Characterizing hydroclimatic variability in tributaries of the Upper Colorado River Basin—WY1911-2001

NASA Astrophysics Data System (ADS)

Matter, Margaret A.; Garcia, Luis A.; Fontane, Darrell G.; Bledsoe, Brian

2010-01-01

SummaryMountain snowpack is the main source of water in the semi-arid Colorado River Basin (CRB), and while the demands for water are increasing, competing and often conflicting, the supply is limited and has become increasingly variable over the 20th Century. Greater variability is believed to contribute to lower accuracy in water supply forecasts, plus greater variability violates the assumption of stationarity, a fundamental assumption of many methods used in water resources engineering planning, design and management. Thus, it is essential to understand the underpinnings of hydroclimatic variability in order to accurately predict effects of climate changes and effectively meet future water supply challenges. A new methodology was applied to characterized time series of temperature, precipitation, and streamflow (i.e., historic and reconstructed undepleted flows) according to the three climate regimes that occurred in CRB during the 20th Century. Results for two tributaries in the Upper CRB show that hydroclimatic variability is more deterministic than previously thought because it entails complementary temperature and precipitation patterns associated with wetter or drier conditions on climate regime and annual scales. Complementary temperature and precipitation patterns characterize climate regime type (e.g., cool/wet and warm/dry), and the patterns entail increasing or decreasing temperatures and changes in magnitude and timing of precipitation according to the climate regime type. Accompanying each climate regime on annual scales are complementary temperature ( T) and precipitation ( P) patterns that are associated with upcoming precipitation and annual basin yield (i.e., total annual flow volume at a streamflow gauge). Annual complementary T and P patterns establish by fall, are detectable as early as September, persist to early spring, are related to the relative magnitude of upcoming precipitation and annual basin yield, are unique to climate regime type, and are specific to each river basin. Thus, while most of the water supply in the Upper CRB originates from winter snowpack, statistically significant indictors of relative magnitude of upcoming precipitation and runoff are evident in the fall, well before appreciable snow accumulation. Results of this study suggest strategies that may integrated into existing forecast methods to potentially improve forecast accuracy and advance lead time by as much as six months (i.e., from April 1 to October 1 of the previous year). These techniques also have applications in downscaling climate models and in river restoration and management.

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

NASA Astrophysics Data System (ADS)

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

2010-11-01

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

The modulated annual cycle: an alternative reference frame for climate anomalies

NASA Astrophysics Data System (ADS)

Wu, Zhaohua; Schneider, Edwin K.; Kirtman, Ben P.; Sarachik, E. S.; Huang, Norden E.; Tucker, Compton J.

2008-12-01

In climate science, an anomaly is the deviation of a quantity from its annual cycle. There are many ways to define annual cycle. Traditionally, this annual cycle is taken to be an exact repeat of itself year after year. This stationary annual cycle may not reflect well the intrinsic nonlinearity of the climate system, especially under external forcing. In this paper, we re-examine the reference frame for anomalies by re-examining the annual cycle. We propose an alternative reference frame for climate anomalies, the modulated annual cycle (MAC) that allows the annual cycle to change from year to year, for defining anomalies. In order for this alternative reference frame to be useful, we need to be able to define the instantaneous annual cycle: we therefore also introduce a new method to extract the MAC from climatic data. In the presence of a MAC, modulated in both amplitude and frequency, we can then define an alternative version of an anomaly, this time with respect to the instantaneous MAC rather than a permanent and unchanging AC. Based on this alternative definition of anomalies, we re-examine some familiar physical processes: in particular SST re-emergence and ENSO phase locking to the annual cycle. We find that the re-emergence mechanism may be alternatively interpreted as an explanation of the change of the annual cycle instead of an explanation of the interannual to interdecadal persistence of SST anomalies. We also find that the ENSO phase locking can largely be attributed to the residual annual cycle (the difference of the MAC and the corresponding traditional annual cycle) contained in the traditional anomaly, and, therefore, can be alternatively interpreted as a part of the annual cycle phase locked to the annual cycle itself. In addition to the examples of reinterpretation of physics of well known climate phenomena, we also present an example of the implications of using a MAC against which to define anomalies. We show that using MAC as a reference framework for anomaly can bypass the difficulty brought by concepts such as “decadal variability of summer (or winter) climate” for understanding the low-frequency variability of the climate system. The concept of an amplitude and frequency modulated annual cycle, a method to extract it, and its implications for the interpretation of physical processes, all may contribute potentially to a more consistent and fruitful way of examining past and future climate variability and change.

Climate Prediction Center - Outreach: 41st Annual Climate Diagnostics &

Science.gov Websites

the University of Maine Climate Change Institute and School of Earth and Climate Sciences and is co (drought, heat waves, severe weather, tropical cyclones) in the framework of climate variability and change and including the use of paleoclimate data. Arctic climate variability and change, and linkages to

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

PubMed

Liu, Huiyu; Zhang, Mingyang; Lin, Zhenshan

2017-10-05

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

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

PubMed Central

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

2009-01-01

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

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

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

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

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

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

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

Trend analysis of hydro-climatic variables in the north of Iran

NASA Astrophysics Data System (ADS)

Nikzad Tehrani, E.; Sahour, H.; Booij, M. J.

2018-04-01

Trend analysis of climate variables such as streamflow, precipitation, and temperature provides useful information for understanding the hydrological changes associated with climate change. In this study, a nonparametric Mann-Kendall test was employed to evaluate annual, seasonal, and monthly trends of precipitation and streamflow for the Neka basin in the north of Iran over a 44-year period (1972 to 2015). In addition, the Inverse Distance Weight (IDW) method was used for annual seasonal, monthly, and daily precipitation trends in order to investigate the spatial correlation between precipitation and streamflow trends in the study area. Results showed a downward trend in annual and winter precipitation (Z < -1.96) and an upward trend in annual maximum daily precipitation. Annual and monthly mean flows for most of the months in the Neka basin decreased by 14% significantly, but the annual maximum daily flow increased by 118%. Results for the trend analysis of streamflow and climatic variables showed that there are statistically significant relationships between precipitation and streamflow (p value < 0.05). Correlation coefficients for Kendall, Spearman's rank and linear regression are 0.43, 0.61, and 0.67, respectively. The spatial presentation of the detected precipitation and streamflow trends showed a downward trend for the mean annual precipitation observed in the upstream part of the study area which is consistent with the streamflow trend. Also, there is a good correlation between monthly and seasonal precipitation and streamflow for all sub-basins (Sefidchah, Gelvard, Abelu). In general, from a hydro-climatic point of view, the results showed that the study area is moving towards a situation with more severe drought events.

Is temperature the main cause of dengue rise in non-endemic countries? The case of Argentina

PubMed Central

2012-01-01

Background Dengue cases have increased during the last decades, particularly in non-endemic areas, and Argentina was no exception in the southern transmission fringe. Although temperature rise has been blamed for this, human population growth, increased travel and inefficient vector control may also be implicated. The relative contribution of geographic, demographic and climatic of variables on the occurrence of dengue cases was evaluated. Methods According to dengue history in the country, the study was divided in two decades, a first decade corresponding to the reemergence of the disease and the second including several epidemics. Annual dengue risk was modeled by a temperature-based mechanistic model as annual days of possible transmission. The spatial distribution of dengue occurrence was modeled as a function of the output of the mechanistic model, climatic, geographic and demographic variables for both decades. Results According to the temperature-based model dengue risk increased between the two decades, and epidemics of the last decade coincided with high annual risk. Dengue spatial occurrence was best modeled by a combination of climatic, demographic and geographic variables and province as a grouping factor. It was positively associated with days of possible transmission, human population number, population fall and distance to water bodies. When considered separately, the classification performance of demographic variables was higher than that of climatic and geographic variables. Conclusions Temperature, though useful to estimate annual transmission risk, does not fully describe the distribution of dengue occurrence at the country scale. Indeed, when taken separately, climatic variables performed worse than geographic or demographic variables. A combination of the three types was best for this task. PMID:22768874

El Niño$-$Southern Oscillation frequency cascade

DOE PAGES

Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel

2015-10-19

The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less

El Niño$-$Southern Oscillation frequency cascade

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

Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel

The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less

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

NASA Astrophysics Data System (ADS)

Arain, M. A.

2015-12-01

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

Climate Variability and Yields of Major Staple Food Crops in Northern Ghana

NASA Astrophysics Data System (ADS)

Amikuzuno, J.

2012-12-01

Climate variability, the short-term fluctuations in average weather conditions, and agriculture affect each other. Climate variability affects the agroecological and growing conditions of crops and livestock, and is recently believed to be the greatest impediment to the realisation of the first Millennium Development Goal of reducing poverty and food insecurity in arid and semi-arid regions of developing countries. Conversely, agriculture is a major contributor to climate variability and change by emitting greenhouse gases and reducing the agroecology's potential for carbon sequestration. What however, is the empirical evidence of this inter-dependence of climate variability and agriculture in Sub-Sahara Africa? In this paper, we provide some insight into the long run relationship between inter-annual variations in temperature and rainfall, and annual yields of the most important staple food crops in Northern Ghana. Applying pooled panel data of rainfall, temperature and yields of the selected crops from 1976 to 2010 to cointegration and Granger causality models, there is cogent evidence of cointegration between seasonal, total rainfall and crop yields; and causality from rainfall to crop yields in the Sudano-Guinea Savannah and Guinea Savannah zones of Northern Ghana. This suggests that inter-annual yields of the crops have been influenced by the total mounts of rainfall in the planting season. Temperature variability over the study period is however stationary, and is suspected to have minimal effect if any on crop yields. Overall, the results confirm the appropriateness of our attempt in modelling long-term relationships between the climate and crop yield variables.

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

PubMed

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

2015-01-15

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

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

NASA Astrophysics Data System (ADS)

Cescatti, A.; Marcolla, B.

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

PubMed

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

2014-08-01

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

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

USGS Publications Warehouse

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

2018-01-01

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

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages. PMID:29420548

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

Treesearch

Kyongho Son; Christina Tague; Carolyn Hunsaker

2016-01-01

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

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

PubMed

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

2009-10-01

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

The effect of vaccination coverage and climate on Japanese encephalitis in Sarawak, Malaysia.

PubMed

Impoinvil, Daniel E; Ooi, Mong How; Diggle, Peter J; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P; Baylis, Matthew; Solomon, Tom

2013-01-01

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

Climate variation explains a third of global crop yield variability

PubMed Central

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

2015-01-01

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

Variability of precipitation in Poland under climate change

NASA Astrophysics Data System (ADS)

Szwed, Małgorzata

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Sensitivity of ring growth and carbon allocation to climatic variation vary within ponderosa pine trees.

PubMed

Kerhoulas, Lucy P; Kane, Jeffrey M

2012-01-01

Most dendrochronological studies focus on cores sampled from standard positions (main stem, breast height), yet vertical gradients in hydraulic constraints and priorities for carbon allocation may contribute to different growth sensitivities with position. Using cores taken from five positions (coarse roots, breast height, base of live crown, mid-crown branch and treetop), we investigated how radial growth sensitivity to climate over the period of 1895-2008 varies by position within 36 large ponderosa pines (Pinus ponderosa Dougl.) in northern Arizona. The climate parameters investigated were Palmer Drought Severity Index, water year and monsoon precipitation, maximum annual temperature, minimum annual temperature and average annual temperature. For each study tree, we generated Pearson correlation coefficients between ring width indices from each position and six climate parameters. We also investigated whether the number of missing rings differed among positions and bole heights. We found that tree density did not significantly influence climatic sensitivity to any of the climate parameters investigated at any of the sample positions. Results from three types of analyses suggest that climatic sensitivity of tree growth varied with position height: (i) correlations of radial growth and climate variables consistently increased with height; (ii) model strength based on Akaike's information criterion increased with height, where treetop growth consistently had the highest sensitivity and coarse roots the lowest sensitivity to each climatic parameter; and (iii) the correlation between bole ring width indices decreased with distance between positions. We speculate that increased sensitivity to climate at higher positions is related to hydraulic limitation because higher positions experience greater xylem tensions due to gravitational effects that render these positions more sensitive to climatic stresses. The low sensitivity of root growth to all climatic variables measured suggests that tree carbon allocation to coarse roots is independent of annual climate variability. The greater number of missing rings in branches highlights the fact that canopy development is a low priority for carbon allocation during poor growing conditions.

Regional patterns of interannual variability of catchment water balances across the continental U.S.: A Budyko framework

NASA Astrophysics Data System (ADS)

Carmona, Alejandra M.; Sivapalan, Murugesu; Yaeger, Mary A.; Poveda, Germán.

2014-12-01

Patterns of interannual variability of the annual water balance are explored using data from 190 MOPEX catchments across the continental U.S. This analysis has led to the derivation of a quantitative, dimensionless, Budyko-type framework to characterize the observed interannual variability of annual water balances. The resulting model is expressed in terms of a humidity index that measures the competition between water and energy availability at the annual time scale, and a similarity parameter (α) that captures the net effects of other short-term climate features and local landscape characteristics. This application of the model to the 190 study catchments revealed the existence of space-time symmetry between spatial (between-catchment) variability and general trends in the temporal (between-year) variability of the annual water balances. The MOPEX study catchments were classified into eight similar catchment groups on the basis of magnitudes of the similarity parameter α. Interesting regional trends of α across the continental U.S. were brought out through identification of similarities between the spatial positions of the catchment groups with the mapping of distinctive ecoregions that implicitly take into account common climatic and vegetation characteristics. In this context, this study has introduced a deep sense of similarity that is evident in observed space-time variability of water balances that also reflect the codependence and coevolution of climate and landscape properties.

Estimates of runoff using water-balance and atmospheric general circulation models

USGS Publications Warehouse

Wolock, D.M.; McCabe, G.J.

1999-01-01

The effects of potential climate change on mean annual runoff in the conterminous United States (U.S.) are examined using a simple water-balance model and output from two atmospheric general circulation models (GCMs). The two GCMs are from the Canadian Centre for Climate Prediction and Analysis (CCC) and the Hadley Centre for Climate Prediction and Research (HAD). In general, the CCC GCM climate results in decreases in runoff for the conterminous U.S., and the HAD GCM climate produces increases in runoff. These estimated changes in runoff primarily are the result of estimated changes in precipitation. The changes in mean annual runoff, however, mostly are smaller than the decade-to-decade variability in GCM-based mean annual runoff and errors in GCM-based runoff. The differences in simulated runoff between the two GCMs, together with decade-to-decade variability and errors in GCM-based runoff, cause the estimates of changes in runoff to be uncertain and unreliable.

How Does Snow Persistence Relate to Annual Streamflow in Mountain Watersheds of the Western U.S. With Wet Maritime and Dry Continental Climates?

NASA Astrophysics Data System (ADS)

Hammond, John C.; Saavedra, Freddy A.; Kampf, Stephanie K.

2018-04-01

With climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.

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

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

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

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

PubMed

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

2016-12-28

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

Characteristics of aggregation of daily rainfall in a middle-latitudes region during a climate variability in annual rainfall amount

NASA Astrophysics Data System (ADS)

Lucero, Omar A.; Rozas, Daniel

Climate variability in annual rainfall occurs because the aggregation of daily rainfall changes. A topic open to debate is whether that change takes place because rainfall becomes more intense, or because it rains more often, or a combination of both. The answer to this question is of interest for water resources planning, hydrometeorological design, and agricultural management. Change in the number of rainy days can cause major disruptions in hydrological and ecological systems, with important economic and social effects. Furthermore, the characteristics of daily rainfall aggregation in ongoing climate variability provide a reference to evaluate the capability of GCM to simulate changes in the hydrologic cycle. In this research, we analyze changes in the aggregation of daily rainfall producing a climate positive trend in annual rainfall in central Argentina, in the southern middle-latitudes. This state-of-the-art agricultural region has a semiarid climate with dry and wet seasons. Weather effects in the region influence world-market prices of several crops. Results indicate that the strong positive trend in seasonal and annual rainfall amount is produced by an increase in number of rainy days. This increase takes place in the 3-month periods January-March (summer) and April-June (autumn). These are also the 3-month periods showing a positive trend in the mean of annual rainfall. The mean of the distribution of annual number of rainy day (ANRD) increased in 50% in a 36-year span (starting at 44 days/year). No statistically significant indications on time changes in the probability distribution of daily rainfall amount were found. Non-periodic fluctuations in the time series of annual rainfall were analyzed using an integral wavelet transform. Fluctuations with a time scale of about 10 and 20 years construct the trend in annual rainfall amount. These types of non-periodic fluctuations have been observed in other regions of the world. This suggests that results of this research could have further geographical validity.

Multidecadal climate variability of global lands and oceans

USGS Publications Warehouse

McCabe, G.J.; Palecki, M.A.

2006-01-01

Principal components analysis (PCA) and singular value decomposition (SVD) are used to identify the primary modes of decadal and multidecadal variability in annual global Palmer Drought Severity Index (PDSI) values and sea-surface temperature (SSTs). The PDSI and SST data for 1925-2003 were detrended and smoothed (with a 10-year moving average) to isolate the decadal and multidecadal variability. The first two principal components (PCs) of the PDSI PCA explained almost 38% of the decadal and multidecadal variance in the detrended and smoothed global annual PDSI data. The first two PCs of detrended and smoothed global annual SSTs explained nearly 56% of the decadal variability in global SSTs. The PDSI PCs and the SST PCs are directly correlated in a pairwise fashion. The first PDSI and SST PCs reflect variability of the detrended and smoothed annual Pacific Decadal Oscillation (PDO), as well as detrended and smoothed annual Indian Ocean SSTs. The second set of PCs is strongly associated with the Atlantic Multidecadal Oscillation (AMO). The SVD analysis of the cross-covariance of the PDSI and SST data confirmed the close link between the PDSI and SST modes of decadal and multidecadal variation and provided a verification of the PCA results. These findings indicate that the major modes of multidecadal variations in SSTs and land-surface climate conditions are highly interrelated through a small number of spatially complex but slowly varying teleconnections. Therefore, these relations may be adaptable to providing improved baseline conditions for seasonal climate forecasting. Published in 2006 by John Wiley & Sons, Ltd.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Tropical cloud forest climate variability and the demise of the Monteverde golden toad

PubMed Central

Anchukaitis, Kevin J.; Evans, Michael N.

2010-01-01

Widespread amphibian extinctions in the mountains of the American tropics have been blamed on the interaction of anthropogenic climate change and a lethal pathogen. However, limited meteorological records make it difficult to conclude whether current climate conditions at these sites are actually exceptional in the context of natural variability. We use stable oxygen isotope measurements from trees without annual rings to reconstruct a century of hydroclimatology in the Monteverde Cloud Forest of Costa Rica. High-resolution measurements reveal coherent isotope cycles that provide annual chronological control and paleoclimate information. Climate variability is dominated by interannual variance in dry season moisture associated with El Niño Southern Oscillation events. There is no evidence of a trend associated with global warming. Rather, the extinction of the Monteverde golden toad (Bufo periglenes) appears to have coincided with an exceptionally dry interval caused by the 1986–1987 El Niño event. PMID:20194772

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

NASA Astrophysics Data System (ADS)

Lehoczky, Annamária; Kern, Zoltán; Pongrácz, Rita

2014-05-01

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

Climatic effects on mosquito abundance in Mediterranean wetlands

PubMed Central

2014-01-01

Background The impact of climate change on vector-borne diseases is highly controversial. One of the principal points of debate is whether or not climate influences mosquito abundance, a key factor in disease transmission. Methods To test this hypothesis, we analysed ten years of data (2003–2012) from biweekly surveys to assess inter-annual and seasonal relationships between the abundance of seven mosquito species known to be pathogen vectors (West Nile virus, Usutu virus, dirofilariasis and Plasmodium sp.) and several climatic variables in two wetlands in SW Spain. Results Within-season abundance patterns were related to climatic variables (i.e. temperature, rainfall, tide heights, relative humidity and photoperiod) that varied according to the mosquito species in question. Rainfall during winter months was positively related to Culex pipiens and Ochlerotatus detritus annual abundances. Annual maximum temperatures were non-linearly related to annual Cx. pipiens abundance, while annual mean temperatures were positively related to annual Ochlerotatus caspius abundance. Finally, we modelled shifts in mosquito abundances using the A2 and B2 temperature and rainfall climate change scenarios for the period 2011–2100. While Oc. caspius, an important anthropophilic species, may increase in abundance, no changes are expected for Cx. pipiens or the salt-marsh mosquito Oc. detritus. Conclusions Our results highlight that the effects of climate are species-specific, place-specific and non-linear and that linear approaches will therefore overestimate the effect of climate change on mosquito abundances at high temperatures. Climate warming does not necessarily lead to an increase in mosquito abundance in natural Mediterranean wetlands and will affect, above all, species such as Oc. caspius whose numbers are not closely linked to rainfall and are influenced, rather, by local tidal patterns and temperatures. The final impact of changes in vector abundance on disease frequency will depend on the direct and indirect effects of climate and other parameters related to pathogen amplification and spillover on humans and other vertebrates. PMID:25030527

Climate Variability Program

NASA Technical Reports Server (NTRS)

Halpern, David (Editor)

2002-01-01

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

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

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

Yang, Qichun; Tian, Hanqin; Li, Xia

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Spatiotemporal patterns of evapotranspiration along the North American east coast as influenced by multiple environmental changes

DOE PAGES

Yang, Qichun; Tian, Hanqin; Li, Xia; ...

2014-08-08

The North American east coast has experienced significant land-use and climate changes since the beginning of the 20th century. In this study, using the Dynamic Land Ecosystem Model 2.0 driven by time-series input data of land use, climate and atmospheric CO 2, we examined how these driving forces have affected the spatiotemporal trends and variability of evapotranspiration (ET) in this region during 1901–2008. Annual ET in the North American east coast during this period was 648.3 ± 38.6 mm/year and demonstrated an increasing trend. Factorial model simulations indicated that climate variability explained 76% of the inter-annual ET variability. Although land-usemore » change only explained 16% of the ET temporal variability, afforestation induced the upward trend of ET and increased annual ET by 12.8 mm/year. Elevated atmospheric CO 2 reduced annual ET by 0.84 mm, and its potential impacts under future atmospheric CO 2 levels could be much larger than estimates for the historical 1901–2008 period. Climate change determined the spatial pattern of ET changes across the entire study area, whereas land-use changes dramatically affected ET in watersheds with significant land conversions. In spite of the multiple benefits from afforestation, its impacts on water resources should be considered in future land-use policy making. As a result, elevated ET may also affect fresh water availability for the increasing social and economic water demands.« less

Disentangling the relative role of climate change on tree growth in an extreme Mediterranean environment.

PubMed

Madrigal-González, Jaime; Andivia, Enrique; Zavala, Miguel A; Stoffel, Markus; Calatayud, Joaquín; Sánchez-Salguero, Raúl; Ballesteros-Cánovas, Juan

2018-06-14

Climate change can impair ecosystem functions and services in extensive dry forests worldwide. However, attribution of climate change impacts on tree growth and forest productivity is challenging due to multiple inter-annual patterns of climatic variability associated with atmospheric and oceanic circulations. Moreover, growth responses to rising atmospheric CO 2 , namely carbon fertilization, as well as size ontogenetic changes can obscure the climate change signature as well. Here we apply Structural Equation Models (SEM) to investigate the relative role of climate change on tree growth in an extreme Mediterranean environment (i.e., extreme in terms of the combination of sandy-unconsolidated soils and climatic aridity). Specifically, we analyzed potential direct and indirect pathways by which different sources of climatic variability (i.e. warming and precipitation trends, the North Atlantic Oscillation, [NAO]; the Mediterranean Oscillation, [MOI]; the Atlantic Mediterranean Oscillation, [AMO]) affect aridity through their control on local climate (in terms of mean annual temperature and total annual precipitation), and subsequently tree productivity, in terms of basal area increments (BAI). Our results support the predominant role of Diameter at Breast Height (DHB) as the main growth driver. In terms of climate, NAO and AMO are the most important drivers of tree growth through their control of aridity (via effects of precipitation and temperature, respectively). Furthermore and contrary to current expectations, our findings also support a net positive role of climate warming on growth over the last 50 years and suggest that impacts of climate warming should be evaluated considering multi-annual and multi-decadal periods of local climate defined by atmospheric and oceanic circulation in the North Atlantic. Copyright © 2018 Elsevier B.V. All rights reserved.

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

USGS Publications Warehouse

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

2009-01-01

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

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

PubMed

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

2012-09-01

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

The trend of the multi-scale temporal variability of precipitation in Colorado River Basin

NASA Astrophysics Data System (ADS)

Jiang, P.; Yu, Z.

2011-12-01

Hydrological problems like estimation of flood and drought frequencies under future climate change are not well addressed as a result of the disability of current climate models to provide reliable prediction (especially for precipitation) shorter than 1 month. In order to assess the possible impacts that multi-scale temporal distribution of precipitation may have on the hydrological processes in Colorado River Basin (CRB), a comparative analysis of multi-scale temporal variability of precipitation as well as the trend of extreme precipitation is conducted in four regions controlled by different climate systems. Multi-scale precipitation variability including within-storm patterns and intra-annual, inter-annual and decadal variabilities will be analyzed to explore the possible trends of storm durations, inter-storm periods, average storm precipitation intensities and extremes under both long-term natural climate variability and human-induced warming. Further more, we will examine the ability of current climate models to simulate the multi-scale temporal variability and extremes of precipitation. On the basis of these analyses, a statistical downscaling method will be developed to disaggregate the future precipitation scenarios which will provide a more reliable and finer temporal scale precipitation time series for hydrological modeling. Analysis results and downscaling results will be presented.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia

NASA Astrophysics Data System (ADS)

Ganendran, L. B.; Sidhu, L. A.; Catchpole, E. A.; Chambers, L. E.; Dann, P.

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

Effects of ambient air temperature, humidity and rainfall on annual survival of adult little penguins Eudyptula minor in southeastern Australia.

PubMed

Ganendran, L B; Sidhu, L A; Catchpole, E A; Chambers, L E; Dann, P

2016-08-01

Seabirds are subject to the influences of local climate variables during periods of land-based activities such as breeding and, for some species, moult; particularly if they undergo a catastrophic moult (complete simultaneous moult) as do penguins. We investigated potential relationships between adult penguin survival and land-based climate variables (ambient air temperature, humidity and rainfall) using 46 years of mark-recapture data of little penguins Eudyptula minor gathered at a breeding colony on Phillip Island in southeastern Australia. Our results showed that adult penguin survival had a stronger association with land-based climate variables during the moult period, when birds were unable to go to sea for up to 3 weeks, than during the breeding period, when birds could sacrifice breeding success in favour of survival. Annual adult survival probability was positively associated with humidity during moult and negatively associated with rainfall during moult. Prolonged heat during breeding and moult had a negative association with annual adult survival. Local climate projections suggest increasing days of high temperatures, fewer days of rainfall which will result in more droughts (and by implication, lower humidity) and more extreme rainfall events. All of these predicted climate changes are expected to have a negative impact on adult penguin survival.

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

PubMed

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

2016-07-01

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

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV)], mean maximum August temperature, mean minimum February temperature, soil water surplus between April and September, and occurrence of autumn (fall) hurricanes, were built into a model to simulate adjusted yield values. The CCV model simulates the yield value with an rmse of 5.1 t ha-1. The mean of the adjusted yield data over the study period was 60.4 t ha-1, with values for the highest and lowest years being 73.1 and 50.6 t ha-1, respectively, and a standard deviation of 5.9 t ha-1. Presumably because of the almost constant high water table and soil water availability, higher precipitation totals, which are inversely related to radiation and temperature, tend to have a negative effect on the yields. Past trends in the values of critical climatic variables and general projections of future climate suggest that, with respect to the climatic environment and as long as land drainage is continued and maintained, future levels of sugarcane yield will rise in Louisiana.

Seasonality of Influenza and Respiratory Syncytial Viruses and the Effect of Climate Factors in Subtropical-Tropical Asia Using Influenza-Like Illness Surveillance Data, 2010 -2012.

PubMed

Kamigaki, Taro; Chaw, Liling; Tan, Alvin G; Tamaki, Raita; Alday, Portia P; Javier, Jenaline B; Olveda, Remigio M; Oshitani, Hitoshi; Tallo, Veronica L

2016-01-01

The seasonality of influenza and respiratory syncytial virus (RSV) is well known, and many analyses have been conducted in temperate countries; however, this is still not well understood in tropical countries. Previous studies suggest that climate factors are involved in the seasonality of these viruses. However, the extent of the effect of each climate variable is yet to be defined. We investigated the pattern of seasonality and the effect of climate variables on influenza and RSV at three sites of different latitudes: the Eastern Visayas region and Baguio City in the Philippines, and Okinawa Prefecture in Japan. Wavelet analysis and the dynamic linear regression model were applied. Climate variables used in the analysis included mean temperature, relative and specific humidity, precipitation, and number of rainy days. The Akaike Information Criterion estimated in each model was used to test the improvement of fit in comparison with the baseline model. At all three study sites, annual seasonal peaks were observed in influenza A and RSV; peaks were unclear for influenza B. Ranges of climate variables at the two Philippine sites were narrower and mean variables were significantly different among the three sites. Whereas all climate variables except the number of rainy days improved model fit to the local trend model, their contributions were modest. Mean temperature and specific humidity were positively associated with influenza and RSV at the Philippine sites and negatively associated with influenza A in Okinawa. Precipitation also improved model fit for influenza and RSV at both Philippine sites, except for the influenza A model in the Eastern Visayas. Annual seasonal peaks were observed for influenza A and RSV but were less clear for influenza B at all three study sites. Including additional data from subsequent more years would help to ascertain these findings. Annual amplitude and variation in climate variables are more important than their absolute values for determining their effect on the seasonality of influenza and RSV.

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

PubMed Central

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

2013-01-01

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

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Trachsel, M.; Rehfeld, K.; Telford, R.; Laepple, T.

2017-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution.

Unlocking the climate riddle in forested ecosystems

Treesearch

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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

PubMed

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

2014-08-01

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

Climatically induced interannual variability in aboveground production in forest-tundra and northern taiga of central Siberia.

PubMed

Knorre, Anastasia A; Kirdyanov, Alexander V; Vaganov, Eugene A

2006-02-01

To investigate the variability of primary production of boreal forest ecosystems under the current climatic changes, we compared the dynamics of annual increments and productivity of the main components of plant community (trees, shrubs, mosses) at three sites in the north of Siberia (Russia). Annual radial growth of trees and shrubs was mostly defined by summer temperature regime (positive correlation), but climatic response of woody plants was species specific and depends on local conditions. Dynamics of annual increments of mosses were opposite to tree growth. The difference in climatic response of the different vegetation components of the forest ecosystems indicates that these components seem to be adapted to use climatic conditions during the short and severe northern summer, and decreasing in annual production of one component is usually combined with the increase of other component productivity. Average productivity in the northern forest ecosystems varies from 0.05 to 0.14 t ha(-1) year(-1) for trees, from 0.05 to 0.18 t ha(-1) year(-1) for shrubs and from 0.54 to 0.66 t ha(-1) year(-1) for mosses. Higher values of tree productivity combined with lower annual moss productivity were found in sites in northern taiga in comparison with forest-tundra. Different tendencies in the productivity of the dominant species from each vegetation level (trees, shrubs, mosses) were indicated for the last 10 years studied (1990-1999): while productivity of mosses is increasing, productivity of trees is decreasing, but there is no obvious trend in the productivity of shrubs. Our results show that in the long term, the main contribution to changes in annual biomass productivity in forest-tundra and northern taiga ecosystems under the predicted climatic changes will be determined by living ground cover.

Regional climate services: A regional partnership between NOAA and USDA

USDA-ARS?s Scientific Manuscript database

Climate services in the Midwest and Northern Plains regions have been enhanced by a recent addition of the USDA Climate Hubs to NOAA’s existing network of partners. This new partnership stems from the intrinsic variability of intra and inter-annual climatic conditions, which makes decision-making fo...

Historical versus Contemporary Climate Forcing on the Annual Nesting Variability of Loggerhead Sea Turtles in the Northwest Atlantic Ocean

PubMed Central

Arendt, Michael D.; Schwenter, Jeffrey A.; Witherington, Blair E.; Meylan, Anne B.; Saba, Vincent S.

2013-01-01

A recent analysis suggested that historical climate forcing on the oceanic habitat of neonate sea turtles explained two-thirds of interannual variability in contemporary loggerhead (Caretta caretta) sea turtle nest counts in Florida, where nearly 90% of all nesting by this species in the Northwest Atlantic Ocean occurs. Here, we show that associations between annual nest counts and climate conditions decades prior to nest counts and those conditions one year prior to nest counts were not significantly different. Examination of annual nest count and climate data revealed that statistical artifacts influenced the reported 31-year lag association with nest counts. The projected importance of age 31 neophytes to annual nest counts between 2020 and 2043 was modeled using observed nest counts between 1989 and 2012. Assuming consistent survival rates among cohorts for a 5% population growth trajectory and that one third of the mature female population nests annually, the 41% decline in annual nest counts observed during 1998–2007 was not projected for 2029–2038. This finding suggests that annual nest count trends are more influenced by remigrants than neophytes. Projections under the 5% population growth scenario also suggest that the Peninsular Recovery Unit could attain the demographic recovery criteria of 106,100 annual nests by 2027 if nest counts in 2019 are at least comparable to 2012. Because the first year of life represents only 4% of the time elapsed through age 31, cumulative survival at sea across decades explains most cohort variability, and thus, remigrant population size. Pursuant to the U.S. Endangered Species Act, staggered implementation of protection measures for all loggerhead life stages has taken place since the 1970s. We suggest that the 1998–2007 nesting decline represented a lagged perturbation response to historical anthropogenic impacts, and that subsequent nest count increases since 2008 reflect a potential recovery response. PMID:24339901

Historical versus contemporary climate forcing on the annual nesting variability of loggerhead sea turtles in the Northwest Atlantic Ocean.

PubMed

Arendt, Michael D; Schwenter, Jeffrey A; Witherington, Blair E; Meylan, Anne B; Saba, Vincent S

2013-01-01

A recent analysis suggested that historical climate forcing on the oceanic habitat of neonate sea turtles explained two-thirds of interannual variability in contemporary loggerhead (Caretta caretta) sea turtle nest counts in Florida, where nearly 90% of all nesting by this species in the Northwest Atlantic Ocean occurs. Here, we show that associations between annual nest counts and climate conditions decades prior to nest counts and those conditions one year prior to nest counts were not significantly different. Examination of annual nest count and climate data revealed that statistical artifacts influenced the reported 31-year lag association with nest counts. The projected importance of age 31 neophytes to annual nest counts between 2020 and 2043 was modeled using observed nest counts between 1989 and 2012. Assuming consistent survival rates among cohorts for a 5% population growth trajectory and that one third of the mature female population nests annually, the 41% decline in annual nest counts observed during 1998-2007 was not projected for 2029-2038. This finding suggests that annual nest count trends are more influenced by remigrants than neophytes. Projections under the 5% population growth scenario also suggest that the Peninsular Recovery Unit could attain the demographic recovery criteria of 106,100 annual nests by 2027 if nest counts in 2019 are at least comparable to 2012. Because the first year of life represents only 4% of the time elapsed through age 31, cumulative survival at sea across decades explains most cohort variability, and thus, remigrant population size. Pursuant to the U.S. Endangered Species Act, staggered implementation of protection measures for all loggerhead life stages has taken place since the 1970s. We suggest that the 1998-2007 nesting decline represented a lagged perturbation response to historical anthropogenic impacts, and that subsequent nest count increases since 2008 reflect a potential recovery response.

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

PubMed

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

2012-02-01

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

Reconstructing coastal environmental condition in the eastern Norwegian Sea by means of Arctica islandica sclerochronological records

NASA Astrophysics Data System (ADS)

Trofimova, Tamara; Andersson, Carin

2015-04-01

Paleo archives are fundament in improving our knowledge of the natural climate variability. Established marine proxy records for the ocean, especially for high latitudes, are both sparsely distributed and are poorly resolved in time. The identification and development of new archives and proxies for studying key ocean processes at annual to sub-annual resolution that can extend the marine instrumental record is therefore a clear priority for marine climate science. The bivalve species Arctica islandica is a unique paleoclimatic archive with an exceptional longevity combined with high temporal resolution, due to accretion of annual growth increments. The aim of this study is to use sclerochronological records of A. islandica to extend instrumental hydrographic records and increase our understanding of a variability of a Norwegian Coastal Current (NCC). The NCC transports warm, low-salinity water northwards, which eventually plays role for the Arctic halocline. Moreover, previous investigations showed the connection of properties and variability of the NCC with catches of commercially valuable fishes. The knowledge of the variability of the NCC is also essential for possible future prediction climate conditions and fish stock variability in the region. In this study we use shells of Arctica islandica collected off the coast of Eggum (Lofoten, Norway). The material was obtained from the depth 5-10 m by dredging along the seabed and by means of scuba divers. We examine the growth patterns of living and subfossil shells. Ongoing work mainly focuses on the construction of a composite growth chronology based on increment-width time series. The results we will compare with existing time series of the environment and climatic parameters to determine the controlling factors and test the applicability of growth chronology in a climate reconstruction. Furthermore, we will perform geochemical analyses of the stable isotope composition (δ18O and δ13C) in shell carbonate to identify seasonal signals and reconstruct the surface water temperature on a sub-annual time-scale.

Interactions between rainfall, deforestation and fires during recent years in the Brazilian Amazonia.

PubMed

Aragão, Luiz Eduardo O C; Malhi, Yadvinder; Barbier, Nicolas; Lima, Andre; Shimabukuro, Yosio; Anderson, Liana; Saatchi, Sassan

2008-05-27

Understanding the interplay between climate and land-use dynamics is a fundamental concern for assessing the vulnerability of Amazonia to climate change. In this study, we analyse satellite-derived monthly and annual time series of rainfall, fires and deforestation to explicitly quantify the seasonal patterns and relationships between these three variables, with a particular focus on the Amazonian drought of 2005. Our results demonstrate a marked seasonality with one peak per year for all variables analysed, except deforestation. For the annual cycle, we found correlations above 90% with a time lag between variables. Deforestation and fires reach the highest values three and six months, respectively, after the peak of the rainy season. The cumulative number of hot pixels was linearly related to the size of the area deforested annually from 1998 to 2004 (r2=0.84, p=0.004). During the 2005 drought, the number of hot pixels increased 43% in relation to the expected value for a similar deforested area (approx. 19000km2). We demonstrated that anthropogenic forcing, such as land-use change, is decisive in determining the seasonality and annual patterns of fire occurrence. Moreover, droughts can significantly increase the number of fires in the region even with decreased deforestation rates. We may expect that the ongoing deforestation, currently based on slash and burn procedures, and the use of fires for land management in Amazonia will intensify the impact of droughts associated with natural climate variability or human-induced climate change and, therefore, a large area of forest edge will be under increased risk of fires.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

Effects of simulated daily precipitation patterns on annual plant populations depend on life stage and climatic region.

PubMed

Köchy, Martin

2008-03-27

To improve the understanding of consequences of climate change for annual plant communities, I used a detailed, grid-based model that simulates the effect of daily rainfall variability on individual plants in five climatic regions on a gradient from 100 to 800 mm mean annual precipitation (MAP). The model explicitly considers moisture storage in the soil. I manipulated daily rainfall variability by changing the daily mean rain (DMR, rain volume on rainy days averaged across years for each day of the year) by +/- 20%. At the same time I adjusted intervals appropriately between rainy days for keeping the mean annual volume constant. In factorial combination with changing DMR I also changed MAP by +/- 20%. Increasing MAP generally increased water availability, establishment, and peak shoot biomass. Increasing DMR increased the time that water was continuously available to plants in the upper 15 to 30 cm of the soil (longest wet period, LWP). The effect of DMR diminished with increasing humidity of the climate. An interaction between water availability and density-dependent germination increased the establishment of seedlings in the arid region, but in the more humid regions the establishment of seedlings decreased with increasing DMR. As plants matured, competition among individuals and their productivity increased, but the size of these effects decreased with the humidity of the regions. Therefore, peak shoot biomass generally increased with increasing DMR but the effect size diminished from the semiarid to the mesic Mediterranean region. Increasing DMR reduced via LWP the annual variability of biomass in the semiarid and dry Mediterranean regions. More rainstorms (greater DMR) increased the recharge of soil water reservoirs in more arid sites with consequences for germination, establishment, productivity, and population persistence. The order of magnitudes of DMR and MAP overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

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

NASA Astrophysics Data System (ADS)

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

2004-12-01

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

Annually resolved North Atlantic marine climate over the last millennium

NASA Astrophysics Data System (ADS)

Reynolds, D. J.; Scourse, J. D.; Halloran, P. R.; Nederbragt, A. J.; Wanamaker, A. D.; Butler, P. G.; Richardson, C. A.; Heinemeier, J.; Eiríksson, J.; Knudsen, K. L.; Hall, I. R.

2016-12-01

Owing to the lack of absolutely dated oceanographic information before the modern instrumental period, there is currently significant debate as to the role played by North Atlantic Ocean dynamics in previous climate transitions (for example, Medieval Climate Anomaly-Little Ice Age, MCA-LIA). Here we present analyses of a millennial-length, annually resolved and absolutely dated marine δ18O archive. We interpret our record of oxygen isotope ratios from the shells of the long-lived marine bivalve Arctica islandica (δ18O-shell), from the North Icelandic shelf, in relation to seawater density variability and demonstrate that solar and volcanic forcing coupled with ocean circulation dynamics are key drivers of climate variability over the last millennium. During the pre-industrial period (AD 1000-1800) variability in the sub-polar North Atlantic leads changes in Northern Hemisphere surface air temperatures at multi-decadal timescales, indicating that North Atlantic Ocean dynamics played an active role in modulating the response of the atmosphere to solar and volcanic forcing.

Climatic effects on breeding grounds are more important drivers of breeding phenology in migrant birds than carry-over effects from wintering grounds.

PubMed

Ockendon, Nancy; Leech, Dave; Pearce-Higgins, James W

2013-01-01

Long-distance migrants may be particularly vulnerable to climate change on both wintering and breeding grounds. However, the relative importance of climatic variables at different stages of the annual cycle is poorly understood, even in well-studied Palaearctic migrant species. Using a national dataset spanning 46 years, we investigate the impact of wintering ground precipitation and breeding ground temperature on breeding phenology and clutch size of 19 UK migrants. Although both spring temperature and arid zone precipitation were significantly correlated with laying date, the former accounted for 3.5 times more inter-annual variation. Neither climate variable strongly affected clutch size. Thus, although carry-over effects had some impact, they were weaker drivers of reproductive traits than conditions on the breeding grounds.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

How does the terrestrial carbon exchange respond to inter-annual climatic variations? A quantification based on atmospheric CO2 data

NASA Astrophysics Data System (ADS)

Rödenbeck, Christian; Zaehle, Sönke; Keeling, Ralph; Heimann, Martin

2018-04-01

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as inter-annual climate sensitivity. We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical inter-annual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.

Decadal trend of precipitation and temperature patterns and impacts on snow-related variables in a semiarid region, Sierra Nevada, Spain.

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

2016-04-01

In the current context of global change, mountainous areas constitute singular locations in which these changes can be traced. Early detection of significant shifts of snow state variables in semiarid regions can help assess climate variability impacts and future snow dynamics in northern latitudes. The Sierra Nevada mountain range, in southern Spain, is a representative example of snow areas in Mediterranean-climate regions and both monitoring and modelling efforts have been performed to assess this variability and its significant scales. This work presents a decadal trend analysis throughout the 50-yr period 1960-2010 performed on some snow-related variables over Sierra Nevada, in Spain, which is included in the global climate change observatories network around the world. The study area comprises 4583 km2 distributed throughout the five head basins influenced by these mountains, with altitude values ranging from 140 to 3479 m.a.s.l., just 40 km from the Mediterranean coastline. Meteorological variables obtained from 44 weather stations from the National Meteorological Agency were studied and further used as input to the distributed hydrological model WiMMed (Polo et al., 2010), operational at the study area, to obtain selected snow variables. Decadal trends were obtained, together with their statistical significance, over the following variables, averaged over the whole study area: (1) annual precipitation; (2) annual snowfall; annual (3) mean, (4) maximum and (5) minimum daily temperature; annual (6) mean and (7) maximum daily fraction of snow covered areas; (8) annual number of days with snow cover; (9) mean and (10) maximum daily snow water equivalent; (11) annual number of extreme precipitation events; and (12) mean intensity of the annual extreme precipitation events. These variables were also studied over each of the five regions associated to each basin in the range. Globally decreasing decadal trends were obtained for all the meteorological variables, with the exception of the average annual mean and maximum daily temperature. In the case of the snow-related variables, no significant trends are observed at this time scale; nonetheless, a global decreasing rate is predominant in most of the variables. The torrential events are more frequent in the last decades of the study period, with an apparently increasing associated dispersion. This study constitutes a first sound analysis of the long-term observed trends of the snow regime in this area under the context of increasing temperature and decreasing precipitation regimes. The results highlight the complexity of non-linearity in environmental processes in Mediterranean regions, and point out to a significant shift in the precipitation and temperature regime, and thus on the snow-affected hydrological variables in the study area.

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

USGS Publications Warehouse

Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

2007-01-01

Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela.

PubMed

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

2014-01-01

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

Rain, temperature, and child-adolescent height among Native Amazonians in Bolivia.

PubMed

Godoy, R; Goodman, E; Reyes-Garcia, V; Eisenberg, D T A; Leonard, W R; Huanca, T; McDade, T W; Tanner, S; Jha, N

2008-01-01

Global climate change and recent studies on early-life origins of well-being suggest that climate events early in life might affect health later in life. The study tested hypotheses about the association between the level and variability of rain and temperature early in life on the height of children and adolescents in a foraging-farming society of native Amazonians in Bolivia (Tsimane'). Measurements were taken for 525 children aged 2-12 and 218 adolescents aged 13-23 in 13 villages in 2005. Log of standing height was regressed on mean annual level and mean intra-annual monthly coefficient of variation (CV) of rain and mean annual level of temperature during gestation, birth year, and ages 2-4. Controls include age, quinquennium and season of birth, parent's attributes, and dummy variables for surveyors and villages. Climate variables were only related with the height of boys age 2-12. The level and CV of rain during birth year and the CV of rain and level of temperature during ages 2-4 were associated with taller stature. There were no secular changes in temperature (1973-2005) or rain (1943-2005). The height of young females and males is well protected from climate events, but protection works less well for boys ages 2-12.

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.

Biogeographical drivers of ragweed pollen concentrations in Europe

NASA Astrophysics Data System (ADS)

Matyasovszky, István; Makra, László; Tusnády, Gábor; Csépe, Zoltán; Nyúl, László G.; Chapman, Daniel S.; Sümeghy, Zoltán; Szűcs, Gábor; Páldy, Anna; Magyar, Donát; Mányoki, Gergely; Erostyák, János; Bodnár, Károly; Bergmann, Karl-Christian; Deák, Áron József; Thibaudon, Michel; Albertini, Roberto; Bonini, Maira; Šikoparija, Branko; Radišić, Predrag; Gehrig, Regula; Rybníček, Ondřej; Severova, Elena; Rodinkova, Victoria; Prikhodko, Alexander; Maleeva, Anna; Stjepanović, Barbara; Ianovici, Nicoleta; Berger, Uwe; Seliger, Andreja Kofol; Weryszko-Chmielewska, Elżbieta; Šaulienė, Ingrida; Shalaboda, Valentina; Yankova, Raina; Peternel, Renata; Ščevková, Jana; Bullock, James M.

2017-06-01

The drivers of spatial variation in ragweed pollen concentrations, contributing to severe allergic rhinitis and asthma, are poorly quantified. We analysed the spatiotemporal variability in 16-year (1995-2010) annual total (66 stations) and annual total (2010) (162 stations) ragweed pollen counts and 8 independent variables (start, end and duration of the ragweed pollen season, maximum daily and calendar day of the maximum daily ragweed pollen counts, last frost day in spring, first frost day in fall and duration of the frost-free period) for Europe (16 years, 1995-2010) as a function of geographical coordinates. Then annual total pollen counts, annual daily peak pollen counts and date of this peak were regressed against frost-related variables, daily mean temperatures and daily precipitation amounts. To achieve this, we assembled the largest ragweed pollen data set to date for Europe. The dependence of the annual total ragweed pollen counts and the eight independent variables against geographical coordinates clearly distinguishes the three highly infected areas: the Pannonian Plain, Western Lombardy and the Rhône-Alpes region. All the eight variables are sensitive to longitude through its temperature dependence. They are also sensitive to altitude, due to the progressively colder climate with increasing altitude. Both annual total pollen counts and the maximum daily pollen counts depend on the start and the duration of the ragweed pollen season. However, no significant changes were detected in either the eight independent variables as a function of increasing latitude. This is probably due to a mixed climate induced by strong geomorphological inhomogeneities in Europe.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

[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.

Effects of climate variables on intra-annual stem radial increment in Pinus cembra (L.) along the alpine treeline ecotone

PubMed Central

GRUBER, Andreas; ZIMMERMANN, Jolanda; WIESER, Gerhard; OBERHUBER, Walter

2011-01-01

Within the alpine treeline ecotone tree growth is increasingly restricted by extreme climate conditions. Although intra-annual stem growth recorded by dendrometers can be linked to climate, stem diameter increments in slow-growing subalpine trees are masked by changes in tree water status. We tested the hypothesis that intra-annual radial stem growth in Pinus cembra is influenced by different climate variables along the treeline ecotone in the Austrian Alps. Dendrometer traces were compared with dynamics of xylem cell development to date onset of cambial activity and radial stem growth in spring. Daily fluctuations in stem radius reflected changes in tree water status throughout the treeline ecotone. Extracted daily radial increments were significantly correlated with air temperature at the timberline and treeline only, where budburst, cambial activity and enlargement of first tracheids also occurred quite similarly. A close relationship was detected between radial increment and number of enlarging tracheids throughout the treeline ecotone. We conclude that (i) the relationship between climate and radial stem growth within the treeline ecotone is dependent on a close coupling to atmospheric climate conditions and (ii) initiation of cambial activity and radial growth in spring can be distinguished from stem re-hydration by histological analysis. PMID:21423861

Effects of climate variables on intra-annual stem radial increment in Pinus cembra (L.) along the alpine treeline ecotone.

PubMed

Gruber, Andreas; Zimmermann, Jolanda; Wieser, Gerhard; Oberhuber, Walter

2009-08-01

Within the alpine treeline ecotone tree growth is increasingly restricted by extreme climate conditions. Although intra-annual stem growth recorded by dendrometers can be linked to climate, stem diameter increments in slow-growing subalpine trees are masked by changes in tree water status.We tested the hypothesis that intra-annual radial stem growth in Pinus cembra is influenced by different climate variables along the treeline ecotone in the Austrian Alps. Dendrometer traces were compared with dynamics of xylem cell development to date onset of cambial activity and radial stem growth in spring.Daily fluctuations in stem radius reflected changes in tree water status throughout the treeline ecotone. Extracted daily radial increments were significantly correlated with air temperature at the timberline and treeline only, where budburst, cambial activity and enlargement of first tracheids also occurred quite similarly. A close relationship was detected between radial increment and number of enlarging tracheids throughout the treeline ecotone.We conclude that (i) the relationship between climate and radial stem growth within the treeline ecotone is dependent on a close coupling to atmospheric climate conditions and (ii) initiation of cambial activity and radial growth in spring can be distinguished from stem re-hydration by histological analysis.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed

NASA Astrophysics Data System (ADS)

Li, Qiang; Wei, Xiaohua; Zhang, Mingfang; Liu, Wenfei; Giles-Hansen, Krysta; Wang, Yi

2018-02-01

Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.

Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: The Australian case

Treesearch

Grant J. Williamson; Lynda D. Prior; Matt Jolly; Mark A. Cochrane; Brett P. Murphy; David M. J. S. Bowman

2016-01-01

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-...

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas

2016-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.

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

PubMed Central

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

2014-01-01

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

Characterizing phenological vegetation dynamics amidst extreme climate variability in Australia with MODIS VI data

NASA Astrophysics Data System (ADS)

Broich, M.; Huete, A. R.; Xuanlon, M.; Davies, K.; Restrepo-Coupe, N.; Ratana, P.

2012-12-01

Australia's climate is extremely variable with inter-annual rainfall at any given site varying by 5- or 6-fold or more, across the continent. In addition to such inter-annual variability, there can be significant intra-annual variability, especially in monsoonal Australia (e.g. the wet tropical savannas) and Mediterranean climates in SW Australia where prolonged dry seasons occur each year. This presents unique challenges to the characterization of seasonal dynamics with satellite datasets. In contrast to annual reoccurring temperature-driven phenology of northern hemisphere mid-latitudes, vegetation dynamics of the vast and dry Australian interior are poorly quantified by existing remote sensing products. For example, in the current global-based MODIS phenology product, central Australia is covered by ~30% fill values for any given year. Two challenges are specific to Australian landscapes: first, the difficulty of characterizing seasonality of rainfall-driven ecosystems in interior Australia where duration and magnitude of green-up and brown down cycles show high inter annual variability; second, modeling two phenologic layers, the trees and the grass in savannas were the trees are evergreen but the herbaceous understory varies with rainfall. Savannas cover >50% of Australia. Australia's vegetation and climate are different from other continents. A MODIS phenology product capable of characterizing vegetation dynamics across the continent is being developed in this research as part of the AusCover national expert network aiming to provide Australian biophysical remote sensing data time-series and continental-scale map products. These products aim to support the Terrestrial Ecosystem Research Network (TERN) serving ecosystem research in Australia. The MODIS land surface product for Australia first searches the entire time series of each Climate Modeling Grid pixel for low-high-low extreme point sequences. A double logistic function is then fit to each of these sequences allowing identification of growth periods with different magnitudes and durations anywhere in the time series. Results show that the highest absolute variability in peak greenness occurred in cropped areas while the highest relative variability (coefficient of variation) occurred in interior Australia particularly around Lake Eyre, the center of a closed drainage basin in the dry interior of the continent. Across the desert interior, the timing of the green-up onset and the peak greenness was correlated with the landfall of cyclones and the inland penetration and strength of the north Australian summer monsoon (represented by TRMM data). The variability of Australian land surface phenology magnitude and timing was found to be strongly correlated with the swings between La Nina and El Nino events. The information on vegetation dynamics represented here is critical for land surface, fuel accumulation, agricultural production, and permanent ecosystem change modeling in relation to climate trends. A unique research opportunity is provided by recent climate variability: in 2010 a persistent El Nino has given way to a strong two-year La Nina breaking a decade long drought that was followed by record-breaking rainfall across most of the continent and extensive flooding followed by sustained greening.

Interannual variability of mean sea level and its sensitivity to wind climate in an inter-tidal basin

NASA Astrophysics Data System (ADS)

Gerkema, Theo; Duran-Matute, Matias

2017-12-01

The relationship between the annual wind records from a weather station and annual mean sea level in an inter-tidal basin, the Dutch Wadden Sea, is examined. Recent, homogeneous wind records are used, covering the past 2 decades. It is demonstrated that even such a relatively short record is sufficient for finding a convincing relationship. The interannual variability of mean sea level is largely explained by the west-east component of the net wind energy, with some further improvement if one also includes the south-north component and the annual mean atmospheric pressure. Using measured data from a weather station is found to give a slight improvement over reanalysis data, but for both the correlation between annual mean sea level and wind energy in the west-east direction is high. For different tide gauge stations in the Dutch Wadden Sea and along the coast, we find the same qualitative characteristics, but even within this small region, different locations show a different sensitivity of annual mean sea level to wind direction. Correcting observed values of annual mean level for meteorological factors reduces the margin of error (expressed as 95 % confidence interval) by more than a factor of 4 in the trends of the 20-year sea level record. Supplementary data from a numerical hydrodynamical model are used to illustrate the regional variability in annual mean sea level and its interannual variability at a high spatial resolution. This study implies that climatic changes in the strength of winds from a specific direction may affect local annual mean sea level quite significantly.

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2016-02-01

The effects of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The null-space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of predictive uncertainty (due to soil property (parametric) uncertainty) and the inter-annual climate variability due to year to year differences in CESM climate forcings. After calibrating to measured borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant predictive uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Inter-annual climate variability in projected soil moisture content and Stefan number are small. A volume- and time-integrated Stefan number decreases significantly, indicating a shift in subsurface energy utilization in the future climate (latent heat of phase change becomes more important than heat conduction). Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we quantify the relative magnitude of soil property uncertainty to another source of permafrost uncertainty, structural climate model uncertainty. We show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

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

PubMed

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

2014-01-01

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

Measurement of inter- and intra-annual variability of landscape fire activity at a continental scale: the Australian case

NASA Astrophysics Data System (ADS)

Williamson, Grant J.; Prior, Lynda D.; Jolly, W. Matt; Cochrane, Mark A.; Murphy, Brett P.; Bowman, David M. J. S.

2016-03-01

Climate dynamics at diurnal, seasonal and inter-annual scales shape global fire activity, although difficulties of assembling reliable fire and meteorological data with sufficient spatio-temporal resolution have frustrated quantification of this variability. Using Australia as a case study, we combine data from 4760 meteorological stations with 12 years of satellite-derived active fire detections to determine day and night time fire activity, fire season start and end dates, and inter-annual variability, across 61 objectively defined climate regions in three climate zones (monsoon tropics, arid and temperate). We show that geographic patterns of landscape burning (onset and duration) are related to fire weather, resulting in a latitudinal gradient from the monsoon tropics in winter, through the arid zone in all seasons except winter, and then to the temperate zone in summer and autumn. Peak fire activity precedes maximum lightning activity by several months in all regions, signalling the importance of human ignitions in shaping fire seasons. We determined median daily McArthur forest fire danger index (FFDI50) for days and nights when fires were detected: FFDI50 varied substantially between climate zones, reflecting effects of fire management in the temperate zone, fuel limitation in the arid zone and abundance of flammable grasses in the monsoon tropical zone. We found correlations between the proportion of days when FFDI exceeds FFDI50 and the Southern Oscillation index across the arid zone during spring and summer, and Indian Ocean dipole mode index across south-eastern Australia during summer. Our study demonstrates that Australia has a long fire weather season with high inter-annual variability relative to all other continents, making it difficult to detect long term trends. It also provides a way of establishing robust baselines to track changes to fire seasons, and supports a previous conceptual model highlighting multi-temporal scale effects of climate in shaping continental-scale pyrogeography.

Changes in the relationship between annual tree growth and climatic variables for four hardwood species

Treesearch

E.R. Smith; J.C. Rennie

1991-01-01

A study was conducted to characterize temporal and spatial variability in the growth response of four major hardwood species (white oak, chestnut oak, northern red oak, and yellow-poplar) to climatic fluctuations, and to evaluate the role of environmental factors associated with difference in response among individuals. The study incorporated tree-ring data collected...

Sediment Transport Variability in Global Rivers: Implications for the Interpretation of Paleoclimate Signals

NASA Astrophysics Data System (ADS)

Syvitski, J. P.; Hutton, E. W.

2001-12-01

A new numerical approach (HydroTrend, v.2) allows the daily flux of sediment to be estimated for any river, whether gauged or not. The model can be driven by actual climate measurements (precipitation, temperature) or with statistical estimates of climate (modeled climate, remotely-sensed climate). In both cases, the character (e.g. soil depth, relief, vegetation index) of the drainage terrain is needed to complete the model domain. The HydroTrend approach allows us to examine the effects of climate on the supply of sediment to continental margins, and the nature of supply variability. A new relationship is defined as: $Qs = f (Psi) Qs-bar (Q/Q-bar)c+-σ where Qs-bar is the long-term sediment load, Q-bar is the long-term discharge, c and sigma are mean and standard deviation of the inter-annual variability of the rating coefficient, and Psi captures the measurement errors associated with Q and Qs, and the annual transients, affecting the supply of sediment including sediment and water source, and river (flood wave) dynamics. F = F(Psi, s). Smaller-discharge rivers have larger values of s, and s asymptotes to a small but consistent value for larger-discharge rivers. The coefficient c is directly proportional to the long-term suspended load (Qs-bar) and basin relief (R), and inversely proportional to mean annual temperature (T). sigma is directly proportional to the mean annual discharge. The long-term sediment load is given by: Qs-bar = a R1.5 A0.5 TT $ where a is a global constant, A is basin area; and TT is a function of mean annual temperature. This new approach provides estimates of sediment flux at the dynamic (daily) level and provides us a means to experiment on the sensitivity of marine sedimentary deposits in recording a paleoclimate signal. In addition the method provides us with spatial estimates for the flux of sediment to the coastal zone at the global scale.

Adapting to climate variability and change: experiences from cereal-based farming in the central rift and Kobo Valleys, Ethiopia.

PubMed

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions-the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers' perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers' perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Adapting to Climate Variability and Change: Experiences from Cereal-Based Farming in the Central Rift and Kobo Valleys, Ethiopia

NASA Astrophysics Data System (ADS)

Kassie, Belay Tseganeh; Hengsdijk, Huib; Rötter, Reimund; Kahiluoto, Helena; Asseng, Senthold; Van Ittersum, Martin

2013-11-01

Small-holder farmers in Ethiopia are facing several climate related hazards, in particular highly variable rainfall with severe droughts which can have devastating effects on their livelihoods. Projected changes in climate are expected to aggravate the existing challenges. This study examines farmer perceptions on current climate variability and long-term changes, current adaptive strategies, and potential barriers for successful further adaptation in two case study regions—the Central Rift Valley (CRV) and Kobo Valley. The study was based on a household questionnaire, interviews with key stakeholders, and focus group discussions. The result revealed that about 99 % of the respondents at the CRV and 96 % at the Kobo Valley perceived an increase in temperature and 94 % at CRV and 91 % at the Kobo Valley perceived a decrease in rainfall over the last 20-30 years. Inter-annual and intraseasonal rainfall variability also has increased according to the farmers. The observed climate data (1977-2009) also showed an increasing trend in temperature and high inter-annual and intra-seasonal rainfall variability. In contrast to farmers’ perceptions of a decrease in rainfall totals, observed rainfall data showed no statistically significant decline. The interaction among various bio-physical and socio-economic factors, changes in rainfall intensity and reduced water available to crops due to increased hot spells, may have influenced the perception of farmers with respect to rainfall trends. In recent decades, farmers in both the CRV and Kobo have changed farming practices to adapt to perceived climate change and variability, for example, through crop and variety choice, adjustment of cropping calendar, and in situ moisture conservation. These relatively low-cost changes in farm practices were within the limited adaptation capacity of farmers, which may be insufficient to deal with the impacts of future climate change. Anticipated climate change is expected to impose new risks outside the range of current experiences. To enable farmers to adapt to these impacts critical technological, institutional, and market-access constraints need to be removed. Inconsistencies between farmers’ perceptions and observed climate trends (e.g., decrease in annual rainfall) could lead to sub-optimal or counterproductive adaptations, and therefore must be removed by better communication and capacity building, for example through Climate Field Schools. Enabling strategies, which are among others targeted at agricultural inputs, credit supply, market access, and strengthening of local knowledge and information services need to become integral part of government policies to assist farmers to adapt to the impacts of current and future climate change.

Upper-Level Mediterranean Oscillation index and seasonal variability of rainfall and temperature

NASA Astrophysics Data System (ADS)

Redolat, Dario; Monjo, Robert; Lopez-Bustins, Joan A.; Martin-Vide, Javier

2018-02-01

The need for early seasonal forecasts stimulates continuous research in climate teleconnections. The large variability of the Mediterranean climate presents a greater difficulty in predicting climate anomalies. This article reviews teleconnection indices commonly used for the Mediterranean basin and explores possible extensions of one of them, the Mediterranean Oscillation index (MOi). In particular, the anomalies of the geopotential height field at 500 hPa are analyzed using segmentation of the Mediterranean basin in seven spatial windows: three at eastern and four at western. That is, different versions of an Upper-Level Mediterranean Oscillation index (ULMOi) were calculated, and monthly and annual variability of precipitation and temperature were analyzed for 53 observatories from 1951 to 2015. Best versions were selected according to the Pearson correlation, its related p value, and two measures of standardized error. The combination of the Balearic Sea and Libya/Egypt windows was the best for precipitation and temperature, respectively. The ULMOi showed the highest predictive ability in combination with the Atlantic Multidecadal Oscillation index (AMOi) for the annual temperature throughout the Mediterranean basin. The best model built from the indices presented a final mean error between 15 and 25% in annual precipitation for most of the studied area.

Ecophysiological and phenological strategies in seasonally-dry ecosystems: an ecohydrological approach

NASA Astrophysics Data System (ADS)

Vico, Giulia; Manzoni, Stefano; Thompson, Sally; Molini, Annalisa; Porporato, Amilcare

2015-04-01

Seasonally-dry climates are particularly challenging for vegetation, as they are characterized by prolonged dry periods and often marked inter-annual variability. During the dry season plants face predictable physiological stress due to lack of water, whereas the inter-annual variability in rainfall timing and amounts requires plants to develop flexible adaptation strategies. The variety of strategies observed across seasonally-dry (Mediterranean and tropical) ecosystems is indeed wide - ranging from near-isohydric species that adjust stomatal conductance to avoid drought, to anisohydric species that maintain gas exchange during the dry season. A suite of phenological strategies are hypothesized to be associated to ecophysiological strategies. Here we synthetize current knowledge on ecophysiological and phenological adaptations through a comprehensive ecohydrological model linking a soil water balance to a vegetation carbon balance. Climatic regimes are found to select for different phenological strategies that maximize the long-term plant carbon uptake. Inter-annual variability of the duration of the wet season allows coexistence of different drought-deciduous strategies. In contrast, short dry seasons or access to groundwater favour evergreen species. Climatic changes causing more intermittent rainfall and/or shorter wet seasons are predicted to favour drought-deciduous species with opportunistic water use.

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

USGS Publications Warehouse

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

2005-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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

NASA Astrophysics Data System (ADS)

Samuel, Jos M.; Sivapalan, Murugesu

2008-07-01

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

Ad hoc committee on global climate issues: Annual report

USGS Publications Warehouse

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

2000-01-01

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

Importance of scale, land cover, and weather on the abundance of bird species in a managed forest

USGS Publications Warehouse

Grinde, Alexis R.; Hiemi, Gerald J.; Sturtevant, Brian R.; Panci, Hannah; Thogmartin, Wayne E.; Wolter, Peter

2017-01-01

Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.

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

NASA Astrophysics Data System (ADS)

Kärner, Olavi; Post, Piia

2016-11-01

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

The impact of inter-annual rainfall variability on African savannas changes with mean rainfall.

PubMed

Synodinos, Alexis D; Tietjen, Britta; Lohmann, Dirk; Jeltsch, Florian

2018-01-21

Savannas are mixed tree-grass ecosystems whose dynamics are predominantly regulated by resource competition and the temporal variability in climatic and environmental factors such as rainfall and fire. Hence, increasing inter-annual rainfall variability due to climate change could have a significant impact on savannas. To investigate this, we used an ecohydrological model of stochastic differential equations and simulated African savanna dynamics along a gradient of mean annual rainfall (520-780 mm/year) for a range of inter-annual rainfall variabilities. Our simulations produced alternative states of grassland and savanna across the mean rainfall gradient. Increasing inter-annual variability had a negative effect on the savanna state under dry conditions (520 mm/year), and a positive effect under moister conditions (580-780 mm/year). The former resulted from the net negative effect of dry and wet extremes on trees. In semi-arid conditions (520 mm/year), dry extremes caused a loss of tree cover, which could not be recovered during wet extremes because of strong resource competition and the increased frequency of fires. At high mean rainfall (780 mm/year), increased variability enhanced savanna resilience. Here, resources were no longer limiting and the slow tree dynamics buffered against variability by maintaining a stable population during 'dry' extremes, providing the basis for growth during wet extremes. Simultaneously, high rainfall years had a weak marginal benefit on grass cover due to density-regulation and grazing. Our results suggest that the effects of the slow tree and fast grass dynamics on tree-grass interactions will become a major determinant of the savanna vegetation composition with increasing rainfall variability. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate change response of great basin bristlecone pine in the Nevada NSF-EPSCoR Project (www.nvclimatechange.org)

Treesearch

Franco Biondi; Scotty Strachan

2011-01-01

Predicting the future of high-elevation pine populations is closely linked to correctly interpreting their past responses to climatic variability. As a proxy index of climate, dendrochronological records have the advantage of seasonal to annual resolution over multiple centuries to millennia (Bradley 1999). All climate reconstructions rely on the 'uniformity...

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.

Seasonal precipitation forecasting for the Melbourne region using a Self-Organizing Maps approach

NASA Astrophysics Data System (ADS)

Pidoto, Ross; Wallner, Markus; Haberlandt, Uwe

2017-04-01

The Melbourne region experiences highly variable inter-annual rainfall. For close to a decade during the 2000s, below average rainfall seriously affected the environment, water supplies and agriculture. A seasonal rainfall forecasting model for the Melbourne region based on the novel approach of a Self-Organizing Map has been developed and tested for its prediction performance. Predictor variables at varying lead times were first assessed for inclusion within the model by calculating their importance via Random Forests. Predictor variables tested include the climate indices SOI, DMI and N3.4, in addition to gridded global sea surface temperature data. Five forecasting models were developed: an annual model and four seasonal models, each individually optimized for performance through Pearson's correlation r and the Nash-Sutcliffe Efficiency. The annual model showed a prediction performance of r = 0.54 and NSE = 0.14. The best seasonal model was for spring, with r = 0.61 and NSE = 0.31. Autumn was the worst performing seasonal model. The sea surface temperature data contributed fewer predictor variables compared to climate indices. Most predictor variables were supplied at a minimum lead, however some predictors were found at lead times of up to a year.

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

PubMed

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

2016-12-01

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

Hydrothermal extremes at the South-West Pribaikalie during the current climate changes

NASA Astrophysics Data System (ADS)

Voropay, Nadezhda

2017-04-01

Climatic extremes of air temperature and precipitation were analyzed for the Tunka Intermountain Depression (South-West Pribaikalie, Buryatia, Russian Federation). Intermountain depressions occupy a quarter of the territory of the Baikal region. The specific climatic conditions in the depressions are formed due to the geographic location and the influence of latitudinal zonation and altitudinal gradients. Air temperature and precipitation data records from at weather stations for the period 1940-2015 were analyzed. Long-term average annual temperature is negative and varies from -0.8 °C to -2.4 °C. Air temperature absolute minimum is -48 °C, absolute maximum is +36 °C. The long-term average annual precipitation is 370-480 mm, but in some years annual precipitation reach 760 mm. The summer months have about 70% of the total annual precipitation, in July and August the sum may reach 340 mm. Maximum daily sum of rainfalls is 80 mm. The contribution of the global and regional circulation characteristics into the variability of regional climatic characteristics was estimated.

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.

Multi-agent modelling of climate outlooks and food security on a community garden scheme in Limpopo, South Africa.

PubMed

Bharwani, Sukaina; Bithell, Mike; Downing, Thomas E; New, Mark; Washington, Richard; Ziervogel, Gina

2005-11-29

Seasonal climate outlooks provide one tool to help decision-makers allocate resources in anticipation of poor, fair or good seasons. The aim of the 'Climate Outlooks and Agent-Based Simulation of Adaptation in South Africa' project has been to investigate whether individuals, who adapt gradually to annual climate variability, are better equipped to respond to longer-term climate variability and change in a sustainable manner. Seasonal climate outlooks provide information on expected annual rainfall and thus can be used to adjust seasonal agricultural strategies to respond to expected climate conditions. A case study of smallholder farmers in a village in Vhembe district, Limpopo Province, South Africa has been used to examine how such climate outlooks might influence agricultural strategies and how this climate information can be improved to be more useful to farmers. Empirical field data has been collected using surveys, participatory approaches and computer-based knowledge elicitation tools to investigate the drivers of decision-making with a focus on the role of climate, market and livelihood needs. This data is used in an agent-based social simulation which incorporates household agents with varying adaptation options which result in differing impacts on crop yields and thus food security, as a result of using or ignoring the seasonal outlook. Key variables are the skill of the forecast, the social communication of the forecast and the range of available household and community-based risk coping strategies. This research provides a novel approach for exploring adaptation within the context of climate change.

[Application of regression tree in analyzing the effects of climate factors on NDVI in loess hilly area of Shaanxi Province].

PubMed

Liu, Yang; Lü, Yi-he; Zheng, Hai-feng; Chen, Li-ding

2010-05-01

Based on the 10-day SPOT VEGETATION NDVI data and the daily meteorological data from 1998 to 2007 in Yan' an City, the main meteorological variables affecting the annual and interannual variations of NDVI were determined by using regression tree. It was found that the effects of test meteorological variables on the variability of NDVI differed with seasons and time lags. Temperature and precipitation were the most important meteorological variables affecting the annual variation of NDVI, and the average highest temperature was the most important meteorological variable affecting the inter-annual variation of NDVI. Regression tree was very powerful in determining the key meteorological variables affecting NDVI variation, but could not build quantitative relations between NDVI and meteorological variables, which limited its further and wider application.

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

PubMed

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

2013-05-24

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

Inter-Annual and Shorter-Term Variability in Physical and Biological Characteristics Across Barrow Canyon in August - September 2005-2014

NASA Astrophysics Data System (ADS)

Ashjian, C. J.; Okkonen, S. R.; Campbell, R. G.; Alatalo, P.

2014-12-01

Late summer physical and biological conditions along a 37-km transect crossing Barrow Canyon have been described for the past ten years as part of an ongoing program, supported by multiple funding sources including the NSF AON, focusing on inter-annual variability and the formation of a bowhead whale feeding hotspot near Barrow. These repeated transects (at least two per year, separated in time by days-weeks) provide an opportunity to assess the inter-annual and shorter term (days-weeks) changes in hydrographic structure, ocean temperature, current velocity and transport, chlorophyll fluorescence, nutrients, and micro- and mesozooplankton community composition and abundance. Inter-annual variability in all properties was high and was associated with larger scale, meteorological forcing. Shorter-term variability could also be high but was strongly influenced by changes in local wind forcing. The sustained sampling at this location provided critical measures of inter-annual variability that should permit detection of longer-term trends that are associated with ongoing climate change.

Does climate directly influence NPP globally?

PubMed

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

2016-01-01

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

Centennial-scale winter climate variability over the last two millennia in the northern Gulf of Mexico based on paired δ18O and Mg/Ca in Globorotalia truncatulinoides

NASA Astrophysics Data System (ADS)

Fortiz, V.; Thirumalai, K.; Richey, J. N.; Quinn, T. M.

2014-12-01

We present a replicated record of paired foraminiferal δ18O and Mg/Ca variations in multi-cores collected from the Garrison Basin (26º43'N, 93º55'W) in the northern Gulf of Mexico (GOM). Using δ18O (sea surface temperature, SST; sea surface salinity, SSS proxy) and Mg/Ca (SST proxy) variations in non-encrusted planktic foraminifer Globorotalia truncatulinoides we produce time series spanning the last two millennia that is characterized by centennial-scale climate variability. We interpret geochemical variations in G. truncatulinoides to reflect winter climate variability because data from a sediment trap, located ~350 km east of the core site, reveal that annual flux of G. truncatulinoides is heavily weighted towards winter (peak production in January-February; Spear et al., 2011). Similar centennial-scale variability is also observed in the foraminiferal geochemistry of Globigerinoides ruber in the same multi-cores, which likely reflect mean annual climate variations. Our replicated results and comparisons to other SST reconstructions from the region lend confidence that the northern GOM surface ocean underwent large, centennial-scale variability, most likely dominated by changes in winter climate. This variability occurred in a time period where climate forcing is small and background conditions are similar to pre-industrial times. References: Spear, J.W.; Poore, R.Z., and Quinn, T.M., 2011, Globorotalia truncatulinoides (dextral) Mg/Ca as a proxy for Gulf of Mexico winter mixed-layer temperature: Evidence from a sediment trap in the northern Gulf of Mexico. Marine Micropaleontology, 80, 53-61.

Inter-annual variability and spatial coherence of net primary productivity across a western Oregon Cascades landscape

Treesearch

Travis J. Woolley; Mark E. Harmon; Kari B. O’Connell

2015-01-01

Inter-annual variability (IAV) of forest Net Primary Productivity (NPP) is a function of both extrinsic (e.g., climate) and intrinsic (e.g., stand dynamics) drivers. As estimates of NPP in forests are scaled from trees to stands to the landscape, an understanding of the relative effects of these factors on spatial and temporal behavior of NPP is important. Although a...

The magnitude and variability of soil-surface CO2 efflux increase with temperature in Hawaiian tropical montane wet forests

Treesearch

Creighton M. Litton; Christian P. Giardina; Jeremy K. Albano; Michael S. Long; Gregory P. Asner

2011-01-01

Soil-surface CO2 efflux (FS; ‘soil respiration’) accounts for 50% of the CO2 released annually by the terrestrial biosphere to the atmosphere, and the magnitude and variability of this flux are likely to be sensitive to climate change. We measured FS in nine permanent plots along a 5.2C mean annual...

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Climate and soil attributes determine plant species turnover in global drylands.

PubMed

Ulrich, Werner; Soliveres, Santiago; Maestre, Fernando T; Gotelli, Nicholas J; Quero, José L; Delgado-Baquerizo, Manuel; Bowker, Matthew A; Eldridge, David J; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R; Hernández, Rosa M; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A; Raveh, Eran; Romão, Roberto L; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2014-12-01

Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake's beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R 2 )), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R 2 )) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Watershed-scale response of groundwater recharge to inter-annual and inter-decadal variability in precipitation (Alberta, Canada)

NASA Astrophysics Data System (ADS)

Hayashi, Masaki; Farrow, Christopher R.

2014-12-01

Groundwater recharge sets a constraint on aquifer water balance in the context of water management. Historical data on groundwater and other relevant hydrological processes can be used to understand the effects of climatic variability on recharge, but such data sets are rare. The climate of the Canadian prairies is characterized by large inter-annual and inter-decadal variability in precipitation, which provides opportunities to examine the response of groundwater recharge to changes in meteorological conditions. A decadal study was conducted in a small (250 km2) prairie watershed in Alberta, Canada. Relative magnitude of annual recharge, indicated by water-level rise, was significantly correlated with a combination of growing-season precipitation and snowmelt runoff, which drives depression-focussed infiltration of meltwater. Annual precipitation was greater than vapour flux at an experimental site in some years and smaller in other years. On average precipitation minus vapour flux was 10 mm y-1, which was comparable to the magnitude of watershed-scale groundwater recharge estimated from creek baseflow. Average baseflow showed a distinct shift from a low value (4 mm y-1) in 1982-1995 to a high value (15 mm y-1) in 2003-2013, indicating the sensitivity of groundwater recharge to a decadal-scale variability of meteorological conditions.

Glaciers and ice caps outside Greenland

USGS Publications Warehouse

Sharp, Marin; Wolken, G.; Burgess, D.; Cogley, J.G.; Copland, L.; Thomson, L.; Arendt, A.; Wouters, B.; Kohler, J.; Andreassen, L.M.; O'Neel, Shad; Pelto, M.

2015-01-01

Mountain glaciers and ice caps cover an area of over 400 000 km2 in the Arctic, and are a major influence on global sea level (Gardner et al. 2011, 2013; Jacob et al. 2012). They gain mass by snow accumulation and lose mass by meltwater runoff. Where they terminate in water (ocean or lake), they also lose mass by iceberg calving. The climatic mass balance (Bclim, the difference between annual snow accumulation and annual meltwater runoff) is a widely used index of how glaciers respond to climate variability and change. The total mass balance (ΔM) is defined as the difference between annual snow accumulation and annual mass losses (by iceberg calving plus runoff).

Temporal and spatial variability of groundwater recharge on Jeju Island, Korea

USGS Publications Warehouse

Mair, Alan; Hagedorn, Benjamin; Tillery, Suzanne; El-Kadi, Aly I.; Westenbroek, Stephen M.; Ha, Kyoochul; Koh, Gi-Won

2013-01-01

Estimates of groundwater recharge spatial and temporal variability are essential inputs to groundwater flow models that are used to test groundwater availability under different management and climate conditions. In this study, a soil water balance analysis was conducted to estimate groundwater recharge on the island of Jeju, Korea, for baseline, drought, and climate-land use change scenarios. The Soil Water Balance (SWB) computer code was used to compute groundwater recharge and other water balance components at a daily time step using a 100 m grid cell size for an 18-year baseline scenario (1992–2009). A 10-year drought scenario was selected from historical precipitation trends (1961–2009), while the climate-land use change scenario was developed using late 21st century climate projections and a change in urban land use. Mean annual recharge under the baseline, drought, and climate-land use scenarios was estimated at 884, 591, and 788 mm, respectively. Under the baseline scenario, mean annual recharge was within the range of previous estimates (825–959 mm) and only slightly lower than the mean of 902 mm. As a fraction of mean annual rainfall, mean annual recharge was computed as only 42% and less than previous estimates of 44–48%. The maximum historical reported annual pumping rate of 241 × 106 m3 equates to 15% of baseline recharge, which is within the range of 14–16% computed from earlier studies. The model does not include a mechanism to account for additional sources of groundwater recharge, such as fog drip, irrigation, and artificial recharge, and may also overestimate evapotranspiration losses. Consequently, the results presented in this study represent a conservative estimate of total recharge.

Landscape structure and climate influences on hydrologic response

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Predicting tree biomass growth in the temperate-boreal ecotone: is tree size, age, competition or climate response most important?

USGS Publications Warehouse

Foster, Jane R.; Finley, Andrew O.; D'Amato, Anthony W.; Bradford, John B.; Banerjee, Sudipto

2016-01-01

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2and thereby slow rising CO2 concentrations. Forests’ ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals’ size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species likeAcer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92–95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone.

Predicting tree biomass growth in the temperate-boreal ecotone: Is tree size, age, competition, or climate response most important?

PubMed

Foster, Jane R; Finley, Andrew O; D'Amato, Anthony W; Bradford, John B; Banerjee, Sudipto

2016-06-01

As global temperatures rise, variation in annual climate is also changing, with unknown consequences for forest biomes. Growing forests have the ability to capture atmospheric CO2 and thereby slow rising CO2 concentrations. Forests' ongoing ability to sequester C depends on how tree communities respond to changes in climate variation. Much of what we know about tree and forest response to climate variation comes from tree-ring records. Yet typical tree-ring datasets and models do not capture the diversity of climate responses that exist within and among trees and species. We address this issue using a model that estimates individual tree response to climate variables while accounting for variation in individuals' size, age, competitive status, and spatially structured latent covariates. Our model allows for inference about variance within and among species. We quantify how variables influence aboveground biomass growth of individual trees from a representative sample of 15 northern or southern tree species growing in a transition zone between boreal and temperate biomes. Individual trees varied in their growth response to fluctuating mean annual temperature and summer moisture stress. The variation among individuals within a species was wider than mean differences among species. The effects of mean temperature and summer moisture stress interacted, such that warm years produced positive responses to summer moisture availability and cool years produced negative responses. As climate models project significant increases in annual temperatures, growth of species like Acer saccharum, Quercus rubra, and Picea glauca will vary more in response to summer moisture stress than in the past. The magnitude of biomass growth variation in response to annual climate was 92-95% smaller than responses to tree size and age. This means that measuring or predicting the physical structure of current and future forests could tell us more about future C dynamics than growth responses related to climate change alone. © 2015 John Wiley & Sons Ltd.

Ocean angular momentum signals in a climate model and implications for Earth rotation

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Rajamony, J.; Gregory, J. M.

2002-03-01

Estimates of ocean angular momentum (OAM) provide an integrated measure of variability in ocean circulation and mass fields and can be directly related to observed changes in Earth rotation. We use output from a climate model to calculate 240 years of 3-monthly OAM values (two equatorial terms L1 and L2, related to polar motion or wobble, and axial term L3, related to length of day variations) representing the period 1860-2100. Control and forced runs permit the study of the effects of natural and anthropogenically forced climate variability on OAM. All OAM components exhibit a clear annual cycle, with large decadal modulations in amplitude, and also longer period fluctuations, all associated with natural climate variability in the model. Anthropogenically induced signals, inferred from the differences between forced and control runs, include an upward trend in L3, related to inhomogeneous ocean warming and increases in the transport of the Antarctic Circumpolar Current, and a significantly weaker seasonal cycle in L2 in the second half of the record, related primarily to changes in seasonal bottom pressure variability in the Southern Ocean and North Pacific. Variability in mass fields is in general more important to OAM signals than changes in circulation at the seasonal and longer periods analyzed. Relation of OAM signals to changes in surface atmospheric forcing are discussed. The important role of the oceans as an excitation source for the annual, Chandler and Markowitz wobbles, is confirmed. Natural climate variability in OAM and related excitation is likely to measurably affect the Earth rotation, but anthropogenically induced effects are comparatively weak.

Using climate model simulations to assess the current climate risk to maize production

NASA Astrophysics Data System (ADS)

Kent, Chris; Pope, Edward; Thompson, Vikki; Lewis, Kirsty; Scaife, Adam A.; Dunstone, Nick

2017-05-01

The relationship between the climate and agricultural production is of considerable importance to global food security. However, there has been relatively little exploration of climate-variability related yield shocks. The short observational yield record does not adequately sample natural inter-annual variability thereby limiting the accuracy of probability assessments. Focusing on the United States and China, we present an innovative use of initialised ensemble climate simulations and a new agro-climatic indicator, to calculate the risk of severe water stress. Combined, these regions provide 60% of the world’s maize, and therefore, are crucial to global food security. To probe a greater range of inter-annual variability, the indicator is applied to 1400 simulations of the present day climate. The probability of severe water stress in the major maize producing regions is quantified, and in many regions an increased risk is found compared to calculations from observed historical data. Analysis suggests that the present day climate is also capable of producing unprecedented severe water stress conditions. Therefore, adaptation plans and policies based solely on observed events from the recent past may considerably under-estimate the true risk of climate-related maize shocks. The probability of a major impact event occurring simultaneously across both regions—a multi-breadbasket failure—is estimated to be up to 6% per decade and arises from a physically plausible climate state. This novel approach highlights the significance of climate impacts on crop production shocks and provides a platform for considerably improving food security assessments, in the present day or under a changing climate, as well as development of new risk based climate services.

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

Future hotspots of increasing temperature variability in tropical countries

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Temperature and rainfall strongly drive temporal growth variation in Asian tropical forest trees.

PubMed

Vlam, Mart; Baker, Patrick J; Bunyavejchewin, Sarayudh; Zuidema, Pieter A

2014-04-01

Climate change effects on growth rates of tropical trees may lead to alterations in carbon cycling of carbon-rich tropical forests. However, climate sensitivity of broad-leaved lowland tropical trees is poorly understood. Dendrochronology (tree-ring analysis) provides a powerful tool to study the relationship between tropical tree growth and annual climate variability. We aimed to establish climate-growth relationships for five annual-ring forming tree species, using ring-width data from 459 canopy and understory trees from a seasonal tropical forest in western Thailand. Based on 183/459 trees, chronologies with total lengths between 29 and 62 years were produced for four out of five species. Bootstrapped correlation analysis revealed that climate-growth responses were similar among these four species. Growth was significantly negatively correlated with current-year maximum and minimum temperatures, and positively correlated with dry-season precipitation levels. Negative correlations between growth and temperature may be attributed to a positive relationship between temperature and autotrophic respiration rates. The positive relationship between growth and dry-season precipitation levels likely reflects the strong water demand during leaf flush. Mixed-effect models yielded results that were consistent across species: a negative effect of current wet-season maximum temperatures on growth, but also additive positive effects of, for example, prior dry-season maximum temperatures. Our analyses showed that annual growth variability in tropical trees is determined by a combination of both temperature and precipitation variability. With rising temperature, the predominantly negative relationship between temperature and growth may imply decreasing growth rates of tropical trees as a result of global warming.

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

USGS Publications Warehouse

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

2011-01-01

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

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

NASA Astrophysics Data System (ADS)

Chiriboga, A.

2007-12-01

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

Weather and climate applications for rangeland restoration planning

USDA-ARS?s Scientific Manuscript database

Rangeland ecosystems generally have an arid or semi-arid climatology, and are characterized by relatively high variability in seasonal and annual patterns of precipitation. Weather variability during seedling establishment is universally acknowledged as a principal determinant of rangeland seeding...

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Declining annual streamflow distributions in the Pacific Northwest United States, 1948-2006

Treesearch

C. H. Luce; Z. A. Holden

2009-01-01

Much of the discussion on climate change and water in the western United States centers on decreased snowpack and earlier spring runoff. Although increasing variability in annual flows has been noted, the nature of those changes is largely unexplored. We tested for trends in the distribution of annual runoff using quantile regression at 43 gages in the Pacific...

Improving Streamflow Forecasts Using Predefined Sea Surface Temperature

NASA Astrophysics Data System (ADS)

Kalra, A.; Ahmad, S.

2011-12-01

With the increasing evidence of climate variability, water resources managers in the western United States are faced with greater challenges of developing long range streamflow forecast. This is further aggravated by the increases in climate extremes such as floods and drought caused by climate variability. Over the years, climatologists have identified several modes of climatic variability and their relationship with streamflow. These climate modes have the potential of being used as predictor in models for improving the streamflow lead time. With this as the motivation, the current research focuses on increasing the streamflow lead time using predefine climate indices. A data driven model i.e. Support Vector Machine (SVM) based on the statistical learning theory is used to predict annual streamflow volume 3-year in advance. The SVM model is a learning system that uses a hypothesis space of linear functions in a Kernel induced higher dimensional feature space, and is trained with a learning algorithm from the optimization theory. Annual oceanic-atmospheric indices, comprising of Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), El Niño-Southern Oscillations (ENSO), and a new Sea Surface Temperature (SST) data set of "Hondo" Region for a period of 1906-2005 are used to generate annual streamflow volumes. The SVM model is applied to three gages i.e. Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Based on the performance measures the model shows very good forecasts, and the forecast are in good agreement with measured streamflow volumes. Previous research has identified NAO and ENSO as main drivers for extending streamflow forecast lead-time in the UCRB. Inclusion of "Hondo Region" SST information further improve the model's forecasting ability. The overall results of this study revealed that the annual streamflow of the UCRB is significantly influenced by predefine climate modes and the proposed SVM modeling technique incorporating oceanic-atmospheric oscillations is expected to be useful to water managers in the long-term management of the water resources within the UCRB.

Wind extremes in the North Sea basin under climate change: an ensemble study of 12 CMIP5 GCMs

NASA Astrophysics Data System (ADS)

de Winter, R.; Ruessink, G.; Sterl, A.

2012-12-01

Coastal safety may be influenced by climate change, as changes in extreme surge levels and wave extremes may increase the vulnerability of dunes and other coastal defenses. In the North Sea, an area already prone to severe flooding, these high surge levels and waves are generated by severe wind speeds during storm events. As a result of the geometry of the North Sea, not only the maximum wind speed is relevant, but also wind direction. Analyzing changes in a changing climate implies that several uncertainties need to be taken into account. First, there is the uncertainty in climate experiments, which represents the possible development of the emission of greenhouse gases. Second, there is uncertainty between the climate models that are used to analyze the effect of different climate experiments. The third uncertainty is the natural variability of the climate. When this system variability is large, small trends will be difficult to detect. The natural variability results in statistical uncertainty, especially for events with high return values. We addressed the first two types of uncertainties for extreme wind conditions in the North Sea using 12 CMIP5 GCMs. To evaluate the differences between the climate experiments, two climate experiments (rcp4.5 and rcp8.5) from 2050-2100 are compared with historical runs, running from 1950-2000. Rcp4.5 is considered to be a middle climate experiment and rcp8.5 represents high-end climate scenarios. The projections of the 12 GCMs for a given scenario illustrate model uncertainty. We focus on the North Sea basin, because changes in wind conditions could have a large impact on safety of the densely populated North Sea coast, an area that has already a high exposure to flooding. Our results show that, consistent with ERA-Interim results, the annual maximum wind speed in the historical run demonstrates large interannual variability. For the North Sea, the annual maximum wind speed is not projected to change in either rcp4.5 or rcp8.5. In fact, the differences in the 12 GCMs are larger than the difference between the three experiments. Furthermore, our results show that, the variation in direction of annual maximum wind speed is large and this precludes a firm statement on climate-change induced changes in these directions. Nonetheless, most models indicate a decrease in annual maximum wind speed from south-eastern directions and an increase from south-western and western directions. This might be caused by a poleward shift of the storm track. The amount of wind from north-west and north-north-west, wind directions that are responsible for the development of extreme storm surges in the southern part of the North Sea, are not projected to change. However, North Sea coasts that have the longest fetch for western direction, e.g. the German Bight, may encounter more often high storm surge levels and extreme waves when the annual maximum wind will indeed be more often from western direction.

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Climate and Wildfire in Mountains of the Western United States

NASA Astrophysics Data System (ADS)

Alfaro, E.; Westerling, A. L.; Cayan, D. R.

2004-12-01

Since the mid-1980s, there has been a dramatic increase in the area burned in wildfires in mountain forests of the western United States, with mean annual area burned nearly three and a half times higher compared to the preceding one and a half decades.(1) Concomitant increases in variability in annual area burned and in fire suppression costs pose a serious challenge for land management in the mountainous West. The variance in annual area burned since 1987 is nineteen times its previous level. Since managers must be prepared for the worst possible scenarios in every fire season, increased uncertainty about the scale of the western fire season each year imposes high costs on public agencies. Annual real suppression costs in western forests have more than doubled for the Forest Service since 1987, while the variance in annual suppression costs is over four times higher. Although federal agencies' fire suppression budgets have increased recently, they are still close to what would be spent in an "average" year that seldom occurs, while costs tend to fluctuate between low and high extremes. Modeling area burned and suppression costs as a function of climate variability alone, Westerling (2004, unpublished work) found that the probability of the Forest Service's suppression expenses exceeding the current annual suppression budget has exceeded 50% since 1987, a substantial increase from the one-in-three chance over the preceding 40 years. Recent progress in our understanding of the links between climate and wildfire, and in our ability to forecast some aspects of both climate and wildfire season severity a season or more in advance, offers some hope that these costs might be ameliorated through the integration of climate information into fire and fuels management. In addition to the effects of climate variability on wildfire, long-term biomass accumulations in some western ecosystems have fueled an increasing incidence of large, stand-replacing wildfires where such fires were previously rare. These severe large fires can result in erosion and changes in vegetation type, with consequences for water quality, stream flow, future biological productivity of the affected areas, and habitat loss for endangered species. Apart from their deleterious ecological consequences, severe fires can also dramatically affect amenity values for public lands and for homeowners living in the wildland-urban interface. In the National Fire Plan, land management agencies have committed to reducing fuels on millions of hectares of public lands. The primary means are mechanical removal, prescribed fire and wildland fire use. The Forest Service estimates they will need to spend hundreds of millions of dollars per year to meet their fuel reduction targets, while efforts in recent years have not kept up with the current rate of biomass increase. Use of climate information for targeting resources and scheduling prescribed burns could increase the efficiency of these efforts. In this study we review the fire history since 1970 for western mountain forests, and demonstrate apparent links between regional climate variability and decadal-scale changes in annual area burned. This analysis explores how wildfire size and frequency have varied over the past thirty-five years by elevation and latitude, and how climate indices such as precipitation, temperature, drought indices and the timing of spring runoff vary in importance for fire season severity by elevation in forests around the western United States.

Evaluating climate change impacts on streamflow variability based on a multisite multivariate GCM downscaling method in the Jing River of China

NASA Astrophysics Data System (ADS)

Li, Zhi; Jin, Jiming

2017-11-01

Projected hydrological variability is important for future resource and hazard management of water supplies because changes in hydrological variability can cause more disasters than changes in the mean state. However, climate change scenarios downscaled from Earth System Models (ESMs) at single sites cannot meet the requirements of distributed hydrologic models for simulating hydrological variability. This study developed multisite multivariate climate change scenarios via three steps: (i) spatial downscaling of ESMs using a transfer function method, (ii) temporal downscaling of ESMs using a single-site weather generator, and (iii) reconstruction of spatiotemporal correlations using a distribution-free shuffle procedure. Multisite precipitation and temperature change scenarios for 2011-2040 were generated from five ESMs under four representative concentration pathways to project changes in streamflow variability using the Soil and Water Assessment Tool (SWAT) for the Jing River, China. The correlation reconstruction method performed realistically for intersite and intervariable correlation reproduction and hydrological modeling. The SWAT model was found to be well calibrated with monthly streamflow with a model efficiency coefficient of 0.78. It was projected that the annual mean precipitation would not change, while the mean maximum and minimum temperatures would increase significantly by 1.6 ± 0.3 and 1.3 ± 0.2 °C; the variance ratios of 2011-2040 to 1961-2005 were 1.15 ± 0.13 for precipitation, 1.15 ± 0.14 for mean maximum temperature, and 1.04 ± 0.10 for mean minimum temperature. A warmer climate was predicted for the flood season, while the dry season was projected to become wetter and warmer; the findings indicated that the intra-annual and interannual variations in the future climate would be greater than in the current climate. The total annual streamflow was found to change insignificantly but its variance ratios of 2011-2040 to 1961-2005 increased by 1.25 ± 0.55. Streamflow variability was predicted to become greater over most months on the seasonal scale because of the increased monthly maximum streamflow and decreased monthly minimum streamflow. The increase in streamflow variability was attributed mainly to larger positive contributions from increased precipitation variances rather than negative contributions from increased mean temperatures.

Hydrological Excitations of Polar Motion Derived from Different Variables of Fgoals - g2 Climate Model

NASA Astrophysics Data System (ADS)

Winska, M.

2016-12-01

The hydrological contribution to decadal, inter-annual and multi-annual suppress polar motion derived from climate model as well as from GRACE (Gravity Recovery and Climate Experiment) data is discussed here for the period 2002.3-2016.0. The data set used here are Earth Orientation Parameters Combined 04 (EOP C04), Flexible Global Ocean-Atmosphere-Land System Model: Grid-point Version 2 (FGOAL-g2) and Global Land Data Assimilation System (GLDAS) climate models and GRACE CSR RL05 data for polar motion, hydrological and gravimetric excitation, respectively. Several Hydrological Angular Momentum (HAM) functions are calculated here from the selected variables: precipitation, evaporation, runoff, soil moisture, accumulated snow of the FGOALS and GLDAS climate models as well as from the global mass change fields from GRACE data provided by the International Earth Rotation and Reference System Service (IERS) Global Geophysical Fluids Center (GGFC). The contribution of different HAM excitation functions to achieve the full agreement between geodetic observations and geophysical excitation functions of polar motion is studied here.

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

NASA Astrophysics Data System (ADS)

Keyser, Alisa; Westerling, Anthony LeRoy

2017-05-01

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

Long term variability of the annual hydrological regime and sensitivity to temperature phase shifts in Saxony/Germany

NASA Astrophysics Data System (ADS)

Renner, M.; Bernhofer, C.

2011-01-01

The timing of the seasons strongly effects ecosystems and human activities. Recently, there is increasing evidence of changes in the timing of the seasons, such as earlier spring seasons detected in phenological records, advanced seasonal timing of surface temperature, earlier snow melt or streamflow timing. For water resources management there is a need to quantitatively describe the variability in the timing of hydrological regimes and to understand how climatic changes control the seasonal water budget of river basins on the regional scale. In this study, changes of the annual cycle of hydrological variables are analysed for 27 river basins in Saxony/Germany. Thereby monthly series of basin runoff ratios, the ratio of runoff and basin precipitation are investigated for changes and variability of their annual periodicity over the period 1930-2009. Approximating the annual cycle by the means of harmonic functions gave acceptable results, while only two parameters, phase and amplitude, are required. It has been found that the annual phase of runoff ratio, representing the timing of the hydrological regime, is subject to considerable year-to-year variability, being concurrent with basins in similar hydro-climatic conditions. Two distinct basin classes have been identified, whereby basin elevation has been found to be the delimiting factor. An increasing importance of snow on the basin water balance with elevation is apparent and mainly governs the temporal variability of the annual timing of hydrological regimes. Further there is evidence of coincident changes in trend direction (change points in 1971 and 1988) in snow melt influenced basins. In these basins the timing of the runoff ratio is significantly correlated with the timing of temperature, and effects on runoff by temperature phase changes are even amplified. Interestingly, temperature effects may explain the low frequent variability of the second change point until today. However, the first change point can not be explained by temperature alone and other causes have to be considered.

Reconstructing Past Seasonal to Multicentennial-Scale Variability in the NE Atlantic Ocean Using the Long-Lived Marine Bivalve Mollusk Glycymeris glycymeris

NASA Astrophysics Data System (ADS)

Reynolds, D. J.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Halloran, P. R.; Sayer, M. D. J.

2017-11-01

The lack of long-term, highly resolved (annual to subannual) and absolutely dated baseline records of marine variability extending beyond the instrumental period (last 50-100 years) hinders our ability to develop a comprehensive understanding of the role the ocean plays in the climate system. Specifically, without such records, it remains difficult to fully quantify the range of natural climate variability mediated by the ocean and to robustly attribute recent changes to anthropogenic or natural drivers. Here we present a 211 year (1799-2010 C.E.; all dates hereafter are Common Era) seawater temperature (SWT) reconstruction from the northeast Atlantic Ocean derived from absolutely dated, annually resolved, oxygen isotope ratios recorded in the shell carbonate (δ18Oshell) of the long-lived marine bivalve mollusk Glycymeris glycymeris. The annual record was calibrated using subannually resolved δ18Oshell values drilled from multiple shells covering the instrumental period. Calibration verification statistics and spatial correlation analyses indicate that the δ18Oshell record contains significant skill at reconstructing Northeast Atlantic Ocean mean summer SWT variability associated with changes in subpolar gyre dynamics and the North Atlantic Current. Reconciling differences between the δ18Oshell data and corresponding growth increment width chronology demonstrates that 68% of the variability in G. glycymeris shell growth can be explained by the combined influence of biological productivity and SWT variability. These data suggest that G. glycymeris can provide seasonal to multicentennial absolutely dated baseline records of past marine variability that will lead to the development of a quantitative understanding of the role the marine environment plays in the global climate system.

Effects of increased wind power generation on Mid-Norway's energy balance under climate change: A market based approach

NASA Astrophysics Data System (ADS)

Francois, Baptiste; Martino, Sara; Tofte, Lena; Hingray, Benoit; Mo, Birger; Creutin, Jean-Dominique

2017-04-01

Thanks to its huge water storage capacity, Norway has an excess of energy generation at annual scale, although significant regional disparity exists. On average, the Mid-Norway region has an energy deficit and needs to import more electricity than it exports. We show that this energy deficit can be reduced with an increase in wind generation and transmission line capacity, even in future climate scenarios where both mean annual temperature and precipitation are changed. For the considered scenarios, the deficit observed in winter disappears, i.e. when electricity consumption and prices are high. At the annual scale, the deficit behavior depends more on future changes in precipitation. Another consequence of changes in wind production and transmission capacity is the modification of electricity exchanges with neighboring regions which are also modified both in terms of average, variability and seasonality. Keywords: Variable renewable energy, Wind, Hydro, Energy balance, Energy market

Climatic Zones, Soil Moisture Seasonality and Biomass Burning and Their Influence On Ozone Precursor Concentrations Over West Africa as Retrieved from Satellites

NASA Astrophysics Data System (ADS)

Onojeghuo, A. R.; Balzter, H.; Monks, P. S.

