regional climate models showed satisfying results. An earlier onset, as well as a prolongation of the possible time window for the immigration of Ceutorhynchus napi, was projected by the majority of the ensemble members.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

Climate change and maize yield in Iowa

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

Xu, Hong; Twine, Tracy E.; Girvetz, Evan

Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less

Climate change and maize yield in Iowa

DOE PAGES

Xu, Hong; Twine, Tracy E.; Girvetz, Evan

2016-05-24

Climate is changing across the world, including the major maize-growing state of Iowa in the USA. To maintain crop yields, farmers will need a suite of adaptation strategies, and choice of strategy will depend on how the local to regional climate is expected to change. Here we predict how maize yield might change through the 21 st century as compared with late 20 th century yields across Iowa, USA, a region representing ideal climate and soils for maize production that contributes substantially to the global maize economy. To account for climate model uncertainty, we drive a dynamic ecosystem model withmore » output from six climate models and two future climate forcing scenarios. Despite a wide range in the predicted amount of warming and change to summer precipitation, all simulations predict a decrease in maize yields from late 20 th century to middle and late 21 st century ranging from 15% to 50%. Linear regression of all models predicts a 6% state-averaged yield decrease for every 1°C increase in warm season average air temperature. When the influence of moisture stress on crop growth is removed from the model, yield decreases either remain the same or are reduced, depending on predicted changes in warm season precipitation. Lastly, our results suggest that even if maize were to receive all the water it needed, under the strongest climate forcing scenario yields will decline by 10-20% by the end of the 21 st century.« less

The frequency response of a coupled ice sheet-ice shelf-ocean system to climate forcing variability

NASA Astrophysics Data System (ADS)

Goldberg, D.; Snow, K.; Jordan, J. R.; Holland, P.; Arthern, R. J.

2017-12-01

Changes at the West Antarctic ice-ocean boundary in recent decades has triggered significant increases in the regions contribution to global sea-level rise, coincident with large scale, and in some cases potentially unstable, grounding line retreat. Much of the induced change is thought to be driven by fluctuations in the oceanic heat available at the ice-ocean boundary, transported on-shelf via warm Circumpolar Deep Water (CDW). However, the processes in which ocean heat drives ice-sheet loss remains poorly understood, with observational studies routinely hindered by the extreme environment notorious to the Antarctic region. In this study we apply a novel synchronous coupled ice-ocean model, developed within the MITgcm, and are thus able to provide detailed insight into the impacts of short time scale (interannual to decadal) climate variability and feedbacks within the ice-ocean system. Feedbacks and response are assessed in an idealised ice-sheet/ocean-cavity configuration in which the far field ocean condition is adjusted to emulate periodic climate variability patterns. We reveal a non-linear response of the ice-sheet to periodic variations in thermocline depth. These non-linearities illustrate the heightened sensitivity of fast flowing ice-shelves to periodic perturbations in heat fluxes occurring at interannual and decadal time scales. The results thus highlight how small perturbations in variable climate forcing, like that of ENSO, may trigger large changes in ice-sheet response.

Impacts of boundary condition changes on regional climate projections over West Africa

NASA Astrophysics Data System (ADS)

Kim, Jee Hee; Kim, Yeonjoo; Wang, Guiling

2017-06-01

Future projections using regional climate models (RCMs) are driven with boundary conditions (BCs) typically derived from global climate models. Understanding the impact of the various BCs on regional climate projections is critical for characterizing their robustness and uncertainties. In this study, the International Center for Theoretical Physics Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of different aspects of boundary conditions, including lateral BCs and sea surface temperature (SST), on projected future changes of regional climate in West Africa, and BCs from the coupled European Community-Hamburg Atmospheric Model 5/Max Planck Institute Ocean Model are used as an example. Historical, future, and several sensitivity experiments are conducted with various combinations of BCs and CO2 concentration, and differences among the experiments are compared to identify the most important drivers for RCMs. When driven by changes in all factors, the RegCM4-produced future climate changes include significantly drier conditions in Sahel and wetter conditions along the Guinean coast. Changes in CO2 concentration within the RCM domain alone or changes in wind vectors at the domain boundaries alone have minor impact on projected future climate changes. Changes in the atmospheric humidity alone at the domain boundaries lead to a wetter Sahel due to the northward migration of rain belts during summer. This impact, although significant, is offset and dominated by changes of other BC factors (primarily temperature) that cause a drying signal. Future changes of atmospheric temperature at the domain boundaries combined with SST changes over oceans are sufficient to cause a future climate that closely resembles the projection that accounts for all factors combined. Therefore, climate variability and changes simulated by RCMs depend primarily on the variability and change of temperature aspects of the RCM BCs. Moreover, it is found that the response of the RCM climate to different climate change factors is roughly linear in that the projected changes driven by combined factors are close to the sum of projected changes due to each individual factor alone at least for long-term averages. Findings from this study are important for understanding the source(s) of uncertainties in regional climate projections and for designing innovative approaches to climate downscaling and impact assessment.

Cumulative effects of climate and landscape change drive spatial distribution of Rocky Mountain wolverine (Gulo gulo L.).

PubMed

Heim, Nicole; Fisher, Jason T; Clevenger, Anthony; Paczkowski, John; Volpe, John

2017-11-01

Contemporary landscapes are subject to a multitude of human-derived stressors. Effects of such stressors are increasingly realized by population declines and large-scale extirpation of taxa worldwide. Most notably, cumulative effects of climate and landscape change can limit species' local adaptation and dispersal capabilities, thereby reducing realized niche space and range extent. Resolving the cumulative effects of multiple stressors on species persistence is a pressing challenge in ecology, especially for declining species. For example, wolverines ( Gulo gulo L.) persist on only 40% of their historic North American range. While climate change has been shown to be a mechanism of range retractions, anthropogenic landscape disturbance has been recently implicated. We hypothesized these two interact to effect declines. We surveyed wolverine occurrence using camera trapping and genetic tagging at 104 sites at the wolverine range edge, spanning a 15,000 km 2 gradient of climate, topographic, anthropogenic, and biotic variables. We used occupancy and generalized linear models to disentangle the factors explaining wolverine distribution. Persistent spring snow pack-expected to decrease with climate change-was a significant predictor, but so was anthropogenic landscape change. Canid mesocarnivores, which we hypothesize are competitors supported by anthropogenic landscape change, had comparatively weaker effect. Wolverine population declines and range shifts likely result from climate change and landscape change operating in tandem. We contend that similar results are likely for many species and that research that simultaneously examines climate change, landscape change, and the biotic landscape is warranted. Ecology research and species conservation plans that address these interactions are more likely to meet their objectives.

Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model

NASA Technical Reports Server (NTRS)

Hansen, J.; Fung, I.; Lacis, A.; Rind, D.; Lebedeff, S.; Ruedy, R.; Russell, G.

1988-01-01

The global climate effects of time-dependent atmospheric trace gas and aerosol variations are simulated by NASA-Goddard's three-dimensional climate model II, which possesses 8 x 10-deg horizontal resolution, for the cases of a 100-year control run and three different atmospheric composition scenarios in which trace gas growth is respectively a continuation of current exponential trends, a reduced linear growth, and a rapid curtailment of emissions due to which net climate forcing no longer increases after the year 2000. The experiments begin in 1958, run to the present, and encompass measured or estimated changes in CO2, CH4, N2O, chlorofluorocarbons, and stratospheric aerosols. It is shown that the greenhouse warming effect may be clearly identifiable in the 1990s.

An empirical test of the relative and combined effects of land-cover and climate change on local colonization and extinction.

PubMed

Yalcin, Semra; Leroux, Shawn James

2018-04-14

Land-cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land-cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981-1985 and 2001-2005 are correlated with land-cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land-cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land-cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land-cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction. © 2018 John Wiley & Sons Ltd.

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.

Analysis of trend changes in Northern African palaeo-climate by using Bayesian inference

NASA Astrophysics Data System (ADS)

Schütz, Nadine; Trauth, Martin H.; Holschneider, Matthias

2010-05-01

Climate variability of Northern Africa is of high interest due to climate-evolutionary linkages under study. The reconstruction of the palaeo-climate over long time scales, including the expected linkages (> 3 Ma), is mainly accessible by proxy data from deep sea drilling cores. By concentrating on published data sets, we try to decipher rhythms and trends to detect correlations between different proxy time series by advanced mathematical methods. Our preliminary data is dust concentration, as an indicator for climatic changes such as humidity, from the ODP sites 659, 721 and 967 situated around Northern Africa. Our interest is in challenging the available time series with advanced statistical methods to detect significant trend changes and to compare different model assumptions. For that purpose, we want to avoid the rescaling of the time axis to obtain equidistant time steps for filtering methods. Additionally we demand an plausible description of the errors for the estimated parameters, in terms of confidence intervals. Finally, depending on what model we restrict on, we also want an insight in the parameter structure of the assumed models. To gain this information, we focus on Bayesian inference by formulating the problem as a linear mixed model, so that the expectation and deviation are of linear structure. By using the Bayesian method we can formulate the posteriori density as a function of the model parameters and calculate this probability density in the parameter space. Depending which parameters are of interest, we analytically and numerically marginalize the posteriori with respect to the remaining parameters of less interest. We apply a simple linear mixed model to calculate the posteriori densities of the ODP sites 659 and 721 concerning the last 5 Ma at maximum. From preliminary calculations on these data sets, we can confirm results gained by the method of breakfit regression combined with block bootstrapping ([1]). We obtain a significant change point around (1.63 - 1.82) Ma, which correlates with a global climate transition due to the establishment of the Walker circulation ([2]). Furthermore we detect another significant change point around (2.7 - 3.2) Ma, which correlates with the end of the Pliocene warm period (permanent El Niño-like conditions) and the onset of a colder global climate ([3], [4]). The discussion on the algorithm, the results of calculated confidence intervals, the available information about the applied model in the parameter space and the comparison of multiple change point models will be presented. [1] Trauth, M.H., et al., Quaternary Science Reviews, 28, 2009 [2] Wara, M.W., et al., Science, Vol. 309, 2005 [3] Chiang, J.C.H., Annual Review of Earth and Planetary Sciences, Vol. 37, 2009 [4] deMenocal, P., Earth and Planetary Science Letters, 220, 2004

Assessing the implementation of bias correction in the climate prediction

NASA Astrophysics Data System (ADS)

Nadrah Aqilah Tukimat, Nurul

2018-04-01

An issue of the climate changes nowadays becomes trigger and irregular. The increment of the greenhouse gases (GHGs) emission into the atmospheric system day by day gives huge impact to the fluctuated weather and global warming. It becomes significant to analyse the changes of climate parameters in the long term. However, the accuracy in the climate simulation is always be questioned to control the reliability of the projection results. Thus, the Linear Scaling (LS) as a bias correction method (BC) had been applied to treat the gaps between observed and simulated results. About two rainfall stations were selected in Pahang state there are Station Lubuk Paku and Station Temerloh. Statistical Downscaling Model (SDSM) used to perform the relationship between local weather and atmospheric parameters in projecting the long term rainfall trend. The result revealed the LS was successfully to reduce the error up to 3% and produced better climate simulated results.

Extensive wildfires, climate change, and an abrupt state change in subalpine ribbon forests, Colorado.

PubMed

Calder, W John; Shuman, Bryan

2017-10-01

Ecosystems may shift abruptly when the effects of climate change and disturbance interact, and landscapes with regularly patterned vegetation may be especially vulnerable to abrupt shifts. Here we use a fossil pollen record from a regularly patterned ribbon forest (alternating bands of forests and meadows) in Colorado to examine whether past changes in wildfire and climate produced abrupt vegetation shifts. Comparing the percentages of conifer pollen with sedimentary δ 18 O data (interpreted as an indicator of temperature or snow accumulation) indicates a first-order linear relationship between vegetation composition and climate change with no detectable lags over the past 2,500 yr (r = 0.55, P < 0.001). Additionally, however, we find that the vegetation changed abruptly within a century of extensive wildfires, which were recognized in a previous study to have burned approximately 80% of the surrounding 1,000 km 2 landscape 1,000 yr ago when temperatures rose ~0.5°C. The vegetation change was larger than expected from the effects of climate change alone. Pollen assemblages changed from a composition associated with closed subalpine forests to one similar to modern ribbon forests. Fossil pollen assemblages then remained like those from modern ribbon forests for the following ~1,000 yr, providing a clear example of how extensive disturbances can trigger persistent new vegetation states and alter how vegetation responds to climate. © 2017 by the Ecological Society of America.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2014-11-01

Accurately predicting the response of Amazonia to climate change is important for predicting changes across the globe. However, changes in multiple climatic factors simultaneously may result in complex non-linear responses, which are difficult to predict using vegetation models. Using leaf and canopy scale observations, this study evaluated the capability of five vegetation models (CLM3.5, ED2, JULES, SiB3, and SPA) to simulate the responses of canopy and leaf scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation. There was greater model-data consistency in the response of net ecosystem exchange to changes in temperature, than in the response to temperature of leaf area index (LAI), net photosynthesis (An) and stomatal conductance (gs). Modelled canopy scale fluxes are calculated by scaling leaf scale fluxes to LAI, and therefore in this study similarities in modelled ecosystem scale responses to drought and temperature were the result of inconsistent leaf scale and LAI responses among models. Across the models, the response of An to temperature was more closely linked to stomatal behaviour than biochemical processes. Consequently all the models predicted that GPP would be higher if tropical forests were 5 °C colder, closer to the model optima for gs. There was however no model consistency in the response of the An-gs relationship when temperature changes and drought were introduced simultaneously. The inconsistencies in the An-gs relationships amongst models were caused by to non-linear model responses induced by simultaneous drought and temperature change. To improve the reliability of simulations of the response of Amazonian rainforest to climate change the mechanistic underpinnings of vegetation models need more complete validation to improve accuracy and consistency in the scaling of processes from leaf to canopy.

Global Ocean Sedimentation Patterns: Plate Tectonic History Versus Climate Change

NASA Astrophysics Data System (ADS)

Goswami, A.; Reynolds, E.; Olson, P.; Hinnov, L. A.; Gnanadesikan, A.

2014-12-01

Global sediment data (Whittaker et al., 2013) and carbonate content data (Archer, 1996) allows examination of ocean sedimentation evolution with respect to age of the underlying ocean crust (Müller et al., 2008). From these data, we construct time series of ocean sediment thickness and carbonate deposition rate for the Atlantic, Pacific, and Indian ocean basins for the past 120 Ma. These time series are unique to each basin and reflect an integrated response to plate tectonics and climate change. The goal is to parameterize ocean sedimentation tied to crustal age for paleoclimate studies. For each basin, total sediment thickness and carbonate deposition rate from 0.1 x 0.1 degree cells are binned according to basement crustal age; area-corrected moments (mean, variance, etc.) are calculated for each bin. Segmented linear fits identify trends in present-day carbonate deposition rates and changes in ocean sedimentation from 0 to 120 Ma. In the North and South Atlantic and Indian oceans, mean sediment thickness versus crustal age is well represented by three linear segments, with the slope of each segment increasing with increasing crustal age. However, the transition age between linear segments varies among the three basins. In contrast, mean sediment thickness in the North and South Pacific oceans are numerically smaller and well represented by two linear segments with slopes that decrease with increasing crustal age. These opposing trends are more consistent with the plate tectonic history of each basin being the controlling factor in sedimentation rates, rather than climate change. Unlike total sediment thickness, carbonate deposition rates decrease smoothly with crustal age in all basins, with the primary controls being ocean chemistry and water column depth.References: Archer, D., 1996, Global Biogeochem. Cycles 10, 159-174.Müller, R.D., et al., 2008, Science, 319, 1357-1362.Whittaker, J., et al., 2013, Geochem., Geophys., Geosyst. DOI: 10.1002/ggge.20181

Striking Seasonality in the Secular Warming of the Northern Continents: Structure and Mechanisms

NASA Astrophysics Data System (ADS)

Nigam, S.; Thomas, N. P.

2017-12-01

The linear trend in twentieth-century surface air temperature (SAT)—a key secular warming signal— exhibits striking seasonal variations over Northern Hemisphere continents; SAT trends are pronounced in winter and spring but notably weaker in summer and fall. The SAT trends in historical twentieth-century climate simulations informing the Intergovernmental Panel for Climate Change's Fifth Assessment show varied (and often unrealistic) strength and structure, and markedly weaker seasonal variation. The large intra-ensemble spread of winter SAT trends in some historical simulations was surprising, especially in the context of century-long linear trends, with implications for the detection of the secular warming signal. The striking seasonality of observed secular warming over northern continents warrants an explanation and the representation of related processes in climate models. Here, the seasonality of SAT trends over North America is shown to result from land surface-hydroclimate interactions and, to an extent, also from the secular change in low-level atmospheric circulation and related thermal advection. It is argued that the winter dormancy and summer vigor of the hydrologic cycle over middle- to high-latitude continents permit different responses to the additional incident radiative energy from increasing greenhouse gas concentrations. The seasonal cycle of climate, despite its monotony, provides an expanded phase space for the exposition of the dynamical and thermodynamical processes generating secular warming, and an exceptional cost-effective opportunity for benchmarking climate projection models.

Spatial and temporal variation in the association between temperature and salmonellosis in NZ.

PubMed

Lal, Aparna; Hales, Simon; Kirk, Martyn; Baker, Michael G; French, Nigel P

2016-04-01

Modelling the relationship between weather, climate and infectious diseases can help identify high-risk periods and provide understanding of the determinants of longer-term trends. We provide a detailed examination of the non-linear and delayed association between temperature and salmonellosis in three New Zealand cities (Auckland, Wellington and Christchurch). Salmonella notifications were geocoded to the city of residence for the reported case. City-specific associations between weekly maximum temperature and the onset date for reported salmonella infections (1997-2007) were modelled using non-linear distributed lag models, while controlling for season and long-term trends. Relatively high temperatures were positively associated with infection risk in Auckland (n=3,073) and Christchurch (n=880), although the former showed evidence of a more immediate relationship with exposure to high temperatures. There was no significant association between temperature and salmonellosis risk in Wellington. Projected increases in temperature with climate change may have localised health impacts, suggesting that preventative measures will need to be region-specific. This evidence contributes to the increasing concern over the public health impacts of climate change. © 2015 Public Health Association of Australia.

A review of downscaling procedures - a contribution to the research on climate change impacts at city scale

NASA Astrophysics Data System (ADS)

Smid, Marek; Costa, Ana; Pebesma, Edzer; Granell, Carlos; Bhattacharya, Devanjan

2016-04-01

Human kind is currently predominantly urban based, and the majority of ever continuing population growth will take place in urban agglomerations. Urban systems are not only major drivers of climate change, but also the impact hot spots. Furthermore, climate change impacts are commonly managed at city scale. Therefore, assessing climate change impacts on urban systems is a very relevant subject of research. Climate and its impacts on all levels (local, meso and global scale) and also the inter-scale dependencies of those processes should be a subject to detail analysis. While global and regional projections of future climate are currently available, local-scale information is lacking. Hence, statistical downscaling methodologies represent a potentially efficient way to help to close this gap. In general, the methodological reviews of downscaling procedures cover the various methods according to their application (e.g. downscaling for the hydrological modelling). Some of the most recent and comprehensive studies, such as the ESSEM COST Action ES1102 (VALUE), use the concept of Perfect Prog and MOS. Other examples of classification schemes of downscaling techniques consider three main categories: linear methods, weather classifications and weather generators. Downscaling and climate modelling represent a multidisciplinary field, where researchers from various backgrounds intersect their efforts, resulting in specific terminology, which may be somewhat confusing. For instance, the Polynomial Regression (also called the Surface Trend Analysis) is a statistical technique. In the context of the spatial interpolation procedures, it is commonly classified as a deterministic technique, and kriging approaches are classified as stochastic. Furthermore, the terms "statistical" and "stochastic" (frequently used as names of sub-classes in downscaling methodological reviews) are not always considered as synonymous, even though both terms could be seen as identical since they are referring to methods handling input modelling factors as variables with certain probability distributions. In addition, the recent development is going towards multi-step methodologies containing deterministic and stochastic components. This evolution leads to the introduction of new terms like hybrid or semi-stochastic approaches, which makes the efforts to systematically classifying downscaling methods to the previously defined categories even more challenging. This work presents a review of statistical downscaling procedures, which classifies the methods in two steps. In the first step, we describe several techniques that produce a single climatic surface based on observations. The methods are classified into two categories using an approximation to the broadest consensual statistical terms: linear and non-linear methods. The second step covers techniques that use simulations to generate alternative surfaces, which correspond to different realizations of the same processes. Those simulations are essential because there is a limited number of real observational data, and such procedures are crucial for modelling extremes. This work emphasises the link between statistical downscaling methods and the research of climate change impacts at city scale.

Influences of removing linear and nonlinear trends from climatic variables on temporal variations of annual reference crop evapotranspiration in Xinjiang, China.

PubMed

Li, Yi; Yao, Ning; Chau, Henry Wai

2017-08-15

Reference crop evapotranspiration (ET o ) is a key parameter in field irrigation scheduling, drought assessment and climate change research. ET o uses key prescribed (or fixed or reference) land surface parameters for crops. The linear and nonlinear trends in different climatic variables (CVs) affect ET o change. This research aims to reveal how ET o responds after the related CVs were linearly and nonlinearly detrended over 1961-2013 in Xinjiang, China. The ET o -related CVs included minimum (T min ), average (T ave ), and maximum air temperatures (T max ), wind speed at 2m (U 2 ), relative humidity (RH) and sunshine hour (n). ET o was calculated using the Penman-Monteith equation. A total of 29 ET o scenarios, including the original scenario, 14 scenarios in Group I (ET o was recalculated after removing linear trends from single or more CVs) and 14 scenarios in Group II (ET o was recalculated after removing nonlinear trends from the CVs), were generated. The influence of U 2 was stronger than influences of the other CVs on ET o for both Groups I and II either in northern, southern or the entirety of Xinjiang. The weak influences of increased T min , T ave and T max on increasing ET o were masked by the strong effects of decreased U 2 &n and increased RH on decreasing ET o . The effects of the trends in CVs, especially U 2 , on changing ET o were clearly shown. Without the general decreases of U 2 , ET o would have increased in the past 53years. Due to the non-monotone variations of the CVs and ET o , the results of nonlinearly detrending CVs on changing ET o in Group II should be more plausible than the results of linearly detrending CVs in Group I. The decreasing ET o led to a general relief in drought, which was indicated by the recalculated aridity index. Therefore, there would be a slightly lower risk of water utilization in Xinjiang, China. Copyright © 2017 Elsevier B.V. All rights reserved.

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Regression tree modeling of forest NPP using site conditions and climate variables across eastern USA

NASA Astrophysics Data System (ADS)

Kwon, Y.

2013-12-01

As evidence of global warming continue to increase, being able to predict forest response to climate changes, such as expected rise of temperature and precipitation, will be vital for maintaining the sustainability and productivity of forests. To map forest species redistribution by climate change scenario has been successful, however, most species redistribution maps lack mechanistic understanding to explain why trees grow under the novel conditions of chaining climate. Distributional map is only capable of predicting under the equilibrium assumption that the communities would exist following a prolonged period under the new climate. In this context, forest NPP as a surrogate for growth rate, the most important facet that determines stand dynamics, can lead to valid prediction on the transition stage to new vegetation-climate equilibrium as it represents changes in structure of forest reflecting site conditions and climate factors. The objective of this study is to develop forest growth map using regression tree analysis by extracting large-scale non-linear structures from both field-based FIA and remotely sensed MODIS data set. The major issue addressed in this approach is non-linear spatial patterns of forest attributes. Forest inventory data showed complex spatial patterns that reflect environmental states and processes that originate at different spatial scales. At broad scales, non-linear spatial trends in forest attributes and mixture of continuous and discrete types of environmental variables make traditional statistical (multivariate regression) and geostatistical (kriging) models inefficient. It calls into question some traditional underlying assumptions of spatial trends that uncritically accepted in forest data. To solve the controversy surrounding the suitability of forest data, regression tree analysis are performed using Software See5 and Cubist. Four publicly available data sets were obtained: First, field-based Forest Inventory and Analysis (USDA, Forest Service) data set for the 31 eastern most United States. Second, 8-day composite of MODIS Land Cover, FPAR, LAI and GPP/NPP data were obtained from Jan 2001 to Dec 2004 (total 182 composite) and each product were filtered by pixel-level quality assurance data to select best quality pixels. Third, 30-year averaged climate data were collected from National Oceanic and Atmospheric Administration (NOAA) and five climatic variables were obtained: Monthly temperature, precipitation, annual heating and cooling days, and annual frost-free days. Forth, topographic data were obtained from digital elevation model (1km by 1km). This research will provide a better understanding of large-scale forest responses to environmental factors that will be beneficial for the development of important forest management applications.

Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change.

PubMed

Lawing, A Michelle; Polly, P David

2011-01-01

Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr).

Pleistocene Climate, Phylogeny, and Climate Envelope Models: An Integrative Approach to Better Understand Species' Response to Climate Change

PubMed Central

Lawing, A. Michelle; Polly, P. David

2011-01-01

Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr). PMID:22164305

Linear Regression Quantile Mapping (RQM) - A new approach to bias correction with consistent quantile trends

NASA Astrophysics Data System (ADS)

Passow, Christian; Donner, Reik

2017-04-01

Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016

Climate pattern-scaling set for an ensemble of 22 GCMs - adding uncertainty to the IMOGEN version 2.0 impact system

NASA Astrophysics Data System (ADS)

Zelazowski, Przemyslaw; Huntingford, Chris; Mercado, Lina M.; Schaller, Nathalie

2018-02-01

Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25 ± 5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44 ± 4.37 and 14.98 ± 4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

A vertically integrated snow/ice model over land/sea for climate models. I - Development. II - Impact on orbital change experiments

NASA Technical Reports Server (NTRS)

Neeman, Binyamin U.; Ohring, George; Joseph, Joachim H.

1988-01-01

A vertically integrated formulation (VIF) model for sea ice/snow and land snow is discussed which can simulate the nonlinear effects of heat storage and transfer through the layers of snow and ice. The VIF demonstates the accuracy of the multilayer formulation, while benefitting from the computational flexibility of linear formulations. In the second part, the model is implemented in a seasonal dynamic zonally averaged climate model. It is found that, in response to a change between extreme high and low summer insolation orbits, the winter orbital change dominates over the opposite summer change for sea ice. For snow over land the shorter but more pronounced summer orbital change is shown to dominate.

Evaluating the accuracy of climate change pattern emulation for low warming targets

NASA Astrophysics Data System (ADS)

Tebaldi, Claudia; Knutti, Reto

2018-05-01

Global climate policy is increasingly debating the value of very low warming targets, yet not many experiments conducted with global climate models in their fully coupled versions are currently available to help inform studies of the corresponding impacts. This raises the question whether a map of warming or precipitation change in a world 1.5 °C warmer than preindustrial can be emulated from existing simulations that reach higher warming targets, or whether entirely new simulations are required. Here we show that also for this type of low warming in strong mitigation scenarios, climate change signals are quite linear as a function of global temperature. Therefore, emulation techniques amounting to linear rescaling on the basis of global temperature change ratios (like simple pattern scaling) provide a viable way forward. The errors introduced are small relative to the spread in the forced response to a given scenario that we can assess from a multi-model ensemble. They are also small relative to the noise introduced into the estimates of the forced response by internal variability within a single model, which we can assess from either control simulations or initial condition ensembles. Challenges arise when scaling inadvertently reduces the inter-model spread or suppresses the internal variability, both important sources of uncertainty for impact assessment, or when the scenarios have very different characteristics in the composition of the forcings. Taking advantage of an available suite of coupled model simulations under low-warming and intermediate scenarios, we evaluate the accuracy of these emulation techniques and show that they are unlikely to represent a substantial contribution to the total uncertainty.

Effects of different representations of transport in the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Kreyling, Daniel; Rex, Markus

2017-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Interactively coupled chemistry climate models (CCMs) provide a means to realistically simulate the interaction between atmospheric chemistry and dynamics. The calculation of chemistry in CCMs, however, is computationally expensive which renders the use of complex chemistry models not suitable for ensemble simulations or simulations with multiple climate change scenarios. In these simulations ozone is therefore usually prescribed as a climatological field or included by incorporating a fast linear ozone scheme into the model. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. An alternative approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. When using SWIFT in EMAC, there are several possibilities to represent the effect of transport inside the polar vortex: the semi-Lagrangian transport scheme of EMAC and a transport parameterisation that can be useful when using SWIFT in models not having transport of their own. Here, we present results of equivalent simulations with different handling of transport, compare with EMAC simulations with full interactive chemistry and evaluate the results with observations.

Uncertainties Associated with Quantifying Climate Change Impacts on Human Health: A Case Study for Diarrhea

PubMed Central

Kolstad, Erik W.; Johansson, Kjell Arne

2011-01-01

Background Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. Objectives The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. Methods We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. Results The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8–11% (with SDs of 3–5%) by 2010–2039 and 22–29% (SDs of 9–12%) by 2070–2099. Conclusions Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate–health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health. PMID:20929684

Population dynamics can be more important than physiological limits for determining range shifts under climate change.

PubMed

Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

2013-10-01

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.

An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation

NASA Astrophysics Data System (ADS)

Allison, Lesley; Hawkins, Ed; Woollings, Tim

2015-01-01

Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.

nonlinMIP contribution to CMIP6: model intercomparison project for non-linear mechanisms: physical basis, experimental design and analysis principles (v1.0)

NASA Astrophysics Data System (ADS)

Good, Peter; Andrews, Timothy; Chadwick, Robin; Dufresne, Jean-Louis; Gregory, Jonathan M.; Lowe, Jason A.; Schaller, Nathalie; Shiogama, Hideo

2016-11-01

nonlinMIP provides experiments that account for state-dependent regional and global climate responses. The experiments have two main applications: (1) to focus understanding of responses to CO2 forcing on states relevant to specific policy or scientific questions (e.g. change under low-forcing scenarios, the benefits of mitigation, or from past cold climates to the present day), or (2) to understand the state dependence (non-linearity) of climate change - i.e. why doubling the forcing may not double the response. State dependence (non-linearity) of responses can be large at regional scales, with important implications for understanding mechanisms and for general circulation model (GCM) emulation techniques (e.g. energy balance models and pattern-scaling methods). However, these processes are hard to explore using traditional experiments, which explains why they have had so little attention in previous studies. Some single model studies have established novel analysis principles and some physical mechanisms. There is now a need to explore robustness and uncertainty in such mechanisms across a range of models (point 2 above), and, more broadly, to focus work on understanding the response to CO2 on climate states relevant to specific policy/science questions (point 1). nonlinMIP addresses this using a simple, small set of CO2-forced experiments that are able to separate linear and non-linear mechanisms cleanly, with a good signal-to-noise ratio - while being demonstrably traceable to realistic transient scenarios. The design builds on the CMIP5 (Coupled Model Intercomparison Project Phase 5) and CMIP6 DECK (Diagnostic, Evaluation and Characterization of Klima) protocols, and is centred around a suite of instantaneous atmospheric CO2 change experiments, with a ramp-up-ramp-down experiment to test traceability to gradual forcing scenarios. In all cases the models are intended to be used with CO2 concentrations rather than CO2 emissions as the input. The understanding gained will help interpret the spread in policy-relevant scenario projections. Here we outline the basic physical principles behind nonlinMIP, and the method of establishing traceability from abruptCO2 to gradual forcing experiments, before detailing the experimental design, and finally some analysis principles. The test of traceability from abruptCO2 to transient experiments is recommended as a standard analysis within the CMIP5 and CMIP6 DECK protocols.

Spatio-Temporal Dynamics of Maize Yield Water Constraints under Climate Change in Spain

PubMed Central

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent “hot-spots” in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity. PMID:24878747

Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.

PubMed

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.

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

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

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

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

To Tip or Not to Tip: The Case of the Congo Basin Rainforest Realm

NASA Astrophysics Data System (ADS)

Pietsch, S.; Bednar, J. E.; Fath, B. D.; Winter, P. A.

2017-12-01

The future response of the Congo basin rainforest, the second largest tropical carbon reservoir, to climate change is still under debate. Different Climate projections exist stating increase and decrease in rainfall and different changes in rainfall patterns. Within this study we assess all options of climate change possibilities to define the climatic thresholds of Congo basin rainforest stability and assess the limiting conditions for rainforest persistence. We use field data from 199 research plots from the Western Congo basin to calibrate and validate a complex BioGeoChemistry model (BGC-MAN) and assess model performance against an array of possible future climates. Next, we analyze the reasons for the occurrence of tipping points, their spatial and temporal probability of occurrence, will present effects of hysteresis and derive probabilistic spatial-temporal resilience landscapes for the region. Additionally, we will analyze attractors of forest growth dynamics and assess common linear measures for early warning signals of sudden shifts in system dynamics for their robustness in the context of the Congo Basin case, and introduce the correlation integral as a nonlinear measure of risk assessment.

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

DOE PAGES

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

2016-06-16

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

Analysis of recent climatic changes in the Arabian Peninsula region

NASA Astrophysics Data System (ADS)

Nasrallah, H. A.; Balling, R. C.

1996-12-01

Interest in the potential climatic consequences of the continued buildup of anthropo-generated greenhouse gases has led many scientists to conduct extensive climate change studies at the global, hemispheric, and regional scales. In this investigation, analyses are conducted on long-term historical climate records from the Arabian Peninsula region. Over the last 100 years, temperatures in the region increased linearly by 0.63 °C. However, virtually all of this warming occurred from 1911 1935, and over the most recent 50 years, the Arabian Peninsula region has cooled slightly. In addition, the satellite-based measurements of lower-tropospheric temperatures for the region do not show any statistically significant warming over the period 1979 1991. While many other areas of the world are showing a decrease in the diurnal temperature range, the Arabian Peninsula region reveals no evidence of a long-term change in this parameter. Precipitation records for the region show a slight, statistically insignificant decrease over the past 40 years. The results from this study should complement the mass of information that has resulted from similar regional climate studies conducted in the United States, Europe, and Australia.

Stable isotopic constraints on global soil organic carbon turnover

NASA Astrophysics Data System (ADS)

Wang, Chao; Houlton, Benjamin Z.; Liu, Dongwei; Hou, Jianfeng; Cheng, Weixin; Bai, Edith

2018-02-01

Carbon dioxide release during soil organic carbon (SOC) turnover is a pivotal component of atmospheric CO2 concentrations and global climate change. However, reliably measuring SOC turnover rates on large spatial and temporal scales remains challenging. Here we use a natural carbon isotope approach, defined as beta (β), which was quantified from the δ13C of vegetation and soil reported in the literature (176 separate soil profiles), to examine large-scale controls of climate, soil physical properties and nutrients over patterns of SOC turnover across terrestrial biomes worldwide. We report a significant relationship between β and calculated soil C turnover rates (k), which were estimated by dividing soil heterotrophic respiration rates by SOC pools. ln( - β) exhibits a significant linear relationship with mean annual temperature, but a more complex polynomial relationship with mean annual precipitation, implying strong-feedbacks of SOC turnover to climate changes. Soil nitrogen (N) and clay content correlate strongly and positively with ln( - β), revealing the additional influence of nutrients and physical soil properties on SOC decomposition rates. Furthermore, a strong (R2 = 0.76; p < 0.001) linear relationship between ln( - β) and estimates of litter and root decomposition rates suggests similar controls over rates of organic matter decay among the generalized soil C stocks. Overall, these findings demonstrate the utility of soil δ13C for independently benchmarking global models of soil C turnover and thereby improving predictions of multiple global change influences over terrestrial C-climate feedback.

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.

Global projections and climate stabilisation targets

NASA Astrophysics Data System (ADS)

Friedlingstein, Pierre

2014-05-01

The Summary for policy makers of the 5th Assessment Report of the Working Group 1 of IPCC has a figure that has no equivalent in previous IPCC assessment reports. This new figure shows the change in global average surface temperature as a function of cumulative anthropogenic emissions of CO2. In this talk I will describe how the concept of transient climate response to cumulative emissions (TCRE) that supports that figure emerged from the literature over the recent years and what are the fundamental physical and biogeochemical processes that explain this relationship and its linearity. I will also explore the implication of TCRE for long-term climate change and mitigation strategies as well as the limitations of the concept of TCRE.

A walk on the tundra: Host-parasite interactions in an extreme environment.

PubMed

Kutz, Susan J; Hoberg, Eric P; Molnár, Péter K; Dobson, Andy; Verocai, Guilherme G

2014-08-01

Climate change is occurring very rapidly in the Arctic, and the processes that have taken millions of years to evolve in this very extreme environment are now changing on timescales as short as decades. These changes are dramatic, subtle and non-linear. In this article, we discuss the evolving insights into host-parasite interactions for wild ungulate species, specifically, muskoxen and caribou, in the North American Arctic. These interactions occur in an environment that is characterized by extremes in temperature, high seasonality, and low host species abundance and diversity. We believe that lessons learned in this system can guide wildlife management and conservation throughout the Arctic, and can also be generalized to more broadly understand host-parasite interactions elsewhere. We specifically examine the impacts of climate change on host-parasite interactions and focus on: (I) the direct temperature effects on parasites; (II) the importance of considering the intricacies of host and parasite ecology for anticipating climate change impacts; and (III) the effect of shifting ecological barriers and corridors. Insights gained from studying the history and ecology of host-parasite systems in the Arctic will be central to understanding the role that climate change is playing in these more complex systems.

A walk on the tundra: Host–parasite interactions in an extreme environment

PubMed Central

Kutz, Susan J.; Hoberg, Eric P.; Molnár, Péter K.; Dobson, Andy; Verocai, Guilherme G.

2014-01-01

Climate change is occurring very rapidly in the Arctic, and the processes that have taken millions of years to evolve in this very extreme environment are now changing on timescales as short as decades. These changes are dramatic, subtle and non-linear. In this article, we discuss the evolving insights into host–parasite interactions for wild ungulate species, specifically, muskoxen and caribou, in the North American Arctic. These interactions occur in an environment that is characterized by extremes in temperature, high seasonality, and low host species abundance and diversity. We believe that lessons learned in this system can guide wildlife management and conservation throughout the Arctic, and can also be generalized to more broadly understand host–parasite interactions elsewhere. We specifically examine the impacts of climate change on host–parasite interactions and focus on: (I) the direct temperature effects on parasites; (II) the importance of considering the intricacies of host and parasite ecology for anticipating climate change impacts; and (III) the effect of shifting ecological barriers and corridors. Insights gained from studying the history and ecology of host–parasite systems in the Arctic will be central to understanding the role that climate change is playing in these more complex systems. PMID:25180164

An aerobic scope-based habitat suitability index for predicting the effects of multi-dimensional climate change stressors on marine teleosts

NASA Astrophysics Data System (ADS)

Del Raye, Gen; Weng, Kevin C.

2015-03-01

Climate change will expose many marine ecosystems to temperature, oxygen and CO2 conditions that have not been experienced for millennia. Predicting the impact of these changes on marine fishes is difficult due to the complexity of these disparate stressors and the inherent non-linearity of physiological systems. Aerobic scope (the difference between maximum and minimum aerobic metabolic rates) is a coherent, unifying physiological framework that can be used to examine all of the major environmental changes expected to occur in the oceans during this century. Using this framework, we develop a physiology-based habitat suitability model to forecast the response of marine fishes to simultaneous ocean acidification, warming and deoxygenation, including interactions between all three stressors. We present an example of the model parameterized for Thunnus albacares (yellowfin tuna), an important fisheries species that is likely to be affected by climate change. We anticipate that if embedded into multispecies ecosystem models, our model could help to more precisely forecast climate change impacts on the distribution and abundance of other high value species. Finally, we show how our model may indicate the potential for, and limits of, adaptation to chronic stressors.

Modeled climate-induced glacier change in Glacier National Park, 1850-2100

USGS Publications Warehouse

Hall, M.H.P.; Fagre, D.B.

2003-01-01

The glaciers in the Blackfoot-Jackson Glacier Basin of Glacier National Park, Montana, decreased in area from 21.6 square kilometers (km2) in 1850 to 7.4 km2 in 1979. Over this same period global temperatures increased by 0.45??C (?? 0. 15??C). We analyzed the climatic causes and ecological consequences of glacier retreat by creating spatially explicit models of the creation and ablation of glaciers and of the response of vegetation to climate change. We determined the melt rate and spatial distribution of glaciers under two possible future climate scenarios, one based on carbon dioxide-induced global warming and the other on a linear temperature extrapolation. Under the former scenario, all glaciers in the basin will disappear by the year 2030, despite predicted increases in precipitation; under the latter, melting is slower. Using a second model, we analyzed vegetation responses to variations in soil moisture and increasing temperature in a complex alpine landscape and predicted where plant communities are likely to be located as conditions change.

Reducing Uncertainty in Chemistry Climate Model Predictions of Stratospheric Ozone

NASA Technical Reports Server (NTRS)

Douglass, A. R.; Strahan, S. E.; Oman, L. D.; Stolarski, R. S.

2014-01-01

Chemistry climate models (CCMs) are used to predict the future evolution of stratospheric ozone as ozone-depleting substances decrease and greenhouse gases increase, cooling the stratosphere. CCM predictions exhibit many common features, but also a broad range of values for quantities such as year of ozone-return-to-1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to chlorine change from that due to climate change. We show that the sensitivity of lower atmosphere ozone to chlorine change deltaO3/deltaCly is a near linear function of partitioning of total inorganic chlorine (Cly) into its reservoirs; both Cly and its partitioning are controlled by lower atmospheric transport. CCMs with realistic transport agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035 differences in response to chlorine contribute little to the spread in CCM results as the anthropogenic contribution to Cly becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change deltaO3/deltaT due to different contributions from various ozone loss processes, each with their own temperature dependence. In the lower atmosphere, tropical ozone decreases caused by a predicted speed-up in the Brewer-Dobson circulation may or may not be balanced by middle and high latitude increases, contributing most to the spread in late 21st century predictions.

A new framework for climate sensitivity and prediction: a modelling perspective

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.

Mechanisms of elevation-dependent warming over complex terrain in high-resolution simulations of regional climate change

NASA Astrophysics Data System (ADS)

Minder, J. R.; Letcher, T.; Liu, C.

2016-12-01

Numerous observational and modeling studies have suggested that over mountainous terrain certain elevations can experience systematically enhanced rates of near-surface climate warming relative to the surrounding region, a phenomenon referred to as elevation-dependent warming (EDW). In many of these studies high-elevation locations were found to experience the fastest warming rates. A variety of physical mechanisms for EDW have been proposed but there is no consensus as to the dominant cause. We examine EDW in regional climate model (RCM) simulations with very high horizontal resolution (4-km horizontal grid). The simulation domain centers on the Rocky Mountains and intermountain west of the United States. Climate change simulations are conducted using the "pseudo global warming" framework to focus on the regional response to large-scale thermodynamic and radiative climate changes representative of mid-century anthropogenic global climate change. Substantial EDW is found in these simulations. Warming varies with elevation by up to 1°C depending on the season considered. The structure of EDW is only weakly sensitive to variations in horizontal grid spacing ranging from 4 to 36 km. The snow-albedo feedback (SAF) plays a major role in causing the simulated EDW. The elevation band of maximum warming varies seasonally, mostly following the margin of the seasonal snowpack where snow cover and albedo reductions are maximized under climate warming. Additional simulations where the SAF is artificially suppressed demonstrate that EDW variations of up to 0.6°C can be attributed to the SAF. Simulations with a suppressed SAF still exhibit EDW variations up to 0.8°C that must be explained by other mechanisms. This remaining EDW shows a near linear increase in warming with elevation in most months and does not appear to be inherited from the profile of large-scale free-tropospheric warming. Simple theoretical calculations suggest that the non-linear dependence of surface emission on temperature offers one promising mechanism. The role of water vapor and cloud feedbacks are also considered as alternative mechanisms.

Dryland responses to global change suggest the potential for rapid non-linear responses to some changes but resilience to others

NASA Astrophysics Data System (ADS)

Reed, S.; Ferrenberg, S.; Tucker, C.; Rutherford, W. A.; Wertin, T. M.; McHugh, T. A.; Morrissey, E.; Kuske, C.; Belnap, J.

2017-12-01

Drylands represent our planet's largest terrestrial biome, making up over 35% of Earth's land surface. In the context of this vast areal extent, it is no surprise that recent research suggests dryland inter-annual variability and responses to change have the potential to drive biogeochemical cycles and climate at the global-scale. Further, the data we do have suggest drylands can respond rapidly and non-linearly to change. Nevertheless, our understanding of the cross-system consistency of and mechanisms behind dryland responses to a changed environment remains relatively poor. This poor understanding hinders not only our larger understanding of terrestrial ecosystem function, but also our capacity to forecast future global biogeochemical cycles and climate. Here we present data from a series of Colorado Plateau manipulation experiments - including climate, land use, and nitrogen deposition manipulations - to explore how vascular plants, microbial communities, and biological soil crusts (a community of mosses, lichens, and/or cyanobacteria living in the interspace among vascular plants in arid and semiarid ecosystems worldwide) respond to a host of environmental changes. These responses include not only assessments of community composition, but of their function as well. We will explore photosynthesis, net soil CO2 exchange, soil carbon stocks and chemistry, albedo, and nutrient cycling. The experiments were begun with independent questions and cover a range of environmental change drivers and scientific approaches, but together offer a relatively holistic picture of how some drylands can change their structure and function in response to change. In particular, the data show very high ecosystem vulnerability to particular drivers, but surprising resilience to others, suggesting a multi-faceted response of these diverse systems.

Demonstrating the Error Budget for the Climate Absolute Radiance and Refractivity Observatory Through Solar Irradiance Measurements

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; McAndrew, Brendan

2016-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as a method to determine the accuracy of climate change. A CLARREO objective is to improve the accuracy of SI-traceable, absolute calibration at infrared and reflected solar wavelengths to reach on-orbit accuracies required to allow climate change observations to survive data gaps and observe climate change at the limit of natural variability. Such an effort will also demonstrate National Institute of Standards and Technology (NIST) approaches for use in future spaceborne instruments. The current work describes the results of laboratory and field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. SOLARIS allows testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. Results of laboratory calibration measurements are provided to demonstrate key assumptions about instrument behavior that are needed to achieve CLARREO's climate measurement requirements. Absolute radiometric response is determined using laser-based calibration sources and applied to direct solar views for comparison with accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

Predicting changes in reported notifiable disease rates for New Zealand using a SIR modelling approach

NASA Astrophysics Data System (ADS)

McBride, Graham; Slaney, David; Tait, Andrew

2013-04-01

The New Zealand health system has defined as 'notifiable' over 50 diseases. Of these campylobacteriosis is the most commonly reported comprising 41% of all notifications in 2011 (presently about 150 illness cases per 100,000 population per annum). Furthermore, the incidence of this mild illness, which is potentially waterborne, is under-reported by at least an order-of-magnitude. Increased downstream pathogen loads and/or disease incidence have been found to be associated with increased rainfall, particularly in agricultural landscapes. Therefore, given the predominance of agricultural land uses in New Zealand, transmission and exposure to its agent (thermotolerant Campylobacter bacteria) may be affected by changing rainfall and temperature patterns associated with climate change. Reporting rates for other potentially water-borne zoonoses are also noticeable (for example, the reported rate for cryptosporidiosis for 2011 was 14 per 100,000 population). The distribution of Cryptosporidium oocysts in the environment may be influenced by climate change because it has often been implicated in drinking-water contamination, and heavy rainfall events have been found to be associated with increased pathogen loads in rivers and disease incidence. Given this background, which may also be applicable to other countries with agriculturally-dominated landscapes, a New Zealand study was initiated to develop a decision-support system for the projected effects of climate change on a selected suite of environmentally-transmitted pathogens, including Campylobacter and Cryptosporodium oocysts. Herein we report on the manner in which a linear SIR (Susceptible-Ill-Recovered) model previously developed for campylobacteriosis can be extended to cryptosporidiosis, applied to changes in pathogen contact rate and hence reported illness, and coupled to climate change projections associated with different greenhouse gas emission scenarios. The resulting SIR model outputs provided projected changes in reported disease incidence as a function of temperature and rainfall. These models account for age-dependency (children versus adults), which is especially important because children can report substantially higher rates of zoonoses. The model is linear because the zoonotic pathogen 'reservoir' is overwhelmingly among animals, and so the usual interaction in which human-pathogen interactions affect the degree of environmental contamination does not apply in the short term (on the order of one year). Accordingly, the interaction can be approximated by a constant contact rate over a given year, even though the contact rates may vary between decades because of climate change and variability. This linearity property enables the derivation of analytical solutions to the model's governing equations, thereby providing for a more elegant examination of the model's properties and for making projections under climate change. The models have been calibrated to reported rates of these diseases. Simple exponential functions have been used to vary the pathogen contact rates for the reference years 2015, 2040 and 2090 under three climate change scenarios of low, medium and high emissions of greenhouse gases (B1, A1B, and A2). These formulations have been guided by the results of statistical models calibrated to historical disease reporting rates. The models have been used to calculate the ratio of reported illness rates to present rates projected for future years across New Zealand at the ~5 km scale. Detailed results will be presented for the reference year 2040.

A Synoptic Weather Typing Approach to Assess Climate Change Impacts on Meteorological and Hydrological Risks at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Cheng, Chad Shouquan; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been applied in Environment Canada to analyze climatic change impacts on various meteorological/hydrological risks, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the hazardous events, (2) statistical downscaling to provide station-scale future climate information, and (3) estimates of changes in frequency and magnitude of future hazardous meteorological/hydrological events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and various linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into the entire modeling exercise. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. This paper will briefly summarize these research projects, focusing on the modeling exercise and results.

Supporting NGSS-aligned Study of Authentic Data about Climate

NASA Astrophysics Data System (ADS)

Zalles, D. R.

2013-12-01

The subject of climate change holds tremendous opportunity for students to learn how scientists use data to develop and test theories of how the natural world works and appreciate how climate change instantiates cross-cutting NGSS science themes like stability and change, energy and matter, and cause and effect. To do so, students and teachers need help seeing in authentic Earth system data complex climate interactions and generate plans for building greater understanding of the complexities through further data investigation. With ever-growing repositories of global and regional public data and user friendly tools for their display, K-12 educators are challenged to help students study data independently rather than through the usual pre-filtered didactic presentations of data found in textbooks. The paper will describe strategies for facilitating critical thinking about authentic climate-related data in two climate change education projects funded by NASA and NSF, as well as learning outcomes. Data Enhanced Investigations for Climate Change Education (dicce.sri.com) brings data from NASA satellite missions to classrooms. Studying Topography, Orographic Rainfall, and Ecosystems with Geospatial Information Technology (store.sri.com) provides recent climatological and vegetation data about certain study areas in California and New York plus geospatially distributed projected values of temperature, precipitation, and land cover in 2050 and 2099, derived from NCAR's A2 climate change model. Supportive resources help students move from naïve conceptions of simple linear relationships between variables into critical analysis of what other variables could be mediating those relationships. DICCE contains guides for how to interpret multiyear trends that are evident in the NASA mission data in relation to what we know about current climate change. If a learner plots a line of best fit across multiple months or years of regional data and notices that the line is either sloping up or down, the trend guide suggests what this might mean and suggests what additional types of data to examine for verification. For example, the variable euphotic depth looks at ocean surface water clarity. If students notice that euphotic depth has decreased, the trend guide explains how this could be evidence of increased runoff from coastal lands. Yet, increased runoff may or may not be an effect of regional climate change; an effect if from increasingly severe storms, or not an effect if from increased deforestation in the coastal watershed. Or, perhaps both could be occurring. To investigate further, students are encouraged to study if other data about the region shows trends (e.g., accumulated precipitation, rainfall rate, and air temperature) and to see if the decreased euphotic depth is also occurring further from the coastline. This could indicate decreased phytoplankton, which in turn could result from climate change if the decrease is due to increased sea surface temperatures that mitigate upwelling of nutrients from colder depths. The STORE project also stimulates discovery of complex relationships in data. For example, students seeking confirmation of a linear relationship between increased elevation and increased precipitation study authentic data showing how the relationship is mediated by proximity to large bodies of water and storm paths.

Quantification of precipitation measurement discontinuity induced by wind shields on national gauges

USGS Publications Warehouse

Yang, Daqing; Goodison, Barry E.; Metcalfe, John R.; Louie, Paul; Leavesley, George H.; Emerson, Douglas G.; Hanson, Clayton L.; Golubev, Valentin S.; Elomaa, Esko; Gunther, Thilo; Pangburn, Timothy; Kang, Ersi; Milkovic, Janja

1999-01-01

Various combinations of wind shields and national precipitation gauges commonly used in countries of the northern hemisphere have been studied in this paper, using the combined intercomparison data collected at 14 sites during the World Meteorological Organization's (WMO) Solid Precipitation Measurement Intercomparison Project. The results show that wind shields improve gauge catch of precipitation, particularly for snow. Shielded gauges, on average, measure 20–70% more snow than unshielded gauges. Without a doubt, the use of wind shields on precipitation gauges has introduced a significant discontinuity into precipitation records, particularly in cold and windy regions. This discontinuity is not constant and it varies with wind speed, temperature, and precipitation type. Adjustment for this discontinuity is necessary to obtain homogenous precipitation data for climate change and hydrological studies. The relation of the relative catch ratio (RCR, ratio of measurements of shielded gauge to unshielded gauge) versus wind speed and temperature has been developed for Alter and Tretyakov wind shields. Strong linear relations between measurements of shielded gauge and unshielded gauge have also been found for different precipitation types. The linear relation does not fully take into account the varying effect of wind and temperature on gauge catch. Overadjustment by the linear relation may occur at those sites with lower wind speeds, and underadjustment may occur at those stations with higher wind speeds. The RCR technique is anticipated to be more applicable in a wide range of climate conditions. The RCR technique and the linear relation have been tested at selected WMO intercomparison stations, and reasonable agreement between the adjusted amounts and the shielded gauge measurements was obtained at most of the sites. Test application of the developed methodologies to a regional or national network is therefore recommended to further evaluate their applicability in different climate conditions. Significant increase of precipitation is expected due to the adjustment particularly in high latitudes and other cold regions. This will have a meaningful impact on climate variation and change analyses.

Food Crops Response to Climate Change

NASA Astrophysics Data System (ADS)

Butler, E.; Huybers, P.

2009-12-01

Projections of future climate show a warming world and heterogeneous changes in precipitation. Generally, warming temperatures indicate a decrease in crop yields where they are currently grown. However, warmer climate will also open up new areas at high latitudes for crop production. Thus, there is a question whether the warmer climate with decreased yields but potentially increased growing area will produce a net increase or decrease of overall food crop production. We explore this question through a multiple linear regression model linking temperature and precipitation to crop yield. Prior studies have emphasised temporal regression which indicate uniformly decreased yields, but neglect the potentially increased area opened up for crop production. This study provides a compliment to the prior work by exploring this spatial variation. We explore this subject with a multiple linear regression model from temperature, precipitation and crop yield data over the United States. The United States was chosen as the training region for the model because there are good crop data available over the same time frame as climate data and presumably the yield from crops in the United States is optimized with respect to potential yield. We study corn, soybeans, sorghum, hard red winter wheat and soft red winter wheat using monthly averages of temperature and precipitation from NCEP reanalysis and yearly yield data from the National Agriculture Statistics Service for 1948-2008. The use of monthly averaged temperature and precipitation, which neglect extreme events that can have a significant impact on crops limits this study as does the exclusive use of United States agricultural data. The GFDL 2.1 model under a 720ppm CO2 scenario provides temperature and precipitation fields for 2040-2100 which are used to explore how the spatial regions available for crop production will change under these new conditions.

Error Budget for a Calibration Demonstration System for the Reflected Solar Instrument for the Climate Absolute Radiance and Refractivity Observatory

NASA Technical Reports Server (NTRS)

Thome, Kurtis; McCorkel, Joel; McAndrew, Brendan

2013-01-01

A goal of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission is to observe highaccuracy, long-term climate change trends over decadal time scales. The key to such a goal is to improving the accuracy of SI traceable absolute calibration across infrared and reflected solar wavelengths allowing climate change to be separated from the limit of natural variability. The advances required to reach on-orbit absolute accuracy to allow climate change observations to survive data gaps exist at NIST in the laboratory, but still need demonstration that the advances can move successfully from to NASA and/or instrument vendor capabilities for spaceborne instruments. The current work describes the radiometric calibration error budget for the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. The goal of the CDS is to allow the testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. The resulting SI-traceable error budget for reflectance retrieval using solar irradiance as a reference and methods for laboratory-based, absolute calibration suitable for climatequality data collections is given. Key components in the error budget are geometry differences between the solar and earth views, knowledge of attenuator behavior when viewing the sun, and sensor behavior such as detector linearity and noise behavior. Methods for demonstrating this error budget are also presented.

Coupling climate and hydrological models to evaluate the impact of climate change on run of the river hydropower schemes from UK study sites

NASA Astrophysics Data System (ADS)

Pasten-Zapata, Ernesto; Jones, Julie; Moggridge, Helen

2015-04-01

As climate change is expected to generate variations on the Earth's precipitation and temperature, the water cycle will also experience changes. Consequently, water users will have to be prepared for possible changes in future water availability. The main objective of this research is to evaluate the impacts of climate change on river regimes and the implications to the operation and feasibility of run of the river hydropower schemes by analyzing four UK study sites. Run of the river schemes are selected for analysis due to their higher dependence to the available river flow volumes when compared to storage hydropower schemes that can rely on previously accumulated water volumes (linked to poster in session HS5.3). Global Climate Models (GCMs) represent the main tool to assess future climate change. In this research, Regional Climate Models (RCMs), which dynamically downscale GCM outputs providing higher resolutions, are used as starting point to evaluate climate change within the study catchments. RCM daily temperature and precipitation will be downscaled to an appropriate scale for impact studies and bias corrected using different statistical methods: linear scaling, local intensity scaling, power transformation, variance scaling and delta change correction. The downscaled variables will then be coupled to hydrological models that have been previously calibrated and validated against observed daily river flow data. The coupled hydrological and climate models will then be used to simulate historic river flows that are compared to daily observed values in order to evaluate the model accuracy. As this research will employ several different RCMs (from the EURO-CORDEX simulations), downscaling and bias correction methodologies, greenhouse emission scenarios and hydrological models, the uncertainty of each element will be estimated. According to their uncertainty magnitude, a prediction of the best downscaling approach (or approaches) is expected to be obtained. The current progress of the project will be presented along with the steps to be followed in the future.

Tropical climate trends inferred from coral δ18O: a comparison of CMIP5 forward-model results with paleoclimatic observations

NASA Astrophysics Data System (ADS)

Thompson, D. M.; Evans, M. N.; Cole, J. E.; Ault, T. R.; Emile-Geay, J.

2011-12-01

The response of the tropical Pacific Ocean to anthropogenic climate change remains highly uncertain, in part because of the disagreement among 20th-century trends derived from observations and coupled general circulation models (CGCMs). We use a model of reef coral oxygen isotopic composition (δ18O) to compare the observational coral network with synthetic corals ('pseudocorals') modeled from CGCM sea-surface temperature (SST) and sea-surface salinity (SSS). When driven with historical data, we found that a linear temperature and salinity driven model for δ18Ocoral was able to capture the spatial and temporal pattern of ENSO and the linear trend observed in 23 Indo-Pacific coral records between 1958 and 1990. However, we found that none of the pseudocoral networks obtained from a subset of 20th-century AR4 CGCM runs reproduced the magnitude of the secular trend, the change in mean state, or the change in ENSO-related variance observed in the coral network from 1890 to 1990 (Thompson et al., 2011). We believe differences between corals and AR4 CGCM simulated pseudocorals arose from uncertainties in the observed coral network or linear bivariate coral model, undersensitivity of AR4 CGCMs to radiative forcing during the 20th century, and/or biases in the simulated AR4 CGCM SSS fields. Here we apply the same approach to an extended temperature and salinity reanalysis product (SODA v2.2.4, 1871-2008) and CMIP 5 historical simulations to further address 20th-century tropical climate trends and assess remaining uncertainties in both the proxies and models. We explore whether model improvements in the tropical Pacific have led to a stronger agreement between simulated and observed tropical climate trends. [Thompson, D. M., T. R. Ault, M. N. Evans, J. E. Cole, and J. Emile-Geay (2011), Comparison of observed and simulated tropical climate trends using a forward model of coral δ18O, Geophys. Res. Lett., 38, L14706, doi:10.1029/2011GL048224.

The influence of classroom aggression and classroom climate on aggressive-disruptive behavior.

PubMed

Thomas, Duane E; Bierman, Karen L; Powers, C J

2011-01-01

Research suggests that early classroom experiences influence the socialization of aggression. Tracking changes in the aggressive behavior of 4,179 children from kindergarten to second-grade (ages 5-8), this study examined the impact of 2 important features of the classroom context--aggregate peer aggression and climates characterized by supportive teacher-student interactions. The aggregate aggression scores of children assigned to first-grade classrooms predicted the level of classroom aggression (assessed by teacher ratings) and quality of classroom climate (assessed by observers) that emerged by the end of Grade 1. Hierarchical linear model analyses revealed that first-grade classroom aggression and quality of classroom climate made independent contributions to changes in student aggression, as students moved from kindergarten to second grade. Implications for policy and practice are discussed. © 2011 The Authors. Child Development © 2011 Society for Research in Child Development, Inc.

Sensitivity of tropical carbon to climate change constrained by carbon dioxide variability.

PubMed

Cox, Peter M; Pearson, David; Booth, Ben B; Friedlingstein, Pierre; Huntingford, Chris; Jones, Chris D; Luke, Catherine M

2013-02-21

The release of carbon from tropical forests may exacerbate future climate change, but the magnitude of the effect in climate models remains uncertain. Coupled climate-carbon-cycle models generally agree that carbon storage on land will increase as a result of the simultaneous enhancement of plant photosynthesis and water use efficiency under higher atmospheric CO(2) concentrations, but will decrease owing to higher soil and plant respiration rates associated with warming temperatures. At present, the balance between these effects varies markedly among coupled climate-carbon-cycle models, leading to a range of 330 gigatonnes in the projected change in the amount of carbon stored on tropical land by 2100. Explanations for this large uncertainty include differences in the predicted change in rainfall in Amazonia and variations in the responses of alternative vegetation models to warming. Here we identify an emergent linear relationship, across an ensemble of models, between the sensitivity of tropical land carbon storage to warming and the sensitivity of the annual growth rate of atmospheric CO(2) to tropical temperature anomalies. Combined with contemporary observations of atmospheric CO(2) concentration and tropical temperature, this relationship provides a tight constraint on the sensitivity of tropical land carbon to climate change. We estimate that over tropical land from latitude 30° north to 30° south, warming alone will release 53 ± 17 gigatonnes of carbon per kelvin. Compared with the unconstrained ensemble of climate-carbon-cycle projections, this indicates a much lower risk of Amazon forest dieback under CO(2)-induced climate change if CO(2) fertilization effects are as large as suggested by current models. Our study, however, also implies greater certainty that carbon will be lost from tropical land if warming arises from reductions in aerosols or increases in other greenhouse gases.

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.

Climate legacy and lag effects on dryland plant communities in the southwestern U.S.

USGS Publications Warehouse

Bunting, Erin; Munson, Seth M.; Villarreal, Miguel

2017-01-01

Climate change effects on vegetation will likely be strong in the southwestern U.S., which is projected to experience large increases in temperature and changes in precipitation. Plant communities in the southwestern U.S. may be particularly vulnerable to climate change as the productivity of many plant species is strongly water-limited. This study examines the relationship between climate and vegetation condition using a time-series of Landsat imagery across grassland, shrubland, and woodland communities on the Colorado Plateau, USA. We improve on poorly understood inter-annual climate-vegetation relationships by exploring how the responses of different plant communities depend on climate legacies (>12 months) and lag behind shorter-term (3–12 month) changes in water availability. Our results show a prolonged drying trend on the Colorado Plateau since the early 1990s that was punctuated in several years by intense droughts. In areas that experienced sustained dry conditions or a drying trend, vegetation greenness (a proxy for production) increased linearly when conditions were interrupted by wetting events. In contrast, in areas that experienced sustained wet conditions or a wetting trend, vegetation greenness was weakly or not related to wetting events, indicating that production may saturate if vegetation experiences sufficient water availability. Shrubland and woodland communities had stronger relationships with climate at long lags (6–12 months) and many maintained greenness under sustained water deficit, whereas grassland communities had stronger relationships at short lags (3–6 months) and lost greenness even in periods of short-term drought. The results of our study show the importance of identifying climate legacies and lags when assessing indicators of ecological drought, which can be used to improve forecasts of which plant communities will be vulnerable under future climate change.

Sensitivity of a global climate model to the critical Richardson number in the boundary layer parameterization

DOE PAGES

Zhang, Ning; Liu, Yangang; Gao, Zhiqiu; ...

2015-04-27

The critical bulk Richardson number (Ri cr) is an important parameter in planetary boundary layer (PBL) parameterization schemes used in many climate models. This paper examines the sensitivity of a Global Climate Model, the Beijing Climate Center Atmospheric General Circulation Model, BCC_AGCM to Ri cr. The results show that the simulated global average of PBL height increases nearly linearly with Ri cr, with a change of about 114 m for a change of 0.5 in Ri cr. The surface sensible (latent) heat flux decreases (increases) as Ri cr increases. The influence of Ri cr on surface air temperature and specificmore » humidity is not significant. The increasing Ri cr may affect the location of the Westerly Belt in the Southern Hemisphere. Further diagnosis reveals that changes in Ri cr affect stratiform and convective precipitations differently. Increasing Ri cr leads to an increase in the stratiform precipitation but a decrease in the convective precipitation. Significant changes of convective precipitation occur over the inter-tropical convergence zone, while changes of stratiform precipitation mostly appear over arid land such as North Africa and Middle East.« less

Impacts of agricultural management and climate change on future soil organic carbon dynamics in North China Plain.

PubMed

Wang, Guocheng; Li, Tingting; Zhang, Wen; Yu, Yongqiang

2014-01-01

Dynamics of cropland soil organic carbon (SOC) in response to different management practices and environmental conditions across North China Plain (NCP) were studied using a modeling approach. We identified the key variables driving SOC changes at a high spatial resolution (10 km × 10 km) and long time scale (90 years). The model used future climatic data from the FGOALS model based on four future greenhouse gas (GHG) concentration scenarios. Agricultural practices included different rates of nitrogen (N) fertilization, manure application, and stubble retention. We found that SOC change was significantly influenced by the management practices of stubble retention (linearly positive), manure application (linearly positive) and nitrogen fertilization (nonlinearly positive) - and the edaphic variable of initial SOC content (linearly negative). Temperature had weakly positive effects, while precipitation had negligible impacts on SOC dynamics under current irrigation management. The effects of increased N fertilization on SOC changes were most significant between the rates of 0 and 300 kg ha-1 yr-1. With a moderate rate of manure application (i.e., 2000 kg ha-1 yr-1), stubble retention (i.e., 50%), and an optimal rate of nitrogen fertilization (i.e., 300 kg ha-1 yr-1), more than 60% of the study area showed an increase in SOC, and the average SOC density across NCP was relatively steady during the study period. If the rates of manure application and stubble retention doubled (i.e., manure application rate of 4000 kg ha-1 yr-1 and stubble retention rate of 100%), soils across more than 90% of the study area would act as a net C sink, and the average SOC density kept increasing from 40 Mg ha-1 during 2010s to the current worldwide average of ∼ 55 Mg ha-1 during 2060s. The results can help target agricultural management practices for effectively mitigating climate change through soil C sequestration.

Impacts of Agricultural Management and Climate Change on Future Soil Organic Carbon Dynamics in North China Plain

PubMed Central

Wang, Guocheng; Li, Tingting; Zhang, Wen; Yu, Yongqiang

2014-01-01

Dynamics of cropland soil organic carbon (SOC) in response to different management practices and environmental conditions across North China Plain (NCP) were studied using a modeling approach. We identified the key variables driving SOC changes at a high spatial resolution (10 km×10 km) and long time scale (90 years). The model used future climatic data from the FGOALS model based on four future greenhouse gas (GHG) concentration scenarios. Agricultural practices included different rates of nitrogen (N) fertilization, manure application, and stubble retention. We found that SOC change was significantly influenced by the management practices of stubble retention (linearly positive), manure application (linearly positive) and nitrogen fertilization (nonlinearly positive) – and the edaphic variable of initial SOC content (linearly negative). Temperature had weakly positive effects, while precipitation had negligible impacts on SOC dynamics under current irrigation management. The effects of increased N fertilization on SOC changes were most significant between the rates of 0 and 300 kg ha−1 yr−1. With a moderate rate of manure application (i.e., 2000 kg ha−1 yr−1), stubble retention (i.e., 50%), and an optimal rate of nitrogen fertilization (i.e., 300 kg ha−1 yr−1), more than 60% of the study area showed an increase in SOC, and the average SOC density across NCP was relatively steady during the study period. If the rates of manure application and stubble retention doubled (i.e., manure application rate of 4000 kg ha−1 yr−1 and stubble retention rate of 100%), soils across more than 90% of the study area would act as a net C sink, and the average SOC density kept increasing from 40 Mg ha−1 during 2010s to the current worldwide average of ∼55 Mg ha−1 during 2060s. The results can help target agricultural management practices for effectively mitigating climate change through soil C sequestration. PMID:24722689

Predicting the response of seven Asian glaciers to future climate scenarios using a simple linear glacier model

NASA Astrophysics Data System (ADS)

Ren, Diandong; Karoly, David J.

2008-03-01

Observations from seven Central Asian glaciers (35-55°N; 70-95°E) are used, together with regional temperature data, to infer uncertain parameters for a simple linear model of the glacier length variations. The glacier model is based on first order glacier dynamics and requires the knowledge of reference states of forcing and glacier perturbation magnitude. An adjoint-based variational method is used to optimally determine the glacier reference states in 1900 and the uncertain glacier model parameters. The simple glacier model is then used to estimate the glacier length variations until 2060 using regional temperature projections from an ensemble of climate model simulations for a future climate change scenario (SRES A2). For the period 2000-2060, all glaciers are projected to experience substantial further shrinkage, especially those with gentle slopes (e.g., Glacier Chogo Lungma retreats ˜4 km). Although nearly one-third of the year 2000 length will be reduced for some small glaciers, the existence of the glaciers studied here is not threatened by year 2060. The differences between the individual glacier responses are large. No straightforward relationship is found between glacier size and the projected fractional change of its length.

Developing effective communication materials on the health effects of climate change for vulnerable groups: a mixed methods study.

PubMed

Kreslake, Jennifer M; Price, Katherine M; Sarfaty, Mona

2016-09-07

Individuals with chronic health conditions or low socioeconomic status (SES) are more vulnerable to the health impacts of climate change. Health communication can provide information on the management of these impacts. This study tested, among vulnerable audiences, whether viewing targeted materials increases knowledge about the health impacts of climate change and strength of climate change beliefs, and whether each are associated with stronger intentions to practice recommended behaviors. Low-SES respondents with chronic conditions were recruited for an online survey in six cities. Respondents were shown targeted materials illustrating the relationship between climate change and chronic conditions. Changes in knowledge and climate change beliefs (pre- and post-test) and behavioral intentions (post-test only) were tested using McNemar tests of marginal frequencies of two binary outcomes or paired t-tests, and multivariable linear regression. Qualitative interviews were conducted among target audiences to triangulate survey findings and make recommendations on the design of messages. Respondents (N = 122) reflected the target population regarding income, educational level and prevalence of household health conditions. (1) Knowledge. Significant increases in knowledge were found regarding: groups that are most vulnerable to heat (children [p < 0.001], individuals with heart disease [p < 0.001], or lung disease [p = 0.019]); and environmental conditions that increase allergy-producing pollen (increased heat [p = 0.003], increased carbon dioxide [p < 0.001]). (2) Strength of certainty that climate change is happening increased significantly between pre- and post-test (p < 0.001), as did belief that climate change affected respondents' health (p < 0.001). (3) Behavioral intention. At post-test, higher knowledge of heat vulnerabilities and environmental conditions that trigger pollen allergies were associated with greater behavioral intention scores (p = 0.001 and p = 0.002, respectively). In-depth interviews (N = 15) revealed that vulnerable audiences are interested in immediate-term advice on health management and protective behaviors related to their chronic conditions, but took less notice of messages about collective action to slow or stop climate change. Respondents identified both appealing and less favorable design elements in the materials. Individuals who are vulnerable to the health effects of climate change benefit from communication materials that explain, using graphics and concise language, how climate change affects health conditions and how to engage in protective adaptation behaviors.

Inferring climate variability from skewed proxy records

NASA Astrophysics Data System (ADS)

Emile-Geay, J.; Tingley, M.

2013-12-01

Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and compared to other proxy records. (2) a multiproxy reconstruction of temperature over the Common Era (Mann et al., 2009), where we find that about one third of the records display significant departures from normality. Accordingly, accounting for skewness in proxy predictors has a notable influence on both reconstructed global mean and spatial patterns of temperature change. Inferring climate variability from skewed proxy records thus requires cares, but can be done with relatively simple tools. References - Mann, M. E., Z. Zhang, S. Rutherford, R. S. Bradley, M. K. Hughes, D. Shindell, C. Ammann, G. Faluvegi, and F. Ni (2009), Global signatures and dynamical origins of the little ice age and medieval climate anomaly, Science, 326(5957), 1256-1260, doi:10.1126/science.1177303. - Moy, C., G. Seltzer, D. Rodbell, and D. Anderson (2002), Variability of El Niño/Southern Oscillation activ- ity at millennial timescales during the Holocene epoch, Nature, 420(6912), 162-165.

Assessing the present and future probability of Hurricane Harvey's rainfall

NASA Astrophysics Data System (ADS)

Emanuel, Kerry

2017-11-01

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981–2000 and will increase to 18% over the period 2081–2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century.

Temporal Changes in Mortality Related to Extreme Temperatures for 15 Cities in Northeast Asia: Adaptation to Heat and Maladaptation to Cold.

PubMed

Chung, Yeonseung; Noh, Heesang; Honda, Yasushi; Hashizume, Masahiro; Bell, Michelle L; Guo, Yue-Liang Leon; Kim, Ho

2017-05-15

Understanding how the temperature-mortality association worldwide changes over time is crucial to addressing questions of human adaptation under climate change. Previous studies investigated the temporal changes in the association over a few discrete time frames or assumed a linear change. Also, most studies focused on attenuation of heat-related mortality and studied the United States or Europe. This research examined continuous temporal changes (potentially nonlinear) in mortality related to extreme temperature (both heat and cold) for 15 cities in Northeast Asia (1972-2009). We used a generalized linear model with splines to simultaneously capture 2 types of nonlinearity: nonlinear association between temperature and mortality and nonlinear change over time in the association. We combined city-specific results to generate country-specific results using Bayesian hierarchical modeling. Cold-related mortality remained roughly constant over decades and slightly increased in the late 2000s, with a larger increase for cardiorespiratory deaths than for deaths from other causes. Heat-related mortality rates have decreased continuously over time, with more substantial decrease in earlier decades, for older populations and for cardiorespiratory deaths. Our findings suggest that future assessment of health effects of climate change should account for the continuous changes in temperature-related health risk and variations by factors such as age, cause of death, and location. © Crown copyright 2017.

Temporal Variation Analysis on Climate of Dry-Hot Valley Since 1950s in Upper Yangtze River Basin, China

NASA Astrophysics Data System (ADS)

Sun, L.; Cai, Y.

2017-12-01

Climate of dry-hot valley areas regarding their long term temporal changes are seldom studied. In this paper, climate change in lower reach of Yalongjiang River, a typical dry-hot valley area locating in upper Yangtze River Basin, was analyzed. Ten single meteorological factors were used to investigate basic climatic characteristics, and two integrated index (i.e. relative evapotranspiration(AET/P), standard precipitation evapotranspiration index(SPEI)) were selected to reflect changes from human activities and gauge climate drought regime. Mann-Kendall mutation test was applied to identify mutation year, and variation trends were diagnosed with linear regression and distance average analysis. Mean values were tested to find if there were significant changes resulting from a large artificial reservoir constructed in 1999. Results of mutation test showed that minimum temperature, relative humidity, and AET/P in two stations changed significantly in 2000s. Temperature increased since 1990s, and other single index fluctuated in recent 50 years. Precipitation decreased and temperature increased in autumn significantly, while precipitation in summer decreased slightly. The variation of SPEI implied that the area was humid from 1980s to 2000s, but drought in 2010s. The results of mean test indicated that 56% meteorological index changed significantly, which might be related to the construction of the large reservoir. This research not only reveals the climate change in a dry-hot valley, but also helps study concerning human activities especially the construction of cascade reservoirs in the future in this area.

Stationary Waves of the Ice Age Climate.

NASA Astrophysics Data System (ADS)

Cook, Kerry H.; Held, Isaac M.

1988-08-01

A linearized, steady state, primitive equation model is used to simulate the climatological zonal asymmetries (stationary eddies) in the wind and temperature fields of the 18 000 YBP climate during winter. We compare these results with the eddies simulated in the ice age experiments of Broccoli and Manabe, who used CLIMAP boundary conditions and reduced atmospheric CO2 in an atmospheric general circulation model (GCM) coupled with a static mixed layer ocean model. The agreement between the models is good, indicating that the linear model can be used to evaluate the relative influences of orography, diabatic heating, and transient eddy heat and momentum transports in generating stationary waves. We find that orographic forcing dominates in the ice age climate. The mechanical influence of the continental ice sheets on the atmosphere is responsible for most of the changes between the present day and ice age stationary eddies. This concept of the ice age climate is complicated by the sensitivity of the stationary eddies to the large increase in the magnitude of the zonal mean meridional temperature gradient simulated in the ice age GCM.

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species.

PubMed

Pomara, Lars Y; LeDee, Olivia E; Martin, Karl J; Zuckerberg, Benjamin

2014-07-01

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range-wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back-cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long-term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long-term demographic decline and range contraction for a species of high-conservation concern. Range-wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal-limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management. © 2013 John Wiley & Sons Ltd.

Northern Winter Climate Change: Assessment of Uncertainty in CMIP5 Projections Related to Stratosphere-Troposphere Coupling

NASA Technical Reports Server (NTRS)

Manzini, E.; Karpechko, A.Yu.; Anstey, J.; Shindell, Drew Todd; Baldwin, M.P.; Black, R.X.; Cagnazzo, C.; Calvo, N.; Charlton-Perez, A.; Christiansen, B.;

Linking the Mediterranean regional and the global climate change

NASA Astrophysics Data System (ADS)

Lionello, Piero; Scarascia, Luca

2017-04-01

This contribution analyzes 22 CMIP5 global climate projections to show how is the regional climate change in the Mediterranean related to the global climate change. The aim is to use these recent results to revisit evidences suggesting that the Mediterranean region is a climate change hot spot. Results show that future increase of temperature in the Mediterranean region has a strong seasonal connotation, with summer warming at a pace 40% larger than the global mean. This future trend is consistent with the global reduction of the meridional temperature gradient that is produced by climate change. However spatial distribution of changes shows a strong a sub-regional modulation depending of the land-sea contrast, the role of soil moisture feedback and changes of large scale atmospheric circulation leading to increased subsidence conditions. Projections show that precipitation decrease will affect most of the region, but with a strong difference between southern and northern areas, where CMIP5 projections suggest a 7% and 3% decrease of annual precipitation for each degree of global warming, respectively. For both Mediterranean temperature and precipitation, the dependence is substantially linear in the range up to 40C of global warming. Interannual variability and intermodel differences are a substantial source of uncertainty for precipitation (while there is a robust consensus for temperature changes). Therefore, future precipitation changes are still a controversial issue, in terms of intensity and precise location of the transition belt that separates the decrease of precipitation over the MR from areas in central and northern Europe, where precipitation is expected to increase. On this respect, though the overall drying trend appears consolidated in the scientific literature, its precise evaluation remains to some extent controversial.

The influence of ENSO, PDO and PNA on secular rainfall variations in Hawai`i

NASA Astrophysics Data System (ADS)

Frazier, Abby G.; Elison Timm, Oliver; Giambelluca, Thomas W.; Diaz, Henry F.

2017-11-01

Over the last century, significant declines in rainfall across the state of Hawai`i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for these long-term trends. Gridded seasonal rainfall from 1920 to 2012 is used to perform an empirical orthogonal function (EOF) analysis. The leading EOF components are correlated with three indices of natural climate variations (El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Pacific North American (PNA)), and multiple linear regression (MLR) is used to model the leading components with climate indices. PNA is the dominant mode of wet season (November-April) variability, while ENSO is most significant in the dry season (May-October). To assess whether there is an anthropogenic influence on rainfall, two methods are used: a linear trend term is included in the MLR, and pattern correlation coefficients (PCC) are calculated between recent rainfall trends and future changes in rainfall projected by downscaling methods. PCC results indicate that recent observed rainfall trends in the wet season are positively correlated with future expected changes in rainfall, while dry season PCC results do not show a clear pattern. The MLR results, however, show that the trend term adds significantly to model skill only in the dry season. Overall, MLR and PCC results give weak and inconclusive evidence for detection of anthropogenic signals in the observed rainfall trends.

Climate Tolerances and Habitat Requirements Jointly Shape the Elevational Distribution of the American Pika (Ochotona princeps), with Implications for Climate Change Effects.

PubMed

Yandow, Leah H; Chalfoun, Anna D; Doak, Daniel F

2015-01-01

Some of the most compelling examples of ecological responses to climate change are elevational range shifts of individual species, which have been observed throughout the world. A growing body of evidence, however, suggests substantial mediation of simple range shifts due to climate change by other limiting factors. Understanding limiting factors for a species within different contexts, therefore, is critical for predicting responses to climate change. The American pika (Ochotona princeps) is an ideal species for investigating distributions in relation to climate because of their unusual and well-understood natural history as well as observed shifts to higher elevation in parts of their range. We tested three hypotheses for the climatic or habitat characteristics that may limit pika presence and abundance: summer heat, winter snowpack, and forage availability. We performed these tests using an index of pika abundance gathered in a region where environmental influences on pika distribution have not been well-characterized. We estimated relative pika abundance via scat surveys and quantified climatic and habitat characteristics across two North-Central Rocky Mountain Ranges, the Wind River and Bighorn ranges in Wyoming, USA. Pika scat density was highest at mid-elevations and increased linearly with forage availability in both ranges. Scat density also increased with temperatures conducive to forage plant growth, and showed a unimodal relationship with the number of days below -5°C, which is modulated by insulating snowpack. Our results provide support for both the forage availability and winter snowpack hypotheses. Especially in montane systems, considering the context-dependent nature of climate effects across regions and elevations as well as interactions between climatic and other critical habitat characteristics, will be essential for predicting future species distributions.

Climate Tolerances and Habitat Requirements Jointly Shape the Elevational Distribution of the American Pika (Ochotona princeps), with Implications for Climate Change Effects

PubMed Central

Yandow, Leah H.; Chalfoun, Anna D.; Doak, Daniel F.

2015-01-01

Some of the most compelling examples of ecological responses to climate change are elevational range shifts of individual species, which have been observed throughout the world. A growing body of evidence, however, suggests substantial mediation of simple range shifts due to climate change by other limiting factors. Understanding limiting factors for a species within different contexts, therefore, is critical for predicting responses to climate change. The American pika (Ochotona princeps) is an ideal species for investigating distributions in relation to climate because of their unusual and well-understood natural history as well as observed shifts to higher elevation in parts of their range. We tested three hypotheses for the climatic or habitat characteristics that may limit pika presence and abundance: summer heat, winter snowpack, and forage availability. We performed these tests using an index of pika abundance gathered in a region where environmental influences on pika distribution have not been well-characterized. We estimated relative pika abundance via scat surveys and quantified climatic and habitat characteristics across two North-Central Rocky Mountain Ranges, the Wind River and Bighorn ranges in Wyoming, USA. Pika scat density was highest at mid-elevations and increased linearly with forage availability in both ranges. Scat density also increased with temperatures conducive to forage plant growth, and showed a unimodal relationship with the number of days below -5°C, which is modulated by insulating snowpack. Our results provide support for both the forage availability and winter snowpack hypotheses. Especially in montane systems, considering the context-dependent nature of climate effects across regions and elevations as well as interactions between climatic and other critical habitat characteristics, will be essential for predicting future species distributions. PMID:26244851

Climate tolerances and habitat requirements jointly shape the elevational distribution of the American Pika (Ochotona princeps), with implications for climate change effects

USGS Publications Warehouse

Yandow, Leah H.; Chalfoun, Anna D.; Doak, Daniel F.

2015-01-01

Some of the most compelling examples of ecological responses to climate change are elevational range shifts of individual species, which have been observed throughout the world. A growing body of evidence, however, suggests substantial mediation of simple range shifts due to climate change by other limiting factors. Understanding limiting factors for a species within different contexts, therefore, is critical for predicting responses to climate change. The American pika (Ochotona princeps) is an ideal species for investigating distributions in relation to climate because of their unusual and well-understood natural history as well as observed shifts to higher elevation in parts of their range. We tested three hypotheses for the climatic or habitat characteristics that may limit pika presence and abundance: summer heat, winter snowpack, and forage availability. We performed these tests using an index of pika abundance gathered in a region where environmental influences on pika distribution have not been well-characterized. We estimated relative pika abundance via scat surveys and quantified climatic and habitat characteristics across two North-Central Rocky Mountain Ranges, the Wind River and Bighorn ranges in Wyoming, USA. Pika scat density was highest at mid-elevations and increased linearly with forage availability in both ranges. Scat density also increased with temperatures conducive to forage plant growth, and showed a unimodal relationship with the number of days below -5°C, which is modulated by insulating snowpack. Our results provide support for both the forage availability and winter snowpack hypotheses. Especially in montane systems, considering the context-dependent nature of climate effects across regions and elevations as well as interactions between climatic and other critical habitat characteristics, will be essential for predicting future species distributions.

Seasonal hydrologic responses to climate change in the Pacific Northwest

NASA Astrophysics Data System (ADS)

Vano, Julie A.; Nijssen, Bart; Lettenmaier, Dennis P.

2015-04-01

Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land-surface hydrology model applied at 1/16° latitude-longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC-8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin-specific transfer functions to estimate future changes in long-term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first-order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations.

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

PubMed Central

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

2016-01-01

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

Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change

PubMed Central

Benmarhnia, Tarik; Grenier, Patrick; Brand, Allan; Fournier, Michel; Deguen, Séverine; Smargiassi, Audrey

2015-01-01

Objectives: We propose a novel approach to examine vulnerability in the relationship between heat and years of life lost and apply to neighborhood social disparities in Montreal and Paris. Methods: We used historical data from the summers of 1990 through 2007 for Montreal and from 2004 through 2009 for Paris to estimate daily years of life lost social disparities (DYLLD), summarizing social inequalities across groups. We used Generalized Linear Models to separately estimate relative risks (RR) for DYLLD in association with daily mean temperatures in both cities. We used 30 climate scenarios of daily mean temperature to estimate future temperature distributions (2021–2050). We performed random effect meta-analyses to assess the impact of climate change by climate scenario for each city and compared the impact of climate change for the two cities using a meta-regression analysis. Results: We show that an increase in ambient temperature leads to an increase in social disparities in daily years of life lost. The impact of climate change on DYLLD attributable to temperature was of 2.06 (95% CI: 1.90, 2.25) in Montreal and 1.77 (95% CI: 1.61, 1.94) in Paris. The city explained a difference of 0.31 (95% CI: 0.14, 0.49) on the impact of climate change. Conclusion: We propose a new analytical approach for estimating vulnerability in the relationship between heat and health. Our results suggest that in Paris and Montreal, health disparities related to heat impacts exist today and will increase in the future. PMID:26402690

Quantifying Vulnerability to Extreme Heat in Time Series Analyses: A Novel Approach Applied to Neighborhood Social Disparities under Climate Change.

PubMed

Benmarhnia, Tarik; Grenier, Patrick; Brand, Allan; Fournier, Michel; Deguen, Séverine; Smargiassi, Audrey

2015-09-22

We propose a novel approach to examine vulnerability in the relationship between heat and years of life lost and apply to neighborhood social disparities in Montreal and Paris. We used historical data from the summers of 1990 through 2007 for Montreal and from 2004 through 2009 for Paris to estimate daily years of life lost social disparities (DYLLD), summarizing social inequalities across groups. We used Generalized Linear Models to separately estimate relative risks (RR) for DYLLD in association with daily mean temperatures in both cities. We used 30 climate scenarios of daily mean temperature to estimate future temperature distributions (2021-2050). We performed random effect meta-analyses to assess the impact of climate change by climate scenario for each city and compared the impact of climate change for the two cities using a meta-regression analysis. We show that an increase in ambient temperature leads to an increase in social disparities in daily years of life lost. The impact of climate change on DYLLD attributable to temperature was of 2.06 (95% CI: 1.90, 2.25) in Montreal and 1.77 (95% CI: 1.61, 1.94) in Paris. The city explained a difference of 0.31 (95% CI: 0.14, 0.49) on the impact of climate change. We propose a new analytical approach for estimating vulnerability in the relationship between heat and health. Our results suggest that in Paris and Montreal, health disparities related to heat impacts exist today and will increase in the future.

Reply to communications by Fu et al. international journal of biometeorology

NASA Astrophysics Data System (ADS)

Wang, Huanjiong; Rutishauser, This; Tao, Zexing; Zhong, Shuying; Ge, Quansheng; Dai, Junhu

2016-12-01

Temperature sensitivity of plant phenology (ST) is a determining factor of as to what degree climate change impacts on plant species. Fu et al . (Int J Biometeorol 60:1611-1613, 2016) claimed that long long-term linear trends mask phenological shifts. However, the decreased and increased ST was both found in warming scenarios. The conceptual scheme telling the nonlinear relationship between spring temperature and leaf unfolding date proposed by Fu et al . (Int J Biometeorol 60:1611-1613, 2016) cannot be supported by observation data across Europe. Therefore, linking declined ST to climate warming is misleading, and future ST changes are more uncertain than they suggested.

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus)

PubMed Central

Catto, Sarah; Mutumi, Gregory L.; Finger, Nikita; Webala, Paul W.

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy’s horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency. PMID:29186147

Testing the Sensory Drive Hypothesis: Geographic variation in echolocation frequencies of Geoffroy's horseshoe bat (Rhinolophidae: Rhinolophus clivosus).

PubMed

Jacobs, David S; Catto, Sarah; Mutumi, Gregory L; Finger, Nikita; Webala, Paul W

2017-01-01

Geographic variation in sensory traits is usually influenced by adaptive processes because these traits are involved in crucial life-history aspects including orientation, communication, lineage recognition and mate choice. Studying this variation can therefore provide insights into lineage diversification. According to the Sensory Drive Hypothesis, lineage diversification may be driven by adaptation of sensory systems to local environments. It predicts that acoustic signals vary in association with local climatic conditions so that atmospheric attenuation is minimized and transmission of the signals maximized. To test this prediction, we investigated the influence of climatic factors (specifically relative humidity and temperature) on geographic variation in the resting frequencies of the echolocation pulses of Geoffroy's horseshoe bat, Rhinolophus clivosus. If the evolution of phenotypic variation in this lineage tracks climate variation, human induced climate change may lead to decreases in detection volumes and a reduction in foraging efficiency. A complex non-linear interaction between relative humidity and temperature affects atmospheric attenuation of sound and principal components composed of these correlated variables were, therefore, used in a linear mixed effects model to assess their contribution to observed variation in resting frequencies. A principal component composed predominantly of mean annual temperature (factor loading of -0.8455) significantly explained a proportion of the variation in resting frequency across sites (P < 0.05). Specifically, at higher relative humidity (around 60%) prevalent across the distribution of R. clivosus, increasing temperature had a strong negative effect on resting frequency. Climatic factors thus strongly influence acoustic signal divergence in this lineage, supporting the prediction of the Sensory Drive Hypothesis. The predicted future increase in temperature due to climate change is likely to decrease the detection volume in echolocating bats and adversely impact their foraging efficiency.

A new statistical approach to climate change detection and attribution

NASA Astrophysics Data System (ADS)

Ribes, Aurélien; Zwiers, Francis W.; Azaïs, Jean-Marc; Naveau, Philippe

2017-01-01

We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the " models are statistically indistinguishable from the truth" paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951-2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 ± 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings (-0.01± 0.02 K).

Identifying ontogenetic, environmental and individual components of forest tree growth

PubMed Central

Chaubert-Pereira, Florence; Caraglio, Yves; Lavergne, Christian; Guédon, Yann

2009-01-01

Background and Aims This study aimed to identify and characterize the ontogenetic, environmental and individual components of forest tree growth. In the proposed approach, the tree growth data typically correspond to the retrospective measurement of annual shoot characteristics (e.g. length) along the trunk. Methods Dedicated statistical models (semi-Markov switching linear mixed models) were applied to data sets of Corsican pine and sessile oak. In the semi-Markov switching linear mixed models estimated from these data sets, the underlying semi-Markov chain represents both the succession of growth phases and their lengths, while the linear mixed models represent both the influence of climatic factors and the inter-individual heterogeneity within each growth phase. Key Results On the basis of these integrative statistical models, it is shown that growth phases are not only defined by average growth level but also by growth fluctuation amplitudes in response to climatic factors and inter-individual heterogeneity and that the individual tree status within the population may change between phases. Species plasticity affected the response to climatic factors while tree origin, sampling strategy and silvicultural interventions impacted inter-individual heterogeneity. Conclusions The transposition of the proposed integrative statistical modelling approach to cambial growth in relation to climatic factors and the study of the relationship between apical growth and cambial growth constitute the next steps in this research. PMID:19684021

Effects of future climate and land use scenarios on riverine source water quality.

PubMed

Delpla, Ianis; Rodriguez, Manuel J

2014-09-15

Surface water quality is particularly sensitive to land use practices and climatic events that affect its catchment. The relative influence of a set of watershed characteristics (climate, land use, morphology and pedology) and climatic variables on two key water quality parameters (turbidity and fecal coliforms (FC)) was examined in 24 eastern Canadian catchments at various spatial scales (1 km, 5 km, 10 km and the entire catchment). A regression analysis revealed that the entire catchment was a better predictor of water quality. Based on this information, linear mixed effect models for predicting turbidity and FC levels were developed. A set of land use and climate scenarios was considered and applied within the water quality models. Four land use scenarios (no change, same rate of variation, optimistic and pessimistic) and three climate change scenarios (B1, A1B and A2) were tested and variations for the near future (2025) were assessed and compared to the reference period (2000). Climate change impacts on water quality remained low annually for this time horizon (turbidity: +1.5%, FC: +1.6%, A2 scenario). On the other hand, the influence of land use changes appeared to predominate. Significant benefits for both parameters could be expected following the optimistic scenario (turbidity: -16.4%, FC: -6.3%; p < 0.05). However, pessimistic land use scenario led to significant increases on an annual basis (turbidity: +11.6%, FC: +15.2%; p < 0.05). Additional simulations conducted for the late 21st century (2090) revealed that climate change impacts could become equivalent to those modeled for land use for this horizon. Copyright © 2014 Elsevier B.V. All rights reserved.

Historical factors shaped species diversity and composition of Salix in eastern Asia.

PubMed

Wang, Qinggang; Su, Xiangyan; Shrestha, Nawal; Liu, Yunpeng; Wang, Siyang; Xu, Xiaoting; Wang, Zhiheng

2017-02-08

Ambient energy, niche conservatism, historical climate stability and habitat heterogeneity hypothesis have been proposed to explain the broad-scale species diversity patterns and species compositions, while their relative importance have been controversial. Here, we assessed the relative contributions of contemporary climate, historical climate changes and habitat heterogeneity in shaping Salix species diversity and species composition in whole eastern Asia as well as mountains and lowlands using linear regressions and distance-based redundancy analyses, respectively. Salix diversity was negatively related with mean annual temperature. Habitat heterogeneity was more important than contemporary climate in shaping Salix diversity patterns, and their relative contributions were different in mountains and lowlands. In contrast, the species composition was strongly influenced by contemporary climate and historical climate change than habitat heterogeneity, and their relative contributions were nearly the same both in mountains and lowlands. Our findings supported niche conservatism and habitat heterogeneity hypotheses, but did not support ambient energy and historical climate stability hypotheses. The diversity pattern and species composition of Salix could not be well-explained by any single hypothesis tested, suggesting that other factors such as disturbance history and diversification rate may be also important in shaping the diversity pattern and composition of Salix species.

Plant responses, climate pivot points, and trade-offs in water-limited ecosystems

NASA Astrophysics Data System (ADS)

Munson, S. M.; Bunting, E.

2017-12-01

Ecosystem transitions and thresholds are conceptually well-defined and have become a framework to address vegetation response to climate change and land-use intensification, yet there are few approaches to define the environmental conditions which can lead to them. We demonstrate a novel climate pivot point approach using long-term monitoring data from a broad network of permanent plots, satellite imagery, and experimental treatments across the southwestern U.S. The climate pivot point identifies conditions that lead to decreased plant performance and serves as an early warning sign of increased vulnerability of crossing a threshold into an altered ecosystem state. Plant responses and climate pivot points aligned with the lifespan and structural characteristics of species, were modified by soil and landscape attributes of a site, and had non-linear dynamics in some cases. Species with strong increases in abundance when water was available were most susceptible to losses during water shortages, reinforcing plant energetic and physiological tradeoffs. Future research to uncover the heterogeneity of plant responses and climate pivot points at multiple scales can lead to greater understanding of shifts in ecosystem productivity and vulnerability to climate change.

Historical factors shaped species diversity and composition of Salix in eastern Asia

PubMed Central

Wang, Qinggang; Su, Xiangyan; Shrestha, Nawal; Liu, Yunpeng; Wang, Siyang; Xu, Xiaoting; Wang, Zhiheng

2017-01-01

Ambient energy, niche conservatism, historical climate stability and habitat heterogeneity hypothesis have been proposed to explain the broad-scale species diversity patterns and species compositions, while their relative importance have been controversial. Here, we assessed the relative contributions of contemporary climate, historical climate changes and habitat heterogeneity in shaping Salix species diversity and species composition in whole eastern Asia as well as mountains and lowlands using linear regressions and distance-based redundancy analyses, respectively. Salix diversity was negatively related with mean annual temperature. Habitat heterogeneity was more important than contemporary climate in shaping Salix diversity patterns, and their relative contributions were different in mountains and lowlands. In contrast, the species composition was strongly influenced by contemporary climate and historical climate change than habitat heterogeneity, and their relative contributions were nearly the same both in mountains and lowlands. Our findings supported niche conservatism and habitat heterogeneity hypotheses, but did not support ambient energy and historical climate stability hypotheses. The diversity pattern and species composition of Salix could not be well-explained by any single hypothesis tested, suggesting that other factors such as disturbance history and diversification rate may be also important in shaping the diversity pattern and composition of Salix species. PMID:28176816

Modeling workplace bullying using catastrophe theory.

PubMed

Escartin, J; Ceja, L; Navarro, J; Zapf, D

2013-10-01

Workplace bullying is defined as negative behaviors directed at organizational members or their work context that occur regularly and repeatedly over a period of time. Employees' perceptions of psychosocial safety climate, workplace bullying victimization, and workplace bullying perpetration were assessed within a sample of nearly 5,000 workers. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes in workplace bullying. More specifically, the present study examines whether a nonlinear dynamical systems model (i.e., a cusp catastrophe model) is superior to the linear combination of variables for predicting the effect of psychosocial safety climate and workplace bullying victimization on workplace bullying perpetration. According to the AICc, and BIC indices, the linear regression model fits the data better than the cusp catastrophe model. The study concludes that some phenomena, especially unhealthy behaviors at work (like workplace bullying), may be better studied using linear approaches as opposed to nonlinear dynamical systems models. This can be explained through the healthy variability hypothesis, which argues that positive organizational behavior is likely to present nonlinear behavior, while a decrease in such variability may indicate the occurrence of negative behaviors at work.

U.S. Federal Investments in Climate Change Education: They're Warming Up! (Invited)

NASA Astrophysics Data System (ADS)

Karsten, J. L.; Niepold, F.; Wei, M.; Usgcrp Education Interagency Working Group

2010-12-01

Many similarities exist between the U.S. federal government and the climate system, in terms of their complexity. Government operates through a dynamic interplay of sub-systems (different agencies), pressure gradients (political interests), energy transformations (converting dollars into activity through Congressional appropriations, grants and contracts), and non-linear positive and negative feedback mechanisms (MOU’s, competing agency missions). ‘Viscosity’ in the system makes progress difficult. The good news is that, like the climate, federal investments in climate change education are heating up, due to man-made inputs. Individual agency investments in projects to improve and monitor public understanding of climate change and its impacts are rapidly becoming more coupled and coherent. This paper will discuss several efforts now underway. In FY 2009, dedicated, multi-million dollar funding led to creation of NSF’s Climate Change Education (CCE) and NASA’s Global Climate Change Education (GCCE) grant programs, which are funding a projects to develop pedagogically-sound learning resources, professional development strategies, tool kits, and web-based clearinghouses offering scientifically accurate information about climate change to different learner audiences. NOAA has been able to firmly establish their Environmental Literacy Grant (ELG) program because of the America COMPETES Act. Related programs are being developed within the EPA and USDA’s NIFA and U.S. Forest Service. Several other agencies have revamped their strategic plans to increase focus on communicating with and educating teachers, students, policymakers, and the general public about climate change, adaptation, and mitigation issues. To foster larger networks of scientists and educators, minimize duplication, and encourage synergy and scale-up, NSF, NOAA, and NASA have initiated joint meetings of their CCE, GCCE, and ELG Principal Investigators and shared evaluations. Additional cross-agency linkages are being encouraged through NSF’s new Climate Change Education Partnership (CCEP) program, which launched 15 Phase I Partnerships focused around specific geographic regions or scientific themes unified by common climate change impacts. When fully implemented in Phase II, CCEP expects to increase the adoption of high quality educational resources and their impact on public climate literacy. Phase I strategic planning efforts will identify and engage relevant stakeholders, inventory existing climate change education resources for that theme or region, conduct a needs analysis, and develop a robust strategic plan for implementation in Phase II. The U.S. Global Change Research Program (USGCRP) is the primary organizational structure through which the 13 federal agencies that conduct climate-related research, education, and outreach are coordinating their efforts. The Climate Literacy framework is one example of the constructive collaboration that has been achieved through the USGCRP Education Interagency Working Group. Additional efforts are being planned through a new Interagency Climate Communication and Education Task Force.

Burden of climate change on malaria mortality.

PubMed

Dasgupta, Shouro

2018-06-01

In 2016, an estimated 445,000 deaths and 216 million cases of malaria occurred worldwide, while 70% of the deaths occurred in children under five years old. Changes in climatic exposures such as temperature and precipitation make malaria one of the most climate sensitive outcomes. Using a global malaria mortality dataset for 105 countries between 1980 and 2010, we find a non-linear relationship between temperature and malaria mortality and estimate that the global optimal temperature threshold beyond which all-age malaria mortality increases is 20.8 °C, while in the case of child mortality; a significantly lower optimum temperature of 19.3° is estimated. Our results also suggest that this optimal temperature is 28.4 °C and 26.3 °C in Africa and Asia, respectively - the continents where malaria is most prevalent. Furthermore, we estimate that child mortality (ages 0-4) is likely to increase by up to 20% in some areas due to climate change by the end of the 21st century. Copyright © 2018 Elsevier GmbH. All rights reserved.

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.

Slowing down of North Pacific climate variability and its implications for abrupt ecosystem change.

PubMed

Boulton, Chris A; Lenton, Timothy M

2015-09-15

Marine ecosystems are sensitive to stochastic environmental variability, with higher-amplitude, lower-frequency--i.e., "redder"--variability posing a greater threat of triggering large ecosystem changes. Here we show that fluctuations in the Pacific Decadal Oscillation (PDO) index have slowed down markedly over the observational record (1900-present), as indicated by a robust increase in autocorrelation. This "reddening" of the spectrum of climate variability is also found in regionally averaged North Pacific sea surface temperatures (SSTs), and can be at least partly explained by observed deepening of the ocean mixed layer. The progressive reddening of North Pacific climate variability has important implications for marine ecosystems. Ecosystem variables that respond linearly to climate forcing will have become prone to much larger variations over the observational record, whereas ecosystem variables that respond nonlinearly to climate forcing will have become prone to more frequent "regime shifts." Thus, slowing down of North Pacific climate variability can help explain the large magnitude and potentially the quick succession of well-known abrupt changes in North Pacific ecosystems in 1977 and 1989. When looking ahead, despite model limitations in simulating mixed layer depth (MLD) in the North Pacific, global warming is robustly expected to decrease MLD. This could potentially reverse the observed trend of slowing down of North Pacific climate variability and its effects on marine ecosystems.

Statistical approach to the analysis of olive long-term pollen season trends in southern Spain.

PubMed

García-Mozo, H; Yaezel, L; Oteros, J; Galán, C

2014-03-01

Analysis of long-term airborne pollen counts makes it possible not only to chart pollen-season trends but also to track changing patterns in flowering phenology. Changes in higher plant response over a long interval are considered among the most valuable bioindicators of climate change impact. Phenological-trend models can also provide information regarding crop production and pollen-allergen emission. The interest of this information makes essential the election of the statistical analysis for time series study. We analysed trends and variations in the olive flowering season over a 30-year period (1982-2011) in southern Europe (Córdoba, Spain), focussing on: annual Pollen Index (PI); Pollen Season Start (PSS), Peak Date (PD), Pollen Season End (PSE) and Pollen Season Duration (PSD). Apart from the traditional Linear Regression analysis, a Seasonal-Trend Decomposition procedure based on Loess (STL) and an ARIMA model were performed. Linear regression results indicated a trend toward delayed PSE and earlier PSS and PD, probably influenced by the rise in temperature. These changes are provoking longer flowering periods in the study area. The use of the STL technique provided a clearer picture of phenological behaviour. Data decomposition on pollination dynamics enabled the trend toward an alternate bearing cycle to be distinguished from the influence of other stochastic fluctuations. Results pointed to show a rising trend in pollen production. With a view toward forecasting future phenological trends, ARIMA models were constructed to predict PSD, PSS and PI until 2016. Projections displayed a better goodness of fit than those derived from linear regression. Findings suggest that olive reproductive cycle is changing considerably over the last 30years due to climate change. Further conclusions are that STL improves the effectiveness of traditional linear regression in trend analysis, and ARIMA models can provide reliable trend projections for future years taking into account the internal fluctuations in time series. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

An energy balance model exploration of the impacts of interactions between surface albedo, cloud cover and water vapor on polar amplification

NASA Astrophysics Data System (ADS)

Södergren, A. Helena; McDonald, Adrian J.; Bodeker, Gregory E.

2017-11-01

We examine the effects of non-linear interactions between surface albedo, water vapor and cloud cover (referred to as climate variables) on amplified warming of the polar regions, using a new energy balance model. Our simulations show that the sum of the contributions to surface temperature changes due to any variable considered in isolation is smaller than the temperature changes from coupled feedback simulations. This non-linearity is strongest when all three climate variables are allowed to interact. Surface albedo appears to be the strongest driver of this non-linear behavior, followed by water vapor and clouds. This is because increases in longwave radiation absorbed by the surface, related to increases in water vapor and clouds, and increases in surface absorbed shortwave radiation caused by a decrease in surface albedo, amplify each other. Furthermore, our results corroborate previous findings that while increases in cloud cover and water vapor, along with the greenhouse effect itself, warm the polar regions, water vapor also significantly warms equatorial regions, which reduces polar amplification. Changes in surface albedo drive large changes in absorption of incoming shortwave radiation, thereby enhancing surface warming. Unlike high latitudes, surface albedo change at low latitudes are more constrained. Interactions between surface albedo, water vapor and clouds drive larger increases in temperatures in the polar regions compared to low latitudes. This is in spite of the fact that, due to a forcing, cloud cover increases at high latitudes and decreases in low latitudes, and that water vapor significantly enhances warming at low latitudes.

Climate Change in Alpine Regions - Regional Characteristics of a Global Phenomenon by the Example of Air Temperature

NASA Astrophysics Data System (ADS)

Lang, Erich; Stary, Ulrike

2017-04-01

For nearly 50 years the Austrian Research Centre for Forests (BFW) has been engaged in research in the Alpine region recording measuring data at extreme sites. Data series of this duration provide already a good insight into the evolution of climate parameters. Extrapolations derived from it are suitable for comparison with results from climate change models or supplement them with regard to their informative value. This is useful because climate change models describe a simplified picture of reality based on the size of the data grid they use. Analysis of time series of two air temperature measuring stations in different torrent catchment areas indicate that 1) predictions of temperature rise for the Alpine region in Austria will have to be revised upwards, and 2) only looking at the data of seasons (or shorter time periods), reveals the real dramatic effect of climate change. Considering e.g. the annual average data of air temperature of the years 1969-2016 at the climate station "Fleissner" (altitude 1210m a.s.l; Upper Mölltal, Carinthia) a significant upward trend is visible. Using a linear smoothing function an increase of the average annual air temperature of about 2.2°C within 50 years emerges. The calculated temperature rise thus confirms the general fear of an increase of more than 2.0°C till the middle of the 21st century. Looking at the seasonal change of air temperature, significant positive trends are shown in all four seasons. But the level of the respective temperature increase varies considerably and indicates the highest increase in spring (+3.3°C), and the lowest one in autumn (+1.3°C, extrapolated for a time period of 50 years). The maximum increase of air temperature at the measuring station "Pumpenhaus" (altitude 980m a.s.l), which is situated in the "Karnische Alpen" in the south of Austria, is even stronger. From a time series of 28 years (with data recording starting in 1989) the maximum rise of temperature was 5.4°C detected for the summer (calculated over a period of 50 years). The predicted overall rise in the annual average temperature within 50 years is +3.9°C, whereas the rise of temperature at the station "Fleissner", located in the "Hohen Tauern", is +2.3°C; both based on determined linear smoothing functions and for the same measuring period (1989-2016). As the effects of the calculated changes of air temperature on the alpine habitat (the entire ecosystem, natural hazards and tourism) and the characteristics of climate change vary strongly from a geographical point of view (as shown by the two examples of air temperature data), a comprehensive analysis of data series from climatic measurement stations (including precipitation, snow covering, radiation…) in the Alpine region is urgently necessary, to be able to work on targeted climate adaptation strategies for these sensitive areas.

[Evolution of maize climate productivity and its response to climate change in Heilongjiang Province, China.

PubMed

Li, Xiu Fen; Zhao, Hui Ying; Zhu, Hai Xia; Wang, Ping; Wang, Qiu Jing; Wang, Ming; Li, Yu Guang

2016-08-01

Under the background of climate change, revealing the change trend and spatial diffe-rence of maize climate productivity in-depth and understanding the regularity of maize climatic resources utilization can provide scientific basis for the macro-decision of agricultural production in Heilongjiang Province. Based on the 1981-2014 meteorological data of 72 weather stations and the corresponding maize yield data in Heilongjiang Province, by the methods of step by step revisal, spatial interpolation and linear trend analysis, this paper studied the photosynthetic productivity (PP), light-temperature productivity (LTP), and climatic productivity (CP) of spring maize, and their temporal and spatial variation characteristics, main influencing factors and light energy utilization efficiency, and evaluated the maize climate productivities under different climate scenarios in the future. The results showed that during the study period, the mean PP, LTP and CP in Heilongjiang Province were 26558, 19953, 18742 kg·hm -2 , respectively. Maize PP, LTP and CP were high in plains and low in mountains, and gradually decreased from southwest to northeast. PP, LTP and CP presented significantly increasing trends, and the increase rates were 378, 723 and 560 kg·hm -2 ·(10 a) -1 , respectively. The increase of radiation and temperature had positive effect on maize production in Heilongjiang Province. The potential productivity of maize presented significant response to climate change. The decrease of solar radiation led to the decline of PP in western Songnen Plain, but the increased temperature compensated the negative effect of solar radiation, so the downward trend of LTP was slowed. The response to climate warming was particularly evident in North and East, and LTP was significantly increased, which was sensitive to the change of precipitation in southwest of Songnen Plain and part of Sanjiang Plain. The average ratio of maize actual yield to its climate productivity was only 24.1%, there was still 75.9% to be developed. In the future, the warm and wet climate would benefit the improvement of maize climate productivity, while the cold and dry climate would make an adverse impact.

Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming

NASA Astrophysics Data System (ADS)

Schewe, Jacob; Levermann, Anders

2017-07-01

Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic-thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.

Impacts of global change on the concentrations and dilution of combined sewer overflows in a drinking water source.

PubMed

Jalliffier-Verne, Isabelle; Leconte, Robert; Huaringa-Alvarez, Uriel; Madoux-Humery, Anne-Sophie; Galarneau, Martine; Servais, Pierre; Prévost, Michèle; Dorner, Sarah

2015-03-01

This study presents an analysis of climate change impacts on a large river located in Québec (Canada) used as a drinking water source. Combined sewer overflow (CSO) effluents are the primary source of fecal contamination of the river. An analysis of river flowrates was conducted using historical data and predicted flows from a future climate scenario. A spatio-temporal analysis of water quality trends with regard to fecal contamination was performed and the effects of changing flowrates on the dilution of fecal contaminants were analyzed. Along the river, there was a significant spatial trend for increasing fecal pollution downstream of CSO outfalls. Escherichia coli concentrations (upper 95th percentile) increased linearly from 2002 to 2012 at one drinking water treatment plant intake. Two critical periods in the current climate were identified for the drinking water intakes considering both potential contaminant loads and flowrates: local spring snowmelt that precedes river peak flow and extra-tropical storm events that occur during low flows. Regionally, climate change is expected to increase the intensity of the impacts of hydrological conditions on water quality in the studied basin. Based on climate projections, it is expected that spring snowmelt will occur earlier and extreme spring flowrates will increase and low flows will generally decrease. High and low flows are major factors related to the potential degradation of water quality of the river. However, the observed degradation of water quality over the past 10 years suggests that urban development and population growth may have played a greater role than climate. However, climate change impacts will likely be observed over a longer period. Source water protection plans should consider climate change impacts on the dilution of contaminants in addition to local land uses changes in order to maintain or improve water quality. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of long term climate change on net infiltration at Yucca Mountain, Nevada

USGS Publications Warehouse

Flint, Alan I.; Flint, Lorraine E.; Hevesi, Joseph A.

1993-01-01

Net infiltration and recharge at Yucca Mountain, Nevada, a potential site for a high level nuclear waste repository, are determined both by the rock properties and past and future changes in climate. A 1-dimensional model was constructed to represent a borehole being drilled through the unsaturated zone. The rock properties were matched to the lithologies expected to be encountered in the borehole. As current paleoclimate theory assumes that 18O increases with wetter and cooler global climates, a past climate scenario, built on depletion of 18O from ocean sediments was used as a basis for climate change over the past 700,000 years. The climate change was simulated by assigning net infiltration values as a linear function of 8O. Assuming the rock properties, lithologies and climate scenarios are correct, simulations indicated that Yucca Mountain is not in steady state equilibrium at the surface (250 meters. Based on the cyclic climate inputs, the near surface is currently in a long term drying trend (for the last 3,000 years) yet recharge into the water table is continuing to occur at an average rate equivalent to the average input rate of the climate model, indicating that conditions at depth are damped out over very long time periods. The Paintbrush Tuff nonwelded units, positioned between the Tiva Canyon and Topopah Spring welded Tuff Members, do not appear to act as capillary barrier and therefore would not perch water. The low porosity vitric caprock and basal vitrophyre of the Topopah Spring Member, however, act as restrictive layers. The higher porosity rock directly above the caprock reduces the potential for the caprock to perch water leaving the basal vitrophyre as the most likely location for perched water to develop.

Climate-driven longitudinal trends in pasture-borne helminth infections of dairy cattle.

PubMed

Charlier, Johannes; Ghebretinsae, Aklilu H; Levecke, Bruno; Ducheyne, Els; Claerebout, Edwin; Vercruysse, Jozef

2016-12-01

Helminth parasites of grazing ruminants are highly prevalent globally and impact negatively on animal productivity and food security. There is a growing concern that climate change increases helminth disease frequency and intensity. In Europe, these concerns stem from case reports and theoretical life cycle models assessing the effects of climate change scenarios on helminth epidemiology. We believe this study is the first to investigate climate-driven trends in helminth infections of cattle on a cohort of randomly selected farms. One thousand, six hundred and eighty dairy farms were monitored over an 8year period for the two major helminth infections in temperate climate regions and climate-driven trends were investigated by multivariable linear mixed models. The general levels of exposure to Fasciola hepatica decreased over the study period while those to Ostertagia ostertagi increased, and this could at least be partially explained by meteorological factors (i.e. the number of rainy (precipitation >1mm) and warm days (average daily temperature >10°C) in a year). The longitudinal trends varied according to the altitude and the agricultural region of the farm. This study shows that longitudinal epidemiological data from sentinel farms combined with meteorological datasets can significantly contribute to understanding the effects of climate on infectious disease dynamics. When local environmental conditions are taken into account, the effects of climate change on disease dynamics can also be understood at more local scales. We recommend setting up a longitudinal sampling strategy across Europe in order to monitor climate-driven changes in helminth disease risk to inform adaptation strategies to promote animal health and productivity. Copyright © 2016 Australian Society for Parasitology. Published by Elsevier Ltd. All rights reserved.