2015-12-01

West Africa is a region with six different climatic zones including a rich savannah affected by biomass burning annually, the Niger delta oil producing region with major gas flaring sites and a long coastline. Research on atmospheric pollution using remotely sensed data over West Africa has mostly been conducted at regional scale or for individual countries, with little emphasis on the dynamics of climatic zones and the diversity of land cover types. This study analyses annual seasonal dynamics of emissions of two ozone precursors stratified by climatic zone: nitrogen dioxide (NO2) from OMI and carbon monoxide (CO) from TES. The different sources of these pollutants and their seasonality are explicitly considered. Results indicate that the highest annual wet season NO2 column concentrations were in the semi-arid zone (1.33 x 1015 molecules cm-2) after prolonged periods of low soil moisture while the highest dry season were observed in the wet sub-humid zone (2.62 x 1015 molecules cm-2) where the savannah fires occur annually. The highest annual CO concentrations (> 3.1 x 1018 molecules cm-2) were from the Niger Delta, located in the humid zone. There were indications of atmospheric transport of CO from the southern hemisphere in the west season. Climate change induced soil moisture variability was most prominent in the dry sub-humid and semi-arid climatic zones (±0.015m3m-3) . The causal effects of soil moisture variability on NO2 emissions and their seasonal cycles were tested using the Granger causality test. Causal effects of inter-zonal exchanges/transport of NO2 and CO emissions respectively were inferred using Directed Acyclic Graphs. The results indicate that NO2, CO and their seasonal ratios are strongly affected by changes in soil moisture.

Monthly paleostreamflow reconstruction from annual tree-ring chronologies

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Rosenberg, D. E.; DeRose, R. J.; Rittenour, T. M.

2018-02-01

Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate-change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a multiple linear regression model for monthly streamflow reconstruction is presented that expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. This approach is used to reconstruct 600 years of monthly streamflows at two sites on the Bear and Logan rivers in northern Utah. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson's correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly flows during the reference period (10/1942 to 9/2015). Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions, rather than using resampling of the observed record. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a larger range of natural variability in drought and pluvial events and better evaluate extreme events with recurrence intervals longer than the observed record. Establishing this natural baseline is critical when estimating future hydrologic risks under conditions of a non-stationary climate.

Hydrological changes impacts on annual runoff distribution in seasonally dry basins

NASA Astrophysics Data System (ADS)

Viola, F.; Caracciolo, D.; Feng, X.

2017-12-01

Runoff is expected to be modified in the next future by climate change as well as by land use change. Given its importance for water supply and ecosystem functioning, it is therefore imperative to develop adaptation strategies and new policies for regional water resources management and planning. To do so, the identification and attribution of natural flow regime shifts as a result of climate and land use changes are of crucial importance. In this context, the Budyko's curve has begun to be widely adopted to separate the contributions of climate and land use changes to the variation of runoff over long-term periods by using the multi-year averages of hydrological variables. In this study, a framework based on Fu's equation is proposed and applied to separate the impacts of climate and land use changes on the future annual runoff distribution in seasonally dry basins, such as those in Mediterranean climates. In particular, this framework improves a recently developed method to obtain annual runoff probability density function (pdf) in seasonally dry basins from annual rainfall and potential evapotranspiration statistics, and from knowledge of the Fu's equation parameter ω. The effect of climate change has been taken into account through the variation of the first order statistics of annual rainfall and potential evapotranspiration, consistent with general circulation models' outputs, while the Fu's equation parameter ω has been changed to represent land use change. The effects of the two factors of change (i.e., climate and land use) on the annual runoff pdf have been first independently and then jointly analyzed, by reconstructing the annual runoff pdfs for the current period and, based on likely scenarios, within the next 100 years. The results show that, for large basins, climate change is the dominant driver of the decline in annual runoff, while land use change is a secondary but important factor.

Responses of runoff to historical and future climate variability over China

NASA Astrophysics Data System (ADS)

Wu, Chuanhao; Hu, Bill X.; Huang, Guoru; Wang, Peng; Xu, Kai

2018-03-01

China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960-2008) water budget data and climate projections from 28 global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.1 to 3.2) and potential evaporation (PET) elasticity (from -2.2 to -0.1) across China. The P elasticity is larger in north-eastern and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties' elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960-2008, the climate contribution to R ranges from -2.4 to 3.6 % yr-1 across China, with the negative contribution in north-eastern China and the positive contribution in western China and some parts of the south-west. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071-2100, the mean annual P is projected to increase in most parts of China, especially the western regions, while the mean annual PET is projected to increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China are projected to become wetter and drier in the period 2071-2100, respectively (relative to the baseline 1971-2000).

A century of hydrological variability and trends in the Fraser River Basin

NASA Astrophysics Data System (ADS)

Déry, Stephen J.; Hernández-Henríquez, Marco A.; Owens, Philip N.; Parkes, Margot W.; Petticrew, Ellen L.

2012-06-01

This study examines the 1911-2010 variability and trends in annual streamflow at 139 sites across the Fraser River Basin (FRB) of British Columbia (BC), Canada. The Fraser River is the largest Canadian waterway flowing to the Pacific Ocean and is one of the world’s greatest salmon rivers. Our analyses reveal high runoff rates and low interannual variability in alpine and coastal rivers, and low runoff rates and high interannual variability in most streams in BC’s interior. The interannual variability in streamflow is also low in rivers such as the Adams, Chilko, Quesnel and Stuart where the principal salmon runs of the Fraser River occur. A trend analysis shows a spatially coherent signal with increasing interannual variability in streamflow across the FRB in recent decades, most notably in spring and summer. The upward trend in the coefficient of variation in annual runoff coincides with a period of near-normal annual runoff for the Fraser River at Hope. The interannual variability in streamflow is greater in regulated rather than natural systems; however, it is unclear whether it is predominantly flow regulation that leads to these observed differences. Environmental changes such as rising air temperatures, more frequent polarity changes in large-scale climate teleconnections such as El Niño-Southern Oscillation and Pacific Decadal Oscillation, and retreating glaciers may be contributing to the greater range in annual runoff fluctuations across the FRB. This has implications for ecological processes throughout the basin, for example affecting migrating and spawning salmon, a keystone species vital to First Nations communities as well as to commercial and recreational fisheries. To exemplify this linkage between variable flows and biological responses, the unusual FRB runoff anomalies observed in 2010 are discussed in the context of that year’s sockeye salmon run. As the climate continues to warm, greater variability in annual streamflow, and hence in hydrological extremes, may influence ecological processes and human usage throughout the FRB in the 21st century.

Climatic variability in sclerochronological records from the northern North Sea

NASA Astrophysics Data System (ADS)

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

2016-12-01

Highly resolved palaeoreconstructions that can extend instrumental records back through time is a fundament for our understanding of a climate of the last millennia. Only a few established extratropical marine paleo archives enable the reconstruction of key ocean processes at annual to sub-annual time scales. Bivalves have been shown to provide a useful archive with high temporal resolution. The species Arctica islandica is unique proxy due to its exceptional longevity combined with sensitivity to changes in environmental conditions. In this study, we investigate the impact of climate variability on sclerochronological records of A. islandica from the Viking Bank in the northern North Sea. The hydrographical characteristics of this location are mainly controlled by the major inflow of Atlantic water in the North Sea and can potentially be reflected in the shell composition and growth of A. islandica. To reconstruct environment conditions, we use shells of living and subfossil specimens of A. islandica collected by dredging at depths around 100 meters. The annual growth bands within the shells were determined and growth increments widths were measured. By cross-matching 30 individual increment-width time series, we built an absolutely dated 265-year long shell-growth chronology spanning the time interval 1748-2013 AD. The relatively high Rbar (>0.5) and EPS (>0.85) values indicate a common environmental forcing on the shell growth within the population. The growth chronology preserves a 20-30 yr variability prior to 1900 which fades out towards the present. That change suggests a possible regime shift at the beginning of a 20th century. Ongoing work mainly focuses on comparing the shell-growth chronology with existing observational time series of climatic parameters to determine controlling factors and test the use of growth chronologies for climate reconstruction in this area. For reconstructing seasonality, we analyse the stable oxygen isotope composition of the shell carbonate. Preliminary results of temperature reconstruction are in agreement with observations and show a seasonal variability with an amplitude of less than 4oC. Future work includes the development of an annually resolved oxygen isotope record and subsequent temperature reconstruction.

Reconstructing Tropical Southwest Pacific Climate Variability and Mean State Changes at Vanuatu during the Medieval Climate Anomaly using Geochemical Proxies from Corals

NASA Astrophysics Data System (ADS)

Lawman, A. E.; Quinn, T. M.; Partin, J. W.; Taylor, F. W.; Thirumalai, K.; WU, C. C.; Shen, C. C.

2017-12-01

The Medieval Climate Anomaly (MCA: 950-1250 CE) is identified as a period during the last 2 millennia with Northern Hemisphere surface temperatures similar to the present. However, our understanding of tropical climate variability during the MCA is poorly constrained due to a lack of sub-annually resolved proxy records. We investigate seasonal and interannual variability during the MCA using geochemical records developed from two well preserved Porites lutea fossilized corals from the tropical southwest Pacific (Tasmaloum, Vanuatu; 15.6°S, 166.9°E). Absolute U/Th dates of 1127.1 ± 2.7 CE and 1105.1 ± 3.0 CE indicate that the selected fossil corals lived during the MCA. We use paired coral Sr/Ca and δ18O measurements to reconstruct sea surface temperature (SST) and the δ18O of seawater (a proxy for salinity). To provide context for the fossil coral records and test whether the mean state and climate variability at Vanuatu during the MCA is similar to the modern climate, our analysis also incorporates two modern coral records from Sabine Bank (15.9°S, 166.0°E) and Malo Channel (15.7°S, 167.2°E), Vanuatu for comparison. We quantify the uncertainty in our modern and fossil coral SST estimates via replication with multiple, overlapping coral records. Both the modern and fossil corals reproduce their respective mean SST value over their common period of overlap, which is 25 years in both cases. Based on over 100 years of monthly Sr/Ca data from each time period, we find that SSTs at Vanuatu during the MCA are 1.3 ± 0.7°C cooler relative to the modern. We also find that the median amplitude of the annual cycle is 0.8 ± 0.3°C larger during the MCA relative to the modern. Multiple data analysis techniques, including the standard deviation and the difference between the 95th and 5th percentiles of the annual SST cycle estimates, also show that the MCA has greater annual SST variability relative to the modern. Stable isotope data acquisition is ongoing, and when complete we will have a suite of records of paired coral Sr/Ca and δ18O measurements. We will apply similar statistical techniques developed for the Sr/Ca-SST record to also investigate variability in the δ18O of seawater (salinity). Modern salinity variability at Vanuatu arises due to hydrological anomalies associated with the El Niño-Southern Oscillation in the tropical Pacific.

Tradeoffs between water requirements and yield stability in annual vs. perennial crops

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel A.

2018-02-01

Population growth and changes in climate and diets will likely further increase the pressure on agriculture and water resources globally. Currently, staple crops are obtained from annuals plants. A shift towards perennial crops may enhance many ecosystem services, but at the cost of higher water requirements and lower yields. It is still unclear when the advantages of perennial crops overcome their disadvantages and perennial crops are thus a sustainable solution. Here we combine a probabilistic description of the soil water balance and crop development with an extensive dataset of traits of congeneric annuals and perennials to identify the conditions for which perennial crops are more viable than annual ones with reference to yield, yield stability, and effective use of water. We show that the larger and more developed roots of perennial crops allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species, but their yields remain lower when considering grain crops. Furthermore, perennial crops have higher and more variable irrigation requirements and lower water productivity. These results are important to understand the potential consequences for yield, its stability, and water resource use of a shift from annual to perennial crops and, more generally, if perennial crops may be more resilient than annual crops in the face of climatic fluctuations.

Projected Changes in Mean and Interannual Variability of Surface Water over Continental China

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

Leng, Guoyong; Tang, Qiuhong; Huang, Maoyi

Five General Circulation Model (GCM) climate projections under the RCP8.5 emission scenario were used to drive the Variable Infiltration Capacity (VIC) hydrologic model to investigate the impacts of climate change on hydrologic cycle over continental China in the 21st century. The bias-corrected climatic variables were generated for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5) by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). Results showed much larger fractional changes of annual mean Evaportranspiration (ET) per unit warming than the corresponding fractional changes of Precipitation (P) per unit warming across the country especially for South China,more » which led to notable decrease of surface water variability (P-E). Specifically, negative trends for annual mean runoff up to -0.33%/decade and soil moisture trends varying between -0.02 to -0.13%/decade were found for most river basins across China. Coincidentally, interannual variability for both runoff and soil moisture exhibited significant positive trends for almost all river basins across China, implying an increase in extremes relative to the mean conditions. Noticeably, the largest positive trends for runoff variability and soil moisture variability, which were up to 38 0.41%/decade and 0.90%/decade, both occurred in Southwest China. In addition to the regional contrast, intra-seasonal variation was also large for the runoff mean and runoff variability changes, but small for the soil moisture mean and variability changes. Our results suggest that future climate change could further exacerbate existing water-related risks (e.g. floods and droughts) across China as indicated by the marked decrease of surface water amounts combined with steady increase of interannual variability throughout the 21st century. This study highlights the regional contrast and intra-seasonal variations for the projected hydrologic changes and could provide muti-scale guidance for assessing effective adaptation strategies for the country on a river basin, regional, or as whole.« less

Macroecological patterns of sexual size dimorphism in turtles of the world

USGS Publications Warehouse

Agha, Mickey; Ennen, Joshua R.; Nowakowski, A. Justin; Lovich, Jeffrey E.; Sweat, Sarah C.; Todd, Brian D.

2018-01-01

Sexual size dimorphism (SSD) is a well-documented phenomenon in both plants and animals; however, the ecological and evolutionary mechanisms that drive and maintain SSD patterns across geographic space at regional and global scales are understudied, especially for reptiles. Our goal was to examine geographic variation of turtle SSD and to explore ecological and environmental correlates using phylogenetic comparative methods. We use published body size data on 135 species from nine turtle families to examine how geographic patterns and the evolution of SSD are influenced by habitat specialization, climate (annual mean temperature and annual precipitation) and climate variability, latitude, or a combination of these predictor variables. We found that geographic variation, magnitude and direction of turtle SSD are best explained by habitat association, annual temperature variance and annual precipitation. Use of semi-aquatic and terrestrial habitats was associated with male-biased SSD, whereas use of aquatic habitat was associated with female-biased SSD. Our results also suggest that greater temperature variability is associated with female-biased SSD. In contrast, wetter climates are associated with male-biased SSD compared with arid climates that are associated with female-biased SSD. We also show support for a global latitudinal trend in SSD, with females being larger than males towards the poles, especially in the families Emydidae and Geoemydidae. Estimates of phylogenetic signal for both SSD and habitat type indicate that closely related species occupy similar habitats and exhibit similar direction and magnitude of SSD. These global patterns of SSD may arise from sex-specific reproductive behaviour, fecundity and sex-specific responses to environmental factors that differ among habitats and vary systematically across latitude. Thus, this study adds to our current understanding that while SSD can vary dramatically across and within turtle species under phylogenetic constraints, it may be driven, maintained and exaggerated by habitat type, climate and geographic location.

In the hot seat : Insolation and ENSO controls on vegetation productivity in tropical Africa inferred from NDVI

NASA Astrophysics Data System (ADS)

Ivory, S.; Russell, J. L.; Cohen, A. S.

2010-12-01

Threats to tropical biodiversity with serious and costly implications for both ecosystems and human well-being in Africa have led the IPCC to classify this region as vulnerable to negative impacts from climate change. Yet little is known about how vegetation communities respond to altered patterns of rainfall and evaporation. Paleoclimate records within the tropics can help answer questions about how vegetation response to climate forcing changes over time. However, sparse spatial extent of records and uncertainty surrounding the climate-vegetation relationship complicate these insights. Understanding the climatic mechanisms involved in landscape change at all temporal scales creates the need for quantitative constraints of the modern relationship between climatic controls, hydrology, and vegetation. Though modern observational data can help elucidate this relationship, low resolution and complicated rainfall/vegetation associations make them less than ideal. Satellite data of vegetation productivity (NDVI) with continuous high-resolution spatial coverage provides a robust and elegant tool for identifying the link between global and regional controls and vegetation. We use regression analyses of variables either previously proposed or potentially important in regulating Afro-tropical vegetation (insolation, out-going long-wave radiation, geopotential height, Southern Oscillation Index, Indian Ocean Dipole, Indian Monsoon precipitation, sea-level pressure, surface wind, sea-surface temperature) on continuous, time-varying spatial fields of 8km NDVI for sub-Saharan Africa. These analyses show the importance of global atmospheric controls in producing regional intra-annual and inter-annual vegetation variability. Dipole patterns emerge primarily correlated with both the seasonal and inter-annual extent of the Intertropical Convergence Zone (ITCZ). Inter-annual ITCZ variability drives patterns in African vegetation resulting from the effect of insolation anomalies and ENSO events on atmospheric circulation rather than sea surface temperatures or teleconnections to mid/high latitudes. Global controls on tropical atmospheric circulation regulate vegetation throughout sub-Saharan Africa on many time scales through alteration of dry season length and moisture convergence, rather than precipitation amount.

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America

PubMed Central

Falk, Donald A.; Westerling, Anthony L.; Swetnam, Thomas W.

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread. PMID:29244839

Direct and indirect climate controls predict heterogeneous early-mid 21st century wildfire burned area across western and boreal North America.

PubMed

Kitzberger, Thomas; Falk, Donald A; Westerling, Anthony L; Swetnam, Thomas W

2017-01-01

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread.

Influence of precipitation and crop germination on resource selection by mule deer (Odocoileus hemionus) in southwest Colorado

USGS Publications Warehouse

Carrollo, Emily M.; Johnson, Heather E.; Fischer, Justin W.; Hammond, Matthew; Dorsey, Patricia D.; Anderson, Charles; Vercauteren, Kurt C.; Walter, W. David

2017-01-01

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km2, and for two summer seasons that ranged between 5.51 and 6.24 km2. Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Influence of Precipitation and Crop Germination on Resource Selection by Mule Deer (Odocoileus hemionus) in Southwest Colorado.

PubMed

Carrollo, Emily M; Johnson, Heather E; Fischer, Justin W; Hammond, Matthew; Dorsey, Patricia D; Anderson, Charles; Vercauteren, Kurt C; Walter, W David

2017-11-09

Mule deer (Odocoileus hemionus) populations in the western United States provide many benefits to local economies but can also cause considerable damage to agriculture, particularly damage to lucrative crops. Limited information exists to understand resource selection of mule deer in response to annual variation in crop rotation and climatic conditions. We tested the hypothesis that mule deer select certain crops, and in particular sunflower, based on annual climatic variability. Our objective was to use movements, estimates of home range, and resource selection analysis to identify resources selected by mule deer. We used annually-derived crop-specific datasets along with Global Positioning System collars to monitor 14 mule deer in an agricultural area near public lands in southwestern Colorado, USA. We estimated home ranges for two winter seasons that ranged between 7.68 and 9.88 km 2 , and for two summer seasons that ranged between 5.51 and 6.24 km 2 . Mule deer selected areas closer to forest and alfalfa for most periods during 2012, but selected areas closer to sunflower in a majority of periods during 2013. Considerable annual variation in climate patterns and precipitation levels appeared to influence selection by mule deer because of variability in crop rotation and success of germination of specific crops.

Annual Proxy Records from Tropical Cloud Forest Trees in the Monteverde Cloud Forest, Costa Rica

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Evans, M. N.; Wheelwright, N. T.; Schrag, D. P.

2005-12-01

The extinction of the Golden Toad (Bufo periglenes) from Costa Rica's Monteverde Cloud Forest prompted research into the causes of ecological change in the montane forests of Costa Rica. Subsequent analysis of meteorological data has suggested that warmer global surface and tropical Pacific sea surface temperatures contribute to an observed decrease in cloud cover at Monteverde. However, while recent studies may have concluded that climate change is already having an effect on cloud forest environments in Costa Rica, without the context provided by long-term climate records, it is difficult to confidently conclude that the observed ecological changes are the result of anthropogenic climate forcing, land clearance in the lowland rainforest, or natural variability in tropical climate. To address this, we develop high-resolution proxy paleoclimate records from trees without annual rings in the Monteverde Cloud Forest in Costa Rica. Calibration of an age model in these trees is a fundamental prerequisite for proxy paleoclimate reconstructions. Our approach exploits the isotopic seasonality in the δ18O of water sources (fog versus rainfall) used by trees over the course of a single year. Ocotea tenera individuals of known age and measured annual growth increments were sampled in long-term monitored plantation sites in order to test this proposed age model. High-resolution (200μm increments) stable isotope measurements on cellulose reveal distinct, coherent δ18O cycles of 6 to 10‰. The calculated growth rates derived from the isotope timeseries match those observed from basal growth increment measurements. Spatial fidelity in the age model and climate signal is examined by using multiple cores from multiple trees and multiple sites. These data support our hypothesis that annual isotope cycles in these trees can be used to provide chronological control in the absence of rings. The ability of trees to record interannual climate variability in local hydrometeorology and remote climate forcing is evaluated using the isotope signal from multiple trees, local meteorological observations, and climate field data for the well-observed 1997-1998 warm El Niño-Southern Oscillation (ENSO) event. The successful calibration of our age model is a necessary step toward the development of long, annually-resolved paleoclimate reconstructions from old trees, even without rings, which will be used to evaluate the cause of recent observed climate change at Monteverde and as proxies for tropical climate field reconstructions.

Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular

NASA Astrophysics Data System (ADS)

Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.

2015-12-01

The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had meaningful result with artificial and natural effect. It is expected to predict future forest fire risk with future climate variables as the climate changes.

DCERP Annual Technical Report III: March 2009-February 2010. Executive Summary

DTIC Science & Technology

2010-04-01

groundwater passing though marshes to the estuary. Loading estimates may vary considerably depending on inter-annual hydrologic (storm versus drought ...climatic events (i.e., hurricanes and droughts ); and integrate results with the other DCERP modules. The benefits of the Aquatic/Estuarine Module...inter-annual hydrologic (storm versus drought years) variability. ▪ Several large phytoplankton blooms in mid-estuary to upper estuary locations

Unraveling climate influences on the distribution of the parapatric newts Lissotriton vulgaris meridionalis and L. italicus.

PubMed

Iannella, Mattia; Cerasoli, Francesco; Biondi, Maurizio

2017-01-01

Climate is often considered as a key ecological factor limiting the capability of expansion of most species and the extent of suitable habitats. In this contribution, we implement Species Distribution Models (SDMs) to study two parapatric amphibians, Lissotriton vulgaris meridionalis and L. italicus , investigating if and how climate has influenced their present and past (Last Glacial Maximum and Holocene) distributions. A database of 901 GPS presence records was generated for the two newts. SDMs were built through Boosted Regression Trees and Maxent, using the Worldclim bioclimatic variables as predictors. Precipitation-linked variables and the temperature annual range strongly influence the current occurrence patterns of the two Lissotriton species analyzed. The two newts show opposite responses to the most contributing variables, such as BIO7 (temperature annual range), BIO12 (annual precipitation), BIO17 (precipitation of the driest quarter) and BIO19 (precipitation of the coldest quarter). The hypothesis of climate influencing the distributions of these species is also supported by the fact that the co-occurrences within the sympatric area fall in localities characterized by intermediate values of these predictors. Projections to the Last Glacial Maximum and Holocene scenarios provided a coherent representation of climate influences on the past distributions of the target species. Computation of pairwise variables interactions and the discriminant analysis allowed a deeper interpretation of SDMs' outputs. Further, we propose a multivariate environmental dissimilarity index (MEDI), derived through a transformation of the multivariate environmental similarity surface (MESS), to deal with extrapolation-linked uncertainties in model projections to past climate. Finally, the niche equivalency and niche similarity tests confirmed the link between SDMs outputs and actual differences in the ecological niches of the two species. The different responses of the two species to climatic factors have significantly contributed to shape their current distribution, through contractions, expansions and shifts over time, allowing to maintain two wide allopatric areas with an area of sympatry in Central Italy. Moreover, our SDMs hindcasting shows many concordances with previous phylogeographic studies carried out on the same species, thus corroborating the scenarios of potential distribution during the Last Glacial Maximum and the Holocene emerging from the models obtained.

Stationarity and Inequality from the Mississippi to the Kissimmee: Climatic Control of Temporal Patterns in Catchment Discharge and Solute Export

NASA Astrophysics Data System (ADS)

Jawitz, J. W.

2011-12-01

What are the relative contributions of climatic variability, land management, and local geomorphology in determining the temporal dynamics of streamflow and the export of solutes from watersheds to receiving water bodies? A simple analytical framework is introduced for characterizing the temporal inequality of stream discharge and solute export from catchments using Lorenz diagrams and the associated Gini coefficient. These descriptors are used to illustrate a broad range of observed flow variability with a synthesis of multi-decadal flow data from 22 rivers in Florida. The analytical framework is extended to comprehensively link variability in flows and loads to climatically-driven inputs in terms of these inequality-based metrics. Further, based on a synthesis of data from the basins of the Baltic Sea, the Mississippi River, the Kissimmee River and other tributaries to Lake Okeechobee, FL, it is shown that inter-annual variations in exported loads for geogenic constituents, and for total N and total P, are dominantly controlled by discharge. Emergence of this consistent pattern across diverse managed catchments is attributed to the anthropogenic legacy of accumulated nutrient sources generating memory, similar to ubiquitously present sources for geogenic constituents. Multi-decadal phosphorus load data from 4 of the primary tributaries to Lake Okeechobee and sodium and nitrate load data from 9 of the Hubbard Brook, NH long-term study site catchments are used to examine the relation between inequality of climatic inputs, river flows and catchment loads. The intra-annual loads to Lake Okeechobee are shown to be highly unequal, such that 90% of annual load is delivered in as little as 15% of the time. Analytic expressions are developed for measures of inequality in terms of parameters of the lognormal distribution under general conditions that include intermittency. In cases where climatic variability is high compared to that of concentrations (chemostatic conditions), such as for P in the Lake Okeechobee basin and Na in Hubbard Brook, the temporal inequality of rainfall and flow are strong surrogates for load inequality. However, in cases where variability of concentrations is high compared to that of flows (chemodynamic conditions), such as for nitrate in the Hubbard Brook catchments, load inequality is greater than rainfall or flow inequality. The measured degree of correspondence between climatic, flow, and load inequality for these data sets are shown to be well described using the general inequality framework introduced here. Important implications are that (1) variations in hydro-climatic or anthropogenic forcing can be used to robustly predict inter-annual variations in flows and loads, (2) water quality problems in receiving inland and coastal waters may persist until the accumulated storages of nutrients have been substantially depleted, and (3) remedial measures designed to intercept or capture exported flows and loads must be designed with consideration of the intra-annual inequality.

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

NASA Technical Reports Server (NTRS)

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

Accounting for downscaling and model uncertainty in fine-resolution seasonal climate projections over the Columbia River Basin

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2018-01-01

Climate change is expected to have severe impacts on natural systems as well as various socio-economic aspects of human life. This has urged scientific communities to improve the understanding of future climate and reduce the uncertainties associated with projections. In the present study, ten statistically downscaled CMIP5 GCMs at 1/16th deg. spatial resolution from two different downscaling procedures are utilized over the Columbia River Basin (CRB) to assess the changes in climate variables and characterize the associated uncertainties. Three climate variables, i.e. precipitation, maximum temperature, and minimum temperature, are studied for the historical period of 1970-2000 as well as future period of 2010-2099, simulated with representative concentration pathways of RCP4.5 and RCP8.5. Bayesian Model Averaging (BMA) is employed to reduce the model uncertainty and develop a probabilistic projection for each variable in each scenario. Historical comparison of long-term attributes of GCMs and observation suggests a more accurate representation for BMA than individual models. Furthermore, BMA projections are used to investigate future seasonal to annual changes of climate variables. Projections indicate significant increase in annual precipitation and temperature, with varied degree of change across different sub-basins of CRB. We then characterized uncertainty of future projections for each season over CRB. Results reveal that model uncertainty is the main source of uncertainty, among others. However, downscaling uncertainty considerably contributes to the total uncertainty of future projections, especially in summer. On the contrary, downscaling uncertainty appears to be higher than scenario uncertainty for precipitation.

Temporal dynamics of direct N2O fluxes from agro-ecosystems in cold climates: importance of year-round measurements in multiple cropping systems

NASA Astrophysics Data System (ADS)

Wagner-Riddle, C.; Tenuta, M.

2014-12-01

Soil N2O fluxes (direct emissions) are highly variable in time and space due to soil, weather and management drivers. In cold climates, freeze/thaw cycles and short growing seasons can enhance soil N2O production contributing to the temporal variability of fluxes. Year-round measurements of N2O fluxes in multiple cropping systems are needed to decrease the uncertainty of annual emission estimates and to devise mitigation practices for emission reduction in cold climates. We have deployed a micrometeorological flux-gradient approach coupled to a tunable diode laser absorption spectroscopy system at two long-term sites in Canada: Elora, Ontario (2000-2014) and Glenlea, Manitoba (2006-2014). Quasi-simultaneous half-hourly flux measurements on four 4-ha fields within a level and aerodynamically homogeneous landscape were obtained allowing for comparison of crop type and/or management practices within and between years. Annual crops such as corn, soybeans, wheat, and barley received typical inorganic fertilizer and/or manure applications, and best management practices such as timing of application and reduced tillage were studied. Perennial grass-alfalfa hayfields were compared to annual crops during selected time periods. Here we synthesize the long-term datasets from these two sites, and quantify the overall contribution of non-growing season (mainly freeze/thaw cycles) and growing season (mainly nitrogen application) to annual emission totals. Uncertainties of regional estimates for cold-climates will be assessed using these long-term datasets.

Net primary productivity of subalpine meadows in Yosemite National Park in relation to climate variability

USGS Publications Warehouse

Moore, Peggy E.; Van Wagtendonk, Jan W.; Yee, Julie L.; McClaran, Mitchel P.; Cole, David N.; McDougald, Neil K.; Brooks, Matthew L.

2013-01-01

Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate. Our objective was to describe patterns and variability in aboveground live vascular plant biomass in relation to climatic factors. We harvested aboveground biomass at peak growth from four 64-m2 plots each in xeric, mesic, and hydric meadows annually from 1994 to 2000. Data from nearby weather stations provided independent variables of spring snow water content, snow-free date, and thawing degree days for a cumulative index of available energy. We assembled these climatic variables into a set of mixed effects analysis of covariance models to evaluate their relationships with annual aboveground net primary productivity (ANPP), and we used an information theoretic approach to compare the quality of fit among candidate models. ANPP in the xeric meadow was negatively related to snow water content and thawing degree days and in the mesic meadow was negatively related to snow water content. Relationships between ANPP and these 2 covariates in the hydric meadow were not significant. Increasing snow water content may limit ANPP in these meadows if anaerobic conditions delay microbial activity and nutrient availability. Increased thawing degree days may limit ANPP in xeric meadows by prematurely depleting soil moisture. Large within-year variation of ANPP in the hydric meadow limited sensitivity to the climatic variables. These relationships suggest that, under projected warmer and drier conditions, ANPP will increase in mesic meadows but remain unchanged in xeric meadows because declines associated with increased temperatures would offset the increases from decreased snow water content.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The influence of soil-site factors on sugar maple (Acer saccharum Marsh.) growth response to climatic change in central Ontario

NASA Astrophysics Data System (ADS)

Schutten, K.; Gedalof, Z.

2010-12-01

Over the past several decades, concerns about climatic change and its potential impacts on Canada’s various geographical regions and associated ecological processes have grown steadily, especially among land and resource managers. As these risks transition into tangible outcomes in the field, it will be important for resource managers to understand historical climatic variability and natural ecological trends in order to effectively respond to a changing climate. Sugar maple (Acer saccharum Marsh.) is considered a stable endpoint for mature forests in the northern hardwood community of central Ontario, and it tends to be the dominant species, in a beech-ironwood-yellow birch matrix. In North America, this species is used for both hardwood lumber and for maple sugar (syrup) products; where it dominates, large recreational opportunities also exist. There are many biotic and abiotic factors that play a large role in the growth and productivity of sugar maple stands, such as soil pH, moisture regime, and site slope and aspect. This research undertaking aims to add to the body of literature addressing the following question: how do site factors influence the sensitivity of sugar maple growth to climatic change? The overall objective of the research is to evaluate how biotic and abiotic factors influence the sensitivity of sugar maple annual radial growth to climatic variability. This research will focus on sugar maple growth and productivity in Algonquin Provincial Park, and the impact that climatic variability has had in the past on these stands based on site-specific characteristics. In order to complete this goal, 20 sites were identified in Algonquin Provincial Park based on variability of known soil and site properties. These sites were visited in order to collect biotic and abiotic site data, and to measure annual radial growth increment of trees. Using regional climate records and standard dendrochronological methods, the collected increment growth data will be used to build site-specific chronologies in order to determine the differences in tree growth response to climatic variability due to differences in soil and site quality. Preliminary results suggest that variability in site-specific abiotic and biotic conditions may strongly influence individual stand growth responses to climatic variability.

Connecting differential responses of native and invasive riparian plants to climate change and environmental alteration.

PubMed

Flanagan, Neal E; Richardson, Curtis J; Ho, Mengchi

2015-04-01

Climate change is predicted to impact river systems in the southeastern United States through alterations of temperature, patterns of precipitation and hydrology. Future climate scenarios for the southeastern United States predict (1) surface water temperatures will warm in concert with air temperature, (2) storm flows will increase and base flows will decrease, and (3) the annual pattern of synchronization between hydroperiod and water temperature will be altered. These alterations are expected to disturb floodplain plant communities, making them more vulnerable to establishment of invasive species. The primary objective of this study is to evaluate whether native and invasive riparian plant assemblages respond differently to alterations of climate and land use. To study the response of riparian wetlands to watershed and climate alterations, we utilized an existing natural experiment imbedded in gradients of temperature and hydrology-found among dammed and undammed rivers. We evaluated a suite of environmental variables related to water temperature, hydrology, watershed disturbance, and edaphic conditions to identify the strongest predictors of native and invasive species abundances. We found that native species abundance is strongly influenced by climate-driven variables such as temperature and hydrology, while invasive species abundance is more strongly influenced by site-specific factors such as land use and soil nutrient availability. The patterns of synchronization between plant phenology, annual hydrographs, and annual water temperature cycles may be key factors sustaining the viability of native riparian plant communities. Our results demonstrate the need to understand the interactions between climate, land use, and nutrient management in maintaining the species diversity of riparian plant communities. Future climate change is likely to result in diminished competitiveness of native plant species, while the competitiveness of invasive species will increase due to anthropogenic watershed disturbance and accelerated nutrient and sediment export.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Impact of spectral nudging on regional climate simulation over CORDEX East Asia using WRF

NASA Astrophysics Data System (ADS)

Tang, Jianping; Wang, Shuyu; Niu, Xiaorui; Hui, Pinhong; Zong, Peishu; Wang, Xueyuan

2017-04-01

In this study, the impact of the spectral nudging method on regional climate simulation over the Coordinated Regional Climate Downscaling Experiment East Asia (CORDEX-EA) region is investigated using the Weather Research and Forecasting model (WRF). Driven by the ERA-Interim reanalysis, five continuous simulations covering 1989-2007 are conducted by the WRF model, in which four runs adopt the interior spectral nudging with different wavenumbers, nudging variables and nudging coefficients. Model validation shows that WRF has the ability to simulate spatial distributions and temporal variations of the surface climate (air temperature and precipitation) over CORDEX-EA domain. Comparably the spectral nudging technique is effective in improving the model's skill in the following aspects: (1), the simulated biases and root mean square errors of annual mean temperature and precipitation are obviously reduced. The SN3-UVT (spectral nudging with wavenumber 3 in both zonal and meridional directions applied to U, V and T) and SN6 (spectral nudging with wavenumber 6 in both zonal and meridional directions applied to U and V) experiments give the best simulations for temperature and precipitation respectively. The inter-annual and seasonal variances produced by the SN experiments are also closer to the ERA-Interim observation. (2), the application of spectral nudging in WRF is helpful for simulating the extreme temperature and precipitation, and the SN3-UVT simulation shows a clear advantage over the other simulations in depicting both the spatial distributions and inter-annual variances of temperature and precipitation extremes. With the spectral nudging, WRF is able to preserve the variability in the large scale climate information, and therefore adjust the temperature and precipitation variabilities toward the observation.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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

PubMed

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

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

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

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Fire-climate interactions in the American west since 1400 CE

Treesearch

Valerie Trouet; Alan H. Taylor; Eugene R. Wahl; Carl N. Skinner

2010-01-01

Despite a strong anthropogenic fingerprint on 20th Century wildland fire activity in the American West, climate remains a main driver. A better understanding of the spatiotemporal variability in fire‐climate interactions is therefore crucial for fire management. Here, we present annually resolved, tree‐ring based fire records for four regions in the American West that...

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

PubMed

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

2016-09-01

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

Climate and life-history evolution in evening primroses (Oenothera, Onagraceae): a phylogenetic comparative analysis.

PubMed

Evans, Margaret E K; Hearn, David J; Hahn, William J; Spangle, Jennifer M; Venable, D Lawrence

2005-09-01

Evolutionary ecologists have long sought to understand the conditions under which perennial (iteroparous) versus annual (semelparous) plant life histories are favored. We evaluated the idea that aridity and variation in the length of droughts should favor the evolution of an annual life history, both by decreasing adult survival and by increasing the potential for high seedling survival via reduced plant cover. We calculated phylogenetically independent contrasts of climate with respect to life history in a clade of winter-establishing evening primroses (sections Anogra and Kleinia; Oenothera; Onagraceae), which includes seven annuals, 12 perennials, and two variable taxa. Climate variables were quantified from long-term records at weather stations near collection localities. To explicitly account for phylogenetic uncertainty, contrasts were calculated on a random sample of phylogenetic trees from the posterior distribution of a Bayesian analysis of DNA sequence data. Statements of association are based on comparing the per-tree mean contrast, which has a null expectation of zero, to a set of per-tree mean contrasts calculated on the same trees, after randomizing the climate data. As predicted, increased annual aridity, increased annual potential evapotranspiration, and decreased annual precipitation were associated with transitions to the annual habit, but these trends were not significantly different from the null pattern. Transitions to the annual habit were not significantly associated with increases in one measure of aridity in summer nor with increased summer drought, but they were associated with significantly increased maximum summer temperatures. In winter, increased aridity and decreased precipitation were significantly associated with transitions to the annual habit. Changes in life history were not significantly associated with changes in the coefficient of variation of precipitation, either on an annual or seasonal (summer vs. winter) basis. Though we cannot attribute causality on the basis of a correlational, historical study, our results are consistent with the idea that increased heat and drought at certain times of the year favor the evolution of the annual habit. Increased heat in summer may cause adult survival to decline, while increased aridity and decreased precipitation in the season of seedling recruitment (winter) may favor a drought-avoiding, short-lived annual strategy. Not all of the predicted patterns were observed: the capability for drought-induced dormancy may preclude change in habit in response to summer drought in our study group.

Socio-economic vulnerability to climate change in the central mountainous region of eastern Mexico.

PubMed

Esperón-Rodríguez, Manuel; Bonifacio-Bautista, Martín; Barradas, Víctor L

2016-03-01

Climate change effects are expected to be more severe for some segments of society than others. In Mexico, climate variability associated with climate change has important socio-economic and environmental impacts. From the central mountainous region of eastern Veracruz, Mexico, we analyzed data of total annual precipitation and mean annual temperature from 26 meteorological stations (1922-2008) and from General Circulation Models. We developed climate change scenarios based on the observed trends with projections to 2025, 2050, 2075, and 2100, finding considerable local climate changes with reductions in precipitation of over 700 mm and increases in temperature of ~9°C for the year 2100. Deforested areas located at windward were considered more vulnerable, representing potential risk for natural environments, local communities, and the main crops cultivated (sugarcane, coffee, and corn). Socio-economic vulnerability is exacerbated in areas where temperature increases and precipitation decreases.

Relationships between large-scale circulation patterns and carbon dioxide exchange by a deciduous forest

NASA Astrophysics Data System (ADS)

Zhang, Jingyong; Wu, Lingyun; Huang, Gang; Notaro, Michael

2011-02-01

In this study, we focus on a deciduous forest in central Massachusetts and investigate the relationships between global climate indices and CO2 exchange using eddy-covariance flux measurements from 1992 to 2007. Results suggest that large-scale circulation patterns influence the annual CO2 exchange in the forest through their effects on the local surface climate. Annual gross ecosystem exchange (GEE) in the forest is closely associated with spring El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), previous fall Atlantic Multidecadal Oscillation (AMO), and previous winter East Pacific-North Pacific (EP-NP) pattern. Annual net ecosystem exchange (NEE) responds to previous fall AMO and PDO, while annual respiration (R) is impacted by previous fall ENSO and Pacific/North American Oscillation (PNA). Regressions based on these relationships are developed to simulate the annual GEE, NEE, and R. To avoid problems of multicollinearity, we compute a "Composite Index for GEE (CIGEE)" based on a linear combination of spring ENSO and PDO, fall AMO, and winter EP-NP and a "Composite Index for R (CIR)" based on a linear combination of fall ENSO and PNA. CIGEE, CIR, and fall AMO and PDO can explain 41, 27, and 40% of the variance of the annual GEE, R, and NEE, respectively. We further apply the methodology to two other northern midlatitude forests and find that interannual variabilities in NEE of the two forests are largely controlled by large-scale circulation patterns. This study suggests that global climate indices provide the potential for predicting CO2 exchange variability in the northern midlatitude forests.

Hydroclimate temporal variability in a coastal Mediterranean watershed: the Tafna basin, North-West Algeria

NASA Astrophysics Data System (ADS)

Boulariah, Ouafik; Longobardi, Antonia; Meddi, Mohamed

2017-04-01

One of the major challenges scientists, practitioners and stakeholders are nowadays involved in, is to provide the worldwide population with reliable water supplies, protecting, at the same time, the freshwater ecosystems quality and quantity. Climate and land use changes undermine the balance between water demand and water availability, causing alteration of rivers flow regime. Knowledge of hydro-climate variables temporal and spatial variability is clearly helpful to plan drought and flood hazard mitigation strategies but also to adapt them to future environmental scenarios. The present study relates to the coastal semi-arid Tafna catchment, located in the North-West of Algeria, within the Mediterranean basin. The aim is the investigation of streamflow and rainfall indices temporal variability in six sub-basins of the large catchment Tafna, attempting to relate streamflow and rainfall changes. Rainfall and streamflow time series have been preliminary tested for data quality and homogeneity, through the coupled application of two-tailed t test, Pettitt test and Cumsum tests (significance level of 0.1, 0.05 and 0.01). Subsequently maximum annual daily rainfall and streamflow and average daily annual rainfall and streamflow time series have been derived and tested for temporal variability, through the application of the Mann Kendall and Sen's test. Overall maximum annual daily streamflow time series exhibit a negative trend which is however significant for only 30% of the station. Maximum annual daily rainfall also e exhibit a negative trend which is intend significant for the 80% of the stations. In the case of average daily annual streamflow and rainfall, the tendency for decrease in time is unclear and, in both cases, appear significant for 60% of stations.

Hydrologic impacts of changes in climate and glacier extent in the Gulf of Alaska watershed

NASA Astrophysics Data System (ADS)

Beamer, J. P.; Hill, D. F.; McGrath, D.; Arendt, A.; Kienholz, C.

2017-09-01

High-resolution regional-scale hydrologic models were used to quantify the response of late 21st century runoff from the Gulf of Alaska (GOA) watershed to changes in regional climate and glacier extent. NCEP Climate Forecast System Reanalysis data were combined with five Coupled Model Intercomparison Project Phase 5 general circulation models (GCMs) for two representative concentration pathway (RCP) scenarios (4.5 and 8.5) to develop meteorological forcing for the period 2070-2099. A hypsographic model was used to estimate future glacier extent given assumed equilibrium line altitude (ELA) increases of 200 and 400 m. GCM predictions show an increase in annual precipitation of 12% for RCP 4.5 and 21% for RCP 8.5, and an increase in annual temperature of 2.5°C for RCP 4.5 and 4.3°C for RCP 8.5, averaged across the GOA. Scenarios with perturbed climate and glaciers predict annual GOA-wide runoff to increase by 9% for RCP4.5/ELA200 case and 14% for the RCP8.5/ELA400 case. The glacier runoff decreased by 14% for RCP4.5/ELA200 and by 34% for the RCP8.5/ELA400 case. Intermodel variability in annual runoff was found to be approximately twice the variability in precipitation input. Additionally, there are significant changes in runoff partitioning and increases in snowpack runoff are dominated by increases in rain-on-snow events. We present results aggregated across the entire GOA and also for individual watersheds to illustrate the range in hydrologic regime changes and explore the sensitivities of these results by independently perturbing only climate forcings and only glacier cover.

Simulated impacts of climate change on phosphorus loading to Lake Michigan

USGS Publications Warehouse

Robertson, Dale M.; Saad, David A.; Christiansen, Daniel E.; Lorenz, David J

2016-01-01

Phosphorus (P) loading to the Great Lakes has caused various types of eutrophication problems. Future climatic changes may modify this loading because climatic models project changes in future meteorological conditions, especially for the key hydrologic driver — precipitation. Therefore, the goal of this study is to project how P loading may change from the range of projected climatic changes. To project the future response in P loading, the HydroSPARROW approach was developed that links results from two spatially explicit models, the SPAtially Referenced Regression on Watershed attributes (SPARROW) transport and fate watershed model and the water-quantity Precipitation Runoff Modeling System (PRMS). PRMS was used to project changes in streamflow throughout the Lake Michigan Basin using downscaled meteorological data from eight General Circulation Models (GCMs) subjected to three greenhouse gas emission scenarios. Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.

Using a predictive model to evaluate spatiotemporal variability in streamflow permanence across the Pacific Northwest region

NASA Astrophysics Data System (ADS)

Jaeger, K. L.

2017-12-01

The U.S. Geological Survey (USGS) has developed the PRObability Of Streamflow PERmanence (PROSPER) model, a GIS-based empirical model that provides predictions of the annual probability of a stream channel having year-round flow (Streamflow permanence probability; SPP) for any unregulated and minimally-impaired stream channel in the Pacific Northwest (Washington, Oregon, Idaho, western Montana). The model provides annual predictions for 2004-2016 at a 30-m spatial resolution based on monthly or annually updated values of climatic conditions, and static physiographic variables associated with the upstream basin. Prediction locations correspond to the channel network consistent with the National Hydrography Dataset stream grid and are publicly available through the USGS StreamStats platform (https://water.usgs.gov/osw/streamstats/). In snowmelt-driven systems, the most informative predictor variable was mean upstream snow water equivalent on May 1, which highlights the influence of late spring snow cover for supporting streamflow in mountain river networks. In non-snowmelt-driven systems, the most informative variable was mean annual precipitation. Streamflow permanence probabilities varied across the study area by geography and from year-to-year. Notably lower SPP corresponded to the climatically drier subregions of the study area. Higher SPP were concentrated in coastal and higher elevation mountain regions. In addition, SPP appeared to trend with average hydroclimatic conditions, which were also geographically coherent. The year-to-year variability lends support for the growing recognition of the spatiotemporal dynamism of streamflow permanence. An analysis of three focus basins located in contrasting geographical and hydroclimatic settings demonstrates differences in the sensitivity of streamflow permanence to antecedent climate conditions as a function of geography. Consequently, results suggest that PROSPER model can be a useful tool to evaluate regions of the landscape that may be resilient or sensitive to drought conditions, allowing for targeted management efforts to protect critical reaches.

Future changes in peak river flows across northern Eurasia as inferred from an ensemble of regional climate projections under the IPCC RCP8.5 scenario

NASA Astrophysics Data System (ADS)

Shkolnik, Igor; Pavlova, Tatiana; Efimov, Sergey; Zhuravlev, Sergey

2018-01-01

Climate change simulation based on 30-member ensemble of Voeikov Main Geophysical Observatory RCM (resolution 25 km) for northern Eurasia is used to drive hydrological model CaMa-Flood. Using this modeling framework, we evaluate the uncertainties in the future projection of the peak river discharge and flood hazard by 2050-2059 relative to 1990-1999 under IPCC RCP8.5 scenario. Large ensemble size, along with reasonably high modeling resolution, allows one to efficiently sample natural climate variability and increase our ability to predict future changes in the hydrological extremes. It has been shown that the annual maximum river discharge can almost double by the mid-XXI century in the outlets of major Siberian rivers. In the western regions, there is a weak signal in the river discharge and flood hazard, hardly discernible above climate variability. Annual maximum flood area is projected to increase across Siberia mostly by 2-5% relative to the baseline period. A contribution of natural climate variability at different temporal scales to the uncertainty of ensemble prediction is discussed. The analysis shows that there expected considerable changes in the extreme river discharge probability at locations of the key hydropower facilities. This suggests that the extensive impact studies are required to develop recommendations for maintaining regional energy security.

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

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

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

DTIC Science & Technology

2016-09-01

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

Climate change and associated spatial heterogeneity of Pakistan: Empirical evidence using multidisciplinary approach.

PubMed

Ali, Ghaffar

2018-09-01

Climate change is a multidimensional phenomenon, which has various implications for the environment and socio-economic conditions of the people. Its effects are deeper in an agrarian economy which is susceptible to the vagaries of nature. Therefore, climate change directly impacts the society in different ways, and society must pay the cost. Focusing on this truth, the main objective of this research was to investigate the empirical changes and spatial heterogeneity in the climate of Pakistan in real terms using time series data. Climate change and variability in Pakistan, over time, were estimated from 1961 to 2014 using all the climate variables for the very first time. Several studies were available on climate change impacts, mitigation, and adaptation; however, it was difficult to observe exactly how much change occurred in which province and when. A multidisciplinary approach was utilized to estimate the absolute change through a combination of environmental, econometric, and remote sensing methods. Moreover, the Autoregressive Distributed Lag (ARDL) model was used to ascertain the extent of variability in climate change and information was digitalized through ground truthing. Results showed that the average temperature of Pakistan increased by 2°C between 1960 and 1987 and 4°C between 1988 and 2014, and R 2 was 0.978. The rate of temperature increased 0.09°C between 1960 and 2014. The mean annual precipitation of Pakistan increased by 478mm, and its R 2 were 0.34-0.64. The mean annual humidity of Pakistan increased by 2.94%, and the rate of humidity has been increased by 0.97% from 1988 to 2014. Notably, Sindh and Balochistan provinces have shown a significant spatial heterogeneity regarding the increase in precipitation. Statistically all variables are significant. This would serve as a baseline information for climate change-related studies in Pakistan and its application in different sectors. This would also serve the plant breeders and policymakers of the country. Copyright © 2018 Elsevier B.V. All rights reserved.

Observations and simulations of the ionospheric lunar tide: Seasonal variability

NASA Astrophysics Data System (ADS)

Pedatella, N. M.