The Importance of Considering the Temporal Distribution of Climate Variables for Ecological-Economic Modeling to Calculate the Consequences of Climate Change for Agriculture

NASA Astrophysics Data System (ADS)

Plegnière, Sabrina; Casper, Markus; Hecker, Benjamin; Müller-Fürstenberger, Georg

2014-05-01

The basis of many models to calculate and assess climate change and its consequences are annual means of temperature and precipitation. This method leads to many uncertainties especially at the regional or local level: the results are not realistic or too coarse. Particularly in agriculture, single events and the distribution of precipitation and temperature during the growing season have enormous influences on plant growth. Therefore, the temporal distribution of climate variables should not be ignored. To reach this goal, a high-resolution ecological-economic model was developed which combines a complex plant growth model (STICS) and an economic model. In this context, input data of the plant growth model are daily climate values for a specific climate station calculated by the statistical climate model (WETTREG). The economic model is deduced from the results of the plant growth model STICS. The chosen plant is corn because corn is often cultivated and used in many different ways. First of all, a sensitivity analysis showed that the plant growth model STICS is suitable to calculate the influences of different cultivation methods and climate on plant growth or yield as well as on soil fertility, e.g. by nitrate leaching, in a realistic way. Additional simulations helped to assess a production function that is the key element of the economic model. Thereby the problems when using mean values of temperature and precipitation in order to compute a production function by linear regression are pointed out. Several examples show why a linear regression to assess a production function based on mean climate values or smoothed natural distribution leads to imperfect results and why it is not possible to deduce a unique climate factor in the production function. One solution for this problem is the additional consideration of stress indices that show the impairment of plants by water or nitrate shortage. Thus, the resulting model takes into account not only the ecological factors (e.g. the plant growth) or the economical factors as a simple monetary calculation, but also their mutual influences. Finally, the ecological-economic model enables us to make a risk assessment or evaluate adaptation strategies.

Assessing the present and future probability of Hurricane Harvey's rainfall.

PubMed

Emanuel, Kerry

2017-11-28

We estimate, for current and future climates, the annual probability of areally averaged hurricane rain of Hurricane Harvey's magnitude by downscaling large numbers of tropical cyclones from three climate reanalyses and six climate models. For the state of Texas, we estimate that the annual probability of 500 mm of area-integrated rainfall was about 1% in the period 1981-2000 and will increase to 18% over the period 2081-2100 under Intergovernmental Panel on Climate Change (IPCC) AR5 representative concentration pathway 8.5. If the frequency of such event is increasingly linearly between these two periods, then in 2017 the annual probability would be 6%, a sixfold increase since the late 20th century. Copyright © 2017 the Author(s). Published by PNAS.

Economic implications of climate-driven trends in global hydropower generation

NASA Astrophysics Data System (ADS)

Turner, S. W. D.; Galelli, S.; Hejazi, M. I.; Clarke, L.; Edmonds, J.; Kim, S. H.

2017-12-01

Recent progress in global scale hydrological and dam modeling has allowed for the study of climate change impacts on global hydropower production. Here we explore how these impacts could affect the composition of global electricity supply, and what those changes could mean for power sector emissions and investment needs in the 21st century. Regional hydropower projections are developed for two emissions scenarios by forcing a coupled global hydrological and dam model (1593 major hydropower dams; 54% global installed capacity) with downscaled, bias-corrected climate realizations derived from sixteen General Circulation Models (GCMs). To incorporate possible non-linearity in hydropower response to climate change, dam simulations incorporate plant specifications (e.g., maximum turbine flow), reservoir storage dynamics, reservoir bathymetry, evaporation losses and bespoke, site specific operations. Consequent impacts on regional and global-level electricity generation and associated emissions and investment costs are examined using the Global Change Assessment Model (GCAM). We show that changes in hydropower generation resulting from climate change can shift power demands onto and away from carbon intensive technologies, resulting in significant impacts on CO2 emissions for several regions. Many of these countries are also highly vulnerable to investment impacts (costs of new electricity generating facilities to make up for shortfalls in hydro), which in some cases amount to tens of billions of dollars by 2100. The Balkans region—typified by weak economies in a drying region that relies heavily on hydropower—emerges as the most vulnerable. Reduced impacts of climate change on hydropower production under a low emissions scenario coincide with increased costs of marginal power generating capacity (low emissions requires greater uptake of clean generating technologies, which are more expensive). This means impacts on power sector investment costs are similar for high and low emissions scenarios.

Identifying and Reconciling Risk Across Sectors: The implications of differing views of risk in climate policy, environmental conservation, and the finance sector

NASA Astrophysics Data System (ADS)

Johns, T.; Henderson, I.; Thoumi, G.

2014-12-01

The presence and valuation of risk are commonalities that link the diverse fields of climate change science and policy, environmental conservation, and the financial/investment sector. However, the definition and perception of risks vary widely across these critically linked fields. The "Stranded Asset" concept developed by organizations like the Carbon Tracker Initiative begins to elucidate the links between climate change risk and financial risk. Stranded assets are those that may lose some or all value from climate disruption, changes in demand-side dynamics and/or a more stringent regulatory environment. In order to shift financial flows toward climate change mitigation, emissions-heavy activities that present finance and investment opportunities must also be assessed for their GHG-asset risk attributes in terms of their contribution and vulnerability to climate disruption, as well as other environmental externalities. Until the concept of GHG-asset risk in investment is reconciled with the risks of climate change and environmental conservation, it will not be possible to shift business and financial practices, and unlock private sector resources to address the climate change and conservation challenge. UNEP-FI is researching the application of the concept of Value-atRisk (VaR) to explore links between the financial sector and deforestation/REDD+. The research will test the hypothesis that climate risk is a financial risk, and propose tools to identify and quantify risks associated with unsustainable land-use investments. The tools developed in this research will help investors, managers and governments assess their exposures to the material REDD-related risks in their portfolios. This will inform the development of 'zero net deforestation' investment indices to allow investors to lower the 'deforestation' exposure of 'benchmark' financial indices used by many of the largest money managers. A VaR analysis will be performed, combining the notion of externality with the traditional approach of external (exogenous) risk analysis. The VaR component introduces probabilities for different scenarios and may ultimately lead to a full distribution for the holistic losses. These distributions are non-parametric and non-linear since climate change is an "event-risk".

Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5

NASA Astrophysics Data System (ADS)

Dufresne, J.-L.; Foujols, M.-A.; Denvil, S.; Caubel, A.; Marti, O.; Aumont, O.; Balkanski, Y.; Bekki, S.; Bellenger, H.; Benshila, R.; Bony, S.; Bopp, L.; Braconnot, P.; Brockmann, P.; Cadule, P.; Cheruy, F.; Codron, F.; Cozic, A.; Cugnet, D.; de Noblet, N.; Duvel, J.-P.; Ethé, C.; Fairhead, L.; Fichefet, T.; Flavoni, S.; Friedlingstein, P.; Grandpeix, J.-Y.; Guez, L.; Guilyardi, E.; Hauglustaine, D.; Hourdin, F.; Idelkadi, A.; Ghattas, J.; Joussaume, S.; Kageyama, M.; Krinner, G.; Labetoulle, S.; Lahellec, A.; Lefebvre, M.-P.; Lefevre, F.; Levy, C.; Li, Z. X.; Lloyd, J.; Lott, F.; Madec, G.; Mancip, M.; Marchand, M.; Masson, S.; Meurdesoif, Y.; Mignot, J.; Musat, I.; Parouty, S.; Polcher, J.; Rio, C.; Schulz, M.; Swingedouw, D.; Szopa, S.; Talandier, C.; Terray, P.; Viovy, N.; Vuichard, N.

2013-05-01

We present the global general circulation model IPSL-CM5 developed to study the long-term response of the climate system to natural and anthropogenic forcings as part of the 5th Phase of the Coupled Model Intercomparison Project (CMIP5). This model includes an interactive carbon cycle, a representation of tropospheric and stratospheric chemistry, and a comprehensive representation of aerosols. As it represents the principal dynamical, physical, and bio-geochemical processes relevant to the climate system, it may be referred to as an Earth System Model. However, the IPSL-CM5 model may be used in a multitude of configurations associated with different boundary conditions and with a range of complexities in terms of processes and interactions. This paper presents an overview of the different model components and explains how they were coupled and used to simulate historical climate changes over the past 150 years and different scenarios of future climate change. A single version of the IPSL-CM5 model (IPSL-CM5A-LR) was used to provide climate projections associated with different socio-economic scenarios, including the different Representative Concentration Pathways considered by CMIP5 and several scenarios from the Special Report on Emission Scenarios considered by CMIP3. Results suggest that the magnitude of global warming projections primarily depends on the socio-economic scenario considered, that there is potential for an aggressive mitigation policy to limit global warming to about two degrees, and that the behavior of some components of the climate system such as the Arctic sea ice and the Atlantic Meridional Overturning Circulation may change drastically by the end of the twenty-first century in the case of a no climate policy scenario. Although the magnitude of regional temperature and precipitation changes depends fairly linearly on the magnitude of the projected global warming (and thus on the scenario considered), the geographical pattern of these changes is strikingly similar for the different scenarios. The representation of atmospheric physical processes in the model is shown to strongly influence the simulated climate variability and both the magnitude and pattern of the projected climate changes.

Changing Climate Drives Lagging and Accelerating Glacier Responses and Accelerating Adjustments of the Hazard Regime

NASA Astrophysics Data System (ADS)

Kargel, Jeffrey

2013-04-01

It is virtually universally recognized among climate and cryospheric scientists that climate and greenhouse gas abundances are closely correlated. Disagreements mainly pertain to the fundamental triggers for large fluctuations in climate and greenhouse gases during the pre-industrial era, and exactly how coupling is achieved amongst the dynamic solid Earth, the Sun, orbital and rotational dynamics, greenhouse gas abundances, and climate. Also unsettled is the climate sensitivity defined as the absolute linkage between the magnitude of climate warming/cooling and greenhouse gas increase/decrease. Important questions concern lagging responses (either greenhouse gases lagging climate fluctuations, or vice versa) and the causes of the lags. In terms of glacier and ice sheet responses to climate change, there also exist several processes causing lagging responses to climate change inputs. The simplest parameterization giving a glacier's lagging response time, τ, is that given by Jóhanneson et al. (1989), modified slightly here as τ = b/h, where b is a measure of ablation rate and h is a measure of glacier thickness. The exact definitions of τ, b, and h are subject to some interpretive license, but for a back-of-the-envelope approximation, we may take b as the magnitude of the mean ablation rate over the whole ablation area, and h as the mean glacier thickness in the glacier ablation zone. τ remains a bit ambiguous but may be considered as an exponential time scale for a decreasing response of b to a climatic step change. For some climate changes, b and h can be taken as the values prior to the climate change, but for large climatic shifts, this parameterization must be iterated. The actual response of a glacier at any time is the sum of exponentially decreasing responses from past changes. (Several aspects of glacier dynamics cause various glacier responses to differ from this idealized glacier-response theory.) Some important details relating to the retreat (or advances) of glaciers due to historic and future anthropogenic and longer term climate change relate to a changing glacier hazard regime. Climate change is connected to changes in the geographic distribution and magnitudes of potentially hazardous glacier lakes, large rock and ice avalanches, ice-dammed rivers, and surges. I shall consider these changes in hazard environment in relation to response-time theory and dynamical divergences from idealized response-time theory. Case histories of certain hazard-prone regions, including developments in fast-response-type glaciers and slow-response glaciers and ice sheets will also be discussed. In short, there will be a strong tendency of the hazard regimes of glacierized regions to shift far more rapidly in the 21st century than they did in the 20th century. The magnitude of the shifts will be more dramatic than any simple linear scaling to climate warming would suggest; this is largely because, due to lagging responses, glaciers are still trying to catch up to a new equilibrium for 20th century climate, while climate change remains a moving target that will drive accelerating glacier responses (including responses in hazard environments) in most glacierized regions.

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

USGS Publications Warehouse

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

2009-01-01

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

Modeling daily soil temperature over diverse climate conditions in Iran—a comparison of multiple linear regression and support vector regression techniques

NASA Astrophysics Data System (ADS)

Delbari, Masoomeh; Sharifazari, Salman; Mohammadi, Ehsan

2018-02-01

The knowledge of soil temperature at different depths is important for agricultural industry and for understanding climate change. The aim of this study is to evaluate the performance of a support vector regression (SVR)-based model in estimating daily soil temperature at 10, 30 and 100 cm depth at different climate conditions over Iran. The obtained results were compared to those obtained from a more classical multiple linear regression (MLR) model. The correlation sensitivity for the input combinations and periodicity effect were also investigated. Climatic data used as inputs to the models were minimum and maximum air temperature, solar radiation, relative humidity, dew point, and the atmospheric pressure (reduced to see level), collected from five synoptic stations Kerman, Ahvaz, Tabriz, Saghez, and Rasht located respectively in the hyper-arid, arid, semi-arid, Mediterranean, and hyper-humid climate conditions. According to the results, the performance of both MLR and SVR models was quite well at surface layer, i.e., 10-cm depth. However, SVR performed better than MLR in estimating soil temperature at deeper layers especially 100 cm depth. Moreover, both models performed better in humid climate condition than arid and hyper-arid areas. Further, adding a periodicity component into the modeling process considerably improved the models' performance especially in the case of SVR.

Detecting climate forcing and feedback signals in surface climate change

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

The Earth has warmed in the last century and a large component of that warming has been attributed to the build-up of anthropogenic greenhouse gases. There are also numerous feedback processes which can introduce strong, regionalized asymmetries to the overall warming trend. These processes alter the surface energy budget, and thus affect the surface air temperature, which is one of the primary measures of how the climate is changing. However, the degree to which a given forcing or feedback process alters surface temperatures is contingent on the effective heat capacity of the atmosphere which is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, which can lead to a strongly amplified temperature response in shallow boundary layers. Therefore, if a climate forcing or feedback is acting across a wide range of conditions of the boundary layer, then this non-linear response of the surface climate to perturbations in the forcing must be accounted for in order to correctly assess the effect of the forcing on the surface climatology.

Effects of urbanization on climate of İstanbul and Ankara

NASA Astrophysics Data System (ADS)

Karaca, Mehmet; Tayanç, Mete; Toros, Hüseyi˙n.

The purpose of this work is to study regional climate change and investigate the effects of urbanization on climates of two largest cities in Turkey: İstanbul and Ankara. Air temperature (mean, maximum and minimum) data of İstanbul and Ankara are analyzed to study regional climate change and to understand the possible effects of urbanization on the climate of these regions owing to industrialization and large flux of migration from rural parts of the country. For the trend analysis, linear regression and the sequential version of the Mann-Kendall test is used. A significant upward trend is found in the urban temperatures of southern İstanbul, which is the most highly populated and industrialized part of the city compared to its rural parts. Northern stations do not show any warming trend; instead, they have a cooling trend. Urbanization and industrialization in the southern part of İstanbul has a negative effect on regional cooling. In spite of Ankara's urban geometry and air pollution problem, the urban station in Ankara does not show any warming trend. A significant urban heat island intensity ( urban-rural) is not observed in Ankara.

Natural recovery of biological soil crusts after disturbance

USGS Publications Warehouse

Weber, Bettina; Bowker, Matthew A.; Zhang, Yuanming; Belnap, Jayne

2016-01-01

Natural recovery of biological soil crusts (biocrusts) is influenced by a number of different parameters, such as climate, soil conditions, the severity of disturbance, and the timing of disturbance relative to the climatic conditions. In recent studies, it has been shown that recovery is often not linear, but a highly dynamic process directly influenced by non-linear external parameters as extraordinary climatic conditions (e.g., particularly dry or wet year). Natural recovery often follows a general succession pattern, starting out with cyanobacteria and algae, which is then followed by lichens and bryophytes at a later stage. However, this general sequence can be altered by parameters like dust deposition, fire effects, and special climatic conditions as in fog deserts and under mesic climates. Recent studies have proposed that under favorable, stable soil conditions, the initial soil-stabilizing cyanobacteria-dominated succession stages may be omitted and moss-dominated biocrusts can develop in the initial phases of biocrust development. During natural recovery of biocrusts, soil properties change, e.g., soil nutrient and organic matter contents increase. Also, silt and clay contents of encrusted soils increase with biocrust maturity, which may be caused by two mechanisms, i.e. entrapment of fine soil particles by biocrusts and the new formation of smaller particles by weathering of the existing substrate.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

A Possible Strategy for the Use of Solar Climate Engineering

NASA Astrophysics Data System (ADS)

Ackerman, T. P.; Russotto, R. D.; Kravitz, B.

2016-12-01

The Paris accord signals an international effort to hold global temperature change below 2°C above pre-industrial levels, raising the question of what role solar climate engineering (SCE) might play in meeting this objective. However, avoiding continuing, long-term application of SCE with an ever increasing magnitude requires an "exit strategy", i. e., a plan to phase out SCE by removing stabilizing and removing CO2. Here we present results from a series of climate model runs that combine both CO2 and SCE transient forcings over a 200-year period (2000 to 2200). Our results confirm past results that maintaining both global surface air temperature (TA) and precipitation (P) at baseline levels is not feasible. They also demonstrate a quasi-linear relationship between changes in SCE and changes in P. Zonally-averaged changes in TA show, as expected, polar amplification of warming, but that enhancement scales uniformly with the change in global TA. We draw several conclusions from our results: (1) There are plausible scenarios in which SCE can be part of an integrated strategy to meet the temperature goals of the Paris accord. (2) Applying transient forcings can be used to maintain some, but not all, globally-averaged climate system variables (such as TA or P) at a prescribed baseline level. That globally-averaged stability, however, is achieved by averaging over changes in spatial distributions. These spatial changes create difficult issues regarding prediction of regional climate changes due to SCE and potential impacts on regional societies. (3) Our inability to predict interannual climate variability on the annual-to-decadal time scale suggests that it may take a decade or more to provide reliable detection and attribution of the global climate impacts of SCE following its inception (the so-called time of emergence). Furthermore, it will take much longer to determine regional impacts.

Species Richness Patterns and Water-Energy Dynamics in the Drylands of Northwest China

PubMed Central

Zerbe, Stefan; Abdusalih, Nurbay; Tang, Zhiyao; Ma, Ming; Yin, Linke; Mohammat, Anwar; Han, Wenxuan; Fang, Jingyun

2013-01-01

Dryland ecosystems are highly vulnerable to climatic and land-use changes, while the mechanisms underlying patterns of dryland species richness are still elusive. With distributions of 3637 native vascular plants, 154 mammals, and 425 birds in Xinjiang, China, we tested the water-energy dynamics hypothesis for species richness patterns in Central Asian drylands. Our results supported the water-energy dynamics hypothesis. We found that species richness of all three groups was a hump-shaped function of energy availability, but a linear function of water availability. We further found that water availability had stronger effects on plant richness, but weaker effects on vertebrate richness than energy availability. We conducted piecewise linear regressions to detect the breakpoints in the relationship between species richness and potential evapotranspiration which divided Xinjiang into low and high energy regions. The concordance between mammal and plant richness was stronger in high than in low energy regions, which was opposite to that between birds and plants. Plant richness had stronger effects than climate on mammal richness regardless of energy levels, but on bird richness only in high energy regions. The changes in the concordance between vertebrate and plant richness along the climatic gradient suggest that cautions are needed when using concordance between taxa in conservation planning. PMID:23840472

Air - water temperature relationships in the trout streams of southeastern Minnesota’s carbonate - sandstone landscape

USGS Publications Warehouse

Krider, Lori A.; Magner, Joseph A.; Perry, Jim; Vondracek, Bruce C.; Ferrington, Leonard C.

2013-01-01

Carbonate-sandstone geology in southeastern Minnesota creates a heterogeneous landscape of springs, seeps, and sinkholes that supply groundwater into streams. Air temperatures are effective predictors of water temperature in surface-water dominated streams. However, no published work investigates the relationship between air and water temperatures in groundwater-fed streams (GWFS) across watersheds. We used simple linear regressions to examine weekly air-water temperature relationships for 40 GWFS in southeastern Minnesota. A 40-stream, composite linear regression model has a slope of 0.38, an intercept of 6.63, and R2 of 0.83. The regression models for GWFS have lower slopes and higher intercepts in comparison to surface-water dominated streams. Regression models for streams with high R2 values offer promise for use as predictive tools for future climate conditions. Climate change is expected to alter the thermal regime of groundwater-fed systems, but will do so at a slower rate than surface-water dominated systems. A regression model of intercept vs. slope can be used to identify streams for which water temperatures are more meteorologically than groundwater controlled, and thus more vulnerable to climate change. Such relationships can be used to guide restoration vs. management strategies to protect trout streams.

Species richness patterns and water-energy dynamics in the drylands of Northwest China.

PubMed

Li, Liping; Wang, Zhiheng; Zerbe, Stefan; Abdusalih, Nurbay; Tang, Zhiyao; Ma, Ming; Yin, Linke; Mohammat, Anwar; Han, Wenxuan; Fang, Jingyun

2013-01-01

Dryland ecosystems are highly vulnerable to climatic and land-use changes, while the mechanisms underlying patterns of dryland species richness are still elusive. With distributions of 3637 native vascular plants, 154 mammals, and 425 birds in Xinjiang, China, we tested the water-energy dynamics hypothesis for species richness patterns in Central Asian drylands. Our results supported the water-energy dynamics hypothesis. We found that species richness of all three groups was a hump-shaped function of energy availability, but a linear function of water availability. We further found that water availability had stronger effects on plant richness, but weaker effects on vertebrate richness than energy availability. We conducted piecewise linear regressions to detect the breakpoints in the relationship between species richness and potential evapotranspiration which divided Xinjiang into low and high energy regions. The concordance between mammal and plant richness was stronger in high than in low energy regions, which was opposite to that between birds and plants. Plant richness had stronger effects than climate on mammal richness regardless of energy levels, but on bird richness only in high energy regions. The changes in the concordance between vertebrate and plant richness along the climatic gradient suggest that cautions are needed when using concordance between taxa in conservation planning.

Energy Switching Threshold for Climatic Benefits

NASA Astrophysics Data System (ADS)

Zhang, X.; Cao, L.; Caldeira, K.

2013-12-01

Climate change is one of the great challenges facing humanity currently and in the future. Its most severe impacts may still be avoided if efforts are made to transform current energy systems (1). A transition from the global system of high Greenhouse Gas (GHG) emission electricity generation to low GHG emission energy technologies is required to mitigate climate change (2). Natural gas is increasingly seen as a choice for transitions to renewable sources. However, recent researches in energy and climate puzzled about the climate implications of relying more energy on natural gas. On one hand, a shift to natural gas is promoted as climate mitigation because it has lower carbon per unit energy than coal (3). On the other hand, the effect of switching to natural gas on nuclear-power and other renewable energies development may offset benefits from fuel-switching (4). Cheap natural gas is causing both coal plants and nuclear plants to close in the US. The objective of this study is to measure and evaluate the threshold of energy switching for climatic benefits. We hypothesized that the threshold ratio of energy switching for climatic benefits is related to GHGs emission factors of energy technologies, but the relation is not linear. A model was developed to study the fuel switching threshold for greenhouse gas emission reduction, and transition from coal and nuclear electricity generation to natural gas electricity generation was analyzed as a case study. The results showed that: (i) the threshold ratio of multi-energy switching for climatic benefits changes with GHGs emission factors of energy technologies. (ii)The mathematical relation between the threshold ratio of energy switching and GHGs emission factors of energies is a curved surface function. (iii) The analysis of energy switching threshold for climatic benefits can be used for energy and climate policy decision support.

Sensitivity of Statistical Downscaling Techniques to Reanalysis Choice and Implications for Regional Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Manzanas, R., Sr.; Brands, S.; San Martin, D., Sr.; Gutiérrez, J. M., Sr.

2014-12-01

This work shows that local-scale climate projections obtained by means of statistical downscaling are sensitive to the choice of reanalysis used for calibration. To this aim, a Generalized Linear Model (GLM) approach is applied to downscale daily precipitation in the Philippines. First, the GLMs are trained and tested -under a cross-validation scheme- separately for two distinct reanalyses (ERA-Interim and JRA-25) for the period 1981-2000. When the observed and downscaled time-series are compared, the attained performance is found to be sensitive to the reanalysis considered if climate change signal bearing variables (temperature and/or specific humidity) are included in the predictor field. Moreover, performance differences are shown to be in correspondence with the disagreement found between the raw predictors from the two reanalyses. Second, the regression coefficients calibrated either with ERA-Interim or JRA-25 are subsequently applied to the output of a Global Climate Model (MPI-ECHAM5) in order to assess the sensitivity of local-scale climate change projections (up to 2100) to reanalysis choice. In this case, the differences detected in present climate conditions are considerably amplified, leading to "delta-change" estimates differing by up to a 35% (on average for the entire country) depending on the reanalysis used for calibration. Therefore, reanalysis choice is shown to importantly contribute to the uncertainty of local-scale climate change projections, and, consequently, should be treated with equal care as other, well-known, sources of uncertainty -e.g., the choice of the GCM and/or downscaling method.- Implications of the results for the entire tropics, as well as for the Model Output Statistics downscaling approach are also briefly discussed.

Long-term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover.

PubMed

Liang, Yuting; Jiang, Yuji; Wang, Feng; Wen, Chongqing; Deng, Ye; Xue, Kai; Qin, Yujia; Yang, Yunfeng; Wu, Liyou; Zhou, Jizhong; Sun, Bo

2015-12-01

To understand soil microbial community stability and temporal turnover in response to climate change, a long-term soil transplant experiment was conducted in three agricultural experiment stations over large transects from a warm temperate zone (Fengqiu station in central China) to a subtropical zone (Yingtan station in southern China) and a cold temperate zone (Hailun station in northern China). Annual soil samples were collected from these three stations from 2005 to 2011, and microbial communities were analyzed by sequencing microbial 16S ribosomal RNA gene amplicons using Illumina MiSeq technology. Our results revealed a distinctly differential pattern of microbial communities in both northward and southward transplantations, along with an increase in microbial richness with climate cooling and a corresponding decrease with climate warming. The microbial succession rate was estimated by the slope (w value) of linear regression of a log-transformed microbial community similarity with time (time-decay relationship). Compared with the low turnover rate of microbial communities in situ (w=0.046, P<0.001), the succession rate at the community level was significantly higher in the northward transplant (w=0.058, P<0.001) and highest in the southward transplant (w=0.094, P<0.001). Climate warming lead to a faster succession rate of microbial communities as well as lower species richness and compositional changes compared with in situ and climate cooling, which may be related to the high metabolic rates and intense competition under higher temperature. This study provides new insights into the impacts of climate change on the fundamental temporal scaling of soil microbial communities and microbial phylogenetic biodiversity.

A process-based investigation into the impact of the Congo basin deforestation on surface climate

NASA Astrophysics Data System (ADS)

Bell, Jean P.; Tompkins, Adrian M.; Bouka-Biona, Clobite; Sanda, I. Seidou

2015-06-01

The sensitivity of climate to the loss of the Congo basin rainforest through changes in land cover properties is examined using a regional climate model. The complete removal of the Congo basin rainforest results in a dipole rainfall anomaly pattern, characterized by a decrease (˜-42%) in rainfall over the western Congo and an increase (˜10%) in the basin's eastern part. Three further experiments systematically examine the individual response to the changes in albedo, surface roughness, and evapotranspiration efficiency that accompany deforestation. The increased albedo (˜) caused by the Congo basin rainforest clearance results in cooler and drier climate conditions over the entire basin. The drying is accompanied with a reduction in available surface energy. Reducing evapotranspiration efficiency or roughness length produces similar positive air temperature anomaly patterns. The decreased evapotranspiration efficiency leads to a dipole response in rainfall, similar to that resulting from a reduced surface roughness following Congo basin rainforest clearance. This precipitation anomaly pattern is strongly linked to the change in low-level water vapor transport, the influence of the Rift valley highlands, and the spatial pattern of water recycling activity. The climate responds linearly to the separate albedo, surface roughness, and evapotranspiration efficiency changes, which can be summed to produce a close approximation to the impact of the full deforestation experiment. It is suggested that the widely contrasting climate responses to deforestation in the literature could be partly due to the relative magnitude of change of the radiative and nonradiative parameterizations in their respective land surface schemes.

Climate change or climate cycles? Snowpack trends in the Olympic and Cascade Mountains, Washington, USA.

PubMed

Barry, Dwight; McDonald, Shea

2013-01-01

Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region's precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models' relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses' time series. Posterior model probabilities of the 29 "most plausible" models ranged from 0.33 to 0.91 (mean = 0.58, s = 0.15). The majority of these time series (55%) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35% between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.

Thermokarst transformation of permafrost preserved glaciated landscapes.

NASA Astrophysics Data System (ADS)

Kokelj, S.; Tunnicliffe, J. F.; Fraser, R.; Kokoszka, J.; Lacelle, D.; Lantz, T. C.; Lamoureux, S. F.; Rudy, A.; Shakil, S.; Tank, S. E.; van der Sluijs, J.; Wolfe, S.; Zolkos, S.

2017-12-01

Thermokarst is the fundamental mechanism of landscape change and a primary driver of downstream effects in a warming circumpolar world. Permafrost degradation is inherently non-linear because latent heat effects can inhibit thawing. However, once this thermal transition is crossed thermokarst can accelerate due to the interaction of thermal, physical and ecological feedbacks. In this paper we highlight recent climate and precipitation-driven intensification of thaw slumping that is transforming permafrost preserved glaciated landscapes in northwestern Canada. The continental distribution of slump affected terrain reflects glacial extents and recessional positions of the Laurentide Ice sheet. On this basis and in conjunction with intense thermokarst in cold polar environments, we highlight the critical roles of geological legacy and climate history in dictating the sensitivity of permafrost terrain. These glaciated landscapes, maintained in a quasi-stable state throughout much of the late Holocene are now being transformed into remarkably dynamic environments by climate-driven thermokarst. Individual disturbances displace millions of cubic metres of previously frozen material downslope, converting upland sedimentary stores into major source areas. Precipitation-driven evacuation of sediment by fluidized mass flows perpetuates non-linear enlargement of disturbances. The infilling of valleys with debris deposits tens of metres thick increases stream base-levels and promotes rapid valley-side erosion. These processes destabilize adjacent slopes and proliferate disturbance effects. Physically-based modeling of thaw slump development provides insight into the trajectories of landscape change, and the mapping of fluvial linkages portrays the cascade of effects across watershed scales. Post-glacial or "paraglacial" models of landscape evolution provide a useful framework for understanding the nature and magnitude of climate-driven changes in permafrost preserved glaciated landscapes.

New insights into thermal growing conditions of Portuguese grapevine varieties under changing climates

NASA Astrophysics Data System (ADS)

Santos, João A.; Costa, Ricardo; Fraga, Helder

2018-03-01

New decision support tools for Portuguese viticulture are urging under a climate change context. In the present study, heat and chilling accumulation conditions of a collection of 44 grapevine cultivars currently grown in Portugal are assessed at very high spatial resolution ( 1 km) and for 1981-2015. Two bioclimatic indices that incorporate non-linear plant-temperature relationships are selected for this purpose: growing degree hours—GDH (February-October) and chilling portions—CP (October-February). The current thermal growing conditions of each variety are examined and three clusters of grapevine cultivars are identified based on their GDH medians, thus assembling varieties with close heat accumulation requirements and providing more physiologically consistent information when compared to previous studies, as non-linear plant-temperature relationships are herein taken into account. These new clusters are also a complement to previous bioclimatic zoning. Ensemble mean projections under two anthropogenic-driven scenarios (RCP4.5 and RCP8.5, 2041-2070), from four EURO-CORDEX simulations, reveal a widespread increase of GDH and decrease of CP, but with spatial heterogeneities. The spatial variability of these indices throughout Portugal is projected to decrease (strongest increases of GDH in the coolest regions of the northeast) and to increase (strongest decreases of CP in the warmest regions of the south and west), respectively. The typical heat accumulation conditions of each cluster are projected to gradually shift north-eastwards and to higher-elevation areas, whereas insufficient chilling may represent a new challenge in warmer future climates. An unprecedented level of detail for a large collection of grapevine varieties in Portugal is provided, thus promoting a better planning of climate change adaptation measures.

Assessing and managing stressors in a changing marine environment.

PubMed

Chapman, Peter M

2017-11-30

We are facing a dynamic future in the face of multiple stressors acting individually and in combination: climate change; habitat change/loss; overfishing; invasive species; harmful algal blooms/eutrophication; and, chemical contaminants. Historic assessment and management approaches will be inadequate for addressing risks from climate change and other stressors. Wicked problems (non-linear, complex, competing risks and benefits, not easily solvable), will become increasingly common. We are facing irreversible changes to our planetary living conditions. Agreed protection goals and considering both the negatives (risks) and the positives (benefits) of all any and all actions are required, as is judicious and appropriate use of the Precautionary Principle. Researchers and managers need to focus on: determining tipping points (alternative stable points); maintaining ecosystem services; and, managing competing ecosystem services. Marine (and other) scientists are urged to focus their research on wicked problems to allow for informed decision-making on a planetary basis. Copyright © 2016 Elsevier Ltd. All rights reserved.

Modeling soil organic carbon dynamics and their driving factors in the main global cereal cropping systems

NASA Astrophysics Data System (ADS)

Wang, Guocheng; Zhang, Wen; Sun, Wenjuan; Li, Tingting; Han, Pengfei

2017-10-01

Changes in the soil organic carbon (SOC) stock are determined by the balance between the carbon input from organic materials and the output from the decomposition of soil C. The fate of SOC in cropland soils plays a significant role in both sustainable agricultural production and climate change mitigation. The spatiotemporal changes of soil organic carbon in croplands in response to different carbon (C) input management and environmental conditions across the main global cereal systems were studied using a modeling approach. We also identified the key variables that drive SOC changes at a high spatial resolution (0.1° × 0.1°) and over a long timescale (54 years from 1961 to 2014). A widely used soil C turnover model (RothC) and state-of-the-art databases of soil and climate variables were used in the present study. The model simulations suggested that, on a global average, the cropland SOC density increased at annual rates of 0.22, 0.45 and 0.69 Mg C ha-1 yr-1 under crop residue retention rates of 30, 60 and 90 %, respectively. Increasing the quantity of C input could enhance soil C sequestration or reduce the rate of soil C loss, depending largely on the local soil and climate conditions. Spatially, under a specific crop residue retention rate, relatively higher soil C sinks were found across the central parts of the USA, western Europe, and the northern regions of China. Relatively smaller soil C sinks occurred in the high-latitude regions of both the Northern and Southern hemispheres, and SOC decreased across the equatorial zones of Asia, Africa and America. We found that SOC change was significantly influenced by the crop residue retention rate (linearly positive) and the edaphic variable of initial SOC content (linearly negative). Temperature had weak negative effects, and precipitation had significantly negative impacts on SOC changes. The results can help guide carbon input management practices to effectively mitigate climate change through soil C sequestration in croplands on a global scale.

Land cover and land use changes in the oil and gas regions of Northwestern Siberia under changing climatic conditions

NASA Astrophysics Data System (ADS)

Yu, Qin; Epstein, Howard E.; Engstrom, Ryan; Shiklomanov, Nikolay; Strelestskiy, Dmitry

2015-12-01

Northwestern Siberia has been undergoing a range of land cover and land use changes associated with climate change, animal husbandry and development of mineral resources, particularly oil and gas. The changes caused by climate and oil/gas development Southeast of the city of Nadym were investigated using multi-temporal and multi-spatial remotely sensed images. Comparison between high spatial resolution imagery acquired in 1968 and 2006 indicates that 8.9% of the study area experienced an increase in vegetation cover (e.g. establishment of new saplings, extent of vegetated cover) in response to climate warming while 10.8% of the area showed a decrease in vegetation cover due to oil and gas development and logging activities. Waterlogging along linear structures and vehicle tracks was found near the oil and gas development site, while in natural landscapes the drying of thermokarst lakes is evident due to warming caused permafrost degradation. A Landsat time series dataset was used to document the spatial and temporal dynamics of these ecosystems in response to climate change and disturbances. The impacts of land use on surface vegetation, radiative, and hydrological properties were evaluated using Landsat image-derived biophysical indices. The spatial and temporal analyses suggest that the direct impacts associated with infrastructure development were mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance and can have significant implications for changes in permafrost dynamics and surface energy budgets at landscape and regional scales.

Scaling Forest Management Practices in Earth System Models: Case Study of Southeast and Pacific Northwest Forests

NASA Astrophysics Data System (ADS)

Pourmokhtarian, A.; Becknell, J. M.; Hall, J.; Desai, A. R.; Boring, L. R.; Duffy, P.; Staudhammer, C. L.; Starr, G.; Dietze, M.

2014-12-01

A wide array of human-induced disturbances can alter the structure and function of forests, including climate change, disturbance and management. While there have been numerous studies on climate change impacts on forests, interactions of management with changing climate and natural disturbance are poorly studied. Forecasts of the range of plausible responses of forests to climate change and management are need for informed decision making on new management approaches under changing climate, as well as adaptation strategies for coming decades. Terrestrial biosphere models (TBMs) provide an excellent opportunity to investigate and assess simultaneous responses of terrestrial ecosystems to climatic perturbations and management across multiple spatio-temporal scales, but currently do not represent a wide array of management activities known to impact carbon, water, surface energy fluxes, and biodiversity. The Ecosystem Demography model 2 (ED2) incorporates non-linear impacts of fine-scale (~10-1 km) heterogeneity in ecosystem structure both horizontally and vertically at a plant level. Therefore it is an ideal candidate to incorporate different forest management practices and test various hypotheses under changing climate and across various spatial scales. The management practices that we implemented were: clear-cut, conversion, planting, partial harvest, low intensity fire, restoration, salvage, and herbicide. The results were validated against observed data across 8 different sites in the U.S. Southeast (Duke Forest, Joseph Jones Ecological Research Center, North Carolina Loblolly Pine, and Ordway-Swisher Biological Station) and Pacific Northwest (Metolius Research Natural Area, H.J. Andrews Experimental Forest, Wind River Field Station, and Mount Rainier National Park). These sites differ in regards to climate, vegetation, soil, and historical land disturbance as well as management approaches. Results showed that different management practices could successfully and realistically be implemented in the ED2 model at a site level. Moreover, sensitivity analyses determined the most important processes at different spatial scales, and also those which could be ignored while minimizing overall error.

Crop-climate relationships of cereals in Greece and the impacts of recent climate trends

NASA Astrophysics Data System (ADS)

Mavromatis, Theodoros

2015-05-01

Notwithstanding technological developments, agricultural production is still affected by uncontrollable factors, such weather and climate. Within this context, the present study aims at exploring the relative influence of growing season climate on the yields of major cereals (hard and soft wheat, maize, and barley) on a regional scale in Greece. To this end, crop-climate relationships and the impacts of climate trends over the period 1978-2005 were explored using linear regression and change point analysis (CPA). Climate data used include maximum (Tx) and minimum temperature (Tn), diurnal temperature range (Tr), precipitation (Prec), and solar radiation (Rad). Temperature effects were the most substantial. Yields reduced by 1.8-7.1 %/°C with increasing Tx and by 1.4-6.1 %/°C with decreasing Tr. The warming trends of Tn caused bilateral yield effects (from -3.7 to 8.4 %/°C). The fewer significantly increasing Rad and decreasing Prec anomalies were associated with larger yield decreases (within the range of 2.2 % MJ/m2/day (for maize) to 4.9 % MJ/m2/day (for hard wheat)) and smaller yield increases (from 0.04 to 1.4 %/mm per decade), respectively. Wheat and barley—the most vulnerable cereals—were most affected by the trends of extreme temperatures and least by Tr. On the contrary, solar radiation has proven to be the least affecting climate variable on all cereals. Despite the similarity in the direction of crop responses with both analyses, yield changes were much more substantial in the case of CPA analysis. In conclusion, regional climate change has affected Greek cereal productivity, in a few, but important for cereal production, regions. The results of this study are expected to be valuable in anticipating the effects of weather/climate on other warm regions worldwide, where the upper temperature limit for some cereals and further changes in climate may push them past suitability for their cultivation.

[Paleoclimate of La Guajira, Colombia; by the growth rings of Capparis odoratissima (Capparidaceae)].

PubMed

Ramírez, Jorge Andrés; Ignacio del Valle, Jorge

2011-09-01

There is great concern about the effect of climate change in arid and subarid areas of the tropics. Climate change combined with other anthropogenic activities such as deforestation, fires and over-grazing can accelerate their degradation and, consequently, the increases in losses of biological and economic productivity. Climate models, both local and global, predict that rainfall in the arid Peninsula of La Guajira in the Colombian Caribbean would be reduced and temperature would be increased as a result of climate change. However, as there are only suitable climate records since 1972, it is not possible to verify if, indeed, this is happening. To try to verify the hypothesis of reducing rainfall and rising temperatures we developed a growth ring chronology of Capparis odoratissima in the Middle Peninsula of La Guajira with 17 trees and 45 series which attain 48 years back. We use standard dendrochronological methods that showed statistically significant linear relationship with local climatic variables such as air temperature, sea surface temperature (SST), annual precipitation and wind speed; we also reach to successful relationship of the chronology with global climatic variables as the indices SOI and MEI of the ENSO phenomenon. The transfer functions estimated with the time series (1955 and 2003) do not showed statistically significant trends, indicating that during this period of time the annual precipitation or temperatures have not changed. The annual nature of C. odoratissima growth rings, the possibility of cross-dated among the samples of this species, and the high correlation with local and global climatic variables indicate a high potential of this species for dendrochronological studies in this part of the American continent.

The American Climate Prospectus: a risk-centered analysis of the economic impacts of climate change

NASA Astrophysics Data System (ADS)

Jina, A.; Houser, T.; Hsiang, S. M.; Kopp, R. E., III; Delgado, M.; Larsen, K.; Mohan, S.; Rasmussen, D.; Rising, J.; Wilson, P. S.; Muir-Wood, R.

2014-12-01

The American Climate Prospectus (ACP), the analysis underlying the Risky Business project, quantitatively assessed the climate risks posed to the United States' economy in six sectors - crop yields, energy demand, coastal property, crime, labor productivity, and mortality [1]. The ACP is unique in its characterization of the full probability distribution of economic impacts of climate change throughout the 21st century, making it an extremely useful basis for risk assessments. Three key innovations allow for this characterization. First, climate projections from CMIP5 models are scaled to a temperature probability distribution derived from a coarser climate model (MAGICC). This allows a more accurate representation of the whole distribution of future climates (in particular the tails) than a simple ensemble average. These are downscaled both temporally and spatially. Second, a set of local sea level rise and tropical cyclone projections are used in conjunction with the most detailed dataset of coastal property in the US in order to capture the risks of rising seas and storm surge. Third, we base many of our sectors on empirically-derived responses to temperature and precipitation. Each of these dose-response functions is resampled many times to populate a statistical distribution. Combining these with uncertainty in emissions scenario, climate model, and weather, we create the full probability distribution of climate impacts from county up to national levels, as well as model the effects upon the economy as a whole. Results are presented as likelihood ranges, as well as changes to return intervals of extreme events. The ACP analysis allows us to compare between sectors to understand the magnitude of required policy responses, and also to identify risks through time. Many sectors displaying large impacts at the end of the century, like those of mortality, have smaller changes in the near-term, due to non-linearities in the response functions. Other sectors, like coastal damages, have monotonically increasing costs throughout the 21st century. Taken together, the results from the ACP presents a unique and novel view of the short-, medium-, and long-term economic risks of climate change in the US. References: [1] T. Houser et al (2014), American Climate Prospectus, www.climateprospectus.org.

Ecosystem Evapotranspiration as a Response to Climate and Vegetation Coverage Changes in Northwest Yunnan, China

PubMed Central

Yang, Hao; Luo, Peng; Wang, Jun; Mou, Chengxiang; Mo, Li; Wang, Zhiyuan; Fu, Yao; Lin, Honghui; Yang, Yongping; Bhatta, Laxmi Dutt

2015-01-01

Climate and human-driven changes play an important role in regional droughts. Northwest Yunnan Province is a key region for biodiversity conservation in China, and it has experienced severe droughts since the beginning of this century; however, the extent of the contributions from climate and human-driven changes remains unclear. We calculated the ecosystem evapotranspiration (ET) and water yield (WY) of northwest Yunnan Province, China from 2001 to 2013 using meteorological and remote sensing observation data and a Surface Energy Balance System (SEBS) model. Multivariate regression analyses were used to differentiate the contribution of climate and vegetation coverage to ET. The results showed that the annual average vegetation coverage significantly increased over time with a mean of 0.69 in spite of the precipitation fluctuation. Afforestation/reforestation and other management efforts attributed to vegetation coverage increase in NW Yunnan. Both ET and WY considerably fluctuated with the climate factors, which ranged from 623.29 mm to 893.8 mm and –51.88 mm to 384.40 mm over the time period. Spatially, ET in the southeast of NW Yunnan (mainly in Lijiang) increased significantly, which was in line with the spatial trend of vegetation coverage. Multivariate linear regression analysis indicated that climatic factors accounted for 85.18% of the ET variation, while vegetation coverage explained 14.82%. On the other hand, precipitation accounted for 67.5% of the WY. We conclude that the continuous droughts in northwest Yunnan were primarily climatically driven; however, man-made land cover and vegetation changes also increased the vulnerability of local populations to drought. Because of the high proportion of the water yield consumed for subsistence and poor infrastructure for water management, local populations have been highly vulnerable to climate drought conditions. We suggest that conservation of native vegetation and development of water-conserving agricultural practices should be implemented as adaptive strategies to mitigate climate change. PMID:26237220

Ecosystem Evapotranspiration as a Response to Climate and Vegetation Coverage Changes in Northwest Yunnan, China.

PubMed

Yang, Hao; Luo, Peng; Wang, Jun; Mou, Chengxiang; Mo, Li; Wang, Zhiyuan; Fu, Yao; Lin, Honghui; Yang, Yongping; Bhatta, Laxmi Dutt

2015-01-01

Climate and human-driven changes play an important role in regional droughts. Northwest Yunnan Province is a key region for biodiversity conservation in China, and it has experienced severe droughts since the beginning of this century; however, the extent of the contributions from climate and human-driven changes remains unclear. We calculated the ecosystem evapotranspiration (ET) and water yield (WY) of northwest Yunnan Province, China from 2001 to 2013 using meteorological and remote sensing observation data and a Surface Energy Balance System (SEBS) model. Multivariate regression analyses were used to differentiate the contribution of climate and vegetation coverage to ET. The results showed that the annual average vegetation coverage significantly increased over time with a mean of 0.69 in spite of the precipitation fluctuation. Afforestation/reforestation and other management efforts attributed to vegetation coverage increase in NW Yunnan. Both ET and WY considerably fluctuated with the climate factors, which ranged from 623.29 mm to 893.8 mm and -51.88 mm to 384.40 mm over the time period. Spatially, ET in the southeast of NW Yunnan (mainly in Lijiang) increased significantly, which was in line with the spatial trend of vegetation coverage. Multivariate linear regression analysis indicated that climatic factors accounted for 85.18% of the ET variation, while vegetation coverage explained 14.82%. On the other hand, precipitation accounted for 67.5% of the WY. We conclude that the continuous droughts in northwest Yunnan were primarily climatically driven; however, man-made land cover and vegetation changes also increased the vulnerability of local populations to drought. Because of the high proportion of the water yield consumed for subsistence and poor infrastructure for water management, local populations have been highly vulnerable to climate drought conditions. We suggest that conservation of native vegetation and development of water-conserving agricultural practices should be implemented as adaptive strategies to mitigate climate change.

Understanding Differences in Chemistry Climate Model Projections of Stratospheric Ozone

NASA Technical Reports Server (NTRS)

Douglass, A. R.; Strahan, S. E.; Oman, L. D.; Stolarski, R. S.

2014-01-01

Chemistry climate models (CCMs) are used to project future evolution of stratospheric ozone as concentrations of ozone-depleting substances (ODSs) decrease and greenhouse gases increase, cooling the stratosphere. CCM projections exhibit not only many common features but also a broad range of values for quantities such as year of ozone return to 1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to ODS concentration change from that due to climate change. We show that the sensitivity of lower stratospheric ozone to chlorine change Delta Ozone/Delta inorganic chlorine is a near-linear function of partitioning of total inorganic chlorine into its reservoirs; both inorganic chlorine and its partitioning are largely controlled by lower stratospheric transport. CCMs with best performance on transport diagnostics agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035, differences in Delta Ozone/Delta inorganic chlorine contribute little to the spread in CCM projections as the anthropogenic contribution to inorganic chlorine becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change Delta Ozone/Delta T due to different contributions from various ozone loss processes, each with its own temperature dependence. Ozone decrease in the tropical lower stratosphere caused by a projected speedup in the Brewer-Dobson circulation may or may not be balanced by ozone increases in the middle- and high-latitude lower stratosphere and upper troposphere. This balance, or lack thereof, contributes most to the spread in late 21st century projections.

Variation in piñon pine growth responses to climate across gradients of environmental stress using an individual-based approach

NASA Astrophysics Data System (ADS)

Redmond, M. D.; Kelsey, K.; Urza, A.; Barger, N. N.

2015-12-01

Forest and woodland ecosystems play a crucial role in the global carbon cycle and may be strongly affected by changing climate. Here we use an individual-based approach to model piñon pine (Pinus edulis) radial growth responses to climate across gradients of environmental stress. We sampled piñon pine trees at 24 sites across southwestern Colorado that varied in soil available water capacity, elevation, and latitude, obtaining a total of 552 pinon pine tree ring series. We used linear mixed effect models to assess piñon pine growth responses to climate and site-level environmental stress (mean annual climatic water deficit and soil available water capacity). Using a similar modeling approach, we also determined long-term growth trends across our gradients of environmental stress. Piñon pine growth was strongly positively associated with winter precipitation and strongly negatively associated with summer vapor pressure deficit. However, the strength of the relationship between winter precipitation and piñon pine growth was affected by site-level environmental stress. Trees at sites with greater climatic water deficit (i.e. hotter, drier sites) were more sensitive to winter precipitation. Interestingly, trees at sites with greater soil available water capacity were also more sensitive to winter precipitation, as these trees had much higher growth rates during years of high precipitation. We found weak evidence of long-term declines in piñon growth rates over the past century within our study area. Growth trends overtime did vary across our soil available water capacity gradient: trees growing at sites with higher soil available water capacity responded more positively to the cool, wet climate conditions of the 1910s and 1980s, whereas tree growth rates at sites with lower soil available water capacity declined more linearly over the last century. Our findings suggest that the sensitivity of woodland ecosystems to changing climate will vary across the landscape due to differences in edaphic and physiographic factors. These results support recent dendroecology studies that emphasize the need to use a more individual-based approach to enhance our understanding of tree growth responses to climate.

Future premature mortality due to O3, secondary inorganic aerosols and primary PM in Europe--sensitivity to changes in climate, anthropogenic emissions, population and building stock.

PubMed

Geels, Camilla; Andersson, Camilla; Hänninen, Otto; Lansø, Anne Sofie; Schwarze, Per E; Skjøth, Carsten Ambelas; Brandt, Jørgen

2015-03-04

Air pollution is an important environmental factor associated with health impacts in Europe and considerable resources are used to reduce exposure to air pollution through emission reductions. These reductions will have non-linear effects on exposure due, e.g., to interactions between climate and atmospheric chemistry. By using an integrated assessment model, we quantify the effect of changes in climate, emissions and population demography on exposure and health impacts in Europe. The sensitivity to the changes is assessed by investigating the differences between the decades 2000-2009, 2050-2059 and 2080-2089. We focus on the number of premature deaths related to atmospheric ozone, Secondary Inorganic Aerosols and primary PM. For the Nordic region we furthermore include a projection on how population exposure might develop due to changes in building stock with increased energy efficiency. Reductions in emissions cause a large significant decrease in mortality, while climate effects on chemistry and emissions only affects premature mortality by a few percent. Changes in population demography lead to a larger relative increase in chronic mortality than the relative increase in population. Finally, the projected changes in building stock and infiltration rates in the Nordic indicate that this factor may be very important for assessments of population exposure in the future.

Future Premature Mortality Due to O3, Secondary Inorganic Aerosols and Primary PM in Europe — Sensitivity to Changes in Climate, Anthropogenic Emissions, Population and Building Stock

PubMed Central

Geels, Camilla; Andersson, Camilla; Hänninen, Otto; Lansø, Anne Sofie; Schwarze, Per E.; Ambelas Skjøth, Carsten; Brandt, Jørgen

2015-01-01

Air pollution is an important environmental factor associated with health impacts in Europe and considerable resources are used to reduce exposure to air pollution through emission reductions. These reductions will have non-linear effects on exposure due, e.g., to interactions between climate and atmospheric chemistry. By using an integrated assessment model, we quantify the effect of changes in climate, emissions and population demography on exposure and health impacts in Europe. The sensitivity to the changes is assessed by investigating the differences between the decades 2000–2009, 2050–2059 and 2080–2089. We focus on the number of premature deaths related to atmospheric ozone, Secondary Inorganic Aerosols and primary PM. For the Nordic region we furthermore include a projection on how population exposure might develop due to changes in building stock with increased energy efficiency. Reductions in emissions cause a large significant decrease in mortality, while climate effects on chemistry and emissions only affects premature mortality by a few percent. Changes in population demography lead to a larger relative increase in chronic mortality than the relative increase in population. Finally, the projected changes in building stock and infiltration rates in the Nordic indicate that this factor may be very important for assessments of population exposure in the future. PMID:25749320

Assimilating Non-linear Effects of Customized Large-Scale Climate Predictors on Downscaled Precipitation over the Tropical Andes

NASA Astrophysics Data System (ADS)

Molina, J. M.; Zaitchik, B. F.

2016-12-01

Recent findings considering high CO2 emission scenarios (RCP8.5) suggest that the tropical Andes may experience a massive warming and a significant precipitation increase (decrease) during the wet (dry) seasons by the end of the 21st century. Variations on rainfall-streamflow relationships and seasonal crop yields significantly affect human development in this region and make local communities highly vulnerable to climate change and variability. We developed an expert-informed empirical statistical downscaling (ESD) algorithm to explore and construct robust global climate predictors to perform skillful RCP8.5 projections of in-situ March-May (MAM) precipitation required for impact modeling and adaptation studies. We applied our framework to a topographically-complex region of the Colombian Andes where a number of previous studies have reported El Niño-Southern Oscillation (ENSO) as the main driver of climate variability. Supervised machine learning algorithms were trained with customized and bias-corrected predictors from NCEP reanalysis, and a cross-validation approach was implemented to assess both predictive skill and model selection. We found weak and not significant teleconnections between precipitation and lagged seasonal surface temperatures over El Niño3.4 domain, which suggests that ENSO fails to explain MAM rainfall variability in the study region. In contrast, series of Sea Level Pressure (SLP) over American Samoa -likely associated with the South Pacific Convergence Zone (SPCZ)- explains more than 65% of the precipitation variance. The best prediction skill was obtained with Selected Generalized Additive Models (SGAM) given their ability to capture linear/nonlinear relationships present in the data. While SPCZ-related series exhibited a positive linear effect in the rainfall response, SLP predictors in the north Atlantic and central equatorial Pacific showed nonlinear effects. A multimodel (MIROC, CanESM2 and CCSM) ensemble of ESD projections revealed an increased variability and a positive and significant trend in the MAM precipitation mean in the next decades, with accentuated changes and projection uncertainty after 2050. ESD traces (2050-2100) from MIROC presented the highest changes in the precipitation mean ( 60%) when compared with the observations.

Uncertainty of climate change impact on groundwater reserves - Application to a chalk aquifer

NASA Astrophysics Data System (ADS)

Goderniaux, Pascal; Brouyère, Serge; Wildemeersch, Samuel; Therrien, René; Dassargues, Alain

2015-09-01

Recent studies have evaluated the impact of climate change on groundwater resources for different geographical and climatic contexts. However, most studies have either not estimated the uncertainty around projected impacts or have limited the analysis to the uncertainty related to climate models. In this study, the uncertainties around impact projections from several sources (climate models, natural variability of the weather, hydrological model calibration) are calculated and compared for the Geer catchment (465 km2) in Belgium. We use a surface-subsurface integrated model implemented using the finite element code HydroGeoSphere, coupled with climate change scenarios (2010-2085) and the UCODE_2005 inverse model, to assess the uncertainty related to the calibration of the hydrological model. This integrated model provides a more realistic representation of the water exchanges between surface and subsurface domains and constrains more the calibration with the use of both surface and subsurface observed data. Sensitivity and uncertainty analyses were performed on predictions. The linear uncertainty analysis is approximate for this nonlinear system, but it provides some measure of uncertainty for computationally demanding models. Results show that, for the Geer catchment, the most important uncertainty is related to calibration of the hydrological model. The total uncertainty associated with the prediction of groundwater levels remains large. By the end of the century, however, the uncertainty becomes smaller than the predicted decline in groundwater levels.

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.

Detecting Anthropogenic and Climate Change Induced Land Cover and Land Use Change in the Vicinity of an Oil/gas Facility in Northwestern Siberia, Russia

NASA Astrophysics Data System (ADS)

Yu, Q.; Shiklomanov, N. I.; Streletskiy, D. A.; Engstrom, R.; Epstein, H. E.

2015-12-01

Arctic ecosystems are changing dramatically due to changes in climate, vegetation and human activities. Northwestern Siberia is one of the regions which has been undergoing various land cover and land use changes associated primarily with animal husbandry and oil/gas development. These changes have been exacerbated by warming climatic conditions over the last fifty years. In this study, we investigated land cover and land use changes associated with oil and gas development southeast of the city of Nadym within the context of climate change based on multi-source and multi-temporal remote sensing imagery. The impacts of land use on surface vegetation, radiation, and hydrological properties were evaluated using the Normalized Difference Vegetation Index (NDVI), albedo and the Normalized Difference Water Index (NDWI). The results from a comparison between high spatial resolution imagery acquired in1968 and 2006 indicate that the vegetation cover was reduced in areas disturbed by oil and gas development. Vegetation cover increased in natural landscapes over the same period,. Water logging was found along the linear structures near the oil/gas development, while in natural landscapes the drying of thermokarst lakes is evident due to permafrost degradation. Derived indices suggest that the direct impacts associated with infrastructure development are mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance.

Impact of natural variability on the perception of climate change for the upcoming decades: Analysis of the CanESM2-LE and CESM-LE large ensembles

NASA Astrophysics Data System (ADS)

Rondeau-Genesse, G.; Braun, M.; Chaumont, D.

2017-12-01

The pace of climate change can have a direct impact on the efforts required to adapt. However, for relatively short time scales, this pace can be masked by natural variability (NV). In some cases, this variability might cause, for a few decades, climate change to exceed what would be expected from the greenhouse gas (GHG) emissions alone or, to the contrary, it might cause slowdowns or even hiatuses. This phenomenon is difficult to explore using ensembles such as CMIP5, which are composed of multiple climatological models and thus combine both NV and inter-model differences. This study analyses CanESM2-LE and CESM-LE, two state-of-the-art large ensembles (LE) comprised of multiple realizations from a single climatological model and a single GHG emission scenario. We explore the relationship between NV and climate change over the next few decades in Canada and the United States. Temperature indices, namely the mean annual temperature and the 3-day maximum and minimum temperatures are assessed. Results indicate that under the RCP8.5, temperatures within most of the individual large ensemble members will increase in a roughly linear manner between 2021 and 2060. Nevertheless, in some regions such as parts of Canada and Alaska, there is a 20 to 35% probability that the temperature increase will slow down between 2021 and 2040. Such a slowdown in warming temperatures would provide some leeway for adaptation projects, but this phenomenon is caused by NV alone and, as such, is only temporary. Indeed, members of the large ensembles where a slowdown of warming is found during the 2021-2040 period are two to five times more likely to experience a period of very fast warming in the following decades. The opposite scenario, where the changes expected by 2050 would occur early because of NV, remains fairly uncommon for the mean annual temperature. For the extreme temperature indices however, this early warming still occurs in 5 to 20% of the large ensemble members. As such, while our results indicate that the dominant pattern in Canada and the United States is a fairly linear warming, the chances for other patterns is non negligible for the upcoming decades. This reinforces the need for constant, uninterrupted efforts towards climate change adaptation.

Investigating the Linear Dependence of Direct and Indirect Radiative Forcing on Emission of Carbonaceous Aerosols in a Global Climate Model

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

Chen, Yanju; Wang, Hailong; Singh, Balwinder

The linearity of dependence of aerosol direct and indirect radiative forcing (DRF and IRF) on emissions is essential to answer the policy-relevant question on how the change in forcing would result from a change in emission. In this study, the forcing-to-emission relationship is investigated for black carbon (BC) and primary organic carbon (OC) emitted from North America and Asia. Direct and indirect radiative forcing of BC and OC are simulated with the Community Atmosphere Model (CAM5.1). Two diagnostics are introduced to aid in policy-relevant discussion: emission-normalized forcing (ENF) and linearity (R). DRF is linearly related to emission for both BCmore » and OC from the two regions and emission-normalized DRF is similar, within 15%. IRF is linear to emissions for weaker sources and regions far from source (North American BC and OC), while for large emission sources and near source regions (Asian OC) the response of forcing to emission is sub-linear. In North America emission-normalized IRF (ENIRF) is 2-4 times higher than that in Asia. The difference among regions and species is primarily caused by failure of accumulation mode particles to become CCN, and then to activate into CDNC. Optimal aggregation area (30ºx 30º) has been used to communicate the regional variation of forcing-to-emission relationship. For IRF, only 15-40% of the Earth’s surface is significantly affected by the two emission regions, but the forcing in these regions comprises most of the global impact. Linearity of IRF occurs in about two-thirds of the significant regions except for Asian OC. ENF is an effective tool to estimate forcing changes due to reduction of surface emissions, as long as there is sufficient attention to the causes of nonlinearity in the simulations used to derive ENIRF (emission into polluted regions and emission elevation). The differences in ENIRF have important implications for policy decisions. Lower ENIRF in more polluted region like Asia means that reductions of large amounts of OC in these regions would be relatively climate-neutral rather than causing significant warming via IRF reduction.« less

ENSO Diversity Changes Due To Global Warming In CESM-LE

NASA Astrophysics Data System (ADS)

Carreric, A.; Dewitte, B.; Guemas, V.

2017-12-01

The El Niño Southern Oscillation (ENSO) is predicted to be modified due to global warming based on the CMIP3 and CMIP5 data bases. In particular the frequency of occurrence of extreme Eastern Pacific El Niño events is to double in the future in response to the increase in green-house gazes. Such forecast relies however on state-of-the-art models that still present mean state biases and do not simulate realistically key features of El Niño events such as its diversity which is related to the existence of at least two types of El Niño events, the Eastern Pacific (EP) El Nino and the Central Pacific (CP) El Niño events. Here we take advantage of the Community Earth System Model (CESM) Large Ensemble (LE) that provides 35 realizations of the climate of the 1920-2100 period with a combination of both natural and anthropogenic climate forcing factors, to explore on the one hand methods to detect changes in ENSO statistics and on the other hand to investigate changes in thermodynamical processes associated to the increase oceanic stratification owed to global warming. The CESM simulates realistically many aspects of the ENSO diversity, in particular the non-linear evolution of the phase space of the first two EOF modes of Sea Surface Temperature (SST) anomalies in the tropical Pacific. Based on indices accounting for the two ENSO regimes used in the literature, we show that, although there is no statistically significant (i.e. confidence level > 95%) changes in the occurrence of El Niño types from the present to the future climate, the estimate of the changes is sensitive to the definition of ENSO indices that is used. CESM simulates in particular an increase occurrence of extreme El Niño events that can vary by 28% from one method to the other. It is shown that the seasonal evolution of EP El Niño events is modified from the present to the future climate, with in particular a larger occurrence of events taking place in Austral summer in the warmer climate compared to events peaking in Austral winter. The ENSO non-linearity is also showed to increase, which is interpreted as resulting from the increased stratification based on the analysis of the control experiment and an estimate of the oceanic mixed-layer heat budget. Implications for understanding processes associated to change in ENSO in a warmer climate are discussed.

Comparison of winter wheat yield sensitivity to climate variables under irrigated and rain-fed conditions

NASA Astrophysics Data System (ADS)

Xiao, Dengpan; Shen, Yanjun; Zhang, He; Moiwo, Juana P.; Qi, Yongqing; Wang, Rende; Pei, Hongwei; Zhang, Yucui; Shen, Huitao

2016-09-01

Crop simulation models provide alternative, less time-consuming, and cost-effective means of determining the sensitivity of crop yield to climate change. In this study, two dynamic mechanistic models, CERES (Crop Environment Resource Synthesis) and APSIM (Agricultural Production Systems Simulator), were used to simulate the yield of wheat ( Triticum aestivum L.) under well irrigated (CFG) and rain-fed (YY) conditions in relation to different climate variables in the North China Plain (NCP). The study tested winter wheat yield sensitivity to different levels of temperature, radiation, precipitation, and atmospheric carbon dioxide (CO2) concentration under CFG and YY conditions at Luancheng Agro-ecosystem Experimental Stations in the NCP. The results from the CERES and APSIM wheat crop models were largely consistent and suggested that changes in climate variables influenced wheat grain yield in the NCP. There was also significant variation in the sensitivity of winter wheat yield to climate variables under different water (CFG and YY) conditions. While a temperature increase of 2°C was the threshold beyond which temperature negatively influenced wheat yield under CFG, a temperature rise exceeding 1°C decreased winter wheat grain yield under YY. A decrease in solar radiation decreased wheat grain yield under both CFG and YY conditions. Although the sensitivity of winter wheat yield to precipitation was small under the CFG, yield decreased significantly with decreasing precipitation under the rainfed YY treatment. The results also suggest that wheat yield under CFG linearly increased by ≈3.5% per 60 ppm (parts per million) increase in CO2 concentration from 380 to 560 ppm, and yield under YY increased linearly by ≈7.0% for the same increase in CO2 concentration.

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change.

PubMed

Schut, Antonius G T; Ivits, Eva; Conijn, Jacob G; Ten Brink, Ben; Fensholt, Rasmus

2015-01-01

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982-2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17-36% of all productive areas depending on the NDVI metric used. For only 1-2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity.

Future Climate Change in the Baltic Sea Area

NASA Astrophysics Data System (ADS)

Bøssing Christensen, Ole; Kjellström, Erik; Zorita, Eduardo; Sonnenborg, Torben; Meier, Markus; Grinsted, Aslak

2015-04-01

Regional climate models have been used extensively since the first assessment of climate change in the Baltic Sea region published in 2008, not the least for studies of Europe (and including the Baltic Sea catchment area). Therefore, conclusions regarding climate model results have a better foundation than was the case for the first BACC report of 2008. This presentation will report model results regarding future climate. What is the state of understanding about future human-driven climate change? We will cover regional models, statistical downscaling, hydrological modelling, ocean modelling and sea-level change as it is projected for the Baltic Sea region. Collections of regional model simulations from the ENSEMBLES project for example, financed through the European 5th Framework Programme and the World Climate Research Programme Coordinated Regional Climate Downscaling Experiment, have made it possible to obtain an increasingly robust estimation of model uncertainty. While the first Baltic Sea assessment mainly used four simulations from the European 5th Framework Programme PRUDENCE project, an ensemble of 13 transient regional simulations with twice the horizontal resolution reaching the end of the 21st century has been available from the ENSEMBLES project; therefore it has been possible to obtain more quantitative assessments of model uncertainty. The literature about future climate change in the Baltic Sea region is largely built upon the ENSEMBLES project. Also within statistical downscaling, a considerable number of papers have been published, encompassing now the application of non-linear statistical models, projected changes in extremes and correction of climate model biases. The uncertainty of hydrological change has received increasing attention since the previous Baltic Sea assessment. Several studies on the propagation of uncertainties originating in GCMs, RCMs, and emission scenarios are presented. The number of studies on uncertainties related to downscaling and impact models is relatively small, but more are emerging. A large number of coupled climate-environmental scenario simulations for the Baltic Sea have been performed within the BONUS+ projects (ECOSUPPORT, INFLOW, AMBER and Baltic-C (2009-2011)), using various combinations of output from GCMs, RCMs, hydrological models and scenarios for load and emission of nutrients as forcing for Baltic Sea models. Such a large ensemble of scenario simulations for the Baltic Sea has never before been produced and enables for the first time an estimation of uncertainties.

Challenges and opportunities for improved understanding of regional climate dynamics

NASA Astrophysics Data System (ADS)

Collins, Matthew; Minobe, Shoshiro; Barreiro, Marcelo; Bordoni, Simona; Kaspi, Yohai; Kuwano-Yoshida, Akira; Keenlyside, Noel; Manzini, Elisa; O'Reilly, Christopher H.; Sutton, Rowan; Xie, Shang-Ping; Zolina, Olga

2018-01-01

Dynamical processes in the atmosphere and ocean are central to determining the large-scale drivers of regional climate change, yet their predictive understanding is poor. Here, we identify three frontline challenges in climate dynamics where significant progress can be made to inform adaptation: response of storms, blocks and jet streams to external forcing; basin-to-basin and tropical-extratropical teleconnections; and the development of non-linear predictive theory. We highlight opportunities and techniques for making immediate progress in these areas, which critically involve the development of high-resolution coupled model simulations, partial coupling or pacemaker experiments, as well as the development and use of dynamical metrics and exploitation of hierarchies of models.

Response of the Morus bombycis growing season to temperature and its latitudinal pattern in Japan.

PubMed

Doi, Hideyuki

2012-09-01

Changes in leaf phenology lengthen the growing season length (GSL, the days between leaf budburst and leaf fall) under the global warming. GSL and the leaf phenology response to climate change is one of the most important predictors of climate change effect on plants. Empirical evidence of climatic effects on GSL remains scarce, especially at a regional scale and the latitudinal pattern. This study analyzed the datasets of leaf budburst and fall phenology in Morus bombycis (Urticales), which were observed by the agency of the Japan Meteorological Agency (JMA) from 1953 to 2005 over a wide range of latitudes in Japan (31 to 44° N). In the present study, single regression slopes of leaf phenological timing and air temperature across Japan were calculated and their spatial patterns using general linear models were tested. The results showed that the GSL extension was caused mainly by a delay in leaf fall phenology. Relationships between latitude and leaf phenological and GSL responses against air temperature were significantly negative. The response of leaf phenology and GSL to air temperature at lower latitudes was larger than that at higher latitudes. The findings indicate that GSL extension should be considered with regards to latitude and climate change.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Stand Competition Determines How Different Tree Species Will Cope with a Warming Climate

PubMed Central

Fernández-de-Uña, Laura; Cañellas, Isabel; Gea-Izquierdo, Guillermo

2015-01-01

Plant-plant interactions influence how forests cope with climate and contribute to modulate species response to future climate scenarios. We analysed the functional relationships between growth, climate and competition for Pinus sylvestris, Quercus pyrenaica and Quercus faginea to investigate how stand competition modifies forest sensitivity to climate and simulated how annual growth rates of these species with different drought tolerance would change throughout the 21st century. Dendroecological data from stands subjected to thinning were modelled using a novel multiplicative nonlinear approach to overcome biases related to the general assumption of a linear relationship between covariates and to better mimic the biological relationships involved. Growth always decreased exponentially with increasing competition, which explained more growth variability than climate in Q. faginea and P. sylvestris. The effect of precipitation was asymptotic in all cases, while the relationship between growth and temperature reached an optimum after which growth declined with warmer temperatures. Our growth projections indicate that the less drought-tolerant P. sylvestris would be more negatively affected by climate change than the studied sub-Mediterranean oaks. Q. faginea and P. sylvestris mean growth would decrease under all the climate change scenarios assessed. However, P. sylvestris growth would decline regardless of the competition level, whereas this decrease would be offset by reduced competition in Q. faginea. Conversely, Q. pyrenaica growth would remain similar to current rates, except for the warmest scenario. Our models shed light on the nature of the species-specific interaction between climate and competition and yield important implications for management. Assuming that individual growth is directly related to tree performance, trees under low competition would better withstand the warmer conditions predicted under climate change scenarios but in a variable manner depending on the species. Thinning following an exponential rule may be desirable to ensure long-term conservation of high-density Mediterranean woodlands, particularly in drought-limited sites. PMID:25826446

Changing climate and nutrient transfers: Evidence from high temporal resolution concentration-flow dynamics in headwater catchments.

PubMed

Ockenden, M C; Deasy, C E; Benskin, C McW H; Beven, K J; Burke, S; Collins, A L; Evans, R; Falloon, P D; Forber, K J; Hiscock, K M; Hollaway, M J; Kahana, R; Macleod, C J A; Reaney, S M; Snell, M A; Villamizar, M L; Wearing, C; Withers, P J A; Zhou, J G; Haygarth, P M

2016-04-01

We hypothesise that climate change, together with intensive agricultural systems, will increase the transfer of pollutants from land to water and impact on stream health. This study builds, for the first time, an integrated assessment of nutrient transfers, bringing together a) high-frequency data from the outlets of two surface water-dominated, headwater (~10km(2)) agricultural catchments, b) event-by-event analysis of nutrient transfers, c) concentration duration curves for comparison with EU Water Framework Directive water quality targets, d) event analysis of location-specific, sub-daily rainfall projections (UKCP, 2009), and e) a linear model relating storm rainfall to phosphorus load. These components, in combination, bring innovation and new insight into the estimation of future phosphorus transfers, which was not available from individual components. The data demonstrated two features of particular concern for climate change impacts. Firstly, the bulk of the suspended sediment and total phosphorus (TP) load (greater than 90% and 80% respectively) was transferred during the highest discharge events. The linear model of rainfall-driven TP transfers estimated that, with the projected increase in winter rainfall (+8% to +17% in the catchments by 2050s), annual event loads might increase by around 9% on average, if agricultural practices remain unchanged. Secondly, events following dry periods of several weeks, particularly in summer, were responsible for high concentrations of phosphorus, but relatively low loads. The high concentrations, associated with low flow, could become more frequent or last longer in the future, with a corresponding increase in the length of time that threshold concentrations (e.g. for water quality status) are exceeded. The results suggest that in order to build resilience in stream health and help mitigate potential increases in diffuse agricultural water pollution due to climate change, land management practices should target controllable risk factors, such as soil nutrient status, soil condition and crop cover. Copyright © 2015 Elsevier B.V. All rights reserved.

A Digital Map From External Forcing to the Final Surface Warming Pattern and its Seasonal Cycle

NASA Astrophysics Data System (ADS)

Cai, M.

2015-12-01

Historically, only the thermodynamic processes (e.g., water vapor, cloud, surface albedo, and atmospheric lapse rate) that directly influence the top of the atmosphere (TOA) radiative energy flux balance are considered in climate feedback analysis. One of my recent research areas is to develop a new framework for climate feedback analysis that explicitly takes into consideration not only the thermodynamic processes that the directly influence the TOA radiative energy flux balance but also the local dynamical (e.g., evaporation, surface sensible heat flux, vertical convections etc) and non-local dynamical (large-scale horizontal energy transport) processes in aiming to explain the warming asymmetry between high and low latitudes, between ocean and land, and between the surface and atmosphere. In the last 5-6 years, we have developed a coupled atmosphere-surface climate feedback-response analysis method (CFRAM) as a new framework for estimating climate feedback and sensitivity in coupled general circulation models with a full physical parameterization package. In the CFRAM, the isolation of partial temperature changes due to an external forcing alone or an individual feedback is achieved by solving the linearized infrared radiation transfer model subject to individual energy flux perturbations (external or due to feedbacks). The partial temperature changes are addable and their sum is equal to the (total) temperature change (in the linear sense). The CFRAM is used to isolate the partial temperature changes due to the external forcing, due to water vapor feedback, clouds, surface albedo, local vertical convection, and non-local atmospheric dynamical feedbacks, as well as oceanic heat storage. It has been shown that seasonal variations in the cloud feedback, surface albedo feedback, and ocean heat storage/dynamics feedback, directly caused by the strong annual cycle of insolation, contribute primarily to the large seasonal variation of polar warming. Furthermore, the CO2 forcing, and water vapor and atmospheric dynamics feedbacks add to the maximum polar warming in fall/winter.

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

Climate Change and Tropical Total Lightning

NASA Technical Reports Server (NTRS)

Albrecht, R.; Petersen, W.; Buechler, D.; Goodman, S.; Blakeslee, R.; Christian, H.

2009-01-01

While global warming is regarded as a fact by many in the scientific community, its future impact remains a challenge to be determined and measured. The International Panel on Climate Change (IPCC) assessment report (IPCC, 2007) shows inconclusive answers on global rainfall trends and general agreement on a future drier climate with increased global warming. The relationship between temperature, humidity and convection is not linear and is strongly dependent on regional scale features, such as topography and land cover. Furthermore, the relationship between convective lightning production (thunderstorms) and temperature is even more complicated, being subjected to the cloud dynamics and microphysics. Total lightning (intracloud and cloud-to-ground) monitoring is a relatively new field of observation. Global and tropical total lightning began to be more extensively measured by satellites in the mid 90s. In this scope, the Lightning Imaging Sensor (LIS) onboard of the Tropical Rainfall Measurement Mission (TRMM) has been operational for over 11 years. Here we address total lightning trends observed by LIS from 1998 to 2008 in different temporal (annual and seasonal) and spatial (large and regional) scales. The observed 11-year trends are then associate to different predicted/hypothesized climate change scenarios.

When goals diverge: Staff consensus and the organizational climate.

PubMed

Melnick, Gerald; Ulaszek, Wendy R; Lin, Hsiu-Ju; Wexler, Harry K

2009-08-01

A sample of correctional officers and prison substance abuse treatment staff collected by the National Criminal Justice Treatment Practices Survey is used to provide an exploratory study of an aspect of organizational culture consisting of consensus (agreement) among prison personnel regarding their beliefs about rehabilitation in the presence of conflicting organizational goals and aspects of the organizational climate important to change. Findings show that among those staff members responding to the survey, the belief in rehabilitation scale mean score was associated with higher levels of organizational commitment, and interdepartmental coordination. However, an hierarchical linear modeling (HLM) analysis that used an index score derived from the standard deviation for staff consensus regarding these same beliefs about rehabilitation produced a different pattern of results, showing that high levels of consensus were associated with job frustration, cynicism towards the ability of the institution to change, and lower levels of organizational commitment. The authors conclude that, although the sample may not express the beliefs of corrections officers or prison-based treatment staff at large, within the sample, consensus appeared to play a unique role in evaluating the effect of divergent goals on organizational climate as it relates to change, and warrants consideration when considering the effects of organizational climate.

Estimating Past Temperature Change in Antarctica Based on Ice Core Stable Water Isotope Diffusion

NASA Astrophysics Data System (ADS)

Kahle, E. C.; Markle, B. R.; Holme, C.; Jones, T. R.; Steig, E. J.

2017-12-01

The magnitude of the last glacial-interglacial transition is a key target for constraining climate sensitivity on long timescales. Ice core proxy records and general circulation models (GCMs) both provide insight on the magnitude of climate change through the last glacial-interglacial transition, but appear to provide different answers. In particular, the magnitude of the glacial-interglacial temperature change reconstructed from East Antarctic ice-core water-isotope records is greater ( 9 degrees C) than that from most GCM simulations ( 6 degrees C). A possible source of this difference is error in the linear-scaling of water isotopes to temperature. We employ a novel, nonlinear temperature-reconstruction technique using the physics of water-isotope diffusion to infer past temperature. Based on new, ice-core data from the South Pole, this diffusion technique suggests East Antarctic temperature change was smaller than previously thought. We are able to confirm this result using a simple, water-isotope fractionation model to nonlinearly reconstruct temperature change at ice core locations across Antarctica based on combined oxygen and hydrogen isotope ratios. Both methods produce a temperature change of 6 degrees C for South Pole, agreeing with GCM results for East Antarctica. Furthermore, both produce much larger changes in West Antarctica, also in agreement with GCM results and independent borehole thermometry. These results support the fidelity of GCMs in simulating last glacial maximum climate, and contradict the idea, based on previous work, that the climate sensitivity of current GCMs is too low.

Forecasted range shifts of arid-land fishes in response to climate change

USGS Publications Warehouse

Whitney, James E.; Whittier, Joanna B.; Paukert, Craig P.; Olden, Julian D.; Strecker, Angela L.

2017-01-01

Climate change is poised to alter the distributional limits, center, and size of many species. Traits may influence different aspects of range shifts, with trophic generality facilitating shifts at the leading edge, and greater thermal tolerance limiting contractions at the trailing edge. The generality of relationships between traits and range shifts remains ambiguous however, especially for imperiled fishes residing in xeric riverscapes. Our objectives were to quantify contemporary fish distributions in the Lower Colorado River Basin, forecast climate change by 2085 using two general circulation models, and quantify shifts in the limits, center, and size of fish elevational ranges according to fish traits. We examined relationships among traits and range shift metrics either singly using univariate linear modeling or combined with multivariate redundancy analysis. We found that trophic and dispersal traits were associated with shifts at the leading and trailing edges, respectively, although projected range shifts were largely unexplained by traits. As expected, piscivores and omnivores with broader diets shifted upslope most at the leading edge while more specialized invertivores exhibited minimal changes. Fishes that were more mobile shifted upslope most at the trailing edge, defying predictions. No traits explained changes in range center or size. Finally, current preference explained multivariate range shifts, as fishes with faster current preferences exhibited smaller multivariate changes. Although range shifts were largely unexplained by traits, more specialized invertivorous fishes with lower dispersal propensity or greater current preference may require the greatest conservation efforts because of their limited capacity to shift ranges under climate change.

A Combined Solar and Geomagnetic Index for Thermospheric Climate

NASA Technical Reports Server (NTRS)

Hunt, Linda; Mlynczak, Marty

2015-01-01

Infrared radiation from nitric oxide (NO) at 5.3 Â is a primary mechanism by which the thermosphere cools to space. The SABER instrument on the NASA TIMED satellite has been measuring thermospheric cooling by NO for over 13 years. Physically, changes in NO emission are due to changes in temperature, atomic oxygen, and the NO density. These physical changes however are driven by changes in solar irradiance and changes in geomagnetic conditions. We show that the SABER time series of globally integrated infrared power (Watts) radiated by NO can be replicated accurately by a multiple linear regression fit using the F10.7, Ap, and Dst indices. This fit enables several fundamental properties of NO cooling to be determined as well as their variability with time, permitting reconstruction of the NO power time series back nearly 70 years with extant databases of these indices. The relative roles of solar ultraviolet and geomagnetic processes in determining the NO cooling are derived and shown to be solar cycle dependent. This reconstruction provides a long-term time series of an integral radiative constraint on thermospheric climate that can be used to test climate models.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Spatiotemporal distribution and variation of GPP in the Greater Khingan Mountains from 1982 to 2015

NASA Astrophysics Data System (ADS)

Hu, L.; Fan, W.; Liu, S.; Ren, H.; Xu, X.

2017-12-01

GPP (Gross Primary Productivity) is an important index to reflect the productivity of plants because it refers to the organic accumulated by green plants on land through assimilating the carbon dioxide in the atmosphere by photosynthesis and a serial of physiological processes in plants. Therefore, GPP plays a significant role in studying the carbon sink of terrestrial ecosystem and plants' reaction to global climate change. Remote sensing provides an efficient way to estimate GPP at regional and global scales and its products can be used to monitor the spatiotemporal variation of terrestrial ecosystem.As the Greater Khingan Mountains is the only bright coniferous forest of cool temperate zone in China and accounts for about 30% of the forest in China. This region is sensitive to climate change, but its forest coverage presented a significant variation due to fire disasters, excessive deforestation and so on. Here, we aimed at studying the variation pattern of GPP in the Greater Khingan Mountains and further found impact factors for the change in order to improve the understanding of what have and will happen on plants and carbon cycle under climate change.Based on GPP product from the GLASS program, we first studied spatial distribution of plants in the Greater Khingan Mountains from 1982 to 2015. With a linear regression model, seasonal and inter-annual GPP variability were explored on pixel and regional scale. We analyzed some climatic factors (e.g. temperature and precipitation) and terrain in order to find the driven factors for the GPP variations. The Growing Season Length (GSL) was also regarded as a factor and was retrieved from GIMMS 3g NDVI datasets using dynamic threshold method. We found that GPP in study area linearly decreased with the increasing elevation. Both annual accumulated GPP (AAG) and maximum daily GPP (during mid-June to mid-July) gained obvious improvement over the past 34 years under climate warming and drying (Fig.1 and Fig.2). Further studies showed temperature had positive correlation with GPP while precipitation had negative effect; Moreover, multi-regression results reflected that temperature rather than precipitation was the dominant climatic factor for plants in study area. The extension of GSL also increased the AAG.

Model-based evidence for persistent species zonation shifts in the southern Rocky Mountains under a warming climate

NASA Astrophysics Data System (ADS)

Foster, A.; Shuman, J. K.; Shugart, H. H., Jr.; Dwire, K. A.; Fornwalt, P.; Sibold, J.; Negrón, J. F.

2016-12-01

Forests in the Rocky Mountains are a crucial part of the North American carbon budget, but increases in disturbances such as insect outbreaks and fire, in conjunction with climate change, threaten their vitality. Mean annual temperatures in the western United States have increased by 2°C since 1950 and the higher elevations are warming faster than the rest of the landscape. It is predicted that this warming trend will continue, and that by the end of this century, nearly 50% of the western US landscape will have climate profiles with no current analog within that region. Individual tree-based modeling allows various climate change scenarios and their effects on forest dynamics to be tested. We use an updated individual-based gap model, the University of Virginia Forest Model Enhanced (UVAFME) at a subalpine site in the southern Rocky Mountains. UVAFME has been quantitatively and qualitatively validated in the southern Rocky Mountains, and results show that UVAFME-output on size structure, biomass, and species composition compares reasonably to inventory data and descriptions of vegetation zonation and successional dynamics for the region. We perform a climate sensitivity test in which temperature is first increased linearly by 2°C over 100 years, stabilized for 200 years, cooled back to present climate values over 100 years, and again stabilized for 200 years. This test is conducted to determine what effect elevated temperatures may have on vegetation zonation, and how persistent the changes may be if the climate is brought back to its current state. Results show that elevated temperatures within the southern Rocky Mountains may lead to decreases in biomass and changes in species composition as species migrate upslope. These changes are also likely to be fairly persistent for at least one- to two-hundred years. The results from this study suggest that UVAFME and other individual-based gap models can be used to inform forest management and climate mitigation strategies for this vitally important region.

Cost of preventing workplace heat-related illness through worker breaks and the benefit of climate-change mitigation

NASA Astrophysics Data System (ADS)

Takakura, Jun'ya; Fujimori, Shinichiro; Takahashi, Kiyoshi; Hijioka, Yasuaki; Hasegawa, Tomoko; Honda, Yasushi; Masui, Toshihiko

2017-06-01

The exposure of workers to hot environments is expected to increase as a result of climate change. In order to prevent heat-related illness, it is recommended that workers take breaks during working hours. However, this would lead to reductions in worktime and labor productivity. In this study, we estimate the economic cost of heat-related illness prevention through worker breaks associated with climate change under a wide range of climatic and socioeconomic conditions. We calculate the worktime reduction based on the recommendation of work/rest ratio and the estimated future wet bulb glove temperature, which is an index of heat stresses. Corresponding GDP losses (cost of heat-related illness prevention through worker breaks) are estimated using a computable general equilibrium model throughout this century. Under the highest emission scenario, GDP losses in 2100 will range from 2.6 to 4.0% compared to the current climate conditions. On the other hand, GDP losses will be less than 0.5% if the 2.0 °C goal is achieved. The benefit of climate-change mitigation for avoiding worktime loss is comparable to the cost of mitigation (cost of the greenhouse gas emission reduction) under the 2.0 °C goal. The relationship between the cost of heat-related illness prevention through worker breaks and global average temperature rise is approximately linear, and the difference in economic loss between the 1.5 °C goal and the 2.0 °C goal is expected to be approximately 0.3% of global GDP in 2100. Although climate mitigation and socioeconomic development can limit the vulnerable regions and sectors, particularly in developing countries, outdoor work is still expected to be affected. The effectiveness of some adaptation measures such as additional installation of air conditioning devices or shifting the time of day for working are also suggested. In order to reduce the economic impacts, adaptation measures should also be implemented as well as pursing ambitious climate change mitigation targets.

Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems

USGS Publications Warehouse

Cloern, James E.; Abreu, Paulo C.; Carstensen, Jacob; Chauvaud, Laurent; Elmgren, Ragnar; Grall, Jacques; Greening, Holly; Johansson, John O.R.; Kahru, Mati; Sherwood, Edward T.; Xu, Jie; Yin, Kedong

2016-01-01

Time series of environmental measurements are essential for detecting, measuring and understanding changes in the Earth system and its biological communities. Observational series have accumulated over the past 2–5 decades from measurements across the world's estuaries, bays, lagoons, inland seas and shelf waters influenced by runoff. We synthesize information contained in these time series to develop a global view of changes occurring in marine systems influenced by connectivity to land. Our review is organized around four themes: (i) human activities as drivers of change; (ii) variability of the climate system as a driver of change; (iii) successes, disappointments and challenges of managing change at the sea-land interface; and (iv) discoveries made from observations over time. Multidecadal time series reveal that many of the world's estuarine–coastal ecosystems are in a continuing state of change, and the pace of change is faster than we could have imagined a decade ago. Some have been transformed into novel ecosystems with habitats, biogeochemistry and biological communities outside the natural range of variability. Change takes many forms including linear and nonlinear trends, abrupt state changes and oscillations. The challenge of managing change is daunting in the coastal zone where diverse human pressures are concentrated and intersect with different responses to climate variability over land and over ocean basins. The pace of change in estuarine–coastal ecosystems will likely accelerate as the human population and economies continue to grow and as global climate change accelerates. Wise stewardship of the resources upon which we depend is critically dependent upon a continuing flow of information from observations to measure, understand and anticipate future changes along the world's coastlines.

A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

PubMed Central

Liu, Junguo; Folberth, Christian; Yang, Hong; Röckström, Johan; Abbaspour, Karim; Zehnder, Alexander J. B.

2013-01-01

Food security and water scarcity have become two major concerns for future human's sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security. PMID:23460901

Intercomparison of the capabilities of simplified climate models to project the effects of aviation CO2 on climate

NASA Astrophysics Data System (ADS)

Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.

2013-08-01

This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less

Climate reconstruction from borehole temperatures influenced by groundwater flow

NASA Astrophysics Data System (ADS)

Kurylyk, B.; Irvine, D. J.; Tang, W.; Carey, S. K.; Ferguson, G. A. G.; Beltrami, H.; Bense, V.; McKenzie, J. M.; Taniguchi, M.

2017-12-01

Borehole climatology offers advantages over other climate reconstruction methods because further calibration steps are not required and heat is a ubiquitous subsurface property that can be measured from terrestrial boreholes. The basic theory underlying borehole climatology is that past surface air temperature signals are reflected in the ground surface temperature history and archived in subsurface temperature-depth profiles. High frequency surface temperature signals are attenuated in the shallow subsurface, whereas low frequency signals can be propagated to great depths. A limitation of analytical techniques to reconstruct climate signals from temperature profiles is that they generally require that heat flow be limited to conduction. Advection due to groundwater flow can thermally `contaminate' boreholes and result in temperature profiles being rejected for regional climate reconstructions. Although groundwater flow and climate change can result in contrasting or superimposed thermal disturbances, groundwater flow will not typically remove climate change signals in a subsurface thermal profile. Thus, climate reconstruction is still possible in the presence of groundwater flow if heat advection is accommodated in the conceptual and mathematical models. In this study, we derive a new analytical solution for reconstructing surface temperature history from borehole thermal profiles influenced by vertical groundwater flow. The boundary condition for the solution is composed of any number of sequential `ramps', i.e. periods with linear warming or cooling rates, during the instrumented and pre-observational periods. The boundary condition generation and analytical temperature modeling is conducted in a simple computer program. The method is applied to reconstruct climate in Winnipeg, Canada and Tokyo, Japan using temperature profiles recorded in hydrogeologically active environments. The results demonstrate that thermal disturbances due to groundwater flow and climate change must be considered in a holistic manner as opposed to isolating either perturbation as was done in prior analytical studies.

Generalized Dissimilarity Modeling of Late-Quaternary Variations in Pollen-Based Compositional Dissimilarity

NASA Astrophysics Data System (ADS)

Williams, J. W.; Blois, J.; Ferrier, S.; Manion, G.; Fitzpatrick, M.; Veloz, S.; He, F.; Liu, Z.; Otto-Bliesner, B. L.

2011-12-01

In Quaternary paleoecology and paleoclimatology, compositionally dissimilar fossil assemblages usually indicate dissimilar environments; this relationship underpins assemblage-level techniques for paleoenvironmental reconstruction such as mutual climatic ranges or the modern analog technique. However, there has been relatively little investigation into the form of the relationship between compositional dissimilarity and climatic dissimilarity. Here we apply generalized dissimilarity modeling (GDM; Ferrier et al. 2007) as a tool for modeling the expected non-linear relationships between compositional and climatic dissimilarity. We use the CCSM3.0 transient paleoclimatic simulations from the SynTrace working group (Liu et al. 2009) and a new generation of fossil pollen maps from eastern North America (Blois et al. 2011) to 1) assess the spatial relationships between compositional dissimilarity and climatic dissimilarity and 2) whether these spatial relationships change over time. We used a taxonomic list of 106 genus-level pollen types, six climatic variables (winter precipitation and mean temperature, summer precipitation and temperature, seasonality of precipitation, and seasonality of temperature) that were chosen to minimize collinearity, and a cross-referenced pollen and climate dataset mapped for time slices spaced 1000 years apart. When GDM was trained for one time slice, the correlation between predicted and observed spatial patterns of community dissimilarity for other times ranged between 0.3 and 0.73. The selection of climatic predictor variables changed over time, as did the form of the relationship between compositional turnover and climatic predictors. Summer temperature was the only variable selected for all time periods. These results thus suggest that the relationship between compositional dissimilarity in pollen assemblages (and, by implication, beta diversity in plant communities) and climatic dissimilarity can change over time, for reasons to be further studied.

Transient Earth system responses to cumulative carbon dioxide emissions: linearities, uncertainties, and probabilities in an observation-constrained model ensemble

NASA Astrophysics Data System (ADS)

Steinacher, M.; Joos, F.

2016-02-01

Information on the relationship between cumulative fossil CO2 emissions and multiple climate targets is essential to design emission mitigation and climate adaptation strategies. In this study, the transient response of a climate or environmental variable per trillion tonnes of CO2 emissions, termed TRE, is quantified for a set of impact-relevant climate variables and from a large set of multi-forcing scenarios extended to year 2300 towards stabilization. An ˜ 1000-member ensemble of the Bern3D-LPJ carbon-climate model is applied and model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte Carlo-type framework. Uncertainties in TRE estimates include both scenario uncertainty and model response uncertainty. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.9 °C (68 % confidence interval (c.i.): 1.3 to 2.7 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and a steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic meridional overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The constrained model ensemble is also applied to determine the response to a pulse-like emission and in idealized CO2-only simulations. The transient climate response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the equilibrium climate sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed

Fisichelli, Nicholas A; Schuurman, Gregor W; Monahan, William B; Ziesler, Pamela S

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979-2013) at 340 parks and projected potential future visitation (2041-2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67-77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8-23%) and expansion of the visitation season at individual parks (13-31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation.

Protected Area Tourism in a Changing Climate: Will Visitation at US National Parks Warm Up or Overheat?

PubMed Central

Fisichelli, Nicholas A.; Schuurman, Gregor W.; Monahan, William B.; Ziesler, Pamela S.

2015-01-01

Climate change will affect not only natural and cultural resources within protected areas but also tourism and visitation patterns. The U.S. National Park Service systematically collects data regarding its 270+ million annual recreation visits, and therefore provides an opportunity to examine how human visitation may respond to climate change from the tropics to the polar regions. To assess the relationship between climate and park visitation, we evaluated historical monthly mean air temperature and visitation data (1979–2013) at 340 parks and projected potential future visitation (2041–2060) based on two warming-climate scenarios and two visitation-growth scenarios. For the entire park system a third-order polynomial temperature model explained 69% of the variation in historical visitation trends. Visitation generally increased with increasing average monthly temperature, but decreased strongly with temperatures > 25°C. Linear to polynomial monthly temperature models also explained historical visitation at individual parks (R2 0.12-0.99, mean = 0.79, median = 0.87). Future visitation at almost all parks (95%) may change based on historical temperature, historical visitation, and future temperature projections. Warming-mediated increases in potential visitation are projected for most months in most parks (67–77% of months; range across future scenarios), resulting in future increases in total annual visits across the park system (8–23%) and expansion of the visitation season at individual parks (13–31 days). Although very warm months at some parks may see decreases in future visitation, this potential change represents a relatively small proportion of visitation across the national park system. A changing climate is likely to have cascading and complex effects on protected area visitation, management, and local economies. Results suggest that protected areas and neighboring communities that develop adaptation strategies for these changes may be able to both capitalize on opportunities and minimize detriment related to changing visitation. PMID:26083361

Long-term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover

PubMed Central

Liang, Yuting; Jiang, Yuji; Wang, Feng; Wen, Chongqing; Deng, Ye; Xue, Kai; Qin, Yujia; Yang, Yunfeng; Wu, Liyou; Zhou, Jizhong; Sun, Bo

2015-01-01

To understand soil microbial community stability and temporal turnover in response to climate change, a long-term soil transplant experiment was conducted in three agricultural experiment stations over large transects from a warm temperate zone (Fengqiu station in central China) to a subtropical zone (Yingtan station in southern China) and a cold temperate zone (Hailun station in northern China). Annual soil samples were collected from these three stations from 2005 to 2011, and microbial communities were analyzed by sequencing microbial 16S ribosomal RNA gene amplicons using Illumina MiSeq technology. Our results revealed a distinctly differential pattern of microbial communities in both northward and southward transplantations, along with an increase in microbial richness with climate cooling and a corresponding decrease with climate warming. The microbial succession rate was estimated by the slope (w value) of linear regression of a log-transformed microbial community similarity with time (time–decay relationship). Compared with the low turnover rate of microbial communities in situ (w=0.046, P<0.001), the succession rate at the community level was significantly higher in the northward transplant (w=0.058, P<0.001) and highest in the southward transplant (w=0.094, P<0.001). Climate warming lead to a faster succession rate of microbial communities as well as lower species richness and compositional changes compared with in situ and climate cooling, which may be related to the high metabolic rates and intense competition under higher temperature. This study provides new insights into the impacts of climate change on the fundamental temporal scaling of soil microbial communities and microbial phylogenetic biodiversity. PMID:25989371

Low degree Earth's gravity coefficients determined from different space geodetic observations and climate models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

2017-04-01

Large scale mass redistribution and its transport within the Earth system causes changes in the Earth's rotation in space, gravity field and Earth's ellipsoid shape. These changes are observed in the ΔC21, ΔS21, and ΔC20 spherical harmonics gravity coefficients, which are proportional to the mass load-induced Earth rotational excitations. In this study, linear trend, decadal, inter-annual, and seasonal variations of low degree spherical harmonics coefficients of Earth's gravity field, determined from different space geodetic techniques, Gravity Recovery and Climate Experiment (GRACE), satellite laser ranging (SLR), Global Navigation Satellite System (GNSS), Earth rotation, and climate models, are examined. In this way, the contribution of each measurement technique to interpreting the low degree surface mass density of the Earth is shown. Especially, we evaluate an usefulness of several climate models from the Coupled Model Intercomparison Project phase 5 (CMIP5) to determine the low degree Earth's gravity coefficients using GRACE satellite observations. To do that, Terrestrial Water Storage (TWS) changes from several CMIP5 climate models are determined and then these simulated data are compared with the GRACE observations. Spherical harmonics ΔC21, ΔS21, and ΔC20 changes are calculated as the sum of atmosphere and ocean mass effect (GAC values) taken from GRACE and a land surface hydrological estimate from the selected CMIP5 climate models. Low degree Stokes coefficients of the surface mass density determined from GRACE, SLR, GNSS, Earth rotation measurements and climate models are compared to each other in order to assess their consistency. The comparison is done by using different types of statistical and signal processing methods.

The Impact of Climate Change on the Potential Distribution of Agricultural Pests: The Case of the Coffee White Stem Borer (Monochamus leuconotus P.) in Zimbabwe

PubMed Central

Kutywayo, Dumisani; Chemura, Abel; Kusena, Winmore; Chidoko, Pardon; Mahoya, Caleb

2013-01-01

The production of agricultural commodities faces increased risk of pests, diseases and other stresses due to climate change and variability. This study assesses the potential distribution of agricultural pests under projected climatic scenarios using evidence from the African coffee white stem borer (CWB), Monochamus leuconotus (Pascoe) (Coleoptera: Cerambycidae), an important pest of coffee in Zimbabwe. A species distribution modeling approach utilising Boosted Regression Trees (BRT) and Generalized Linear Models (GLM) was applied on current and projected climate data obtained from the WorldClim database and occurrence data (presence and absence) collected through on-farm biological surveys in Chipinge, Chimanimani, Mutare and Mutasa districts in Zimbabwe. Results from both the BRT and GLM indicate that precipitation-related variables are more important in determining species range for the CWB than temperature related variables. The CWB has extensive potential habitats in all coffee areas with Mutasa district having the largest model average area suitable for CWB under current and projected climatic conditions. Habitat ranges for CWB will increase under future climate scenarios for Chipinge, Chimanimani and Mutare districts while it will decrease in Mutasa district. The highest percentage change in area suitable for the CWB was for Chimanimani district with a model average of 49.1% (3 906 ha) increase in CWB range by 2080. The BRT and GLM predictions gave similar predicted ranges for Chipinge, Chimanimani and Mutasa districts compared to the high variation in current and projected habitat area for CWB in Mutare district. The study concludes that suitable area for CWB will increase significantly in Zimbabwe due to climate change and there is need to develop adaptation mechanisms. PMID:24014222

Assessing distributions of two invasive species of contrasting habits in future climate.

PubMed

Panda, Rajendra Mohan; Behera, Mukunda Dev; Roy, Partha Sarathi

2018-05-01

Understanding the impact of climate change on species invasion is crucial for sustainable biodiversity conservation. Through this study, we try to answer how species differing in phenological cycles, specifically Cassia tora and Lantana camara, differ in the manner in which they invade new regions in India in the future climate. Since both species occupy identical niches, exploring their invasive potential in different climate change scenarios will offer critical insights into invasion and inform ecosystem management. We use three modelling protocols (i.e., maximum entropy, generalised linear model and generalised additive model) to predict the current distribution. Projections are made for both moderate (A1B) and extreme (A2) IPCC (Intergovernmental Panel on Climate Change) scenarios for the year 2050 and 2100. The study reveals that the distributions of C. tora (annual) and L. camara (perennial) would depend on the precipitation of the warmest quarter and moisture availability. C. tora may demonstrate physiological tolerance to the mean diurnal temperature range and L. camara to the solar radiation. C. tora may invade central India, while L. camara may invade the Western Himalaya, parts of the Eastern Himalaya and the Western Ghats. The distribution ranges of both species could shift in the northern and north-eastern directions in India, owing to changes in moisture availability. The possible alterations in precipitation regimes could lead to water stress, which might have cascading effects on species invasion. L. camara might adapt to climate change better compared with C. tora. This comparative analysis of the future distributions of two invasive plants with contrasting habits demonstrates that temporal complementarity would prevail over the competition. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Mapping of the Land Cover Spatiotemporal Characteristics in Northern Russia Caused by Climate Change

NASA Astrophysics Data System (ADS)

Panidi, E.; Tsepelev, V.; Torlopova, N.; Bobkov, A.

2016-06-01

The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.

Estimating future burned areas under changing climate in the EU-Mediterranean countries.

PubMed

Amatulli, Giuseppe; Camia, Andrea; San-Miguel-Ayanz, Jesús

2013-04-15

The impacts of climate change on forest fires have received increased attention in recent years at both continental and local scales. It is widely recognized that weather plays a key role in extreme fire situations. It is therefore of great interest to analyze projected changes in fire danger under climate change scenarios and to assess the consequent impacts of forest fires. In this study we estimated burned areas in the European Mediterranean (EU-Med) countries under past and future climate conditions. Historical (1985-2004) monthly burned areas in EU-Med countries were modeled by using the Canadian Fire Weather Index (CFWI). Monthly averages of the CFWI sub-indices were used as explanatory variables to estimate the monthly burned areas in each of the five most affected countries in Europe using three different modeling approaches (Multiple Linear Regression - MLR, Random Forest - RF, Multivariate Adaptive Regression Splines - MARS). MARS outperformed the other methods. Regression equations and significant coefficients of determination were obtained, although there were noticeable differences from country to country. Climatic conditions at the end of the 21st Century were simulated using results from the runs of the regional climate model HIRHAM in the European project PRUDENCE, considering two IPCC SRES scenarios (A2-B2). The MARS models were applied to both scenarios resulting in projected burned areas in each country and in the EU-Med region. Results showed that significant increases, 66% and 140% of the total burned area, can be expected in the EU-Med region under the A2 and B2 scenarios, respectively. Copyright © 2013 Elsevier B.V. All rights reserved.

Modelled non-linear response to climate of Hardangerjøkulen ice cap, southern Norway, since the mid-Holocene

NASA Astrophysics Data System (ADS)

Åkesson, Henning; Nisancioglu, Kerim H.; Giesen, Rianne H.; Morlighem, Mathieu

2016-04-01

Glacier and ice cap volume changes currently amount to half of the total cryospheric contribution to sea-level rise and are projected to remain substantial throughout the 21st century. To simulate glacier behavior on centennial and longer time scales, models rely on simplified dynamics and tunable parameters for processes not well understood. Model calibration is often done using present-day observations, even though the relationship between parameters and parametrized processes may be altered for significantly different glacier states. In this study, we simulate the Hardangerjøkulen ice cap in southern Norway since the mid-Holocene, through the Little Ice Age (LIA) and into the future. We run an ensemble for both calibration and transient experiments, using a two-dimensional ice flow model with mesh refinement. For the Holocene, we apply a simple mass balance forcing based on climate reconstructions. For the LIA until 1962, we use geomorphological evidence and measured outlet glacier positions to find a mass balance history, while we use direct mass balance measurements from 1963 until today. Given a linear climate forcing, we show that Hardangerøkulen grew from ice-free conditions in the mid-Holocene, to its maximum LIA extent in a highly non-linear fashion. We relate this to local bed topography and demonstrate that volume and area of some but not all outlet glaciers, as well as the entire ice cap, become decoupled for several centuries during our simulation of the late Holocene, before co-varying approaching the LIA. Our model is able to simulate most recorded ice cap and outlet glacier changes from the LIA until today. We show that present-day Hardangerøkulen is highly sensitive to mass balance changes, and estimate that the ice cap will melt completely by the year 2100.

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.

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

Path Dependence of Regional Climate Change

NASA Astrophysics Data System (ADS)

Herrington, Tyler; Zickfeld, Kirsten

2013-04-01

Path dependence of the climate response to CO2 forcing has been investigated from a global mean perspective, with evidence suggesting that long-term global mean temperature and precipitation changes are proportional to cumulative CO2 emissions, and independent of emissions pathway. Little research, however, has been done on path dependence of regional climate changes, particularly in areas that could be affected by tipping points. Here, we utilize the UVic Earth System Climate Model version 2.9, an Earth System Model of Intermediate Complexity. It consists of a 3-dimensional ocean general circulation model, coupled with a dynamic-thermodynamic sea ice model, and a thermodynamic energy-moisture balance model of the atmosphere. This is then coupled with a terrestrial carbon cycle model and an ocean carbon-cycle model containing an inorganic carbon and marine ecosystem component. Model coverage is global with a zonal resolution of 3.6 degrees and meridional resolution of 1.8 degrees. The model is forced with idealized emissions scenarios across five cumulative emission groups (1300 GtC, 2300 GtC, 3300 GtC, 4300 GtC, and 5300 GtC) to explore the path dependence of (and the possibility of hysteresis in) regional climate changes. Emission curves include both fossil carbon emissions and emissions from land use changes, and span a variety of peak and decline scenarios with varying emission rates, as well as overshoot and instantaneous pulse scenarios. Tipping points being explored include those responsible for the disappearance of summer Arctic sea-ice, the irreversible melt of the Greenland Ice Sheet, the collapse of the Atlantic Thermohaline Circulation, and the dieback of the Amazonian Rainforest. Preliminary results suggest that global mean climate change after cessation of CO2 emissions is independent of the emissions pathway, only varying with total cumulative emissions, in accordance with results from earlier studies. Forthcoming analysis will investigate path dependence of regional climate change. Some evidence exists to support the idea of hysteresis in the Greenland Ice Sheet, and since tipping points represent non-linear elements of the climate system, we suspect that the other tipping points might also show path dependence.

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

Nile Basin Vegetation Response and Vulnerability to Climate Change: A Multi-Sensor Remote Sensing Approach

NASA Astrophysics Data System (ADS)

Yitayew, M.; Didan, K.; Barreto-munoz, A.

2013-12-01

The Nile Basin is one of the world's water resources hotspot that is home to over 437 million people in ten riparian countries with 54% or 238 millions live directly within the basin. The basin like all other basins of the world is facing water resources challenges exacerbated by climate change and increased demand. Nowadays any water resource management action in the basin has to assess the impacts of climate change to be able to predict future water supply and also to help in the negotiation process. Presently, there is a lack of basin wide weather networks to understand sensitivity of the vegetation cover to the impacts of climate change. Vegetation plays major economic and ecological functions in the basin and provides key services ranging from pastoralism, agricultural production, firewood, habitat and food sources for the rich wildlife, as well as a major role in the carbon cycle and climate regulation of the region. Under the threat of climate change and the incessant anthropogenic pressure the distribution and services of the region's ecosystems are projected to change The goal of this work is to assess and characterize how the basin vegetation productivity, distribution, and phenology have changed over the last 30+ years and what are the key climatic drivers of this change. This work makes use of a newly generated multi-sensor long-term land surface data set about vegetation and phenology. Vegetation indices derived from remotely sensed surface reflectance data are commonly used to characterize phenology or vegetation dynamics accurately and with enough spatial and temporal resolution to support change detection. We used more than 30 years of vegetation index and growing season data from AVHRR and MODIS sensors compiled by the Vegetation Index and Phenology laboratory (VIP LAB) at the University of Arizona. Available climate data about precipitation and temperature for the corresponding 30 years period is also used for this analysis. We looked at the changes in the vegetation index signal and to a lesser degree the change in land cover and land use over the last 30 years. Using the climate data record we looked at the drivers of this change. The sensitivity of the basin to climate change was assessed using the multi-linear regression analysis on the covariance of the change in key phenology parameters and the two climate drivers considered here. The overall response was very complex owing to the complicated climate regime and topography of the region. Vegetation response was mostly stable in high lands with a slightly decreasing trend over low and mid-elevations. Over the same period we also observed an intensification of agriculture production corresponding to an increase in percent cover and productivity. We also observed a decrease in forest cover associated with land use conversion. These changes were mostly driven by the precipitation regimes with little impact of the temperature. Climate models project an eventual decrease in precipitation and increase in temperature over the basin. Coupled with these results and observations these projected changes point to major challenges to the vegetation cover, productivity, and associated ecosystem services of the Nile basin.

Climatic effects of large-scale deforestation in Earth System Models

NASA Astrophysics Data System (ADS)

Brovkin, V.; Boysen, L.; Pongratz, J.

2017-12-01

Processes in terrestrial ecosystems, to a large extent, are controlled by climate and CO2 concentration. In turn, geographical distribution of vegetation cover strongly affects heat, moisture, and momentum fluxes between land surface and atmosphere (biogeophysical effects). Anthropogenic land use and land cover changes (LULCC) are now included into Earth System Models (ESMs) in the form of historical and hypothetical future scenarios as a forcing in the Coupled Model Intercomparison project, phase 6 (CMIP6). A propagation of climatic effects from land to the ocean in ESMs allows to investigate a global climate response to LULCC in addition to analysis of local effects over deforested land. One complication in the analysis of global climatic effects of historical and future LULCC scenarios is their relatively small amplitude. To increase the signal-to-noise ratio, the Land Use Model Intercomparison Project (LUMIP) suggested an idealized deforestation simulation following a prototype of 1%-CO2 increase experiment commonly used in CMIPs. The idealized experiment allows to investigate - in a harmonized way across models - a response of land surface biophysics and climate to a large-scale deforestation of 20 million km2 distributed over the most forested parts of globe. The forest is removed linearly over a period of 50 years, with an additional 30 years with no specified change in forest cover. Boundary conditions such as CO2 concentration and other forcings are kept at the pre-industrial level. We will present results of idealized deforestation experiments and other sensitivity runs with the CMIP6-version of MPI-ESM, which will be part of the later multi-model comparison. A special focus will be put on less well investigated aspects of LULCC that the idealized setup is particularly well suited for studying, such as non-linearities of the model response to the deforestation forcing and detectability of the signal over time.

Interactive Photochemistry in Earth System Models to Assess Uncertainty in Ozone and Greenhouse Gases. Final report

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

Prather, Michael J.; Hsu, Juno; Nicolau, Alex

Atmospheric chemistry controls the abundances and hence climate forcing of important greenhouse gases including N 2O, CH 4, HFCs, CFCs, and O 3. Attributing climate change to human activities requires, at a minimum, accurate models of the chemistry and circulation of the atmosphere that relate emissions to abundances. This DOE-funded research provided realistic, yet computationally optimized and affordable, photochemical modules to the Community Earth System Model (CESM) that augment the CESM capability to explore the uncertainty in future stratospheric-tropospheric ozone, stratospheric circulation, and thus the lifetimes of chemically controlled greenhouse gases from climate simulations. To this end, we have successfullymore » implemented Fast-J (radiation algorithm determining key chemical photolysis rates) and Linoz v3.0 (linearized photochemistry for interactive O 3, N 2O, NO y and CH 4) packages in LLNL-CESM and for the first time demonstrated how change in O2 photolysis rate within its uncertainty range can significantly impact on the stratospheric climate and ozone abundances. From the UCI side, this proposal also helped LLNL develop a CAM-Superfast Chemistry model that was implemented for the IPCC AR5 and contributed chemical-climate simulations to CMIP5.« less

Climate Change and Algal Blooms =

NASA Astrophysics Data System (ADS)

Lin, Shengpan

Algal blooms are new emerging hazards that have had important social impacts in recent years. However, it was not very clear whether future climate change causing warming waters and stronger storm events would exacerbate the algal bloom problem. The goal of this dissertation was to evaluate the sensitivity of algal biomass to climate change in the continental United States. Long-term large-scale observations of algal biomass in inland lakes are challenging, but are necessary to relate climate change to algal blooms. To get observations at this scale, this dissertation applied machine-learning algorithms including boosted regression trees (BRT) in remote sensing of chlorophyll-a with Landsat TM/ETM+. The results show that the BRT algorithm improved model accuracy by 15%, compared to traditional linear regression. The remote sensing model explained 46% of the total variance of the ground-measured chlorophyll- a in the first National Lake Assessment conducted by the US Environmental Protection Agency. That accuracy was ecologically meaningful to study climate change impacts on algal blooms. Moreover, the BRT algorithm for chlorophyll- a would not have systematic bias that is introduced by sediments and colored dissolved organic matter, both of which might change concurrently with climate change and algal blooms. This dissertation shows that the existing atmospheric corrections for Landsat TM/ETM+ imagery might not be good enough to improve the remote sensing of chlorophyll-a in inland lakes. After deriving long-term algal biomass estimates from Landsat TM/ETM+, time series analysis was used to study the relations of climate change and algal biomass in four Missouri reservoirs. The results show that neither temperature nor precipitation was the only factor that controlled temporal variation of algal biomass. Different reservoirs, even different zones within the same reservoir, responded differently to temperature and precipitation changes. These findings were further tested in 1157 lakes across the continental United States. The results show that mean annual algal biomass generally increased with annual temperature. Greater increase was found in lakes with more nutrients. Mean annual algal biomass generally decreased with annual total precipitation. In both the "low" and the "high" greenhouse-gas emission scenarios, mean annual algal biomass in lakes generally increased with climate change, and greater increases are predicted from the high emission scenario.

Variation in skin biology to climate in Shanghai, China.

PubMed

Liu, Xiaoping; Gao, Yanrui; Zhang, Yiyi; Wang, Xuemin

2017-09-01

To explore the relationship between climate and skin condition, and to investigate the variation of skin biology to climatic change. In total, 2005 healthy Chinese volunteers living in Shanghai (aged 13-69 years) were recruited. Transepidermal water loss (TEWL) and SCH were tested on six sites (forehead, cheek, nasolabial, inner forearm, dorsal hand, and palm) by noninvasive devices between January 2005 and December 2012. The corresponding climate data were recorded by local Weather Bureau. TEWL was increased with atmospheric pressure and decreased with temperature, steam pressure, and relative humidity (p < 0.05). SCH was increased with steam pressure and decreased with atmospheric pressure (p < 0.05); there was no obvious trend between SCH and temperature and SCH and relative humidity. To investigate the climate parameters together, we introduced these correlated factors into the multivariate linear regression model which demonstrated that temperature and steam pressure were main factors related to skin biological parameters. At different sites, the effect of climatic factors on skin biology was diverse. Skin biological parameters are associated with climatic factors. Different sites have different sensitivity to climate factors.