2014-07-01

The seasonal variability of the ionospheric lunar tide is investigated using a combination of Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) observations and thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) simulations. The present study focuses on the seasonal variability of the lunar tide in the ionosphere and its potential connection to the occurrence of stratosphere sudden warmings (SSWs). COSMIC maximum F region electron density (NmF2) and total electron content observations reveal a primarily annual variation of the ionospheric lunar tide, with maximum amplitudes occurring at low latitudes during December-February. Simulations of the lunar tide climatology in TIME-GCM display a similar annual variability as the COSMIC observations. This leads to the conclusion that the annual variability of the lunar tide in the ionosphere is not solely due to the occurrence of SSWs. Rather, the annual variability of the lunar tide in the ionosphere is generated by the seasonal variability of the lunar tide at E region altitudes. However, compared to the observations, the ionospheric lunar tide annual variability is weaker in the climatological simulations which is attributed to the occurrence of SSWs during the majority of the years included in the observations. Introducing a SSW into the TIME-GCM simulation leads to an additional enhancement of the lunar tide during Northern Hemisphere winter, increasing the lunar tide annual variability and resulting in an annual variability that is more consistent with the observations. The occurrence of SSWs can therefore potentially bias lunar tide climatologies, and it is important to consider these effects in studies of the lunar tide in the atmosphere and ionosphere.

Climate and soil attributes determine plant species turnover in global drylands

PubMed Central

Maestre, Fernando T.; Gotelli, Nicholas J.; Quero, José L.; Delgado-Baquerizo, Manuel; Bowker, Matthew A.; Eldridge, David J.; Ochoa, Victoria; Gozalo, Beatriz; Valencia, Enrique; Berdugo, Miguel; Escolar, Cristina; García-Gómez, Miguel; Escudero, Adrián; Prina, Aníbal; Alfonso, Graciela; Arredondo, Tulio; Bran, Donaldo; Cabrera, Omar; Cea, Alex; Chaieb, Mohamed; Contreras, Jorge; Derak, Mchich; Espinosa, Carlos I.; Florentino, Adriana; Gaitán, Juan; Muro, Victoria García; Ghiloufi, Wahida; Gómez-González, Susana; Gutiérrez, Julio R.; Hernández, Rosa M.; Huber-Sannwald, Elisabeth; Jankju, Mohammad; Mau, Rebecca L.; Hughes, Frederic Mendes; Miriti, Maria; Monerris, Jorge; Muchane, Muchai; Naseri, Kamal; Pucheta, Eduardo; Ramírez-Collantes, David A.; Raveh, Eran; Romão, Roberto L.; Torres-Díaz, Cristian; Val, James; Veiga, José Pablo; Wang, Deli; Yuan, Xia; Zaady, Eli

2015-01-01

Aim Geographic, climatic, and soil factors are major drivers of plant beta diversity, but their importance for dryland plant communities is poorly known. This study aims to: i) characterize patterns of beta diversity in global drylands, ii) detect common environmental drivers of beta diversity, and iii) test for thresholds in environmental conditions driving potential shifts in plant species composition. Location 224 sites in diverse dryland plant communities from 22 geographical regions in six continents. Methods Beta diversity was quantified with four complementary measures: the percentage of singletons (species occurring at only one site), Whittake’s beta diversity (β(W)), a directional beta diversity metric based on the correlation in species occurrences among spatially contiguous sites (β(R2)), and a multivariate abundance-based metric (β(MV)). We used linear modelling to quantify the relationships between these metrics of beta diversity and geographic, climatic, and soil variables. Results Soil fertility and variability in temperature and rainfall, and to a lesser extent latitude, were the most important environmental predictors of beta diversity. Metrics related to species identity (percentage of singletons and β(W)) were most sensitive to soil fertility, whereas those metrics related to environmental gradients and abundance ((β(R2)) and β(MV)) were more associated with climate variability. Interactions among soil variables, climatic factors, and plant cover were not important determinants of beta diversity. Sites receiving less than 178 mm of annual rainfall differed sharply in species composition from more mesic sites (> 200 mm). Main conclusions Soil fertility and variability in temperature and rainfall are the most important environmental predictors of variation in plant beta diversity in global drylands. Our results suggest that those sites annually receiving ~ 178 mm of rainfall will be especially sensitive to future climate changes. These findings may help to define appropriate conservation strategies for mitigating effects of climate change on dryland vegetation. PMID:25914437

The bivalve Glycymeris longior as an environmental archive for the Mar Argentino, southern South Atlantic

NASA Astrophysics Data System (ADS)

del Socorro Doldan, María; Morsan, Enrique Mario; Giménez, Lucas; Zaidman, Paula Cecilia

2017-04-01

Southern Hemisphere lacks of suitable high-resolution long datasets for the marine environment. This is translated in poor understanding of climate dynamics and processes at regional and continental-scale. We assessed the potential of Glycymeris longior as an environmental indicator for the mid-latitudes of South Atlantic by applying sclerochronological techniques on sample sets collected from San Matías Gulf, Mar Argentino, southern South Atlantic. We present a reconstruction of marine environmental variability of SMG for the period 1890-2016, covering 125 years. The reconstruction is based on the growth increment series for the first absolutely-dated annually-resolved multi-decadal G. longior bivalve on Sothern Atlantic. Shells were collected in 1918, 1933, 1945, 1983, 1989, 2009, 2011, 2015 and 2016. Sample depth varies between collection years. Age of the individuals was estimated from the hinge region of the shell. G. longior forms an annual narrow growth line. Maximal longevity was 40 years old. A strong common environmental signal is apparent in the increment widths. Correlations between the growth increment indices and regional temperature series (sea surface temperatures, continental temperatures) and other proxies were made. Preliminary results indicate that G.longior sclerochronologies, combined with low-frequency proxies can facilitate reconstructions of oceanographic variability. We discuss multi-decadal climate variability. Given the ability to generate annually-resolved chronologies G. longior is likely to be used as a climate recorder in southern South America. Hence, G. longior shells from Pleistocene marine deposits from Patagonia, Argentina, have a considerable potential to contain information of past climate for mid-latitudes of South Atlantic.

Multiple causes of nonstationarity in the Weihe annual low-flow series

NASA Astrophysics Data System (ADS)

Xiong, Bin; Xiong, Lihua; Chen, Jie; Xu, Chong-Yu; Li, Lingqi

2018-02-01

Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

Assessing risks of climate variability and climate change for Indonesian rice agriculture.

PubMed

Naylor, Rosamond L; Battisti, David S; Vimont, Daniel J; Falcon, Walter P; Burke, Marshall B

2007-05-08

El Niño events typically lead to delayed rainfall and decreased rice planting in Indonesia's main rice-growing regions, thus prolonging the hungry season and increasing the risk of annual rice deficits. Here we use a risk assessment framework to examine the potential impact of El Niño events and natural variability on rice agriculture in 2050 under conditions of climate change, with a focus on two main rice-producing areas: Java and Bali. We select a 30-day delay in monsoon onset as a threshold beyond which significant impact on the country's rice economy is likely to occur. To project the future probability of monsoon delay and changes in the annual cycle of rainfall, we use output from the Intergovernmental Panel on Climate Change AR4 suite of climate models, forced by increasing greenhouse gases, and scale it to the regional level by using empirical downscaling models. Our results reveal a marked increase in the probability of a 30-day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9-18% today (depending on the region) to 30-40% at the upper tail of the distribution. Predictions of the annual cycle of precipitation suggest an increase in precipitation later in the crop year (April-June) of approximately 10% but a substantial decrease (up to 75% at the tail) in precipitation later in the dry season (July-September). These results indicate a need for adaptation strategies in Indonesian rice agriculture, including increased investments in water storage, drought-tolerant crops, crop diversification, and early warning systems.

Climate-driven C4 plant distributions in China: divergence in C4 taxa

PubMed Central

Wang, Renzhong; Ma, Linna

2016-01-01

There have been debates on the driving factors of C4 plant expansion, such as PCO2 decline in the late Micocene and warmer climate and precipitation at large-scale modern ecosystems. These disputes are mainly due to the lack of direct evidence and extensive data analysis. Here we use mass flora data to explore the driving factors of C4 distribution and divergent patterns for different C4 taxa at continental scale in China. The results display that it is mean annual climate variables driving C4 distribution at present-day vegetation. Mean annual temperature is the critical restriction of total C4 plants and the precipitation gradients seem to have much less impact. Grass and sedge C4 plants are largely restricted to mean annual temperature and precipitation respectively, while Chenopod C4 plants are strongly restricted by aridity in China. Separate regression analysis can succeed to detect divergences of climate distribution patterns of C4 taxa at global scale. PMID:27302686

Statistical Approaches for Spatiotemporal Prediction of Low Flows

NASA Astrophysics Data System (ADS)

Fangmann, A.; Haberlandt, U.

2017-12-01

An adequate assessment of regional climate change impacts on streamflow requires the integration of various sources of information and modeling approaches. This study proposes simple statistical tools for inclusion into model ensembles, which are fast and straightforward in their application, yet able to yield accurate streamflow predictions in time and space. Target variables for all approaches are annual low flow indices derived from a data set of 51 records of average daily discharge for northwestern Germany. The models require input of climatic data in the form of meteorological drought indices, derived from observed daily climatic variables, averaged over the streamflow gauges' catchments areas. Four different modeling approaches are analyzed. Basis for all pose multiple linear regression models that estimate low flows as a function of a set of meteorological indices and/or physiographic and climatic catchment descriptors. For the first method, individual regression models are fitted at each station, predicting annual low flow values from a set of annual meteorological indices, which are subsequently regionalized using a set of catchment characteristics. The second method combines temporal and spatial prediction within a single panel data regression model, allowing estimation of annual low flow values from input of both annual meteorological indices and catchment descriptors. The third and fourth methods represent non-stationary low flow frequency analyses and require fitting of regional distribution functions. Method three is subject to a spatiotemporal prediction of an index value, method four to estimation of L-moments that adapt the regional frequency distribution to the at-site conditions. The results show that method two outperforms successive prediction in time and space. Method three also shows a high performance in the near future period, but since it relies on a stationary distribution, its application for prediction of far future changes may be problematic. Spatiotemporal prediction of L-moments appeared highly uncertain for higher-order moments resulting in unrealistic future low flow values. All in all, the results promote an inclusion of simple statistical methods in climate change impact assessment.

Modeled intermittency risk for small streams in the Upper Colorado River Basin under climate change

USGS Publications Warehouse

Reynolds, Lindsay V.; Shafroth, Patrick B.; Poff, N. LeRoy

2015-01-01

Longer, drier summers projected for arid and semi-arid regions of western North America under climate change are likely to have enormous consequences for water resources and river-dependent ecosystems. Many climate change scenarios for this region involve decreases in mean annual streamflow, late summer precipitation and late-summer streamflow in the coming decades. Intermittent streams are already common in this region, and it is likely that minimum flows will decrease and some perennial streams will shift to intermittent flow under climate-driven changes in timing and magnitude of precipitation and runoff, combined with increases in temperature. To understand current intermittency among streams and analyze the potential for streams to shift from perennial to intermittent under a warmer climate, we analyzed historic flow records from streams in the Upper Colorado River Basin (UCRB). Approximately two-thirds of 115 gaged stream reaches included in our analysis are currently perennial and the rest have some degree of intermittency. Dry years with combinations of high temperatures and low precipitation were associated with more zero-flow days. Mean annual flow was positively related to minimum flows, suggesting that potential future declines in mean annual flows will correspond with declines in minimum flows. The most important landscape variables for predicting low flow metrics were precipitation, percent snow, potential evapotranspiration, soils, and drainage area. Perennial streams in the UCRB that have high minimum-flow variability and low mean flows are likely to be most susceptible to increasing streamflow intermittency in the future.

Climatic and geographic predictors of life history variation in Eastern Massasauga (Sistrurus catenatus): A range-wide synthesis.

PubMed

Hileman, Eric T; King, Richard B; Adamski, John M; Anton, Thomas G; Bailey, Robyn L; Baker, Sarah J; Bieser, Nickolas D; Bell, Thomas A; Bissell, Kristin M; Bradke, Danielle R; Campa, Henry; Casper, Gary S; Cedar, Karen; Cross, Matthew D; DeGregorio, Brett A; Dreslik, Michael J; Faust, Lisa J; Harvey, Daniel S; Hay, Robert W; Jellen, Benjamin C; Johnson, Brent D; Johnson, Glenn; Kiel, Brooke D; Kingsbury, Bruce A; Kowalski, Matthew J; Lee, Yu Man; Lentini, Andrew M; Marshall, John C; Mauger, David; Moore, Jennifer A; Paloski, Rori A; Phillips, Christopher A; Pratt, Paul D; Preney, Thomas; Prior, Kent A; Promaine, Andrew; Redmer, Michael; Reinert, Howard K; Rouse, Jeremy D; Shoemaker, Kevin T; Sutton, Scott; VanDeWalle, Terry J; Weatherhead, Patrick J; Wynn, Doug; Yagi, Anne

2017-01-01

Elucidating how life history traits vary geographically is important to understanding variation in population dynamics. Because many aspects of ectotherm life history are climate-dependent, geographic variation in climate is expected to have a large impact on population dynamics through effects on annual survival, body size, growth rate, age at first reproduction, size-fecundity relationship, and reproductive frequency. The Eastern Massasauga (Sistrurus catenatus) is a small, imperiled North American rattlesnake with a distribution centered on the Great Lakes region, where lake effects strongly influence local conditions. To address Eastern Massasauga life history data gaps, we compiled data from 47 study sites representing 38 counties across the range. We used multimodel inference and general linear models with geographic coordinates and annual climate normals as explanatory variables to clarify patterns of variation in life history traits. We found strong evidence for geographic variation in six of nine life history variables. Adult female snout-vent length and neonate mass increased with increasing mean annual precipitation. Litter size decreased with increasing mean temperature, and the size-fecundity relationship and growth prior to first hibernation both increased with increasing latitude. The proportion of gravid females also increased with increasing latitude, but this relationship may be the result of geographically varying detection bias. Our results provide insights into ectotherm life history variation and fill critical data gaps, which will inform Eastern Massasauga conservation efforts by improving biological realism for models of population viability and climate change.

Climatic and geographic predictors of life history variation in Eastern Massasauga (Sistrurus catenatus): A range-wide synthesis

PubMed Central

King, Richard B.; Adamski, John M.; Anton, Thomas G.; Bailey, Robyn L.; Baker, Sarah J.; Bieser, Nickolas D.; Bell, Thomas A.; Bissell, Kristin M.; Bradke, Danielle R.; Campa, Henry; Casper, Gary S.; Cedar, Karen; Cross, Matthew D.; DeGregorio, Brett A.; Dreslik, Michael J.; Faust, Lisa J.; Harvey, Daniel S.; Hay, Robert W.; Jellen, Benjamin C.; Johnson, Brent D.; Johnson, Glenn; Kiel, Brooke D.; Kingsbury, Bruce A.; Kowalski, Matthew J.; Lee, Yu Man; Lentini, Andrew M.; Marshall, John C.; Mauger, David; Moore, Jennifer A.; Paloski, Rori A.; Phillips, Christopher A.; Pratt, Paul D.; Preney, Thomas; Prior, Kent A.; Promaine, Andrew; Redmer, Michael; Reinert, Howard K.; Rouse, Jeremy D.; Shoemaker, Kevin T.; Sutton, Scott; VanDeWalle, Terry J.; Weatherhead, Patrick J.; Wynn, Doug; Yagi, Anne

2017-01-01

Elucidating how life history traits vary geographically is important to understanding variation in population dynamics. Because many aspects of ectotherm life history are climate-dependent, geographic variation in climate is expected to have a large impact on population dynamics through effects on annual survival, body size, growth rate, age at first reproduction, size–fecundity relationship, and reproductive frequency. The Eastern Massasauga (Sistrurus catenatus) is a small, imperiled North American rattlesnake with a distribution centered on the Great Lakes region, where lake effects strongly influence local conditions. To address Eastern Massasauga life history data gaps, we compiled data from 47 study sites representing 38 counties across the range. We used multimodel inference and general linear models with geographic coordinates and annual climate normals as explanatory variables to clarify patterns of variation in life history traits. We found strong evidence for geographic variation in six of nine life history variables. Adult female snout-vent length and neonate mass increased with increasing mean annual precipitation. Litter size decreased with increasing mean temperature, and the size–fecundity relationship and growth prior to first hibernation both increased with increasing latitude. The proportion of gravid females also increased with increasing latitude, but this relationship may be the result of geographically varying detection bias. Our results provide insights into ectotherm life history variation and fill critical data gaps, which will inform Eastern Massasauga conservation efforts by improving biological realism for models of population viability and climate change. PMID:28196149

Impacts of Climate Trends and Variability on Livestock Production in Brazil

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Impacts of 2000-2050 Climate Change on Fine Particulate Matter (PM2.5) Air Quality in China Based on Statistical Projections Using an Ensemble of Global Climate Models

NASA Astrophysics Data System (ADS)

Leung, D. M.; Tai, A. P. K.; Shen, L.; Moch, J. M.; van Donkelaar, A.; Mickley, L. J.

2017-12-01

Fine particulate matter (PM2.5) air quality is strongly dependent on not only on emissions but also meteorological conditions. Here we examine the dominant synoptic circulation patterns that control day-to-day PM2.5 variability over China. We perform principal component (PC) analysis on 1998-2016 NCEP/NCAR Reanalysis I daily meteorological fields to diagnose distinct synoptic meteorological modes, and perform PC regression on spatially interpolated 2014-2016 daily mean PM2.5 concentrations in China to identify modes dominantly explaining PM2.5 variability. We find that synoptic systems, e.g., cold-frontal passages, maritime inflow and frontal precipitation, can explain up to 40% of the day-to-day PM2.5 variability in major metropolitan regions in China. We further investigate how annually changing frequencies of synoptic systems, as well as changing local meteorology, drive interannual PM2.5 variability. We apply a spectral analysis on the PC time series to obtain the 1998-2016 annual median synoptic frequency, and use a forward-selection multiple linear regression (MLR) model of satellite-derived 1998-2015 annual mean PM2.5 concentrations on local meteorology and synoptic frequency, selecting predictors that explain the highest fraction of interannual PM2.5 variability while guarding against multicollinearity. To estimate the effect of climate change on future PM2.5 air quality, we project a multimodel ensemble of 15 CMIP5 models under the RCP8.5 scenario on the PM2.5-to-meteorology sensitivities derived for the present-day from the MLR model. Our results show that climate change could be responsible for increases in PM2.5 of more than 25 μg m-3 in northwestern China and 10 mg m-3 in northeastern China by the 2050s. Increases in synoptic frequency of cold-frontal passages cause only a modest 1 μg m-3 decrease in PM2.5 in North China Plain. Our analyses show that climate change imposes a significant penalty on air quality over China and poses serious threat on human health under the RCP8.5 future.

Effect of climate, intra and inter-annual variability, on nutrients emission (C,N, P) in stream water: lessons from an agricultural long term observatory of the temperate zone

NASA Astrophysics Data System (ADS)

Gascuel-Odoux, Chantal; Remi, Dupas; Patrick, Durand; Ophélie, Fovet; Gerard, Gruau; Anne, Jaffrezic; Guillaume, Humbert; Philippe, Merot; Gu, Sen

2016-04-01

Agriculture greatly contributes to modify C, N and P cycles, particularly in animal breeding regions due to high inputs. Climatic conditions, intra and inter-annual variabilities, modify nutrient stream water emissions, acting in time on transfer and transformation, accumulation and mobilization processes, connecting and disconnecting in time different compartments (soil, riparian areas, groundwater). In agricultural catchments, nutrient perturbations are dominated by agricultural land use, and decoupling human activities and climate effects is far from easy. Climate change generally appears as a secondary driver compared to land use. If studied, generally only one nutrient is considered. Only long term, high frequency and multiple element data series can decouple these two drivers. The Kervidy-Naizin watershed belongs to the AgrHyS environmental research observatory (http://www6.inra.fr/ore_agrhys_eng), itself included in RBV (French catchment network of the CZO). On this catchment, 6 years of daily data on DOC, NO3, SRP, TP concentrations allow us to analyze the effect of seasonal and inter-annual climatic variabilities on water quality (C, N, P). Different papers have been published on the effect of climate on nitrate (Molenat et al, 2008), SRP and TP (Dupas et al, 2015) and DOC (Humbert et al, 2015). We will present first results comparing the effect of climate on these three major solute forms of C, N and P. While C and P dynamics are very close and controlled by fluctuation of water table downslope, i.e. in riparian areas, mobilizing C and P in time, nitrate dynamics is controlled by GW dynamics upslope acting as the major N reservoir. As example, the dryness conditions in summer appears a key factor of the C and P emissions in autumn. All the three solute forms interact when anoxic conditions are observed in riparian zones. These basic processes explain how climatic variability can influence and explain interactions between C, N and P emissions in stream water. These results underline three major lack in most of our observatories: high frequency data as flood event are important for C and P emissions; multiple element approach, as very few observatories have currently C, N and P, their solute and particulate forms; climate but also soil wetness, GW fluctuations explaining biotransformation and connection between reservoirs on catchments, so that linking hydrological and biogeochimical condition is necessary to explain export. These lacks of observations is a barrier to develop process based models assessing and predicting the effect of climate on water quality. References Dupas R., Gruau G., Sen Gu, Humbert G., Jaffrezic A., Gascuel-Odoux C., 2015. Groundwater control of biogeochemical processes causing phosphorus release from riparian wetlands. Water Research 84, 307-314 Humbert G., Jaffrezic A., Fovet O., Gruau G., Durand P., 2015. Dry-season length and runoff control annual variability in stream DOC dynamics in a small, shallow groundwater-dominated agricultural watershed. Water Resources Research. Molenat J., Gascuel-Odoux C., Ruiz L., Gruau G., 2008. Role of water table dynamics on stream nitrate export and concentration in agricultural headwater. Journal of Hydrology 348, 363- 378.

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.

Simulating effects of fire disturbance and climate change on boreal forest productivity and evapotranspiration.

PubMed

Kang, Sinkyu; Kimball, John S; Running, Steven W

2006-06-01

We used a terrestrial ecosystem process model, BIOME-BGC, to investigate historical climate change and fire disturbance effects on regional carbon and water budgets within a 357,500 km(2) portion of the Canadian boreal forest. Historical patterns of increasing atmospheric CO2, climate change, and regional fire activity were used as model drivers to evaluate the relative effects of these impacts to spatial patterns and temporal trends in forest net primary production (NPP) and evapotranspiration (ET). Historical trends of increasing atmospheric CO2 resulted in overall 13% and 5% increases in annual NPP and ET from 1994 to 1996, respectively. NPP was found to be relatively sensitive to changes in air temperature (T(a)), while ET was more sensitive to precipitation (P) change within the ranges of observed climate variability (e.g., +/-2 degrees C for T(a) and +/-20% for P). In addition, the potential effect of climate change related warming on NPP is exacerbated or offset depending on whether these changes are accompanied by respective decreases or increases in precipitation. Historical fire activity generally resulted in reductions of both NPP and ET, which consumed an average of approximately 6% of annual NPP from 1959 to 1996. Areas currently occupied by dry conifer forests were found to be subject to more frequent fire activity, which consumed approximately 8% of annual NPP. The results of this study show that the North American boreal ecosystem is sensitive to historical patterns of increasing atmospheric CO2, climate change and regional fire activity. The relative impacts of these disturbances on NPP and ET interact in complex ways and are spatially variable depending on regional land cover and climate gradients.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Fine-spatial scale predictions of understory species using climate- and LiDAR-derived terrain and canopy metrics

NASA Astrophysics Data System (ADS)

Nijland, Wiebe; Nielsen, Scott E.; Coops, Nicholas C.; Wulder, Michael A.; Stenhouse, Gordon B.

2014-01-01

Food and habitat resources are critical components of wildlife management and conservation efforts. The grizzly bear (Ursus arctos) has diverse diets and habitat requirements particularly for understory plant species, which are impacted by human developments and forest management activities. We use light detection and ranging (LiDAR) data to predict the occurrence of 14 understory plant species relevant to bear forage and compare our predictions with more conventional climate- and land cover-based models. We use boosted regression trees to model each of the 14 understory species across 4435 km2 using occurrence (presence-absence) data from 1941 field plots. Three sets of models were fitted: climate only, climate and basic land and forest covers from Landsat 30-m imagery, and a climate- and LiDAR-derived model describing both the terrain and forest canopy. Resulting model accuracies varied widely among species. Overall, 8 of 14 species models were improved by including the LiDAR-derived variables. For climate-only models, mean annual precipitation and frost-free periods were the most important variables. With inclusion of LiDAR-derived attributes, depth-to-water table, terrain-intercepted annual radiation, and elevation were most often selected. This suggests that fine-scale terrain conditions affect the distribution of the studied species more than canopy conditions.

The Eocene climate of China, the early elevation of the Tibetan Plateau and the onset of the Asian Monsoon.

PubMed

Wang, Qing; Spicer, Robert A; Yang, Jian; Wang, Yu-Fei; Li, Cheng-Sen

2013-12-01

Eocene palynological samples from 37 widely distributed sites across China were analysed using co-existence approach to determine trends in space and time for seven palaeoclimate variables: Mean annual temperature, mean annual precipitation, mean temperature of the warmest month, mean temperature of the coldest month, mean annual range of temperature, mean maximum monthly precipitation and mean minimum monthly precipitation. Present day distributions and observed climates within China of the nearest living relatives of the fossil forms were used to find the range of a given variable in which a maximum number of taxa can coexist. Isotherm and isohyet maps for the early, middle and late Eocene were constructed. These illustrate regional changing patterns in thermal and precipitational gradients that may be interpreted as the beginnings of the modern Asian Monsoon system, and suggest that the uplift of parts of the Tibetan Plateau appear to have taken place by the middle to late Eocene. © 2013 John Wiley & Sons Ltd.

Temporal variability patterns in solar radiation estimations

NASA Astrophysics Data System (ADS)

Vindel, José M.; Navarro, Ana A.; Valenzuela, Rita X.; Zarzalejo, Luis F.

2016-06-01

In this work, solar radiation estimations obtained from a satellite and a numerical weather prediction model in mainland Spain have been compared. Similar comparisons have been formerly carried out, but in this case, the methodology used is different: the temporal variability of both sources of estimation has been compared with the annual evolution of the radiation associated to the different study climate zones. The methodology is based on obtaining behavior patterns, using a Principal Component Analysis, following the annual evolution of solar radiation estimations. Indeed, the adjustment degree to these patterns in each point (assessed from maps of correlation) may be associated with the annual radiation variation (assessed from the interquartile range), which is associated, in turn, to different climate zones. In addition, the goodness of each estimation source has been assessed comparing it with data obtained from the radiation measurements in ground by pyranometers. For the study, radiation data from Satellite Application Facilities and data corresponding to the reanalysis carried out by the European Centre for Medium-Range Weather Forecasts have been used.

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

NASA Astrophysics Data System (ADS)

Fox, Bethany; Wilson, Gary; Lee, Daphne

2016-04-01

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

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.

Major modes of short-term climate variability in the newly developed NUIST Earth System Model (NESM)

NASA Astrophysics Data System (ADS)

Cao, Jian; Wang, Bin; Xiang, Baoqiang; Li, Juan; Wu, Tianjie; Fu, Xiouhua; Wu, Liguang; Min, Jinzhong

2015-05-01

A coupled earth system model (ESM) has been developed at the Nanjing University of Information Science and Technology (NUIST) by using version 5.3 of the European Centre Hamburg Model (ECHAM), version 3.4 of the Nucleus for European Modelling of the Ocean (NEMO), and version 4.1 of the Los Alamos sea ice model (CICE). The model is referred to as NUIST ESM1 (NESM1). Comprehensive and quantitative metrics are used to assess the model's major modes of climate variability most relevant to subseasonal-to-interannual climate prediction. The model's assessment is placed in a multi-model framework. The model yields a realistic annual mean and annual cycle of equatorial SST, and a reasonably realistic precipitation climatology, but has difficulty in capturing the spring-fall asymmetry and monsoon precipitation domains. The ENSO mode is reproduced well with respect to its spatial structure, power spectrum, phase locking to the annual cycle, and spatial structures of the central Pacific (CP)-ENSO and eastern Pacific (EP)-ENSO; however, the equatorial SST variability, biennial component of ENSO, and the amplitude of CP-ENSO are overestimated. The model captures realistic intraseasonal variability patterns, the vertical-zonal structures of the first two leading predictable modes of Madden-Julian Oscillation (MJO), and its eastward propagation; but the simulated MJO speed is significantly slower than observed. Compared with the T42 version, the high resolution version (T159) demonstrates improved simulation with respect to the climatology, interannual variance, monsoon-ENSO lead-lag correlation, spatial structures of the leading mode of the Asian-Australian monsoon rainfall variability, and the eastward propagation of the MJO.

Inter-annual and spatial variability in hillslope runoff and mercury flux during spring snowmelt.

PubMed

Haynes, Kristine M; Mitchell, Carl P J

2012-08-01

Spring snowmelt is an important period of mercury (Hg) export from watersheds. Limited research has investigated the potential effects of climate variability on hydrologic and Hg fluxes during spring snowmelt. The purpose of this research was to assess the potential impacts of inter-annual climate variability on Hg mobility in forested uplands, as well as spatial variability in hillslope hydrology and Hg fluxes. We compared hydrological flows, Hg and solute mobility from three adjacent hillslopes in the S7 watershed of the Marcell Experimental Forest, Minnesota during two very different spring snowmelt periods: one following a winter (2009-2010) with severely diminished snow accumulation (snow water equivalent (SWE) = 48 mm) with an early melt, and a second (2010-2011) with significantly greater winter snow accumulation (SWE = 98 mm) with average to late melt timing. Observed inter-annual differences in total Hg (THg) and dissolved organic carbon (DOC) yields were predominantly flow-driven, as the proportion by which solute yields increased was the same as the increase in runoff. Accounting for inter-annual differences in flow, there was no significant difference in THg and DOC export between the two snowmelt periods. The spring 2010 snowmelt highlighted the important contribution of melting soil frost in the timing of a considerable portion of THg exported from the hillslope, accounting for nearly 30% of the THg mobilized. Differences in slope morphology and soil depths to the confining till layer were important in controlling the large observed spatial variability in hydrological flowpaths, transmissivity feedback responses, and Hg flux trends across the adjacent hillslopes.

A 3000-year annual-resolution record of the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Kelly, B. F.; Mariethoz, G.; Hellstrom, J.; Baker, A.

2013-12-01

The North Atlantic Oscillation provides an index of North Atlantic climate variability. The 947-yr long annual resolution record of the North Atlantic Oscillation (NAO) of Trouet et al. (2009, Science, 324, 78-81), the NAO Morocco-Scotland index, combined tree ring and stalagmite data, the latter a single stalagmite growth rate archive from NW Scotland. Trouet et al (2009) noted the unusual persistence of the positive phase of the NAO during the Medieval Climate Anomaly (MCA; 1050-1400AD). In order to better assess the uniqueness of the persistently positive NAO in the MCA, we extend the speleothem portion of the proxy NAO record with a composite of five stalagmites from the same cave system. We present the first-ever composite speleothem growth rate record. Using a combination of lamina counting, U-Th dating, and correlation between growth rate series, we build a continuous, annual-resolution, annually laminated, stalagmite growth rates series for the last 3000 years. We use geostatistical and stochastic approaches appropriate to stalagmite growth rate time series to characterise uncertainty in the stalagmite series and to screen them for periods of relative climate sensitivity vs. periods where there is hydrologically introduced, non-climatic variability. We produce the longest annual-resolution annual lamina record of the NAO for the last 3000 years. The screened stalagmite series is compared to instrumental and proxy records of the NAO. Spectral and wavelet analysis demonstrates that the series contains significant decadal to centennial scale periodicity throughout the record. We demonstrate that the persistently positive NAO during the MCA (1080-1460 CE) is remarkable within the last 3000 years. Two other phases of persistent, positive NAO, occur at 290-550 CE and 660-530 BCE, in agreement with the lower resolution, 5,200-yr Greenland lake sediment NAO proxy (Olsen et al, 2012, Nature Geoscience, 5, 808-812).

Mid-Piacensian mean annual sea surface temperature: an analysis for data-model comparisons

USGS Publications Warehouse

Dowsett, Harry J.; Robinson, Marci M.; Foley, Kevin M.; Stoll, Danielle K.

2010-01-01

Numerical models of the global climate system are the primary tools used to understand and project climate disruptions in the form of future global warming. The Pliocene has been identified as the closest, albeit imperfect, analog to climate conditions expected for the end of this century, making an independent data set of Pliocene conditions necessary for ground truthing model results. Because most climate model output is produced in the form ofmean annual conditions, we present a derivative of the USGS PRISM3 Global Climate Reconstruction which integrates multiple proxies of sea surface temperature (SST) into single surface temperature anomalies. We analyze temperature estimates from faunal and floral assemblage data,Mg/Ca values and alkenone unsaturation indices to arrive at a single mean annual SST anomaly (Pliocene minus modern) best describing each PRISM site, understanding that multiple proxies should not necessarily show concordance. The power of themultiple proxy approach lies within its diversity, as no two proxies measure the same environmental variable. This data set can be used to verify climate model output, to serve as a starting point for model inter-comparisons, and for quantifying uncertainty in Pliocene model prediction in perturbed physics ensembles.

Climate drives shifts in grass reproductive phenology across the western USA

USGS Publications Warehouse

Munson, Seth M.; Long, A. Lexine

2016-01-01

The capacity of grass species to alter their reproductive timing across space and through time can indicate their ability to cope with environmental variability and help predict their future performance under climate change.We determined the long-term (1895–2013) relationship between flowering times of grass species and climate in space and time using herbarium records across ecoregions of the western USA.There was widespread concordance of C3 grasses accelerating flowering time and general delays for C4 grasses with increasing mean annual temperature, with the largest changes for annuals and individuals occurring in more northerly, wetter ecoregions. Flowering time was delayed for most grass species with increasing mean annual precipitation across space, while phenology–precipitation relationships through time were more mixed.Our results suggest that the phenology of most grass species has the capacity to respond to increases in temperature and altered precipitation expected with climate change, but weak relationships for some species in time suggest that climate tracking via migration or adaptation may be required. Divergence in phenological responses among grass functional types, species, and ecoregions suggests that climate change will have unequal effects across the western USA.

Burned forests impact water supplies.

PubMed

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

2018-04-10

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

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

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

Plasticity in Dendroclimatic Response across the Distribution Range of Aleppo Pine (Pinus halepensis)

PubMed Central

de Luis, Martin; Čufar, Katarina; Di Filippo, Alfredo; Novak, Klemen; Papadopoulos, Andreas; Piovesan, Gianluca; Rathgeber, Cyrille B. K.; Raventós, José; Saz, Miguel Angel; Smith, Kevin T.

2013-01-01

We investigated the variability of the climate-growth relationship of Aleppo pine across its distribution range in the Mediterranean Basin. We constructed a network of tree-ring index chronologies from 63 sites across the region. Correlation function analysis identified the relationships of tree-ring index to climate factors for each site. We also estimated the dominant climatic gradients of the region using principal component analysis of monthly, seasonal, and annual mean temperature and total precipitation from 1,068 climatic gridpoints. Variation in ring width index was primarily related to precipitation and secondarily to temperature. However, we found that the dendroclimatic relationship depended on the position of the site along the climatic gradient. In the southern part of the distribution range, where temperature was generally higher and precipitation lower than the regional average, reduced growth was also associated with warm and dry conditions. In the northern part, where the average temperature was lower and the precipitation more abundant than the regional average, reduced growth was associated with cool conditions. Thus, our study highlights the substantial plasticity of Aleppo pine in response to different climatic conditions. These results do not resolve the source of response variability as being due to either genetic variation in provenance, to phenotypic plasticity, or a combination of factors. However, as current growth responses to inter-annual climate variability vary spatially across existing climate gradients, future climate-growth relationships will also likely be determined by differential adaptation and/or acclimation responses to spatial climatic variation. The contribution of local adaptation and/or phenotypic plasticity across populations to the persistence of species under global warming could be decisive for prediction of climate change impacts across populations. In this sense, a more complex forest dynamics modeling approach that includes the contribution of genetic variation and phenotypic plasticity can improve the reliability of the ecological inferences derived from the climate-growth relationships. PMID:24391786

Drought and deluge: Effects of recent climate variability on groundwater levels in eastern Arkansas

USGS Publications Warehouse

Czarnecki, John B.; Schrader, T.P.

2013-01-01

Arkansas experienced wide extremes in climate variability during the period of 2005 to 2010, recording the largest annual precipitation ever recorded in the State (100.05 inches) in 2009. Many weather stations across the State reported between 80 to 90 inches of rainfall in 2009. For comparison, the average annual precipitation in Little Rock, Arkansas, for the period 1878 to 2010 was 47.1 inches. In contrast, 2005 and 2010 were the 7th and 14th driest years on record in Little Rock with 34.55 and 36.52 inches, respectively; both tied as the hottest years ever recorded in Arkansas. The wettest year on record in Little Rock (2009) was interspersed within these dry years, with a total of 81.79 inches. Fifteen weather stations within the State ranked 2009 as the wettest year on record. Extremes in annual precipitation rates may lead to greater variability in groundwater recharge rates and water use, particularly in the agricultural areas in eastern Arkansas that rely heavily on groundwater produced from the Mississippi River Valley alluvial aquifer (hereafter referred to as the alluvial aquifer). How does this variability affect the groundwater system and water use therein? Are the effects of this variability discernable in measured water levels in wells? Czarnecki and Schrader examined these questions and provided some insights, the results of which are presented here.

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

USGS Publications Warehouse

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

2008-01-01

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

Analyzing the responses of species assemblages to climate change across the Great Basin, USA.

NASA Astrophysics Data System (ADS)

Henareh Khalyani, A.; Falkowski, M. J.; Crookston, N.; Yousef, F.

2016-12-01

The potential impacts of climate change on the future distribution of tree species in not well understood. Climate driven changes in tree species distribution could cause significant changes in realized species niches, potentially resulting in the loss of ecotonal species as well as the formation on novel assemblages of overlapping tree species. In an effort to gain a better understating of how the geographic distribution of tree species may respond to climate change, we model the potential future distribution of 50 different tree species across 70 million ha in the Great Basin, USA. This is achieved by leveraging a species realized niche model based on non-parametric analysis of species occurrences across climatic, topographic, and edaphic variables. Spatially explicit, high spatial resolution (30 m) climate variables (e.g., precipitation, and minimum, maximum, and mean temperature) and associated climate indices were generated on an annual basis between 1981-2010 by integrating climate station data with digital elevation data (Shuttle Radar Topographic Mission (SRTM) data) in a thin plate spline interpolation algorithm (ANUSPLIN). Bioclimate models of species niches in in the cotemporary period and three following 30 year periods were then generated by integrating the climate variables, soil data, and CMIP 5 general circulation model projections. Our results suggest that local scale contemporary variations in species realized niches across space are influenced by edaphic and topographic variables as well as climatic variables. The local variability in soil properties and topographic variability across space also affect the species responses to climate change through time and potential formation of species assemblages in future. The results presented here in will aid in the development of adaptive forest management techniques aimed at mitigating negative impacts of climate change on forest composition, structure, and function.

Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

Winter temperature conditions (1670-2010) reconstructed from varved sediments, western Canadian High Arctic

NASA Astrophysics Data System (ADS)

Amann, Benjamin; Lamoureux, Scott F.; Boreux, Maxime P.

2017-09-01

Advances in paleoclimatology from the Arctic have provided insights into long-term climate conditions. However, while past annual and summer temperature have received considerable research attention, comparatively little is known about winter paleoclimate. Arctic winter is of special interest as it is the season with the highest sensitivity to climate change, and because it differs substantially from summer and annual measures. Therefore, information about past changes in winter climate is key to improve our knowledge of past forced climate variability and to reduce uncertainty in climate projections. In this context, Arctic lakes with snowmelt-fed catchments are excellent potential winter climate archives. They respond strongly to snowmelt-induced runoff, and indirectly to winter temperature and snowfall conditions. To date, only a few well-calibrated lake sediment records exist, which appear to reflect site-specific responses with differing reconstructions. This limits the possibility to resolve large-scale winter climate change prior the instrumental period. Here, we present a well-calibrated quantitative temperature and snowfall record for the extended winter season (November through March; NDJFM) from Chevalier Bay (Melville Island, NWT, Canadian Arctic) back to CE 1670. The coastal embayment has a large catchment influenced by nival terrestrial processes, which leads to high sedimentation rates and annual sedimentary structures (varves). Using detailed microstratigraphic analysis from two sediment cores and supported by μ-XRF data, we separated the nival sedimentary units (spring snowmelt) from the rainfall units (summer) and identified subaqueous slumps. Statistical correlation analysis between the proxy data and monthly climate variables reveals that the thickness of the nival units can be used to predict winter temperature (r = 0.71, pc < 0.01, 5-yr filter) and snowfall (r = 0.65, pc < 0.01, 5-yr filter) for the western Canadian High Arctic over the last ca. 400 years. Results reveal a strong variability in winter temperature back to CE 1670 with the coldest decades reconstructed for the period CE 1800-1880, while the warmest decades and major trends are reconstructed for the period CE 1880-1930 (0.26°C/decade) and CE 1970-2010 (0.37°C/decade). Although the first aim of this study was to increase the paleoclimate data coverage for the winter season, the record from Chevalier Bay also holds great potential for more applied climate research such as data-model comparisons and proxy-data assimilation in climate model simulations.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

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

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Climatic variation and the distribution of an amphibian polyploid complex

USGS Publications Warehouse

Otto, C.R.V.; Snodgrass, J.W.; Forester, D.C.; Mitchell, J.C.; Miller, R.W.

2007-01-01

1. The establishment of polyploid populations involves the persistence and growth of the polyploid in the presence of the progenitor species. Although there have been a number of animal polyploid species documented, relatively few inquiries have been made into the large-scale mechanisms of polyploid establishment in animal groups. Herein we investigate the influence of regional climatic conditions on the distributional patterns of a diploid-tetraploid species pair of gray treefrogs, Hyla chrysoscelis and H. versicolor (Anura: Hylidae) in the mid-Atlantic region of eastern North America. 2. Calling surveys at breeding sites were used to document the distribution of each species. Twelve climatic models and one elevation model were generated to predict climatic and elevation values for gray treefrog breeding sites. A canonical analysis of discriminants was used to describe relationships between climatic variables, elevation and the distribution of H. chrysoscelis and H. versicolor. 3. There was a strong correlation between several climatic variables, elevation and the distribution of the gray treefrog complex. Specifically, the tetraploid species almost exclusively occupied areas of higher elevation, where climatic conditions were relatively severe (colder, drier, greater annual variation). In contrast, the diploid species was restricted to lower elevations, where climatic conditions were warmer, wetter and exhibited less annual variation. 4. Clusters of syntopic sites were associated with areas of high variation in annual temperature and precipitation during the breeding season. 5. Our data suggest that large-scale climatic conditions have played a role in the establishment of the polyploid H. versicolor in at least some portions of its range. The occurrence of the polyploid and absence of the progenitor in colder, drier and more varied environments suggests the polyploid may posses a tolerance of severe environmental conditions that is not possessed by the diploid progenitor. 6. Our findings support the hypothesis that increased tolerance to severe environmental conditions is a plausible mechanism of polyploid establishment.

Modelling fire frequency and area burned across phytoclimatic regions in Spain using reanalysis data and the Canadian Fire Weather Index System

NASA Astrophysics Data System (ADS)

Bedia, J.; Herrera, S.; Gutiérrez, J. M.

2013-09-01

We develop fire occurrence and burned area models in peninsular Spain, an area of high variability in climate and fuel types, for the period 1990-2008. We based the analysis on a phytoclimatic classification aiming to the stratification of the territory into homogeneous units in terms of climatic and fuel type characteristics, allowing to test model performance under different climatic and fuel conditions. We used generalized linear models (GLM) and multivariate adaptive regression splines (MARS) as modelling algorithms and temperature, relative humidity, precipitation and wind speed, taken from the ERA-Interim reanalysis, as well as the components of the Canadian Forest Fire Weather Index (FWI) System as predictors. We also computed the standardized precipitation-evapotranspiration index (SPEI) as an additional predictor for the models of burned area. We found two contrasting fire regimes in terms of area burned and number of fires: one characterized by a bimodal annual pattern, characterizing the Nemoral and Oro-boreal phytoclimatic types, and another one exhibiting an unimodal annual cycle, with the fire season concentrated in the summer months in the Mediterranean and Arid regions. The fire occurrence models attained good skill in most of the phytoclimatic zones considered, yielding in some zones notably high correlation coefficients between the observed and modelled inter-annual fire frequencies. Total area burned also exhibited a high dependence on the meteorological drivers, although their ability to reproduce the observed annual burned area time series was poor in most cases. We identified temperature and some FWI system components as the most important explanatory variables, and also SPEI in some of the burned area models, highlighting the adequacy of the FWI system for fire modelling applications and leaving the door opened to the development a more complex modelling framework based on these predictors. Furthermore, we demonstrate the potential usefulness of ERA-Interim reanalysis data for the reconstruction of historical fire-climate relationships at the scale of analysis. Fire frequency predictions may provide a preferable basis for past fire history reconstruction, long-term monitoring and the assessment of future climate impacts on fire regimes across regions, posing several advantages over burned area as response variable.

Geo-climatic heterogeneity in self-reported asthma, allergic rhinitis and chronic bronchitis in Italy.

PubMed

Pesce, G; Bugiani, M; Marcon, A; Marchetti, P; Carosso, A; Accordini, S; Antonicelli, L; Cogliani, E; Pirina, P; Pocetta, G; Spinelli, F; Villani, S; de Marco, R

2016-02-15

Several studies highlighted a great variability, both between and within countries, in the prevalence of asthma and chronic airways diseases. To evaluate if geo-climatic variations can explain the heterogeneity in the prevalence of asthma and respiratory diseases in Italy. Between 2006 and 2010, a postal screening questionnaire on respiratory health was administered to 18,357 randomly selected subjects, aged 20-44, living in 7 centers in northern, central, and southern Italy. A random-effects meta-analysis was fitted to evaluate the between-centers heterogeneity in the prevalence of asthma, asthma-like symptoms, allergic rhinitis, and chronic bronchitis (CB). A principal component analysis (PCA) was performed to synthetize the geo-climatic information (annual mean temperature, range of temperature, annual rainfalls, global solar radiations, altitude, distance from the sea) of all the 110 Italian province capital towns. The associations between these geo-climatic components obtained with PCA and the prevalence of respiratory diseases were analyzed through meta-regression models. 10,464 (57%) subjects responded to the questionnaire. There was a significant between-centers heterogeneity in the prevalence of asthma (I(2)=59.5%, p=0.022) and CB (I(2)=60.5%, p=0.019), but not in that of asthma-like symptoms or allergic rhinitis. Two independent geo-climatic components explaining together about 80% of the overall geo-climatic variability were identified: the first principally summarized the climatic variables; the second the topographic ones. Variations in the prevalence of asthma across centers were significantly associated with differences in the climatic component (p=0.017), but not with differences in the topographic one. Our findings suggest that climate play a role in determining the between-center heterogeneity in the prevalence of asthma in Italy, with higher prevalence in dry-hot Mediterranean climates, and lower in rainy-cold northern climates. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the use of conceptual models for hydrological projections in northern Tunisia.

Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel

2016-01-01

Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2017-01-01

Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Dengue dynamics in Binh Thuan province, southern Vietnam: periodicity, synchronicity and climate variability.

PubMed

Thai, Khoa T D; Cazelles, Bernard; Nguyen, Nam Van; Vo, Long Thi; Boni, Maciej F; Farrar, Jeremy; Simmons, Cameron P; van Doorn, H Rogier; de Vries, Peter J

2010-07-13

Dengue is a major global public health problem with increasing incidence and geographic spread. The epidemiology is complex with long inter-epidemic intervals and endemic with seasonal fluctuations. This study was initiated to investigate dengue transmission dynamics in Binh Thuan province, southern Vietnam. Wavelet analyses were performed on time series of monthly notified dengue cases from January 1994 to June 2009 (i) to detect and quantify dengue periodicity, (ii) to describe synchrony patterns in both time and space, (iii) to investigate the spatio-temporal waves and (iv) to associate the relationship between dengue incidence and El Niño-Southern Oscillation (ENSO) indices in Binh Thuan province, southern Vietnam. We demonstrate a continuous annual mode of oscillation and a multi-annual cycle of around 2-3-years was solely observed from 1996-2001. Synchrony in time and between districts was detected for both the annual and 2-3-year cycle. Phase differences used to describe the spatio-temporal patterns suggested that the seasonal wave of infection was either synchronous among all districts or moving away from Phan Thiet district. The 2-3-year periodic wave was moving towards, rather than away from Phan Thiet district. A strong non-stationary association between ENSO indices and climate variables with dengue incidence in the 2-3-year periodic band was found. A multi-annual mode of oscillation was observed and these 2-3-year waves of infection probably started outside Binh Thuan province. Associations with climatic variables were observed with dengue incidence. Here, we have provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam.

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

PubMed Central

Houle, Daniel

2014-01-01

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

Characterization of the Sahelian-Sudan rainfall based on observations and regional climate models

NASA Astrophysics Data System (ADS)

Salih, Abubakr A. M.; Elagib, Nadir Ahmed; Tjernström, Michael; Zhang, Qiong

2018-04-01

The African Sahel region is known to be highly vulnerable to climate variability and change. We analyze rainfall in the Sahelian Sudan in terms of distribution of rain-days and amounts, and examine whether regional climate models can capture these rainfall features. Three regional models namely, Regional Model (REMO), Rossby Center Atmospheric Model (RCA) and Regional Climate Model (RegCM4), are evaluated against gridded observations (Climate Research Unit, Tropical Rainfall Measuring Mission, and ERA-interim reanalysis) and rain-gauge data from six arid and semi-arid weather stations across Sahelian Sudan over the period 1989 to 2008. Most of the observed rain-days are characterized by weak (0.1-1.0 mm/day) to moderate (> 1.0-10.0 mm/day) rainfall, with average frequencies of 18.5% and 48.0% of the total annual rain-days, respectively. Although very strong rainfall events (> 30.0 mm/day) occur rarely, they account for a large fraction of the total annual rainfall (28-42% across the stations). The performance of the models varies both spatially and temporally. RegCM4 most closely reproduces the observed annual rainfall cycle, especially for the more arid locations, but all of the three models fail to capture the strong rainfall events and hence underestimate its contribution to the total annual number of rain-days and rainfall amount. However, excessive moderate rainfall compensates this underestimation in the models in an annual average sense. The present study uncovers some of the models' limitations in skillfully reproducing the observed climate over dry regions, will aid model users in recognizing the uncertainties in the model output and will help climate and hydrological modeling communities in improving models.

Climate, water use, and land surface transformation in an irrigation intensive watershed - streamflow responses from 1950 through 2010

USGS Publications Warehouse

Dale, Joseph; Zou, Chris B.; Andrews, William J.; Long, James M.; Liang, Ye; Qiao, Lei

2015-01-01

Climatic variability and land surface change have a wide range of effects on streamflow and are often difficult to separate. We analyzed long-term records of climate, land use and land cover, and re-constructed the water budget based on precipitation, groundwater levels, and water use from 1950 through 2010 in the Cimarron–Skeleton watershed and a portion of the Cimarron–Eagle Chief watershed in Oklahoma, an irrigation-intensive agricultural watershed in the Southern Great Plains, USA. Our results show that intensive irrigation through alluvial aquifer withdrawal modifies climatic feedback and alters streamflow response to precipitation. Increase in consumptive water use was associated with decreases in annual streamflow, while returning croplands to non-irrigated grasslands was associated with increases in streamflow. Along with groundwater withdrawal, anthropogenic-induced factors and activities contributed nearly half to the observed variability of annual streamflow. Streamflow was more responsive to precipitation during the period of intensive irrigation between 1965 and 1984 than the period of relatively lower water use between 1985 and 2010. The Cimarron River is transitioning from a historically flashy river to one that is more stable with a lower frequency of both high and low flow pulses, a higher baseflow, and an increased median flow due in part to the return of cropland to grassland. These results demonstrated the interrelationship among climate, land use, groundwater withdrawal and streamflow regime and the potential to design agricultural production systems and adjust irrigation to mitigate impact of increasing climate variability on streamflow in irrigation intensive agricultural watershed.

Evaluating the response of Lake Prespa (SW Balkan) to future climate change projections from a high-resolution model

NASA Astrophysics Data System (ADS)

van der Schriek, Tim; Varotsos, Konstantinos V.; Giannakopoulos, Christos

2017-04-01

The Mediterranean stands out globally due to its sensitivity to (future) climate change. Projections suggest that the Balkans will experience precipitation and runoff decreases of up to 30% by 2100. However, these projections show large regional spatial variability. Mediterranean lake-wetland systems are particularly threatened by projected climate changes that compound increasingly intensive human impacts (e.g. water extraction, drainage, pollution and dam-building). Protecting the remaining systems is extremely important for supporting global biodiversity. This protection should be based on a clear understanding of individual lake-wetland hydrological responses to future climate changes, which requires fine-resolution projections and a good understanding of the impact of hydro-climate variability on individual lakes. Climate change may directly affect lake level (variability), volume and water temperatures. In turn, these variables influence lake-ecology, habitats and water quality. Land-use intensification and water abstraction multiply these climate-driven changes. To date, there are no projections of future water level and -temperature of individual Mediterranean lakes under future climate scenarios. These are, however, of crucial importance to steer preservation strategies on the relevant catchment-scale. Here we present the first projections of water level and -temperature of the Prespa Lakes covering the period 2071-2100. These lakes are of global significance for biodiversity, and of great regional socio-economic importance as a water resource and tourist attraction. Impact projections are assessed by the Regional Climate Model RCA4 of the Swedish Meteorological and Hydrological Institute (SMHI) driven by the Max Planck Institute for Meteorology global climate model MPI-ESM-LR under two RCP future emissions scenarios, the RCP4.5 and the RCP8.5, with the simulations carried out in the framework of EURO-CORDEX. Temperature, evapo(transpi)ration and precipitation over the Prespa catchment were simulated with this high horizontal resolution (12 × 12 km) regional climate model. Lake temperatures were derived from surface temperatures based on physical models, while water levels were calculated with the lake water balance model. Climate simulations indicate that annual- and wet season catchment precipitation does not significantly change by the end of the century. The median precipitation decreases, while precipitation variability increases. The percentage of annual precipitation falling in the wet season increases by 5-10%, indicating a stronger seasonality in the precipitation regime. Summer (lake) temperatures and lake surface evaporation will rise significantly under both explored climate change scenarios. Lake impact projections indicate that evaporation changes will cause the water level of Lake Megali Prespa to fall by 5m to 840-839m. The increased precipitation variability will cause large inter-annual water level fluctuations. Average water level may fall even further if: (1) drier summers lead to more water abstraction for irrigation, and (2) there is a reduction in winter snowfall/accumulation and thus less discharge. These findings are of key importance for developing sustainable lake water resource management in a region that is highly vulnerable to future climate change and already experiences significant water stress. Research paves the way for innovative management adaptation strategies focussed on decreasing water abstraction, for example through introducing smart irrigation and selecting more water efficient crops.

Long-term patterns of air temperatures, daily temperature range, precipitation, grass-reference evapotranspiration and aridity index in the USA Great Plains: Part I. Spatial trends

NASA Astrophysics Data System (ADS)

Kukal, M.; Irmak, S.

2016-11-01

Due to their substantial spatio-temporal behavior, long-term quantification and analyses of important hydrological variables are essential for practical applications in water resources planning, evaluating the water use of agricultural crop production and quantifying crop evapotranspiration patterns and irrigation management vs. hydrologic balance relationships. Observed data at over 800 sites across the Great Plains of USA, comprising of 9 states and 2,307,410 km2 of surface area, which is about 30% of the terrestrial area of the USA, were used to quantify and map large-scale and long-term (1968-2013) spatial trends of air temperatures, daily temperature range (DTR), precipitation, grass-reference evapotranspiration (ETo) and aridity index (AI) at monthly, growing season and annual time steps. Air temperatures had a strong north to south increasing trend, with annual average varying from -1 to 24 °C, and growing season average temperature varying from 8 to 30 °C. DTR gradually decreased from western to eastern parts of the region, with a regional annual and growing season averages of 14.25 °C and 14.79 °C, respectively. Precipitation had a gradual shift towards higher magnitudes from west to east, with the average annual and growing season (May-September) precipitation ranging from 163 to 1486 mm and from 98 to 746 mm, respectively. ETo had a southwest-northeast decreasing trend, with regional annual and growing season averages of 1297 mm and 823 mm, respectively. AI increased from west to east, indicating higher humidity (less arid) towards the east, with regional annual and growing season averages of 0.49 and 0.44, respectively. The spatial datasets and maps for these important climate variables can serve as valuable background for climate change and hydrologic studies in the Great Plains region. Through identification of priority areas from the developed maps, efforts of the concerned personnel and agencies and resources can be diverted towards development of holistic strategies to address water supply and demand challenges under changing climate. These strategies can consist of, but not limited to, advancing water, crop and soil management, and genetic improvements and their relationships with the climatic variables on large scales.

Moderate climate signature in cranial anatomy of late holocene human populations from Southern South America.

PubMed

Paula Menéndez, Lumila

2018-02-01

The aim of this study is to analyze the association between cranial variation and climate in order to discuss their role during the diversification of southern South American populations. Therefore, the specific objectives are: (1) to explore the spatial pattern of cranial variation with regard to the climatic diversity of the region, and (2) to evaluate the differential impact that the climatic factors may have had on the shape and size of the diverse cranial structures studied. The variation in shape and size of 361 crania was studied, registering 62 3D landmarks that capture shape and size variation in the face, cranial vault, and base. Mean, minimum, and maximum annual temperature, as well as mean annual precipitation, but also diet and altitude, were matched for each population sample. A PCA, as well as spatial statistical techniques, including kriging, regression, and multimodel inference were employed. The facial skeleton size presents a latitudinal pattern which is partially associated with temperature diversity. Both diet and altitude are the variables that mainly explain the skull shape variation, although mean annual temperature also plays a role. The association between climate factors and cranial variation is low to moderate, mean annual temperature explains almost 40% of the entire skull, facial skeleton and cranial vault shape variation, while annual precipitation and minimum annual temperature only contribute to the morphological variation when considered together with maximum annual temperature. The cranial base is the structure less associated with climate diversity. These results suggest that climate factors may have had a partial impact on the facial and vault shape, and therefore contributed moderately to the diversification of southern South American populations, while diet and altitude might have had a stronger impact. Therefore, cranial variation at the southern cone has been shaped both by random and nonrandom factors. Particularly, the influence of climate on skull shape has probably been the result of directional selection. This study supports that, although cranial vault is the cranial structure more associated to mean annual temperature, the impact of climate signature on morphology decreases when populations from extreme cold environments are excluded from the analysis. Additionally, it shows that the extent of the geographical scales analyzed, as well as differential sampling may lead to different results regarding the role of ecological factors and evolutionary processes on cranial morphology. © 2017 Wiley Periodicals, Inc.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Climate, soil water storage, and the average annual water balance

USGS Publications Warehouse

Milly, P.C.D.

1994-01-01

This paper describes the development and testing of the hypothesis that the long-term water balance is determined only by the local interaction of fluctuating water supply (precipitation) and demand (potential evapotranspiration), mediated by water storage in the soil. Adoption of this hypothesis, together with idealized representations of relevant input variabilities in time and space, yields a simple model of the water balance of a finite area having a uniform climate. The partitioning of average annual precipitation into evapotranspiration and runoff depends on seven dimensionless numbers: the ratio of average annual potential evapotranspiration to average annual precipitation (index of dryness); the ratio of the spatial average plant-available water-holding capacity of the soil to the annual average precipitation amount; the mean number of precipitation events per year; the shape parameter of the gamma distribution describing spatial variability of storage capacity; and simple measures of the seasonality of mean precipitation intensity, storm arrival rate, and potential evapotranspiration. The hypothesis is tested in an application of the model to the United States east of the Rocky Mountains, with no calibration. Study area averages of runoff and evapotranspiration, based on observations, are 263 mm and 728 mm, respectively; the model yields corresponding estimates of 250 mm and 741 mm, respectively, and explains 88% of the geographical variance of observed runoff within the study region. The differences between modeled and observed runoff can be explained by uncertainties in the model inputs and in the observed runoff. In the humid (index of dryness <1) parts of the study area, the dominant factor producing runoff is the excess of annual precipitation over annual potential evapotranspiration, but runoff caused by variability of supply and demand over time is also significant; in the arid (index of dryness >1) parts, all of the runoff is caused by variability of forcing over time. Contributions to model runoff attributable to small-scale spatial variability of storage capacity are insignificant throughout the study area. The consistency of the model with observational data is supportive of the supply-demand-storage hypothesis, which neglects infiltration excess runoff and other finite-permeability effects on the soil water balance.

Detecting climatically driven phylogenetic and morphological divergence among spruce (Picea) species worldwide

NASA Astrophysics Data System (ADS)

Wang, Guo-Hong; Li, He; Zhao, Hai-Wei; Zhang, Wei-Kang

2017-05-01

This study aimed to elucidate the relationship between climate and the phylogenetic and morphological divergence of spruces (Picea) worldwide. Climatic and georeferenced data were collected from a total of 3388 sites distributed within the global domain of spruce species. A phylogenetic tree and a morphological tree for the global spruces were reconstructed based on DNA sequences and morphological characteristics. Spatial evolutionary and ecological vicariance analysis (SEEVA) was used to detect the ecological divergence among spruces. A divergence index (D) with (0, 1) scaling was calculated for each climatic factor at each node for both trees. The annual mean values, extreme values and annual range of the climatic variables were among the major determinants for spruce divergence. The ecological divergence was significant (P < 0. 001) for 185 of the 279 comparisons at 31 nodes in the phylogenetic tree, as well as for 196 of the 288 comparisons at 32 nodes in the morphological tree. Temperature parameters and precipitation parameters tended to be the main driving factors for the primary divergences of spruce phylogeny and morphology, respectively. Generally, the maximum D of the climatic variables was smaller in the basal nodes than in the remaining nodes. Notably, the primary divergence of morphology and phylogeny among the investigated spruces tended to be driven by different selective pressures. Given the climate scenario of severe and widespread drought over land areas in the next 30-90 years, our findings shed light on the prediction of spruce distribution under future climate change.

Analysis of monthly, winter, and annual temperatures in Zagreb, Croatia, from 1864 to 2010: the 7.7-year cycle and the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Sen, Asok K.; Ogrin, Darko

2016-02-01

Long instrumental records of meteorological variables such as temperature and precipitation are very useful for studying regional climate in the past, present, and future. They can also be useful for understanding the influence of large-scale atmospheric circulation processes on the regional climate. This paper investigates the monthly, winter, and annual temperature time series obtained from the instrumental records in Zagreb, Croatia, for the period 1864-2010. Using wavelet analysis, the dominant modes of variability in these temperature series are identified, and the time intervals over which these modes may persist are delineated. The results reveal that all three temperature records exhibit low-frequency variability with a dominant periodicity at around 7.7 years. The 7.7-year cycle has also been observed in the temperature data recorded at several other stations in Europe, especially in Northern and Western Europe, and may be linked to the North Atlantic Oscillation (NAO) and/or solar/geomagnetic activity.

Evapotranspiration of annual and perennial biofuel crops in a variable climate

DOE PAGES

Abraha, Michael; Chen, Jiquan; Chu, Housen; ...

2015-02-06

Eddy covariance measurements were made in seven fields in the Midwest USA over 4 years (including the 2012 drought year) to estimate evapotranspiration (ET) of newly established rain-fed cellulosic and grain biofuel crops. Four of the converted fields had been managed as grasslands under the USDA’s Conservation Reserve Program (CRP) for 22 years, and three had been in conventional agriculture (AGR) soybean/corn rotation prior to conversion. In 2009, all sites were planted to no-till soybean except one CRP grassland that was left unchanged as a reference site; in 2010, three of the former CRP sites and the three former AGRmore » sites were planted to annual (corn) and perennial (switchgrass and mixed-prairie) grasslands. The annual ET over the 4 years ranged from 45% to 77% (mean = 60%) of the annual precipitation (848–1063 mm; November–October), with the unconverted CRP grassland having the highest ET (622–706 mm). In the fields converted to annual and perennial crops, the annual ET ranged between 480 and 639 mm despite the large variations in growing-season precipitation and in soil water contents, which had strong effects on regional crop yields. Results suggest that in this humid temperate climate, which represents the US Corn Belt, water use by annual and perennial crops is not greatly different across years with highly variable precipitation and soil water availability. Thus, large-scale conversion of row crops to perennial biofuel cropping systems may not strongly alter terrestrial water balances.« less

Evapotranspiration of annual and perennial biofuel crops in a variable climate

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

Abraha, Michael; Chen, Jiquan; Chu, Housen

Eddy covariance measurements were made in seven fields in the Midwest USA over 4 years (including the 2012 drought year) to estimate evapotranspiration (ET) of newly established rain-fed cellulosic and grain biofuel crops. Four of the converted fields had been managed as grasslands under the USDA’s Conservation Reserve Program (CRP) for 22 years, and three had been in conventional agriculture (AGR) soybean/corn rotation prior to conversion. In 2009, all sites were planted to no-till soybean except one CRP grassland that was left unchanged as a reference site; in 2010, three of the former CRP sites and the three former AGRmore » sites were planted to annual (corn) and perennial (switchgrass and mixed-prairie) grasslands. The annual ET over the 4 years ranged from 45% to 77% (mean = 60%) of the annual precipitation (848–1063 mm; November–October), with the unconverted CRP grassland having the highest ET (622–706 mm). In the fields converted to annual and perennial crops, the annual ET ranged between 480 and 639 mm despite the large variations in growing-season precipitation and in soil water contents, which had strong effects on regional crop yields. Results suggest that in this humid temperate climate, which represents the US Corn Belt, water use by annual and perennial crops is not greatly different across years with highly variable precipitation and soil water availability. Thus, large-scale conversion of row crops to perennial biofuel cropping systems may not strongly alter terrestrial water balances.« less

Actual evapotranspiration for a reference crop within measured and future changing climate periods in the Mediterranean region

NASA Astrophysics Data System (ADS)

Katerji, Nader; Rana, Gianfranco; Ferrara, Rossana Monica

2017-08-01

The study compares two formulas for calculating the daily evapotranspiration ET0 for a reference crop. The first formula was proposed by Allen et al. (AL), while the second one was proposed by Katerji and Perrier with the addition of the carbon dioxide (CO2) effect on evapotranspiration (KP). The study analyses the impact of the calculation by the two formulas on the irrigation requirement (IR). Both formulas are based on the Penman-Monteith equation but adopt different approaches for parameterising the canopy resistance r c . In the AL formula, r c is assumed constant and not sensitive to climate change, whereas in the KP formula, r c is first parameterised as a function of climatic variables, then ET0 is corrected for the air CO2 concentration. The two formulas were compared in two periods. The first period involves data from two sites in the Mediterranean region within a measured climate change period (1981-2006) when all the input climatic variables were measured. The second period (2070-2100) involves data from a future climate change period at one site when the input climatic variables were forecasted for two future climate scenarios (A2 and B2). The annual cumulated values of ET0 calculated by the AL formula are systematically lower than those determined by the KP formula. The differences between the ET0 estimation with the AL and KP formulas have a strong impact on the determination of the IR for the reference crop. In fact, for the two periods, the annual values of IR when ET0 is calculated by the AL formula are systematically lower than those calculated by the KP formula. For the actual measured climate change period, this reduction varied from 26 to 28 %, while for the future climate change period, it varied based on the scenario from 16 % (A2) to 20 % (B2).

Effect of inter- and intra-annual thermohaline variability on acoustic propagation

NASA Astrophysics Data System (ADS)

Chu, Peter C.; McDonald, Colleen M.; Kucukosmanoglu, Murat; Judono, Albert; Margolina, Tetyana; Fan, Chenwu

2017-05-01

This paper is to answer the question "How can inter- and intra-annual variability in the ocean be leveraged by the submarine Force?" through quantifying inter- and intra-annual variability in (T, S) fields and in turn underwater acoustic characteristics such as transmission loss, signal excess, and range of detection. The Navy's Generalized Digital Environmental Model (GDEM) is the climatological monthly mean data and represents mean annual variability. An optimal spectral decomposition method is used to produce a synoptic monthly gridded (SMG) (T, S) dataset for the world oceans with 1° ×1° horizontal resolution, 28 vertical levels (surface to 3,000 m depth), monthly time increment from January 1945 to December 2014 now available at the NOAA/NCEI website: http://data.nodc.noaa.gov/cgibin/iso?id=gov.noaa.nodc:0140938. The sound velocity decreases from 1945 to 1975 and increases afterwards due to global climate change. Effect of the inter- and intra-annual (T, S) variability on acoustic propagation in the Yellow Sea is investigated using a well-developed acoustic model (Bellhop) in frequencies from 3.5 kHz to 5 kHz with sound velocity profile (SVP) calculated from GDEM and SMG datasets, various bottom types (silty clay, fine sand, gravelly mud, sandy mud, and cobble or gravel) from the NAVOCEANO`s High Frequency Environmental Algorithms (HFEVA), source and receiver depths. Acoustic propagation ranges are extended drastically due to the inter-annual variability in comparison with the climatological SVP (from GDEM). Submarines' vulnerability of detection as its depth varies and avoidance of short acoustic range due to inter-annual variability are also discussed.

Seasonal and spatial variation in broadleaf forest model parameters

NASA Astrophysics Data System (ADS)

Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.

2009-04-01

Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and vapour pressure deficit.

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

NASA Astrophysics Data System (ADS)

Delpierre, N.; Dufrêne, E.

2009-04-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

[Predictions of potential geographical distribution of Alhagi sparsifolia under climate change].

PubMed

Yang, Xia; Zheng, Jiang-Hua; Mu, Chen; Lin, Jun

2017-02-01

Specific information on geographic distribution of a species is important for its conservation. This study was conducted to determine the potential geographic distribution of Alhagi sparsifolia, which is a plant used in traditional Uighur medicine, and predict how climate change would affect its geographic range. The potential geographic distribution of A. sparsifolia under the current conditions in China was simulated with MaxEnt software based on species presence data at 42 locations and 19 climatic variables. The future distributions of A. sparsifolia were also projected in 2050 and 2070 under the climate change scenarios of RCP2.6 and RCP8.5 described in 5th Assessment Report of the Intergovernmental Panel on Climate Change (IPCC).The result showed that mean temperature of the coldest quarter, annual mean temperature, precipitation of the coldest quarter, annual precipitation, precipitation of the wettest month, mean temperature of the wettest quarter and the temperature annual range were the seven climatic factors influencing the geographic distribution of A. sparsifolia under current climate, the suitable habitats are mainly located in the Xinjiang, in the middle and north of Gansu, in the west of Neimeng, in the north of Nei Monggol. From 2050 to 2070, the model simulations indicated that the suitable habitats of A. sparsifolia would decrease under the climate change scenarios of RCP2.6 and scenarios of RCP8.5 on the whole. Copyright© by the Chinese Pharmaceutical Association.

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

PubMed

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

2016-01-01

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

Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

DOE PAGES

Harp, Dylan R.; Atchley, Adam L.; Painter, Scott L.; ...

2016-02-11

Here, the effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21more » $$^{st}$$ century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.« less

Effect of soil property uncertainties on permafrost thaw projections: A calibration-constrained analysis

DOE PAGES

Harp, D. R.; Atchley, A. L.; Painter, S. L.; ...

2015-06-29

The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows formore » the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. As a result, by comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.« less

Effect of soil property uncertainties on permafrost thaw projections: a calibration-constrained analysis

NASA Astrophysics Data System (ADS)

Harp, D. R.; Atchley, A. L.; Painter, S. L.; Coon, E. T.; Wilson, C. J.; Romanovsky, V. E.; Rowland, J. C.

2015-06-01

The effect of soil property uncertainties on permafrost thaw projections are studied using a three-phase subsurface thermal hydrology model and calibration-constrained uncertainty analysis. The Null-Space Monte Carlo method is used to identify soil hydrothermal parameter combinations that are consistent with borehole temperature measurements at the study site, the Barrow Environmental Observatory. Each parameter combination is then used in a forward projection of permafrost conditions for the 21st century (from calendar year 2006 to 2100) using atmospheric forcings from the Community Earth System Model (CESM) in the Representative Concentration Pathway (RCP) 8.5 greenhouse gas concentration trajectory. A 100-year projection allows for the evaluation of intra-annual uncertainty due to soil properties and the inter-annual variability due to year to year differences in CESM climate forcings. After calibrating to borehole temperature data at this well-characterized site, soil property uncertainties are still significant and result in significant intra-annual uncertainties in projected active layer thickness and annual thaw depth-duration even with a specified future climate. Intra-annual uncertainties in projected soil moisture content and Stefan number are small. A volume and time integrated Stefan number decreases significantly in the future climate, indicating that latent heat of phase change becomes more important than heat conduction in future climates. Out of 10 soil parameters, ALT, annual thaw depth-duration, and Stefan number are highly dependent on mineral soil porosity, while annual mean liquid saturation of the active layer is highly dependent on the mineral soil residual saturation and moderately dependent on peat residual saturation. By comparing the ensemble statistics to the spread of projected permafrost metrics using different climate models, we show that the effect of calibration-constrained uncertainty in soil properties, although significant, is less than that produced by structural climate model uncertainty for this location.

How to make a tree ring: Coupling stem water flow and cambial activity in mature Alpine conifers

NASA Astrophysics Data System (ADS)

Peters, Richard L.; Frank, David C.; Treydte, Kerstin; Steppe, Kathy; Kahmen, Ansgar; Fonti, Patrick

2017-04-01

Inter-annual tree-ring measurements are used to understand tree-growth responses to climatic variability and reconstruct past climate conditions. In parallel, mechanistic models use experimentally defined plant-atmosphere interactions to explain past growth responses and predict future environmental impact on forest productivity. Yet, substantial inconsistencies within mechanistic model ensembles and mismatches with empirical data indicate that significant progress is still needed to understand the processes occurring at an intra-annual resolution that drive annual growth. However, challenges arise due to i) few datasets describing climatic responses of high-resolution physiological processes over longer time-scales, ii) uncertainties on the main mechanistic process limiting radial stem growth and iii) complex interactions between multiple environmental factors which obscure detection of the main stem growth driver, generating a gap between our understanding of intra- and inter-annual growth mechanisms. We attempt to bridge the gap between inter-annual tree-ring width and sub-daily radial stem-growth and provide a mechanistic perspective on how environmental conditions affect physiological processes that shape tree rings in conifers. We combine sub-hourly sap flow and point dendrometer measurements performed on mature Alpine conifers (Larix decidua) into an individual-based mechanistic tree-growth model to simulate sub-hourly cambial activity. The monitored trees are located along a high elevational transect in the Swiss Alps (Lötschental) to analyse the effect of increasing temperature. The model quantifies internal tree hydraulic pathways that regulate the turgidity within the cambial zone and induce cell enlargement for radial growth. The simulations are validated against intra-annual growth patterns derived from xylogenesis data and anatomical analyses. Our efforts advance the process-based understanding of how climate shapes the annual tree-ring structures and could potentially improve our ability to reconstruct the climate of the past and predict future growth under changing climate.

Decadal climate variability and the spatial organization of deep hydrological drought

NASA Astrophysics Data System (ADS)

Barros, Ana P.; Hodes, Jared L.; Arulraj, Malarvizhi

2017-10-01

Empirical Orthogonal Function (EOF), wavelet, and wavelet coherence analysis of baseflow time-series from 126 streamgauges (record-length > 50 years; small and mid-size watersheds) in the US South Atlantic (USSA) region reveal three principal modes of space-time variability: (1) a region-wide dominant mode tied to annual precipitation that exhibits non-stationary decadal variability after the mid 1990s concurrent with the warming of the AMO (Atlantic Multidecadal Oscillation); (2) two spatial modes, east and west of the Blue Ridge, exhibiting nonstationary seasonal to sub-decadal variability before and after 1990 attributed to complex nonlinear interactions between ENSO and AMO impacting precipitation and recharge; and (3) deep (decadal) and shallow (< 6 years) space-time modes of groundwater variability separating basins with high and low annual mean baseflow fraction (MBF) by physiographic region. The results explain the propagation of multiscale climate variability into the regional groundwater system through recharge modulated by topography, geomorphology, and geology to determine the spatial organization of baseflow variability at decadal (and longer) time-scales, that is, deep hydrologic drought. Further, these findings suggest potential for long-range predictability of hydrological drought in small and mid-size watersheds, where baseflow is a robust indicator of nonstationary yield capacity of the underlying groundwater basins. Predictive associations between climate mode indices and deep baseflow (e.g. persistent decreases of the decadal-scale components of baseflow during the cold phase of the AMO in the USSA) can be instrumental toward improving forecast lead-times and long-range mitigation of severe drought.

Modeling physical and chemical climate of the northeastern United States for a geographic information system

Treesearch

Scott V. Ollinger; John D. Aber; Anthony C. Federer; Gary M. Lovett; Jennifer M. Ellis

1995-01-01

A model of physical and chemical climate was developed for New York and New England that can be used in a GIs for integration with ecosystem models. The variables included are monthly average maximum and minimum daily temperatures, precipitation, humidity, and solar radiation, as well as annual atmospheric deposition of sulfur and nitrogen. Equations generated from...

Quantifying the intra-annual uncertainties in climate change assessment over 10 sub-basins across the Pacific Northwest US

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2017-04-01

Uncertainty is an inevitable feature of climate change impact assessments. Understanding and quantifying different sources of uncertainty is of high importance, which can help modeling agencies improve the current models and scenarios. In this study, we have assessed the future changes in three climate variables (i.e. precipitation, maximum temperature, and minimum temperature) over 10 sub-basins across the Pacific Northwest US. To conduct the study, 10 statistically downscaled CMIP5 GCMs from two downscaling methods (i.e. BCSD and MACA) were utilized at 1/16 degree spatial resolution for the historical period of 1970-2000 and future period of 2010-2099. For the future projections, two future scenarios of RCP4.5 and RCP8.5 were used. Furthermore, Bayesian Model Averaging (BMA) was employed to develop a probabilistic future projection for each climate variable. Results indicate superiority of BMA simulations compared to individual models. Increasing temperature and precipitation are projected at annual timescale. However, the changes are not uniform among different seasons. Model uncertainty shows to be the major source of uncertainty, while downscaling uncertainty significantly contributes to the total uncertainty, especially in summer.

Masting in ponderosa pine: comparisons of pollen and seed over space and time.

PubMed

Mooney, Kailen A; Linhart, Yan B; Snyder, Marc A

2011-03-01

Many plant species exhibit variable and synchronized reproduction, or masting, but less is known of the spatial scale of synchrony, effects of climate, or differences between patterns of pollen and seed production. We monitored pollen and seed cone production for seven Pinus ponderosa populations (607 trees) separated by up to 28 km and 1,350 m in elevation in Boulder County, Colorado, USA for periods of 4-31 years for a mean per site of 8.7 years for pollen and 12.1 for seed cone production. We also analyzed climate data and a published dataset on 21 years of seed production for an eighth population (Manitou) 100 km away. Individual trees showed high inter-annual variation in reproduction. Synchrony was high within populations, but quickly became asynchronous among populations with a combination of increasing distance and elevational difference. Inter-annual variation in temperature and precipitation had differing influences on seed production for Boulder County and Manitou. We speculate that geographically variable effects of climate on reproduction arise from environmental heterogeneity and population genetic differentiation, which in turn result in localized synchrony. Although individual pines produce pollen and seed, only one-third of the covariation within trees was shared. As compared to seed cones, pollen had lower inter-annual variation at the level of the individual tree and was more synchronous. However, pollen and seed production were similar with respect to inter-annual variation at the population level, spatial scales of synchrony and associations with climate. Our results show that strong masting can occur at a localized scale, and that reproductive patterns can differ between pollen and seed cone production in a hermaphroditic plant.

Shallow bedrock limits groundwater seepage-based headwater climate refugia

USGS Publications Warehouse

Briggs, Martin A.; Lane, John W.; Snyder, Craig D.; White, Eric A.; Johnson, Zachary; Nelms, David L.; Hitt, Nathaniel P.

2018-01-01

Groundwater/surface-water exchanges in streams are inexorably linked to adjacent aquifer dynamics. As surface-water temperatures continue to increase with climate warming, refugia created by groundwater connectivity is expected to enable cold water fish species to survive. The shallow alluvial aquifers that source groundwater seepage to headwater streams, however, may also be sensitive to seasonal and long-term air temperature dynamics. Depth to bedrock can directly influence shallow aquifer flow and thermal sensitivity, but is typically ill-defined along the stream corridor in steep mountain catchments. We employ rapid, cost-effective passive seismic measurements to evaluate the variable thickness of the shallow colluvial and alluvial aquifer sediments along a headwater stream supporting cold water-dependent brook trout (Salvelinus fontinalis) in Shenandoah National Park, VA, USA. Using a mean depth to bedrock of 2.6 m, numerical models predicted strong sensitivity of shallow aquifer temperature to the downward propagation of surface heat. The annual temperature dynamics (annual signal amplitude attenuation and phase shift) of potential seepage sourced from the shallow modeled aquifer were compared to several years of paired observed stream and air temperature records. Annual stream water temperature patterns were found to lag local air temperature by ∼8–19 d along the stream corridor, indicating that thermal exchange between the stream and shallow groundwater is spatially variable. Locations with greater annual signal phase lag were also associated with locally increased amplitude attenuation, further suggestion of year-round buffering of channel water temperature by groundwater seepage. Numerical models of shallow groundwater temperature that incorporate regional expected climate warming trends indicate that the summer cooling capacity of this groundwater seepage will be reduced over time, and lower-elevation stream sections may no longer serve as larger-scale climate refugia for cold water fish species, even with strong groundwater discharge.

The different climatic response of pedogenic hematite and ferrimagnetic minerals: Evidence from particle-sized modern soils over the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Gao, Xinbo; Hao, Qingzhen; Wang, Luo; Oldfield, Frank; Bloemendal, Jan; Deng, Chenglong; Song, Yang; Ge, Junyi; Wu, Haibin; Xu, Bing; Li, Fengjiang; Han, Long; Fu, Yu; Guo, Zhengtang

2018-01-01

In recent years, increasing interest in loess studies has focused on qualitative and quantitative paleoclimatic reconstruction using the imperfect antiferromagnetic mineral hematite. However, the linkage between the hematite formation and climatic variables remains controversial. Here we present the results of a comprehensive investigation of the magnetic properties and statistical analysis of a suite of clay and silt fractions of modern soil samples from 179 sites across the Chinese Loess Plateau (CLP) and adjacent regions. Our objective was to clarify the relationships between modern climatic variables and pedogenic hematite, as well as pedogenic ferrimagnetic minerals. First-order reversal curve measurements were also conducted on representative particle-sized subsamples from a N-S transect to understand the differences in magnetic mineralogy between the two fractions. Our results show that pipette extraction separates the fine-grained superparamagnetic (SP) and most of the single-domain (SD) magnetic grains into the clay fraction, and that the remaining silt fraction displays the magnetic properties of coarse pseudo-single domain (PSD) or a mixture of multidomain (MD)/PSD and a few SD particles. Only the pedogenic clay fraction shows a strong correlation with climatic variables. The application of redundancy analysis helps to distinguish the climate variables controlling the formation of ferrimagnetic minerals and hematite during pedogenesis. On the CLP, pedogenic ferrimagnetic minerals are sensitive to mean annual precipitation, while pedogenic hematite formation is preferentially dependent on mean annual temperature. The confirmation of the temperature-dependent nature of hematite on the CLP provides a new possibility for quantitatively reconstructing the paleotemperature history of Chinese loess/paleosol sequences.

The Different Climatic Response of Pedogenic Hematite and Ferrimagnetic Minerals: Evidence from Particle-Sized Modern Soils over the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Gao, X.; Hao, Q.; Luo, W.; Oldfield, F.; Bloemendal, J.; Deng, C.; Song, Y.; Ge, J.; Wu, H.; Xu, B.; Li, F.; Han, L.; Fu, Y.; Guo, Z.

2017-12-01

In recent years, increasing interest in loess studies has focused on qualitative and quantitative paleoclimatic reconstruction using the imperfect antiferromagnetic mineral hematite. However, the linkage between the hematite formation and climatic variables remains controversial. Here we present the results of a comprehensive investigation of the magnetic properties and statistical analysis of a suite of clay and silt fractions of modern soil samples from 179 sites across the Chinese Loess Plateau (CLP) and adjacent regions. Our objective was to clarify the relationships between modern climatic variables and pedogenic hematite, as well as pedogenic ferrimagnetic minerals. First-order reversal curve measurements were also conducted on representative particle-sized subsamples from a N-S transect to understand the differences in magnetic mineralogy between the two fractions. Our results show that pipette extraction separates the fine-grained superparamagnetic (SP) and most of the single-domain (SD) magnetic grains into the clay fraction, and that the remaining silt fraction displays the magnetic properties of coarse pseudo-single domain (PSD) or a mixture of multidomain (MD)/PSD and a few SD particles. Only the pedogenic clay fraction shows a strong correlation with climatic variables. The application of redundancy analysis helps to distinguish the climate variables controlling the formation of ferrimagnetic minerals and hematite during pedogenesis. On the CLP, pedogenic ferrimagnetic minerals are sensitive to mean annual precipitation, while pedogenic hematite formation is preferentially dependent on mean annual temperature. The confirmation of the temperature-dependent nature of hematite on the CLP provides a new possibility for quantitatively reconstructing the paleotemperature history of Chinese loess/paleosol sequences.

Effects of afforestation on runoff and sediment load in an upland Mediterranean catchment.

PubMed

Buendia, C; Bussi, G; Tuset, J; Vericat, D; Sabater, S; Palau, A; Batalla, R J

2016-01-01

This paper assesses annual and seasonal trends in runoff and sediment load resulting from climate variability and afforestation in an upland Mediterranean basin, the Ribera Salada (NE Iberian Peninsula). We implemented a hydrological and sediment transport distributed model (TETIS) with a daily time-step, using continuous discharge and sediment transport data collected at a monitoring station during the period 2009-2013. Once calibrated and validated, the model was used to simulate the hydrosedimentary response of the basin for the period 1971-2014 using historical climate and land use data. Simulated series were further used to (i) detect sediment transport and hydrologic trends at different temporal scales (annual, seasonal); (ii) assess changes in the contribution of extreme events (i.e. low and high flows) and (ii) assess the relative effect of forest expansion and climate variability on trends observed by applying a scenario of constant land use. The non-parametric Mann-Kendall test indicated upward trends for temperature and decreasing trends (although non-significant) for precipitation. Downward trends occurred for annual runoff, and less significantly for sediment yield. Reductions in runoff were less intense when afforestation was not considered in the model, while trends in sediment yield were reversed. Results also indicated that an increase in the river's torrential behaviour may have occurred throughout the studied period, with low and high flow events gaining importance with respect to the annual contribution, although its magnitude was reduced over time. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

Weather-centric rangeland revegetation planning

USGS Publications Warehouse

Hardegree, Stuart P.; Abatzoglou, John T.; Brunson, Mark W.; Germino, Matthew; Hegewisch, Katherine C.; Moffet, Corey A.; Pilliod, David S.; Roundy, Bruce A.; Boehm, Alex R.; Meredith, Gwendwr R.

2018-01-01

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

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

PubMed

Roland, Jens; Matter, Stephen F

2013-01-01

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

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

NASA Astrophysics Data System (ADS)

Ahani, Hossien; Kherad, Mehrzad; Kousari, Mohammad Reza; van Roosmalen, Lieke; Aryanfar, Ramin; Hosseini, Seyyed Mashaallah

2013-05-01

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955-2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann-Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.

A sensitivity study of the coupled simulation of the Northeast Brazil rainfall variability

NASA Astrophysics Data System (ADS)

Misra, Vasubandhu

2007-06-01

Two long-term coupled ocean-land-atmosphere simulations with slightly different parameterization of the diagnostic shallow inversion clouds in the atmospheric general circulation model (AGCM) of the Center for Ocean-Land-Atmosphere Studies (COLA) coupled climate model are compared for their annual cycle and interannual variability of the northeast Brazil (NEB) rainfall variability. It is seen that the solar insolation affected by the changes to the shallow inversion clouds results in large scale changes to the gradients of the SST and the surface pressure. The latter in turn modulates the surface convergence and the associated Atlantic ITCZ precipitation and the NEB annual rainfall variability. In contrast, the differences in the NEB interannual rainfall variability between the two coupled simulations is attributed to their different remote ENSO forcing.

Global Water Resources Under Future Changes: Toward an Improved Estimation

NASA Astrophysics Data System (ADS)

Islam, M.; Agata, Y.; Hanasaki, N.; Kanae, S.; Oki, T.

2005-05-01

Global water resources availability in the 21st century is going to be an important concern. Despite its international recognition, however, until now there are very limited global estimates of water resources, which considered the geographical linkage between water supply and demand, defined by runoff and its passage through river network. The available studies are again insufficient due to reasons like different approaches in defining water scarcity, simply based on annual average figures without considering the inter-annual or seasonal variability, absence of the inclusion of virtual water trading, etc. In this study, global water resources under future climate change associated with several socio-economic factors were estimated varying over both temporal and spatial scale. Global runoff data was derived from several land surface models under the GSWP2 (Global Soil Wetness Project) project, which was further processed through TRIP (Total Runoff Integrated Pathways) river routing model to produce a 0.5x0.5 degree grid based figure. Water abstraction was estimated for the same spatial resolution for three sectors as domestic, industrial and agriculture. GCM outputs from CCSR and MRI were collected to predict the runoff changes. Socio-economic factors like population and GDP growth, affected mostly the demand part. Instead of simply looking at annual figures, monthly figures for both supply and demand was considered. For an average year, such a seasonal variability can affect the crop yield significantly. In other case, inter-annual variability of runoff can cause for an absolute drought condition. To account for vulnerabilities of a region to future changes, both inter-annual and seasonal effects were thus considered. At present, the study assumed the future agricultural water uses to be unchanged under climatic changes. In this connection, EPIC model is underway to use for estimating future agricultural water demand under climatic changes on a monthly basis. From the estimation of present stress level (withdrawal to resource ratio), the months between January to May was found to have the highest number of population above water stress level, while the months between June to August having lower population in stress. The regions suffering from high seasonal variability are those of Asian monsoon zone, south-central Africa and central-east part of South America. Inter-annual variability, on the other hand, is dominant mostly along the Middle-east or Sahara regions and the western part of South America and Latin America. Virtual water trading among countries was estimated on per capita basis. It shows that many Middle east countries are able to compensate their water stress significantly through virtual water trading. The overall effect of climate change on lowering of river runoff mostly affected Europe, southern part of China and Latin America. India or Central Africa have better runoff availability under changing climate, but still subject to a higher water stress because of socio-economic factors like high population growth and expected increase in rate of water uses. Decrease in population as well as saturation level of maximum water uses along most European countries, on the contrary, relaxed the pressure of lowering river runoff, causing no significant change in future stress.

Regional modelling of nitrate leaching from Swiss organic and conventional cropping systems under climate change

NASA Astrophysics Data System (ADS)

Calitri, Francesca; Necpalova, Magdalena; Lee, Juhwan; Zaccone, Claudio; Spiess, Ernst; Herrera, Juan; Six, Johan

2016-04-01

Organic cropping systems have been promoted as a sustainable alternative to minimize the environmental impacts of conventional practices. Relatively little is known about the potential to reduce NO3-N leaching through the large-scale adoption of organic practices. Moreover, the potential to mitigate NO3-N leaching and thus the N pollution under future climate change through organic farming remain unknown and highly uncertain. Here, we compared regional NO3-N leaching from organic and conventional cropping systems in Switzerland using a terrestrial biogeochemical process-based model DayCent. The objectives of this study are 1) to calibrate and evaluate the model for NO3-N leaching measured under various management practices from three experiments at two sites in Switzerland; 2) to estimate regional NO3-N leaching patterns and their spatial uncertainty in conventional and organic cropping systems (with and without cover crops) for future climate change scenario A1B; 3) to explore the sensitivity of NO3-N leaching to changes in soil and climate variables; and 4) to assess the nitrogen use efficiency for conventional and organic cropping systems with and without cover crops under climate change. The data for model calibration/evaluation were derived from field experiments conducted in Liebefeld (canton Bern) and Eschikon (canton Zürich). These experiments evaluated effects of various cover crops and N fertilizer inputs on NO3-N leaching. The preliminary results suggest that the model was able to explain 50 to 83% of the inter-annual variability in the measured soil drainage (RMSE from 12.32 to 16.89 cm y-1). The annual NO3-N leaching was also simulated satisfactory (RMSE = 3.94 to 6.38 g N m-2 y-1), although the model had difficulty to reproduce the inter-annual variability in the NO3-N leaching losses correctly (R2 = 0.11 to 0.35). Future climate datasets (2010-2099) from the 10 regional climate models (RCM) were used in the simulations. Regional NO3-N leaching predictions for conventional cropping system with a three years rotation (silage maize, potatoes and winter wheat) in Zurich and Bern cantons varied from 6.30 to 16.89 g N m-2 y-1 over a 30-years period. Further simulations and analyses will follow to provide insights into understanding of driving variables and patterns of N losses by leaching in response to changes from conventional to organic cropping systems, and climate change.

Importance of the Annual Cycles of SST and Solar Irradiance for Circulation and Rainfall: A Climate Model Simulation Study

NASA Technical Reports Server (NTRS)

Sud, Yogesh C.; Lau, William K. M.; Walker, G. K.; Mehta, V. M.

2001-01-01

Annual cycle of climate and precipitation is related to annual cycle of sunshine and sea-surface temperatures. Understanding its behavior is important for the welfare of humans worldwide. For example, failure of Asian monsoons can cause widespread famine and grave economic disaster in the subtropical regions. For centuries meteorologists have struggled to understand the importance of the summer sunshine and associated heating and the annual cycle of sea-surface temperatures (SSTs) on rainfall in the subtropics. Because the solar income is pretty steady from year to year, while SSTs depict large interannual variability as consequence of the variability of ocean dynamics, the influence of SSTs on the monsoons are better understood through observational and modeling studies whereas the relationship of annual rainfall to sunshine remains elusive. However, using NASA's state of the art climate model(s) that can generate realistic climate in a computer simulation, one can answer such questions. We asked the question: if there was no annual cycle of the sunshine (and its associated land-heating) or the SST and its associated influence on global circulation, what will happen to the annual cycle of monsoon rains? By comparing the simulation of a 4-year integration of a baseline Control case with two parallel anomaly experiments: 1) with annual mean solar and 2) with annual mean sea-surface temperatures, we were able to draw the following conclusions: (1) Tropical convergence zone and rainfall which moves with the Sun into the northern and southern hemispheres, specifically over the Indian, African, South American and Australian regions, is strongly modulated by the annual cycles of SSTs as well as solar forcings. The influence of the annual cycle of solar heating over land, however, is much stronger than the corresponding SST influence for almost all regions, particularly the subtropics; (2) The seasonal circulation patterns over the vast land-masses of the Northern Hemisphere at mid and high latitudes also get strongly influenced by the annual cycles of solar heating. The SST influence is largely limited to the oceanic regions of these latitudes; (3) The annual mode of precipitation over Amazonia has an equatorial regime revealing a maxima in the month of March associated with SST, and another maxima in the month of January associated with the solar annual cycles, respectively. The baseline simulation, which has both annual cycles, depicts both annual modes and its rainfall is virtually equal to the sum of those two modes; (4) Rainfall over Sahelian-Africa is significantly reduced (increased) in simulations lacking (invoking) solar irradiation with (without) the annual cycle. In fact, the dominant influence of solar irradiation emerges in almost all monsoonal-land regions: India, Southeast Asia, as well as Australia. The only exception is the Continental United States, where solar annual cycle shows only a relatively minor influence on the annual mode of rainfall.

Wheat yield loss attributable to heat waves, drought and water excess at the global, national and subnational scales

NASA Astrophysics Data System (ADS)

Zampieri, M.; Ceglar, A.; Dentener, F.; Toreti, A.

2017-06-01

Heat waves and drought are often considered the most damaging climatic stressors for wheat. In this study, we characterize and attribute the effects of these climate extremes on wheat yield anomalies (at global and national scales) from 1980 to 2010. Using a combination of up-to-date heat wave and drought indexes (the latter capturing both excessively dry and wet conditions), we have developed a composite indicator that is able to capture the spatio-temporal characteristics of the underlying physical processes in the different agro-climatic regions of the world. At the global level, our diagnostic explains a significant portion (more than 40%) of the inter-annual production variability. By quantifying the contribution of national yield anomalies to global fluctuations, we have found that just two concurrent yield anomalies affecting the larger producers of the world could be responsible for more than half of the global annual fluctuations. The relative importance of heat stress and drought in determining the yield anomalies depends on the region. Moreover, in contrast to common perception, water excess affects wheat production more than drought in several countries. We have also performed the same analysis at the subnational level for France, which is the largest wheat producer of the European Union, and home to a range of climatic zones. Large subnational variability of inter-annual wheat yield is mostly captured by the heat and water stress indicators, consistently with the country-level result.

The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

2015-04-01

Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012

PubMed Central

Bai, Jie; Li, Longhui

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang. PMID:28841645

The dominant role of climate change in determining changes in evapotranspiration in Xinjiang, China from 2001 to 2012.

PubMed

Yuan, Xiuliang; Bai, Jie; Li, Longhui; Kurban, Alishir; De Maeyer, Philippe

2017-01-01

The Xinjiang Uyghur Autonomous Region of China has experienced significant land cover and climate change since the beginning of the 21st century. However, a reasonable simulation of evapotranspiration (ET) and its response to environmental factors are still unclear. For this study, to simulate ET and its response to climate and land cover change in Xinjiang, China from 2001 to 2012, we used the Common Land Model (CoLM) by adding irrigation effects for cropland and modifying root distributions and the root water uptake process for shrubland. Our results indicate that mean annual ET from 2001 to 2012 was 131.22 (±21.78) mm/year and demonstrated no significant trend (p = 0.12). The model simulation also indicates that climate change was capable of explaining 99% of inter-annual ET variability; land cover change only explained 1%. Land cover change caused by the expansion of croplands increased annual ET by 1.11 mm while climate change, mainly resulting from both decreased temperature and precipitation, reduced ET by 21.90 mm. Our results imply that climate change plays a dominant role in determining changes in ET, and also highlight the need for appropriate land-use strategies for managing water sources in dryland ecosystems within Xinjiang.

Global lake evaporation accelerated by changes in surface energy allocation in a warmer climate

NASA Astrophysics Data System (ADS)

Wang, Wei; Lee, Xuhui; Xiao, Wei; Liu, Shoudong; Schultz, Natalie; Wang, Yongwei; Zhang, Mi; Zhao, Lei

2018-06-01

Lake evaporation is a sensitive indicator of the hydrological response to climate change. Variability in annual lake evaporation has been assumed to be controlled primarily by the incoming surface solar radiation. Here we report simulations with a numerical model of lake surface fluxes, with input data based on a high-emissions climate change scenario (Representative Concentration Pathway 8.5). In our simulations, the global annual lake evaporation increases by 16% by the end of the century, despite little change in incoming solar radiation at the surface. We attribute about half of this projected increase to two effects: periods of ice cover are shorter in a warmer climate and the ratio of sensible to latent heat flux decreases, thus channelling more energy into evaporation. At low latitudes, annual lake evaporation is further enhanced because the lake surface warms more slowly than the air, leading to more long-wave radiation energy available for evaporation. We suggest that an analogous change in the ratio of sensible to latent heat fluxes in the open ocean can help to explain some of the spread among climate models in terms of their sensitivity of precipitation to warming. We conclude that an accurate prediction of the energy balance at the Earth's surface is crucial for evaluating the hydrological response to climate change.

Evidence for increasingly variable Palmer Drought Severity Index in the United States since 1895.

PubMed

Rayne, Sierra; Forest, Kaya

2016-02-15

Annual and summertime trends towards increasingly variable values of the Palmer Drought Severity Index (PDSI) over a sub-decadal period (five years) were investigated within the contiguous United States between 1895 and the present. For the contiguous United States as a whole, there is a significant increasing trend in the five-year running minimum-maximum ranges for the annual PDSI (aPDSI5 yr(min|max, range)). During this time frame, the average aPDSI5 yr(min|max, range) has increased by about one full unit, indicating a substantial increase in drought variability over short time scales across the United States. The end members of the running aPDSI5 yr(min|max, range) highlight even more rapid changes in the drought index variability within the past 120 years. This increasing variability in the aPDSI5 yr(min|max, range) is driven primarily by changes taking place in the Pacific and Atlantic Ocean coastal climate regions, climate regions which collectively comprise one-third the area of the contiguous United States. Similar trends were found for the annual and summertime Palmer Hydrological Drought Index (PHDI), the Palmer Modified Drought Index (PMDI), and the Palmer Z Index (PZI). Overall, interannual drought patterns in the contiguous United States are becoming more extreme and difficult to predict, posing a challenge to agricultural and other water-resource related planning efforts. Copyright © 2015 Elsevier B.V. All rights reserved.

Integration of ENSO Signal Power Through Hydrological Processes in the Little River Watershed

NASA Astrophysics Data System (ADS)

Keener, V. W.; Jones, J. W.; Bosch, D. D.; Cho, J.

2011-12-01

The relationship of the El-Nino/Southern Oscillation (ENSO) to hydrology is typically discussed in terms of the ability to separate significantly different hydrologic variable responses versus the anomaly that has taken place. Most of the work relating ENSO trends to proxy variables had been done on precipitation records until the mid 1990s, at which point increasing numbers of studies started to focus on ENSO relationships with streamflow as well as other environmental variables. The signals in streamflow are typically complex, representing the integration of both climatic, landscape, and anthropological responses that are able to strengthen the inherent ENSO signal in chaotic regional precipitation data. There is a need to identify climate non-stationarities related to ENSO and their links to watershed-scale outcomes. For risk-management in particular, inter-annual modes of climate variability and their seasonal expression are of interest. In this study, we analyze 36 years of historical monthly streamflow data from the Little River Watershed (LWR), a coastal plain ecosystem in Georgia, in conjunction with wavelet spectral analysis and modeling via the Soil & Water Assessment Tool (SWAT). Using both spectral and physical models allows us to identify the mechanism by which the ENSO signal power in surface and simulated groundwater flow is strengthened as compared to precipitation. The clear increase in the power of the inter-annual climate signal is demonstrated by shared patterns in water budget and exceedance curves, as well as in high ENSO related energy in the 95% significant wavelet spectra for each variable and the NINO 3.4 index. In the LRW, the power of the ENSO teleconnection is increased in both the observed and simulated stream flow through the mechanisms of groundwater flow and interflow, through confinement by a geological layer, the Hawthorn Formation. This non-intuitive relationship between ENSO signal strength and streamflow could prove to be helpful for making seasonal climate predictions in a geographic area with a weaker than desirable ENSO signal, as a predictive relationship could be found between streamflow or other proxy hydro-climatic variables.

Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

NASA Astrophysics Data System (ADS)

Peel, M. C.; Srikanthan, R.; McMahon, T. A.; Karoly, D. J.

2015-04-01

Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), mean annual temperature (MAT), mean annual runoff (MAR), the standard deviation of annual precipitation (SDP), standard deviation of runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 worldwide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainties from the 17 catchments and 5 GCMs for 2015-2044 (A1B) were MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould-Dincer Gamma (G-DG) procedure was applied to each annual runoff time series for hypothetical reservoir capacities of 1 × MAR and 3 × MAR and the average uncertainties in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were 25.1% (1 × MAR) and 11.9% (3 × MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1 × MAR or 3 × MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable - these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

On Budyko curve as a consequence of climate-soil-vegetation equilibrium hypothesis

NASA Astrophysics Data System (ADS)

Pande, S.

2012-04-01

A hypothesis that Budyko curve is a consequence of stable equilibriums of climate-soil-vegetation co-evolution is tested at biome scale. We assume that i) distribution of vegetation, soil and climate within a biome is a distribution of equilibriums of similar soil-vegetation dynamics and that this dynamics is different across different biomes and ii) soil and vegetation are in dynamic equilibrium with climate while in static equilibrium with each other. In order to test the hypothesis, a two stage regression is considered using MOPEX/Hydrologic Synthesis Project dataset for basins in eastern United States. In the first stage, multivariate regression (Seemingly Unrelated Regression) is performed for each biome with soil (estimated porosity and slope of soil water retention curve) and vegetation characteristics (5-week NDVI gradient) as dependent variables and aridity index, vegetation and soil characteristics as independent variables for respective dependent variables. The regression residuals of the first stage along with aridity index then serve as second stage independent variables while actual vaporization to precipitation ratio (vapor index) serving as dependent variable. Insignificance, if revealed, of a first stage parameter allows us to reject the role of corresponding soil or vegetation characteristics in the co-evolution hypothesis. Meanwhile the significance of second stage regression parameter corresponding to a first stage residual allow us to reject the hypothesis that Budyko curve is a locus "solely" of climate-soil-vegetation co-evolution equilibrium points. Results suggest lack of evidence for soil-vegetation co-evolution in Prairies and Mixed/SouthEast Forests (unlike in Deciduous Forests) though climate plays a dominant role in explaining within biome soil and vegetation characteristics across all the biomes. Preliminary results indicate absence of effects beyond climate-soil-vegetation co-evolution in explaining the ratio of annual total minimum monthly flows to precipitation in Deciduous Forests though other three biome types show presence of effects beyond co-evolutionary. Such an analysis can yield insights into the nature of hydrologic change when assessed along the Budyko curve as well as non co-evolutionary effects such as anthropogenic effects on basin scale annual water balances.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Climatic and biotic controls on annual carbon storage in Amazonian ecosystems

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, A.D.; Helfrich, J.; Moore, B.; Vorosmarty, C.J.

2000-01-01

1 The role of undisturbed tropical land ecosystems in the global carbon budget is not well understood. It has been suggested that inter-annual climate variability can affect the capacity of these ecosystems to store carbon in the short term. In this paper, we use a transient version of the Terrestrial Ecosystem Model (TEM) to estimate annual carbon storage in undisturbed Amazonian ecosystems during the period 1980-94, and to understand the underlying causes of the year-to-year variations in net carbon storage for this region. 2 We estimate that the total carbon storage in the undisturbed ecosystems of the Amazon Basin in 1980 was 127.6 Pg C, with about 94.3 Pg C in vegetation and 33.3 Pg C in the reactive pool of soil organic carbon. About 83% of the total carbon storage occurred in tropical evergreen forests. Based on our model's results, we estimate that, over the past 15 years, the total carbon storage has increased by 3.1 Pg C (+ 2%), with a 1.9-Pg C (+2%) increase in vegetation carbon and a 1.2-Pg C (+4%) increase in reactive soil organic carbon. The modelled results indicate that the largest relative changes in net carbon storage have occurred in tropical deciduous forests, but that the largest absolute changes in net carbon storage have occurred in the moist and wet forests of the Basin. 3 Our results show that the strength of interannual variations in net carbon storage of undisturbed ecosystems in the Amazon Basin varies from a carbon source of 0.2 Pg C/year to a carbon sink of 0.7 Pg C/year. Precipitation, especially the amount received during the drier months, appears to be a major controller of annual net carbon storage in the Amazon Basin. Our analysis indicates further that changes in precipitation combine with changes in temperature to affect net carbon storage through influencing soil moisture and nutrient availability. 4 On average, our results suggest that the undisturbed Amazonian ecosystems accumulated 0.2 Pg C/year as a result of climate variability and increasing atmospheric CO2 over the study period. This amount is large enough to have compensated for most of the carbon losses associated with tropical deforestation in the Amazon during the same period. 5 Comparisons with empirical data indicate that climate variability and CO2 fertilization explain most of the variation in net carbon storage for the undisturbed ecosystems. Our analyses suggest that assessment of the regional carbon budget in the tropics should be made over at least one cycle of El Nino-Southern Oscillation because of inter-annual climate variability. Our analyses also suggest that proper scaling of the site-specific and sub-annual measurements of carbon fluxes to produce Basin-wide flux estimates must take into account seasonal and spatial variations in net carbon storage.

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

DOE PAGES

Boer, George J.; Smith, Douglas M.; Cassou, Christophe; ...

2016-01-01

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

Inter-annual Variability of Snowfall in the Lower Peninsula of Michigan, USA

NASA Astrophysics Data System (ADS)

Meng, L.

2016-12-01

Winter snowfall, particularly lake-effect snowfall, impacts all aspects of Michigan life in the wintertime, from motorsports and tourism to impacting the day-to-day lives of residents. Understanding the inter-annual variability of winter snowfall will provide sound basis for local community safety management and improve weather forecasting. This study attempts to understand the trend in winter snowfall and the influencing factors of winter snowfall variability in the Lower Peninsula of Michigan (LPM) using station snowfall measurements and statistical analysis. Our study demonstrates that snowfall has significantly increased from 1932 to 2015. Correlation analysis suggests that regionally average air temperatures have a strong negative relationship with snowfall in LPM. On average, approximately 27% of inter-annual variability in snowfall can be explained by regionally average air temperatures. ENSO events are also negatively related to snowfall in LPM and can explain 8% of inter-annual variability. North Atlantic Oscillation (NAO) does not have strong influence on snowfall. Composite analysis demonstrates that on annual basis, more winter snowfall occurs during the years with higher maximum ice cover (MIC) than during the years with lower MIC in Lake Michigan. Higher MIC is often associated with lower air temperatures which are negatively related to winter snowfall. This study could provide insight on future snow related climate model improvement and weather forecasting.

Climate change impacts on rainfall and temperature in sugarcane growing Upper Gangetic Plains of India

NASA Astrophysics Data System (ADS)

Verma, Ram Ratan; Srivastava, Tapendra Kumar; Singh, Pushpa

2018-01-01

Assessment of variability in climate extremes is crucial for managing their aftermath on crops. Sugarcane (Saccharum officinarum L.), a major C4 crop, dominates the Upper Gangetic Plain (UGP) in India and is vulnerable to both direct and indirect effects of changes in temperature and rainfall. The present study was taken up to assess the weekly, monthly, seasonal, and annual trends of rainfall and temperature variability during the period 1956-2015 (60 years) for envisaging the probabilities of different levels of rainfall suitable for sugarcane in UGP in the present climate scenario. The analysis revealed that 87% of total annual rainfall was received during southwest monsoon months (June-September) while post-monsoon (October to February) and pre-monsoon months (March-May) accounted for only 9.4 and 3.6%, respectively. There was a decline in both monthly and annual normal rainfall during the period 1986-2015 as compared to 1956-1985, and an annual rainfall deficiency of 205.3 mm was recorded. Maximum monthly normal rainfall deficiencies of 52.8, 84.2, and 54.0 mm were recorded during the months of July, August, and September, respectively, while a minimum rainfall deficiency of 2.2 mm was observed in November. There was a decline by 196.3 mm in seasonal normal rainfall during June-September (kharif). The initial probability of a week going dry was higher (> 70%) from the 1st to the 25th week; however, standard meteorological weeks (SMW) 26 to 37 had more than 50% probability of going wet. The normal annual maximum temperature (Tmax) decreased by 0.4 °C while normal annual minimum temperatures (Tmin) increased by 0.21 °C. Analysis showed that there was an increase in frequency of drought from 1986 onwards in the zone and a monsoon rainfall deficit by about 21.25% during June-September which coincided with tillering and grand growth stage of sugarcane. The imposed drought during the growth and elongation phase is emerging as a major constraint in realizing high cane productivity in the zone. Strategies for mitigating the negative impacts of rainfall and temperature variability on sugarcane productivity through improvement in existing adaptation strategies are proposed.

A modern pollen-climate dataset from the Darjeeling area, eastern Himalaya: Assessing its potential for past climate reconstruction

NASA Astrophysics Data System (ADS)

Ghosh, Ruby; Bruch, Angela A.; Portmann, Felix; Bera, Subir; Paruya, Dipak Kumar; Morthekai, P.; Ali, Sheikh Nawaz

2017-10-01

Relying on the ability of pollen assemblages to differentiate among elevationally stratified vegetation zones, we assess the potential of a modern pollen-climate dataset from the Darjeeling area, eastern Himalaya, in past climate reconstructions. The dataset includes 73 surface samples from 25 sites collected from a c. 130-3600 m a.s.l. elevation gradient along a horizontal distance of c. 150 km and 124 terrestrial pollen taxa, which are analysed with respect to various climatic and environmental variables such as mean annual temperature (MAT), mean annual precipitation (MAP), mean temperature of coldest quarter (MTCQ), mean temperature of warmest quarter (MTWQ), mean precipitation of driest quarter (MPDQ), mean precipitation of wettest quarter (MPWQ), AET (actual evapotranspiration) and MI (moisture index). To check the reliability of the modern pollen-climate relationships different ordination methods are employed and subsequently tested with Huisman-Olff-Fresco (HOF) models. A series of pollen-climate parameter transfer functions using weighted-averaging regression and calibration partial least squares (WA-PLS) models are developed to reconstruct past climate changes from modern pollen data, and have been cross-validated. Results indicate that three of the environmental variables i.e., MTCQ, MPDQ and MI have strong potential for past climate reconstruction based on the available surface pollen dataset. The potential of the present modern pollen-climate relationship for regional quantitative paleoclimate reconstruction is further tested on a Late Quaternary fossil pollen profile from the Darjeeling foothill region with previously reconstructed and quantified climate. The good agreement with existing data allows for new insights in the hydroclimatic conditions during the Last glacial maxima (LGM) with (winter) temperature being the dominant controlling factor for glacial changes during the LGM in the eastern Himalaya.

Impacts of future climate change on river discharge based on hydrological inference: A case study of the Grand River Watershed in Ontario, Canada.

PubMed

Li, Zhong; Huang, Guohe; Wang, Xiuquan; Han, Jingcheng; Fan, Yurui

2016-04-01

Over the recent years, climate change impacts have been increasingly studied at the watershed scale. However, the impact assessment is strongly dependent upon the performance of the climatic and hydrological models. This study developed a two-step method to assess climate change impacts on water resources based on the Providing Regional Climates for Impacts Studies (PRECIS) modeling system and a Hydrological Inference Model (HIM). PRECIS runs provided future temperature and precipitation projections for the watershed under the Intergovernmental Panel on Climate Change SRES A2 and B2 emission scenarios. The HIM based on stepwise cluster analysis is developed to imitate the complex nonlinear relationships between climate input variables and targeted hydrological variables. Its robust mathematical structure and flexibility in predictor selection makes it a desirable tool for fully utilizing various climate modeling outputs. Although PRECIS and HIM cannot fully cover the uncertainties in hydro-climate modeling, they could provide efficient decision support for investigating the impacts of climate change on water resources. The proposed method is applied to the Grand River Watershed in Ontario, Canada. The model performance is demonstrated with comparison to observation data from the watershed during the period 1972-2006. Future river discharge intervals that accommodate uncertainties in hydro-climatic modeling are presented and future river discharge variations are analyzed. The results indicate that even though the total annual precipitation would not change significantly in the future, the inter-annual distribution is very likely to be altered. The water availability is expected to increase in Winter while it is very likely to decrease in Summer over the Grand River Watershed, and adaptation strategies would be necessary. Copyright © 2016 Elsevier B.V. All rights reserved.

A first approach to calculate BIOCLIM variables and climate zones for Antarctica

NASA Astrophysics Data System (ADS)

Wagner, Monika; Trutschnig, Wolfgang; Bathke, Arne C.; Ruprecht, Ulrike

2018-02-01

For testing the hypothesis that macroclimatological factors determine the occurrence, biodiversity, and species specificity of both symbiotic partners of Antarctic lecideoid lichens, we present a first approach for the computation of the full set of 19 BIOCLIM variables, as available at http://www.worldclim.org/ for all regions of the world with exception of Antarctica. Annual mean temperature (Bio 1) and annual precipitation (Bio 12) were chosen to define climate zones of the Antarctic continent and adjacent islands as required for ecological niche modeling (ENM). The zones are based on data for the years 2009-2015 which was obtained from the Antarctic Mesoscale Prediction System (AMPS) database of the Ohio State University. For both temperature and precipitation, two separate zonings were specified; temperature values were divided into 12 zones (named 1 to 12) and precipitation values into five (named A to E). By combining these two partitions, we defined climate zonings where each geographical point can be uniquely assigned to exactly one zone, which allows an immediate explicit interpretation. The soundness of the newly calculated climate zones was tested by comparison with already published data, which used only three zones defined on climate information from the literature. The newly defined climate zones result in a more precise assignment of species distribution to the single habitats. This study provides the basis for a more detailed continental-wide ENM using a comprehensive dataset of lichen specimens which are located within 21 different climate regions.

Impacts of precipitation and temperature trends on different time scales on the water cycle and water resource availability in mountainous Mediterranean catchments.

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Herrero, Javier; José Polo, María

2017-04-01

Climatology trends, precipitation and temperature variations condition the hydrological evolution of the river flow response at basin and sub-basin scales. The link between both climate and flow trends is crucial in mountainous areas, where small variations in temperature can produce significant impacts on precipitation (occurrence as rainfall or snowfall), snowmelt and evaporation, and consequently very different flow signatures. This importance is greater in semiarid regions, where the high variability of the climatic annual and seasonal regimes usually amplifies this impact on river flow. The Sierra Nevada National Park (Southern Spain), with altitudes ranging from 2000 to 3500 m.a.s.l., is part of the global climate change observatories network and a clear example of snow regions in a semiarid environment. This mountain range is head of different catchments, being the Guadalfeo River Basin one of the most influenced by the snow regime. This study shows the observed 55-year (1961-2015) trends of annual precipitation and daily mean temperature, and the associated impacts on snowfall and snow persistence, and the resulting trend of the annual river flow in the Guadalfeo River Basin (Southern Spain), a semiarid abrupt mountainous area (up to 3450 m a.s.l.) facing the Mediterranean Sea where the Alpine and Mediterranean climates coexist in a domain highly influenced by the snow regime, and a significant seasonality in the flow regime. The annual precipitation and annual daily mean temperature experimented a decreasing trend of 2.05 mm/year and an increasing trend of 0.037 °C/year, respectively, during the study period, with a high variability on a decadal basis. However, the torrential precipitation events are more frequent in the last few years of the study period, with an apparently increasing associated dispersion. The estimated annual snowfall trend shows a decreasing trend of 0.24 mm/year, associated to the decrease of precipitation rather than to temperature increase. From the analyses of river flow observations and hydrological modelling, these trends result in an estimated decreasing annual trend of the mean river inflow to reservoirs of 0.091 m3/s, which is equivalent to a mean loss of 2.87 hm3/year during the study period. Nonetheless, these results are associated to a high variability of both extreme values and the annual and decadal values. Moreover, the decrease of the annual inflow is approximately a 25% higher than the loss of precipitation, due to the impact on the different water fluxes from the snowpack associated to the enhanced torrential behaviour of both snowfall/rainfall occurrence and snow persistence. The results show the complexity of hydrological processes in Mediterranean regions, especially under the snow influence, and point out to a significant shift in the precipitation and temperature regime, and thus on the snow-affected hydrological variables in the study area, with a decrease of the available water resource volume in the medium and long term. However, on an annual basis, years with an intense snowfall regime but mild and longer dry periods result in a significant increase of the annual river flow and water storage. Reservoir operation criteria and water allocation should undergo a revision based on hydrological modelling of the snow regions and scenario analysis.

The key role of dry days in changing regional climate and precipitation regimes

USGS Publications Warehouse

Polade, Suraj; Pierce, David W.; Cayan, Daniel R.; Gershunov, Alexander; Dettinger, Michael D.

2014-01-01

Future changes in the number of dry days per year can either reinforce or counteract projected increases in daily precipitation intensity as the climate warms. We analyze climate model projected changes in the number of dry days using 28 coupled global climate models from the Coupled Model Intercomparison Project, version 5 (CMIP5). We find that the Mediterranean Sea region, parts of Central and South America, and western Indonesia could experience up to 30 more dry days per year by the end of this century. We illustrate how changes in the number of dry days and the precipitation intensity on precipitating days combine to produce changes in annual precipitation, and show that over much of the subtropics the change in number of dry days dominates the annual changes in precipitation and accounts for a large part of the change in interannual precipitation variability.

Phenological Responses to ENSO in the Global Oceans

NASA Astrophysics Data System (ADS)

Racault, M.-F.; Sathyendranath, S.; Menon, N.; Platt, T.

2017-01-01

Phenology relates to the study of timing of periodic events in the life cycle of plants or animals as influenced by environmental conditions and climatic forcing. Phenological metrics provide information essential to quantify variations in the life cycle of these organisms. The metrics also allow us to estimate the speed at which living organisms respond to environmental changes. At the surface of the oceans, microscopic plant cells, so-called phytoplankton, grow and sometimes form blooms, with concentrations reaching up to 100 million cells per litre and extending over many square kilometres. These blooms can have a huge collective impact on ocean colour, because they contain chlorophyll and other auxiliary pigments, making them visible from space. Phytoplankton populations have a high turnover rate and can respond within hours to days to environmental perturbations. This makes them ideal indicators to study the first-level biological response to environmental changes. In the Earth's climate system, the El Niño-Southern Oscillation (ENSO) dominates large-scale inter-annual variations in environmental conditions. It serves as a natural experiment to study and understand how phytoplankton in the ocean (and hence the organisms at higher trophic levels) respond to climate variability. Here, the ENSO influence on phytoplankton is estimated through variations in chlorophyll concentration, primary production and timings of initiation, peak, termination and duration of the growing period. The phenological variabilities are used to characterise phytoplankton responses to changes in some physical variables: sea surface temperature, sea surface height and wind. It is reported that in oceanic regions experiencing high annual variations in the solar cycle, such as in high latitudes, the influence of ENSO may be readily measured using annual mean anomalies of physical variables. In contrast, in oceanic regions where ENSO modulates a climate system characterised by a seasonal reversal of the wind forcing, such as the monsoon system in the Indian Ocean, phenology-based mean anomalies of physical variables help refine evaluation of the mechanisms driving the biological responses and provide a more comprehensive understanding of the integrated processes.

Rainfall effects on rare annual plants

USGS Publications Warehouse

Levine, J.M.; McEachern, A.K.; Cowan, C.

2008-01-01

Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood.We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future.Species showed 9 to 100-fold between-year variation in plant density over the 5–12 years of censusing, including a severe drought and a wet El Niño year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants.Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect.Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life table response experiments indicated that variation in germination has the same potential as the seeds produced per germinant to drive variation in population growth rates, but only the former was clearly related to rainfall.Synthesis. Our work suggests that future changes in the timing and temperatures associated with the first major rains, acting through germination, may more strongly affect population persistence than changes in season-long rainfall.

Long-term patterns of air temperatures, daily temperature range, precipitation, grass-reference evapotranspiration and aridity index in the USA great plains: Part II. Temporal trends

NASA Astrophysics Data System (ADS)

Kukal, M.; Irmak, S.

2016-11-01

Detection of long-term changes in climate variables over large spatial scales is a very important prerequisite to the development of effective mitigation and adaptation measures for the future potential climate change and for developing strategies for future hydrologic balance analyses under changing climate. Moreover, there is a need for effective approaches of providing information about these changes to decision makers, water managers and stakeholders to aid in efficient implementation of the developed strategies. This study involves computation, mapping and analyses of long-term (1968-2013) county-specific trends in annual, growing-season (1st May-30th September) and monthly air temperatures [(maximum (Tmax), minimum (Tmin) and average (Tavg)], daily temperature range (DTR), precipitation, grass reference evapotranspiration (ETo) and aridity index (AI) over the USA Great Plains region using datasets from over 800 weather station sites. Positive trends in annual Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were observed in 71%, 89%, 85%, 31%, 61%, 38% and 66% of the counties in the region, respectively, whereas these proportions were 48%, 89%, 62%, 20%, 57%, 28%, and 63%, respectively, for the growing-season averages of the same variables. On a regional average basis, the positive trends in growing-season Tavg, Tmax and Tmin, DTR, precipitation, ETo and AI were 0.18 °C decade-1, 0.19 °C decade-1, 0.17 °C decade-1, 0.09 °C decade-1, 1.12 mm yr-1, 0.4 mm yr-1 and 0.02 decade-1, respectively, and the negative trends were 0.21 °C decade-1, 0.06 °C decade-1, 0.09 °C decade-1, 0.22 °C decade-1, 1.16 mm yr-1, 0.76 mm yr-1 and 0.02 decade-1, respectively. The temporal trends were highly variable in space and were appropriately represented using monthly, annual and growing-season maps developed using Geographic Information System (GIS) techniques. The long-term and spatial and temporal information and data for a large region provided in this study can be used to analyze county-level trends in important climatic/hydrologic variables in context of climate change, water resources, agricultural and natural resources response to climate change.

Untangling Trends and Drivers of Changing River Discharge Along Florida's Gulf Coast

NASA Astrophysics Data System (ADS)

Glodzik, K.; Kaplan, D. A.; Klarenberg, G.

2017-12-01

Along the relatively undeveloped Big Bend coastline of Florida, discharge in many rivers and springs is decreasing. The causes are unclear, though they likely include a combination of groundwater extraction for water supply, climate variability, and altered land use. Saltwater intrusion from altered freshwater influence and sea level rise is causing transformative ecosystem impacts along this flat coastline, including coastal forest die-off and oyster reef collapse. A key uncertainty for understanding river discharge change is predicting discharge from rainfall, since Florida's karstic bedrock stores large amounts of groundwater, which has a long residence time. This study uses Dynamic Factor Analysis (DFA), a multivariate data reduction technique for time series, to find common trends in flow and reveal hydrologic variables affecting flow in eight Big Bend rivers since 1965. The DFA uses annual river flows as response time series, and climate data (annual rainfall and evapotranspiration by watershed) and climatic indices (El Niño Southern Oscillation [ENSO] Index and North Atlantic Oscillation [NAO] Index) as candidate explanatory variables. Significant explanatory variables (one evapotranspiration and three rainfall time series) explained roughly 50% of discharge variation across rivers. Significant trends (representing unexplained variation) were shared among rivers, with geographical grouping of five northern rivers and three southern rivers, along with a strong downward trend affecting six out of eight systems. ENSO and NAO had no significant impact. Advancing knowledge of these dynamics is necessary for forecasting how altered rainfall and temperatures from climate change may impact flows. Improved forecasting is especially important given Florida's reliance on groundwater extraction to support its growing population.

Season-specific climate signal and reconstruction from a new tree-ring network in the southwestern U.S

NASA Astrophysics Data System (ADS)

Griffin, D.; Woodhouse, C. A.; Meko, D. M.; Stahle, D. W.; Faulstich, H.; Leavitt, S. W.; Touchan, R.; Castro, C. L.; Carrillo, C.

2011-12-01

Our research group has updated existing tree-ring collections from over 50 sampling sites in the southwestern U.S. The new and archived specimens, carefully dated with dendrochronology, have been analyzed for width variations of "earlywood" and "latewood." These are the two components of annual rings in conifers that form in spring and summer, respectively. The network of primary tree-ring data has been used to develop a suite of well-replicated chronologies that extend through the 2008 growing season and are sensitive to the season-specific climate variability of the Southwest. Correlation function analysis indicates that the earlywood chronologies are closely related to cool season (October-April) precipitation variability and the chronologies derived from latewood are generally sensitive to precipitation and temperature conditions during the warm season (June-August). These proxy data originate from biological organisms and are not without bias; however, they do constitute a new means for evaluating the recent paleoclimatic history of the North American summer monsoon. The monsoon is a major component of the region's climate, impacting social and environmental systems and delivering up to 60% of the annual precipitation in the southwestern U.S. We have developed latewood-based retrodictions of monsoon precipitation that explain over half of the variance in the instrumental record, pass standard verification tests, and point to periods of persistent drought and wetness during the last 300-500 years. These reconstructions are being used to evaluate the monsoon's long-term spatiotemporal variability and its relationship to cool season climate and the major modes of ocean-atmosphere variability.

Remotely Sensed Northern Vegetation Response to Changing Climate: Growing Season and Productivity Perspective

NASA Technical Reports Server (NTRS)

Ganguly, S.; Park, Taejin; Choi, Sungho; Bi, Jian; Knyazikhin, Yuri; Myneni, Ranga

2016-01-01

Vegetation growing season and maximum photosynthetic state determine spatiotemporal variability of seasonal total gross primary productivity of vegetation. Recent warming induced impacts accelerate shifts on growing season and physiological status over Northern vegetated land. Thus, understanding and quantifying these changes are very important. Here, we first investigate how vegetation growing season and maximum photosynthesis state are evolved and how such components contribute on inter-annual variation of seasonal total gross primary productivity. Furthermore, seasonally different response of northern vegetation to changing temperature and water availability is also investigated. We utilized both long-term remotely sensed data to extract larger scale growing season metrics (growing season start, end and duration) and productivity (i.e., growing season summed vegetation index, GSSVI) for answering these questions. We find that regionally diverged growing season shift and maximum photosynthetic state contribute differently characterized productivity inter-annual variability and trend. Also seasonally different response of vegetation gives different view of spatially varying interaction between vegetation and climate. These results highlight spatially and temporally varying vegetation dynamics and are reflective of biome-specific responses of northern vegetation to changing climate.

The spatial-temporal dynamics of open surface water bodies in CONUS during 1984-2016

NASA Astrophysics Data System (ADS)

Zou, Z.; Xiao, X.; Dong, J.; Qin, Y.; Doughty, R.; Menarguez, M.; Wang, J.

2017-12-01

Open surface water bodies provided 80% of the total water withdrawals in the Contiguous United States (CONUS) in 1985-2010. The inter-annual variability and changing trends of surface water body areas have various impacts on the human society and ecosystems. This study made use of all Landsat 5, 7, and 8 surface reflectance archives ( 370,000 images) during 1984-2016 and a water index- and pixel-based approach to detect and map open surface water bodies in the cloud-based platform of Google Earth Engine. The year-long water body area and annual average water body area were calculated for each of the last 33 years and their inter-annual variations during 1984-2016 were analyzed through anomaly analysis while their changing trends were analyzed through linear regressions. The national annual average water body areas varied from 265,000 to 281,000 km2 during 1984-2016, which is 3% below to 3% above the mean value 274,000 km2. In state level, significant decreasing trends were found in both year-long and annual average water body areas in some states of dry climates in west and southwest U.S., including Oregon, Nevada, Utah, Arizona, New Mexico, and Oklahoma. In comparison, significant increasing trends were found in some states of wet climates in the southeast and north U.S., including Indiana, Ohio, New Jersey, Delaware, Virginia, Tennessee, North Carolina, South Carolina, Louisiana, Alabama, Georgia, North Dakota and South Dakota. Open surface water body areas in CONUS decreased in relatively dry areas but increased in relatively wet areas. The relationships between open surface water body area variability and climate factors (precipitation, temperature) and human impacts (water exploitation) were also analyzed.

Climate-driven diversity change in annual grasslands: Drought plus deluge does not equal normal.

PubMed

Harrison, Susan P; LaForgia, Marina L; Latimer, Andrew M

2018-04-01

Climate forecasts agree that increased variability and extremes will tend to reduce the availability of water in many terrestrial ecosystems. Increasingly severe droughts may be exacerbated both by warmer temperatures and by the relative unavailability of water that arrives in more sporadic and intense rainfall events. Using long-term data and an experimental water manipulation, we examined the resilience of a heterogeneous annual grassland community to a prolonged series of dry winters that led to a decline in plant species richness (2000-2014), followed by a near-record wet winter (2016-2017), a climatic sequence that broadly resembles the predicted future in its high variability. In our 80, 5-m 2 observational plots, species richness did not recover in response to the wet winter, and the positive relationship of richness to annual winter rainfall thus showed a significant weakening trend over the 18-year time period. In experiments on 100, 1-m 2 plots, wintertime water supplementation increased and drought shelters decreased the seedling survival and final individual biomass of native annual forbs, the main functional group contributing to the observed long-term decline in richness. Water supplementation also increased the total cover of native annual forbs, but only increased richness within nested subplots to which seeds were also added. We conclude that prolonged dry winters, by increasing seedling mortality and reducing growth of native forbs, may have diminished the seedbank and thus the recovery potential of diversity in this community. However, the wet winter and the watering treatment did cause recovery of the community mean values of a key functional trait (specific leaf area, an indicator of drought intolerance), suggesting that some aggregate community properties may be stabilized by functional redundancy among species. © 2017 John Wiley & Sons Ltd.

Statistical link between external climate forcings and modes of ocean variability

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan; Perona, Paolo

2017-07-01

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

Response of Subalpine Conifers in the Sierra Nevada, California, U.S.A., to 20th-Century Warming and Decadal Climate Variability

Treesearch

Constance I. Millar; Robert D. Westfall; Diane L. Delany; John C. King; Lisa J. Graumlich

2004-01-01

Four independent studies of conifer growth between 1880 and 2002 in upper elevation forests of the central Sierra Nevada, California, U.S.A., showed correlated multidecadal and century-long responses associated with climate. Using tree-ring and ecological plot analysis, we studied annual branch growth of krummholz Pinus albicaulis; invasion by P....

Ecosystem responses to climate change at a Low Arctic and a High Arctic long-term research site

Treesearch

John E. Hobbie; Gaius R. Shaver; Edward B. Rastetter; Jessica E. Cherry; Scott J. Goetz; Kevin C. Guay; William A. Gould; George W. Kling

2017-01-01

Long-term measurements of ecological effects of warming are often not statistically significant because of annual variability or signal noise. These are reduced in indicators that filter or reduce the noise around the signal and allow effects of climate warming to emerge. In this way, certain indicators act as medium pass filters integrating the signal over years-to-...

Development of flood regressions and climate change scenarios to explore estimates of future peak flows

USGS Publications Warehouse

Burns, Douglas A.; Smith, Martyn J.; Freehafer, Douglas A.

2015-12-31

The application uses predictions of future annual precipitation from five climate models and two future greenhouse gas emissions scenarios and provides results that are averaged over three future periods—2025 to 2049, 2050 to 2074, and 2075 to 2099. Results are presented in ensemble form as the mean, median, maximum, and minimum values among the five climate models for each greenhouse gas emissions scenario and period. These predictions of future annual precipitation are substituted into either the precipitation variable or a water balance equation for runoff to calculate potential future peak flows. This application is intended to be used only as an exploratory tool because (1) the regression equations on which the application is based have not been adequately tested outside the range of the current climate and (2) forecasting future precipitation with climate models and downscaling these results to a fine spatial resolution have a high degree of uncertainty. This report includes a discussion of the assumptions, uncertainties, and appropriate use of this exploratory application.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

NASA Astrophysics Data System (ADS)

Sun, S.; Sun, G.; Cohen, E.; McNulty, S. G.; Caldwell, P.; Duan, K.; Zhang, Y.

2015-12-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) dynamically downscaled climate projections of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12 digit Hydrologic Unit Code level) in the conterminous US (CONUS), and evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or 2-digit HUCs. Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8 °C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 g C m-2 yr-1 (9 %) increase in GPP. Response to climate change was highly variable across the 82, 773 watersheds, but in general, the majority would see consistent increases in all variables evaluated. Over half of the 82 773 watersheds, mostly found in the northeast and the southern part of the southwest would have an increase in annual Q (>100 mm yr-1 or 20 %). This study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results will be useful for policy-makers and land managers in formulating appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Changes in the Amplitude and Phase of the Annual Cycle: quantifying from surface wind series in China

NASA Astrophysics Data System (ADS)

Feng, Tao

2013-04-01

Climate change is not only reflected in the changes in annual means of climate variables but also in the changes in their annual cycles (seasonality), especially in the regions outside the tropics. Changes in the timing of seasons, especially the wind season, have gained much attention worldwide in recent decade or so. We introduce long-range correlated surrogate data to Ensemble Empirical Mode Decomposition method, which represent the statistic characteristics of data better than white noise. The new method we named Ensemble Empirical Mode Decomposition with Long-range Correlated noise (EEMD-LRC) and applied to 600 station wind speed records. This new method is applied to investigate the trend in the amplitude of the annual cycle of China's daily mean surface wind speed for the period 1971-2005. The amplitude of seasonal variation decrease significantly in the past half century over China, which can be well explained by Annual Cycle component from EEMD-LRC. Furthermore, the phase change of annual cycle lead to strongly shorten of wind season in spring, and corresponding with strong windy day frequency change over Northern China.

Climate Expressions in Cellulose Isotopologues Over the Southeast Asian Monsoon Domain

NASA Astrophysics Data System (ADS)

Herzog, M. G.; LeGrande, A. N.; Anchukaitis, K. J.

2013-12-01

Southeast Asia experiences a highly variant climate, strongly influenced by the Southeast Asian monsoon. Oxygen isotopes in the alpha cellulose of tree rings can be used as a proxy measure of climate, but it is not clear which parameter (precipitation, temperature, water vapor, etc) is the most influential. Earlier forward models using observed meteorological data have been successful simulating tree ring cellulose oxygen isotopes in the tropics. However, by creating a cellulose oxygen isotope model which uses input data from GISS ModelE climate runs, we are able to reduce model variability and integrate δ18O in tree ring cellulose over the entire monsoon domain for the past millennium. Simulated timescales of δ18O in cellulose show a consistent annual cycle, allowing confidence in the identification of interdecadal and interannual climate variability. By comparing paleoclimate data with Global Circulation Model (GCM) outputs and a forward tree cellulose δ18O model, this study explores how δ18O can be used as a proxy measure of the monsoon on both local and regional scales. Simulated δ18O in soil water and δ18O in water vapor were found to explain the most variability in the paleoclimate data. Precipitation amount and temperature held little significance. Our results suggest that δ18O in tree cellulose is most influenced by regional controls directly related to cellulose production. top: monthly modeled output for d18O cellulose center: annually averaged model output of d18O cellulose bottom: observed monthly paleoproxy data for d18O cellulose

Isolating the Effects of the Warming Trend from the General Climate Change in Water Resources: California Case

NASA Astrophysics Data System (ADS)

Wang, J.; Yin, H.; Chung, F.

2008-12-01

While the population growth, the future land use change, and the desire for better environmental preservation and protection are adding up pressure on water resources management in California, California is facing an extra challenge of addressing potential climate change impacts on water supple and demand in California. The concerns on water facilities planning and flood control caused by climate change include modified precipitation patterns, changes in snow levels and runoff patterns due to increased air temperatures. Although long-term climate projections are largely uncertain, there appears to be a strong consistency in predicting the warming trend of future surface temperature, and the resulting shift in the seasonal patterns of runoff. However, projected changes in precipitation (wetting or drying), which control annual runoff, are far less certain. This paper attempts to separate the effects of warming trend from the effects of precipitation trend on water planning especially in California where reservoir operations are more sensitive to seasonal patterns of runoff than to the total annual runoff. The water resources systems planning model, CALSIM2, is used to evaluate climate change impact on water resource management in California. Rather than directly ingesting estimated streamflows from climate model projections into CALSIM2, a three step perturbation ratio method is proposed to introduce climate change impact into the planning model. Firstly, monthly perturbation ratio of projected monthly inflow to simulated historical monthly inflow is applied to observed historical monthly inflow to generate climate change inflows to major dams and reservoirs. To isolate the effects of warming trend on water resources, a further annual inflow adjustment is applied to the inflows generated in step one to preserve the volume of the observed annual inflow. To re-introduce the effects of precipitation trend on water resources, an additional inflow trend adjustment is applied to the adjusted climate change inflow. Therefore, three CALSIM2 experiments will be implemented: (1) base run with the observed historic inflow (1921 to 2003); (2) sensitivity run with the adjusted climate change inflow through annual inflow adjustment; (3) sensitivity run with the adjusted climate change inflow through annual inflow adjustment and inflow trend adjustment. To account for the variability of various climate models in projecting future climates, the uncertainty in future emission scenarios, and the difference in different projection periods, estimated inflows from 6 climate models for 2 emission scenarios (A2 and B1) and two projection periods (2030-2059 and 2070-2099) are included in the CALSIM model experiments.

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn

PubMed Central

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0–7.0 mm, AP of 344.0–1089.0 mm, CI of -47.7–0.0°C, and ART of 26.1–45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China. PMID:26177033

Evaluation of Limiting Climatic Factors and Simulation of a Climatically Suitable Habitat for Chinese Sea Buckthorn.

PubMed

Li, Guoqing; Du, Sheng; Guo, Ke

2015-01-01

Chinese sea buckthorn (Hippophae rhamnoides subsp. sinensis) has considerable economic potential and plays an important role in reclamation and soil and water conservation. For scientific cultivation of this species across China, we identified the key climatic factors and explored climatically suitable habitat in order to maximize survival of Chinese sea buckthorn using MaxEnt and GIS tools, based on 98 occurrence records from herbarium and publications and 13 climatic factors from Bioclim, Holdridge life zone and Kria' index variables. Our simulation showed that the MaxEnt model performance was significantly better than random, with an average test AUC value of 0.93 with 10-fold cross validation. A jackknife test and the regularized gain change, which were applied to the training algorithm, showed that precipitation of the driest month (PDM), annual precipitation (AP), coldness index (CI) and annual range of temperature (ART) were the most influential climatic factors in limiting the distribution of Chinese sea buckthorn, which explained 70.1% of the variation. The predicted map showed that the core of climatically suitable habitat was distributed from the southwest to northwest of Gansu, Ningxia, Shaanxi and Shanxi provinces, where the most influential climate variables were PDM of 1.0-7.0 mm, AP of 344.0-1089.0 mm, CI of -47.7-0.0°C, and ART of 26.1-45.0°C. We conclude that the distribution patterns of Chinese sea buckthorn are related to the northwest winter monsoon, the southwest summer monsoon and the southeast summer monsoon systems in China.

Climate variability reflected by tree-ring width and δ18O in a heavily glaciated area of the Patagonian Andes since the Little Ice Age

NASA Astrophysics Data System (ADS)

Meier, W. J. H.; Wernicke, J., Jr.; Braun, M.; Aravena, J. C.; Jaña, R.; Griessinger, J.

2016-12-01

Since the end of the Little Ice Age, the area of the Northern and Southern Patagonian ice sheet decreased by more than 14% and 11%, respectively. The melting increased since the last decade by 2.3%. The glaciers of Cordillera Darwin recorded a surface decrease of approximately 14% for the last 140 years. The reason for the excessive glacial change is often explained through the rise in temperature combined with a decrease in precipitation or a change in seasonality. Since a spatially coherent coverage of climatological measurement is lacking it is not possible to verify this assumption in a differentiated manner. Hence, the German- Chilean joint project "Responses of GlAciers, Biosphere and hYdrology to climate Variability and climate chAnge across the Southern Andes (GABY-VASA)" aims to determine the influence of long and short term climate variabilities (El Niño-Southern Oscillation (ENSO), Southern Hemisphere Annular Mode (SAM)) on the cryo- and biosphere. Trees growing at the glacier margins and at the natural treeline were sampled at four different locations ranging from the humid western part of the southern Andes (annual precipitation > 10.000mma-1) to the distinct dryer eastern part (annual precipitation < 500mma-1). Besides the tree-ring width based temperature reconstruction the precipitation variability reflected by δ18O in tree-rings is a promising approach to obtain detailed information of small-scaled hydro climatic conditions. Furthermore the use of δ18O as a proxy in combination with tree-ring width offers the opportunity of meteorological back trajectories and the derivation of air masses since the Little Ice Age. It thus interlinks past and present climate and allows to draw conclusions about the driving forces of glacial change.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Anthropogenic nitrogen deposition alters growth responses of European beech (Fagus sylvativa L.) to climate change.

PubMed

Hess, Carsten; Niemeyer, Thomas; Fichtner, Andreas; Jansen, Kirstin; Kunz, Matthias; Maneke, Moritz; von Wehrden, Henrik; Quante, Markus; Walmsley, David; von Oheimb, Goddert; Härdtle, Werner

2018-02-01

Global change affects the functioning of forest ecosystems and the services they provide, but little is known about the interactive effects of co-occurring global change drivers on important functions such as tree growth and vitality. In the present study we quantified the interactive (i.e. synergistic or antagonistic) effects of atmospheric nitrogen (N) deposition and climatic variables (temperature, precipitation) on tree growth (in terms of tree-ring width, TRW), taking forest ecosystems with European beech (Fagus sylvatica L.) as an example. We hypothesised that (i) N deposition and climatic variables can evoke non-additive responses of the radial increment of beech trees, and (ii) N loads have the potential to strengthen the trees' sensitivity to climate change. In young stands, we found a synergistic positive effect of N deposition and annual mean temperature on TRW, possibly linked to the alleviation of an N shortage in young stands. In mature stands, however, high N deposition significantly increased the trees' sensitivity to increasing annual mean temperatures (antagonistic effect on TRW), possibly due to increased fine root dieback, decreasing mycorrhizal colonization or shifts in biomass allocation patterns (aboveground vs. belowground). Accordingly, N deposition and climatic variables caused both synergistic and antagonistic effects on the radial increment of beech trees, depending on tree age and stand characteristics. Hence, the nature of interactions could mediate the long-term effects of global change drivers (including N deposition) on forest carbon sequestration. In conclusion, our findings illustrate that interaction processes between climatic variables and N deposition are complex and have the potential to impair growth and performance of European beech. This in turn emphasises the importance of multiple-factor studies to foster an integrated understanding and models aiming at improved projections of tree growth responses to co-occurring drivers of global change. Copyright © 2017 Elsevier Ltd. All rights reserved.

Inter-Annual Variability in Stream Water Temperature, Microclimate and Heat Exchanges: a Comparison of Forest and Moorland Environments

NASA Astrophysics Data System (ADS)

Garner, G.; Hannah, D. M.; Malcolm, I.; Sadler, J. P.

2012-12-01

Riparian forest is recognised as important for moderating stream temperature variability and has the potential to mitigate thermal extremes in a changing climate. Previous research on the heat exchanges controlling water column temperature has often been short-term or seasonally-constrained, with the few multi-year studies limited to a maximum of two years. This study advances previous work by providing a longer-term perspective which allows assessment of inter-annual variability in stream temperature, microclimate and heat exchange dynamics between a semi-natural woodland and a moorland (no trees) reach of the Girnock Burn, a tributary of the Scottish Dee. Automatic weather stations collected 15-minute data over seven consecutive years, which to our knowledge is a unique data set in providing the longest term perspective to date on stream temperature, microclimate and heat exchange processes. Results for spring-summer indicate that the presence of a riparian canopy has a consistent effect between years in reducing the magnitude and variability of mean daily water column temperature and daily net energy totals. Differences in the magnitude and variability in net energy fluxes between the study reaches were driven primarily by fluctuations in net radiation and latent heat fluxes in response to between- and within-year variability in growth of the riparian forest canopy at the forest and prevailing weather conditions at both the forest and moorland. This research provides new insights on the inter-annual variability of stream energy exchanges for moorland and forested reaches under a wide range of climatological and hydrological conditions. The findings therefore provide a more robust process basis for modelling the impact of changes in forest practice and climate change on river thermal dynamics.

Wave climate simulation for southern region of the South China Sea

NASA Astrophysics Data System (ADS)

Mirzaei, Ali; Tangang, Fredolin; Juneng, Liew; Mustapha, Muzneena Ahmad; Husain, Mohd Lokman; Akhir, Mohd Fadzil

2013-08-01

This study investigates long-term variability and wave characteristic trends in the southern region of the South China Sea (SCS). We implemented the state-of-the art WAVEWATCH III spectral wave model to simulate a 31-year wave hindcast. The simulation results were used to assess the inter-annual variability and long-term changes in the SCS wave climate for the period 1979 to 2009. The model was forced with Climate Forecast System Reanalysis winds and validated against altimeter data and limited available measurements from an Acoustic Wave and Current recorder located offshore of Terengganu, Malaysia. The mean annual significant wave height and peak wave period indicate the occurrence of higher wave heights and wave periods in the central SCS and lower in the Sunda shelf region. Consistent with wind patterns, the wave direction also shows southeasterly (northwesterly) waves during the summer (winter) monsoon. This detailed hindcast demonstrates strong inter-annual variability of wave heights, especially during the winter months in the SCS. Significant wave height correlated negatively with Niño3.4 index during winter, spring and autumn seasons but became positive in the summer monsoon. Such correlations correspond well with surface wind anomalies over the SCS during El Nino events. During El Niño Modoki, the summer time positive correlation extends northeastwards to cover the entire domain. Although significant positive trends were found at 95 % confidence levels during May, July and September, there is significant negative trend in December covering the Sunda shelf region. However, the trend appears to be largely influenced by large El Niño signals.

Projected changes in snowfall extremes and interannual variability of snowfall in the western United States

NASA Astrophysics Data System (ADS)

Lute, A. C.; Abatzoglou, J. T.; Hegewisch, K. C.

2015-02-01

Projected warming will have significant impacts on snowfall accumulation and melt, with implications for water availability and management in snow-dominated regions. Changes in snowfall extremes are confounded by projected increases in precipitation extremes. Downscaled climate projections from 20 global climate models were bias-corrected to montane Snowpack Telemetry stations across the western United States to assess mid-21st century changes in the mean and variability of annual snowfall water equivalent (SFE) and extreme snowfall events, defined by the 90th percentile of cumulative 3 day SFE amounts. Declines in annual SFE and number of snowfall days were projected for all stations. Changes in the magnitude of snowfall event quantiles were sensitive to historical winter temperature. At climatologically cooler locations, such as in the Rocky Mountains, changes in the magnitude of snowfall events mirrored changes in the distribution of precipitation events, with increases in extremes and less change in more moderate events. By contrast, declines in snowfall event magnitudes were found for all quantiles in warmer locations. Common to both warmer and colder sites was a relative increase in the magnitude of snowfall extremes compared to annual SFE and a larger fraction of annual SFE from snowfall extremes. The coefficient of variation of annual SFE increased up to 80% in warmer montane regions due to projected declines in snowfall days and the increased contribution of snowfall extremes to annual SFE. In addition to declines in mean annual SFE, more frequent low-snowfall years and less frequent high-snowfall years were projected for every station.

Intercomparison of model response and internal variability across climate model ensembles

NASA Astrophysics Data System (ADS)

Kumar, Devashish; Ganguly, Auroop R.

2017-10-01

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

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

Boer, George J.; Smith, Douglas M.; Cassou, Christophe

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

Paleoclimatic Reconstructions From Plant Macrofossils For The Last Glacial Maximum, Middle Holocene, And Latest Holocene In The American Southwest

NASA Astrophysics Data System (ADS)

Thompson, R. S.; Anderson, K.; Pelltier, R.; Strickland, L. E.; Shafer, S. L.; Bartlein, P. J.

2013-12-01

Fossil plant remains preserved in a variety of geologic settings provide direct evidence of where individual species lived in the past, and there are long-established methods for paleoclimatic reconstructions based on comparisons between modern and past geographic ranges of plant species. In principle, these methods use relatively straightforward procedures that frequently result in what appear to be very precise estimates of past temperature and moisture conditions. The reconstructed estimates can be mapped for specific time slices for synoptic-scale reconstructions for data-model comparisons. Although paleobotanical data can provide apparently precise estimates of past climatic conditions, it is difficult to gauge the associated uncertainties. The estimates may be affected by the choice of modern calibration data, reconstruction methods employed, and whether the climatic variable under consideration is an important determinant of the distributions of the species being considered. For time-slice reconstructions, there are also issues involving the adequacy of the spatial coverage of the fossil data and the degree of variability through time. To examine some of these issues, we estimated annual precipitation and summer and winter temperatures for the Last Glacial Maximum (LGM, 21000 × 1000 yr BP), Middle Holocene (MH, 6000 × 500 yr BP), and Latest Holocene (LH, the last 500 yrs), based on the application of four quantitative approaches to paleobotanical assemblages preserved in packrat middens in the American Southwest. Our results indicate that historic variability and difficulties in interpolating climatic values to fossil sites may impose ranges of uncertainties of more than × 1°C for temperature and × 50 mm for annual precipitation. Climatic estimates based on modern midden assemblages generally fall within these ranges, although there may be biases that differ regionally. Samples of similar age and location provide similar climatic estimates, and the four approaches usually result in anomalies of the same sign, but with differing amplitudes. There is considerable variability among the anomalies for samples within each time slice, and different time slices have different geographic coverages of samples. The reconstructed temperature anomalies are similar between the MH and LH time slices, and generally fall within the uncertainties related to the modern climatic data. LGM anomalies were significantly colder, and for many samples exceeded -5°C in both winter and summer. There are what appear to be significant MH annual precipitation anomalies to the south (dry after 6.2 ka)and to the northwest (wet before 6.2 ka), but it may be misleading to compare these, given the differences in age. Positive annual precipitation anomalies for the LGM are more than 100 mm in the northwest, and smaller in the northeast and south.

Association between climate factors, pollen counts, and childhood hay fever prevalence in the United States.

PubMed

Silverberg, Jonathan I; Braunstein, Marc; Lee-Wong, Mary

2015-02-01

Climate factors and pollen counts may play a role in hay fever. We sought to determine the impact of specific climate factors and pollen counts on the US prevalence of hay fever and statewide variation in prevalence. We used a merged analysis of the 2007 National Survey of Children's Health from a representative sample of 91,642 children aged 0 to 17 years and the 2006-2007 National Climate Data Center and Weather Service measurements of relative humidity (%), indoor heating degree days, precipitation, Palmer Hydrological Drought Index, clear sky and issued ultraviolet indices, stratospheric ozone levels, and outdoor air temperature and National Allergy Bureau total pollen counts. Multivariate survey logistic regression models controlled for sex, race/ethnicity, age, household income, and birthplace. The US prevalence of hay fever in childhood was 18.0% (95% CI, 17.7% to 18.2%), with the highest prevalence in southeastern and southern states. Hay fever prevalence was significantly lower with second and third quartile mean annual relative humidity (logistic regression, P ≤ .01 for both), fourth quartile mean annual Palmer Hydrological Drought Index (P = .02), third and fourth quartile mean annual heating degree days (P < .0001 for both), and third and fourth quartile mean annual stratospheric ozone levels but increased with second, third, and fourth quartile mean annual temperature (P ≤ .02 for both), fourth quartile mean annual precipitation (P = .0007), mean total pollen counts (P = .01), and second, third, and fourth quartile issued ultraviolet index (P ≤ .0001 for all). Principal-component analysis was also used to determine the combined effects of correlated climate variables and pollen counts. This study provides evidence of the influence of climate on the US prevalence of childhood hay fever. Copyright © 2014 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

How well do CMIP5 Climate Models Reproduce the Hydrologic Cycle of the Colorado River Basin?