GRACE storage-runoff hystereses reveal the dynamics of ...

EPA Pesticide Factsheets

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. However, there is a poor understanding of these processes at the regional scale—primarily because of our inability to measure water stores and fluxes in the subsurface. Now NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites quantify changes in the amount of water stored across and through the Earth, providing measurements of regional hydrologic behavior. Here we apply GRACE data to characterize for the first time how regional watersheds function as simple, dynamic systems through a series of hysteresis loops. While the physical processes underlying the loops are inherently complex, the vertical integration of terrestrial water in the GRACE signal provides process-based insights into the dynamic and non-linear function of regional-scale watersheds. We use this process-based understanding with GRACE data to effectively forecast seasonal runoff (mean R2 of 0.91) and monthly runoff (mean R2 of 0.77) in three regional-scale watersheds (>150,000 km2) of the Columbia River Basin, USA. Data from the Gravity Recovery and Climate Experiment (GRACE) satellites provide a novel dataset for understanding changes in the amount of water stored across and through the surface of the Ear

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.

Influence of climate and eolian dust on the major-element chemistry and clay mineralogy of soils in the northern Bighorn basin, U.S.A.

USGS Publications Warehouse

Reheis, M.C.

1990-01-01

Soil chronosequences in the northern Bighorn basin permit the study of chronologic changes in the major-element chemistry and clay mineralogy of soils formed in different climates. Two chronosequences along Rock Creek in south-central Montana formed on granitic alluvium in humid and semiarid climates over the past two million years. A chronosequence at the Kane fans in north-central Wyoming formed on calcareous alluvium in an arid climate over the past 600,000 years. Detailed analyses of elemental chemistry indicate that the soils in all three areas gradually incorporated eolian dust that contained less zirconium, considered to be chemically immobile during weathering, than did the alluvium. B and C horizons of soils in the wettest of the chronosequences developed mainly at logarithmic rates, suggesting that leaching, initially rapid but decelerating, dominated the dust additions. In contrast, soils in the most arid of the chronosequences developed at linear rates that reflect progressive dust additions that were little affected by leaching. Both weathering and erosion may cause changes with time to appear logarithmic in A horizons of soils under the moist and semiarid climatic regimes. Clay minerals form with time in the basal B and C horizons and reflect climatic differences in the three areas. Vermiculite, mixed-layer illite-smectite, and smectite form in the soils of the moist-climate chronosequence; smectite forms in the semiarid-climate chronosequence; and smectite and palygorskite form in the arid-climate chronosequence. ?? 1990.

Regional modeling of large wildfires under current and potential future climates in Colorado and Wyoming, USA

USGS Publications Warehouse

West, Amanda; Kumar, Sunil; Jarnevich, Catherine S.

2016-01-01

Regional analysis of large wildfire potential given climate change scenarios is crucial to understanding areas most at risk in the future, yet wildfire models are not often developed and tested at this spatial scale. We fit three historical climate suitability models for large wildfires (i.e. ≥ 400 ha) in Colorado andWyoming using topography and decadal climate averages corresponding to wildfire occurrence at the same temporal scale. The historical models classified points of known large wildfire occurrence with high accuracies. Using a novel approach in wildfire modeling, we applied the historical models to independent climate and wildfire datasets, and the resulting sensitivities were 0.75, 0.81, and 0.83 for Maxent, Generalized Linear, and Multivariate Adaptive Regression Splines, respectively. We projected the historic models into future climate space using data from 15 global circulation models and two representative concentration pathway scenarios. Maps from these geospatial analyses can be used to evaluate the changing spatial distribution of climate suitability of large wildfires in these states. April relative humidity was the most important covariate in all models, providing insight to the climate space of large wildfires in this region. These methods incorporate monthly and seasonal climate averages at a spatial resolution relevant to land management (i.e. 1 km2) and provide a tool that can be modified for other regions of North America, or adapted for other parts of the world.

A growing degree-day model for determination of Fasciola hepatica infection risk in New Zealand with future predictions using climate change models.

PubMed

Haydock, L A J; Pomroy, W E; Stevenson, M A; Lawrence, K E

2016-09-15

Infections of ruminants with Fasciola hepatica are considered to be of regional importance within New Zealand but there is very little recent information on its prevalence or severity other than anecdotal reports. Generally they are considered to be of secondary importance compared to gastrointestinal nematode infections. Utilizing data from Virtual Climate Stations (n=11491) distributed on a 5km grid around New Zealand a growing degree-day model was used to describe the risk of infection with liver fluke from 1972 to 2012 and then to apply the predictions to estimate the risk of fluke infections within New Zealand for the years 2040 and 2090. The growing degree-day model was validated against the most recent survey of infection within New Zealand in 1984. A strong positive linear relationship for 1984 between F. hepatica prevalence in lambs and infection risk (p<0.001; R 2 =0.71) was found indicating the model was effective for New Zealand. A linear regression for risk values from 14 regions in New Zealand for 1972-2012 did not show any discernible change in risk of infection over this time period (p>0.05). Post-hoc comparisons indicate the risk in Westland was found to be substantially higher (p<0.05) than all other regions with Northland ranked second highest. Notable predicted changes in F. hepatica infection risk in 2040 and 2090 were detected although they did vary between different climate change scenarios. The highest average percentage changes in infection risk were found in regions with low initial risk values such as Canterbury and Otago; in these regions 2090 infection risk is expected to rise by an average of 186% and 184%, respectively. Despite the already high levels of infection risk in Westland, values are expected to rise by a further 76% by 2090. The model does show some areas with little change with Taranaki predicted to experience only very minor increases in infection risk with average 2040 and 2090 predicted changes of 0% and 29%, respectively. Overall, these results suggest the significance of F. hepatica in New Zealand farming systems is probably underestimated and that this risk will generally increase with global warming following climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of climate change on water quality in the Yaquina ...

EPA Pesticide Factsheets

As part of a larger study to examine the effect of climate change (CC) on estuarine resources, we simulated the effect of rising sea level, alterations in river discharge, and increasing atmospheric temperatures on water quality in the Yaquina Estuary. Due to uncertainty in the effects of climate change, initial model simulations were performed for different steady river discharge rates that span the historical range in inflow, and for a range of increases in sea level and atmospheric temperature. Model simulations suggest that in the central portion of the estuary (19 km from mouth), a 60-cm increase in sea level will result in a 2-3 psu change in salinity across a broad range of river discharges. For the oligohaline portion of the estuary, salinity increases associated with a rise in sea level of 60 cm are only apparent at low river discharge rates (< 50 m3 s-1). Simulations suggest that the water temperatures near the mouth of the estuary will decrease due to rising sea level, while water temperatures in upriver portions of the estuary will increase due to rising atmospheric temperatures. We present results which demonstrate how the interaction of changes in river discharge, rising sea level, and atmospheric temperature associated with climate change produce non-linear patterns in the response of estuarine salinity and temperature, which vary with location inside the estuary and season. We also will discuss the importance of presenting results in a mann

Equilibrium and Effective Climate Sensitivity

NASA Astrophysics Data System (ADS)

Rugenstein, M.; Bloch-Johnson, J.

2016-12-01

Atmosphere-ocean general circulation models, as well as the real world, take thousands of years to equilibrate to CO2 induced radiative perturbations. Equilibrium climate sensitivity - a fully equilibrated 2xCO2 perturbation - has been used for decades as a benchmark in model intercomparisons, as a test of our understanding of the climate system and paleo proxies, and to predict or project future climate change. Computational costs and limited time lead to the widespread practice of extrapolating equilibrium conditions from just a few decades of coupled simulations. The most common workaround is the "effective climate sensitivity" - defined through an extrapolation of a 150 year abrupt2xCO2 simulation, including the assumption of linear climate feedbacks. The definitions of effective and equilibrium climate sensitivity are often mixed up and used equivalently, and it is argued that "transient climate sensitivity" is the more relevant measure for predicting the next decades. We present an ongoing model intercomparison, the "LongRunMIP", to study century and millennia time scales of AOGCM equilibration and the linearity assumptions around feedback analysis. As a true ensemble of opportunity, there is no protocol and the only condition to participate is a coupled model simulation of any stabilizing scenario simulating more than 1000 years. Many of the submitted simulations took several years to conduct. As of July 2016 the contribution comprises 27 scenario simulations of 13 different models originating from 7 modeling centers, each between 1000 and 6000 years. To contribute, please contact the authors as soon as possible We present preliminary results, discussing differences between effective and equilibrium climate sensitivity, the usefulness of transient climate sensitivity, extrapolation methods, and the state of the coupled climate system close to equilibrium. Caption for the Figure below: Evolution of temperature anomaly and radiative imbalance of 22 simulations with 12 models (color indicates the model). 20 year moving average.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

How Does The Climate Change?

NASA Astrophysics Data System (ADS)

Jones, R. N.

2011-12-01

In 1997, maximum temperature in SE Australia shifted up by 0.8°C at pH0<0.01. Rainfall decreased by 13% in 1997-2010 compared to 1900-1996. Statistically significant shifts also occur in impact indicators: baumé levels in winegrapes shift >21 days earlier from 1998, streamflow records decrease by 30-70% from 1997 and annual mean forest fire danger index increased by 38% from 1997. Despite catastrophic fires killing 178 people in early 2009, the public remains unaware of this large change in their exposure. When regional temperature was separated into internally and externally forced components, the latter component was found to warm in two steps, in 1968-73 and 1997. These dates coincide with shifts in zonal mean temperature (24-44S; Figure 1). Climate model output shows similar step and trend behavior. Tests run on zonal, hemispheric and global mean temperature observations found shifts in all regions. 1997 marks a shift in global temperature of 0.3°C at pH0<0.01. Similar shifts occur in long-term tide gauge records around the globe (e.g., Figure 2) and in ocean heat content. The prevailing paradigm for how climate variables change is signal-noise construct combining a smooth signal with variations caused by internal climate variability. There seems to be no sound theoretical basis for this assumption. On the contrary, complex system behavior would suggest non-linear responses to externally forced change, especially at the regional scale. Some of our most basic assumptions about how climate changes may need to be re-examined.

Are the impacts of land use on warming underestimated in climate policy?

NASA Astrophysics Data System (ADS)

Mahowald, Natalie M.; Ward, Daniel S.; Doney, Scott C.; Hess, Peter G.; Randerson, James T.

2017-09-01

While carbon dioxide emissions from energy use must be the primary target of climate change mitigation efforts, land use and land cover change (LULCC) also represent an important source of climate forcing. In this study we compute time series of global surface temperature change separately for LULCC and non-LULCC sources (primarily fossil fuel burning), and show that because of the extra warming associated with the co-emission of methane and nitrous oxide with LULCC carbon dioxide emissions, and a co-emission of cooling aerosols with non-LULCC emissions of carbon dioxide, the linear relationship between cumulative carbon dioxide emissions and temperature has a two-fold higher slope for LULCC than for non-LULCC activities. Moreover, projections used in the Intergovernmental Panel on Climate Change (IPCC) for the rate of tropical land conversion in the future are relatively low compared to contemporary observations, suggesting that the future projections of land conversion used in the IPCC may underestimate potential impacts of LULCC. By including a ‘business as usual’ future LULCC scenario for tropical deforestation, we find that even if all non-LULCC emissions are switched off in 2015, it is likely that 1.5 °C of warming relative to the preindustrial era will occur by 2100. Thus, policies to reduce LULCC emissions must remain a high priority if we are to achieve the low to medium temperature change targets proposed as a part of the Paris Agreement. Future studies using integrated assessment models and other climate simulations should include more realistic deforestation rates and the integration of policy that would reduce LULCC emissions.

Dissemination of Climate Model Output to the Public and Commercial Sector

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

Robert Stockwell, PhD

2010-09-23

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature andmore » precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).« less

Grasping time scales from galactic life cycles to personal life projects at a linear scale of 1 mm per 100 years

NASA Astrophysics Data System (ADS)

Holm Jacobsen, Bo

2010-05-01

The ambition is to make the citizen (i.e. pupil/student/scholar/voter/journalist/politician) comprehend better and more scientifically all time scales from the lifespan of the universe to the personal life project by a consistent geographical mapping of time at a scale of 1 mm per 100 years. The processes which change earth systems like life, climate, topography and plate tectonics operate at very different timescales. The understanding of these systems is essential not only for students and scholars of earth science but also for pupils, voters and politicians who make decisions of possibly significant consequence to climate and biodiversity not only for our generation but for thousands or even millions of years ahead. With a consistent linear mapping of time to a scale of 1 millimetre per 100 years, historical time (

An Coral Ensemble Approach to Reconstructing Central Pacific Climate Change During the Holocene

NASA Astrophysics Data System (ADS)

Atwood, A. R.; Cobb, K. M.; Grothe, P. R.; Sayani, H. R.; Southon, J. R.; Edwards, R. L.; Deocampo, D.; Chen, T.; Townsend, K. J.; Hagos, M. M.; Chiang, J. C. H.

2016-12-01

The processes that control El Niño-Southern Oscillation (ENSO) variability on long timescales are still poorly understood. As a consequence, limited progress has been made in understanding how ENSO will change under greenhouse gas forcing. The mid-Holocene provides a well-defined target to study the fundamental controls of ENSO variability. A large number of paleo-ENSO records spanning the tropical Pacific indicate that ENSO variability was reduced by as much as 50% between 3000-6000 yr BP, relative to modern times. Dynamical models of ENSO suggest that ENSO properties can shift in response to changes in the tropical Pacific mean state and/or seasonal cycle, but few proxy records can resolve such changes during the interval in question with enough accuracy. While decades of research have demonstrated the fidelity of tropical Pacific coral d18O records to quantify interannual temperature and precipitation anomalies associated with ENSO, substantial mean offsets exist across overlapping coral sequences that have made it difficult to quantify past changes in mean climate. Here, we test a new approach to reconstruct changes in mean climate from coral records using a large ensemble of bulk d18O measurements on radiometrically-dated fossil corals from Christmas Island that span the Holocene. In contrast to the traditional method of high-resolution sampling to reconstruct monthly climate conditions, we implement a bulk approach, which dramatically reduces the analysis time needed to estimate mean coral d18O and enables a large number of corals to be analyzed in the production of an ensemble of mean climate estimates. A pseudo-coral experiment based on simulations with a Linear Inverse Model and a coupled GCM is used to determine the number of bulk coral estimates that are required to resolve a given mean climate perturbation. In addition to these bulk measurements, short transects are sampled at high resolution to constrain changes in the amplitude of the seasonal cycle. We present preliminary results from our joint bulk/high-resolution sampling approach that provide new constraints on changes in mean climate and seasonality in the central equatorial Pacific over the last 6,000 yr BP.

Effects of Climate Change on Range Forage Production in the San Francisco Bay Area

PubMed Central

Chaplin-Kramer, Rebecca; George, Melvin R.

2013-01-01

The San Francisco Bay Area in California, USA is a highly heterogeneous region in climate, topography, and habitats, as well as in its political and economic interests. Successful conservation strategies must consider various current and future competing demands for the land, and should pay special attention to livestock grazing, the dominant non-urban land-use. The main objective of this study was to predict changes in rangeland forage production in response to changes in temperature and precipitation projected by downscaled output from global climate models. Daily temperature and precipitation data generated by four climate models were used as input variables for an existing rangeland forage production model (linear regression) for California’s annual rangelands and projected on 244 12 km x 12 km grid cells for eight Bay Area counties. Climate model projections suggest that forage production in Bay Area rangelands may be enhanced by future conditions in most years, at least in terms of peak standing crop. However, the timing of production is as important as its peak, and altered precipitation patterns could mean delayed germination, resulting in shorter growing seasons and longer periods of inadequate forage quality. An increase in the frequency of extremely dry years also increases the uncertainty of forage availability. These shifts in forage production will affect the economic viability and conservation strategies for rangelands in the San Francisco Bay Area. PMID:23472102

Earlier occurrence and increased explanatory power of climate for the first incidence of potato late blight caused by Phytophthora infestans in Fennoscandia

PubMed Central

Wiik, Lars; Hannukkala, Asko; Andreasson, Erik; Chen, Deliang; Ou, Tinghai; Liljeroth, Erland; Lankinen, Åsa

2017-01-01

Background Late blight (caused by Phytophthora infestans) is a devastating potato disease that has been found to occur earlier in the season over the last decades in Fennoscandia. Up until now the reasons for this change have not been investigated. Possible explanations for this change are climate alterations, changes in potato production or changes in pathogen biology, such as increased fitness or changes in gene flow within P. infestans populations. The first incidence of late blight is of high economic importance since fungicidal applications should be typically applied two weeks before the first signs of late blight and are repeated on average once a week. Methods We use field observations of first incidence of late blight in experimental potato fields from five sites in Sweden and Finland covering a total of 30 years and investigate whether the earlier incidence of late blight can be related to the climate. Results We linked the field data to meteorological data and found that the previous assumption, used in common late blight models, that the disease only develops at relative humidity levels above 90% had to be rejected. Rather than the typically assumed threshold relationship between late blight disease development and relative humidity we found a linear relationship. Our model furthermore showed two distinct responses of late blight to climate. At the beginning of the observation time (in Sweden until the early 90s and in Finland until the 2000s) the link between climate and first incidence was very weak. However, for the remainder of the time period the link was highly significant, indicating a change in the biological properties of the pathogen which could for example be a change in the dominating reproduction mode or a physiological change in the response of the pathogen to climate. Conclusions The study shows that models used in decision support systems need to be checked and re-parametrized regularly to be able to capture changes in pathogen biology. While this study was performed with data from Fennoscandia this new pathogen biology and late blight might spread to (or already be present at) other parts of the world as well. The strong link between climate and first incidence together with the presented model offers a tool to assess late blight incidence in future climates. PMID:28558041

Earlier occurrence and increased explanatory power of climate for the first incidence of potato late blight caused by Phytophthora infestans in Fennoscandia.

PubMed

Lehsten, Veiko; Wiik, Lars; Hannukkala, Asko; Andreasson, Erik; Chen, Deliang; Ou, Tinghai; Liljeroth, Erland; Lankinen, Åsa; Grenville-Briggs, Laura

2017-01-01

Late blight (caused by Phytophthora infestans) is a devastating potato disease that has been found to occur earlier in the season over the last decades in Fennoscandia. Up until now the reasons for this change have not been investigated. Possible explanations for this change are climate alterations, changes in potato production or changes in pathogen biology, such as increased fitness or changes in gene flow within P. infestans populations. The first incidence of late blight is of high economic importance since fungicidal applications should be typically applied two weeks before the first signs of late blight and are repeated on average once a week. We use field observations of first incidence of late blight in experimental potato fields from five sites in Sweden and Finland covering a total of 30 years and investigate whether the earlier incidence of late blight can be related to the climate. We linked the field data to meteorological data and found that the previous assumption, used in common late blight models, that the disease only develops at relative humidity levels above 90% had to be rejected. Rather than the typically assumed threshold relationship between late blight disease development and relative humidity we found a linear relationship. Our model furthermore showed two distinct responses of late blight to climate. At the beginning of the observation time (in Sweden until the early 90s and in Finland until the 2000s) the link between climate and first incidence was very weak. However, for the remainder of the time period the link was highly significant, indicating a change in the biological properties of the pathogen which could for example be a change in the dominating reproduction mode or a physiological change in the response of the pathogen to climate. The study shows that models used in decision support systems need to be checked and re-parametrized regularly to be able to capture changes in pathogen biology. While this study was performed with data from Fennoscandia this new pathogen biology and late blight might spread to (or already be present at) other parts of the world as well. The strong link between climate and first incidence together with the presented model offers a tool to assess late blight incidence in future climates.

Spectrum of 100-kyr glacial cycle: Orbital inclination, not eccentricity

PubMed Central

Muller, Richard A.; MacDonald, Gordon J.

1997-01-01

Spectral analysis of climate data shows a strong narrow peak with period ≈100 kyr, attributed by the Milankovitch theory to changes in the eccentricity of the earth’s orbit. The narrowness of the peak does suggest an astronomical origin; however the shape of the peak is incompatible with both linear and nonlinear models that attribute the cycle to eccentricity or (equivalently) to the envelope of the precession. In contrast, the orbital inclination parameter gives a good match to both the spectrum and bispectrum of the climate data. Extraterrestrial accretion from meteoroids or interplanetary dust is proposed as a mechanism that could link inclination to climate, and experimental tests are described that could prove or disprove this hypothesis. PMID:11607741

Functional Resilience against Climate-Driven Extinctions – Comparing the Functional Diversity of European and North American Tree Floras

PubMed Central

Liebergesell, Mario; Stahl, Ulrike; Freiberg, Martin; Welk, Erik; Kattge, Jens; Cornelissen, J. Hans C.; Peñuelas, Josep

2016-01-01

Future global change scenarios predict a dramatic loss of biodiversity for many regions in the world, potentially reducing the resistance and resilience of ecosystem functions. Once before, during Plio-Pleistocene glaciations, harsher climatic conditions in Europe as compared to North America led to a more depauperate tree flora. Here we hypothesize that this climate driven species loss has also reduced functional diversity in Europe as compared to North America. We used variation in 26 traits for 154 North American and 66 European tree species and grid-based co-occurrences derived from distribution maps to compare functional diversity patterns of the two continents. First, we identified similar regions with respect to contemporary climate in the temperate zone of North America and Europe. Second, we compared the functional diversity of both continents and for the climatically similar sub-regions using the functional dispersion-index (FDis) and the functional richness index (FRic). Third, we accounted in these comparisons for grid-scale differences in species richness, and, fourth, investigated the associated trait spaces using dimensionality reduction. For gymnosperms we find similar functional diversity on both continents, whereas for angiosperms functional diversity is significantly greater in Europe than in North America. These results are consistent across different scales, for climatically similar regions and considering species richness patterns. We decomposed these differences in trait space occupation into differences in functional diversity vs. differences in functional identity. We show that climate-driven species loss on a continental scale might be decoupled from or at least not linearly related to changes in functional diversity. This might be important when analyzing the effects of climate-driven biodiversity change on ecosystem functioning. PMID:26848836

Changing climatic response: a conceptual model for glacial cycles and the Mid-Pleistocene Transition

NASA Astrophysics Data System (ADS)

Daruka, I.; Ditlevsen, P. D.

2014-03-01

Milankovitch's astronomical theory of glacial cycles, attributing ice age climate oscillations to orbital changes in Northern Northern-Hemisphere insolation, is challenged by the paleoclimatic record. The climatic response to the variations in insolation is far from trivial. In general the glacial cycles are highly asymmetric in time, with slow cooling from the interglacials to the glacials (inceptions) and very rapid warming from the glacials to the interglacials (terminations). We shall refer to this fast-slow dynamics as the "saw-tooth" shape of the paleoclimatic record. This is non-linearly related to the time-symmetric variations in the orbital forcing. However, the most pronounced challenge to the Milankovitch theory is the Mid-Pleistocene Transition (MPT) occurring about one million years ago. During that event, the prevailing 41 kyr glacial cycles, corresponding to the almost harmonic obliquity cycle were replaced by longer saw-tooth shaped cycles with a time scale around 100 kyr. The MPT must have been driven by internal changes in climate response, since it does not correspond to any apparent changes in the orbital forcing. In order to identify possible mechanisms causing the observed changes in glacial dynamics, it is relevant to study simplified models with the capability of generating temporal behavior similar to the observed records. We present a simple oscillator type model approach, with two variables, a temperature anomaly and an ice volume analogous, climatic memory term. The generalization of the ice albedo feedback is included in terms of an effective multiplicative coupling between this latter climatic memory term (representing the internal degrees of freedom) and the external drive. The simple model reproduces the temporal asymmetry of the late Pleistocene glacial cycles and suggests that the MPT can be explained as a regime shift, aided by climatic noise, from a period 1 frequency locking to the obliquity cycle to a period 2-3 frequency locking to the same obliquity cycle. The change in dynamics has been suggested to be a result of a slow gradual decrease in atmospheric greenhouse gas concentration. The presence of chaos in the (non-autonomous) glacial dynamics and a critical dependence on initial conditions raises fundamental questions about climate predictability.

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.

Latest research related to climate change analysis with applications in impact studies over the territory of Serbia

NASA Astrophysics Data System (ADS)

Vukovic, Ana; Vujadinovic, Mirjam; Djurdjevic, Vladimir; Cvetkovic, Bojan; Djordjevic, Marija; Ruml, Mirjana; Rankovic-Vasic, Zorica; Przic, Zoran; Stojicic, Djurdja; Krzic, Aleksandra; Rajkovic, Borivoj

2015-04-01

Serbia is a country with relatively small scale terrain features with economy mostly based on local landowners' agricultural production. Climate change analysis must be downscaled accordingly, to recognize climatological features of the farmlands. Climate model simulations and impact studies significantly contribute to the future strategic planning in economic development and therefore impact analysis must be approached with high level of confidence. This paper includes research related to climate change and impacts in Serbia resulted from cooperative work of the modeling and user community. Dynamical downscaling of climate projections for the 21st century with multi-model approach and statistical bias correction are done in order to prepare model results for impact studies. Presented results are from simulations performed using regional EBU-POM model, which is forced with A1B and A2 SRES/IPCC (2007) with comparative analysis with other regional models and from the latest high resolution NMMB simulations forced with RCP8.5 IPCC scenario (2012). Application of bias correction of the model results is necessary when calculated indices are not linearly dependent on the model results and delta approach in presenting results with respect to present climate simulations is insufficient. This is most important during the summer over the north part of the country where model bias produce much higher temperatures and less precipitation, which is known as "summer drying problem" and is common in regional models' simulations over the Pannonian valley. Some of the results, which are already observed in present climate, like higher temperatures and disturbance in the precipitation pattern, lead to present and future advancement of the start of the vegetation period toward earlier dates, associated with an increased risk of the late spring frost, extended vegetation period, disturbed preparation for the rest period, increased duration and frequency of the draught periods, etc. Based on the projected climate changes an application is proposed of the ensemble seasonal forecasts for early preparation in case of upcoming unfavorable weather conditions. This paper was realized as a part of the projects "Studying climate change and its influence on the environment: impacts, adaptation and mitigation" (43007) and "Assessment of climate change impacts on water resources in Serbia" (37005) financed by the Ministry of Education and Science of the Republic of Serbia within the framework of integrated and interdisciplinary research for the period 2011-2015.

A new method for probabilistic assessment of regional climate impacts in dependence of cumulative GHG emission budgets

NASA Astrophysics Data System (ADS)

Frieler, Katja; Meinshausen, Malte; Braun, Nadine; Hare, Bill

2010-05-01

Given the expected and already observed impacts of climate change there is growing agreement that global mean temperature rise should be limited to below 2 or 1.5 degrees. The translation of such a temperature target into guidelines for global emission reduction over the coming decades has become one of the most important and urgent tasks. In fact, there are four recent studies (Meinshausen et al. 2009, Allen et al. 2009, Matthews et al. 2009 and Zickfeld et al. 2009) which take a very comprehensive approach to quantifying the current uncertainties related to the question of what are the "allowed amounts" of global emissions given specific limits of global warming. Here, we present an extension of this budget approach allowing to focus on specific regional impacts. The method is based on probabilistic projections of regional temperature and precipitation changes providing the input for available impact functions. Using the example of Greenland's surface mass balance (Gregory et al., 2006) we will demonstrate how the probability of specific impacts can be described in dependence of global GHG emission budgets taking into account the uncertainty of global mean temperature projections as well as uncertainties of regional climate patterns varying from AOGCM to AOGCM. The method utilizes the AOGCM based linear relation between global mean temperature changes and regionally averaged changes in temperature and precipitation. It allows to handle the variations of regional climate projections from AR4 AOGCM runs independent of the uncertainties of global mean temperature change that are estimated by a simple climate model (Meinshausen et al., 2009). While the linearity of this link function is already established for temperature and to a lesser degree (depending on the region) also for precipitation (Santer et al. 1990; Mitchell et al. 1999; Giorgi et al., 2008; Solomon et al., 2009), we especially focus on the quantification of the uncertainty (in particularly the inter-AOGCM variations) of the associated scaling coefficients. Our approach is based on a linear mixed effects model (e.g. Bates and Pinheiro, 2001). In comparison to other scaling approaches we do not fit separate models for the temperature and precipitation data but we apply a two-dimensional model, i.e., we explicitly account for the fact that models (scenarios or runs) showing an especially high temperature increase may also show high precipitation increases or vice versa. Coupling the two-dimensional distribution of the scaling coefficients with the uncertainty distributions of global mean temperature change given different GHG emission trajectories finally provides time series of two dimensional uncertainty distributions of regional changes in temperature and precipitation, where both components might be correlated. These samples provide the input for regional specific impact functions. In case of Greenland we use a function by Gregory et al., 2006 that allows us to calculate changes in sea level rise due to changes in Greenland's surface mass balance in dependence of regionally averaged changes in temperature and precipitation. The precipitation signal turns out to be relatively strong for Greenland with AOGCMs consistently showing increasing precipitation with increasing global mean temperature. In addition, temperature and precipitation increases turned out to be highly correlated for Greenland: Models showing an especially high temperature increase also show high precipitation increases reflected by a correlation coefficient of 0.88 for the inter-model variations of both components of the scaling coefficients. Taking these correlations into account is especially important because the surface mass balance of the Greenland ice sheet critically depends on the interaction of the temperature and precipitation component of climate change: Increasing precipitation may at least partly balance the loss due to increasing temperatures.

Contribution of urban expansion and a changing climate to decline of a butterfly fauna.

PubMed

Casner, Kayce L; Forister, Matthew L; O'Brien, Joshua M; Thorne, James; Waetjen, David; Shapiro, Arthur M

2014-06-01

Butterfly populations are naturally patchy and undergo extinctions and recolonizations. Analyses based on more than 2 decades of data on California's Central Valley butterfly fauna show a net loss in species richness through time. We analyzed 22 years of phenological and faunistic data for butterflies to investigate patterns of species richness over time. We then used 18-22 years of data on changes in regional land use and 37 years of seasonal climate data to develop an explanatory model. The model related the effects of changes in land-use patterns, from working landscapes (farm and ranchland) to urban and suburban landscapes, and of a changing climate on butterfly species richness. Additionally, we investigated local trends in land use and climate. A decline in the area of farmland and ranchland, an increase in minimum temperatures during the summer and maximum temperatures in the fall negatively affected net species richness, whereas increased minimum temperatures in the spring and greater precipitation in the previous summer positively affected species richness. According to the model, there was a threshold between 30% and 40% working-landscape area below which further loss of working-landscape area had a proportionally greater effect on butterfly richness. Some of the isolated effects of a warming climate acted in opposition to affect butterfly richness. Three of the 4 climate variables that most affected richness showed systematic trends (spring and summer mean minimum and fall mean maximum temperatures). Higher spring minimum temperatures were associated with greater species richness, whereas higher summer temperatures in the previous year and lower rainfall were linked to lower richness. Patterns of land use contributed to declines in species richness (although the pattern was not linear), but the net effect of a changing climate on butterfly richness was more difficult to discern. © 2014 Society for Conservation Biology.

Will climate change affect outbreak patterns of planthoppers in Bangladesh?

PubMed

Ali, M P; Huang, Dingcheng; Nachman, G; Ahmed, Nur; Begum, Mahfuz Ara; Rabbi, M F

2014-01-01

Recently, planthoppers outbreaks have intensified across Asia resulting in heavy rice yield losses. The problem has been widely reported as being induced by insecticides while other factors such as global warming that could be potential drivers have been neglected. Here, we speculate that global warming may increase outbreak risk of brown planthopper (Nilaparvata lugens Stål.). We present data that demonstrate the relationship between climate variables (air temperature and precipitation) and the abundance of brown planthopper (BPH) during 1998-2007. Data show that BPH has become significantly more abundant in April over the 10-year period, but our data do not indicate that this is due to a change in climate, as no significant time trends in temperature and precipitation could be demonstrated. The abundance of BPH varied considerably between months within a year which is attributed to seasonal factors, including the availability of suitable host plants. On the other hand, the variation within months is attributed to fluctuations in monthly temperature and precipitation among years. The effects of these weather variables on BPH abundance were analyzed statistically by a general linear model. The statistical model shows that the expected effect of increasing temperatures is ambiguous and interacts with the amount of rainfall. According to the model, months or areas characterized by a climate that is either cold and dry or hot and wet are likely to experience higher levels of BPH due to climate change, whereas other combinations of temperature and rainfall may reduce the abundance of BPH. The analysis indicates that global warming may have contributed to the recent outbreaks of BPH in some rice growing areas of Asia, and that the severity of such outbreaks is likely to increase if climate change exaggerates. Our study highlights the need to consider climate change when designing strategies to manage planthoppers outbreaks.

The effects of climate change on heating energy consumption of office buildings in different climate zones in China

NASA Astrophysics Data System (ADS)

Meng, Fanchao; Li, Mingcai; Cao, Jingfu; Li, Ji; Xiong, Mingming; Feng, Xiaomei; Ren, Guoyu

2017-06-01

Climate plays an important role in heating energy consumption owing to the direct relationship between space heating and changes in meteorological conditions. To quantify the impact, the Transient System Simulation Program software was used to simulate the heating loads of office buildings in Harbin, Tianjin, and Shanghai, representing three major climate zones (i.e., severe cold, cold, and hot summer and cold winter climate zones) in China during 1961-2010. Stepwise multiple linear regression was performed to determine the key climatic parameters influencing heating energy consumption. The results showed that dry bulb temperature (DBT) is the dominant climatic parameter affecting building heating loads in all three climate zones across China during the heating period at daily, monthly, and yearly scales (R 2 ≥ 0.86). With the continuous warming climate in winter over the past 50 years, heating loads decreased by 14.2, 7.2, and 7.1 W/m2 in Harbin, Tianjin, and Shanghai, respectively, indicating that the decreasing rate is more apparent in severe cold climate zone. When the DBT increases by 1 °C, the heating loads decrease by 253.1 W/m2 in Harbin, 177.2 W/m2 in Tianjin, and 126.4 W/m2 in Shanghai. These results suggest that the heating energy consumption can be well predicted by the regression models at different temporal scales in different climate conditions owing to the high determination coefficients. In addition, a greater decrease in heating energy consumption in northern severe cold and cold climate zones may efficiently promote the energy saving in these areas with high energy consumption for heating. Particularly, the likely future increase in temperatures should be considered in improving building energy efficiency.

Perspectives on massive coral growth rates in a changing ocean.

PubMed

Lough, Janice M; Cantin, Neal E

2014-06-01

The tropical ocean environment is changing at an unprecedented rate, with warming and severe tropical cyclones creating obvious impacts to coral reefs within the last few decades and projections of acidification raising concerns for the future of these iconic and economically important ecosystems. Documenting variability and detecting change in global and regional climate relies upon high-quality observational records of climate variables supplemented, prior to the mid-19th century, with reconstructions from various sources of proxy climate information. Here we review how annual density banding patterns that are recorded in the skeletons of massive reef-building corals have been used to document environmental change and impacts within coral reefs. Massive corals provide a historical perspective of continuous calcification processes that pre-date most ecological observations of coral reefs. High-density stress bands, abrupt declines in annual linear extension, and evidence of partial mortality within the skeletal growth record reveal signatures of catastrophic stress events that have recently been attributed to mass bleaching events caused by unprecedented thermal stress. Comparison of recent trends in annual calcification with century-scale baseline calcification rates reveals that the frequency of growth anomalies has increased since the late 1990s throughout most of the world's coral reef ecosystems. Continuous coral growth histories provide valuable retrospective information on the coral response to environmental change and the consequences of anthropogenic climate change. Co-ordinated efforts to synthesize and combine global calcification histories will greatly enhance our understanding of current calcification responses to a changing ocean. © 2014 Marine Biological Laboratory.

Linking hydro-climate to the sediment archive: a combined monitoring and calibration study from a varved lake in central Turkey

NASA Astrophysics Data System (ADS)

Roberts, C. Neil; Dean, Jonathan R.; Eastwood, Warren J.; Jones, Matthew D.; Allcock, Samantha L.; Leng, Melanie J.; Metcalfe, Sarah E.; Woodbridge, Jessie; Yiǧitbaşıoǧlu, Hakan

2016-04-01

Hydro-climatic reconstructions from lake sediment proxies require an understanding of modern formation processes and calibration over multiple years. Here we use Nar Gölü, a non-outlet, monomictic maar lake in central Turkey, as a field site for such a natural experiment. Fieldwork since 1997 has included observations and measurements of lake water and sediment trap samples, and automated data logging (Jones et al., 2005; Woodbridge and Roberts, 2010; Dean et al., 2015). We compare these data to isotopic, chemical and biotic proxies preserved in the lake's annually-varved sediments. Nar Gölü underwent a 3 m lake-level fall between 2000 and 2010, and δ18O in both water and carbonates is correlated with this lake-level fall, responding to the change in water balance. Over the same period, sedimentary diatom assemblages responded via changes in habitat availability and mixing regime, while conductivity inferred from diatoms showed a rise in inferred salinity, although with a non-linear response to hydro-climatic forcing. There were also non-linear shifts in carbonate mineralogy and elemental chemistry. Building on the relationship between lake water balance and the sediment isotope record, we calibrated sedimentary δ18O against local meteorological records to derive a P/E drought index for central Anatolia. Application to of this to the longer sediment core isotope record from Nar Gölü (Jones et al. 2006) highlights major drought events over the last 600 years (Yiǧitbaşıoǧlu et al., 2015). Although this lacustrine record offers an archive of annually-dated, decadally-averaged hydro-climatic change, there were also times of non-linear lake response to climate. Robust reconstruction therefore requires understanding of physical processes as well as application of statistical correlations. Dean, J.R., Eastwood, W.J., Roberts, N., Jones, M.D., Yiǧitbaşıoǧlu, H., Allcock, S.L., Woodbridge, J., Metcalfe, S.E. and Leng, M.J. (2015) Tracking the hydro-climatic signal from lake to sediment: a field study from central Turkey, J. Hydrol. 529, 608-621. Jones, MD, Leng, MJ, Roberts, CN, Turkes, M, Moyeed, R (2005) A coupled calibration and modelling approach to the understanding of dry-land lake oxygen isotope records. J Paleolimnol 34: 391-411 Jones, M.D., Roberts, N., Leng, M.J. and Türkeş, M. (2006) A high-resolution late Holocene lake isotope record from Turkey and links to North Atlantic and monsoon climate. Geology 34 (5), 361-364. Woodbridge, J, & Roberts, N (2010) Linking neo- and palaeolimnology: a case study using crater lake diatoms from central Turkey. J Paleolimnol 44: 855-871 Yiǧitbaşıoǧlu, H., Dean, J.R., Eastwood, W.J., Roberts, N., Jones, M.D. and Leng, M.J. (2015) A 600 year-long drought index for central Anatolia. Journal of Black Sea/Mediterranean Environment, Special Issue: 84-88

Characterization of the Dynamics of Climate Systems and Identification of Missing Mechanisms Impacting the Long Term Predictive Capabilities of Global Climate Models Utilizing Dynamical Systems Approaches to the Analysis of Observed and Modeled Climate

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

Bhatt, Uma S.; Wackerbauer, Renate; Polyakov, Igor V.

The goal of this research was to apply fractional and non-linear analysis techniques in order to develop a more complete characterization of climate change and variability for the oceanic, sea ice and atmospheric components of the Earth System. This research applied two measures of dynamical characteristics of time series, the R/S method of calculating the Hurst exponent and Renyi entropy, to observational and modeled climate data in order to evaluate how well climate models capture the long-term dynamics evident in observations. Fractional diffusion analysis was applied to ARGO ocean buoy data to quantify ocean transport. Self organized maps were appliedmore » to North Pacific sea level pressure and analyzed in ways to improve seasonal predictability for Alaska fire weather. This body of research shows that these methods can be used to evaluate climate models and shed light on climate mechanisms (i.e., understanding why something happens). With further research, these methods show promise for improving seasonal to longer time scale forecasts of climate.« less

Climate Intervention as an Optimization Problem

NASA Astrophysics Data System (ADS)

Caldeira, Ken; Ban-Weiss, George A.

2010-05-01

Typically, climate models simulations of intentional intervention in the climate system have taken the approach of imposing a change (eg, in solar flux, aerosol concentrations, aerosol emissions) and then predicting how that imposed change might affect Earth's climate or chemistry. Computations proceed from cause to effect. However, humans often proceed from "What do I want?" to "How do I get it?" One approach to thinking about intentional intervention in the climate system ("geoengineering") is to ask "What kind of climate do we want?" and then ask "What pattern of radiative forcing would come closest to achieving that desired climate state?" This involves defining climate goals and a cost function that measures how closely those goals are attained. (An important next step is to ask "How would we go about producing these desired patterns of radiative forcing?" However, this question is beyond the scope of our present study.) We performed a variety of climate simulations in NCAR's CAM3.1 atmospheric general circulation model with a slab ocean model and thermodynamic sea ice model. We then evaluated, for a specific set of climate forcing basis functions (ie, aerosol concentration distributions), the extent to which the climate response to a linear combination of those basis functions was similar to a linear combination of the climate response to each basis function taken individually. We then developed several cost functions (eg, relative to the 1xCO2 climate, minimize rms difference in zonal and annual mean land temperature, minimize rms difference in zonal and annual mean runoff, minimize rms difference in a combination of these temperature and runoff indices) and then predicted optimal combinations of our basis functions that would minimize these cost functions. Lastly, we produced forward simulations of the predicted optimal radiative forcing patterns and compared these with our expected results. Obviously, our climate model is much simpler than reality and predictions from individual models do not provide a sound basis for action; nevertheless, our model results indicate that the general approach outlined here can lead to patterns of radiative forcing that make the zonal annual mean climate of a high CO2 world markedly more similar to that of a low CO2 world simultaneously for both temperature and hydrological indices, where degree of similarity is measured using our explicit cost functions. We restricted ourselves to zonally uniform aerosol concentrations distributions that can be defined in terms of a positive-definite quadratic equation on the sine of latitude. Under this constraint, applying an aerosol distribution in a 2xCO2 climate that minimized a combination of rms difference in zonal and annual mean land temperature and runoff relative to the 1xCO2 climate, the rms difference in zonal and annual mean temperatures was reduced by ~90% and the rms difference in zonal and annual mean runoff was reduced by ~80%. This indicates that there may be potential for stratospheric aerosols to diminish simultaneously both temperature and hydrological cycle changes caused by excess CO2 in the atmosphere. Clearly, our model does not include many factors (eg, socio-political consequences, chemical consequences, ocean circulation changes, aerosol transport and microphysics) so we do not argue strongly for our specific climate model results, however, we do argue strongly in favor of our methodological approach. The proposed approach is general, in the sense that cost functions can be developed that represent different valuations. While the choice of appropriate cost functions is inherently a value judgment, evaluating those functions for a specific climate simulation is a quantitative exercise. Thus, the use of explicit cost functions in evaluating model results for climate intervention scenarios is a clear way of separating value judgments from purely scientific and technical issues.

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

A Synoptic Weather Typing Approach and Its application to Assess Climate Change Impacts on Extreme Weather Events at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Shouquan Cheng, Chad; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada for several research projects to analyze climatic change impacts on a number of extreme weather events, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the extreme weather events, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projections of changes in frequency and intensity of future extreme weather events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and a number of linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into each of the three parts of the projects. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. The modeled results from these projects found that the frequency and intensity of future extreme weather events are projected to significantly increase under a changing climate in this century. This talk will introduce these research projects and outline the modeling exercise and result verification process. The major findings on future projections from the studies will be summarized in the presentation as well. One of the major conclusions from the studies is that the procedures (including synoptic weather typing) used in the studies are useful for climate change impact analysis on future extreme weather events. The implication of the significant increases in frequency and intensity of future extreme weather events would be useful to be considered when revising engineering infrastructure design standards and developing adaptation strategies and policies.

Biological communities in San Francisco Bay track large-scale climate forcing over the North Pacific

NASA Astrophysics Data System (ADS)

Cloern, James E.; Hieb, Kathryn A.; Jacobson, Teresa; Sansó, Bruno; Di Lorenzo, Emanuele; Stacey, Mark T.; Largier, John L.; Meiring, Wendy; Peterson, William T.; Powell, Thomas M.; Winder, Monika; Jassby, Alan D.

2010-11-01

Long-term observations show that fish and plankton populations in the ocean fluctuate in synchrony with large-scale climate patterns, but similar evidence is lacking for estuaries because of shorter observational records. Marine fish and invertebrates have been sampled in San Francisco Bay since 1980 and exhibit large, unexplained population changes including record-high abundances of common species after 1999. Our analysis shows that populations of demersal fish, crabs and shrimp covary with the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), both of which reversed signs in 1999. A time series model forced by the atmospheric driver of NPGO accounts for two-thirds of the variability in the first principal component of species abundances, and generalized linear models forced by PDO and NPGO account for most of the annual variability of individual species. We infer that synchronous shifts in climate patterns and community variability in San Francisco Bay are related to changes in oceanic wind forcing that modify coastal currents, upwelling intensity, surface temperature, and their influence on recruitment of marine species that utilize estuaries as nursery habitat. Ecological forecasts of estuarine responses to climate change must therefore consider how altered patterns of atmospheric forcing across ocean basins influence coastal oceanography as well as watershed hydrology.

Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

PubMed

Carvalho, B M; Rangel, E F; Vale, M M

2017-08-01

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

How much would five trillion tonnes of carbon warm the climate?

NASA Astrophysics Data System (ADS)

Tokarska, Katarzyna Kasia; Gillett, Nathan P.; Weaver, Andrew J.; Arora, Vivek K.

2016-04-01

While estimates of fossil fuel reserves and resources are very uncertain, and the amount which could ultimately be burnt under a business as usual scenario would depend on prevailing economic and technological conditions, an amount of five trillion tonnes of carbon (5 EgC), corresponding to the lower end of the range of estimates of the total fossil fuel resource, is often cited as an estimate of total cumulative emissions in the absence of mitigation actions. The IPCC Fifth Assessment Report indicates that an approximately linear relationship between warming and cumulative carbon emissions holds only up to around 2 EgC emissions. It is typically assumed that at higher cumulative emissions the warming would tend to be less than that predicted by such a linear relationship, with the radiative saturation effect dominating the effects of positive carbon-climate feedbacks at high emissions, as predicted by simple carbon-climate models. We analyze simulations from four state-of-the-art Earth System Models (ESMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and seven Earth System Models of Intermediate Complexity (EMICs), driven by the Representative Concentration Pathway 8.5 Extension scenario (RCP 8.5 Ext), which represents a very high emission scenario of increasing greenhouse gas concentrations in absence of climate mitigation policies. Our results demonstrate that while terrestrial and ocean carbon storage varies between the models, the CO2-induced warming continues to increase approximately linearly with cumulative carbon emissions even for higher levels of cumulative emissions, in all four ESMs. Five of the seven EMICs considered simulate a similarly linear response, while two exhibit less warming at higher cumulative emissions for reasons we discuss. The ESMs simulate global mean warming of 6.6-11.0°C, mean Arctic warming of 15.3-19.7°C, and mean regional precipitation increases and decreases by more than a factor of four, in response to 5EgC, with smaller forcing contributions from other greenhouse gases. These results indicate that the unregulated exploitation of the fossil fuel resource would ultimately result in considerably more profound climate changes than previously suggested.

The Response of Tropical Tropospheric Ozone to ENSO

NASA Technical Reports Server (NTRS)

Oman, L. D.; Ziemke, J. R.; Douglass, A. R.; Waugh, D. W.; Lang, C.; Rodriguez, J. M.; Nielsen, J. E.

2011-01-01

We have successfully reproduced the Ozone ENSO Index (OEI) in the Goddard Earth Observing System (GEOS) chemistry-climate model (CCM) forced by observed sea surface temperatures over a 25-year period. The vertical ozone response to ENSO is consistent with changes in the Walker circulation. We derive the sensitivity of simulated ozone to ENSO variations using linear regression analysis. The western Pacific and Indian Ocean region shows similar positive ozone sensitivities from the surface to the upper troposphere, in response to positive anomalies in the Nino 3.4 Index. The eastern and central Pacific region shows negative sensitivities with the largest sensitivity in the upper troposphere. This vertical response compares well with that derived from SHADOZ ozonesondes in each region. The OEI reveals a response of tropospheric ozone to circulation change that is nearly independent of changes in emissions and thus it is potentially useful in chemistry-climate model evaluation.

Thermal Tolerance of the Coffee Berry Borer Hypothenemus hampei: Predictions of Climate Change Impact on a Tropical Insect Pest

PubMed Central

Jaramillo, Juliana; Chabi-Olaye, Adenirin; Kamonjo, Charles; Jaramillo, Alvaro; Vega, Fernando E.; Poehling, Hans-Michael; Borgemeister, Christian

2009-01-01

Coffee is predicted to be severely affected by climate change. We determined the thermal tolerance of the coffee berry borer , Hypothenemus hampei, the most devastating pest of coffee worldwide, and make inferences on the possible effects of climate change using climatic data from Colombia, Kenya, Tanzania, and Ethiopia. For this, the effect of eight temperature regimes (15, 20, 23, 25, 27, 30, 33 and 35°C) on the bionomics of H. hampei was studied. Successful egg to adult development occurred between 20–30°C. Using linear regression and a modified Logan model, the lower and upper thresholds for development were estimated at 14.9 and 32°C, respectively. In Kenya and Colombia, the number of pest generations per year was considerably and positively correlated with the warming tolerance. Analysing 32 years of climatic data from Jimma (Ethiopia) revealed that before 1984 it was too cold for H. hampei to complete even one generation per year, but thereafter, because of rising temperatures in the area, 1–2 generations per year/coffee season could be completed. Calculated data on warming tolerance and thermal safety margins of H. hampei for the three East African locations showed considerably high variability compared to the Colombian site. The model indicates that for every 1°C rise in thermal optimum (Topt.), the maximum intrinsic rate of increase (r max) will increase by an average of 8.5%. The effects of climate change on the further range of H. hampei distribution and possible adaption strategies are discussed. Abstracts in Spanish and French are provided as supplementary material Abstract S1 and Abstract S2. PMID:19649255

Climate change impacts on faecal indicator and waterborne pathogen concentrations and disease

NASA Astrophysics Data System (ADS)

Hofstra, Nynke; Vermeulen, Lucie C.; Wondmagegn, Berhanu Y.

2013-04-01

Changes in temperature and precipitation patterns may impact on the concentrations of the faecal indicator E. coli and waterborne pathogens, such as Cryptosporidium, in the surface water, and consequently - through drinking water, recreational water or consumption of irrigated vegetables - on the risk of waterborne disease. Although an increased temperature would generally increase the decline of pathogens and therefore decrease the surface water concentrations, increased precipitation and an increased incidence of extreme precipitation may increase surface water concentrations through increased (sub-)surface runoff and an increased risk of sewer overflows. And while the diluting effect of increased precipitation decreases the surface water concentration, decreased precipitation increases the percentage of sewage in the surface water and therefore increases the concentration. Moreover, (extreme) precipitation after drought may also increase the concentration. Changes in behaviour, such as increased recreation and irrigation with higher temperatures may impact on the disease risk. What the balance is between these positive and negative impacts of climate change on faecal indicator and waterborne pathogen concentrations and disease is not well known yet. A lack of available statistical or process-based models and suitable scenarios prevents quantitative analyses. We will present two examples of recent studies that aim to assess the impact of climate change on faecal indicator concentrations and waterborne disease. The first is a study on the relationship between climate variables and E. coli concentrations in the water of river systems in the Netherlands for the period 1985 - 2010. This study shows that each of the variables water temperature (negatively), precipitation and discharge (both positively) are significantly correlated with E. coli concentrations for most measurement locations. We will also present a linear regression model, including all of these variables. In the second example we assess the relationship between the weather variables precipitation and minimum and maximum temperature and the number of diarrhoeal cases in Ethiopia. We have digitised data from the Ethiopian health service and hospitals on the number of diarrhoeal cases for the period 2005 - 2010 and used meteorological data from their weather service. Very strong correlations can be found between the monthly weather variables and the number of diarrhoeal cases and a linear regression model including all variables explains a large part of the variability of the data. The studies indicate that climate change may increase the waterborne pathogen concentration in surface water and disease risk and should therefore not be ignored as a threat to microbial water quality.

Child Centred Approach to Climate Change and Health Adaptation through Schools in Bangladesh: A Cluster Randomised Intervention Trial

PubMed Central

Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat

2015-01-01

Background Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. Methods This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. Results None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. Conclusions These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic. PMID:26252381

Facilitating adaptation in montane plants to changing precipitation along an elevation gradient

USGS Publications Warehouse

Hess, Steve; Leopold, Christina

2017-01-01

Montane plant communities throughout the world have responded to changes in precipitation and temperature regimes by shifting ranges upward in elevation. Continued warmer, drier climate conditions have been documented and are projected to increase in high-elevation areas in Hawai‘i, consistent with climate change effects reported in other environments throughout the world. Organisms that cannot disperse or adapt biologically to projected climate scenarios in situ may decrease in distributional range and abundance over time. Restoration efforts will need to accommodate future climate change and account for the interactive effects of existing invasive species to ensure long-term persistence. As part of a larger, ongoing restoration effort, we hypothesized that plants from a lower-elevation forest ecotype would have higher rates of survival and growth compared to high-elevation forest conspecifics when grown in common plots along an elevation gradient. We monitored climate conditions at planting sites to identify whether temperature or rainfall influenced survival and growth after 20 weeks. We found that origin significantly affected survival in only one of three native montane species, Dodonaea viscosa. Contrary to our hypothesis, 75.2% of seedlings from high-elevation origin survived in comparison to 58.7% of seedlings from low elevation across the entire elevation gradient. Origin also influenced survival in linearized mixed models that controlled for temperature, precipitation, and elevation in D. viscosa and Chenopodium oahuense. Only C. oahuense seedlings had similar predictors of growth and survival. There were no common patterns of growth or survival between species, indicating that responses to changing precipitation and emperature regimes varied between montane plant species. Results also suggest that locally sourced seed is important to ensure highest survival at restoration sites. Further experimentation on larger spatial and temporal scales is necessary to determine the empirical responses of species and communities to changing climate in the full context of highly degraded Hawaiian ecosystems.

Child Centred Approach to Climate Change and Health Adaptation through Schools in Bangladesh: A Cluster Randomised Intervention Trial.

PubMed

Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat

2015-01-01

Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic.

Food for Thought: Crop Yields in the Columbia River Basin in an Altered Future

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Nelson, R.; Stockle, C.; Kruger, C.; Brady, M.; Adam, J. C.

2013-12-01

Growth of global population and food consumption in the next several decades is expected to result in a food security challenge. Strategies to address this challenge, such as enhancing agricultural productivity and resiliency, need to be considered within the context of a full range of plausible consequences so as to identify investments that create win-win-win scenarios for the environment, economy, and society. Regional earth systems models can provide the necessary scale-appropriate framework to inform the decision making context for adaptation strategies, especially in the context of global change. In an altered future, changes to climate, technology and socioeconomics affect regional agriculture both directly and indirectly. These effects are not independent and an integrated process-based model may better capture unanticipated non-linear and non-monotonic responses and feedbacks over time . BioEarth is a research initiative designed to explore the coupling of multiple stand-alone earth systems models to generate usable information for agricultural and natural resource decision making at the regional scale at decadal time-steps. This project focuses on the U.S. Pacific Northwest (PNW) region and is a framework that integrates atmospheric, terrestrial, aquatic, and economic models. We apply component models of BioEarth to the Columbia River basin in the PNW to study the direct and indirect impacts of climate change on regional irrigated and dryland crop yields for a variety of annual and perennial crops. Results indicate that the net effect of climate change on crop yields is dependent on the crop type. There is a negative effect of temperature on yields for most crops. Dryland winter wheat is a notable exception. With warming, although the available growing season increases, faster thermal accumulation results in a shorter time to maturity. Precipitation changes in the region have a positive impact on dryland agriculture. Carbon dioxide (CO2) fertilization has a positive impact on crop yields for most crops. This positive impact is minimal for corn which is a C4 crop that is already CO2 efficient. The net response is an increase in yields for dryland agriculture and depends on the crop type for irrigated agriculture. Although, climate change results in increased water shortages and water rights curtailment in the region, this does not translate into an increased negative effect on yields. This could be attributed to higher water use efficiency under elevated CO2 levels as well crops getting through growth stages earlier in the season with wetter spring conditions. The non linear and non monotonic nature of the response of climate change on crop yields is discussed. In accounting for biophysical effects of climate change on crop yields, socio-economic effects cannot be ignored because biophysical effects are nested with the framework of human decision making. We also discuss our results in the context of socioeconomic factors . Current results assume no adaptation strategies and incorporating this is our next step.

Historical changes in lake ice-out dates as indicators of climate change in New England, 1850-2000

USGS Publications Warehouse

Hodgkins, G.A.; James, Ivan; Huntington, T.G.

2002-01-01

Various studies have shown that changes over time in spring ice-out dates can be used as indicators of climate change. Ice-out dates from 29 lakes in New England (USA) with 64 to 163 years of record were assembled and analysed for this study. Ice-out dates have become significantly earlier in New England since the 1800s. Changes in ice-out dates between 1850 and 2000 were 9 days and 16 days in the northern/mountainous and southern regions of New England respectively. The changes in the ice-out data over time were very consistent within each of the two regions of New England, and more consistent than four air-temperature records in each region. The ice-out dates of the two regions had a different response to changes in air temperature. The inferred late winter-early spring air-temperature warming in both regions of New England since 1850, based on linear regression analysis, was about 1.5 ??C. Published in 2002 by John Wiley & Sons, Ltd.

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events.

PubMed

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions.

Interpreting the Climatic Effects on Xylem Functional Traits in Two Mediterranean Oak Species: The Role of Extreme Climatic Events

PubMed Central

Rita, Angelo; Borghetti, Marco; Todaro, Luigi; Saracino, Antonio

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions. PMID:27532008

The interdecadal worsening of weather conditions affecting aerosol pollution in the Beijing area in relation to climate warming

NASA Astrophysics Data System (ADS)

Zhang, Xiaoye; Zhong, Junting; Wang, Jizhi; Wang, Yaqiang; Liu, Yanju

2018-04-01

The weather conditions affecting aerosol pollution in Beijing and its vicinity (BIV) in wintertime have worsened in recent years, particularly after 2010. The relation between interdecadal changes in weather conditions and climate warming is uncertain. Here, we analyze long-term variations of an integrated pollution-linked meteorological index (which is approximately and linearly related to aerosol pollution), the extent of changes in vertical temperature differences in the boundary layer (BL) in BIV, and northerly surface winds from Lake Baikal during wintertime to evaluate the potential contribution of climate warming to changes in meteorological conditions directly related to aerosol pollution in this area; this is accomplished using NCEP reanalysis data, surface observations, and long-term vertical balloon sounding observations since 1960. The weather conditions affecting BIV aerosol pollution are found to have worsened since the 1960s as a whole. This worsening is more significant after 2010, with PM2.5 reaching unprecedented high levels in many cities in China, particularly in BIV. The decadal worsening of meteorological conditions in BIV can partly be attributed to climate warming, which is defined by more warming in the higher layers of the boundary layer (BL) than the lower layers. This worsening can also be influenced by the accumulation of aerosol pollution, to a certain extent (particularly after 2010), because the increase in aerosol pollution from the ground leads to surface cooling by aerosol-radiation interactions, which facilitates temperature inversions, increases moisture accumulations, and results in the extra deterioration of meteorological conditions. If analyzed as a linear trend, weather conditions have worsened by ˜ 4 % each year from 2010 to 2017. Given such a deterioration rate, the worsening of weather conditions may lead to a corresponding amplitude increase in PM2.5 in BIV during wintertime in the next 5 years (i.e., 2018 to 2022). More stringent emission reduction measures will need to be conducted by the government.