NASA Astrophysics Data System (ADS)

Gautam, J.; Mascaro, G.

2017-12-01

The Colorado River, which is the primary source of water for nearly 40 million people in the arid Southwestern states of the United States, has been experiencing an extended drought since 2000, which has led to a significant reduction in water supply. As the water demands increase, one of the major challenges for water management in the region has been the quantification of uncertainties associated with streamflow predictions in the Colorado River Basin (CRB) under potential changes of future climate. Hence, testing the reliability of model predictions in the CRB is critical in addressing this challenge. In this study, we evaluated the performances of 17 General Circulation Models (GCMs) from the Coupled Model Intercomparison Project Phase Five (CMIP5) and 4 Regional Climate Models (RCMs) in reproducing the statistical properties of the hydrologic cycle in the CRB. We evaluated the water balance components at four nested sub-basins along with the inter-annual and intra-annual changes of precipitation (P), evaporation (E), runoff (R) and temperature (T) from 1979 to 2005. Most of the models captured the net water balance fairly well in the most-upstream basin but simulated a weak hydrological cycle in the evaporation channel at the downstream locations. The simulated monthly variability of P had different patterns, with correlation coefficients ranging from -0.6 to 0.8 depending on the sub-basin and the models from same parent institution clustering together. Apart from the most-upstream sub-basin where the models were mainly characterized by a negative seasonal bias in SON (of up to -50%), most of them had a positive bias in all seasons (of up to +260%) in the other three sub-basins. The models, however, captured the monthly variability of T well at all sites with small inter-model variabilities and a relatively similar range of bias (-7 °C to +5 °C) across all seasons. Mann-Kendall test was applied to the annual P and T time-series where majority of the models and all observed products displayed nonsignificant trends for annual P. In contrast, more than half of the models exhibited significant trend with annual T as the observations. The results of this work provide support when selecting climate models for impact studies required to develop policies and plan investments aimed at ensuring water sustainability in the CRB.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

How Ocean Color Influences the Interplay Between Annual and Interannual Tropical Pacific Variability

NASA Astrophysics Data System (ADS)

Hammann, A. C.; Gnanadesikan, A.

2010-12-01

While the basic mechanisms responsible for ENSO have long been known, many details still evade our understanding. Since the behavior of the real climate system appears to be highly sensitive to such details, however, our ability to model, let alone predict it with any confidence has so far been rather restricted. Not only can small perturbations in many state variables lead to strongly amplified responses, but also do spatial and temporal scales of variability rarely occur in isolation from each other. Both points are born out in the study by Anderson et al. (2009), who removed surface chlorophyll in different regions of the tropical (but mostly off-equatorial) Pacific in a coupled ocean-atmosphere-land-ice model. Different removal patterns lead to large differences in the amplitudes of both ENSO and the equatorial annual cycle. Anderson et al.’s analysis focuses on ENSO and reveals that the transmission of off-equatorial perturbations to the equator happens mainly through a changed atmospheric response to SST anomalies. Here, we analyze the same data with respect to the annual cycle and how it interacts with ENSO. Guilyardi (2006) reports that observations and models alike show a zero-sum-type behavior of annual and ENSO-scale variability; increased spectral power in the annual band means decreased power in the ENSO band and vice versa. This is not the case for the different patterns of chlorophyll removal in our model, and hence it appears that this removal changes a fundamental part of its mean state. The dynamics of the annual cycle are likely influenced by oceanic meridional temperature advection, which provides another possible route for off-to-equatorial signal propagation. A common aspect of the tropical annual cycle in most coupled climate models is the presence of a double ITCZ instead of a single north-shifted one. Even though this appears to be unrelated to (albeit influenced by) the changes in ocean color, our model exhibits a much improved, dominantly northern ITCZ when compared with the GFDL CM2.1 model; all other components being the same, we use an isopycnal ocean model, whereas CM2.1 uses horizontal coordinates.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-06-01

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

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

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

PubMed

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

2018-05-22

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

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: sensitivity to climatic variability.

Treesearch

Melisa L. Holman; David L. Peterson

2006-01-01

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...

Modeling the influence of precipitation and nitrogen deposition on forest understory fuel connectivity in Sierra Nevada mixed-conifer forest

Treesearch

M. Hurteau; M. North; T. Foines

2009-01-01

Climate change models for California’s Sierra Nevada predict greater inter-annual variability in precipitation over the next 50 years. These increases in precipitation variability coupled with increases in nitrogen deposition fromfossil fuel consumption are likely to result in increased productivity levels and significant increases in...

Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature

PubMed Central

Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M.; Stevenson, Pablo R.; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C.; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M.

2017-01-01

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage. PMID:28301482

Forest biomass density across large climate gradients in northern South America is related to water availability but not with temperature.

PubMed

Álvarez-Dávila, Esteban; Cayuela, Luis; González-Caro, Sebastián; Aldana, Ana M; Stevenson, Pablo R; Phillips, Oliver; Cogollo, Álvaro; Peñuela, Maria C; von Hildebrand, Patricio; Jiménez, Eliana; Melo, Omar; Londoño-Vega, Ana Catalina; Mendoza, Irina; Velásquez, Oswaldo; Fernández, Fernando; Serna, Marcela; Velázquez-Rua, Cesar; Benítez, Doris; Rey-Benayas, José M

2017-01-01

Understanding and predicting the likely response of ecosystems to climate change are crucial challenges for ecology and for conservation biology. Nowhere is this challenge greater than in the tropics as these forests store more than half the total atmospheric carbon stock in their biomass. Biomass is determined by the balance between biomass inputs (i.e., growth) and outputs (mortality). We can expect therefore that conditions that favor high growth rates, such as abundant water supply, warmth, and nutrient-rich soils will tend to correlate with high biomass stocks. Our main objective is to describe the patterns of above ground biomass (AGB) stocks across major tropical forests across climatic gradients in Northwestern South America. We gathered data from 200 plots across the region, at elevations ranging between 0 to 3400 m. We estimated AGB based on allometric equations and values for stem density, basal area, and wood density weighted by basal area at the plot-level. We used two groups of climatic variables, namely mean annual temperature and actual evapotranspiration as surrogates of environmental energy, and annual precipitation, precipitation seasonality, and water availability as surrogates of water availability. We found that AGB is more closely related to water availability variables than to energy variables. In northwest South America, water availability influences carbon stocks principally by determining stand structure, i.e. basal area. When water deficits increase in tropical forests we can expect negative impact on biomass and hence carbon storage.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

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

Demographic patterns of a widespread long-lived tree are associated with rainfall and disturbances along rainfall gradients in SE Australia

PubMed Central

Cohn, Janet S; Lunt, Ian D; Bradstock, Ross A; Hua, Quan; McDonald, Simon

2013-01-01

Predicting species distributions with changing climate has often relied on climatic variables, but increasingly there is recognition that disturbance regimes should also be included in distribution models. We examined how changes in rainfall and disturbances along climatic gradients determined demographic patterns in a widespread and long-lived tree species, Callitris glaucophylla in SE Australia. We examined recruitment since 1950 in relation to annual (200–600 mm) and seasonal (summer, uniform, winter) rainfall gradients, edaphic factors (topography), and disturbance regimes (vertebrate grazing [tenure and species], fire). A switch from recruitment success to failure occurred at 405 mm mean annual rainfall, coincident with a change in grazing regime. Recruitment was lowest on farms with rabbits below 405 mm rainfall (mean = 0–0.89 cohorts) and highest on less-disturbed tenures with no rabbits above 405 mm rainfall (mean = 3.25 cohorts). Moderate levels of recruitment occurred where farms had no rabbits or less disturbed tenures had rabbits above and below 405 mm rainfall (mean = 1.71–1.77 cohorts). These results show that low annual rainfall and high levels of introduced grazing has led to aging, contracting populations, while higher annual rainfall with low levels of grazing has led to younger, expanding populations. This study demonstrates how demographic patterns vary with rainfall and spatial variations in disturbances, which are linked in complex ways to climatic gradients. Predicting changes in tree distribution with climate change requires knowledge of how rainfall and key disturbances (tenure, vertebrate grazing) will shift along climatic gradients. PMID:23919160

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

USGS Publications Warehouse

Poore, Richard Z.

2008-01-01

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

Modeled impact of anthropogenic land cover change on climate

USGS Publications Warehouse

Findell, K.L.; Shevliakova, E.; Milly, P.C.D.; Stouffer, R.J.

2007-01-01

Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory's climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with potential natural vegetation cover). Differences in the annual mean climatic fields analyzed did not exhibit global field significance. Within some of the regions of land cover change, however, there are relatively large changes of many surface climatic variables. These changes are highly significant locally in the annual mean and in most months of the year in eastern Europe and northern India. They can be explained mainly as direct and indirect consequences of model-prescribed increases in surface albedo, decreases in rooting depth, and changes of stomatal control that accompany deforestation. ?? 2007 American Meteorological Society.

Impacts of Soil-aquifer Heat and Water Fluxes on Simulated Global Climate

NASA Technical Reports Server (NTRS)

Krakauer, N.Y.; Puma, Michael J.; Cook, B. I.

2013-01-01

Climate models have traditionally only represented heat and water fluxes within relatively shallow soil layers, but there is increasing interest in the possible role of heat and water exchanges with the deeper subsurface. Here, we integrate an idealized 50m deep aquifer into the land surface module of the GISS ModelE general circulation model to test the influence of aquifer-soil moisture and heat exchanges on climate variables. We evaluate the impact on the modeled climate of aquifer-soil heat and water fluxes separately, as well as in combination. The addition of the aquifer to ModelE has limited impact on annual-mean climate, with little change in global mean land temperature, precipitation, or evaporation. The seasonal amplitude of deep soil temperature is strongly damped by the soil-aquifer heat flux. This not only improves the model representation of permafrost area but propagates to the surface, resulting in an increase in the seasonal amplitude of surface air temperature of >1K in the Arctic. The soil-aquifer water and heat fluxes both slightly decrease interannual variability in soil moisture and in landsurface temperature, and decrease the soil moisture memory of the land surface on seasonal to annual timescales. The results of this experiment suggest that deepening the modeled land surface, compared to modeling only a shallower soil column with a no-flux bottom boundary condition, has limited impact on mean climate but does affect seasonality and interannual persistence.

Western juniper and ponderosa pine ecotonal climate-growth relationships across landscape gradients in southern Oregon

USGS Publications Warehouse

Knutson, K.C.; Pyke, D.A.

2008-01-01

Forecasts of climate change for the Pacific northwestern United States predict warmer temperatures, increased winter precipitation, and drier summers. Prediction of forest growth responses to these climate fluctuations requires identification of climatic variables limiting tree growth, particularly at limits of free species distributions. We addressed this problem at the pine-woodland ecotone using tree-ring data for western juniper (Juniperus occidentalis var. occidentalis Hook.) and ponderosa pine (Pinus ponderosa Dougl. ex Loud.) from southern Oregon. Annual growth chronologies for 1950-2000 were developed for each species at 17 locations. Correlation and linear regression of climate-growth relationships revealed that radial growth in both species is highly dependent on October-June precipitation events that recharge growing season soil water. Mean annual radial growth for the nine driest years suggests that annual growth in both species is more sensitive to drought at lower elevations and sites with steeper slopes and sandy or rocky soils. Future increases in winter precipitation could increase productivity in both species at the pine-woodland ecotone. Growth responses, however, will also likely vary across landscape features, and our findings suggest that heightened sensitivity to future drought periods and increased temperatures in the two species will predominantly occur at lower elevation sites with poor water-holding capacities. ?? 2008 NRC.

Assessment of surface air temperature over the Arctic Ocean in reanalysis and IPCC AR4 model simulations with IABP/POLES observations

NASA Astrophysics Data System (ADS)

Liu, Jiping; Zhang, Zhanhai; Hu, Yongyun; Chen, Liqi; Dai, Yongjiu; Ren, Xiaobo

2008-05-01

The surface air temperature (SAT) over the Arctic Ocean in reanalyses and global climate model simulations was assessed using the International Arctic Buoy Programme/Polar Exchange at the Sea Surface (IABP/POLES) observations for the period 1979-1999. The reanalyses, including the National Centers for Environmental Prediction Reanalysis II (NCEP2) and European Centre for Medium-Range Weather Forecast 40-year Reanalysis (ERA40), show encouraging agreement with the IABP/POLES observations, although some spatiotemporal discrepancies are noteworthy. The reanalyses have warm annual mean biases and underestimate the observed interannual SAT variability in summer. Additionally, NCEP2 shows an excessive warming trend. Most model simulations (coordinated by the International Panel on Climate Change for its Fourth Assessment Report) reproduce the annual mean, seasonal cycle, and trend of the observed SAT reasonably well, particularly the multi-model ensemble mean. However, large discrepancies are found. Some models have the annual mean SAT biases far exceeding the standard deviation of the observed interannul SAT variability and the across-model standard deviation. Spatially, the largest inter-model variance of the annual mean SAT is found over the North Pole, Greenland Sea, Barents Sea and Baffin Bay. Seasonally, a large spread of the simulated SAT among the models is found in winter. The models show interannual variability and decadal trend of various amplitudes, and can not capture the observed dominant SAT mode variability and cooling trend in winter. Further discussions of the possible attributions to the identified SAT errors for some models suggest that the model's performance in the sea ice simulation is an important factor.

Interannual Variability in Global Soil Respiration on a 0.5 Degree Grid Cell Basis (1980-1994)

DOE Data Explorer

Raich, James W. [Iowa State University, Ames, IA (USA); Potter, Christopher S. [NASA Ames Research Center (ARC), Moffett Field, Mountain View, CA (United States); Bhagawat, Dwipen [Iowa State Univ., Ames, IA (United States); Olson, L. M. [CDIAC, Oak Ridge National Laboratory, Oak Ridge, TN

2003-08-01

The Principal Investigators used a climate-driven regression model to develop spatially resolved estimates of soil-CO2 emissions from the terrestrial land surface for each month from January 1980 to December 1994, to evaluate the effects of interannual variations in climate on global soil-to-atmosphere CO2 fluxes. The mean annual global soil-CO2 flux over this 15-y period was estimated to be 80.4 (range 79.3-81.8) Pg C. Monthly variations in global soil-CO2 emissions followed closely the mean temperature cycle of the Northern Hemisphere. Globally, soil-CO2 emissions reached their minima in February and peaked in July and August. Tropical and subtropical evergreen broad-leaved forests contributed more soil-derived CO2 to the atmosphere than did any other vegetation type (~30% of the total) and exhibited a biannual cycle in their emissions. Soil-CO2 emissions in other biomes exhibited a single annual cycle that paralleled the seasonal temperature cycle. Interannual variability in estimated global soil-CO2 production is substantially less than is variability in net carbon uptake by plants (i.e., net primary productivity). Thus, soils appear to buffer atmospheric CO2 concentrations against far more dramatic seasonal and interannual differences in plant growth. Within seasonally dry biomes (savannas, bushlands, and deserts), interannual variability in soil-CO2 emmissions correlated significantly with interannual differences in precipitation. At the global scale, however, annual soil-CO2 fluxes correlated with mean annual temperature, with a slope of 3.3 PgCY-1 per degree Celsius. Although the distribution of precipitation influences seasonal and spatial patterns of soil-CO2 emissions, global warming is likely to stimulate CO2 emissions from soils.

Ozone trends over the United States at different times of day

NASA Astrophysics Data System (ADS)

Yan, Yingying; Lin, Jintai; He, Cenlin

2018-01-01

In the United States, the decline of summertime daytime peak ozone in the last 20 years has been clearly connected to reductions in anthropogenic emissions. However, questions remain about how and through what mechanisms ozone at other times of day have changed over recent decades. Here we analyze the interannual variability and trends of ozone at different hours of day, using observations from about 1000 US sites during 1990-2014. We find a clear diurnal cycle both in the magnitude of ozone trends and in the relative importance of climate variability versus anthropogenic emissions to ozone changes. Interannual climate variability has mainly been associated with the detrended fluctuation in the US annual daytime ozone over 1990-2014, with a much smaller effect on the nighttime ozone. Reductions in anthropogenic emissions of nitrogen oxides have led to substantial growth in the US annual average nighttime ozone due to reduced ozone titration, while the summertime daytime ozone has declined. Environmental policymaking might consider further improvements to reduce ozone levels at night and other non-peak hours.

Ozone trends over the United States at different times of day

NASA Astrophysics Data System (ADS)

Lin, J.; Yan, Y.

2017-12-01

In the United States, the decline of summertime daytime peak ozone in the last 20 years has been clearly connected to reductions in anthropogenic emissions. Yet questions remain on how and through what mechanisms ozone at other times of day have changed over the recent decades. Here we analyze the interannual variability and trends of ozone at different hours of day, using observations from about 1000 US sites during 1990-2014. We find a clear diurnal cycle both in the magnitude of ozone trends and in the relative importance of climate variability versus anthropogenic emissions to ozone changes. Interannual climate variability has mainly been associated with the de-trended fluctuation in the US annual daytime ozone over 1990-2014, with a much smaller effect on the nighttime ozone. Reductions in anthropogenic emissions of nitrogen oxides have led to substantial growth in the US annual average nighttime ozone due to reduced ozone titration, while the summertime daytime ozone has declined. Environmental policymaking might consider further improvements to reduce ozone levels at night and other non-peak hours.

Studying Basin Water Balance Variations at Inter- and Intra-annual Time Scales Based On the Budyko Hypothesis and GRACE Gravimetry Satellite Observations

NASA Astrophysics Data System (ADS)

Shen, H.

2017-12-01

Increasing intensity in global warming and anthropogenic activities has triggered significant changes over regional climates and landscapes, which, in turn, drive the basin water cycle and hydrological balance into a complex and unstable state. Budyko hypothesis is a powerful tool to characterize basin water balance and hydrological variations at long-term average scale. However, due to the absence of basin water storage change, applications of Budyko theory to the inter-annual and intra-annual time scales has been prohibited. The launch of GRACE gavimetry satellites provides a great opportunity to quantify terrestrial water storage change, which can be further introduced into the Budyko hypothesis to reveal the inter- and intra-annual response of basin water components under impacts of climate variability and/or human activities. This research targeted Hai River Basin (in China) and Murray-Darling Basin (in Australia), which have been identified with a continuous groundwater depletion trend as well as impacts by extreme climates in the past decade. This can help us to explore how annual or seasonal precipitation were redistributed to evapotranspiration and runoff via changing basin water storage. Moreover, the impacts of vegetation on annual basin water balance will be re-examined. Our results are expected to provide deep insights about the water cycle and hydrological behaviors for the targeted basins, as well as a proof for a consideration of basin water storage change into the Budyko model at inter- or intra-annual time steps.

Projecting pest population dynamics under global warming: the combined effect of inter- and intra-annual variations.

PubMed

Zidon, Royi; Tsueda, Hirotsugu; Morin, Efrat; Morin, Shai

2016-06-01

The typical short generation length of insects makes their population dynamics highly sensitive not only to mean annual temperatures but also to their intra-annual variations. To consider the combined effect of both thermal factors under global warming, we propose a modeling framework that links general circulation models (GCMs) with a stochastic weather generator and population dynamics models to predict species population responses to inter- and intra-annual temperature changes. This framework was utilized to explore future changes in populations of Bemisia tabaci, an invasive insect pest-species that affects multiple agricultural systems in the Mediterranean region. We considered three locations representing different pest status and climatic conditions: Montpellier (France), Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local daily temperature realizations representing current and future (mid-21st century) climatic conditions under two emission scenarios for the three locations. Our simulations predicted a significant increase in the average number of annual generations and in population size, and a significant lengthening of the growing season in all three locations. A negative effect was found only in Seville for the summer season, where future temperatures lead to a reduction in population size. High variability in population size was observed between years with similar annual mean temperatures, suggesting a strong effect of intra-annual temperature variation. Critical periods were from late spring to late summer in Montpellier and from late winter to early summer in Seville and Beit-Jamal. Although our analysis suggested that earlier seasonal activity does not necessarily lead to increased populations load unless an additional generation is produced, it is highly likely that the insect will become a significant pest of open-fields at Mediterranean latitudes above 40° during the next 50 years. Our simulations also implied that current predictions based on mean temperature anomalies are relatively conservative and it is better to apply stochastic tools to resolve complex responses to climate change while taking natural variability into account. In summary, we propose a modeling framework capable of determining distinct intra-annual temperature patterns leading to large or small population sizes, for pest risk assessment and management planning of both natural and agricultural ecosystems.

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

NASA Astrophysics Data System (ADS)

Mutz, Sebastian; Ehlers, Todd

2017-04-01

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

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.

A demographic approach to study effects of climate change in desert plants.

PubMed

Salguero-Gómez, Roberto; Siewert, Wolfgang; Casper, Brenda B; Tielbörger, Katja

2012-11-19

Desert species respond strongly to infrequent, intense pulses of precipitation. Consequently, indigenous flora has developed a rich repertoire of life-history strategies to deal with fluctuations in resource availability. Examinations of how future climate change will affect the biota often forecast negative impacts, but these-usually correlative-approaches overlook precipitation variation because they are based on averages. Here, we provide an overview of how variable precipitation affects perennial and annual desert plants, and then implement an innovative, mechanistic approach to examine the effects of precipitation on populations of two desert plant species. This approach couples robust climatic projections, including variable precipitation, with stochastic, stage-structured models constructed from long-term demographic datasets of the short-lived Cryptantha flava in the Colorado Plateau Desert (USA) and the annual Carrichtera annua in the Negev Desert (Israel). Our results highlight these populations' potential to buffer future stochastic precipitation. Population growth rates in both species increased under future conditions: wetter, longer growing seasons for Cryptantha and drier years for Carrichtera. We determined that such changes are primarily due to survival and size changes for Cryptantha and the role of seed bank for Carrichtera. Our work suggests that desert plants, and thus the resources they provide, might be more resilient to climate change than previously thought.

A demographic approach to study effects of climate change in desert plants

PubMed Central

Salguero-Gómez, Roberto; Siewert, Wolfgang; Casper, Brenda B.; Tielbörger, Katja

2012-01-01

Desert species respond strongly to infrequent, intense pulses of precipitation. Consequently, indigenous flora has developed a rich repertoire of life-history strategies to deal with fluctuations in resource availability. Examinations of how future climate change will affect the biota often forecast negative impacts, but these—usually correlative—approaches overlook precipitation variation because they are based on averages. Here, we provide an overview of how variable precipitation affects perennial and annual desert plants, and then implement an innovative, mechanistic approach to examine the effects of precipitation on populations of two desert plant species. This approach couples robust climatic projections, including variable precipitation, with stochastic, stage-structured models constructed from long-term demographic datasets of the short-lived Cryptantha flava in the Colorado Plateau Desert (USA) and the annual Carrichtera annua in the Negev Desert (Israel). Our results highlight these populations' potential to buffer future stochastic precipitation. Population growth rates in both species increased under future conditions: wetter, longer growing seasons for Cryptantha and drier years for Carrichtera. We determined that such changes are primarily due to survival and size changes for Cryptantha and the role of seed bank for Carrichtera. Our work suggests that desert plants, and thus the resources they provide, might be more resilient to climate change than previously thought. PMID:23045708

Genome scans for divergent selection in natural populations of the widespread hardwood species Eucalyptus grandis (Myrtaceae) using microsatellites

PubMed Central

Song, Zhijiao; Zhang, Miaomiao; Li, Fagen; Weng, Qijie; Zhou, Chanpin; Li, Mei; Li, Jie; Huang, Huanhua; Mo, Xiaoyong; Gan, Siming

2016-01-01

Identification of loci or genes under natural selection is important for both understanding the genetic basis of local adaptation and practical applications, and genome scans provide a powerful means for such identification purposes. In this study, genome-wide simple sequence repeats markers (SSRs) were used to scan for molecular footprints of divergent selection in Eucalyptus grandis, a hardwood species occurring widely in costal areas from 32° S to 16° S in Australia. High population diversity levels and weak population structure were detected with putatively neutral genomic SSRs. Using three FST outlier detection methods, a total of 58 outlying SSRs were collectively identified as loci under divergent selection against three non-correlated climatic variables, namely, mean annual temperature, isothermality and annual precipitation. Using a spatial analysis method, nine significant associations were revealed between FST outlier allele frequencies and climatic variables, involving seven alleles from five SSR loci. Of the five significant SSRs, two (EUCeSSR1044 and Embra394) contained alleles of putative genes with known functional importance for response to climatic factors. Our study presents critical information on the population diversity and structure of the important woody species E. grandis and provides insight into the adaptive responses of perennial trees to climatic variations. PMID:27748400

Forced Atlantic Multidecadal Variability Over the Past Millennium

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

Interannual variability in the atmospheric CO2 rectification over a boreal forest region

NASA Astrophysics Data System (ADS)

Chen, Baozhang; Chen, Jing M.; Worthy, Douglas E. J.

2005-08-01

Ecosystem CO2 exchange with the atmosphere and the planetary boundary layer (PBL) dynamics are correlated diurnally and seasonally. The strength of this kind of covariation is quantified as the rectifier effect, and it affects the vertical gradient of CO2 and thus the global CO2 distribution pattern. An 11-year (1990-1996, 1999-2002), continuous CO2 record from Fraserdale, Ontario (49°52'29.9″N, 81°34'12.3″W), along with a coupled vertical diffusion scheme (VDS) and ecosystem model named Boreal Ecosystem Productivity Simulator (BEPS), are used to investigate the interannual variability of the rectifier effect over a boreal forest region. The coupled model performed well (r2 = 0.70 and 0.87, at 40 m at hourly and daily time steps, respectively) in simulating CO2 vertical diffusion processes. The simulated annual atmospheric rectifier effect varies from 3.99 to 5.52 ppm, while the diurnal rectifying effect accounted for about a quarter of the annual total (22.8˜28.9%).The atmospheric rectification of CO2 is not simply influenced by terrestrial source and sink strengths, but by seasonal and diurnal variations in the land CO2 flux and their interaction with PBL dynamics. Air temperature and moisture are found to be the dominant climatic factors controlling the rectifier effect. The annual rectifier effect is highly correlated with annual mean temperature (r2 = 0.84), while annual mean air relative humidity can explain 51% of the interannual variation in rectification. Seasonal rectifier effect is also found to be more sensitive to climate variability than diurnal rectifier effect.

Mechanisms Controlling Global Mean Sea Surface Temperature Determined From a State Estimate

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Piecuch, C. G.

2018-04-01

Global mean sea surface temperature (T¯) is a variable of primary interest in studies of climate variability and change. The temporal evolution of T¯ can be influenced by surface heat fluxes (F¯) and by diffusion (D¯) and advection (A¯) processes internal to the ocean, but quantifying the contribution of these different factors from data alone is prone to substantial uncertainties. Here we derive a closed T¯ budget for the period 1993-2015 based on a global ocean state estimate, which is an exact solution of a general circulation model constrained to most extant ocean observations through advanced optimization methods. The estimated average temperature of the top (10-m thick) level in the model, taken to represent T¯, shows relatively small variability at most time scales compared to F¯, D¯, or A¯, reflecting the tendency for largely balancing effects from all the latter terms. The seasonal cycle in T¯ is mostly determined by small imbalances between F¯ and D¯, with negligible contributions from A¯. While D¯ seems to simply damp F¯ at the annual period, a different dynamical role for D¯ at semiannual period is suggested by it being larger than F¯. At periods longer than annual, A¯ contributes importantly to T¯ variability, pointing to the direct influence of the variable ocean circulation on T¯ and mean surface climate.

Implications for water use of a shift from annual to perennial crops - A stochastic modelling approach based on a trait meta-analysis

NASA Astrophysics Data System (ADS)

Vico, Giulia; Brunsell, Nathaniel

2017-04-01

The projected population growth and changes in climate and dietary habits will further increase the pressure on water resources globally. Within precision farming, a host of technical solutions has been developed to reduce water consumption for agricultural uses. The next frontier for a more sustainable agriculture is the combination of reduced water requirements with enhanced ecosystem services. Currently, staple grains are obtained from annuals crops. A shift from annual to perennial crops has been suggested as a way to enhance ecosystem services. In fact, perennial plants, with their continuous soil cover and the higher allocation of resources to the below ground, contribute to the reduction of soil erosion and nutrient losses, while enhancing carbon sequestration in the root zone. Nevertheless, the net effect of a shift to perennial crops on water use for agriculture is still unknown, despite its relevance for the sustainability of such a shift. We explore here the implications for water management at the field- to farm-scale of a shift from annual to perennial crops, under rainfed and irrigated agriculture. A probabilistic description of the soil water balance and crop development is employed to quantify water requirements and yields and their inter-annual variability, as a function of rainfall patterns, soil and crop features. Optimal irrigation strategies are thus defined in terms of maximization of yield and minimization of required irrigation volumes and their inter-annual variability. The probabilistic model is parameterized based on an extensive meta-analysis of traits of co-generic annual and perennial species to explore the consequences for water requirements of shifting from annual to perennial crops under current and future climates. We show that the larger and more developed roots of perennial crops may allow a better exploitation of soil water resources and a reduction of yield variability with respect to annual species. At the same time, perennial crops are larger and may require adequate water supply for longer periods, thus leading to higher water requirements. Furthermore, they lead to lower yields per unit area, thus requiring irrigation of larger areas.

An Investigation of the Hydroclimate Variability of Eastern Africa

NASA Astrophysics Data System (ADS)

Smith, K. A.; Semazzi, F. H. M.

2015-12-01

The flow of the Victoria Nile, and the productivity of the dams along it, is determined by the level of Lake Victoria, which is primarily dictated by the rainfall and temperature variability over the Lake Victoria Basin. Notwithstanding the indisputable decline of water resources over the lake basin during the Long Rains of March - May, there is a strong indication based on IPCC climate projections that this trend, which has persisted for several decades, will reverse in the next few decades. This phenomenon has come to be known as the Eastern-Central African climate change paradox and could have profound implications on sustainable development for the next few decades in Lake Victoria Basin. The purpose of this study is to investigate the climate variability associated with the East African Climate Change Paradox for the recent decades. This research analyzes observations to understand the sources of variability and potential physical mechanisms related to the decline in precipitation over Eastern Africa. We then investigate the hydrological factors involved in the decline of Lake Victoria levels in the context of the decline in rainfall. While East Africa has been experiencing persistent decline of the Long Rains for multiple decades, this same decline is not seen in annual rainfall. The remaining seasons show an increase in rainfall which is compensating for the decline of the Long Rains. It is possible that the Long Rains season is shifting in such a way that the season starts earlier, in February, and ending sooner. The corresponding annual Lake Victoria levels modeled using observed rainfall do not decline in the recent decades, except when the Long Rains seasonal variability is considered without variability from other seasons. This shift could impact hydroelectric power planning on a monthly or seasonal time scale, and could potentially have a large impact on agriculture, since it would shift the growing season in the region.

Climate-driven increase in the variability and multi-year mean level of severe thunderstorm-related losses and thunderstorm forcing environments in the U.S. since 1970

NASA Astrophysics Data System (ADS)

Sander, Julia; Eichner, Jan; Faust, Eberhard; Steuer, Markus

2013-04-01

In the year 2011, direct losses from thunderstorms reached US 26 billion (insured) and US 47 billion (economic), thus equalling the dimension of losses caused by Hurricane Sandy in the New York area 2012. Beyond doubt the 2011 damages had outlier characteristics due to two cities hit by tornadoes. Nonetheless a substantial increase in the variability of normalised direct economic and insured severe thunderstorm-related losses in the U.S. east of the Rocky Mountains over the period 1970-2009 (March - September) has been detected. Besides the annual variability, also the multi-year mean level of losses has strongly increased. Our study focused on sizeable severe thunderstorm events causing at least US 250 million in normalized economic losses. The high threshold guarantees homogeneity over time, because those events regularly covered several states and thus are very unlikely to have been missed at any time due to reporting variability. To shed light on the question whether the strong increase was driven by an external climate driver, the time series of normalized losses (annual counts and annual loss aggregate) was correlated with the time series of thunderstorm forcing environments. The latter were inferred from NCEP/NCAR reanalysis data and comprise 6-hourly CAPE and vertical wind shear data combined to form a variable called Thunderstorm Severity Potential (TSP). From the notable correlation found between the time series of normalized thunderstorm-related losses and meteorologically registered thunderstorm forcing environments (TSP) it could be inferred that climate was the dominant driver for the increase in variability and average level of thunderstorm-related losses over the period 1970-2009. An important component in the rise of TSP over time could be identified in CAPE, as we found a substantial rise in the annual number of exceedances of a high CAPE threshold in the reanalysis data. Recent studies imply that the changes observed in our study, particularly regarding an increase in high-level CAPE environments, are consistent with the modelled effects of anthropogenic climate change. The physical chain of climate change-driven increasing levels of specific humidity (Willett et al. 2010) leading to rising levels of CAPE as one of the preconditions of more severe thunderstorm forcing environments has already been established by measurements and climate model experiments (Trapp et al. 2007, 2009). Literature: Sander, J., J. Eichner, E. Faust, and M.Steuer, 2012: Rising variability in thunderstorm-related U.S. losses as a reflection of changes in large-scale thunderstorm forcing, submitted paper. Trapp, R. J., N. S. Diffenbaugh, H. E. Brooks, M. E. Baldwin, E. D. Robinson, and J. S. Pal, 2007: Changes in severe thunderstorm environment frequency during the 21st century caused by anthropogenically enhanced global radiative forcing. Proc. Natl. Acad. Sci. U.S.A., 104, 19719-19723. Trapp, R. J., N. S. Diffenbaugh, and A. Gluhovsky, 2009: Transient response of severe thunderstorm forcing to elevated greenhouse gas concentrations. Geophys. Res. Lett., 36, L01703, 6 pp., doi:10.1029/2008GL036203. Willett, K. M., P. D. Jones, P. W. Thorne, and N. P. Gillett, 2010: A comparison of large scale changes in surface humidity over land in observations and CMIP3 general circulation models. Environ. Res. Lett., 5, 025210, 13pp., doi:10.1088/1748-9326/5/2/025210.

Relative importance of precipitation frequency and intensity in inter-annual variation of precipitation in Singapore during 1980-2013

NASA Astrophysics Data System (ADS)

Li, Xin; Babovic, Vladan

2017-04-01

Observed studies on inter-annual variation of precipitation provide insight into the response of precipitation to anthropogenic climate change and natural climate variability. Inter-annual variation of precipitation results from the concurrent variations of precipitation frequency and intensity, understanding of the relative importance of frequency and intensity in the variability of precipitation can help fathom its changing properties. Investigation of the long-term changes of precipitation schemes has been extensively carried out in many regions across the world, however, detailed studies of the relative importance of precipitation frequency and intensity in inter-annual variation of precipitation are still limited, especially in the tropics. Therefore, this study presents a comprehensive framework to investigate the inter-annual variation of precipitation and the dominance of precipitation frequency and intensity in a tropical urban city-state, Singapore, based on long-term (1980-2013) daily precipitation series from 22 rain gauges. First, an iterative Mann-Kendall trend test method is applied to detect long-term trends in precipitation total, frequency and intensity at both annual and seasonal time scales. Then, the relative importance of precipitation frequency and intensity in inducing the inter-annual variation of wet-day precipitation total is analyzed using a dominance analysis method based on linear regression. The results show statistically significant upward trends in wet-day precipitation total, frequency and intensity at annual time scale, however, these trends are not evident during the monsoon seasons. The inter-annual variation of wet-day precipitation is mainly dominated by precipitation intensity for most of the stations at annual time scale and during the Northeast monsoon season. However, during the Southwest monsoon season, the inter-annual variation of wet-day precipitation is mainly dominated by precipitation frequency. These results have implications for water resources management practices in Singapore.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Relationship between annual precipitation variability and ENSO in Southern California for the Common Era (last 2,000 years)

NASA Astrophysics Data System (ADS)

DU, X.; Hendy, I. L.; Hinnov, L.; Brown, E. T.; Schimmelmann, A.; Pak, D. K.

2017-12-01

The El Niño-Southern Oscillation (ENSO) has a major influence on Southern California's hydroclimate as demonstrated by both historical observations and model simulations. Santa Barbara Basin (SBB) off Southern California preserves a unique varved (i.e. annually laminated) marine sedimentary archive of modern and Holocene hydroclimate variability, notably including the transition from the regionally dry Medieval Climate Anomaly (MCA) to the wetter Little Ice Age (LIA). Here we present sub-annually resolved scanning XRF elemental counts for the last 2,000 years in SBB from core SPR0901-03KC. Titanium (associated with silicate minerals) is delivered more efficiently to SBB sediments during times of enhanced river flow and in the Mediterranean climate of Southern California, river flow only occurs after precipitation. The Ti record suggests that the precipitation frequency was reduced during the MCA except for a pluvial episode at CE 1075-1121, but increased during the LIA. Time series analysis of Ti counts indicates ENSO variability robustly increased during the intervals CE 450-520, 650-720, 980-1150, 1380-1550 and 1720-1750, and experienced relatively quiescent intervals between CE 50-150, 250-400, 550-650, 750-950, 1150-1280 and 1580-1620. Generally the LIA in Southern California is characterized by more active ENSO variability with long periodicities (4-7 yr) and multi-decadal variability (54 yr). MCA drought episodes were associated with less active ENSO. Active ENSO variability in Southern California during the last 2,000 years coincided with reconstructed southward migration of the Intertropical Convergence Zone (ITCZ) suggesting the ITCZ may play a role in the waxing and waning of ENSO teleconnections between the central Pacific and the west coast of North America.

Evidence for Large Decadal Variability in the Tropical Mean Radiative Energy Budget

NASA Technical Reports Server (NTRS)

Wielicki, Bruce A.; Wong, Takmeng; Allan, Richard; Slingo, Anthony; Kiehl, Jeffrey T.; Soden, Brian J.; Gordon, C. T.; Miller, Alvin J.; Yang, Shi-Keng; Randall, David R.;

Precipitation variability on global pasturelands may affect food security in livestock-dependent regions

NASA Astrophysics Data System (ADS)

Sloat, L.; Gerber, J. S.; Samberg, L. H.; Smith, W. K.; West, P. C.; Herrero, M.; Brendan, P.; Cecile, G.; Katharina, W.; Smith, W. K.

2016-12-01

The need to feed an increasing number of people while maintaining biodiversity and ecosystem services is one of the key challenges currently facing humanity. Livestock systems are likely to be a crucial piece of this puzzle, as urbanization and changing diets in much of the world lead to increases in global meat consumption. This predicted increase in global demand for livestock products will challenge the ability of pastures and rangelands to maintain or increase their productivity. The majority of people that depend on animal production for food security do so through grazing and herding on natural rangelands, and these systems make a significant contribution to global production of meat and milk. The vegetation dynamics of natural forage are highly dependent on climate, and subject to disruption with changes in climate and climate variability. Precipitation heterogeneity has been linked to the ecosystem dynamics of grazing lands through impacts on livestock carrying capacity and grassland degradation potential. Additionally, changes in precipitation variability are linked to the increased incidence of extreme events (e.g. droughts, floods) that negatively impact food production and food security. Here, we use the inter-annual coefficient of variation (CV) of precipitation as a metric to assess climate risk on global pastures. Comparisons of global satellite measures of vegetation greenness to climate reveal that the CV of precipitation is negatively related to mean annual NDVI, such that areas with low year-to-year precipitation variability have the highest measures of vegetation greenness, and vice versa. Furthermore, areas with high CV of precipitation support lower livestock densities and produce less meat. A sliding window analysis of changes in CV of precipitation over the last century shows that, overall, precipitation variability is increasing in global pasture areas, although global maps reveal a patchwork of both positive and negative changes. We use this information to identify regions in which changes in the variability of precipitation may already be affecting the ability of grazing systems to support intensified livestock production, and assess the potential impacts of those changes on pasture productivity.

Climate and Southern Africa's Water-Energy-Food Nexus

NASA Astrophysics Data System (ADS)

Conway, D.; Osborn, T.; Dorling, S.; Ringler, C.; Lankford, B.; Dalin, C.; Thurlow, J.; Zhu, T.; Deryng, D.; Landman, W.; Archer van Garderen, E.; Krueger, T.; Lebek, K.

2014-12-01

Numerous challenges coalesce to make Southern Africa emblematic of the connections between climate and the water-energy-food nexus. Rainfall and river flows in the region show high levels of variability across a range of spatial and temporal scales. Physical and socioeconomic exposure to climate variability and change is high, for example, the contribution of electricity produced from hydroelectric sources is over 30% in Madagascar and Zimbabwe and almost 100% in the DRC, Lesotho, Malawi, and Zambia. The region's economy is closely linked with that of the rest of the African continent and climate-sensitive food products are an important item of trade. Southern Africa's population is concentrated in regions exposed to high levels of hydro-meteorological variability, and will increase rapidly over the next four decades. The capacity to manage the effects of climate variability tends, however, to be low. Moreover, with climate change annual precipitation levels, soil moisture and runoff are likely to decrease and rising temperatures will increase evaporative demand. Despite high levels of hydro-meteorological variability, the sectoral and cross-sectoral water-energy-food linkages with climate in Southern Africa have not been considered in detail. Lack of data and questionable reliability are compounded by complex dynamic relationships. We review the role of climate in Southern Africa's nexus, complemented by empirical analysis of national level data on climate, water resources, crop and energy production, and economic activity. Our aim is to examine the role of climate variability as a driver of production fluctuations in the nexus, and to improve understanding of the magnitude and temporal dimensions of their interactions. We first consider national level exposure of food, water and energy production to climate in aggregate economic terms and then examine the linkages between interannual and multi-year climate variability and economic activity, focusing on food and hydropower production. We then review the potential for connecting areas with robust seasonal climate forecasting skill with key precursors of economic output and conclude by identifying knowledge gaps in our understanding of regional and national economic linkages in the climate and water-energy-food nexus.

Dengue Dynamics in Binh Thuan Province, Southern Vietnam: Periodicity, Synchronicity and Climate Variability

PubMed Central

Thai, Khoa T. D.; Cazelles, Bernard; Nguyen, Nam Van; Vo, Long Thi; Boni, Maciej F.; Farrar, Jeremy; Simmons, Cameron P.; van Doorn, H. Rogier; de Vries, Peter J.

2010-01-01

Background Dengue is a major global public health problem with increasing incidence and geographic spread. The epidemiology is complex with long inter-epidemic intervals and endemic with seasonal fluctuations. This study was initiated to investigate dengue transmission dynamics in Binh Thuan province, southern Vietnam. Methodology Wavelet analyses were performed on time series of monthly notified dengue cases from January 1994 to June 2009 (i) to detect and quantify dengue periodicity, (ii) to describe synchrony patterns in both time and space, (iii) to investigate the spatio-temporal waves and (iv) to associate the relationship between dengue incidence and El Niño-Southern Oscillation (ENSO) indices in Binh Thuan province, southern Vietnam. Principal Findings We demonstrate a continuous annual mode of oscillation and a multi-annual cycle of around 2–3-years was solely observed from 1996–2001. Synchrony in time and between districts was detected for both the annual and 2–3-year cycle. Phase differences used to describe the spatio-temporal patterns suggested that the seasonal wave of infection was either synchronous among all districts or moving away from Phan Thiet district. The 2–3-year periodic wave was moving towards, rather than away from Phan Thiet district. A strong non-stationary association between ENSO indices and climate variables with dengue incidence in the 2–3-year periodic band was found. Conclusions A multi-annual mode of oscillation was observed and these 2–3-year waves of infection probably started outside Binh Thuan province. Associations with climatic variables were observed with dengue incidence. Here, we have provided insight in dengue population transmission dynamics over the past 14.5 years. Further studies on an extensive time series dataset are needed to test the hypothesis that epidemics emanate from larger cities in southern Vietnam. PMID:20644621

Stochastic variation in avian survival rates: Life-history predictions, population consequences, and the potential responses to human perturbations and climate change

USGS Publications Warehouse

Schmutz, Joel A.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Stochastic variation in survival rates is expected to decrease long-term population growth rates. This expectation influences both life-history theory and the conservation of species. From this expectation, Pfister (1998) developed the important life-history prediction that natural selection will have minimized variability in those elements of the annual life cycle (such as adult survival rate) with high sensitivity. This prediction has not been rigorously evaluated for bird populations, in part due to statistical difficulties related to variance estimation. I here overcome these difficulties, and in an analysis of 62 populations, I confirm her prediction by showing a negative relationship between the proportional sensitivity (elasticity) of adult survival and the proportional variance (CV) of adult survival. However, several species deviated significantly from this expectation, with more process variance in survival than predicted. For instance, projecting the magnitude of process variance in annual survival for American redstarts (Setophaga ruticilla) for 25 years resulted in a 44% decline in abundance without assuming any change in mean survival rate. For most of these species with high process variance, recent changes in harvest, habitats, or changes in climate patterns are the likely sources of environmental variability causing this variability in survival. Because of climate change, environmental variability is increasing on regional and global scales, which is expected to increase stochasticity in vital rates of species. Increased stochasticity in survival will depress population growth rates, and this result will magnify the conservation challenges we face.

Seasonal and Inter-annual Variation in Wood Production in Tropical Trees on Barro Colorado Island, Panama, is Related to Local Climate and Species Functional Traits

NASA Astrophysics Data System (ADS)

Cushman, K.; Muller-Landau, H. C.; Kellner, J. R.; Wright, S. J.; Condit, R.; Detto, M.; Tribble, C. M.

2015-12-01

Tropical forest carbon budgets play a major role in global carbon dynamics, but the responses of tropical forests to current and future inter-annual climatic variation remains highly uncertain. Better predictions of future tropical forest carbon fluxes require an improved understanding of how different species of tropical trees respond to changes in climate at seasonal and inter-annual temporal scales. We installed dendrometer bands on a size-stratified sample of 2000 trees in old growth forest on Barro Colorado Island, Panama, a moist lowland forest that experiences an annual dry season of approximately four months. Tree diameters were measured at the beginning and end of the rainy season since 2008. Additionally, we recorded the canopy illumination level, canopy intactness, and liana coverage of all trees during each census. We used linear mixed-effects models to evaluate how tree growth was related to seasonal and interannual variation in local climate, tree condition, and species identity, and how species identity effects related to tree functional traits. Climatic variables considered included precipitation, solar radiation, soil moisture, and climatological water deficit, and were all calculated from high-quality on-site measurements. Functional traits considered included wood density, maximum adult stature, deciduousness, and drought tolerance. We found that annual wood production was positively related to water availability, with higher growth in wetter years. Species varied in their response to seasonal water availability, with some species showing more pronounced reduction of growth during the dry season when water availability is limited. Interspecific variation in seasonal and interannual growth patterns was related to life-history strategies and species functional traits. The finding of higher growth in wetter years is consistent with previous tree ring studies conducted on a small subset of species with reliable annual rings. Together with previous findings that seed production at this site is higher in sunnier (and drier) years, this suggests strong climate-related shifts in allocation. This study highlights the importance of considering forest species composition and potential allocational shifts when predicting carbon fluxes in response to local climate variation.

Long-term growth-increment chronologies reveal diverse influences of climate forcing on freshwater and forest biota in the Pacific Northwest

USGS Publications Warehouse

Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Brim-Box, Jayne; Tepley, Alan J.

2015-01-01

Analyses of how organisms are likely to respond to a changing climate have focused largely on the direct effects of warming temperatures, though changes in other variables may also be important, particularly the amount and timing of precipitation. Here, we develop a network of eight growth-increment width chronologies for freshwater mussel species in the Pacific Northwest, United States and integrate them with tree-ring data to evaluate how terrestrial and aquatic indicators respond to hydroclimatic variability, including river discharge and precipitation. Annual discharge averaged across water years (October 1–September 30) was highly synchronous among river systems and imparted a coherent pattern among mussel chronologies. The leading principal component of the five longest mussel chronologies (1982–2003; PC1mussel) accounted for 47% of the dataset variability and negatively correlated with the leading principal component of river discharge (PC1discharge; r = −0.88; P < 0.0001). PC1mussel and PC1discharge were closely linked to regional wintertime precipitation patterns across the Pacific Northwest, the season in which the vast majority of annual precipitation arrives. Mussel growth was also indirectly related to tree radial growth, though the nature of the relationships varied across the landscape. Negative correlations occurred in forests where tree growth tends to be limited by drought while positive correlations occurred in forests where tree growth tends to be limited by deep or lingering snowpack. Overall, this diverse assemblage of chronologies illustrates the importance of winter precipitation to terrestrial and freshwater ecosystems and suggests that a complexity of climate responses must be considered when estimating the biological impacts of climate variability and change.

Long-term growth-increment chronologies reveal diverse influences of climate forcing on freshwater and forest biota in the Pacific Northwest.

PubMed

Black, Bryan A; Dunham, Jason B; Blundon, Brett W; Brim-Box, Jayne; Tepley, Alan J

2015-02-01

Analyses of how organisms are likely to respond to a changing climate have focused largely on the direct effects of warming temperatures, though changes in other variables may also be important, particularly the amount and timing of precipitation. Here, we develop a network of eight growth-increment width chronologies for freshwater mussel species in the Pacific Northwest, United States and integrate them with tree-ring data to evaluate how terrestrial and aquatic indicators respond to hydroclimatic variability, including river discharge and precipitation. Annual discharge averaged across water years (October 1-September 30) was highly synchronous among river systems and imparted a coherent pattern among mussel chronologies. The leading principal component of the five longest mussel chronologies (1982-2003; PC1(mussel)) accounted for 47% of the dataset variability and negatively correlated with the leading principal component of river discharge (PC1(discharge); r = -0.88; P < 0.0001). PC1(mussel) and PC1(discharge) were closely linked to regional wintertime precipitation patterns across the Pacific Northwest, the season in which the vast majority of annual precipitation arrives. Mussel growth was also indirectly related to tree radial growth, though the nature of the relationships varied across the landscape. Negative correlations occurred in forests where tree growth tends to be limited by drought while positive correlations occurred in forests where tree growth tends to be limited by deep or lingering snowpack. Overall, this diverse assemblage of chronologies illustrates the importance of winter precipitation to terrestrial and freshwater ecosystems and suggests that a complexity of climate responses must be considered when estimating the biological impacts of climate variability and change. © 2014 John Wiley & Sons Ltd.

Modeling drivers of phosphorus loads in Chesapeake Bay tributaries and inferences about long-term change

USGS Publications Warehouse

Ryberg, Karen R.; Blomquist, Joel; Sprague, Lori A.; Sekellick, Andrew J.; Keisman, Jennifer

2018-01-01

Causal attribution of changes in water quality often consists of correlation, qualitative reasoning, listing references to the work of others, or speculation. To better support statements of attribution for water-quality trends, structural equation modeling was used to model the causal factors of total phosphorus loads in the Chesapeake Bay watershed. By transforming, scaling, and standardizing variables, grouping similar sites, grouping some causal factors into latent variable models, and using methods that correct for assumption violations, we developed a structural equation model to show how causal factors interact to produce total phosphorus loads. Climate (in the form of annual total precipitation and the Palmer Hydrologic Drought Index) and anthropogenic inputs are the major drivers of total phosphorus load in the Chesapeake Bay watershed. Increasing runoff due to natural climate variability is offsetting purposeful management actions that are otherwise decreasing phosphorus loading; consequently, management actions may need to be reexamined to achieve target reductions in the face of climate variability.

Adaptation to climate through flowering phenology: a case study in Medicago truncatula.