Differences in the efficacy of climate forcings explained by variations in atmospheric boundary layer depth.

PubMed

Davy, Richard; Esau, Igor

2016-05-25

The Earth has warmed in the last century and a large component of that warming has been attributed to increased anthropogenic greenhouse gases. There are also numerous processes that introduce strong, regionalized variations to the overall warming trend. However, the ability of a forcing to change the surface air temperature depends on its spatial and temporal distribution. Here we show that the efficacy of a forcing is determined by the effective heat capacity of the atmosphere, which in cold and dry climates is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, and so we get a strongly amplified temperature response in shallow boundary layers. This must be accounted for to assess the efficacy of a climate forcing, and also implies that multiple climate forcings cannot be linearly combined to determine the temperature response.

Differences in the efficacy of climate forcings explained by variations in atmospheric boundary layer depth

PubMed Central

Davy, Richard; Esau, Igor

2016-01-01

The Earth has warmed in the last century and a large component of that warming has been attributed to increased anthropogenic greenhouse gases. There are also numerous processes that introduce strong, regionalized variations to the overall warming trend. However, the ability of a forcing to change the surface air temperature depends on its spatial and temporal distribution. Here we show that the efficacy of a forcing is determined by the effective heat capacity of the atmosphere, which in cold and dry climates is defined by the depth of the planetary boundary layer. This can vary by an order of magnitude on different temporal and spatial scales, and so we get a strongly amplified temperature response in shallow boundary layers. This must be accounted for to assess the efficacy of a climate forcing, and also implies that multiple climate forcings cannot be linearly combined to determine the temperature response. PMID:27221757

The Change of Climate and Terrestrial Carbon Cycle over Tibetan Plateau in CMIP5 Models

NASA Astrophysics Data System (ADS)

Li, S.

2015-12-01

Six earth system models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated over Tibetan Plateau (TP) by comparing the modeled temperature (Tas), precipitation (Pr), net primary production (NPP) and leaf area index (LAI) with the observed Tas, Pr, IGBP NPP and MPIM LAI in the historical, and then we analyzed the change of climate and carbon cycle and explored the relationship between the carbon cycle and main climatic drivers in the historical and representative concentration pathway 4.5 (RCP4.5) simulation over TP. While model results differ, their region spatial distributions from 1971 to 2000 agree reasonably with observed Tas, Pr and proxy LAI and NPP. The climatic variables, LAI and carbon flux vary between two simulations, the ration of NPP to gross primary production (GPP) does not change much in the historical and RCP4.5 scenarios. The linear trends of LAI and carbon flux show an obvious continuous increase from historical climatic period (1971-2000) to the first two climatic periods (2011-2040; 2041-2700) of RCP4.5, then the trends decrease in the third climatic period (2071-2100) of RCP4.5. The cumulative multi model ensemble (MME) net biome production (NBP) is 0.32 kgCm-2yr-1 during 1850 to 2005 and 1.43 kgCm-2yr-1 during 2006 to 2100, the Tibetan Plateau is a carbon sink during the historical scenario, and TP will uptake more carbon from atmosphere during 2006 to 2100 than 1850 to 2005 under RCP4.5 scenario. LAI, GPP, NPP, Ra and Rh appear more related to the Tas than Pr and Rsds, and the Tas is the primary climatic driver for the plant growth and carbon cycle. With the climate change in twenty-first century under RCP4.5 scenario, Tas still is the primary climate driver for the plant growth and carbon cycle, but the effect of temperature on plant growth and carbon cycle gets weaker.

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.

Modelling and economic evaluation of forest biome shifts under climate change in Southwest Germany

Treesearch

Marc Hanewinkel; Susan Hummel; Dominik Cullmann

2010-01-01

We evaluated the economic effects of a predicted shift from Norway spruce (Picea abies) to European beech (Fagus sylvatica) for a forest area of 1.3 million ha in southwest Germany. The shift was modelled with a generalized linear model (GLM) by using presence/absence data from the National Forest Inventory in Baden-Wurttemberg...

Development rates of Late Quaternary soils, Silver Lake Playa, California

USGS Publications Warehouse

Reheis, M.C.; Harden, J.W.; McFadden, L.D.; Shroba, R.R.

1989-01-01

Soils formed on alluvial fan deposits that range in age from about 35 000 to 200 yr BP near Silver Lake playa in the Mojave Desert permit study of the rates of soil development in an arid, hyperthermic climate. Field-described properties of soils were quantified and analyzed using a soil development index that combines properties and horizon thicknesses. Pedogenic CaCO3 (as indicated by color), pH increase, and dry consistence appear to change with age at linear rates, whereas rubification appears to change at a logarithmic rate. The linear rates are best attributed to the progressive accumulation of CaCO3- and salt-rich eolian dust derived from the playa and other mnore distant sources. The total-texture values of soils on fans older than 10 000 yr BP are similar, which suggests that playas in this area may have been wet enough to restrict the availability of fines from these sources for many thousands of years prior to 10 000 yr BP. Equations derived from regressions of soil age and properties can be used to estimate ages of undated, lithologically similar deposits in similar climates and geomorphic settings. -from Authors

How Unusual were Hurricane Harvey's Rains?

NASA Astrophysics Data System (ADS)

Emanuel, K.

2017-12-01

We apply an advanced technique for hurricane risk assessment to evaluate the probability of hurricane rainfall of Harvey's magnitude. The technique embeds a detailed computational hurricane model in the large-scale conditions represented by climate reanalyses and by climate models. We simulate 3700 hurricane events affecting the state of Texas, from each of three climate reanalyses spanning the period 1980-2016, and 2000 events from each of six climate models for each of two periods: the period 1981-2000 from historical simulations, and the period 2081-2100 from future simulations under Representative Concentration Pathway (RCP) 8.5. On the basis of these simulations, we estimate that hurricane rain of Harvey's magnitude in the state of Texas would have had an annual probability of 0.01 in the late twentieth century, and will have an annual probability of 0.18 by the end of this century, with remarkably small scatter among the six climate models downscaled. If the event frequency is changing linearly over time, this would yield an annual probability of 0.06 in 2017.

What Do GDGT Thermometers Tell us About Environmental Changes During the Holocene in Central Africa?

NASA Astrophysics Data System (ADS)

Menot, G.; Garcin, Y.; Bard, E. G.; Deschamps, P.

2017-12-01

Africa has been recognized by the IPCC group as one of the most vulnerable continents to climate change. Validation of models currently used for future climate projections relies in part on their ability to reproduce past climate variability. Especially the past abrupt climatic and environmental events that have punctuated the recent history of the African continent are of prime interest to model the transient and non-linear response of the African monsoon and vegetation to both external forcing and internal feedbacks. The role of temperature among other controls of the hydrological cycle has to be assessed. However, reliable temperature benchmark sequences on continents remain scare and not evenly distributed. The recent discovery of tetraethers as paleothermometer has raised a considerable interest as these lipid biomarkers fill a gap between "quantitative but discrete" and "qualitative but continuous" proxies on continents. Their broad application is however to date hampered by the few constrains on their origin as well as on their dynamics and fates related to pedogenic, transport and sedimentary processes. Previous studies on the lake Barombi (Cameroon) demonstrate the potential of newly retrieved lacustrine sequences to document hydrological changes associated with the African humid Period and vegetation changes related to the late Holocene `rainforest crisis' with an appropriate time resolution. Preliminary reconstructed temperature profile reveals a clear shift at the end of the African Humid Period. Prior any interpretation of a climate signal, a more complete characterization of the tetraether distributions is however needed together with a thorough comparison with other sedimentological proxies. Such an approach should allow identifying the processes that have altered the validity of the tetraether record as changes in soil erosion or lacustrine stratification.

How robust is the pre-1931 National Climatic Data Center—climate divisional dataset? Examples from Georgia and Louisiana

NASA Astrophysics Data System (ADS)

Allard, Jason; Thompson, Clint; Keim, Barry D.

2015-04-01

The National Climatic Data Center's climate divisional dataset (CDD) is commonly used in climate change analyses. This dataset is a spatially continuous dataset for the conterminous USA from 1895 to the present. The CDD since 1931 is computed by averaging all available representative cooperative weather station data into a single monthly value for each of the 344 climate divisions of the conterminous USA, while pre-1931 data for climate divisions are derived from statewide averages using regression equations. This study examines the veracity of these pre-1931 data. All available Cooperative Observer Program (COOP) stations within each climate division in Georgia and Louisiana were averaged into a single monthly value for each month and each climate division from 1897 to 1930 to generate a divisional dataset (COOP DD), using similar methods to those used by the National Climatic Data Center to generate the post-1931 CDD. The reliability of the official CDD—derived from statewide averages—to produce temperature and precipitation means and trends prior to 1931 are then evaluated by comparing that dataset with the COOP DD with difference-of-means tests, correlations, and linear regression techniques. The CDD and the COOP DD are also compared to a divisional dataset derived from the United States Historical Climatology Network (USHCN) data (USHCN DD), with difference of means and correlation techniques, to demonstrate potential impacts of inhomogeneities within the CDD and the COOP DD. The statistical results, taken as a whole, not only indicate broad similarities between the CDD and COOP DD but also show that the CDD does not adequately portray pre-1931 temperature and precipitation in certain climate divisions within Georgia and Louisiana. In comparison with the USHCN DD, both the CDD and the COOP DD appear to be subject to biases that probably result from changing stations within climate divisions. As such, the CDD should be used judiciously for long-term studies of climate change, and past studies using the CDD should be evaluated in the context of these new findings.

Simple but accurate GCM-free approach for quantifying anthropogenic climate change

NASA Astrophysics Data System (ADS)

Lovejoy, S.

2014-12-01

We are so used to analysing the climate with the help of giant computer models (GCM's) that it is easy to get the impression that they are indispensable. Yet anthropogenic warming is so large (roughly 0.9oC) that it turns out that it is straightforward to quantify it with more empirically based methodologies that can be readily understood by the layperson. The key is to use the CO2 forcing as a linear surrogate for all the anthropogenic effects from 1880 to the present (implicitly including all effects due to Greenhouse Gases, aerosols and land use changes). To a good approximation, double the economic activity, double the effects. The relationship between the forcing and global mean temperature is extremely linear as can be seen graphically and understood without fancy statistics, [Lovejoy, 2014a] (see the attached figure and http://www.physics.mcgill.ca/~gang/Lovejoy.htm). To an excellent approximation, the deviations from the linear forcing - temperature relation can be interpreted as the natural variability. For example, this direct - yet accurate approach makes it graphically obvious that the "pause" or "hiatus" in the warming since 1998 is simply a natural cooling event that has roughly offset the anthropogenic warming [Lovejoy, 2014b]. Rather than trying to prove that the warming is anthropogenic, with a little extra work (and some nonlinear geophysics theory and pre-industrial multiproxies) we can disprove the competing theory that it is natural. This approach leads to the estimate that the probability of the industrial scale warming being a giant natural fluctuation is ≈0.1%: it can be dismissed. This destroys the last climate skeptic argument - that the models are wrong and the warming is natural. It finally allows for a closure of the debate. In this talk we argue that this new, direct, simple, intuitive approach provides an indispensable tool for communicating - and convincing - the public of both the reality and the amplitude of anthropogenic warming. ReferencesLovejoy, S. (2014a), Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming, Climate Dynamics, 42, 2339-2351 doi: 10.1007/s00382-014-2128-2. Lovejoy, S. (2014b), Return periods of global climate fluctuations and the pause, Geophys. Res. Lett., 41, 4704-4710 doi: doi: 10.1002/2014GL060478.

Future road salt use in Switzerland: an example of an effective climate service

NASA Astrophysics Data System (ADS)

Zubler, Elias M.; Fischer, Andreas M.; Schlegel, Thomas H.; Liniger, Mark A.

2015-04-01

The application of salt is the predominant measure taken to enhance road safety in Switzerland by clearing the roads from snow or preventing frozen surfaces during winter. The need for road salt exhibits a strong interannual variability, according to Schweizer Salinen AG - the Swiss monopolist for production and distribution of road salt. These fluctuations are to a large extent a direct consequence of the year-to-year variability in winter climate. In the course of the 21st century, Swiss climate is projected to depart significantly from present and past conditions. By the end of the century, winter temperatures over Switzerland are expected to rise by about 2-4°C relative to the mean over the period 1980-2009, while winter precipitation may either increase or decrease based on ENSEMBLES regional climate model projections under the SRES-scenario A1B. Faced with these changes, Schweizer Salinen AG asked for an estimate of the expected future road salt use for designing their long-term business strategy. The study is based on climate change projections from the CH2011 initiative and later extensions thereof as well as monthly sales data of road salt from Schweizer Salinen AG. For the period 1997-2013, a linear relationship was derived between the average number of days with snowfall and the road salt amount sold over "saltation years" defined from October 1st to September 30th in the 26 cantons (provinces) of Switzerland. The ad-hoc linear relationship was applied to the climate change projections to obtain future salt use information in three future periods for the greenhouse gas emission scenarios A1B, A2 and RCP3PD. We find that the expected future salt use is likely to be reduced by about 50% in 2045-2074 under the scenario A1B. Currently, the countrywide mean annual road salt use corresponds to about 220'000 tons. In a particularly snow-rich year, the company sells up to 400'000 tons. At the end of the century, following a pessimistic scenario such as A1B or A2, the long-term mean salt use may even drop below today's annual minimum of 70'000 tons.

Extraction of Urban Morphology Parameters from Generic European Datasets: A Case Study for Antwerp, Berlin and Almada

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart

2014-05-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heat waves. The response of urban societies to the evolving climate depends not only on their regional climate characteristics but also on other local factors such as the urban heat island effect. Simulation of this phenomenon with local urban climate models requires comprehensive information about the urban morphology. This study focusses on the extraction of the planar and frontal area indices from detailed 3D city models and their relationship with the European Soil Sealing Level database from the European Environment Agency. These parameters have been calculated on a 1km2 grid and compared with soil sealing values aggregated at the same spatial resolution. The optimal size of the grid is a trade-off between the level of detail and the robustness of the established relationships by reducing the scatter at small scales. Moreover, the transferability of the results to other geographical areas has been investigated. The analyses have been conducted in the framework of the NACLIM FP7 project funded by the European Commission and include the cities of Antwerp (BE), Berlin (DE) and Almada (PT) represented by different climate and urban characteristics. First results show a correlation of 70% between the planar area index and the averaged soil sealing using a linear regression model at a 1km scale. Moreover, a good correspondence has been found between the relationships for Antwerp and Berlin which is promising for urban climate modellers to reduce model complexity and analyse various climate scenarios in an effective way.

Earth system responses to cumulative carbon emissions

NASA Astrophysics Data System (ADS)

Steinacher, M.; Joos, F.

2015-07-01

Information on the relationship between cumulative fossil carbon emissions and multiple climate targets are essential to design emission mitigation and climate adaptation strategies. In this study, the transient responses in different climate variables are quantified for a large set of multi-forcing scenarios extended to year 2300 towards stabilization and in idealized experiments using the Bern3D-LPJ carbon-climate model. The model outcomes are constrained by 26 physical and biogeochemical observational data sets in a Bayesian, Monte-Carlo type framework. Cumulative fossil emissions of 1000 Gt C result in a global mean surface air temperature change of 1.88 °C (68 % confidence interval (c.i.): 1.28 to 2.69 °C), a decrease in surface ocean pH of 0.19 (0.18 to 0.22), and in steric sea level rise of 20 cm (13 to 27 cm until 2300). Linearity between cumulative emissions and transient response is high for pH and reasonably high for surface air and sea surface temperatures, but less pronounced for changes in Atlantic Meridional Overturning, Southern Ocean and tropical surface water saturation with respect to biogenic structures of calcium carbonate, and carbon stocks in soils. The slopes of the relationships change when CO2 is stabilized. The Transient Climate Response is constrained, primarily by long-term ocean heat observations, to 1.7 °C (68 % c.i.: 1.3 to 2.2 °C) and the Equilibrium Climate Sensitivity to 2.9 °C (2.0 to 4.2 °C). This is consistent with results by CMIP5 models, but inconsistent with recent studies that relied on short-term air temperature data affected by natural climate variability.

Forecasting climate change impacts on the distribution of wetland habitat in the Midwestern United states.

PubMed

Garris, Heath W; Mitchell, Randall J; Fraser, Lauchlan H; Barrett, Linda R

2015-02-01

Shifting precipitation patterns brought on by climate change threaten to alter the future distribution of wetlands. We developed a set of models to understand the role climate plays in determining wetland formation on a landscape scale and to forecast changes in wetland distribution for the Midwestern United States. These models combined 35 climate variables with 21 geographic and anthropogenic factors thought to encapsulate other major drivers of wetland distribution for the Midwest. All models successfully recreated a majority of the variation in current wetland area within the Midwest, and showed that wetland area was significantly associated with climate, even when controlling for landscape context. Inferential (linear) models identified a consistent negative association between wetland area and isothermality. This is likely the result of regular inundation in areas where precipitation accumulates as snow, then melts faster than drainage capacity. Moisture index seasonality was identified as a key factor distinguishing between emergent and forested wetland types, where forested wetland area at the landscape scale is associated with a greater seasonal variation in water table depth. Forecasting models (neural networks) predicted an increase in potential wetland area in the coming century, with areas conducive to forested wetland formation expanding more rapidly than areas conducive to emergent wetlands. Local cluster analyses identified Iowa and Northeastern Missouri as areas of anticipated wetland expansion, indicating both a risk to crop production within the Midwest Corn Belt and an opportunity for wetland conservation, while Northern Minnesota and Michigan are potentially at risk of wetland losses under a future climate. © 2014 John Wiley & Sons Ltd.

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

PubMed Central

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

2015-01-01

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

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the seasonality of centennial/semi-centennial climatic tendencies and dominated oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asia, as well as in the Northwest Pacific SST. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Seasonality of climate change and oscillations in the Northeast Asia and Northwest Pacific

NASA Astrophysics Data System (ADS)

Ponomarev, V.; Salomatin, A.; Kaplunenko, D.; Krokhin, V.

2003-04-01

The main goals of this study are to estimate and compare the centennial/semi-centennial climatic tendencies and oscillations in surface air temperature and precipitation over continental and marginal areas of the Northeast Asian, as well as in the Northwest Pacific SST for all months of a year. We use monthly mean data for the 20th century from the NOAA Global History Climatic Network, JMA data base and WMU/COADS World Atlas of Surface Marine Data. Details of climate change/oscillations associated with cooling or warming in different areas and periods of a year are revealed. Wavelet analyses and two methods of the linear trend estimation are applied. First one is least-squares (LS) method with Fisher’s test for statistical significance level. Second one is nonparametric robust (NR) method, based on Theil's rank regression and Kendall's test for statistical significance level. The NR method should be applied to time series with abnormal distribution function typical for precipitation time series. Application of the NR method result in increase the statistical significance of both positive and negative linear trends in all cases of abnormal distribution with negative/positive skewness and low/high kurtosis. Using this method, we have determined spatial patterns of statistically significant climatic trends in surface air temperature, precipitation in the Northeast Asia, and in the Northwest Pacific SST. The most substantial centennial warming in the vast continental area of the mid-latitude band is found mainly for December March. The semi-centennial/ centennial cooling occurs in South Siberia and the subarctic mid-continental area in June September. Opposite tendencies were also revealed in precipitation and SST. Positive semi-centennial tendency in the SST in the second half of the 20th century predominates in the Kuroshio region and in the northwestern area of the subarctic gyre in winter. Negative tendency in the SST dominates in the southwestern subarctic gyre and the offshore area of the subtropic gyre in summer. Comparison of air temperature, precipitation, SST trends and oscillations in different seasons over land marginal and continental areas, as well as in the subarctic and subtropic zones indicates general features of the Northeast Asian Monsoon change/oscillation in 20th century and its second half. Similar features of seasonality in centennial, semi-centennial trends and dominated oscillations are manifested. Climate change and oscillation in the Northwest Pacific marginal seas revealed for the 20th century are explained.

Dynamic climate emulators for solar geoengineering

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

MacMartin, Douglas G.; Kravitz, Ben

2016-12-22

Climate emulators trained on existing simulations can be used to project project the climate effects that result from different possible future pathways of anthropogenic forcing, without further relying on general circulation model (GCM) simulations. We extend this idea to include different amounts of solar geoengineering in addition to different pathways of greenhouse gas concentrations, by training emulators from a multi-model ensemble of simulations from the Geoengineering Model Intercomparison Project (GeoMIP). The emulator is trained on the abrupt 4 × CO 2 and a compensating solar reduction simulation (G1), and evaluated by comparing predictions against a simulated 1 % per yearmore » CO 2 increase and a similarly smaller solar reduction (G2). We find reasonable agreement in most models for predicting changes in temperature and precipitation (including regional effects), and annual-mean Northern Hemisphere sea ice extent, with the difference between simulation and prediction typically being smaller than natural variability. This verifies that the linearity assumption used in constructing the emulator is sufficient for these variables over the range of forcing considered. Annual-minimum Northern Hemisphere sea ice extent is less well predicted, indicating a limit to the linearity assumption.« less

Trends in Global Vegetation Activity and Climatic Drivers Indicate a Decoupled Response to Climate Change

PubMed Central

Schut, Antonius G. T.; Ivits, Eva; Conijn, Jacob G.; ten Brink, Ben; Fensholt, Rasmus

2015-01-01

Detailed understanding of a possible decoupling between climatic drivers of plant productivity and the response of ecosystems vegetation is required. We compared trends in six NDVI metrics (1982–2010) derived from the GIMMS3g dataset with modelled biomass productivity and assessed uncertainty in trend estimates. Annual total biomass weight (TBW) was calculated with the LINPAC model. Trends were determined using a simple linear regression, a Thiel-Sen medium slope and a piecewise regression (PWR) with two segments. Values of NDVI metrics were related to Net Primary Production (MODIS-NPP) and TBW per biome and land-use type. The simple linear and Thiel-Sen trends did not differ much whereas PWR increased the fraction of explained variation, depending on the NDVI metric considered. A positive trend in TBW indicating more favorable climatic conditions was found for 24% of pixels on land, and for 5% a negative trend. A decoupled trend, indicating positive TBW trends and monotonic negative or segmented and negative NDVI trends, was observed for 17–36% of all productive areas depending on the NDVI metric used. For only 1–2% of all pixels in productive areas, a diverging and greening trend was found despite a strong negative trend in TBW. The choice of NDVI metric used strongly affected outcomes on regional scales and differences in the fraction of explained variation in MODIS-NPP between biomes were large, and a combination of NDVI metrics is recommended for global studies. We have found an increasing difference between trends in climatic drivers and observed NDVI for large parts of the globe. Our findings suggest that future scenarios must consider impacts of constraints on plant growth such as extremes in weather and nutrient availability to predict changes in NPP and CO2 sequestration capacity. PMID:26466347

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield uncertainty that result from different climate model simulation input and bias correction methods. We simulate wheat yields using a General Linear Model that includes the effects of seasonal maximum temperatures and precipitation, since wheat is sensitive to heat stress during important developmental stages. We use the same statistical model to predict future wheat yields using the recently available bias-corrected simulations of EURO-CORDEX-Adjust. While statistical models are often criticized for their lack of complexity, an advantage is that we are here able to consider only the effect of the choice of climate model, resolution or bias correction method on yield. Initial results using both past and future bias-corrected climate simulations with a process-based model will also be presented. Through these methods, we make recommendations in preparing climate model output for crop models.

Evolution of Diurnal Asymmetry of Surface Temperature over Different Climatic Zones

NASA Astrophysics Data System (ADS)

Rajendran, V.; C T, D.; Chakravorty, A.; AghaKouchak, A.

2016-12-01

The increase in drought, flood, diseases, crop failure etc. in the recent past has created an alarm amongst the researchers. One of the main reasons behind the intensification of these environmental hazards is the recent revelation of climate change, which is generally attributed to the human induced global warming, represented by an increase in global mean temperature. However, in order to formulate policies to mitigate and prevent the threats due to global warming, its key driving factors should be analysed at high spatial and temporal resolution. Diurnal Temperature Range (DTR) is one of the indicators of global warming. The study of the evolution of the DTR is crucial, since it affects agriculture, health, ecosystems, transport, etc. Recent studies reveal that diurnal asymmetry has decreased globally, whereas a few regional studies report a contradictory pattern and attributed them to localized feedback processes. However, an evident conclusion cannot be made using the linear trend approaches employed in the past studies and the evolution of diurnal asymmetry should be investigated using non-linear trend approach for better perception. Hence, the regional evolution of DTR trend has been analysed using the spatially-temporally Multidimensional Ensemble Empirical Mode Decomposition (MEEMD) method over India and observed a positive trend in over-all mean of DTR, while its rate of increase has declined in the recent decades. Further, the grids showing negative trend in DTR is observed in arid deserts and warm-temperate grasslands and positive trend over the west coast and sub-tropical forest in the North-East. This transition predominantly began from the west coast and is stretched with an increase in magnitude. These changes are more pronounced during winter and post-monsoon seasons, especially in the arid desert and warm-temperate grasslands, where the rate of increase in minimum temperature is higher than that of the maximum temperature. These analyses suggest that the DTR changes are influenced by both, local and global factors working in tandem, since a warmed up ocean produces contradictory DTR trends in different climatic zones. It can be inferred from this study that the impact of a global change in a region will depend on the regional climate.

Response of streamflow to projected climate change scenarios in an eastern Himalayan catchment of India

NASA Astrophysics Data System (ADS)

Senzeba, K. T.; Rajkumari, S.; Bhadra, A.; Bandyopadhyay, A.

2016-04-01

Snowmelt run-off model (SRM) based on degree-day approach has been employed to evaluate the change in snow-cover depletion and corresponding streamflow under different projected climatic scenarios for an eastern Himalayan catchment in India. Nuranang catchment located at Tawang district of Arunachal Pradesh with an area of 52 km2 is selected for the present study with an elevation range of 3143-4946 m above mean sea level. Satellite images from October to June of the selected hydrological year 2006-2007 were procured from National Remote Sensing Centre, Hyderabad. Snow cover mapping is done using NDSI method. Based on long term meteorological data, temperature and precipitation data of selected hydrological year are normalized to represent present climatic condition. The projected temperature and precipitation data are downloaded from NCAR's GIS data portal for different emission scenarios (SRES), viz., A1B, A2, B1; and IPCC commitment (non-SRES) scenario for different future years (2020, 2030, 2040 and 2050). Projected temperature and precipitation data are obtained at desired location by spatially interpolating the gridded data and then by statistical downscaling using linear regression. Snow depletion curves for all projected scenarios are generated for the study area and compared with conventional depletion curve for present climatic condition. Changes in cumulative snowmelt depth for different future years are highest under A1B and lowest under IPCC commitment, whereas A2 and B1 values are in-between A1B and IPCC commitment. Percentage increase in streamflow for different future years follows almost the same trend as change in precipitation from present climate under all projected climatic scenarios. Hence, it was concluded that for small catchments having seasonal snow cover, the total streamflow under projected climatic scenarios in future years will be primarily governed by the change in precipitation and not by change in snowmelt depth. Advancing of depletion curves for different future years are highest under A1B and lowest under IPCC commitment. A2 and B1 values are in-between A1B and IPCC commitment.

Biome changes in Asia since the mid-Holocene - an analysis of different transient Earth system model simulations

NASA Astrophysics Data System (ADS)

Dallmeyer, Anne; Claussen, Martin; Ni, Jian; Cao, Xianyong; Wang, Yongbo; Fischer, Nils; Pfeiffer, Madlene; Jin, Liya; Khon, Vyacheslav; Wagner, Sebastian; Haberkorn, Kerstin; Herzschuh, Ulrike

2017-02-01

The large variety of atmospheric circulation systems affecting the eastern Asian climate is reflected by the complex Asian vegetation distribution. Particularly in the transition zones of these circulation systems, vegetation is supposed to be very sensitive to climate change. Since proxy records are scarce, hitherto a mechanistic understanding of the past spatio-temporal climate-vegetation relationship is lacking. To assess the Holocene vegetation change and to obtain an ensemble of potential mid-Holocene biome distributions for eastern Asia, we forced the diagnostic biome model BIOME4 with climate anomalies of different transient Holocene climate simulations performed in coupled atmosphere-ocean(-vegetation) models. The simulated biome changes are compared with pollen-based biome records for different key regions.In all simulations, substantial biome shifts during the last 6000 years are confined to the high northern latitudes and the monsoon-westerly wind transition zone, but the temporal evolution and amplitude of change strongly depend on the climate forcing. Large parts of the southern tundra are replaced by taiga during the mid-Holocene due to a warmer growing season and the boreal treeline in northern Asia is shifted northward by approx. 4° in the ensemble mean, ranging from 1.5 to 6° in the individual simulations, respectively. This simulated treeline shift is in agreement with pollen-based reconstructions from northern Siberia. The desert fraction in the transition zone is reduced by 21 % during the mid-Holocene compared to pre-industrial due to enhanced precipitation. The desert-steppe margin is shifted westward by 5° (1-9° in the individual simulations). The forest biomes are expanded north-westward by 2°, ranging from 0 to 4° in the single simulations. These results corroborate pollen-based reconstructions indicating an extended forest area in north-central China during the mid-Holocene. According to the model, the forest-to-non-forest and steppe-to-desert changes in the climate transition zones are spatially not uniform and not linear since the mid-Holocene.

Time-varying trends of global vegetation activity

NASA Astrophysics Data System (ADS)

Pan, N.; Feng, X.; Fu, B.

2016-12-01

Vegetation plays an important role in regulating the energy change, water cycle and biochemical cycle in terrestrial ecosystems. Monitoring the dynamics of vegetation activity and understanding their driving factors have been an important issue in global change research. Normalized Difference Vegetation Index (NDVI), an indicator of vegetation activity, has been widely used in investigating vegetation changes at regional and global scales. Most studies utilized linear regression or piecewise linear regression approaches to obtain an averaged changing rate over a certain time span, with an implicit assumption that the trend didn't change over time during that period. However, no evidence shows that this assumption is right for the non-linear and non-stationary NDVI time series. In this study, we adopted the multidimensional ensemble empirical mode decomposition (MEEMD) method to extract the time-varying trends of NDVI from original signals without any a priori assumption of their functional form. Our results show that vegetation trends are spatially and temporally non-uniform during 1982-2013. Most vegetated area exhibited greening trends in the 1980s. Nevertheless, the area with greening trends decreased over time since the early 1990s, and the greening trends have stalled or even reversed in many places. Regions with browning trends were mainly located in southern low latitudes in the 1980s, whose area decreased before the middle 1990s and then increased at an accelerated rate. The greening-to-browning reversals were widespread across all continents except Oceania (43% of the vegetated areas), most of which happened after the middle 1990s. In contrast, the browning-to-greening reversals occurred in smaller area and earlier time. The area with monotonic greening and browning trends accounted for 33% and 5% of the vegetated area, respectively. By performing partial correlation analyses between NDVI and climatic elements (temperature, precipitation and cloud cover) and analyzing the MEEMD-extracted trends of these climatic elements, we discussed possible driving factors of the time-varying trends of NDVI in several specific regions where trend reversals occurred.

Diagnosis and Quantification of Climatic Sensitivity of Carbon Fluxes in Ensemble Global Ecosystem Models

NASA Astrophysics Data System (ADS)

Wang, W.; Hashimoto, H.; Milesi, C.; Nemani, R. R.; Myneni, R.

2011-12-01

Terrestrial ecosystem models are primary scientific tools to extrapolate our understanding of ecosystem functioning from point observations to global scales as well as from the past climatic conditions into the future. However, no model is nearly perfect and there are often considerable structural uncertainties existing between different models. Ensemble model experiments thus become a mainstream approach in evaluating the current status of global carbon cycle and predicting its future changes. A key task in such applications is to quantify the sensitivity of the simulated carbon fluxes to climate variations and changes. Here we develop a systematic framework to address this question solely by analyzing the inputs and the outputs from the models. The principle of our approach is to assume the long-term (~30 years) average of the inputs/outputs as a quasi-equlibrium of the climate-vegetation system while treat the anomalies of carbon fluxes as responses to climatic disturbances. In this way, the corresponding relationships can be largely linearized and analyzed using conventional time-series techniques. This method is used to characterize three major aspects of the vegetation models that are mostly important to global carbon cycle, namely the primary production, the biomass dynamics, and the ecosystem respiration. We apply this analytical framework to quantify the climatic sensitivity of an ensemble of models including CASA, Biome-BGC, LPJ as well as several other DGVMs from previous studies, all driven by the CRU-NCEP climate dataset. The detailed analysis results are reported in this study.

Direct and indirect climatic drivers of biotic interactions: ice-cover and carbon runoff shaping Arctic char Salvelinus alpinus and brown trout Salmo trutta competitive asymmetries.

PubMed

Ulvan, Eva M; Finstad, Anders G; Ugedal, Ola; Berg, Ole Kristian

2012-01-01

One of the major challenges in ecological climate change impact science is to untangle the climatic effects on biological interactions and indirect cascading effects through different ecosystems. Here, we test for direct and indirect climatic drivers on competitive impact of Arctic char (Salvelinus alpinus L.) on brown trout (Salmo trutta L.) along a climate gradient in central Scandinavia, spanning from coastal to high-alpine environments. As a measure of competitive impact, trout food consumption was measured using (137)Cs tracer methodology both during the ice-covered and ice-free periods, and contrasted between lakes with or without char coexistence along the climate gradient. Variation in food consumption between lakes was best described by a linear mixed effect model including a three-way interaction between the presence/absence of Arctic char, season and Secchi depth. The latter is proxy for terrestrial dissolved organic carbon run-off, strongly governed by climatic properties of the catchment. The presence of Arctic char had a negative impact on trout food consumption. However, this effect was stronger during ice-cover and in lakes receiving high carbon load from the catchment, whereas no effect of water temperature was evident. In conclusion, the length of the ice-covered period and the export of allochthonous material from the catchment are likely major, but contrasting, climatic drivers of the competitive interaction between two freshwater lake top predators. While future climatic scenarios predict shorter ice-cover duration, they also predict increased carbon run-off. The present study therefore emphasizes the complexity of cascading ecosystem effects in future effects of climate change on freshwater ecosystems.

Aridity changes in the Tibetan Plateau in a warming climate

DOE PAGES

Gao, Yanhong; Li, Xia; Leung, Lai-Yung R.; ...

2015-03-10

Desertification in the Tibetan Plateau (TP) has drawn increasing attention in the recent decades. It has been postulated as a consequence of climate aridity due to the observed warming. This study quantifies the aridity changes in the TP and attributes the changes to different climatic factors. Using the ratio of P/PET (precipitation to potential evapotranspiration) as an aridity index to indicate changes in dryness and wetness in a given area, P/PET was calculated using observed records at 83 stations in the TP, with PET calculated using the Penman–Monteith (PM) algorithm. Spatial and temporal changes of P/PET in 1979-2011 are analyzed.more » Results show that stations located in the arid and semi-arid northwestern TP are becoming significantly wetter and stations in the semi-humid southeastern TP are becoming drier, though not significantly, in the recent three decades. The aridity change patterns are significantly correlated with precipitation, sunshine duration and diurnal temperature range changes at confidence level of 99.9% from two-tail t-test. Temporal correlations also confirm the significant correlation between aridity changes with the three variables, with precipitation being the most dominant driver of P/PET changes at interannual time scale. PET changes are insignificant but negatively correlated with P/PET in the cold season. In the warm season, however, correlation between PET changes and P/PET changes are significant at confidence level of 99.9% when the cryosphere melts near the surface. Significant correlation between wind speed changes and aridity changes occurs in limited locations and months. Consistency in the climatology pattern and linear trends in surface air temperature and precipitation calculated using station data, gridded data, and nearest grid-to-stations for the TP average and across sub-basins indicate the robustness of the trends despite the large spatial heterogeneity in the TP that challenge climate monitoring.« less

Evaluation of mean climate in a chemistry-climate model simulation

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Response of Korean pine’s functional traits to geography and climate

PubMed Central

Dong, Yichen

2017-01-01

This study analyzed the characteristics of Korean pine (Pinus koraiensis) functional trait responses to geographic and climatic factors in the eastern region of Northeast China (41°–48°N) and the linear relationships among Korean pine functional traits, to explore this species’ adaptability and ecological regulation strategies under different environmental conditions. Korean pine samples were collected from eight sites located at different latitudes, and the following factors were determined for each site: geographic factors—latitude, longitude, and altitude; temperature factors—mean annual temperature (MAT), growth season mean temperature (GST), and mean temperature of the coldest month (MTCM); and moisture factors—annual precipitation (AP), growth season precipitation (GSP), and potential evapotranspiration (PET). The Korean pine functional traits examined were specific leaf area (SLA), leaf thickness (LT), leaf dry matter content (LDMC), specific root length (SRL), leaf nitrogen content (LNC), leaf phosphorus content (LPC), root nitrogen content (RNC), and root phosphorus content (RPC). The results showed that Korean pine functional traits were significantly correlated to latitude, altitude, GST, MTCM, AP, GSP, and PET. Among the Korean pine functional traits, SLA showed significant linear relationships with LT, LDMC, LNC, LPC, and RPC, and LT showed significant linear relationships with LDMC, SRL, LNC, LPC, RNC, and RPC; the linear relationships between LNC, LPC, RNC, and RPC were also significant. In conclusion, Korean pine functional trait responses to latitude resulted in its adaptation to geographic and climatic factors. The main limiting factors were precipitation and evapotranspiration, followed by altitude, latitude, GST, and MTCM. The impacts of longitude and MAT were not obvious. Changes in precipitation and temperature were most responsible for the close correlation among Korean pine functional traits, reflecting its adaption to habitat variation. PMID:28886053

Response of Korean pine's functional traits to geography and climate.

PubMed

Dong, Yichen; Liu, Yanhong

2017-01-01

This study analyzed the characteristics of Korean pine (Pinus koraiensis) functional trait responses to geographic and climatic factors in the eastern region of Northeast China (41°-48°N) and the linear relationships among Korean pine functional traits, to explore this species' adaptability and ecological regulation strategies under different environmental conditions. Korean pine samples were collected from eight sites located at different latitudes, and the following factors were determined for each site: geographic factors-latitude, longitude, and altitude; temperature factors-mean annual temperature (MAT), growth season mean temperature (GST), and mean temperature of the coldest month (MTCM); and moisture factors-annual precipitation (AP), growth season precipitation (GSP), and potential evapotranspiration (PET). The Korean pine functional traits examined were specific leaf area (SLA), leaf thickness (LT), leaf dry matter content (LDMC), specific root length (SRL), leaf nitrogen content (LNC), leaf phosphorus content (LPC), root nitrogen content (RNC), and root phosphorus content (RPC). The results showed that Korean pine functional traits were significantly correlated to latitude, altitude, GST, MTCM, AP, GSP, and PET. Among the Korean pine functional traits, SLA showed significant linear relationships with LT, LDMC, LNC, LPC, and RPC, and LT showed significant linear relationships with LDMC, SRL, LNC, LPC, RNC, and RPC; the linear relationships between LNC, LPC, RNC, and RPC were also significant. In conclusion, Korean pine functional trait responses to latitude resulted in its adaptation to geographic and climatic factors. The main limiting factors were precipitation and evapotranspiration, followed by altitude, latitude, GST, and MTCM. The impacts of longitude and MAT were not obvious. Changes in precipitation and temperature were most responsible for the close correlation among Korean pine functional traits, reflecting its adaption to habitat variation.

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

NASA Astrophysics Data System (ADS)

Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.

Sensitivity of spectral climate signals to the emissions of atmospheric dust

NASA Astrophysics Data System (ADS)

Xu, X.; Wang, J.; Wang, Y.; Henze, D. K.; Zhang, L.

2015-12-01

Mineral dust particles profoundly influence the Earth climate due to their varied affects on the radiation and cloud physics. The knowledge of dust emissions from daily to seasonal scales is thus important for interpreting the past and predicting the future climate changes. Satellite measured radiances in the shortwave and thermal infrared are sensitive to the amount and properties of mineral dust present in the atmosphere. Therefore, the climate (i.e., monthly averages) of these reflectance spectra could contain valuable information on the change of dust emissions. In this work, we investigate the feasibility of using the climate of spectral radiances for recovering dust emissions. An observation simulation system (OSS) that incorporates the Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) with forward and adjoint global chemistry transport models (GEOS-Chem and FIM-Chem) has been applied to generate synthetic hyperspectral climate data in the shortwave and thermal infrared (TIR) for summer 2008. Along with the calculation of radiances at the top of the atmosphere (TOA), the OSS also computes their Jacobians of these synthetic data to dust optical depth, plume height, and effective radius, as well as the adjoint gradients of spectral radiances to dust emissions. We found that the brightness temperature (BT) in the TIR spectra at TOA is sensitive to both of the dust plume height and particle size. For the same relative changes of these parameters, BT shows largest change with respect to particle size at the wavenumber of 890-1200 cm-1. This demonstrates the potential for retrieving three-dimensional dust information along with the particle size from hyperspectral TIR measurements. We also assess the information content of monthly versus instantaneous radiances for constraining dust emissionsthe from the calculated adjoint gradients. Our analysis may guide new applications of long-term spectral radiance measurements (such as those from GOME, AIRS, IASI, and CrIS instruments) to constrain dust sources, and thus reduce uncertainty in our broader understanding of the impacts of mineral dust on climate.

Vegetation physiology controls continental water cycle responses to climate change

NASA Astrophysics Data System (ADS)

Lemordant, L. A.; Swann, A. L. S.; Cook, B.; Scheff, J.; Gentine, P.

2017-12-01

Abstract per se:Predicting how climate change will affect the hydrologic cycle is of utmost importance for ecological systems and for human life and activities. A typical perspective is that global warming will cause an intensification of the mean state, the so-called "dry gets drier, wet gets wetter" paradigm. While this result is robust over the oceans, recent works suggest it may be less appropriate for terrestrial regions. Using Earth System Models (ESMs) with decoupled surface (vegetation physiology, PHYS) and atmospheric (radiative, ATMO) CO2 responses, we show that the CO2 physiological response dominates the change in the continental hydrologic cycle compared to radiative and precipitation changes due to increased atmospheric CO2, counter to previous assumptions. Using multiple linear regression analysis, we estimate the individual contribution of each of the three main drivers, precipitation, radiation and physiological CO2 forcing (see attached figure). Our analysis reveals that physiological effects dominate changes for 3 key indicators of dryness and/or vegetation stress (namely LAI, P-ET and EF) over the largest fraction of the globe, except for soil moisture which exhibits a more complex response. This highlights the key role of vegetation in controlling future terrestrial hydrologic response.Legend of the Figure attached:Decomposition along the three main drivers of LAI (a), P-ET (b), EF (c) in the control run. Green quantifies the effect of the vegetation physiology based on the run PHYS; red and blue quantify the contribution of, respectively, net radiation and precipitation, based on multiple linear regression in ATMO. Pie charts show for each variable the fraction (labelled in %) of land under the main influence (more than 50% of the changes is attributed to this driver) of one the three main drivers (green for grid points dominated by vegetation physiology, red for grid points dominated by net radiation, and blue for grid points dominated by the precipitation), and under no single driver influence (grey). Based on an article in review at Nature Climate Change as of Aug, 2nd 2017

Assessing non-linear variation of temperature and precipitation for different growth periods of maize and their impacts on phenology in the Midwest of Jilin Province, China

NASA Astrophysics Data System (ADS)

Guo, Enliang; Zhang, Jiquan; Wang, Yongfang; Alu, Si; Wang, Rui; Li, Danjun; Ha, Si

2018-05-01

In the past two decades, the regional climate in China has undergone significant change, resulting in crop yield reduction and complete failure. The goal of this study is to detect the variation of temperature and precipitation for different growth periods of maize and assess their impact on phenology. The daily meteorological data in the Midwest of Jilin Province during 1960-2014 were used in the study. The ensemble empirical mode decomposition method was adopted to analyze the non-linear trend and fluctuation in temperature and precipitation, and the sensitivity of the length of the maize growth period to temperature and precipitation was analyzed by the wavelet cross-transformation method. The results show that the trends of temperature and precipitation change are non-linear for different growth periods of maize, and the average temperature in the sowing-jointing stage was different from that in the other growth stages, showing a slight decrease trend, while the variation amplitude of maximum temperature is smaller than that of the minimum temperature. This indicates that the temperature difference between day and night shows a gradually decreasing trend. Precipitation in the growth period also showed a decreasing non-linear trend, while the inter-annual variability with period of quasi-3-year and quasi-6-year dominated the variation of temperature and precipitation. The whole growth period was shortened by 10.7 days, and the sowing date was advanced by approximately 11 days. We also found that there was a significant resonance period among temperature, precipitation, and phenology. Overall, a negative correlation between phenology and temperature is evident, while a positive correlation with precipitation is exhibited. The results illustrate that the climate suitability for maize has reduced over the past decades.

Changes in Cirrus Cloudiness and their Relationship to Contrails

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Ayers, J. Kirk; Palikonda, Rabindra; Doelling, David R.; Schumann, Ulrich; Gierens, Klaus

2001-01-01

Condensation trails, or contrails, formed in the wake of high-altitude aircraft have long been suspected of causing the formation of additional cirrus cloud cover. More cirrus is possible because 10 - 20% of the atmosphere at typical commercial flight altitudes is clear but ice-saturated. Since they can affect the radiation budget like natural cirrus clouds of equivalent optical depth and microphysical properties, contrail -generated cirrus clouds are another potential source of anthropogenic influence on climate. Initial estimates of contrail radiative forcing (CRF) were based on linear contrail coverage and optical depths derived from a limited number of satellite observations. Assuming that such estimates are accurate, they can be considered as the minimum possible CRF because contrails often develop into cirrus clouds unrecognizable as contrails. These anthropogenic cirrus are not likely to be identified as contrails from satellites and would, therefore, not contribute to estimates of contrail coverage. The mean lifetime and coverage of spreading contrails relative to linear contrails are needed to fully assess the climatic effect of contrails, but are difficult to measure directly. However, the maximum possible impact can be estimated using the relative trends in cirrus coverage over regions with and without air traffic. In this paper, the upper bound of CRF is derived by first computing the change in cirrus coverage over areas with heavy air traffic relative to that over the remainder of the globe assuming that the difference between the two trends is due solely to contrails. This difference is normalized to the corresponding linear contrail coverage for the same regions to obtain an average spreading factor. The maximum contrail-cirrus coverage, estimated as the product of the spreading factor and the linear contrail coverage, is then used in the radiative model to estimate the maximum potential CRF for current air traffic.

A large-scale integrated karst-vegetation recharge model to understand the impact of climate and land cover change

NASA Astrophysics Data System (ADS)

Sarrazin, Fanny; Hartmann, Andreas; Pianosi, Francesca; Wagener, Thorsten

2017-04-01

Karst aquifers are an important source of drinking water in many regions of the world, but their resources are likely to be affected by changes in climate and land cover. Karst areas are highly permeable and produce large amounts of groundwater recharge, while surface runoff is typically negligible. As a result, recharge in karst systems may be particularly sensitive to environmental changes compared to other less permeable systems. However, current large-scale hydrological models poorly represent karst specificities. They tend to provide an erroneous water balance and to underestimate groundwater recharge over karst areas. A better understanding of karst hydrology and estimating karst groundwater resources at a large-scale is therefore needed for guiding water management in a changing world. The first objective of the present study is to introduce explicit vegetation processes into a previously developed karst recharge model (VarKarst) to better estimate evapotranspiration losses depending on the land cover characteristics. The novelty of the approach for large-scale modelling lies in the assessment of model output uncertainty, and parameter sensitivity to avoid over-parameterisation. We find that the model so modified is able to produce simulations consistent with observations of evapotranspiration and soil moisture at Fluxnet sites located in carbonate rock areas. Secondly, we aim to determine the model sensitivities to climate and land cover characteristics, and to assess the relative influence of changes in climate and land cover on aquifer recharge. We perform virtual experiments using synthetic climate inputs, and varying the value of land cover parameters. In this way, we can control for variations in climate input characteristics (e.g. precipitation intensity, precipitation frequency) and vegetation characteristics (e.g. canopy water storage capacity, rooting depth), and we can isolate the effect that each of these quantities has on recharge. Our results show that these factors are strongly interacting and are generating non-linear responses in recharge.

Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future

USGS Publications Warehouse

Homer, Collin G.; Xian, George Z.; Aldridge, Cameron L.; Meyer, Debra K.; Loveland, Thomas R.; O'Donnell, Michael S.

2015-01-01

Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus urophasianus) habitat models to evaluate the effects of potential climate-induced habitat change. Under the 2050 IPCC A1B scenario, 11.6% of currently identified nesting habitat was lost, and 0.002% of new potential habitat was gained, with 4% of summer habitat lost and 0.039% gained. Our results demonstrate the successful ability of remote sensing based sagebrush components, when coupled with precipitation, to forecast future component response using IPCC precipitation scenarios. Our approach also enables future quantification of greater sage-grouse habitat under different precipitation scenarios, and provides additional capability to identify regional precipitation influence on sagebrush component response.

Forest defoliators and climatic change: Potential changes in spatial distribution of outbreaks of western spruce budworm (Lepidoptera: Tortricidae) and gypsy moth (Lepidoptera: Lymantriidae)

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

Williams, D.W.; Liebhold, A.M.

1995-02-01

Changes in geographical ranges and spatial extent of outbreaks of pest species are likely consequences of climatic change. We investigated potential changes in spatial distribution of outbreaks of western spruce budworm, Choristoneura occidentalis Freeman, and gypsy moth, Lymantria dispar (L.), in Oregon and Pennsylvania, respectively using maps of historial defoliation, climate, and forest type in a geographic information system. Maps of defoliation frequency at a resolution of 2 x 2 km were assembled from historical aerial survey data. Weather maps for mean monthly temperature maxima and minima and precipitation over 30 yr were developed by interpolation. Relationships between defoliation statusmore » and environmental variables were estimated using linear discriminant analysis. Five climatic change scenarios were investigated: an increase of 2{degrees}C, a 2{degrees}C increase with a small increase and a small decrease in precipitation, and projections of two general circulation models (GCMs) after 100 yr at doubled carbon dioxide. With an increase in temperature alone, the projected defoliated area decreased relative to ambient conditions for budworm and increased slightly for gypsy moth. With an increase in temperature and precipitation, defoliated area increased for both species. Conversely, defoliated area decreased for both when temperature increased and precipitation decreased. Results for the GCM scenarios contrasted sharply. For one GCM, defoliation by budworm was projected to cover Oregon completely, whereas no defoliation was projected by gypsy moth in Pennsylvania. For the other, defoliation disappeared completely for budworm and slightly exceeded that under ambient conditions for gypsy moth. The results are discussed in terms of current forest composition and its potential changes. 36 refs., 5 figs., 4 tabs.« less

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980–2010

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

Leng, Guoyong

Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (RGST_CY) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in associationmore » with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K~-3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in RGST_CY are mainly observed in Midwest Corn Belt and central High Plains, and are well reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period.« less

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980-2010.

PubMed

Leng, Guoyong

2017-12-15

Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO 2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (R GST_CY ) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in association with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K--3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in R GST_CY are mainly observed in Midwest Corn Belt and central High Plains, but are partly reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period. Copyright © 2017 Elsevier B.V. All rights reserved.

Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality, than in raw time series. The developers and users of homogenisation methods have to bear in mind that the eventual purpose of homogenisation is not to find change-points, but to have the observed time series with statistical properties those characterise well the climate change and climate variability.

On predicting future economic losses from tropical cyclones: Comparing damage functions for the Eastern USA

NASA Astrophysics Data System (ADS)

Geiger, Tobias; Levermann, Anders; Frieler, Katja

2015-04-01

Recent years have seen an intense scientific debate of what to expect from future tropical cyclone activity under climate change [1,2]. Besides the projection of cyclones' genesis points and trajectories it is the cyclone's impact on future societies that needs to be quantified. In our present work, where we focus on the Eastern USA, we start out with a comprehensive comparison of a variety of presently available and novel functional relationships that are used to link cyclones' physical properties with their damage caused on the ground. These so-called damage functions make use of high quality data sets consisting of gridded population data, exposed capital at risk, and information on the cyclone's extension and its translational and locally resolved maximum wind speed. Based on a cross-validation ansatz we train a multitude of damage functions on a large variety of data sets in order to evaluate their performance on an equally sized test sample. Although different damage analyses have been conducted in the literature [3,4,5,6], the efforts have so far primarily been focused on determining fit parameters for individual data sets. As our analysis consists of a wide range of damage functions implemented on identical data sets, we can rigorously evaluate which (type of) damage function (for which set of parameters) does best in reproducing damages and should therefore be used for future loss analysis with highest certainty. We find that the benefits of using locally resolved data input tend to be outweighed by the large uncertainties that accompany the data. More coarse and generalized data input therefore captures the diversity of cyclonic features better. Furthermore, our analysis shows that a non-linear relation between wind speed and damage outperforms the linear as well as the exponential relationship discussed in the literature. In a second step, the damage function with the highest predictive quality is implemented to predict potential future cyclone losses for the Eastern USA until the year 2100. The projection is based on downscaling five different GCM model runs for the RCP8.5 scenario, as conducted by Emanuel et al. [7], and accounts for population and GDP changes relying on the newly developed Shared Socioenonomic Pathways (SSPs) [8]. We hereby contribute valuable input to the scientific community as well as the societies at risk. The possibility of extending this work to different regions in order to access the future impact of tropical cyclones on a global scale will also be discussed. References [1] Thomas R. Knutson, John L. McBride, Johnny Chan, Kerry Emanuel, Greg Holland, Chris Landsea, Isaac Held, James P. Kossin, A. K. Srivastava, and Masato Sugi. Tropical cyclones and climate change. Nature Geoscience, 3(3):157-163, 2010. [2] Robert Mendelsohn, Kerry Emanuel, Shun Chonabayashi, and Laura Bakkensen. The impact of climate change on global tropical cyclone damage. Nature Climate Change, 2(3):205-209, 2012. [3] Silvio Schmidt, Claudia Kemfert, and Peter Höppe. The impact of socio-economics and climate change on tropical cyclone losses in the USA. Regional Environmental Change, 10(1):13-26, 2009. [4] William D. Nordhaus. The Economics of Hurricanes and Implications of Global Warming. Climate Change Economics, 01(01):1-20, 2010. [5] Kerry Emanuel. Global Warming Effects on U.S. Hurricane Damage. Weather, Climate, and Society, 3(4):261-268, 2011. [6] Richard J. Murnane and James B. Elsner. Maximum wind speeds and US hurricane losses. Geophysical Research Letters, 39(16):707, 2012. [7] Kerry Emanuel. Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proceedings of the National Academy of Sciences of the United States of America, 110(30):12219-24, 2013. [8] Detlef P. van Vuuren, Keywan Riahi, and Richard Moss. A proposal for a new scenario framework to support research and assessment in different climate research communities. Global Environmental Change, 22(1):21-35, 2012.

Historical influence of irrigation on climate extremes

NASA Astrophysics Data System (ADS)

Thiery, Wim; Davin, Edouard L.; Lawrence, Dave; Hauser, Mathias; Seneviratne, Sonia I.

2016-04-01

Land irrigation is an essential practice sustaining global food production and many regional economies. During the last decades, irrigation amounts have been growing rapidly. Emerging scientific evidence indicates that land irrigation substantially affects mean climate conditions in different regions of the world. However, a thorough understanding of the impact of irrigation on extreme climatic conditions, such as heat waves, droughts or intense precipitation, is currently still lacking. In this context, we aim to assess the historical influence of irrigation on the occurrence of climate extremes. To this end, two simulations are conducted over the period 1910-2010 with a state-of-the-art global climate model (the Community Earth System Model, CESM): a control simulation including all major anthropogenic and natural external forcings except for irrigation and a second experiment with transient irrigation enabled. The two simulations are evaluated for their ability to represent (i) hot, dry and wet extremes using the HadEX2 and ERA-Interim datasets as a reference, and (ii) latent heat fluxes using LandFlux-EVAL. Assuming a linear combination of climatic responses to different forcings, the difference between both experiments approximates the influence of irrigation. We will analyse the impact of irrigation on a number of climate indices reflecting the intensity and duration of heat waves. Thereby, particular attention is given to the role of soil moisture changes in modulating climate extremes. Furthermore, the contribution of individual biogeophysical processes to the total impact of irrigation on hot extremes is quantified by application of a surface energy balance decomposition technique to the 90th and 99th percentile surface temperature changes.

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.

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

PubMed

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China

NASA Astrophysics Data System (ADS)

Maimaitiaili, Ayisulitan; Aji, xiaokaiti; Kondoh, Akihiko

2016-04-01

Multi Satellites Monitoring of Land Use/Cover Change and Its Driving Forces in Kashgar Region, China Ayisulitan Maimaitiaili1, Xiaokaiti Aji2 Akihiko Kondoh2 1Graduate School of Science, Chiba University, Japan 2Center for Environmental Remote Sensing, Chiba University The spatio-temporal changes of Land Use/Cover (LUCC) and its driving forces in Kashgar region, Xinjiang Province, China, are investigated by using satellite remote sensing and a geographical information system (GIS). Main goal of this paper is to quantify the drivers of LUCC. First, considering lack of the Land Cover (LC) map in whole study area, we produced LC map by using Landsat images. Land use information from Landsat data was collected using maximum likelihood classification method. Land use change was studied based on the change detection method of land use types. Second, because the snow provides a key water resources for stream flow, agricultural production and drinking water for sustaining large population in Kashgar region, snow cover are estimated by Spot Vegetation data. Normalized Difference Snow Index (NDSI) algorithm are applied to make snow cover map, which is used to screen the LUCC and climate change. The best agreement is found with threshold value of NDSI≥0.2 to generate multi-temporal snow cover and snowmelt maps. Third, driving forces are systematically identified by LC maps and statistical data such as climate and socio-economic data, regarding to i) the climate changes and ii) socioeconomic development that the spatial correlation among LUCC, snow cover change, climate and socioeconomic changes are quantified by using liner regression model and negative / positive trend analysis. Our results showed that water bodies, bare land and grass land have decreasing notably. By contrast, crop land and urban area have continually increasing significantly, which are dominated in study area. The area of snow/ice have fluctuated and has strong seasonal trends, total annual snow cover has two peaks in 2005 and 2009. With increasing population from 2,324,375 in 1984 to 4,228,200 in 2014 and crop land reclamation from 6031.4 km2 in 1972 to 16549km2 in 2014 at the study area. Water resources consumption increased with support to large population and irrigate whole crop land area, caused the water shortages that the surface water bodies decreased from 2531.43km2 in the 1972s to 1067.05km2 in the 2014. The grass land with an acreage larger than 6749km2 in 1972 decreased to 922.6 km2 in 2014. The transformations between water bodies, garss land and bare land are remarkbale. The results also suggested high linearity between the LUCC and socioeconomic changes that specific land cover change be cause of the fact that socioeconomic development. In the recent 42 years, average annual temperature have been increasing significantly, although, precipitation have increased but partly weaken effect of the rising temperature, in addition snow cover more sensitive to precipitation than temperature. Results the change of climate showed a nagitive relationship between the NDSI with decrased of the snow cover and climate with increasing of the tempreature. Morover, the relationship between the LUCC and snow cover recorded higher linearity, because the temperature have increased, consequence influence on snow cover that provides melt water for study area which expanding crop land.

Precipitation Change during 1460—2011 in the Upper Lancang River Basin

NASA Astrophysics Data System (ADS)

Shang, H.; Hong, J.; Fan, Z.; Chen, F.; Yu, S.; Wei, W.; Zhang, R.

2017-12-01

Tibetan plateau is the hotspot for climate change research. The long-lived needle leave trees provide valuabe proxies for past change, due to the extreme cold and arid climate conditions. Three tree ring width chronologies and the composite chronology of Picea likiangensis var. balfouriana are developed in the Upper Lancang River Basin of northeastern Tibet. Correlation analysis revealed that the total precipitation from previous October to May in the current year is the dominated climatic factors which limit its radial growth. The linear transfer function is set up to reconstruct the precipitation history during AD1460—2011. The reconstructed series revealed 5 main wet periods (1512 1533, 1551 1630, 1771 1790, 1838 1862, 1976 2011) and six drought periods (1460 1511, 1591 1614, 1659 1729, 1730 1770, 1791 1837, 1892 1930). Spatial correlation analysis demonstrated the reconstructed series could capture the regional precipitation change in the eastern Tibet (94°E 100°E, 29°N 33°N). Comparison between this study and other tree ring precipitation record in the surrounding area reveals the basically consistency and reflect the common wetting trend in the past 20 years. Meanwhile, the longest wet period (1659 1729) and the drought period in the early 20th century in this study is out of phase with the other two precipitation series. It demonstrated the common climatic driving factors in the southeastern and south of Tibetan Plateau and also the local features.

Impacts of ambient temperature on the burden of bacillary dysentery in urban and rural Hefei, China.

PubMed

Cheng, J; Xie, M Y; Zhao, K F; Wu, J J; Xu, Z W; Song, J; Zhao, D S; Li, K S; Wang, X; Yang, H H; Wen, L Y; Su, H; Tong, S L

2017-06-01

Bacillary dysentery continues to be a major health issue in developing countries and ambient temperature is a possible environmental determinant. However, evidence about the risk of bacillary dysentery attributable to ambient temperature under climate change scenarios is scarce. We examined the attributable fraction (AF) of temperature-related bacillary dysentery in urban and rural Hefei, China during 2006-2012 and projected its shifting pattern under climate change scenarios using a distributed lag non-linear model. The risk of bacillary dysentery increased with the temperature rise above a threshold (18·4 °C), and the temperature effects appeared to be acute. The proportion of bacillary dysentery attributable to hot temperatures was 18·74% (95 empirical confidence interval (eCI): 8·36-27·44%). Apparent difference of AF was observed between urban and rural areas, with AF varying from 26·87% (95% eCI 16·21-36·68%) in urban area to -1·90% (95 eCI -25·03 to 16·05%) in rural area. Under the climate change scenarios alone (1-4 °C rise), the AF from extreme hot temperatures (>31·2 °C) would rise greatly accompanied by the relatively stable AF from moderate hot temperatures (18·4-31·2 °C). If climate change proceeds, urban area may be more likely to suffer from rapidly increasing burden of disease from extreme hot temperatures in the absence of effective mitigation and adaptation strategies.

Self-enforcing strategies to deter free-riding in the climate change mitigation game and other repeated public good games

PubMed Central

Heitzig, Jobst; Lessmann, Kai; Zou, Yong

2011-01-01

As the Copenhagen Accord indicates, most of the international community agrees that global mean temperature should not be allowed to rise more than two degrees Celsius above preindustrial levels to avoid unacceptable damages from climate change. The scientific evidence distilled in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change and recent reports by the US National Academies shows that this can only be achieved by vast reductions of greenhouse gas emissions. Still, international cooperation on greenhouse gas emissions reductions suffers from incentives to free-ride and to renegotiate agreements in case of noncompliance, and the same is true for other so-called “public good games.” Using game theory, we show how one might overcome these problems with a simple dynamic strategy of linear compensation when the parameters of the problem fulfill some general conditions and players can be considered to be sufficiently rational. The proposed strategy redistributes liabilities according to past compliance levels in a proportionate and timely way. It can be used to implement any given allocation of target contributions, and we prove that it has several strong stability properties. PMID:21903930

Rethinking the longitudinal stream temperature paradigm: region-wide comparison of thermal infrared imagery reveals unexpected complexity of river temperatures

USGS Publications Warehouse

Fullerton, Aimee H.; Torgersen, Christian E.; Lawler, Joshua J.; Faux, Russell N.; Steel, E. Ashley; Beechie, Timothy J.; Ebersole, Joseph L.; Leibowitz, Scott J.

2015-01-01

Prevailing theory suggests that stream temperature warms asymptotically in a downstream direction, beginning at the temperature of the source in the headwaters and leveling off downstream as it converges to match meteorological conditions. However, there have been few empirical examples of longitudinal patterns of temperature in large rivers due to a paucity of data. We constructed longitudinal thermal profiles (temperature versus distance) for 53 rivers in the Pacific Northwest (USA) using an extensive dataset of remotely sensed summertime river temperatures and classified each profile into one of five patterns of downstream warming: asymptotic (increasing then flattening), linear (increasing steadily), uniform (not changing), parabolic (increasing then decreasing), or complex (not fitting other classes). We evaluated (1) how frequently profiles warmed asymptotically downstream as expected, and (2) whether relationships between river temperature and common hydroclimatic variables differed by profile class. We found considerable diversity in profile shape, with 47% of rivers warming asymptotically, and 53% having alternative profile shapes. Water temperature did not warm substantially over the course of the river for coastal parabolic and uniform profiles, and for some linear and complex profiles. Profile classes showed no clear geographical trends. The degree of correlation between river temperature and hydroclimatic variables differed among profile classes, but there was overlap among classes. Water temperature in rivers with asymptotic or parabolic profiles was positively correlated with August air temperature, tributary temperature and velocity, and negatively correlated with elevation, August precipitation, gradient, and distance upstream. Conversely, associations were less apparent in rivers with linear, uniform, or complex profiles. Factors contributing to the unique shape of parabolic profiles differed for coastal and inland rivers, where downstream cooling was influenced locally by climate or cool water inputs, respectively. Potential drivers of shape for complex profiles were specific to each river. These thermal patterns indicate diverse thermal habitats that may promote resilience of aquatic biota to climate change. Without this spatial context, climate change models may incorrectly estimate loss of thermally suitable habitat.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations.

PubMed

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; Xie, Yangyang; Liu, Saiyan; Meng, Erhao; Li, Pei

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

Projecting changes in annual hydropower generation using regional runoff data: An assessment of the United States federal hydropower plants

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

Kao, Shih -Chieh; Sale, Michael J.; Ashfaq, Moetasim

Federal hydropower plants account for approximately half of installed US conventional hydropower capacity, and are an important part of the national renewable energy portfolio. Utilizing the strong linear relationship between the US Geological Survey WaterWatch runoff and annual hydropower generation, a runoff-based assessment approach is introduced in this study to project changes in annual and regional hydropower generation in multiple power marketing areas. Future climate scenarios are developed with a series of global and regional climate models, and the model output is bias-corrected to be consistent with observed data for the recent past. Using this approach, the median decrease inmore » annual generation at federal projects is projected to be less than –2 TWh, with an estimated ensemble uncertainty of ±9 TWh. Although these estimates are similar to the recently observed variability in annual hydropower generation, and may therefore appear to be manageable, significantly seasonal runoff changes are projected and it may pose significant challenges in water systems with higher limits on reservoir storage and operational flexibility. Lastly, future assessments will be improved by incorporating next-generation climate models, by closer examination of extreme events and longer-term change, and by addressing the interactions among hydropower and other water uses.« less

Projecting changes in annual hydropower generation using regional runoff data: An assessment of the United States federal hydropower plants

DOE PAGES

Kao, Shih -Chieh; Sale, Michael J.; Ashfaq, Moetasim; ...

2014-12-18

Federal hydropower plants account for approximately half of installed US conventional hydropower capacity, and are an important part of the national renewable energy portfolio. Utilizing the strong linear relationship between the US Geological Survey WaterWatch runoff and annual hydropower generation, a runoff-based assessment approach is introduced in this study to project changes in annual and regional hydropower generation in multiple power marketing areas. Future climate scenarios are developed with a series of global and regional climate models, and the model output is bias-corrected to be consistent with observed data for the recent past. Using this approach, the median decrease inmore » annual generation at federal projects is projected to be less than –2 TWh, with an estimated ensemble uncertainty of ±9 TWh. Although these estimates are similar to the recently observed variability in annual hydropower generation, and may therefore appear to be manageable, significantly seasonal runoff changes are projected and it may pose significant challenges in water systems with higher limits on reservoir storage and operational flexibility. Lastly, future assessments will be improved by incorporating next-generation climate models, by closer examination of extreme events and longer-term change, and by addressing the interactions among hydropower and other water uses.« less

Quantifying PM2.5-Meteorology Sensitivities in a Global Climate Model

NASA Technical Reports Server (NTRS)

Westervelt, D. M.; Horowitz, L. W.; Naik, V.; Tai, A. P. K.; Fiore, A. M.; Mauzerall, D. L.

2016-01-01

Climate change can influence fine particulate matter concentrations (PM2.5) through changes in air pollution meteorology. Knowledge of the extent to which climate change can exacerbate or alleviate air pollution in the future is needed for robust climate and air pollution policy decision-making. To examine the influence of climate on PM2.5, we use the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 (GFDL CM3), a fully-coupled chemistry-climate model, combined with future emissions and concentrations provided by the four Representative Concentration Pathways (RCPs). For each of the RCPs, we conduct future simulations in which emissions of aerosols and their precursors are held at 2005 levels while other climate forcing agents evolve in time, such that only climate (and thus meteorology) can influence PM2.5 surface concentrations. We find a small increase in global, annual mean PM2.5 of about 0.21 micro-g/cu m3 (5%) for RCP8.5, a scenario with maximum warming. Changes in global mean PM2.5 are at a maximum in the fall and are mainly controlled by sulfate followed by organic aerosol with minimal influence of black carbon. RCP2.6 is the only scenario that projects a decrease in global PM2.5 with future climate changes, albeit only by -0.06 micro-g/cu m (1.5%) by the end of the 21st century. Regional and local changes in PM2.5 are larger, reaching upwards of 2 micro-g/cu m for polluted (eastern China) and dusty (western Africa) locations on an annually averaged basis in RCP8.5. Using multiple linear regression, we find that future PM2.5 concentrations are most sensitive to local temperature, followed by surface wind and precipitation. PM2.5 concentrations are robustly positively associated with temperature, while negatively related with precipitation and wind speed. Present-day (2006-2015) modeled sensitivities of PM2.5 to meteorological variables are evaluated against observations and found to agree reasonably well with observed sensitivities (within 10e50% over the eastern United States for several variables), although the modeled PM2.5 is less sensitive to precipitation than in the observations due to weaker convective scavenging. We conclude that the hypothesized "climate penalty" of future increases in PM2.5 is relatively minor on a global scale compared to the influence of emissions on PM2.5 concentrations.

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Inferences of Present and Past Changes at Isolated Enclaves and Matrix of Savannas by Carbon Isotopes in a Transitional Forest-Savanna Area in Northern Amazonia

NASA Astrophysics Data System (ADS)

Couto-Santos, F. R.; Luizao, F. J.; Camargo, P. B.

2013-12-01

The evolutionary history of savannas influenced by short term climate cycles, during the Quaternary Period, could prompt variations in forest cover often related to movements of the forest-savanna boundary. In this study we investigated current and past changes in the structure of vegetation and the origins of savannas of different natures in a biogeographically and climatic transitional forest-savanna area in northern Amazonia. Variations in the isotopic composition of soil organic matter (δ13C) from surface soils (0-10 cm) along forest-savanna boundaries, detected by a sigmoidal non-linear function, were used to identify current changes in vegetation, while past changes were inferred by discontinuities in the evolution of δ13C with soil depth using piecewise regression associated with radiocarbon dating (14C). By comparing small isolated savanna enclaves inside a strictly protected nature reserve (ESEC Maracá) with its outskirts unprotected continuous savanna matrix, we found that origins and the patterns of dynamics were distinct between these areas and did not respond in the same way to climate change and fire events, either in the last decades or during the Holocene. The stability of the present boundaries of the surrounding savanna matrix reflects the resilience of the transitional forests under a recent intensified fire regime and favorable climate, while the deep forest soil isotopic signal indicated a forest shrinkage of at least 70 m occurring since its origin in early Holocene until 780 years BP associated with a climate drier than the current one. Contrarily, the protected enclaves inside ESEC Maracá, remained stable since the middle Holocene, suggesting a non-anthropogenic origin related to soil edaphic conditions, but with recent dynamics of advancing forest by 8 m century-1 favored by current climate and lacking fire events. A detailed understanding of the origins of savannas of distinct natures and the way they are affected by climate and fire events provided by carbon isotopes and radiocarbon analysis in both short and long term could help predict the future of these ecosystems under the envisaged climate change scenario. Financial Support: Boticário Group Foundation (Fundação Grupo Boticário); National Council for Scientific and Technological Development (CNPq); The Minas Gerais State Research Foundation (FAPEMIG).

Ambiguity: A new way of thinking about responses to climate change.

PubMed

Fleming, A; Howden, S M

2016-11-15

Diversity, interdisciplinarity and transdisciplinarity are now recognized as vital to tackling wicked problems such as those presented by a changing climate (Nature editorial 2015, Ledford 2015; Dick et al., 2016). Including diverse disciplines in science projects enables a range of different views which often facilitate the creation of innovative solutions. Supporting multiple views and options requires a different way of working beyond traditional reductionist approaches to science, communication and decision-making. To embrace diversity in scientific project teams in order to tackle complex, integrated and urgent issues but to expect singular and linear pathways forward is paradoxical. Much has been written about the need for the scientific community to embrace uncertainty (e.g. Popper, Lempert & Bankes 2005; Lempert et al., 2004; Nelson, Howden & Hayman 2013; Bammer & Smithson 2008). We argue that this in itself will not suffice, and that there is also a need to embrace ambiguity in certain situations. Thus, in this article we explore: (1) what ambiguity is, including the benefits it can offer to climate adaptation in particular, using existing approaches to ambiguity in the arts and humanities as examples (2), we discuss practical meanings of ambiguity in relation to climate change, (3) we propose possible next steps for bringing ambiguity into interdisciplinary practice, and (4) we identify some challenges and necessary preconditions to successfully and appropriately embracing ambiguity. Copyright © 2016 Elsevier B.V. All rights reserved.

Vulnerability of sandy coasts to climate change and anthropic pressures: methodology and preliminary results

NASA Astrophysics Data System (ADS)

Idier, D.; Poumadère, M.; Vinchon, C.; Romieu, E.; Oliveros, C.

2009-04-01

1-INTRODUCTION Climate change is considered in the latest reports of the Intergovernmental Panel on Climate Change IPCC (2007) as unequivocal. Induced vulnerability of the system is defined as "the combination of sensitivity to climatic variations, probability of adverse effects, and adaptive capacity". Substantial methodological challenges remain, in particular estimating the risk of adverse climate change impacts and interpreting relative vulnerability across diverse situations. As stated by the IPCC, the "coastal systems should be considered vulnerable to changes in climate". In these areas, amongst the most serious impacts of sea-level rise (Nicholls, 1996) are erosion and marine inundation. Thus, the coast of metropolitan France, being composed of 31% sandy coasts, is potentially vulnerable, as it has been qualitatively assessed on the pilot coasts of Aquitaine and Languedoc-Roussillon in the RESPONSE project (Vinchon et al., 2008). Within the ANR VULSACO project (VULnerability of SAndy COast to climate change and anthropic pressure), the present day erosion tendencies as well as the potentially future erosion trends are investigated. The main objectives are to: (1) assess indicators of vulnerability to climate change for low-lying linear sandy coastal systems, from the shore to the hinterland, facing undergoing climate change and anthropic pressure until the 2030s; and (2) identify the aggravating or improving effect of human pressure on this vulnerability. This second issue is sometimes considered as a main driver of coastal risks. The methodology proposed in the project considers anthropic adaptation (or not) by putting decision makers in front of potential modifications of the physical system, to study the decision process and the choice of adaptation (or not). The coastal system is defined by its morphology, its physical characteristics and its land use. The time scales will range from short-term (days to weeks, e.g. time scale of extreme events) to medium-term (decades), whereas the space scales range from several tens of meters to several tens of kilometers. The project is based on the study of representative coastal units: 4 sites characterised by low-lying linear sandy beaches but different, representative, hydrodynamic and socio-economic environments. These sites are located in: Mediterranean Sea (Lido of Sète), Atlantic coast (Truc Vert beach and Noirmoutier island) and English channel coast (Est of Dunkerque). Each of these sites is studied following the same methodology, on both the physical and socio-economic dimensions, the aim being to identify vulnerability indicators regarding climate change and anthropic pressure. 2 - METHODOLOGY The work is based on the following methodology, for every site: 1) The compartments of the unit are defined: shoreface, coastline, backshore, hinterland, from a physical and socio-economical point of view. 2) The available data are analysed in order to provide some information on the present trend of the coastal unit, regarding climate change and anthropic pressure, but also to support the model validation. 3) The vulnerability is studied. On one hand, the socio-economic dimension is assessed and, in a risk governance perspective, stake holders are identified and involved. This part of the project combines the study of social perceptions of dangers along with a deliberative workshop. On the other hand, numerical models of the physical behaviour of shoreface and coastline are applied. The selected models cover a time scale from short-term (storm time scale) to long-term (decades). Then, vulnerability can be studied: the vulnerability of coast/beach is defined and studied based on in-situ observations and model results. Most of these models needs some forcing conditions (waves at the boundary of the computational domains for instance). The present day conditions can be potentially modified by climate change. However, the model and literature review on climate change show that the few prediction of wave conditions available for the future deal mainly with the significant wave height, and not so much with the wave direction or period. To compensate this lack of knowledge, a sensitivity study is done to get information on the possible changes within the next decades (2030). It consists in studying the influence of a modification in the characteristics of the present day forcing conditions(like waves) within a reasonable magnitude order. 4) The anthropic pressure is taken into account as a modulator of the physical vulnerability. In each context, participative techniques are used to involve representatives of the main stakeholder groups into decision-making simulations. The scenario of a storm in 2030 is adopted to provide structured interactions during the workshop. Along with socio-economic projections, this simulation relies upon a fictive journal article written on the basis of the model outputs. These methodological choices aim at better understanding how decisions are made by stake holders dealing with risks and scientific uncertainty. Some applied results on the study sites will be presented at the EGU. ACKNOWLEDGEMENTS The VULSACO project is financially supported by the ANR (French National Research Agency) within the Vulnérabilité-Milieux-Climat programm.

Impact of climate change on electricity systems and markets

NASA Astrophysics Data System (ADS)

Chandramowli, Shankar N.

Climate change poses a serious threat to human welfare. There is now unequivocal scientific evidence that human actions are the primary cause of climate change. The principal climate forcing factor is the increasing accumulation of atmospheric carbon dioxide (CO2) due to combustion of fossil fuels for transportation and electricity generation. Generation of electricity account for nearly one-third of the greenhouse (GHG) emissions globally (on a CO2-equivalent basis). Any kind of economy-wide mitigation or adaptation effort to climate change must have a prominent focus on the electric power sector. I have developed a capacity expansion model for the power sector called LP-CEM (Linear Programming based Capacity Expansion Model). LP-CEM incorporates both the long-term climate change effects and the state/regional-level macroeconomic trends. This modeling framework is demonstrated for the electric power system in the Northeast region of United States. Some of the methodological advances introduced in this research are: the use of high-resolution temperature projections in a power sector capacity expansion model; the incorporation of changes in sectoral composition of electricity demand over time; the incorporation of the effects of climate change and variability on both the demand and supply-side of power sector using parameters estimated in the literature; and an inter-model coupling link with a macroeconomic model to account for price elasticity of demand and other effects on the broader macro-economy. LP-CEM-type models can be of use to state/regional level policymakers to plan for future mitigation and adaptation measures for the electric power sector. From the simulation runs, it is shown that scenarios with climate change effects and with high economic growth rates have resulted in higher capacity addition, optimal supply costs, wholesale/retail prices and total ratepayers' costs. LP-CEM is also adapted to model the implications of the proposed Clean Power Plan (Section 111 (d)) rules for the U.S. Northeast region. This dissertation applies an analytical model and an optimization model to investigate the implications of co-implementing an emission cap and an RPS policy for this region. A simplified analytical model of LP-CEM is specified and the first order optimality conditions are derived. The results from this analytical model are corroborated by running LP-CEM simulations under different carbon cap and RPS policy assumptions. A combination of these policies is shown to have a long-term beneficial effect for the final ratepayers in the region. This research conceptually explores the future implications of climate change and extreme weather events on the regional electricity market framework. The significant findings from this research and future policy considerations are discussed in the conclusion chapter.

Climatic impact of Amazon deforestation - a mechanistic model study

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

Ning Zeng; Dickinson, R.E.; Xubin Zeng

1996-04-01

Recent general circulation model (GCM) experiments suggest a drastic change in the regional climate, especially the hydrological cycle, after hypothesized Amazon basinwide deforestation. To facilitate the theoretical understanding os such a change, we develop an intermediate-level model for tropical climatology, including atmosphere-land-ocean interaction. The model consists of linearized steady-state primitive equations with simplified thermodynamics. A simple hydrological cycle is also included. Special attention has been paid to land-surface processes. It generally better simulates tropical climatology and the ENSO anomaly than do many of the previous simple models. The climatic impact of Amazon deforestation is studied in the context of thismore » model. Model results show a much weakened Atlantic Walker-Hadley circulation as a result of the existence of a strong positive feedback loop in the atmospheric circulation system and the hydrological cycle. The regional climate is highly sensitive to albedo change and sensitive to evapotranspiration change. The pure dynamical effect of surface roughness length on convergence is small, but the surface flow anomaly displays intriguing features. Analysis of the thermodynamic equation reveals that the balance between convective heating, adiabatic cooling, and radiation largely determines the deforestation response. Studies of the consequences of hypothetical continuous deforestation suggest that the replacement of forest by desert may be able to sustain a dry climate. Scaling analysis motivated by our modeling efforts also helps to interpret the common results of many GCM simulations. When a simple mixed-layer ocean model is coupled with the atmospheric model, the results suggest a 1{degrees}C decrease in SST gradient across the equatorial Atlantic Ocean in response to Amazon deforestation. The magnitude depends on the coupling strength. 66 refs., 16 figs., 4 tabs.« less

Trends and Correlation Estimation in Climate Sciences: Effects of Timescale Errors

NASA Astrophysics Data System (ADS)

Mudelsee, M.; Bermejo, M. A.; Bickert, T.; Chirila, D.; Fohlmeister, J.; Köhler, P.; Lohmann, G.; Olafsdottir, K.; Scholz, D.

2012-12-01

Trend describes time-dependence in the first moment of a stochastic process, and correlation measures the linear relation between two random variables. Accurately estimating the trend and correlation, including uncertainties, from climate time series data in the uni- and bivariate domain, respectively, allows first-order insights into the geophysical process that generated the data. Timescale errors, ubiquitious in paleoclimatology, where archives are sampled for proxy measurements and dated, poses a problem to the estimation. Statistical science and the various applied research fields, including geophysics, have almost completely ignored this problem due to its theoretical almost-intractability. However, computational adaptations or replacements of traditional error formulas have become technically feasible. This contribution gives a short overview of such an adaptation package, bootstrap resampling combined with parametric timescale simulation. We study linear regression, parametric change-point models and nonparametric smoothing for trend estimation. We introduce pairwise-moving block bootstrap resampling for correlation estimation. Both methods share robustness against autocorrelation and non-Gaussian distributional shape. We shortly touch computing-intensive calibration of bootstrap confidence intervals and consider options to parallelize the related computer code. Following examples serve not only to illustrate the methods but tell own climate stories: (1) the search for climate drivers of the Agulhas Current on recent timescales, (2) the comparison of three stalagmite-based proxy series of regional, western German climate over the later part of the Holocene, and (3) trends and transitions in benthic oxygen isotope time series from the Cenozoic. Financial support by Deutsche Forschungsgemeinschaft (FOR 668, FOR 1070, MU 1595/4-1) and the European Commission (MC ITN 238512, MC ITN 289447) is acknowledged.

Simulating the effects of climatic variation on stem carbon accumulation of a ponderosa pine stand: comparison with annual growth increment data.

PubMed

Hunt, E R; Martin, F C; Running, S W

1991-01-01

Simulation models of ecosystem processes may be necessary to separate the long-term effects of climate change on forest productivity from the effects of year-to-year variations in climate. The objective of this study was to compare simulated annual stem growth with measured annual stem growth from 1930 to 1982 for a uniform stand of ponderosa pine (Pinus ponderosa Dougl.) in Montana, USA. The model, FOREST-BGC, was used to simulate growth assuming leaf area index (LAI) was either constant or increasing. The measured stem annual growth increased exponentially over time; the differences between the simulated and measured stem carbon accumulations were not large. Growth trends were removed from both the measured and simulated annual increments of stem carbon to enhance the year-to-year variations in growth resulting from climate. The detrended increments from the increasing LAI simulation fit the detrended increments of the stand data over time with an R(2) of 0.47; the R(2) increased to 0.65 when the previous year's simulated detrended increment was included with the current year's simulated increment to account for autocorrelation. Stepwise multiple linear regression of the detrended increments of the stand data versus monthly meteorological variables had an R(2) of 0.37, and the R(2) increased to 0.47 when the previous year's meteorological data were included to account for autocorrelation. Thus, FOREST-BGC was more sensitive to the effects of year-to-year climate variation on annual stem growth than were multiple linear regression models.

A conceptual model for glacial cycles and the middle Pleistocene transition

NASA Astrophysics Data System (ADS)

Daruka, István; Ditlevsen, Peter D.

2016-01-01

Milankovitch's astronomical theory of glacial cycles, attributing ice age climate oscillations to orbital changes in Northern-Hemisphere insolation, is challenged by the paleoclimatic record. The climatic response to the variations in insolation is far from trivial. In general the glacial cycles are highly asymmetric in time, with slow cooling from the interglacials to the glacials (inceptions) and very rapid warming from the glacials to the interglacials (terminations). We shall refer to this fast-slow dynamics as the "saw-tooth" shape of the paleoclimatic record. This is non-linearly related to the time-symmetric variations in the orbital forcing. However, the most pronounced challenge to the Milankovitch theory is the middle Pleistocene transition (MPT) occurring about one million years ago. During that event, the prevailing 41 kyr glacial cycles, corresponding to the almost harmonic obliquity cycle were replaced by longer saw-tooth shaped cycles with a time-scale around 100 kyr. The MPT must have been driven by internal changes in climate response, since it does not correspond to any apparent changes in the orbital forcing. In order to identify possible mechanisms causing the observed changes in glacial dynamics, it is relevant to study simplified models with the capability of generating temporal behavior similar to the observed records. We present a simple oscillator type model approach, with two variables, a temperature anomaly and a climatic memory term. The generalization of the ice albedo feedback is included in terms of an effective multiplicative coupling between this latter climatic memory term (representing the internal degrees of freedom) and the external drive. The simple model reproduces the temporal asymmetry of the late Pleistocene glacial cycles and suggests that the MPT can be explained as a regime shift, aided by climatic noise, from a period 1 frequency locking to the obliquity cycle to a period 2-3 frequency locking to the same obliquity cycle. The change in dynamics has been suggested to be a result of a slow gradual decrease in atmospheric greenhouse gas concentration. The critical dependence on initial conditions in the (non-autonomous) glacial dynamics raises fundamental questions about climate predictability.

Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

PubMed

Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

2018-01-01

There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

Tree demography suggests multiple directions and drivers for species range shifts in mountains of Northeastern United States.

PubMed

Wason, Jay W; Dovciak, Martin

2017-08-01

Climate change is expected to lead to upslope shifts in tree species distributions, but the evidence is mixed partly due to land-use effects and individualistic species responses to climate. We examined how individual tree species demography varies along elevational climatic gradients across four states in the northeastern United States to determine whether species elevational distributions and their potential upslope (or downslope) shifts were controlled by climate, land-use legacies (past logging), or soils. We characterized tree demography, microclimate, land-use legacies, and soils at 83 sites stratified by elevation (~500 to ~1200 m above sea level) across 12 mountains containing the transition from northern hardwood to spruce-fir forests. We modeled elevational distributions of tree species saplings and adults using logistic regression to test whether sapling distributions suggest ongoing species range expansion upslope (or contraction downslope) relative to adults, and we used linear mixed models to determine the extent to which climate, land use, and soil variables explain these distributions. Tree demography varied with elevation by species, suggesting a potential upslope shift only for American beech, downslope shifts for red spruce (more so in cool regions) and sugar maple, and no change with elevation for balsam fir. While soils had relatively minor effects, climate was the dominant predictor for most species and more so for saplings than adults of red spruce, sugar maple, yellow birch, cordate birch, and striped maple. On the other hand, logging legacies were positively associated with American beech, sugar maple, and yellow birch, and negatively with red spruce and balsam fir - generally more so for adults than saplings. All species exhibited individualistic rather than synchronous demographic responses to climate and land use, and the return of red spruce to lower elevations where past logging originally benefited northern hardwood species indicates that land use may mask species range shifts caused by changing climate. © 2016 John Wiley & Sons Ltd.

Forcing of stratospheric chemistry and dynamics during the Dalton Minimum

NASA Astrophysics Data System (ADS)

Anet, J. G.; Muthers, S.; Rozanov, E.; Raible, C. C.; Peter, T.; Stenke, A.; Shapiro, A. I.; Beer, J.; Steinhilber, F.; Brönnimann, S.; Arfeuille, F.; Brugnara, Y.; Schmutz, W.

2013-06-01

The response of atmospheric chemistry and climate to volcanic eruptions and a decrease in solar activity during the Dalton Minimum is investigated with the fully coupled atmosphere-ocean-chemistry general circulation model SOCOL-MPIOM covering the time period 1780 to 1840 AD. We carried out several sensitivity ensemble experiments to separate the effects of (i) reduced solar ultra-violet (UV) irradiance, (ii) reduced solar visible and near infrared irradiance, (iii) enhanced galactic cosmic ray intensity as well as less intensive solar energetic proton events and auroral electron precipitation, and (iv) volcanic aerosols. The introduced changes of UV irradiance and volcanic aerosols significantly influence stratospheric climate in the early 19th century, whereas changes in the visible part of the spectrum and energetic particles have smaller effects. A reduction of UV irradiance by 15% causes global ozone decrease below the stratopause reaching 8% in the midlatitudes at 5 hPa and a significant stratospheric cooling of up to 2 °C in the midstratosphere and to 6 °C in the lower mesosphere. Changes in energetic particle precipitation lead only to minor changes in the yearly averaged temperature fields in the stratosphere. Volcanic aerosols heat the tropical lower stratosphere allowing more water vapor to enter the tropical stratosphere, which, via HOx reactions, decreases upper stratospheric and mesospheric ozone by roughly 4%. Conversely, heterogeneous chemistry on aerosols reduces stratospheric NOx leading to a 12% ozone increase in the tropics, whereas a decrease in ozone of up to 5% is found over Antarctica in boreal winter. The linear superposition of the different contributions is not equivalent to the response obtained in a simulation when all forcing factors are applied during the DM - this effect is especially well visible for NOx/NOy. Thus, this study highlights the non-linear behavior of the coupled chemistry-climate system. Finally, we conclude that especially UV and volcanic eruptions dominate the changes in the ozone, temperature and dynamics while the NOx field is dominated by the EPP. Visible radiation changes have only very minor effects on both stratospheric dynamics and chemistry.

Annual trend patterns of phytoplankton species abundance belie homogeneous taxonomical group responses to climate in the NE Atlantic upwelling.

PubMed

Bode, Antonio; Estévez, M Graciela; Varela, Manuel; Vilar, José A

2015-09-01

Phytoplankton is a sentinel of marine ecosystem change. Composed by many species with different life-history strategies, it rapidly responds to environment changes. An analysis of the abundance of 54 phytoplankton species in Galicia (NW Spain) between 1989 and 2008 to determine the main components of temporal variability in relation to climate and upwelling showed that most of this variability was stochastic, as seasonality and long term trends contributed to relatively small fractions of the series. In general, trends appeared as non linear, and species clustered in 4 groups according to the trend pattern but there was no defined pattern for diatoms, dinoflagellates or other groups. While, in general, total abundance increased, no clear trend was found for 23 species, 14 species decreased, 4 species increased during the early 1990s, and only 13 species showed a general increase through the series. In contrast, series of local environmental conditions (temperature, stratification, nutrients) and climate-related variables (atmospheric pressure indices, upwelling winds) showed a high fraction of their variability in deterministic seasonality and trends. As a result, each species responded independently to environmental and climate variability, measured by generalized additive models. Most species showed a positive relationship with nutrient concentrations but only a few showed a direct relationship with stratification and upwelling. Climate variables had only measurable effects on some species but no common response emerged. Because its adaptation to frequent disturbances, phytoplankton communities in upwelling ecosystems appear less sensitive to changes in regional climate than other communities characterized by short and well defined productive periods. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Understanding linkages between global climate indices and terrestrial water storage changes over Africa using GRACE products.

PubMed

Anyah, R O; Forootan, E; Awange, J L; Khaki, M

2018-09-01

Africa, a continent endowed with huge water resources that sustain its agricultural activities is increasingly coming under threat from impacts of climate extremes (droughts and floods), which puts the very precious water resource into jeopardy. Understanding the relationship between climate variability and water storage over the continent, therefore, is paramount in order to inform future water management strategies. This study employs Gravity Recovery And Climate Experiment (GRACE) satellite data and the higher order (fourth order cumulant) statistical independent component analysis (ICA) method to study the relationship between terrestrial water storage (TWS) changes and five global climate-teleconnection indices; El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Madden-Julian Oscillation (MJO), Quasi-Biennial Oscillation (QBO) and the Indian Ocean Dipole (IOD) over Africa for the period 2003-2014. Pearson correlation analysis is applied to extract the connections between these climate indices (CIs) and TWS, from which some known strong CI-rainfall relationships (e.g., over equatorial eastern Africa) are found. Results indicate unique linear-relationships and regions that exhibit strong linkages between CIs and TWS. Moreover, unique regions having strong CI-TWS connections that are completely different from the typical ENSO-rainfall connections over eastern and southern Africa are also identified. Furthermore, the results indicate that the first dominant independent components (IC) of the CIs are linked to NAO, and are characterized by significant reductions of TWS over southern Africa. The second dominant ICs are associated with IOD and are characterized by significant increases in TWS over equatorial eastern Africa, while the combined ENSO and MJO are apparently linked to the third ICs, which are also associated with significant increase in TWS changes over both southern Africa, as well as equatorial eastern Africa. Copyright © 2018 Elsevier B.V. All rights reserved.

Co-producing resilient solutions to climate change: Bridging the gap between science and decision-making around nexus issues

NASA Astrophysics Data System (ADS)

Howarth, C.

2016-12-01

The nexus represents a multi-dimensional means of scientific enquiry encapsulating the complex and non-linear interactions between water, energy, food, environment with the climate, and wider implications for society. These resources are fundamental for human life but are negatively affected by climate change. Methods of analysis, which are currently used, were not built to represent complex systems and are insufficiently equipped to understand positive and negative externalities generated by interactions among different stakeholders involved in the nexus. In addition misalignment between the science that scientists produce and the evidence decision-makers need leads to a range of complexities within the science-policy interface. Adopting a bottom-up, participative approach, the results of five themed workshops organized in the UK (focusing on: shocks and hazards, infrastructure, local economy, governance and governments, finance and insurance) featuring 80 stakeholders from academia, government and industry allow us to map perceptions of opportunities and challenges of better informing decision making on climate change when there is a strong disconnect between the evidence scientists provide and the actions decision makers take. The research identified key areas where gaps could be bridged between science and action and explores how a knowledge co-production approach can help identify opportunities for building a more effective and legitimate policy agenda to face climate risks. Concerns, barriers and opportunities to better inform decision making centred on four themes: communication and collaboration, decision making processes, social and cultural dimensions, and the nature of responses to nexus shocks. In so doing, this analysis provides an assessment of good practice on climate decision-making and highlights opportunities for improvement to bridge gaps in the science-policy interface

Subalpine Forest Carbon Cycling Short- and Long-Term Influence ofClimate and Species

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

Kueppers, L.; Harte, J.

2005-08-23

Ecosystem carbon cycle feedbacks to climate change comprise one of the largest remaining sources of uncertainty in global model predictions of future climate. Both direct climate effects on carbon cycling and indirect effects via climate-induced shifts in species composition may alter ecosystem carbon balance over the long term. In the short term, climate effects on carbon cycling may be mediated by ecosystem species composition. We used an elevational climate and tree species composition gradient in Rocky Mountain subalpine forest to quantify the sensitivity of all major ecosystem carbon stocks and fluxes to these factors. The climate sensitivities of carbon fluxesmore » were species-specific in the cases of relative above ground productivity and litter decomposition, whereas the climate sensitivity of dead wood decay did not differ between species, and total annual soil CO2 flux showed no strong climate trend. Lodge pole pine relative productivity increased with warmer temperatures and earlier snowmelt, while Engelmann spruce relative productivity was insensitive to climate variables. Engelmann spruce needle decomposition decreased linearly with increasing temperature(decreasing litter moisture), while lodgepole pine and subalpine fir needle decay showed a hump-shaped temperature response. We also found that total ecosystem carbon declined by 50 percent with a 2.88C increase in mean annual temperature and a concurrent 63 percent decrease ingrowing season soil moisture, primarily due to large declines in mineral soil and dead wood carbon. We detected no independent effect of species composition on ecosystem C stocks. Overall, our carbon flux results suggest that, in the short term, any change in subalpine forest net carbon balance will depend on the specific climate scenario and spatial distribution of tree species. Over the long term, our carbon stock results suggest that with regional warming and drying, Rocky Mountain subalpine forest will be a net source of carbon to the atmosphere.« less

Hierarchical Linear Modelling of Student and School Effects on Academic Achievement.

ERIC Educational Resources Information Center

Ma, Xin; Klinger, Don A.

2000-01-01

Used hierarchical linear modeling with data from the New Brunswick School Climate Study (Canada) to examine student background, school context, and school climate effects on Grade 6 student achievement in mathematics, science, reading, and writing. Gender, socioeconomic status, and Native ethnicity were significant predictors of academic…

Mid-Holocene to Present Climate Transition in Tropical South America

NASA Astrophysics Data System (ADS)

Turcq, B.; Cordeiro, R.; Sifeddine, A.; Braconnot, P.; Dias, P. S.; Costa, R.; Jorgetti, T.

2008-12-01

The classical illustration of Holocene climate changes in tropical South America is the huge rising of Titicaca lake level from 4400 to 4000 cal BP. Because the Amazon basin is the source of Andean rainfalls we have explored Amazonian data of climate changes during the Holocene to better understand the cause of this abrupt transition. Amazonian data confirm the existence of mid-Holocene dryness: (1) lacustrine level studies show a lower precipitation/evaporation budget than present, with the lowest lake levels between 8500 and 6800 cal BP; (2) although the dominant Holocene vegetation has always been the rainforest in the heart of Amazonia, this forest expanded towards the northwestern and southwestern regions from 6800 to 1550 cal BP, moreover, pioneer elements of the rainforest developed during the mid-Holocene and the best example is those of Cecropia, between 9000 and 5000 cal BP. (3) soil d13C indicates a forest expansion over savannas areas in Roraima (north), Mato Grosso and Rondonia (southwest), during the Holocene. (4) the mid-Holocene (8000- 4000 cal BP) is characterized by repeated occurrences of forest fires, marked by the presence of charcoals in soils and lacustrine sediments. However these different records are not characterized by abrupt transitions at the end of the Middle Holocene in Amazonia. In the Andean records there is a clear north-south shift in the timing of the transition. Analysis of coupled Ocean Atmosphere Model simulations suggest that convection in Amazon basin is directly controlled by insolation leading to an almost linear response of local climate to the global forcing. Differently, in the eastern and south-western regions where the rain is brought by the South American Monsoon, the climate transition appears more abrupt. It may be because the involved climate mechanisms are more complex and depend on Ocean/Atmosphere/Vegetation coupled process (ITCZ position, ZCAS formation, etc.). Tectonic movements or threshold links to lacustrine basin hydrology or to proxy responses to local climate changes must also be carefully taken into account in the identification of abrupt climate changes.

Linking Arctic plant biodiversity measurements with landscape heterogeneity

NASA Astrophysics Data System (ADS)

Gerber, F.; Schaepman-Strub, G.; Furrer, R.

2016-12-01

Climate warming in the Arctic region triggers changes in the vegetation productivity and species composition of the tundra. To investigate these changes and their feedback to climate, we consider species richness and abundance data of the International Tundra EXperiment (ITEX). As this information is very sparse in time and space, we aim to upscale available records to climatically relevant scales with a remote sensing based characterization of the study sites. More precisely, we relate species richness and evenness derived from the ITEX data to summary statistics describing the landscape heterogeneity, which are derived from an elevation model (ASTER GDEM) and spectral satellite observations (LANDSAT 5 and 7). Preliminary results from the statistical analysis using generalized linear mixed models show that no remote sensing based landscape characterization does significantly explain species richness. Reasons could be a mismatch of the spatial scales, an inappropriate characterization of the test sites through the satellite measurements, incomparable plot measurements from the different test sites and/or too few plot measurements. We are looking forward to presenting our results and getting your inputs.

More Intense Mega Heat Waves in the Warmer World

NASA Astrophysics Data System (ADS)

Choi, G.; Robinson, D. A.

2017-12-01

In this study, changes in the occurrences of heat waves on the globe since the mid- 20th century and the synoptic characteristics of mega heat waves at regional scales in the warmer climate are examined. The NCEP-NCAR reanalysis surface data show that there have been no obvious linear changes in the heat wave frequencies at the continental scales since the mid-20th century, but amplified interdecadal variations led to unprecedented intense heat waves in the recent decades at the regional scales. Such mega heat waves have been more frequently observed in the poleward subtropical climate belts as well as in the interior region of continents. According to the analyses of upper tropospheric data, the occurrences of more intense mega heat waves since the late 20th century may be associated with the expansion of subtropical high pressures. These results suggest that populous cities near the subtropical climate zones should provide proactive mega heat wave warning systems for residents due to their vulnerability to the sudden attack of human lives harvest by mega heat waves in the warmer 21st century.

Hydro-climatic Changes: Potential Non-linear Responses of Phosphorus Dynamic in Aquatic/Semi-aquatic Systems

NASA Astrophysics Data System (ADS)

Pant, H. K.

2007-12-01

Depending on resilience, threshold and lag times, hydro-climatic changes can cause nonlinear and/or irreversible changes in phosphorus (P) dynamic, and instigate P enrichment in aquatic/semi-aquatic systems. Thus, studying direct/indirect effects of expected global climate change on bioavailability of organic P in aquatic systems are in critical need, to help manage or increase the resilience of the ecosystem. The central hypothesis of this study is that P dynamic in aquatic, especially freshwater, ecosystem is likely to behave nonlinearly due to expected changes in sediment and water acidity, redox status, etc., because of potential hydro-climatic changes in the decades to come, thus, could face irreversible adverse changes. Devising possible biological and chemical treatments for the removal of P from eutrophic lakes, estuaries, etc, as well as helping in predicting the movement and fate of P under changing hydro-climatic conditions would be crucial to manage aquatic ecosystem in the near future. The critical question is not how much P is stored in any given aquatic/semi-aquatic system, but how the resilience and nonlinearity relate to the stability of stored P are affected due to the levels of environmental stressors, which are expected to fluctuate due to global change in the decades to come. Studies related to 31P Nuclear Magnetic Resonance Spectroscopy analysis, and multiple hydraulic retention cycles showed that, in general, frequent drying and reflooding of a semi-aquatic system such as wetland could significantly increase the bioavailability of P due to degradation of relatively less stable organic P, e.g., glycerophosphate and nucleoside monophosphate. Moreover, nutrients flux from sediments to the water column depended on the concentration gradients of the sediment-water interface and redox status. Shift in equilibrium P concentration of the water column as the water level rises, may cause release of adsorbed P from the sediments. Restoration of a eutrophic system may involve stepwise efforts including control of catchment nutrient inputs, internal nutrient loading, and biomanipulation, however, flooding, previously non-flooded areas, could export massive amount of P to nearby aquatic bodies, in turn, may cause collapse of the ecosystem.

Psychosocial safety climate moderates the job demand-resource interaction in predicting workgroup distress.

PubMed

Dollard, Maureen F; Tuckey, Michelle R; Dormann, Christian

2012-03-01

Psychosocial safety climate (PSC) arises from workplace policies, practices, and procedures for the protection of worker psychological health and safety that are largely driven by management. Many work stress theories are based on the fundamental interaction hypothesis - that a high level of job demands (D) will lead to psychological distress and that this relationship will be offset when there are high job resources (R). However we proposed that this interaction really depends on the organizational context; in particular high levels of psychosocial safety climate will enable the safe utilization of resources to reduce demands. The study sample consisted of police constables from 23 police units (stations) with longitudinal survey responses at two time points separated by 14 months (Time 1, N=319, Time 2, N=139). We used hierarchical linear modeling to assess the effect of the proposed three-way interaction term (PSC×D×R) on change in workgroup distress variance over time. Specifically we confirmed the interaction between emotional demands and emotional resources (assessed at the individual level), in the context of unit psychosocial safety climate (aggregated individual data). As predicted, high emotional resources moderated the positive relationship between emotional demands and change in workgroup distress but only when there were high levels of unit psychosocial safety climate. Results were confirmed using a split-sample analysis. Results support psychosocial safety climate as a property of the organization and a target for higher order controls for reducing work stress. The 'right' climate enables resources to do their job. Copyright © 2011 Elsevier Ltd. All rights reserved.

On the relationship between large-scale climate modes and regional synoptic patterns that drive Victorian rainfall

NASA Astrophysics Data System (ADS)

Verdon-Kidd, D. C.; Kiem, A. S.

2009-04-01

In this paper regional (synoptic) and large-scale climate drivers of rainfall are investigated for Victoria, Australia. A non-linear classification methodology known as self-organizing maps (SOM) is used to identify 20 key regional synoptic patterns, which are shown to capture a range of significant synoptic features known to influence the climate of the region. Rainfall distributions are assigned to each of the 20 patterns for nine rainfall stations located across Victoria, resulting in a clear distinction between wet and dry synoptic types at each station. The influence of large-scale climate modes on the frequency and timing of the regional synoptic patterns is also investigated. This analysis revealed that phase changes in the El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and/or the Southern Annular Mode (SAM) are associated with a shift in the relative frequency of wet and dry synoptic types on an annual to inter-annual timescale. In addition, the relative frequency of synoptic types is shown to vary on a multi-decadal timescale, associated with changes in the Inter-decadal Pacific Oscillation (IPO). Importantly, these results highlight the potential to utilise the link between the regional synoptic patterns derived in this study and large-scale climate modes to improve rainfall forecasting for Victoria, both in the short- (i.e. seasonal) and long-term (i.e. decadal/multi-decadal scale). In addition, the regional and large-scale climate drivers identified in this study provide a benchmark by which the performance of Global Climate Models (GCMs) may be assessed.

Dynamical Downscaling of Climate Change over the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Wang, Y.; Zhang, C.; Hamilton, K. P.; Lauer, A.

2015-12-01

The pseudo-global-warming (PGW) method was applied to the Hawaii Regional Climate Model (HRCM) to dynamically downscale the projected climate in the late 21st century over the Hawaiian Islands. The initial and boundary conditions were adopted from MERRA reanalysis and NOAA SST data for the present-day simulations. The global warming increments constructed from the CMIP3 multi-model ensemble mean were added to the reanalysis and SST data to perform the future climate simulations. We found that the Hawaiian Islands are vulnerable to global warming effects and the changes are diverse due to the varied topography. The windward side will have more clouds and receive more rainfall. The increase of the moisture in the boundary layer makes the major contribution. On the contrary, the leeward side will have less clouds and rainfall. The clouds and rain can slightly slow down the warming trend over the windward side. The temperature increases almost linearly with the terrain height. Cloud base and top heights will slightly decline in response to the slightly lower trade wind inversion base height, while the trade wind occurrence frequency will increase by about 8% in the future. More extreme rainfall events will occur in the warming climate over the Hawaiian Islands. And the snow cover on the top of Mauna Kea and Mauna Loa will nearly disappear in the future winter.

Spatial variability in growth-increment chronologies of long-lived freshwater mussels: Implications for climate impacts and reconstructions

USGS Publications Warehouse

Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Raggon, Mark F.; Zima, Daniela

2010-01-01

Estimates of historical variability in river ecosystems are often lacking, but long-lived freshwater mussels could provide unique opportunities to understand past conditions in these environments. We applied dendrochronology techniques to quantify historical variability in growth-increment widths in valves (shells) of western pearlshell freshwater mussels (Margaritifera falcata). A total of 3 growth-increment chronologies, spanning 19 to 26 y in length, were developed. Growth was highly synchronous among individuals within each site, and to a lesser extent, chronologies were synchronous among sites. All 3 chronologies negatively related to instrumental records of stream discharge, while correlations with measures of water temperature were consistently positive but weaker. A reconstruction of stream discharge was performed using linear regressions based on a mussel growth chronology and the regional Palmer Drought Severity Index (PDSI). Models based on mussel growth and PDSI yielded similar coefficients of prediction (R2Pred) of 0.73 and 0.77, respectively, for predicting out-ofsample observations. From an ecological perspective, we found that mussel chronologies provided a rich source of information for understanding climate impacts. Responses of mussels to changes in climate and stream ecosystems can be very site- and process-specific, underscoring the complex nature of biotic responses to climate change and the need to understand both regional and local processes in projecting climate impacts on freshwater species.

Development, Production and Validation of the NOAA Solar Irradiance Climate Data Record

NASA Astrophysics Data System (ADS)

Coddington, O.; Lean, J.; Pilewskie, P.; Snow, M. A.; Lindholm, D. M.

2015-12-01

A new climate data record of Total Solar Irradiance (TSI) and Solar Spectral Irradiance (SSI), including source code and supporting documentation is now publicly available as part of the National Oceanographic and Atmospheric Administration's (NOAA) National Centers for Environmental Information (NCEI) Climate Data Record (CDR) Program. Daily and monthly averaged values of TSI and SSI, with associated time and wavelength dependent uncertainties, are estimated from 1882 to the present with yearly averaged values since 1610, updated quarterly for the foreseeable future. The new Solar Irradiance Climate Data Record, jointly developed by the University of Colorado at Boulder's Laboratory for Atmospheric and Space Physics (LASP) and the Naval Research Laboratory (NRL), is constructed from solar irradiance models that determine the changes from quiet Sun conditions when bright faculae and dark sunspots are present on the solar disk. The magnitudes of the irradiance changes that these features produce are determined from linear regression of the proxy Mg II index and sunspot area indices against the approximately decade-long solar irradiance measurements made by instruments on the SOlar Radiation and Climate Experiment (SORCE) spacecraft. We describe the model formulation, uncertainty estimates, operational implementation and validation approach. Future efforts to improve the uncertainty estimates of the Solar Irradiance CDR arising from model assumptions, and augmentation of the solar irradiance reconstructions with direct measurements from the Total and Spectral Solar Irradiance Sensor (TSIS: launch date, July 2017) are also discussed.

Performance of the general circulation models in simulating temperature and precipitation over Iran

NASA Astrophysics Data System (ADS)

Abbasian, Mohammadsadegh; Moghim, Sanaz; Abrishamchi, Ahmad

2018-03-01

General Circulation Models (GCMs) are advanced tools for impact assessment and climate change studies. Previous studies show that the performance of the GCMs in simulating climate variables varies significantly over different regions. This study intends to evaluate the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs in simulating temperature and precipitation over Iran. Simulations from 37 GCMs and observations from the Climatic Research Unit (CRU) were obtained for the period of 1901-2005. Six measures of performance including mean bias, root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), linear correlation coefficient (r), Kolmogorov-Smirnov statistic (KS), Sen's slope estimator, and the Taylor diagram are used for the evaluation. GCMs are ranked based on each statistic at seasonal and annual time scales. Results show that most GCMs perform reasonably well in simulating the annual and seasonal temperature over Iran. The majority of the GCMs have a poor skill to simulate precipitation, particularly at seasonal scale. Based on the results, the best GCMs to represent temperature and precipitation simulations over Iran are the CMCC-CMS (Euro-Mediterranean Center on Climate Change) and the MRI-CGCM3 (Meteorological Research Institute), respectively. The results are valuable for climate and hydrometeorological studies and can help water resources planners and managers to choose the proper GCM based on their criteria.

Statistical bias correction method applied on CMIP5 datasets over the Indian region during the summer monsoon season for climate change applications

NASA Astrophysics Data System (ADS)

Prasanna, V.

2018-01-01

This study makes use of temperature and precipitation from CMIP5 climate model output for climate change application studies over the Indian region during the summer monsoon season (JJAS). Bias correction of temperature and precipitation from CMIP5 GCM simulation results with respect to observation is discussed in detail. The non-linear statistical bias correction is a suitable bias correction method for climate change data because it is simple and does not add up artificial uncertainties to the impact assessment of climate change scenarios for climate change application studies (agricultural production changes) in the future. The simple statistical bias correction uses observational constraints on the GCM baseline, and the projected results are scaled with respect to the changing magnitude in future scenarios, varying from one model to the other. Two types of bias correction techniques are shown here: (1) a simple bias correction using a percentile-based quantile-mapping algorithm and (2) a simple but improved bias correction method, a cumulative distribution function (CDF; Weibull distribution function)-based quantile-mapping algorithm. This study shows that the percentile-based quantile mapping method gives results similar to the CDF (Weibull)-based quantile mapping method, and both the methods are comparable. The bias correction is applied on temperature and precipitation variables for present climate and future projected data to make use of it in a simple statistical model to understand the future changes in crop production over the Indian region during the summer monsoon season. In total, 12 CMIP5 models are used for Historical (1901-2005), RCP4.5 (2005-2100), and RCP8.5 (2005-2100) scenarios. The climate index from each CMIP5 model and the observed agricultural yield index over the Indian region are used in a regression model to project the changes in the agricultural yield over India from RCP4.5 and RCP8.5 scenarios. The results revealed a better convergence of model projections in the bias corrected data compared to the uncorrected data. The study can be extended to localized regional domains aimed at understanding the changes in the agricultural productivity in the future with an agro-economy or a simple statistical model. The statistical model indicated that the total food grain yield is going to increase over the Indian region in the future, the increase in the total food grain yield is approximately 50 kg/ ha for the RCP4.5 scenario from 2001 until the end of 2100, and the increase in the total food grain yield is approximately 90 kg/ha for the RCP8.5 scenario from 2001 until the end of 2100. There are many studies using bias correction techniques, but this study applies the bias correction technique to future climate scenario data from CMIP5 models and applied it to crop statistics to find future crop yield changes over the Indian region.

Good News for Borehole Climatology

NASA Astrophysics Data System (ADS)

Rath, Volker; Fidel Gonzalez-Rouco, J.; Goosse, Hugues

2010-05-01

Though the investigation of observed borehole temperatures has proved to be a valuable tool for the reconstruction of ground surface temperature histories, there are many open questions concerning the significance and accuracy of the reconstructions from these data. In particular, the temperature signal of the warming after the Last glacial Maximum (LGM) is still present in borehole temperature profiles. It influences the relatively shallow boreholes used in current paleoclimate inversions to estimate temperature changes in the last centuries. This is shown using Monte Carlo experiments on past surface temperature change, using plausible distributions for the most important parameters, i.e.,amplitude and timing of the glacial-interglacial transition, the prior average temperature, and petrophysical properties. It has been argued that the signature of the last glacial-interglacial transition could be responsible for the high amplitudes of millennial temperature reconstructions. However, in shallow boreholes the additional effect of past climate can reasonably approximated by a linear variation of temperature with depth, and thus be accommodated by a "biased" background heat flow. This is good news for borehole climate, but implies that the geological heat flow values have to be interpreted accordingly. Borehole climate reconstructions from these shallow are most probably underestimating past variability due to the diffusive character of the heat conduction process, and the smoothness constraints necessary for obtaining stable solutions of this ill-posed inverse problem. A simple correction based on subtracting an appropriate prior surface temperature history shows promising results reducing these errors considerably, also with deeper boreholes, where the heat flow signal can not be approximated linearly, and improves the comparisons with AOGCM modeling results.

Predicting Impacts of Lightning Strikes on Aviation under a Changing Climate Using Regression Kriging

NASA Astrophysics Data System (ADS)

Rakas, J.; Ding, C.; Murthi, A.; Lukovic, J.; Bajat, B.

2016-12-01

Lightning is a serious hazard that can cause significant impacts on human infrastructure. In the aviation industry, lightning strikes cause damage and outages to air traffic control equipment and facilities at airports that result in major disruptions in commercial air travel, compounding delays during storm events that lead to losses in the millions of dollars. To date poor attention has been given to how lightning might change with the increase of greenhouse gases and temperature. Under some climate change scenarios, the increase in the occurrence and severity of storms in the future with potential for increases in lightning activity has been studied. Recent findings suggest that lighting rates will increase 12 percent per every degree Celsius rise in global temperatures. That will results to a 50 percent increase by the end of the century. Accurate prediction of the intensity and frequency of lightning strikes is therefore required by the air traffic management and control sector in order to develop more robust adaptation and mitigation strategies under the threat of global climate change and increasing lightning rates. In this work, we use the regression kriging method to predict lightning strikes over several regions over the contiguous United Sates using two meteorological variables- namely convective available potential energy (CAPE) and total precipitation rate. These two variables are used as a measure of storm convection, since strong convections are related to more lightning. Specifically, CAPE multiplied by precipitation is used as a proxy for lightning strikes owing to a strong linear relationship between the two. These two meteorological variables are obtained from a subset of models used in phase 5 of the coupled model inter-comparison experiment pertaining to the "high emissions" climate change scenario corresponding to the representative concentration pathway (RCP) 8.5. Precipitation observations from the National Weather Cooperative Network (COOP) were incorporated as an additional dataset. This scenario indicates a doubling of CAPE and precipitation resulting in significant increases in CAPE×precipitation by the end of the century. Overall, this research highlights the use of global climate models and observations to assess climate change impacts on aviation.

Essays on the Economics of Climate Change, Biofuel and Food Prices

NASA Astrophysics Data System (ADS)

Seguin, Charles

Climate change is likely to be the most important global pollution problem that humanity has had to face so far. In this dissertation, I tackle issues directly and indirectly related to climate change, bringing my modest contribution to the body of human creativity trying to deal with climate change. First, I look at the impact of non-convex feedbacks on the optimal climate policy. Second, I try to derive the optimal biofuel policy acknowledging the potential negative impacts that biofuel production might have on food supply. Finally, I test empirically for the presence of loss aversion in food purchases, which might play a role in the consumer response to food price changes brought about by biofuel production. Non-convexities in feedback processes are increasingly found to be important in the climate system. To evaluate their impact on the optimal greenhouse gas (GHG) abate- ment policy, I introduce non-convex feedbacks in a stochastic pollution control model. I numerically calibrate the model to represent the mitigation of greenhouse gas (GHG) emissions contributing to global climate change. This approach makes two contributions to the literature. First, it develops a framework to tackle stochastic non-convex pollu- tion management problems. Second, it applies this framework to the problem of climate change. This approach is in contrast to most of the economic literature on climate change that focuses either on linear feedbacks or environmental thresholds. I find that non-convex feedbacks lead to a decision threshold in the optimal mitigation policy, and I characterize how this threshold depends on feedback parameters and stochasticity. There is great hope that biofuel can help reduce greenhouse gas emissions from fossil fuel. However, there are some concerns that biofuel would increase food prices. In an optimal control model, a co-author and I look at the optimal biofuel production when it competes for land with food production. In addition oil is not exhaustible and output is subject to climate change induced damages. We find that the competitive outcome does not necessarily yield an underproduction of biofuels, but when it does, second best policies like subsidies and mandates can improve welfare. In marketing, there has been extensive empirical research to ascertain whether there is evidence of loss aversion as predicted by several reference price preference theories. Most of that literature finds that there is indeed evidence of loss aversion for many different goods. I argue that it is possible that some of that evidence seemingly supporting loss aversion arises because price endogeneity is not properly taken into account. Using scanner data I study four product categories: bread, chicken, corn and tortilla chips, and pasta. Taking prices as exogenous, I find evidence of loss aversion for bread and corn and tortilla chips. However, when instrumenting prices, the "loss aversion evidence" disappears.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland.

PubMed

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland

NASA Astrophysics Data System (ADS)

Ren, Shilong; Chen, Xiaoqiu; An, Shuai

2017-04-01

Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology.

Continuous and discrete extreme climatic events affecting the dynamics of a high-arctic reindeer population.

PubMed

Chan, Kung-Sik; Mysterud, Atle; Øritsland, Nils Are; Severinsen, Torbjørn; Stenseth, Nils Chr

2005-10-01

Climate at northern latitudes are currently changing both with regard to the mean and the temporal variability at any given site, increasing the frequency of extreme events such as cold and warm spells. Here we use a conceptually new modelling approach with two different dynamic terms of the climatic effects on a Svalbard reindeer population (the Brøggerhalvøya population) which underwent an extreme icing event ("locked pastures") with 80% reduction in population size during one winter (1993/94). One term captures the continuous and linear effect depending upon the Arctic Oscillation and another the discrete (rare) "event" process. The introduction of an "event" parameter describing the discrete extreme winter resulted in a more parsimonious model. Such an approach may be useful in strongly age-structured ungulate populations, with young and very old individuals being particularly prone to mortality factors during adverse conditions (resulting in a population structure that differs before and after extreme climatic events). A simulation study demonstrates that our approach is able to properly detect the ecological effects of such extreme climate events.

Science and policy applicability of the transient climate response to cumulative emissions of carbon

NASA Astrophysics Data System (ADS)

Rogelj, J.

2014-12-01

The Transient Climate Response to cumulative Carbon Emissions (TCRE) provides a quantification of the near-linear relationship between cumulative emissions of carbon and global-mean temperature increase. For its most recent report, the Intergovernmental Panel on Climate Change bases its assessment on a large body of literature which encompasses multiple lines of evidence. In this session I will look at the literature basis that was available for TCRE at the time of the IPCC Fifth Assessment Report, providing an easy-to-access introduction into the TCRE concept. Building on this basis and summarizing my own recent work on this, I will discuss the strengths and weaknesses of the use of TCRE for climate policy. While the TCRE concept provides a clear long-term view of what is required to stabilize global-mean temperature increase, I will explore how TCRE uncertainties might pose problems for using TCRE as the only policy guidance in near-term policy decisions.

Twentieth century bipolar seesaw of the Arctic and Antarctic surface air temperatures

NASA Astrophysics Data System (ADS)

Chylek, Petr; Folland, Chris K.; Lesins, Glen; Dubey, Manvendra K.

2010-04-01

Understanding the phase relationship between climate changes in the Arctic and Antarctic regions is essential for our understanding of the dynamics of the Earth's climate system. In this paper we show that the 20th century de-trended Arctic and Antarctic temperatures vary in anti-phase seesaw pattern - when the Arctic warms the Antarctica cools and visa versa. This is the first time that a bi-polar seesaw pattern has been identified in the 20th century Arctic and Antarctic temperature records. The Arctic (Antarctic) de-trended temperatures are highly correlated (anti-correlated) with the Atlantic Multi-decadal Oscillation (AMO) index suggesting the Atlantic Ocean as a possible link between the climate variability of the Arctic and Antarctic regions. Recent accelerated warming of the Arctic results from a positive reinforcement of the linear warming trend (due to an increasing concentration of greenhouse gases and other possible forcings) by the warming phase of the multidecadal climate variability (due to fluctuations of the Atlantic Ocean circulation).

Manifestation of remote response over the equatorial Pacific in a climate model

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu; Marx, L.

2007-10-01

In this paper we examine the simulations over the tropical Pacific Ocean from long-term simulations of two different versions of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model that have a different global distribution of the inversion clouds. We find that subtle changes made to the numerics of an empirical parameterization of the inversion clouds can result in a significant change in the coupled climate of the equatorial Pacific Ocean. In one coupled simulation of this study we enforce a simple linear spatial filtering of the diagnostic inversion clouds to ameliorate its spatial incoherency (as a result of the Gibbs effect) while in the other we conduct no such filtering. It is found from the comparison of these two simulations that changing the distribution of the shallow inversion clouds prevalent in the subsidence region of the subtropical high over the eastern oceans in this manner has a direct bearing on the surface wind stress through surface pressure modifications. The SST in the warm pool region responds to this modulation of the wind stress, thus affecting the convective activity over the warm pool region and also the large-scale Walker and Hadley circulation. The interannual variability of SST in the eastern equatorial Pacific Ocean is also modulated by this change to the inversion clouds. Consequently, this sensitivity has a bearing on the midlatitude height response. The same set of two experiments were conducted with the respective versions of the atmosphere general circulation model uncoupled to the ocean general circulation model but forced with observed SST to demonstrate that this sensitivity of the mean climate of the equatorial Pacific Ocean is unique to the coupled climate model where atmosphere, ocean and land interact. Therefore a strong case is made for adopting coupled ocean-land-atmosphere framework to develop climate models as against the usual practice of developing component models independent of each other.

Climate of migration? How climate triggered migration from southwest Germany to North America during the 19th century

NASA Astrophysics Data System (ADS)

Glaser, Rüdiger; Himmelsbach, Iso; Bösmeier, Annette

2017-11-01

This paper contributes to the ongoing debate on the extent to which climate and climatic change can have a negative impact on societies by triggering migration, or even contribute to conflict. It summarizes results from the transdisciplinary project Climate of migration (funded 2010-2014), whose innovative title was created by Franz Mauelshagen and Uwe Lübken. The overall goal of this project was to analyze the relation between climatic and socioeconomic parameters and major migration waves from southwest Germany to North America during the 19th century. The article assesses the extent to which climatic conditions triggered these migration waves. The century investigated was in general characterized by the Little Ice Age with three distinct cooling periods, causing major glacier advances in the alpine regions and numerous climatic extremes such as major floods, droughts and severe winter. Societal changes were tremendous, marked by the warfare during the Napoleonic era (until 1815), the abolition of serfdom (1817), the bourgeois revolution (1847/48), economic freedom (1862), the beginning of industrialization accompanied by large-scale rural-urban migration resulting in urban poverty, and finally by the foundation of the German Empire in 1871.

The presented study is based on quantitative data and a qualitative, information-based discourse analysis. It considers climatic conditions as well as socioeconomic and political issues, leading to the hypothesis of a chain of effects ranging from unfavorable climatic conditions to a decrease in crop yields to rising cereal prices and finally to emigration. These circumstances were investigated extensively for the peak emigration years identified with each migration wave. Furthermore, the long-term relations between emigration and the prevailing climatic conditions, crop yields and cereal prices were statistically evaluated with a sequence of linear models which were significant with explanatory power between 22 and 38 %.

An extended linear scaling method for downscaling temperature and its implication in the Jhelum River basin, Pakistan, and India, using CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Mahmood, Rashid; JIA, Shaofeng

2017-11-01

In this study, the linear scaling method used for the downscaling of temperature was extended from monthly scaling factors to daily scaling factors (SFs) to improve the daily variations in the corrected temperature. In the original linear scaling (OLS), mean monthly SFs are used to correct the future data, but mean daily SFs are used to correct the future data in the extended linear scaling (ELS) method. The proposed method was evaluated in the Jhelum River basin for the period 1986-2000, using the observed maximum temperature (Tmax) and minimum temperature (Tmin) of 18 climate stations and the simulated Tmax and Tmin of five global climate models (GCMs) (GFDL-ESM2G, NorESM1-ME, HadGEM2-ES, MIROC5, and CanESM2), and the method was also compared with OLS to observe the improvement. Before the evaluation of ELS, these GCMs were also evaluated using their raw data against the observed data for the same period (1986-2000). Four statistical indicators, i.e., error in mean, error in standard deviation, root mean square error, and correlation coefficient, were used for the evaluation process. The evaluation results with GCMs' raw data showed that GFDL-ESM2G and MIROC5 performed better than other GCMs according to all the indicators but with unsatisfactory results that confine their direct application in the basin. Nevertheless, after the correction with ELS, a noticeable improvement was observed in all the indicators except correlation coefficient because this method only adjusts (corrects) the magnitude. It was also noticed that the daily variations of the observed data were better captured by the corrected data with ELS than OLS. Finally, the ELS method was applied for the downscaling of five GCMs' Tmax and Tmin for the period of 2041-2070 under RCP8.5 in the Jhelum basin. The results showed that the basin would face hotter climate in the future relative to the present climate, which may result in increasing water requirements in public, industrial, and agriculture sectors; change in the hydrological cycle and monsoon pattern; and lack of glaciers in the basin.

Evaluation of gridding procedures for air temperature over Southern Africa

NASA Astrophysics Data System (ADS)

Eiselt, Kai-Uwe; Kaspar, Frank; Mölg, Thomas; Krähenmann, Stefan; Posada, Rafael; Riede, Jens O.

2017-06-01

Africa is considered to be highly vulnerable to climate change, yet the availability of observational data and derived products is limited. As one element of the SASSCAL initiative (Southern African Science Service Centre for Climate Change and Adaptive Land Management), a cooperation of Angola, Botswana, Namibia, Zambia, South Africa and Germany, networks of automatic weather stations have been installed or improved (http://www.sasscalweathernet.org). The increased availability of meteorological observations improves the quality of gridded products for the region. Here we compare interpolation methods for monthly minimum and maximum temperatures which were calculated from hourly measurements. Due to a lack of longterm records we focused on data ranging from September 2014 to August 2016. The best interpolation results have been achieved combining multiple linear regression (elevation, a continentality index and latitude as predictors) with three dimensional inverse distance weighted interpolation.

Understanding multidecadal variability in ENSO amplitude

NASA Astrophysics Data System (ADS)

Russell, A.; Gnanadesikan, A.

2013-12-01

Sea surface temperatures (SSTs) in the tropical Pacific vary as a result of the coupling between the ocean and atmosphere driven largely by the El Niño - Southern Oscillation (ENSO). ENSO has a large impact on the local climate and hydrology of the tropical Pacific, as well as broad-reaching effects on global climate. ENSO amplitude is known to vary on long timescales, which makes it very difficult to quantify its response to climate change and constrain the physical processes that drive it. In order to assess the extent of unforced multidecadal changes in ENSO variability, a linear regression of local SST changes is applied to the GFDL CM2.1 model 4000-yr pre-industrial control run. The resulting regression coefficient strengths, which represent the sensitivity of SST changes to thermocline depth and zonal wind stress, vary by up to a factor of 2 on multi-decadal time scales. This long-term modulation in ocean-atmosphere coupling is highly correlated with ENSO variability, but do not explain the reasons for such variability. Variation in the relationship between SST changes and wind stress points to a role for changing stratification in the central equatorial Pacific in modulating ENSO amplitudes with stronger stratification reducing the response to winds. The main driving mechanism we have identified for higher ENSO variance are changes in the response of zonal winds to SST anomalies. The shifting convection and precipitation patterns associated with the changing state of the atmosphere also contribute to the variability of the regression coefficients. These mechanisms drive much of the variability in ENSO amplitude and hence ocean-atmosphere coupling in the tropical Pacific.

Effects of CO2 Physiological Forcing on Amazon Climate

NASA Astrophysics Data System (ADS)

Halladay, K.; Good, P.; Kay, G.; Betts, R.

2014-12-01

Earth system models provide us with an opportunity to examine the complex interactions and feedbacks between land surface, vegetation and atmosphere. A more thorough understanding of these interactions is essential in reducing uncertainty surrounding the potential impacts of climate and environmental change on the future state and extent of the Amazon rainforest. This forest is a important resource for the region and globally in terms of ecosystem services, hydrology and biodiversity. We aim to investigate the effect of CO2 physiological forcing on the Amazon rainforest and its feedback on regional climate by using the CMIP5 idealised 1% CO2 simulations with a focus on HadGEM2-ES. In these simulations, the atmospheric CO2 concentration is increased by 1% per year for 140 years, reaching around 1150ppm at the end of the simulation. The use of idealised simulations allows the effect of CO2 to be separated from other forcings and the sensitivities to be quantified. In particular, it enables non-linear feedbacks to be identified. In addition to the fully coupled 1% CO2 simulation, in which all schemes respond to the forcing, we use simulations in which (a) only the biochemistry scheme sees the rising CO2 concentration, and (b) in which rising CO2 is only seen by the radiation scheme. With these simulations we examine the degree to which CO2 effects are additive or non-linear when in combination. We also show regional differences in climate and vegetation response, highlighting areas of increased sensitivity.

How does climate warming affect plant-pollinator interactions?

PubMed

Hegland, Stein Joar; Nielsen, Anders; Lázaro, Amparo; Bjerknes, Anne-Line; Totland, Ørjan

2009-02-01

Climate warming affects the phenology, local abundance and large-scale distribution of plants and pollinators. Despite this, there is still limited knowledge of how elevated temperatures affect plant-pollinator mutualisms and how changed availability of mutualistic partners influences the persistence of interacting species. Here we review the evidence of climate warming effects on plants and pollinators and discuss how their interactions may be affected by increased temperatures. The onset of flowering in plants and first appearance dates of pollinators in several cases appear to advance linearly in response to recent temperature increases. Phenological responses to climate warming may therefore occur at parallel magnitudes in plants and pollinators, although considerable variation in responses across species should be expected. Despite the overall similarities in responses, a few studies have shown that climate warming may generate temporal mismatches among the mutualistic partners. Mismatches in pollination interactions are still rarely explored and their demographic consequences are largely unknown. Studies on multi-species plant-pollinator assemblages indicate that the overall structure of pollination networks probably are robust against perturbations caused by climate warming. We suggest potential ways of studying warming-caused mismatches and their consequences for plant-pollinator interactions, and highlight the strengths and limitations of such approaches.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

The effects of ground hydrology on climate sensitivity to solar constant variations

NASA Technical Reports Server (NTRS)

Chou, S. H.; Curran, R. J.; Ohring, G.

1979-01-01

The effects of two different evaporation parameterizations on the climate sensitivity to solar constant variations are investigated by using a zonally averaged climate model. The model is based on a two-level quasi-geostrophic zonally averaged annual mean model. One of the evaporation parameterizations tested is a nonlinear formulation with the Bowen ratio determined by the predicted vertical temperature and humidity gradients near the earth's surface. The other is the linear formulation with the Bowen ratio essentially determined by the prescribed linear coefficient.

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

PubMed

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

2014-01-01

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

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

NASA Technical Reports Server (NTRS)

Rind, David; Lonergan, P.; Shah, K.

1999-01-01

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Modelling the Holderness coast, eastern England: Past, present and future

NASA Astrophysics Data System (ADS)

Barkwith, A.; Limber, P. W.; Thomas, C. W.; Murray, A.; Jordan, H. M.; Ellis, M. A.

2012-12-01

The Holderness coast of eastern Yorkshire, England, is the most rapidly eroding coastline in Europe. Erosion can locally exceed 10 m in a single year and rates average 0.5 to 3 m yr-1, generally increasing from north to south. Pinned in the north by a chalk headland, the soft till coastline has a characteristic open spiral form terminated by a spit to the south. Erosion currently threatens local communities and infrastructure, including nationally important gas installations. Interventions to restrict local erosion usually result in enhanced erosion in adjacent, unprotected sections of coast, mirroring morphology seen on the large scale. We have initiated a modelling study to investigate the key controls on the form and evolution of this coastline, and its response to climate change, building on the Coastline Evolution Model (CEM) developed at Duke University, NC. We have adapted the CEM to permit an ensemble of simulations to be undertaken, based upon modified offshore wave climates, initial conditions and forcing factors. The CEM follows a standard 1d approach, where the cross-shore is collapsed into a single data point, allowing the planform shoreline shape and dynamics to be simulated. The model facilitates study of a coast with variable erosion rates, and enables simulation of coastline evolution when sediment is supplied from an eroding shoreface. Additionally, the CEM is adapted to use an observed two year, offshore wave climate data set as input. Initial work focussed on reconstruction of current coastline shape from an ensemble of hypothetical early Holocene shoreface positions and past wave climates. First order reconstruction of shoreline shape was achieved using several differing initial conditions and wave climates. For the majority of successful simulations, a steady state was noted for proceeding years, where erosion proceeds at an equal rate along the length of the coast south of the headland. Together with a sensitivity analysis, the derivation of the current coastline provided initial conditions for the second phase of the work: simulating the morphological response of the Holderness coastline to possible future changes in climate over the next century. An ensemble of future possible wave climate perturbations was generated from predictions of the likely response of the North Sea to future climate change over the next century, and applied linearly to the observed wave climate as each simulation progressed. The ensemble output was compared to a baseline simulation, run for a century under current wave climate, to assess the impact of predicted future climate on coastal erosion. Although this study does not currently take into account the changes in storm frequency, rises in sea level or the anthropogenic inputs that could influence the results, the initial output indicates erosional rates over the next century are likely to be retarded for the Holderness coastline under a changing climate.

Development and study of a parallel algorithm of iteratively forming latent functionally-determined structures for classification and analysis of meteorological data

NASA Astrophysics Data System (ADS)

Sorokin, V. A.; Volkov, Yu V.; Sherstneva, A. I.; Botygin, I. A.

2016-11-01

This paper overviews a method of generating climate regions based on an analytic signal theory. When applied to atmospheric surface layer temperature data sets, the method allows forming climatic structures with the corresponding changes in the temperature to make conclusions on the uniformity of climate in an area and to trace the climate changes in time by analyzing the type group shifts. The algorithm is based on the fact that the frequency spectrum of the thermal oscillation process is narrow-banded and has only one mode for most weather stations. This allows using the analytic signal theory, causality conditions and introducing an oscillation phase. The annual component of the phase, being a linear function, was removed by the least squares method. The remaining phase fluctuations allow consistent studying of their coordinated behavior and timing, using the Pearson correlation coefficient for dependence evaluation. This study includes program experiments to evaluate the calculation efficiency in the phase grouping task. The paper also overviews some single-threaded and multi-threaded computing models. It is shown that the phase grouping algorithm for meteorological data can be parallelized and that a multi-threaded implementation leads to a 25-30% increase in the performance.

Coupling between air travel and climate

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Global assessment of experimental climate warming on tundra vegetation: heterogeneity over space and time.

PubMed

Elmendorf, Sarah C; Henry, Gregory H R; Hollister, Robert D; Björk, Robert G; Bjorkman, Anne D; Callaghan, Terry V; Collier, Laura Siegwart; Cooper, Elisabeth J; Cornelissen, Johannes H C; Day, Thomas A; Fosaa, Anna Maria; Gould, William A; Grétarsdóttir, Járngerður; Harte, John; Hermanutz, Luise; Hik, David S; Hofgaard, Annika; Jarrad, Frith; Jónsdóttir, Ingibjörg Svala; Keuper, Frida; Klanderud, Kari; Klein, Julia A; Koh, Saewan; Kudo, Gaku; Lang, Simone I; Loewen, Val; May, Jeremy L; Mercado, Joel; Michelsen, Anders; Molau, Ulf; Myers-Smith, Isla H; Oberbauer, Steven F; Pieper, Sara; Post, Eric; Rixen, Christian; Robinson, Clare H; Schmidt, Niels Martin; Shaver, Gaius R; Stenström, Anna; Tolvanen, Anne; Totland, Orjan; Troxler, Tiffany; Wahren, Carl-Henrik; Webber, Patrick J; Welker, Jeffery M; Wookey, Philip A

2012-02-01

Understanding the sensitivity of tundra vegetation to climate warming is critical to forecasting future biodiversity and vegetation feedbacks to climate. In situ warming experiments accelerate climate change on a small scale to forecast responses of local plant communities. Limitations of this approach include the apparent site-specificity of results and uncertainty about the power of short-term studies to anticipate longer term change. We address these issues with a synthesis of 61 experimental warming studies, of up to 20 years duration, in tundra sites worldwide. The response of plant groups to warming often differed with ambient summer temperature, soil moisture and experimental duration. Shrubs increased with warming only where ambient temperature was high, whereas graminoids increased primarily in the coldest study sites. Linear increases in effect size over time were frequently observed. There was little indication of saturating or accelerating effects, as would be predicted if negative or positive vegetation feedbacks were common. These results indicate that tundra vegetation exhibits strong regional variation in response to warming, and that in vulnerable regions, cumulative effects of long-term warming on tundra vegetation - and associated ecosystem consequences - have the potential to be much greater than we have observed to date. © 2011 Blackwell Publishing Ltd/CNRS.

The local and global climate forcings induced inhomogeneity of Indian rainfall.

PubMed

Nair, P J; Chakraborty, A; Varikoden, H; Francis, P A; Kuttippurath, J

2018-04-16

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

Water2Invest: Global facility for calculating investments needed to bridge the climate-induced water gap

NASA Astrophysics Data System (ADS)

Straatsma, Menno; Droogers, Peter; Brandsma, Jairus; Buytaert, Wouter; Karssenberg, Derek; Meijer, Karen; van Aalst, Maaike; van Beek, Rens; Wada, Yoshihide; Bierkens, Marc

2013-04-01

Decision makers responsible for climate change adaptation investments are confronted with large uncertainties regarding future water availability and water demand, as well as the investment cost required to reduce the water gap. Moreover, scientists have worked hard to increase fundamental knowledge on climate change and its impacts (climate services), while practical use of this knowledge is limited due to a lack of tools for decision support under uncertain long term future scenarios (decision services). The Water2Invest project aims are to (i) assess the joint impact of climate change and socioeconomic change on water scarcity, (ii) integrate impact and potential adaptation in one flow, (iii) prioritize adaptation options to counteract water scarcity on their financial, regional socio-economic and environmental implications, and (iv) deliver all this information in an integrated user-friendly web-based service. Global water availability is computed between 2006 and 2100 using the PCR-GLOBWB water resources model at a 6 minute spatial resolution. Climate change scenarios are based on the fifth Assessment Report (AR5) of the IPCC Coupled Model Intercomparison Project (CMIP5) that defines four CO2 emission scenarios as representative concentration pathways. Water demand is computed for agriculture, industry, domestic, and environmental requirements based on socio-economic scenarios of increase in population and gross domestic product. Using a linear programming algorithm, water is allocated on a monthly basis over the four sectors. Based on these assessments, the user can evaluate various technological and infrastructural adaptation measures to assess the investments needed to bridge the future water gap. Regional environmental and socioeconomic effects of these investments are evaluated, such as environmental flows or downstream effects. A scheme is developed to evaluate the strategies on robustness and flexibility under climate change and scenario uncertainty, and each measure is linked to possibilities for investment and financing mechanisms. The tool can be used by consultants, water authorities, non-governmental and commercial investors alike to test investment strategies, but could also be used by companies as a vehicle for advertisement water saving or crop water productivity technologies that can be evaluated on their effectiveness on the spot. We show initial results based on a preliminary study on the Middle East and North African region.

Bioarchaeology of adaptation to a marginal environment in bronze age Western China.

PubMed

Berger, Elizabeth; Wang, Hui

2017-07-08

This study examines human adaptation to the 4000 BP climate change event, which is said to have increased the marginality of Inner Asian environments. We propose to define "marginal" environments not in relation to a specific economic activity (e.g., agriculture), but in relation to whether humans living there are physiologically stressed. Three sites in the Hexi Corridor of Gansu were studied, one from the early and two from the late Bronze Age (N = 125). The study includes three indicators of physiological stress: linear enamel hypoplasias (LEH); tibial periosteal lesions; and fertility. The early and late Bronze Age groups were compared to examine whether human physiological stress increased. The percent of individuals with LEH declined dramatically, indicating fewer growth disruptions. Tibial periosteal reactions also changed, from mostly active to mostly healing at the time of death, indicating that frailty declined. Fertility, which is sensitive to changes in population health and resource availability, did not change significantly. Counter to the dominant narrative of environmental deterioration and subsistence system collapse, the Bronze Age residents of the Hexi Corridor show no skeletal evidence that they suffered from resource shortages or struggled to adapt in the fluctuating climate that pertained after the 4000 BP climate event. In fact, this study found that people suffered from less frailty and fewer growth disruptions after the unstable climate had persisted for some time. Therefore, in human biological terms, the Hexi Corridor did not become more marginal for human habitation during the Bronze Age. © 2017 Wiley Periodicals, Inc.

Towards a Multi-scale Montecarlo Climate Emulator for Coastal Flooding and Long-Term Coastal Change Modeling: The Beautiful Problem

NASA Astrophysics Data System (ADS)

Rueda, A.; Alvarez Antolinez, J. A.; Hegermiller, C.; Serafin, K.; Anderson, D. L.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Vitousek, S.; Camus, P.; Tomas, A.; Gonzalez, M.; Mendez, F. J.

2016-02-01

Long-term coastal evolution and coastal flooding hazards are the result of the non-linear interaction of multiple oceanographic, hydrological, geological and meteorological forcings (e.g., astronomical tide, monthly mean sea level, large-scale storm surge, dynamic wave set-up, shoreline evolution, backshore erosion). Additionally, interannual variability and trends in storminess and sea level rise are climate drivers that must be considered. Moreover, the chronology of the hydraulic boundary conditions plays an important role since a collection of consecutive minor storm events can have more impact than the 100-yr return level event. Therefore, proper modeling of shoreline erosion, beach recovery and coastal flooding should consider the sequence of storms, the multivariate nature of the hydrodynamic forcings, and the different time scales of interest (seasonality, interannual and decadal variability). To address this `beautiful problem', we propose a hybrid approach that combines: (a) numerical hydrodynamic and morphodynamic models (SWAN for wave transformation, a shoreline change model, X-Beach for modeling infragravity waves and erosion of the backshore during extreme events and RFSM-EDA (Jamieson et al, 2012) for high resolution flooding of the coastal hinterland); (b) long-term data bases (observational and hindcast) of sea state parameters, astronomical tides and non-tidal residuals; and (c) statistical downscaling techniques, non-linear data mining, and extreme value models. The statistical downscaling approaches for multivariate variables are based on circulation patterns (Espejo et al., 2014), the chronology of the circulation patterns (Guanche et al, 2013) and the event hydrographs of multivariate extremes, resulting in a time-dependent climate emulator of hydraulic boundary conditions for coupled simulations of the coastal change and flooding models. ReferencesEspejo et al (2014) Spectral ocean wave climate variability based on circulation patterns, J Phys Oc, doi: 10.1175/JPO-D-13-0276.1 Guanche et al (2013) Autoregressive logistic regression applied to atmospheric circulation patterns, Clim Dyn, doi: 10.1007/s00382-013-1690-3 Jamieson et al (2012) A highly efficient 2D flood model with sub-element topography, Proc. Of the Inst Civil Eng., 165(10), 581-595

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.

Linearized Flux Evolution (LiFE): A technique for rapidly adapting fluxes from full-physics radiative transfer models

NASA Astrophysics Data System (ADS)

Robinson, Tyler D.; Crisp, David

2018-05-01

Solar and thermal radiation are critical aspects of planetary climate, with gradients in radiative energy fluxes driving heating and cooling. Climate models require that radiative transfer tools be versatile, computationally efficient, and accurate. Here, we describe a technique that uses an accurate full-physics radiative transfer model to generate a set of atmospheric radiative quantities which can be used to linearly adapt radiative flux profiles to changes in the atmospheric and surface state-the Linearized Flux Evolution (LiFE) approach. These radiative quantities describe how each model layer in a plane-parallel atmosphere reflects and transmits light, as well as how the layer generates diffuse radiation by thermal emission and by scattering light from the direct solar beam. By computing derivatives of these layer radiative properties with respect to dynamic elements of the atmospheric state, we can then efficiently adapt the flux profiles computed by the full-physics model to new atmospheric states. We validate the LiFE approach, and then apply this approach to Mars, Earth, and Venus, demonstrating the information contained in the layer radiative properties and their derivatives, as well as how the LiFE approach can be used to determine the thermal structure of radiative and radiative-convective equilibrium states in one-dimensional atmospheric models.

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

NASA Astrophysics Data System (ADS)

Mutiibwa, D.; Irmak, S.

2011-12-01

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

Methane emissions associated with the conversion of marshland to cropland and climate change on the Sanjiang Plain of Northeast China from 1950 to 2100

NASA Astrophysics Data System (ADS)

Li, T.; Huang, Y.; Zhang, W.; Yu, Y. Q.

2012-05-01

Wetland loss and climate change are known to alter regional and global methane (CH4) budgets. Over the last six decades, an extensive area of marshland has been converted to cropland on the Sanjiang Plain in Northeast China, and a significant increase in air temperature has also been observed there, while the impacts on regional CH4 budgets remain uncertain. Through model simulation, we estimated the changes in CH4 emissions associated with the conversion of marshland to cropland and climate change in this area. Model simulations indicated a significant reduction of 1.1 Tg yr-1 from the 1950s to the 2000s in regional CH4 emissions. The cumulative reduction of CH4 from 1960 to 2009 was estimated to be ~36 Tg relative to the 1950s, and marshland conversion and the climate contributed 86 % and 14 % of this change, respectively. Interannual variation in precipitation (linear trend with P > 0.2) contributed to yearly fluctuations in CH4 emissions, but the relatively lower amount of precipitation over the period 1960-2009 (47 mm yr-1 lower on average than in the 1950s) contributed ~91 % of the reduction in the area-weighted CH4 flux. Global warming at a rate of 0.3 °C per decade (P < 0.001) has increased CH4 emissions significantly since the 1990s. Relative to the mean of the 1950s, the warming-induced increase in the CH4 flux has averaged 19 kg ha-1 yr-1 over the last two decades. For the RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 scenarios of the fifth IPCC assessment report (AR5), the CH4 flux is predicted to increase by 36 %, 52 %, 78 % and 95 %, respectively, by the 2080s compared to 1961-1990 in response to climate warming and wetting.

Hydroclimate of North Island of New Zealand during the last 45,000 Years.

NASA Astrophysics Data System (ADS)

Piatrunia, N.; Shanahan, T. M.; Augustinus, P. M.; Atkins, D.; Huang, Y.

2016-12-01

Southern hemisphere climate variability and its connection with past changes in the northern hemisphere remains poorly understood. While climate conditions in the polar regions are well-studied, the spatial and temporal resolution of existing southern hemisphere mid-latitude records is limited. New Zealand provides an ideal location for the preservation of high-resolution multi-proxy records in lacustrine cores and the analysis of mid-latitude climate throughout the Holocene and beyond. Here, we present a 45,000-year record of plant wax dD (a proxy for precipitation) and branched GDGT-derived temperatures from Lake Pupuke, on the North Island of New Zealand (36°78.30'S, 174°76.70'E) in order to better constrain changes in the climate of the southern hemisphere mid latitudes. We find that during the last glacial the North Island experienced colder and drier conditions, with temperatures that were > 3.5°C cooler than those experienced during the Holocene. Plant wax dD values vary substantially during the glacial interval, with the most enriched values occurring at 21 kyr and 24.5 kyr. Shifts to more arid conditions during these intervals were associated with intensification of the SH westerlies and the northward migration of the subtropical (STF), subpolar (SPF) and polar fronts (PF). The Lake Pupuke record suggests that deglaciation of New Zealand initiated at 18 kyr, with gradual increases in temperature. dD values continue to decrease gradually through the deglaciation, suggesting a linear response of precipitation to insolation forcing. However, temperature increases abruptly during the Bolling-Allerod warming - coincident with changes in the northern hemisphere. Together, these data suggest a decoupling of the controls on deglacial circulation and temperature changes, with important implications for our understanding of the mechanisms of deglacial climate changes in the southern hemisphere mid-latitudes and the interpretation of proxy records from this region.

Waterfowl Conservation in the US Prairie Pothole Region: Confronting the Complexities of Climate Change

PubMed Central

Niemuth, Neal D.; Fleming, Kathleen K.; Reynolds, Ronald E.

2014-01-01

The Prairie Pothole Region (PPR) is the most important waterfowl production area in North America. However, waterfowl populations there are predicted to decline because of climate-related drying of wetlands. Consequently, changes in the geographic focus of PPR waterfowl conservation have been recommended, which could have long-lasting and costly impacts. We used a 40-year dataset of pond counts collected in the PPR to test hypotheses about climate-related drying. We assessed May (1974–2013) and July (1974–2003) pond numbers in 20 waterfowl survey strata to determine if trends in pond numbers were consistent with predictions of drying. We also assessed trends in precipitation and temperature for the 20 strata and developed models describing May pond numbers from 1974 through 2010 as a function of precipitation, temperature, the previous year’s pond numbers, and location. None of the 20 strata showed significant declines in May pond numbers, although seven strata showed increases over time. July pond numbers declined significantly in one stratum, and increased in seven strata. An index to hydroperiod showed significant increasing trends in three strata, and no strata had decreasing trends. Precipitation increased significantly in two strata and decreased in two from 1974 to 2010; no strata showed significant changes in temperature. The best linear model described pond numbers within all strata as a function of precipitation, temperature, the previous year’s pond numbers, and the latitude and longitude of the stratum, and explained 62% of annual variation in pond numbers. We hypothesize that direct effects of climate change on prairie pothole wetlands and waterfowl may be overshadowed by indirect effects such as intensified land use and increased pressure to drain wetlands. We recommend that an adaptive, data-driven approach be used to resolve uncertainties regarding direct and indirect effects of climate change on prairie wetlands and waterfowl, and guide future conservation efforts. PMID:24937641

Waterfowl conservation in the US Prairie Pothole Region: confronting the complexities of climate change.

PubMed

Niemuth, Neal D; Fleming, Kathleen K; Reynolds, Ronald E

2014-01-01

The Prairie Pothole Region (PPR) is the most important waterfowl production area in North America. However, waterfowl populations there are predicted to decline because of climate-related drying of wetlands. Consequently, changes in the geographic focus of PPR waterfowl conservation have been recommended, which could have long-lasting and costly impacts. We used a 40-year dataset of pond counts collected in the PPR to test hypotheses about climate-related drying. We assessed May (1974-2013) and July (1974-2003) pond numbers in 20 waterfowl survey strata to determine if trends in pond numbers were consistent with predictions of drying. We also assessed trends in precipitation and temperature for the 20 strata and developed models describing May pond numbers from 1974 through 2010 as a function of precipitation, temperature, the previous year's pond numbers, and location. None of the 20 strata showed significant declines in May pond numbers, although seven strata showed increases over time. July pond numbers declined significantly in one stratum, and increased in seven strata. An index to hydroperiod showed significant increasing trends in three strata, and no strata had decreasing trends. Precipitation increased significantly in two strata and decreased in two from 1974 to 2010; no strata showed significant changes in temperature. The best linear model described pond numbers within all strata as a function of precipitation, temperature, the previous year's pond numbers, and the latitude and longitude of the stratum, and explained 62% of annual variation in pond numbers. We hypothesize that direct effects of climate change on prairie pothole wetlands and waterfowl may be overshadowed by indirect effects such as intensified land use and increased pressure to drain wetlands. We recommend that an adaptive, data-driven approach be used to resolve uncertainties regarding direct and indirect effects of climate change on prairie wetlands and waterfowl, and guide future conservation efforts.

Is climate change intensifying the drying-trend in the Caribbean?

NASA Astrophysics Data System (ADS)

Herrera, D. A.; Ault, T.; Fasullo, J.; Carrillo, C. M.

2017-12-01

Since 1950, the Caribbean (11ºN-25ºN; 85ºW-60ºW) has seen a significant drying trend characterized by several recent droughts, some of them contemporaneous with El Niño events. Moreover, the most recent drought from 2013 to 2016 was both the most severe and widespread event since at least 1950, and was associated with high temperatures, likely driven in part by climate change. This work examines the role of increased evaporative demand resulting from warmer temperatures on the drying trend observed in the Caribbean since 1950, using observations and model simulations. Large-scale dynamics associated with drought are also analyzed using sea surface temperature, geopotential height, wind, and precipitation anomalies, as well as radiative fluxes anomalies. Furthermore, land surface model soil moisture and high-resolution self-calibrated Palmer Drought Severity Index (scPDSI) datasets are used to quantify drought severity at local scales. The anthropogenic contribution to drought severity is estimated as the difference between the scPDSI calculated using linearly-detrended temperatures, and the scPDSI computed with the observed trend, with unadjusted precipitation, net radiation, and wind speed. Soil moisture anomalies driven by climate change are derived by comparing a large ensemble of forced simulations against a pre-industrial control. The resulting analysis indicates that anthropogenic forcing has intensified the drying trend in the Caribbean by -0.4 scPDSI-units over 60 years, and has increased the dry-land area by 10%. These findings are consistent with observed potential evapotranspiration (PET) anomalies, which are 30% higher than PET-anomalies estimated using detrended temperatures. These results suggest that climate change is already increasing the risk of drought in the Caribbean by enhancing the atmospheric demand of moisture through temperature, and provide insights into the role of climate change in future drought risk in the region.

Non-linear Feedbacks Between Forest Mortality and Climate Change: Implications for Snow Cover, Water Resources, and Ecosystem Recovery in Western North America (Invited)

NASA Astrophysics Data System (ADS)

Brooks, P. D.; Harpold, A. A.; Biederman, J. A.; Gochis, D. J.; Litvak, M. E.; Ewers, B. E.; Broxton, P. D.; Reed, D. E.

2013-12-01

Unprecedented levels of tree mortality from insect infestation and wildfire are dramatically altering forest structure and composition in Western North America. Warming temperatures and increased drought stress have been implicated as major factors in the increasing spatial extent and frequency of these forest disturbances, but it is unclear how these changes in forest structure will interact with ongoing climate change to affect snowmelt water resources either for society or for ecosystem recovery following mortality. Because surface discharge, groundwater recharge, and ecosystem productivity all depend on seasonal snowmelt, a critical knowledge gap exists not only in predicting discharge, but in quantifying spatial and temporal variability in the partitioning of snowfall into abiotic vapor loss, plant available water, recharge, and streamflow within the complex mosaic of forest disturbance and topography that characterizes western mountain catchments. This presentation will address this knowledge gap by synthesizing recent work on snowpack dynamics and ecosystem productivity from seasonally snow-covered forests along a climate gradient from Arizona to Wyoming; including undisturbed sites, recently burned forests, and areas of extensive insect-induced forest mortality. Both before-after and control-impacted studies of forest disturbance on snow accumulation and ablation suggest that the spatial scale of snow distribution increases following disturbance, but net snow water input in a warming climate will increase only in topographically sheltered areas. While forest disturbance changes spatial scale of snowpack partitioning, the amount and especially the timing of snow cover accumulation and ablation are strongly related to interannual variability in ecosystem productivity with both earlier snowmelt and later snow accumulation associated with decreased carbon uptake. Empirical analyses and modeling are being developed to identify landscapes most sensitive to climate change as well as to develop management alternatives that minimize the effects of disturbance on high elevation forests and the services of water provision and carbon storage they provide.

Implications of a lightning-rich tundra biome for permafrost carbon and vegetation dynamics

NASA Astrophysics Data System (ADS)

Chen, Y.; Veraverbeke, S.; Randerson, J. T.

2017-12-01

Lightning is a major ignition source of wildfires in circumpolar boreal forests but rarely occurs in arctic tundra. While theoretical and empirical work suggests that climate change will increase lightning strikes in temperate regions, much less is known about future changes in lightning across terrestrial ecosystems at high northern latitudes. Here we analyzed the spatial and temporal patterns of lightning flash rate (FR) from the satellite observations and surface detection networks. Regression models between the observed FR from the Optical Transient Detector on the MicroLab-1 satellite (later renamed OV-1) and meteorological parameters, including surface temperature (T), convective available potential energy (CAPE), and convective precipitation (CP) from ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-interim reanalysis, were established and assessed. We found that FR had significant linear correlations with CAPE and CP, and a strong non-linear relationship with T. The statistical model based on T and CP can reproduce most of the spatial and temporal variability in FR in the circumpolar region. By using the regression model and meteorological predictions from 24 earth system models in the Coupled Model Intercomparison Project Phase 5 (CMIP5), we estimated the spatial distribution of FR by the end of the 21st century. Due to increases in surface temperature and convection, modeled FR shows substantial increase in northern biomes, including a 338% change in arctic tundra and a 185% change in regions with permafrost soil carbon reservoirs. These changes highlight a new mechanism by which permafrost carbon is vulnerable to the sustained impacts of climate warming. Increased fire in a warmer and lightning-rich future near the treeline has the potential to accelerate the northward migration of trees, which may further enhance warming and the abundance of lightning strikes.

[Effect of climate change on the fisheries conununity pattern in the overwintering ground of open waters of northern East China Sea].

PubMed

Liu, Zun-lei; Yuan, Xing-wei; Yang, Lin-lin; Yan, Li-ping; Tian, Yong-jun; Chen, Jia-hua

2015-03-01

Data sets of 26 fisheries target species from the fishery-depen-dent and fishery-independent surveys in the overwintering ground of open waters of northern East China Sea (OW-NECS), combined sea surface temperature (SST), were used to examine the links between diversity index, pattern of common variability and climate changes based on the principal component analysis (PCA) and generalized additive model (GAM). The results showed that the shift from a cold regime to a warm regime was detected in SST during the 1970s-2011 with step changes around 1982/ 1983. SST increased during the cold regime and the warm regime before 1998 (warming trend period, 1972-1998), and decreased during the warm regime after 1998 (cooling trend period, 1999-2011). Shannon diversity index was largely dependent on the filefish, which contributed up to 50% of the total production as a single species, with low diversity in the waters of the OW-NECS, during the late 1980s and early 1990s. Excluding the filefish, the diversity index linearly increased and decreased during 1972-1998 and 1999-2011, respectively. The variation pattern generally corresponds with the trend in water temperature, strongly suggesting the effect of the SST on the diversity. The first two components (PC1 and PC2) of PCA for target species, which accounted for 32.43% of the total variance, showed evident decadal variation patterns with a step change during 1992-1999 and inter-annual variability with short-period fluctuation, respectively. It seems that PC1 was associated with large scale climatic change, while PC2 was related to inter-annual oceanographic variability such as ENSO events. Linear fitting results showed winEOF1 had significant effect on PC1, and GAM analysis for PC1 showed that winter EOF1 (winEOF1) and summer EOF2 (sumEOF2) can explain 88.9% of the total variance. Nonlinear effect was also found between PC2 and win EOF1, indicating that the fish community structure, which had predominantly decadal/inter-annual variation patterns, was influenced by inter-annual variations in oceanographic conditions.

A century of changing flows: Forest management changed flow magnitudes and warming advanced the timing of flow in a southwestern US river

PubMed Central

2017-01-01

The continued provision of water from rivers in the southwestern United States to downstream cities, natural communities and species is at risk due to higher temperatures and drought conditions in recent decades. Snowpack and snowfall levels have declined, snowmelt and peak spring flows are arriving earlier, and summer flows have declined. Concurrent to climate change and variation, a century of fire suppression has resulted in dramatic changes to forest conditions, and yet, few studies have focused on determining the degree to which changing forests have altered flows. In this study, we evaluated changes in flow, climate, and forest conditions in the Salt River in central Arizona from 1914–2012 to compare and evaluate the effects of changing forest conditions and temperatures on flows. After using linear regression models to remove the influence of precipitation and temperature, we estimated that annual flows declined by 8–29% from 1914–1963, coincident with a 2-fold increase in basal area, a 2-3-fold increase in canopy cover, and at least a 10-fold increase in forest density within ponderosa pine forests. Streamflow volumes declined by 37–56% in summer and fall months during this period. Declines in climate-adjusted flows reversed at mid-century when spring and annual flows increased by 10–31% from 1964–2012, perhaps due to more winter rainfall. Additionally, peak spring flows occurred about 12 days earlier in this period than in the previous period, coincident with winter and spring temperatures that increased by 1–2°C. While uncertainties remain, this study adds to the knowledge gained in other regions that forest change has had effects on flow that were on par with climate variability and, in the case of mid-century declines, well before the influence of anthropogenic warming. Current large-scale forest restoration projects hold some promise of recovering seasonal flows. PMID:29176868

Among-tree variability and feedback effects result in different growth responses to climate change at the upper treeline in the Swiss Alps.

PubMed

Jochner, Matthias; Bugmann, Harald; Nötzli, Magdalena; Bigler, Christof

2017-10-01

Upper treeline ecotones are important life form boundaries and particularly sensitive to a warming climate. Changes in growth conditions at these ecotones have wide-ranging implications for the provision of ecosystem services in densely populated mountain regions like the European Alps. We quantify climate effects on short- and long-term tree growth responses, focusing on among-tree variability and potential feedback effects. Although among-tree variability is thought to be substantial, it has not been considered systematically yet in studies on growth-climate relationships. We compiled tree-ring data including almost 600 trees of major treeline species ( Larix decidua , Picea abies , Pinus cembra , and Pinus mugo ) from three climate regions of the Swiss Alps. We further acquired tree size distribution data using unmanned aerial vehicles. To account for among-tree variability, we employed information-theoretic model selections based on linear mixed-effects models (LMMs) with flexible choice of monthly temperature effects on growth. We isolated long-term trends in ring-width indices (RWI) in interaction with elevation. The LMMs revealed substantial amounts of previously unquantified among-tree variability, indicating different strategies of single trees regarding when and to what extent to invest assimilates into growth. Furthermore, the LMMs indicated strongly positive temperature effects on growth during short summer periods across all species, and significant contributions of fall ( L. decidua ) and current year's spring ( L. decidua , P. abies ). In the longer term, all species showed consistently positive RWI trends at highest elevations, but different patterns with decreasing elevation. L. decidua exhibited even negative RWI trends compared to the highest treeline sites, whereas P. abies , P. cembra , and P. mugo showed steeper or flatter trends with decreasing elevation. This does not only reflect effects of ameliorated climate conditions on tree growth over time, but also reveals first signs of long-suspected negative and positive feedback of climate change on stand dynamics at treeline.

Matching Social and Biophysical Scales in Extensive Livestock Production as a Basis for Adaptation to Global Change

NASA Astrophysics Data System (ADS)

Sayre, N. F.; Bestelmeyer, B.

2015-12-01

Global livestock production is heterogeneous, and its benefits and costs vary widely across global contexts. Extensive grazing lands (or rangelands) constitute the vast majority of the land dedicated to livestock production globally, but they are relatively minor contributors to livestock-related environmental impacts. Indeed, the greatest potential for environmental damage in these lands lies in their potential for conversion to other uses, including agriculture, mining, energy production and urban development. Managing such conversion requires improving the sustainability of livestock production in the face of fragmentation, ecological and economic marginality and climate change. We present research from Mongolia and the United States demonstrating methods of improving outcomes on rangelands by improving the fit between the scales of social and biophysical processes. Especially in arid and semi-arid settings, rangelands exhibit highly variable productivity over space and time and non-linear or threshold dynamics in vegetation; climate change is projected to exacerbate these challenges and, in some cases, diminish overall productivity. Policy and governance frameworks that enable landscape-scale management and administration enable range livestock producers to adapt to these conditions. Similarly, livestock breeds that have evolved to withstand climate and vegetation change improve producers' prospects in the face of increasing variability and declining productivity. A focus on the relationships among primary production, animal production, spatial connectivity, and scale must underpin adaptation strategies in rangelands.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

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

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

DOE PAGES

Huang, Shengzhi; Leng, Guoyong; Huang, Qiang; ...

2017-07-19

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating themore » potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. In conclusion, this study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.« less

Ongoing climatic extreme dynamics in Siberia

NASA Astrophysics Data System (ADS)

Gordov, E. P.; Shulgina, T. M.; Okladnikov, I. G.; Titov, A. G.

2013-12-01

Ongoing global climate changes accompanied by the restructuring of global processes in the atmosphere and biosphere are strongly pronounced in the Northern Eurasia regions, especially in Siberia. Recent investigations indicate not only large changes in averaged climatic characteristics (Kabanov and Lykosov, 2006, IPCC, 2007; Groisman and Gutman, 2012), but more frequent occurrence and stronger impacts of climatic extremes are reported as well (Bulygina et al., 2007; IPCC, 2012: Climate Extremes, 2012; Oldenborh et al., 2013). This paper provides the results of daily temperature and precipitation extreme dynamics in Siberia for the last three decades (1979 - 2012). Their seasonal dynamics is assessed using 10th and 90th percentile-based threshold indices that characterize frequency, intensity and duration of climatic extremes. To obtain the geographical pattern of these variations with high spatial resolution, the sub-daily temperature data from ECMWF ERA-Interim reanalysis and daily precipitation amounts from APHRODITE JMA dataset were used. All extreme indices and linear trend coefficients have been calculated using web-GIS information-computational platform Climate (http://climate.scert.ru/) developed to support collaborative multidisciplinary investigations of regional climatic changes and their impacts (Gordov et al., 2012). Obtained results show that seasonal dynamics of daily temperature extremes is asymmetric for tails of cold and warm temperature extreme distributions. Namely, the intensity of warming during cold nights is higher than during warm nights, especially at high latitudes of Siberia. The similar dynamics is observed for cold and warm day-time temperatures. Slight summer cooling was observed in the central part of Siberia. It is associated with decrease in warm temperature extremes. In the southern Siberia in winter, we also observe some cooling mostly due to strengthening of the cold temperature extremes. Changes in daily precipitation extremes are spatially inhomogeneous. The largest increase in frequency and intensity of heavy precipitation is observed in the north of East Siberia. Negative trends related to precipitation amount decrease are found in the central West Siberia and in the south of East Siberia. The authors acknowledge partial financial support for this research from the Russian Foundation for Basic Research projects (11-05-01190 and 13-05-12034), SB RAS Integration project 131 and project VIII.80.2.1., the Ministry of Education and Science of the Russian Federation contract 8345 and grant of the President of Russian Federation (decree 181).

Probabilistic accounting of uncertainty in forecasts of species distributions under climate change

USGS Publications Warehouse

Wenger, Seth J.; Som, Nicholas A.; Dauwalter, Daniel C.; Isaak, Daniel J.; Neville, Helen M.; Luce, Charles H.; Dunham, Jason B.; Young, Michael K.; Fausch, Kurt D.; Rieman, Bruce E.

2013-01-01

Forecasts of species distributions under future climates are inherently uncertain, but there have been few attempts to describe this uncertainty comprehensively in a probabilistic manner. We developed a Monte Carlo approach that accounts for uncertainty within generalized linear regression models (parameter uncertainty and residual error), uncertainty among competing models (model uncertainty), and uncertainty in future climate conditions (climate uncertainty) to produce site-specific frequency distributions of occurrence probabilities across a species’ range. We illustrated the method by forecasting suitable habitat for bull trout (Salvelinus confluentus) in the Interior Columbia River Basin, USA, under recent and projected 2040s and 2080s climate conditions. The 95% interval of total suitable habitat under recent conditions was estimated at 30.1–42.5 thousand km; this was predicted to decline to 0.5–7.9 thousand km by the 2080s. Projections for the 2080s showed that the great majority of stream segments would be unsuitable with high certainty, regardless of the climate data set or bull trout model employed. The largest contributor to uncertainty in total suitable habitat was climate uncertainty, followed by parameter uncertainty and model uncertainty. Our approach makes it possible to calculate a full distribution of possible outcomes for a species, and permits ready graphical display of uncertainty for individual locations and of total habitat.

Precipitation Based Malaria Patterns in the Amazon -- Will Deforestation Alter Risk?

NASA Astrophysics Data System (ADS)

Olson, S. H.; Durieux, L.; Elguero, E.; Foley, J.; Gagnon, R.; Guegan, J.; Patz, J.

2007-12-01

The World Health Organization, estimates that forty-two percent of malaria cases are "associated with policies and practices regarding land use, deforestation, water resource management, settlement siting and modified house design". This estimate was drawn from expert opinion and studies performed at local scales, but little research has investigated the cumulative impacts of land use and land cover changes occurring in the Amazon Basin on malaria. Much less is understood about the impact of changing land use and subsequent precipitation regimes on malaria risk. To understand how land use practices may alter malaria patterns in the Basin we present an analysis of municipio (n=755) malaria case data and monthly precipitation patterns between 1996 and 1999. Climate data originated from the CRU TS 2.1 half-degree grid resolution climate data set. We present a hierarchical (random coefficients) log-linear Poisson model relating malaria incidence to precipitation for both municipos and states. At the Basin scale precipitation and cases show strong relationships. Precipitation and cases are asynchronous across the period of observation, but detailed inspection of states and individual municipios reveal geographic dependencies of precipitation and malaria incidence. Future research will link the patterns of precipitation and malaria to anticipated changes in climate from deforestation in the Basin.

Global metabolic impacts of recent climate warming.

PubMed

Dillon, Michael E; Wang, George; Huey, Raymond B

2010-10-07

Documented shifts in geographical ranges, seasonal phenology, community interactions, genetics and extinctions have been attributed to recent global warming. Many such biotic shifts have been detected at mid- to high latitudes in the Northern Hemisphere-a latitudinal pattern that is expected because warming is fastest in these regions. In contrast, shifts in tropical regions are expected to be less marked because warming is less pronounced there. However, biotic impacts of warming are mediated through physiology, and metabolic rate, which is a fundamental measure of physiological activity and ecological impact, increases exponentially rather than linearly with temperature in ectotherms. Therefore, tropical ectotherms (with warm baseline temperatures) should experience larger absolute shifts in metabolic rate than the magnitude of tropical temperature change itself would suggest, but the impact of climate warming on metabolic rate has never been quantified on a global scale. Here we show that estimated changes in terrestrial metabolic rates in the tropics are large, are equivalent in magnitude to those in the north temperate-zone regions, and are in fact far greater than those in the Arctic, even though tropical temperature change has been relatively small. Because of temperature's nonlinear effects on metabolism, tropical organisms, which constitute much of Earth's biodiversity, should be profoundly affected by recent and projected climate warming.

[Effects of climate warming and drying on millet yield in Gansu Province and related countermeasures].

PubMed

Cao, Ling; Wang, Qiang; Deng, Zhen-yong; Guo, Xiao-qin; Ma, Xing-xiang; Ning, Hui-fang

2010-11-01

Based on the data of air temperature, precipitation, and millet yield from Ganzhou, Anding, and Xifeng, the representative stations in Hexi moderate arid oasis irrigation area, moderate sub-arid dry area in middle Gansu, and moderate sub-humid dry area in eastern Gansu, respectively, this paper calculated the regional active accumulated temperature of > or = 0 degrees C, > or =5 degrees C, > or =10 degrees C, > or =15 degrees C, and > or =20 degrees C in millet growth period, and the average temperature and precipitation in millet key growth stages. The millet climatic yield was isolated by orthogonal polynomial, and the change characteristics of climate and millet climatic yield as well as the effects of climate change on millet yield were analyzed by statistical methods of linear tendency, cumulative anomaly, and Mann-Kendall. The results showed that warming and drying were the main regional features in the modern climatic change of Gansu. The regional temperature had a significant upward trend since the early 1990s, while the precipitation was significantly reduced from the late 1980s. There were significant correlations between millet yield and climatic factors. The millet yield in dry areas increased with the increasing temperature and precipitation in millet key growth stages, and that in Hexi Corridor area increased with increasing temperature. Warming and drying affected millet yield prominently. The weather fluctuation index of regional millet yield in Xifeng, Anding, and Ganzhou accounted for 73%, 72%, and 54% of real output coefficient variation, respectively, and the percentages increased significantly after warming. Warming was conducive to the increase of millet production, and the annual increment of millet climatic yield in Xifeng, Anding, and Ganzhou after warming was 30.6, 43.1, and 121.1 kg x hm(-2), respectively. Aiming at the warming and drying trend in Gansu Province in the future, the millet planting area in the Province should be further expanded, and the millet planting structure should be adjusted. At the same time, according to the different regional and yearly climatic types, different varieties should be selected, and various planting measures should be taken.