PubMed

Burgarella, Concetta; Chantret, Nathalie; Gay, Laurène; Prosperi, Jean-Marie; Bonhomme, Maxime; Tiffin, Peter; Young, Nevin D; Ronfort, Joelle

2016-07-01

Local climatic conditions likely constitute an important selective pressure on genes underlying important fitness-related traits such as flowering time, and in many species, flowering phenology and climatic gradients strongly covary. To test whether climate shapes the genetic variation on flowering time genes and to identify candidate flowering genes involved in the adaptation to environmental heterogeneity, we used a large Medicago truncatula core collection to examine the association between nucleotide polymorphisms at 224 candidate genes and both climate variables and flowering phenotypes. Unlike genome-wide studies, candidate gene approaches are expected to enrich for the number of meaningful trait associations because they specifically target genes that are known to affect the trait of interest. We found that flowering time mediates adaptation to climatic conditions mainly by variation at genes located upstream in the flowering pathways, close to the environmental stimuli. Variables related to the annual precipitation regime reflected selective constraints on flowering time genes better than the other variables tested (temperature, altitude, latitude or longitude). By comparing phenotype and climate associations, we identified 12 flowering genes as the most promising candidates responsible for phenological adaptation to climate. Four of these genes were located in the known flowering time QTL region on chromosome 7. However, climate and flowering associations also highlighted largely distinct gene sets, suggesting different genetic architectures for adaptation to climate and flowering onset. © 2016 John Wiley & Sons Ltd.

Assessment of climate change impacts on runoff in China using climate elasticity and multiple CMIP5 GCMs

NASA Astrophysics Data System (ADS)

Wu, C.; Hu, B. X.; Wang, P.; Xu, K.

2017-12-01

The occurrence of climate warming is unequivocal and is expected to alter the temporal-spatial patterns of regional water resources. Based on the long-term (1960-2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results indicate a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from -2.3 to -0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. Climate projections suggest that there is large uncertainty involved among the GCM simulations, but most project a consistent change in P (or PET) over China at the mean annual scale. During the future period of 2071-2100, the mean annual P will likely increase in most parts of China particularly the western regions, while the mean annual PET will likely increase in the whole China especially the southern regions due to future increases in temperature. Moreover, larger increases are projected for higher emission scenarios. Compared with the baseline 1971-2000, the arid regions and humid regions of China will likely become wetter and drier in the period 2071-2100, respectively.

Growth-climate relationships across topographic gradients in the northern Great Lakes

USGS Publications Warehouse

Dymond, S.F.; D'Amato, A.W.; Kolka, R.K.; Bolstad, P.V.; Sebestyen, S.D.; Bradford, John B.

2016-01-01

Climatic conditions exert important control over the growth, productivity, and distribution of forests, and characterizing these relationships is essential for understanding how forest ecosystems will respond to climate change. We used dendrochronological methods to develop climate–growth relationships for two dominant species, Populus tremuloides (quaking aspen) and Pinus resinosa (red pine), in the upper Great Lakes region to understand how climate and water availability influence annual forest productivity. Trees were sampled along a topographic gradient at the Marcell Experimental Forest (Minnesota, USA) to assess growth response to variations in temperature and different water availability metrics (precipitation, potential evapotranspiration (PET), cumulative moisture index (CMI), and soil water storage). Climatic variables were able to explain 33–58% of the variation in annual growth (as measured by ring-width increment) for quaking aspen and 37–74% of the variation for red pine. Climate–growth relationships were influenced by topography for quaking aspen but not for red pine. Annual ring growth for quaking aspen decreased with June CMI on ridges, decreased with temperature in the November prior to the growing season on sideslopes, and decreased with June PET on toeslopes. Red pine growth increased with increasing July PET across all topographic positions. These results indicate the sensitivity of both quaking aspen and red pine to local climate and show several vulnerabilities of these species to shifts in water supply and temperature because of climate change.

Assessment of wildland fire impacts on watershed annual water yield: Analytical framework and case studies in the United States

Treesearch

Dennis W. Hallema; Ge Sun; Peter V. Caldwell; Steve Norman; Erika Cohen Mack; Yongqiang Liu; Eric J. Ward; Steve McNulty

2016-01-01

More than 50% of water supplies in the conterminous United States originate on forestland or rangeland, and are potentially under increasing stress as a result of larger and more severe wildfires. Little is known however about the long-term impacts of fire on annual water yield, and the role of climate variability within this context. We here propose a framework for...

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

PubMed

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

2017-10-01

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

Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom.

PubMed

Fodor, Nándor; Foskolos, Andreas; Topp, Cairistiona F E; Moorby, Jon M; Pásztor, László; Foyer, Christine H

2018-01-01

Dairy farming is one the most important sectors of United Kingdom (UK) agriculture. It faces major challenges due to climate change, which will have direct impacts on dairy cows as a result of heat stress. In the absence of adaptations, this could potentially lead to considerable milk loss. Using an 11-member climate projection ensemble, as well as an ensemble of 18 milk loss estimation methods, temporal changes in milk production of UK dairy cows were estimated for the 21st century at a 25 km resolution in a spatially-explicit way. While increases in UK temperatures are projected to lead to relatively low average annual milk losses, even for southern UK regions (<180 kg/cow), the 'hottest' 25×25 km grid cell in the hottest year in the 2090s, showed an annual milk loss exceeding 1300 kg/cow. This figure represents approximately 17% of the potential milk production of today's average cow. Despite the potential considerable inter-annual variability of annual milk loss, as well as the large differences between the climate projections, the variety of calculation methods is likely to introduce even greater uncertainty into milk loss estimations. To address this issue, a novel, more biologically-appropriate mechanism of estimating milk loss is proposed that provides more realistic future projections. We conclude that South West England is the region most vulnerable to climate change economically, because it is characterised by a high dairy herd density and therefore potentially high heat stress-related milk loss. In the absence of mitigation measures, estimated heat stress-related annual income loss for this region by the end of this century may reach £13.4M in average years and £33.8M in extreme years.

2000 Years of Drought Variability in Inner Asia from Tree Rings

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

2016-03-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Stochastic soil water balance under seasonal climates

PubMed Central

Feng, Xue; Porporato, Amilcare; Rodriguez-Iturbe, Ignacio

2015-01-01

The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude and the phase difference between the climatic forcings. The results provide accurate descriptions of probabilistic soil moisture dynamics under seasonal climates without requiring extensive numerical simulations. We also find that the transfer of soil moisture between the wet to the dry season is responsible for hysteresis in the hydrological response, showing asymmetrical trajectories in the mean soil moisture and in the transient Budyko's curves during the ‘dry-down‘ versus the ‘rewetting‘ phases of the year. Furthermore, in some dry climates where rainfall and potential evapotranspiration are in-phase, annual evapotranspiration can be shown to increase because of inter-seasonal soil moisture transfer, highlighting the importance of soil water storage in the seasonal context. PMID:25663808

Seasonal climate variability in historical and prehistorical times deduced from varved lake sediments: Calibration of records from Lakes Woseriner See and Tiefer See

NASA Astrophysics Data System (ADS)

Czymzik, Markus; Kienel, Ulrike; Dreibrodt, Stefan; Brauer, Achim

2013-04-01

Societies are susceptible to the effects of even short-term climate variations on water supply, health, and agricultural productivity. However, understanding of human-climate interactions is limited due to the lack of high-resolution climate records in space and time. Varved lake sediments provide long time-series of seasonal climate variability directly from populated areas that can be compared to historical and archeological records. Calibration against meteorological data enables process-based insights into sediment deposition within the lake that can be extrapolated into the past using transfer functions. Lakes Woseriner See (53°40'N/12°2'E; 37 m asl.) and Tiefer See (53°23'N/13°97'E, 65 m asl.) in northeastern Germany are located only 35 km apart. Situated within the former settlement areas, the lakes are well suited for studying climate influences on society related to the Neolithic Funnelbeaker culture or the Slavic colonization. Sub-recent annual laminations allow to establish climate proxy data-series at seasonal resolution that can be calibrated against the long meteorological record from the nearby City of Schwerin. Seasonal climate proxy data-series covering the last 90 years have been obtained from short sediment cores applying a combination of microfacies analyses, X-ray fluorescence scanning (µ-XRF), and varve counting. Main sediment microfacies in both lakes are endogenic calcite varves comprising calcite and organic layer couplets of varying thickness, diatom layers, and dispersed detrital grains. Calibration against meteorological data indicates that variations in sediment layer thickness and composition are not stationary through time but influenced by inter-annual variations in meteorological conditions.

Impact of climate change on potential evapotranspiration under a historical and future climate scenario in the Huang-Huai-Hai Plain, China

NASA Astrophysics Data System (ADS)

Liu, Qin; Yan, Changrong; Ju, Hui; Garré, Sarah

2018-04-01

Climate change is widely accepted to be one of the most critical problems faced by the Huang-Huai-Hai Plain (3H Plain), which is a region in which there is an over-exploitation of groundwater and where future warmer and drought conditions might intensify crop water demand. In this study, the spatiotemporal patterns of ET0 and primary driving meteorological variables were investigated based on a historical and RCP 8.5 scenario daily data set from 40 weather stations over the 3H Plain using linear regression, spline interpolation method, a partial derivative analysis, and multivariate regression. The results indicated a negative trend in all the analysed periods (except spring) of the past 54 years of which only summer and the entire year were statistically significant ( p < 0.01) with slopes of -1.09 and -1.29 mm a-1, respectively. In contrast, a positive trend was observed in all four seasons and the entire year under the RCP 8.5 scenario, with the biggest increment equal to 1.36 mm a-1 in summer and an annual increment of 3.37 mm a-1. The spatial patterns of the seasonal and annual ET0 exhibited the lowest values in southeastern regions and the highest values in northeastern parts of Shandong Province, probably because of the combined effects of various meteorological variables over the past 54 years. Relative humidity (RH) together with solar radiation (RS) were detected to be the main climatic factors controlling the reduction of ET0 in summer, autumn, and the entire year on the 3H Plain. ET0 in spring was mainly sensitive to changes in RS and RH, whereas ET0 in winter was most sensitive to changes in wind speed (WS) and decreased due to declining RH. Under the future RCP 8.5 scenario, the annual ET0 distribution displays a rich spatial structure with a clear northeast-west gradient and an area with low values in the southern regions, which is similarly detected in spring and summer. The most sensitive and primary controlling variables with respect to the increment of future ET0 are in the first place RS and then mean temperature in spring, while they turn to be mean temperature and then RS in summer. In autumn, future ET0 is most sensitive to RH changes. WS and RH are the controlling variables for ET0 in winter. Annual future ET0 is most sensitive to RH changes, and accordingly, RS is responsible for the predicted increment of the annual ET0. Better understanding of current and future spatiotemporal patterns of ET0 and of the regional response of ET0 to climate change can contribute to the establishment of a policy to realize a more efficient use of water resources and a sustainable agricultural production in the 3H Plain.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Climate Change of 4°C GlobalWarming above Pre-industrial Levels

NASA Astrophysics Data System (ADS)

Wang, Xiaoxin; Jiang, Dabang; Lang, Xianmei

2018-07-01

Using a set of numerical experiments from 39 CMIP5 climate models, we project the emergence time for 4°C global warming with respect to pre-industrial levels and associated climate changes under the RCP8.5 greenhouse gas concentration scenario. Results show that, according to the 39 models, the median year in which 4°C global warming will occur is 2084. Based on the median results of models that project a 4°C global warming by 2100, land areas will generally exhibit stronger warming than the oceans annually and seasonally, and the strongest enhancement occurs in the Arctic, with the exception of the summer season. Change signals for temperature go outside its natural internal variabilities globally, and the signal-tonoise ratio averages 9.6 for the annual mean and ranges from 6.3 to 7.2 for the seasonal mean over the globe, with the greatest values appearing at low latitudes because of low noise. Decreased precipitation generally occurs in the subtropics, whilst increased precipitation mainly appears at high latitudes. The precipitation changes in most of the high latitudes are greater than the background variability, and the global mean signal-to-noise ratio is 0.5 and ranges from 0.2 to 0.4 for the annual and seasonal means, respectively. Attention should be paid to limiting global warming to 1.5°C, in which case temperature and precipitation will experience a far more moderate change than the natural internal variability. Large inter-model disagreement appears at high latitudes for temperature changes and at mid and low latitudes for precipitation changes. Overall, the intermodel consistency is better for temperature than for precipitation.

Predictors of High Streamflow Events in the Fraser River Basin of British Columbia, Canada

NASA Astrophysics Data System (ADS)

Curry, C.

2016-12-01

The Fraser River basin (FRB) of British Columbia is one of the largest and most important watersheds in Western North America, and is home to a rich diversity of biological species and economic assets that depend implicitly upon its extensive riverine habitats. The hydrology of the FRB is dominated by snow accumulation and melt processes, leading to a prominent annual peak streamflow invariably occurring in June-July. However, while annual peak daily streamflow (APDF) during the spring freshet in the FRB is historically well correlated with basin-averaged, annual maximum snow water equivalent (SWEmax), there are numerous occurrences of anomalously large APDF in below- or near-normal SWEmax years, some of which have resulted in damaging floods in the region. An imperfect understanding of which other climatic factors contribute to these anomalously large APDFs complicates future projections of streamflow magnitude and frequency. We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by both observations and an ensemble of CMIP3 climate models in an attempt to discover the proximate causes of anomalous APDF events in the FRB. At several hydrometric stations representing a range of elevations, the relative importance of a set of predictors characterizing the magnitude and timing of rainfall, snowfall, and temperature is examined within a regression framework. The results indicate that next to the magnitude of SWEmax, the rate of warming subsequent to the date of SWEmax is the most influential variable for predicting APDF magnitudes in the lower FRB. Finally, the role of large-scale climate modes of variability for APDF magnitude and timing in the basin will be briefly discussed.

Seasonal dynamics of microbial community composition and function in oak canopy and open grassland soils

USGS Publications Warehouse

Waldrop, M.P.; Firestone, M.K.

2006-01-01

Soil microbial communities are closely associated with aboveground plant communities, with multiple potential drivers of this relationship. Plants can affect available soil carbon, temperature, and water content, which each have the potential to affect microbial community composition and function. These same variables change seasonally, and thus plant control on microbial community composition may be modulated or overshadowed by annual climatic patterns. We examined microbial community composition, C cycling processes, and environmental data in California annual grassland soils from beneath oak canopies and in open grassland areas to distinguish factors controlling microbial community composition and function seasonally and in association with the two plant overstory communities. Every 3 months for up to 2 years, we monitored microbial community composition using phospholipid fatty acid (PLFA) analysis, microbial biomass, respiration rates, microbial enzyme activities, and the activity of microbial groups using isotope labeling of PLFA biomarkers (13C-PLFA) . Distinct microbial communities were associated with oak canopy soils and open grassland soils and microbial communities displayed seasonal patterns from year to year. The effects of plant species and seasonal climate on microbial community composition were similar in magnitude. In this Mediterranean ecosystem, plant control of microbial community composition was primarily due to effects on soil water content, whereas the changes in microbial community composition seasonally appeared to be due, in large part, to soil temperature. Available soil carbon was not a significant control on microbial community composition. Microbial community composition (PLFA) and 13C-PLFA ordination values were strongly related to intra-annual variability in soil enzyme activities and soil respiration, but microbial biomass was not. In this Mediterranean climate, soil microclimate appeared to be the master variable controlling microbial community composition and function. ?? 2006 Springer Science+Business Media, Inc.

Hydrographical variability and major ecosystem changes as recorded in the growth of Arctica islandica from the northern North Sea

NASA Astrophysics Data System (ADS)

Trofimova, Tamara; Andersson, Carin; Bonitz, Fabian

2017-04-01

Reconstruction of marine climate variability on regional to global scales requires a network of climatically sensitive annually resolved archives from key oceanographic locations. The small number of records existing to date impedes the application of a network approach. In this study, we aim at improving the spatial coverage of annually resolved paleo proxy records by investigating the impact of climate variability on sclerochronological records of A. islandica from the Viking Bank in the northern North Sea. The northern North Sea has an excellent oceanographic setting because its hydrography is primarily controlled by the major Atlantic water inflow to the North Sea. Using annual growth increment measurements of 30 shells we constructed a 265-year shell-growth chronology spanning the time interval AD 1748-2013. Chronology statistics (Rbar (>0.5) and EPS (>0.85)) indicate a robust signal of a common environmental forcing controlling shell growth for the major part of the record. Comparison with other sclerochronologies from the oceanographically related locations reveals a coherency on longer time scales, which is likely a response to a common environmental driver or a combination of such drivers. No significant correlation on the year-on-year level has been found between the chronology and time series of temperature and salinity from the area close to the study site. However, the timing of major hydrographical anomalies described for the region (Great Salinity Anomalies) coincide with a decrease in shell growth; likely in response to an impact on lower trophic levels, i.e. plankton composition and abundance. Spectral analysis of the chronology reveals a 21-26 year periodicity recorded in the shell growth. The variability on a similar time scale has been observed in multiple records from the North Atlantic and in model outputs. It has been suggested to represent one of the dominant scales of multi-decadal variability especially pronounced prior to the 20th century. In our chronology this variability is clearly observed prior to the 1920's and fades out towards present day. This change coincides with the most significant regime shift in the North Atlantic observed in the 20th-century, connected with dramatic warming and increasing Atlantic inflow. Hence, our data show that growth chronology from the Viking Bank region has a high potential to be used in climate variability studies and can significantly contribute to the development of a spatial sclerochronological network.

Effect of inter-annual variability in pasture growth and irrigation response on farm productivity and profitability based on biophysical and farm systems modelling.

PubMed

Vogeler, Iris; Mackay, Alec; Vibart, Ronaldo; Rendel, John; Beautrais, Josef; Dennis, Samuel

2016-09-15

Farm system and nutrient budget models are increasingly being used in analysis to inform on farm decision making and evaluate land use policy options at regional scales. These analyses are generally based on the use of average annual pasture yields. In New Zealand (NZ), like in many countries, there is considerable inter-annual variation in pasture growth rates, due to climate. In this study a modelling approach was used to (i) include inter-annual variability as an integral part of the analysis and (ii) test the approach in an economic analysis of irrigation in a case study within the Hawkes Bay Region of New Zealand. The Agricultural Production Systems Simulator (APSIM) was used to generate pasture dry matter yields (DMY) for 20 different years and under both dryland and irrigation. The generated DMY were linked to outputs from farm-scale modelling for both Sheep and Beef Systems (Farmaxx Pro) and Dairy Systems (Farmax® Dairy Pro) to calculate farm production over 20 different years. Variation in DMY and associated livestock production due to inter-annual variation in climate was large, with a coefficient of variations up to 20%. Irrigation decreased this inter-annual variation. On average irrigation, with unlimited available water, increased income by $831 to 1195/ha, but when irrigation was limited to 250mm/ha/year income only increased by $525 to 883/ha. Using pasture responses in individual years to capturing the inter-annual variation, rather than the pasture response averaged over 20years resulted in lower financial benefits. In the case study income from irrigation based on an average year were 10 to >20% higher compared with those obtained from individual years. Copyright © 2016 Elsevier B.V. All rights reserved.

Fire history and fire-climate relationships in upper elevation forests of the southwestern United States

NASA Astrophysics Data System (ADS)

Margolis, Ellis Quinn

Fire history and fire-climate relationships of upper elevation forests of the southwestern United States are imperative for informing management decisions in the face of increased crown fire occurrence and climate change. I used dendroecological techniques to reconstruct fires and stand-replacing fire patch size in the Madrean Sky Islands and Mogollon Plateau. Reconstructed patch size (1685-1904) was compared with contemporary patch size (1996-2004). Reconstructed fires at three sites had stand-replacing patches totaling > 500 ha. No historical stand-replacing fire patches were evident in the mixed conifer/aspen forests of the Sky Islands. Maximum stand-replacing fire patch size of modern fires (1129 ha) was greater than that reconstructed from aspen (286 ha) and spruce-fir (521 ha). Undated spruce-fir patches may be evidence of larger (>2000ha) stand-replacing fire patches. To provide climatological context for fire history I used correlation and regionalization analyses to document spatial and temporal variability in climate regions, and El-Nino Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) and the Atlantic Multi-decadal Oscillation (AMO) teleconnections using 273 tree-ring chronologies (1732-1979). Four regions were determined by common variability in annual ring width. The component score time series replicate spatial variability in 20th century droughts (e.g., 1950's) and pluvials (e.g., 1910's). Two regions were significantly correlated with instrumental SOI and AMO, and three with PDO. Sub-regions within the southwestern U.S. varied geographically between the instrumental (1900-1979) and the pre-instrumental periods (1732-1899). Mapped correlations between ENSO, PDO and AMO, and tree-ring indices illustrate detailed sub-regional variability in the teleconnections. I analyzed climate teleconnections, and fire-climate relationships of historical upper elevation fires from 16 sites in 8 mountain ranges. I tested for links between Palmer Drought Severity Index and tree-ring reconstructed ENSO, PDO and AMO phases (1905-1978 and 1700-1904). Upper elevation fires (115 fires, 84 fire years, 1623-1904) were compared with climate indices. ENSO, PDO, and AMO affected regional PDSI, but AMO and PDO teleconnections changed between periods. Fire occurrence was significantly related to inter-annual variability in PDSI, precipitation, ENSO, and phase combinations of ENSO and PDO, but not AMO (1700-1904). Reduced upper elevation fire (1785-1840) was coincident with a cool AMO phase.

Climatic change controls productivity variation in global grasslands

PubMed Central

Gao, Qingzhu; Zhu, Wenquan; Schwartz, Mark W.; Ganjurjav, Hasbagan; Wan, Yunfan; Qin, Xiaobo; Ma, Xin; Williamson, Matthew A.; Li, Yue

2016-01-01

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms. PMID:27243565

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

High-resolution multi-model projections of onshore wind resources over Portugal under a changing climate

NASA Astrophysics Data System (ADS)

Nogueira, Miguel; Soares, Pedro M. M.; Tomé, Ricardo; Cardoso, Rita M.

2018-05-01

We present a detailed evaluation of wind energy density (WED) over Portugal, based on the EURO-CORDEX database of high-resolution regional climate model (RCM) simulations. Most RCMs showed reasonable accuracy in reproducing the observed near-surface wind speed. The climatological patterns of WED displayed large sub-regional heterogeneity, with higher values over coastal regions and steep orography. Subsequently, we investigated the future changes of WED throughout the twenty-first century, considering mid- and end-century periods, and two emission scenarios (RCP4.5 and RCP8.5). On the yearly average, the multi-model ensemble WED changes were below 10% (15%) under RCP4.5 (RCP8.5). However, the projected WED anomalies displayed strong seasonality, dominated by low positive values in summer (< 10% for both scenarios), negative values in winter and spring (up to - 10% (- 20%) under RCP4.5 (RCP8.5)), and stronger negative anomalies in autumn (up to - 25% (- 35%) under RCP4.5 (RCP8.5)). These projected WED anomalies displayed large sub-regional variability. The largest reductions (and lowest increases) are linked to the northern and central-eastern elevated terrain, and the southwestern coast. In contrast, the largest increases (and lowest reductions) are linked to the central-western orographic features of moderate elevation. The projections also showed changes in inter-annual variability of WED, with small increases for annual averages, but with distinct behavior when considering year-to-year variability over a specific season: small increases in winter, larger increases in summer, slight decrease in autumn, and no relevant change in spring. The changes in inter-annual variability also displayed strong dependence on the underlying terrain. Finally, we found significant model spread in the magnitude of projected WED anomalies and inter-annual variability, affecting even the signal of the changes.

Contingency in the Direction and Mechanics of Soil Organic Matter Responses to Increased Rainfall

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

Berhe, Asmeret A.; Suttle, K. Blake; Burton, Sarah D.

2012-09-03

Shifts in regional precipitation patterns will be a major component of global climate change. Rainfall will show greater and more variable changes in response to rising earth surface temperatures than most other climatic variables, and will be a major driver of ecosystem change. We studied the consequences of predicted changes in California’s rainy season for storage and stabilization mechanisms of soil organic matter (SOM). In a controlled and replicated experiment, we amended rainfall over large plots of natural grassland in accordance with alternative scenarios of future climate change. Results show that increases in annual rainfall have important consequences for soilmore » C storage, but that the strength and even direction of these effects depend entirely on seasonal timing. Rainfall increases during the winter rainy season led to pronounced C loss from soil while rainfall increases after the typical rainy season increased soil C stocks. Analysis of mineral-OM associations reveals a powerful mechanism underlying this difference: increased winter rainfall vastly diminished the role of Fe and Al oxides in SOM stabilization. Dithionite extractable crystalline Fe oxides explained more than 35 percent of the variability in C storage in ambient control and spring-addition treatments, compared to less than 0.01 percent in the winter-addition treatment. Likewise, poorly crystalline Fe and Al oxides explained more than 25 and 40 percent of the variability in C storage, respectively, in the control and spring-addition treatments compared to less than 5 percent in the -winter-addition treatment. Increases in annual precipitation identical in amount but at three-month offsets produced opposite effects on soil C storage. These results highlight the complexity inherent in biospheric feedbacks to the climate system, and the way that careful experimentation can penetrate that complexity to improve predictions of ecosystem and climatic change.« less

Can mountain glacier melting explains the GRACE-observed mass loss in the southeast Tibetan Plateau: From a climate perspective?

NASA Astrophysics Data System (ADS)

Song, Chunqiao; Ke, Linghong; Huang, Bo; Richards, Keith S.

2015-01-01

The southeast Tibetan Plateau (SETP) includes the majority of monsoonal temperate glaciers in High Mountain Asia (HMA), which is an important source of water for the upper reaches of several large Asian river systems. Climatic change and variability has substantial impacts on cryosphere and hydrological processes in the SETP. The Gravity Recovery and Climate Experiment (GRACE) gravimetry observations between 2003 and 2009 suggest that there was an average mass loss rate of - 5.99 ± 2.78 Gigatonnes (Gt)/yr in this region. Meanwhile, the hydrological data by model calculations from the GLDAS/Noah and CPC are used to estimate terrestrial water storage (TWS) changes with a slight negative trend of about - 0.3 Gt/yr. The recent studies (Kääb et al., 2012; Gardner et al., 2013) reported the thinning rates of mountain glaciers in HMA based on the satellite laser altimetry, and an approximate estimation of the glacier mass budget in the SETP was 4.69 ± 2.03 Gt/yr during 2003-2009. This estimate accounted for a large proportion ( 78.3%) of the difference between the GRACE TWS and model-calculated TWS changes. To better understand the cause of sharp mass loss existing in the SETP, the correlations between key climatic variables (precipitation and temperature) and the GRACE TWS changes are examined at different timescales between 2003 and 2011. The results show that precipitation is the leading factors of abrupt, seasonal and multi-year undulating signals of GRACE TWS anomaly time series, but with weak correlations with the inter-annual trend and annual mass budget of GRACE TWS. In contrast, the annual mean temperature is tightly associated with the annual net mass budget (r = 0.81, p < 0.01), which indirectly suggests that the GRACE-observed mass loss in the SETP may be highly related to glacial processes.

Climate variability slows evolutionary responses of Colias butterflies to recent climate change.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2015-03-07

How does recent climate warming and climate variability alter fitness, phenotypic selection and evolution in natural populations? We combine biophysical, demographic and evolutionary models with recent climate data to address this question for the subalpine and alpine butterfly, Colias meadii, in the southern Rocky Mountains. We focus on predicting patterns of selection and evolution for a key thermoregulatory trait, melanin (solar absorptivity) on the posterior ventral hindwings, which affects patterns of body temperature, flight activity, adult and egg survival, and reproductive success in Colias. Both mean annual summer temperatures and thermal variability within summers have increased during the past 60 years at subalpine and alpine sites. At the subalpine site, predicted directional selection on wing absorptivity has shifted from generally positive (favouring increased wing melanin) to generally negative during the past 60 years, but there is substantial variation among years in the predicted magnitude and direction of selection and the optimal absorptivity. The predicted magnitude of directional selection at the alpine site declined during the past 60 years and varies substantially among years, but selection has generally been positive at this site. Predicted evolutionary responses to mean climate warming at the subalpine site since 1980 is small, because of the variability in selection and asymmetry of the fitness function. At both sites, the predicted effects of adaptive evolution on mean population fitness are much smaller than the fluctuations in mean fitness due to climate variability among years. Our analyses suggest that variation in climate within and among years may strongly limit evolutionary responses of ectotherms to mean climate warming in these habitats. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Land-surface initialisation improves seasonal climate prediction skill for maize yield forecast.

PubMed

Ceglar, Andrej; Toreti, Andrea; Prodhomme, Chloe; Zampieri, Matteo; Turco, Marco; Doblas-Reyes, Francisco J

2018-01-22

Seasonal crop yield forecasting represents an important source of information to maintain market stability, minimise socio-economic impacts of crop losses and guarantee humanitarian food assistance, while it fosters the use of climate information favouring adaptation strategies. As climate variability and extremes have significant influence on agricultural production, the early prediction of severe weather events and unfavourable conditions can contribute to the mitigation of adverse effects. Seasonal climate forecasts provide additional value for agricultural applications in several regions of the world. However, they currently play a very limited role in supporting agricultural decisions in Europe, mainly due to the poor skill of relevant surface variables. Here we show how a combined stress index (CSI), considering both drought and heat stress in summer, can predict maize yield in Europe and how land-surface initialised seasonal climate forecasts can be used to predict it. The CSI explains on average nearly 53% of the inter-annual maize yield variability under observed climate conditions and shows how concurrent heat stress and drought events have influenced recent yield anomalies. Seasonal climate forecast initialised with realistic land-surface achieves better (and marginally useful) skill in predicting the CSI than with climatological land-surface initialisation in south-eastern Europe, part of central Europe, France and Italy.

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

NASA Astrophysics Data System (ADS)

Cannon, Alex J.

2018-01-01

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

Assessing the impacts of climate and land use and land cover change on the freshwater availability in the Brahmaputra River basin

USGS Publications Warehouse

Pervez, Md Shahriar; Henebry, Geoffrey M.

2015-01-01

New hydrological insights for the region: Basin average annual ET was found to be sensitive to changes in CO2 concentration and temperature, while total water yield, streamflow, and groundwater recharge were sensitive to changes in precipitation. The basin hydrological components were predicted to increase with seasonal variability in response to climate and land use change scenarios. Strong increasing trends were predicted for total water yield, streamflow, and groundwater recharge, indicating exacerbation of flooding potential during August–October, but strong decreasing trends were predicted, indicating exacerbation of drought potential during May–July of the 21st century. The model has potential to facilitate strategic decision making through scenario generation integrating climate change adaptation and hazard mitigation policies to ensure optimized allocation of water resources under a variable and changing climate.

A methodological critique on using temperature-conditioned resampling for climate projections as in the paper of Gerstengarbe et al. (2013) winter storm- and summer thunderstorm-related loss events in Theoretical and Applied Climatology (TAC)

NASA Astrophysics Data System (ADS)

Wechsung, Frank; Wechsung, Maximilian

2016-11-01

The STatistical Analogue Resampling Scheme (STARS) statistical approach was recently used to project changes of climate variables in Germany corresponding to a supposed degree of warming. We show by theoretical and empirical analysis that STARS simply transforms interannual gradients between warmer and cooler seasons into climate trends. According to STARS projections, summers in Germany will inevitably become dryer and winters wetter under global warming. Due to the dominance of negative interannual correlations between precipitation and temperature during the year, STARS has a tendency to generate a net annual decrease in precipitation under mean German conditions. Furthermore, according to STARS, the annual level of global radiation would increase in Germany. STARS can be still used, e.g., for generating scenarios in vulnerability and uncertainty studies. However, it is not suitable as a climate downscaling tool to access risks following from changing climate for a finer than general circulation model (GCM) spatial scale.

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set

NASA Astrophysics Data System (ADS)

Day, J. J.; Tietsche, S.; Collins, M.; Goessling, H. F.; Guemas, V.; Guillory, A.; Hurlin, W. J.; Ishii, M.; Keeley, S. P. E.; Matei, D.; Msadek, R.; Sigmond, M.; Tatebe, H.; Hawkins, E.

2015-10-01

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.

Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment.

PubMed

Zhang, Lei; Lu, Wenxi; An, Yonglei; Li, Di; Gong, Lei

2012-01-01

The impacts of climate change on streamflow and non-point source pollutant loads in the Shitoukoumen reservoir catchment are predicted by combining a general circulation model (HadCM3) with the Soil and Water Assessment Tool (SWAT) hydrological model. A statistical downscaling model was used to generate future local scenarios of meteorological variables such as temperature and precipitation. Then, the downscaled meteorological variables were used as input to the SWAT hydrological model calibrated and validated with observations, and the corresponding changes of future streamflow and non-point source pollutant loads in Shitoukoumen reservoir catchment were simulated and analyzed. Results show that daily temperature increases in three future periods (2010-2039, 2040-2069, and 2070-2099) relative to a baseline of 1961-1990, and the rate of increase is 0.63°C per decade. Annual precipitation also shows an apparent increase of 11 mm per decade. The calibration and validation results showed that the SWAT model was able to simulate well the streamflow and non-point source pollutant loads, with a coefficient of determination of 0.7 and a Nash-Sutcliffe efficiency of about 0.7 for both the calibration and validation periods. The future climate change has a significant impact on streamflow and non-point source pollutant loads. The annual streamflow shows a fluctuating upward trend from 2010 to 2099, with an increase rate of 1.1 m(3) s(-1) per decade, and a significant upward trend in summer, with an increase rate of 1.32 m(3) s(-1) per decade. The increase in summer contributes the most to the increase of annual load compared with other seasons. The annual NH (4) (+) -N load into Shitoukoumen reservoir shows a significant downward trend with a decrease rate of 40.6 t per decade. The annual TP load shows an insignificant increasing trend, and its change rate is 3.77 t per decade. The results of this analysis provide a scientific basis for effective support of decision makers and strategies of adaptation to climate change.

Coupled dynamics that determine the position and variability of the ITCZ

NASA Astrophysics Data System (ADS)

Xie, S.; Miyama, T.; Wang, Y.; Xu, H.; de Szoeke, S.

2006-05-01

The intertropical convergence zone (ITCZ) is displaced north of the equator in the eastern Pacific and Atlantic Oceans, as a result of asymmetry in continental geometry and air-sea interactions. This latitudinal asymmetry plays an important role in shaping the equatorial annual cycle, the seasonality of the equatorial mode in both the ocean basins, and the tropical Atlantic meridional mode. Despite its climatic importance, the northward- displaced ITCZ is poorly simulated in state-of-the-art global climate models, casting doubts on their simulations of the past and current climate and projection of future climate. A regional ocean-atmosphere model has been developed to study the effects of external influences (e.g., high- latitude cooling in the northern North Atlantic) and internal feedback on the Pacific ITCZ. The regional ocean- atmosphere model (ROAM) reproduces salient features of eastern Pacific climate, including a northward- displaced intertropical convergence zone (ITCZ) collocated with a zonal band of high SSTs, a low-cloud deck in the Southeast Pacific, the equatorial cold tongue and its annual cycle. The model climate - such as the position of the ITCZ, equatorial annual cycle and maximum SST - is sensitive to the treatment of low cloud. In another experiment where tropical North Atlantic SST is lowered by 2C, equatorial Pacific SST decreases by up to 3C in January-April but changes much less in other seasons, resulting in a weakened equatorial annual cycle. Central American mountains, poorly resolved in global models, appear to play an important role in this cross-basin interaction. The coupled dynamics of the ITCZ in the model and its utility to downscale coarse- resolution paleoclimate simulations will be discussed.

Including the dynamic relationship between climatic variables and leaf area index in a hydrological model to improve streamflow prediction under a changing climate

NASA Astrophysics Data System (ADS)

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

2015-06-01

Anthropogenic climate change is projected to enrich the atmosphere with carbon dioxide, change vegetation dynamics and influence the availability of water at the catchment scale. This study combines a nonlinear model for estimating changes in leaf area index (LAI) due to climatic fluctuations with the variable infiltration capacity (VIC) hydrological model to improve catchment streamflow prediction under a changing climate. The combined model was applied to 13 gauged sub-catchments with different land cover types (crop, pasture and tree) in the Goulburn-Broken catchment, Australia, for the "Millennium Drought" (1997-2009) relative to the period 1983-1995, and for two future periods (2021-2050 and 2071-2100) and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5) which were compared with the baseline historical period of 1981-2010. This region was projected to be warmer and mostly drier in the future as predicted by 38 Coupled Model Intercomparison Project Phase 5 (CMIP5) runs from 15 global climate models (GCMs) and for two emission scenarios. The results showed that during the Millennium Drought there was about a 29.7-66.3 % reduction in mean annual runoff due to reduced precipitation and increased temperature. When drought-induced changes in LAI were included, smaller reductions in mean annual runoff of between 29.3 and 61.4 % were predicted. The proportional increase in runoff due to modeling LAI was 1.3-10.2 % relative to not including LAI. For projected climate change under the RCP4.5 emission scenario, ignoring the LAI response to changing climate could lead to a further reduction in mean annual runoff of between 2.3 and 27.7 % in the near-term (2021-2050) and 2.3 to 23.1 % later in the century (2071-2100) relative to modeling the dynamic response of LAI to precipitation and temperature changes. Similar results (near-term 2.5-25.9 % and end of century 2.6-24.2 %) were found for climate change under the RCP8.5 emission scenario. Incorporating climate-induced changes in LAI in the VIC model reduced the projected declines in streamflow and confirms the importance of including the effects of changes in LAI in future projections of streamflow.

Fluctuations of cambial activity in relation to precipitation result in annual rings and intra-annual growth zones of xylem and phloem in teak (Tectona grandis) in Ivory Coast

PubMed Central

Dié, Agathe; Kitin, Peter; Kouamé, François N'Guessan; Van den Bulcke, Jan; Van Acker, Joris; Beeckman, Hans

2012-01-01

Background and Aims Teak forms xylem rings that potentially carry records of carbon sequestration and climate in the tropics. These records are only useful when the structural variations of tree rings and their periodicity of formation are known. Methods The seasonality of ring formation in mature teak trees was examined via correlative analysis of cambial activity, xylem and phloem formation, and climate throughout 1·5 years. Xylem and phloem differentiation were visualized by light microscopy and scanning electron microscopy. Key Results A 3 month dry season resulted in semi-deciduousness, cambial dormancy and formation of annual xylem growth rings (AXGRs). Intra-annual xylem and phloem growth was characterized by variable intensity. Morphometric features of cambium such as cambium thickness and differentiating xylem layers were positively correlated. Cambium thickness was strongly correlated with monthly rainfall (R2 = 0·7535). In all sampled trees, xylem growth zones (XGZs) were formed within the AXGRs during the seasonal development of new foliage. When trees achieved full leaf, the xylem in the new XGZs appeared completely differentiated and functional for water transport. Two phloem growth rings were formed in one growing season. Conclusions The seasonal formation pattern and microstructure of teak xylem suggest that AXGRs and XGZs can be used as proxies for analyses of the tree history and climate at annual and intra-annual resolution. PMID:22805529

EnviroAtlas - Biological nitrogen fixation in natural/semi-natural ecosystems by 12-digit HUC for the Conterminous United States, 2006

EPA Pesticide Factsheets

This EnviroAtlas dataset contains data on the mean biological nitrogen fixation in natural/semi-natural ecosystems per 12-digit Hydrologic Unit (HUC) in 2006. Biological N fixation (BNF) in natural/semi-natural ecosystems was estimated using a correlation with actual evapotranspiration (AET). This correlation is based on a global meta-analysis of BNF in natural/semi-natural ecosystems (Cleveland et al. 1999). AET estimates for 2006 were calculated using a regression equation describing the correlation of AET with climate (average annual daily temperature, average annual minimum daily temperature, average annual maximum daily temperature, and annual precipitation) and land use/land cover variables in the conterminous US (Sanford and Selnick 2013). Data describing annual average minimum and maximum daily temperatures and total precipitation for 2006 were acquired from the PRISM climate dataset (http://prism.oregonstate.edu). Average annual climate data were then calculated for individual 12-digit USGS Hydrologic Unit Codes (HUC12s; http://water.usgs.gov/GIS/huc.html; 22 March 2011 release) using the Zonal Statistics tool in ArcMap 10.0. AET for individual HUC12s was estimated using equations described in Sanford and Selnick (2013). BNF in natural/semi-natural ecosystems within individual HUC12s was modeled with an equation describing the statistical relationship between BNF (kg N ha-1 yr-1) and actual evapotranspiration (AET; cm yr-1) and scaled to the proportion

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

Bond-Lamberty, Benjamin; Bunn, Andrew G.; Thomson, Allison M.

High-latitude northern ecosystems are experiencing rapid climate changes, and represent a large potential climate feedback because of their high soil carbon densities and shifting disturbance regimes. A significant carbon flow from these ecosystems is soil respiration (RS, the flow of carbon dioxide, generated by plant roots and soil fauna, from the soil surface to atmosphere), and any change in the high-latitude carbon cycle might thus be reflected in RS observed in the field. This study used two variants of a machine-learning algorithm and least squares regression to examine how remotely-sensed canopy greenness (NDVI), climate, and other variables are coupled tomore » annual RS based on 105 observations from 64 circumpolar sites in a global database. The addition of NDVI roughly doubled model performance, with the best-performing models explaining ~62% of observed RS variability« less

Mars dust storms - Interannual variability and chaos

NASA Technical Reports Server (NTRS)

Ingersoll, Andrew P.; Lyons, James R.

1993-01-01

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

A CLIMATOLOGY OF TEMPERATURE AND PRECIPITATION VARIABILITY IN THE UNITED STATES

EPA Science Inventory

This paper examines the seasonal and variance and standardized range for temperature and the seasonal end annual coefficient of variation and normalized standardized range for precipitation, on a climatic division level for the contiguous United States for the period 1895 to 1985...

Agronomic responses to late-seeded cover crops in a semiarid region

USDA-ARS?s Scientific Manuscript database

Intensification of cropping systems in the Great Plains beyond annual cropping practices may be limited by inadequate precipitation, short growing seasons, and highly variable climatic conditions. Inclusion of cover crops in dryland cropping systems may serve as an effective intensification strateg...

Mid Pleistocene foraminiferal mass extinction coupled with phytoplankton evolution

PubMed Central

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

2016-01-01

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

The influence of multiyear drought on the annual rainfall-runoff relationship: An Australian perspective

NASA Astrophysics Data System (ADS)

Saft, Margarita; Western, Andrew W.; Zhang, Lu; Peel, Murray C.; Potter, Nick J.

2015-04-01

Most current long-term (decadal and longer) hydrological predictions implicitly assume that hydrological processes are stationary even under changing climate. However, in practice, we suspect that changing climatic conditions may affect runoff generation processes and cause changes in the rainfall-runoff relationship. In this article, we investigate whether temporary but prolonged (i.e., of the order of a decade) shifts in rainfall result in changes in rainfall-runoff relationships at the catchment scale. Annual rainfall and runoff records from south-eastern Australia are used to examine whether interdecadal climate variability induces changes in hydrological behavior. We test statistically whether annual rainfall-runoff relationships are significantly different during extended dry periods, compared with the historical norm. The results demonstrate that protracted drought led to a significant shift in the rainfall-runoff relationship in ˜44% of the catchment-dry periods studied. The shift led to less annual runoff for a given annual rainfall, compared with the historical relationship. We explore linkages between cases where statistically significant changes occurred and potential explanatory factors, including catchment properties and characteristics of the dry period (e.g., length, precipitation anomalies). We find that long-term drought is more likely to affect transformation of rainfall to runoff in drier, flatter, and less forested catchments. Understanding changes in the rainfall-runoff relationship is important for accurate streamflow projections and to help develop adaptation strategies to deal with multiyear droughts.

Constraining estimates of global soil respiration by quantifying sources of variability.

PubMed

Jian, Jinshi; Steele, Meredith K; Thomas, R Quinn; Day, Susan D; Hodges, Steven C

2018-05-10

Quantifying global soil respiration (R SG ) and its response to temperature change are critical for predicting the turnover of terrestrial carbon stocks and their feedbacks to climate change. Currently, estimates of R SG range from 68 to 98 Pg C year -1 , causing considerable uncertainty in the global carbon budget. We argue the source of this variability lies in the upscaling assumptions regarding the model format, data timescales, and precipitation component. To quantify the variability and constrain R SG , we developed R SG models using Random Forest and exponential models, and used different timescales (daily, monthly, and annual) of soil respiration (R S ) and climate data to predict R SG . From the resulting R SG estimates (range = 66.62-100.72 Pg), we calculated variability associated with each assumption. Among model formats, using monthly R S data rather than annual data decreased R SG by 7.43-9.46 Pg; however, R SG calculated from daily R S data was only 1.83 Pg lower than the R SG from monthly data. Using mean annual precipitation and temperature data instead of monthly data caused +4.84 and -4.36 Pg C differences, respectively. If the timescale of R S data is constant, R SG estimated by the first-order exponential (93.2 Pg) was greater than the Random Forest (78.76 Pg) or second-order exponential (76.18 Pg) estimates. These results highlight the importance of variation at subannual timescales for upscaling to R SG . The results indicated R SG is lower than in recent papers and the current benchmark for land models (98 Pg C year -1 ), and thus may change the predicted rates of terrestrial carbon turnover and the carbon to climate feedback as global temperatures rise. © 2018 John Wiley & Sons Ltd.

Temporal dynamics of groundwater-surface water interaction under the effects of climate change: A case study in the Kiskatinaw River Watershed, Canada

NASA Astrophysics Data System (ADS)

Saha, Gopal Chandra; Li, Jianbing; Thring, Ronald W.; Hirshfield, Faye; Paul, Siddhartho Shekhar

2017-08-01

Groundwater-surface water (GW-SW) interaction plays a vital role in the functioning of riparian ecosystem, as well as sustainable water resources management. In this study, temporal dynamics of GW-SW interaction were investigated under climate change. A case study was chosen for a study area along the Kiskatinaw River in Mainstem sub-watershed of the Kiskatinaw River Watershed, British Columbia, Canada. A physically based and distributed GW-SW interaction model, Gridded Surface Subsurface Hydrologic Analysis (GSSHA), was used. Two different greenhouse gas (GHG) emission scenarios (i.e., A2: heterogeneous world with self-reliance and preservation of local identities, and B1: more integrated and environmental friendly world) of SRES (Special Report on Emissions Scenarios) from Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) were used for climate change study for 2020-2040. The simulation results showed that climate change influences significantly the temporal patterns of GW-SW interaction by generating variable temporal mean groundwater contributions to streamflow. Due to precipitation variability, these contributions varied monthly, seasonally, and annually. The mean annual groundwater contribution to streamflow during 2020-2040 under the A2 and B1 scenarios is expected to be 74.5% (σ = 2%) and 75.6% (σ = 3%), respectively. As compared to that during the base modeling period (2007-2011), the mean annual groundwater contribution to streamflow during 2020-2040 under the A2 and B1 scenarios is expected to decrease by 5.5% and 4.4%, respectively, due to the increased precipitation (on average 6.7% in the A2 and 4.8% in the B1 scenarios) and temperature (on average 0.83 °C in the A2 and 0.64 °C in the B1 scenarios). The results obtained from this study will provide useful information in the long-term seasonal and annual water extractions from the river for future water supply, as well as for evaluating the ecological conditions of the stream, which will be beneficial to aquatic ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Effects of climate variability on forest hydrology and carbon sequestration on the Santee Experimental Forest in coastal South Carolina

Treesearch

Zhaohua Dai; Carl C. Trettin; Devendra M. Amatya

2013-01-01

Long-term weather and hydrology data from the Santee Experimental Forest were used to assess trends in air temperature, precipitation, and the water balance in gauged watersheds over a 63-year period. Since 1946, the mean annual air temperature has increased at a rate of 0.19 °C per decade, a rate higher than the global mean for the same period. Total annual...

Impacts of climate variability and change on crop yield in sub-Sahara Africa

NASA Astrophysics Data System (ADS)

Pan, S.; Zhang, J.; Yang, J.; Chen, G.; Xu, R.; Zhang, B.; Lou, Y.

2017-12-01

Much concern has been raised about the impacts of climate change and climate extremes on Africa's food security. The impact of climate change on Africa's agriculture is likely to be severe compared to other continents due to high rain-fed agricultural dependence, and limited ability to mitigate and adapt to climate change. In recent decades, warming in Africa is more pronounced and faster than the global average and this trend is likely to continue in the future. However, quantitative assessment on impacts of climate extremes and climate change on crop yield has not been well investigated yet. By using an improved agricultural module of the Dynamic Land Ecosystem Model (DLEM-AG2) driven by spatially-explicit information on land use, climate and other environmental changes, we have assessed impacts of historical climate variability and future climate change on food crop yield across the sub-Sahara Africa during1980-2016 and the rest of the 21st century (2017-2099). Our simulated results indicate that African crop yield in the past three decades shows an increasing trend primarily due to cropland expansion. However, crop yield shows substantially spatial and temporal variation due to inter-annual and inter-decadal climate variability and spatial heterogeneity of environmental drivers. Droughts have largely reduced crop yield in the most vulnerable regions of Sub-Sahara Africa. Future projections with DLEM-AG2 show that food crop production in Sub-Sahara Africa would be favored with limiting end-of-century warming to below 1.50 C.

Hydrological Footprints of Urban Developments in the Lake Simcoe Watershed, Canada: A Combined Paired-Catchment and Change Detection Modeling Approach

NASA Astrophysics Data System (ADS)

Oni, S. K.; Futter, M. N.; Buttle, J. M.; Dillon, P.

2014-12-01

Urban sprawl and regional climate variability are major stresses on surface water resources in many places. The Lake Simcoe watershed (LSW) Ontario, Canada, is no exception. The LSW is predominantly agricultural but is experiencing rapid population growth due to its proximity to the greater Toronto area. This has led to extensive land use changes which have impacted its water resources and altered runoff patterns in some rivers draining to the lake. Here, we use a paired-catchment approach, hydrological change detection modelling and remote sensing analysis of satellite images to evaluate the impacts of land use change on the hydrology of the LSW (1994 to 2008). Results show that urbanization increased up to 16% in Lovers Creek, the most-urban impacted catchment. Annual runoff from Lovers Creek increased from 239 to 442 mm/yr in contrast to the reference catchment (Black River at Washago) where runoff was relatively stable with an annual mean of 474 mm/yr. Increased annual runoff from Lovers Creek was not accompanied by an increase in annual precipitation. Discriminant function analysis suggests that early (1992-1997; pre-major development) and late (2004-2009; fully urbanized) periods for Lovers Creek separated mainly based on model parameter sets related to runoff flashiness and evapotranspiration. As a result, parameterization in either period cannot be used interchangeably to produce credible runoff simulations in Lovers Creek due to greater scatter between the parameters in canonical space. Separation of early and late period parameter sets for the reference catchment was based on climate and snowmelt related processes. This suggests that regional climatic variability could be influencing hydrologic change in the reference catchment whereas urbanization amplified the regional natural hydrologic changes in urbanizing catchments of the LSW.

Impact of Climate Change on Energy Demand in the Midwestern USA

NASA Astrophysics Data System (ADS)

Yan, M. B.; Zhang, F.; Franklin, M.; Kotamarthi, V. R.

2008-12-01

The impact of climate change on energy demand and use is a significant issue for developing future GHG emission scenarios and developing adaptation and mitigation strategies. A number of studies have evaluated the increase in GHG emissions as a result of changes in energy production from fossil fuels, but the consequences of climate change on energy consumption have not been the focus of many studies. Here we focus on the impacts of climate change on energy use at a regional scale using the Midwestern USA as a test. The paper presents results of analyzing energy use in response to ambient temperature changes in a 17-year period from 1989 to 2006 and projection of energy use under future climate scenarios (2010-2061). This study consisted of a two-step procedure. In the first step, sensitivity of historic energy demand, specifically electricity and natural gas in residential and commercial sectors (42% of end-use energy), with respect to many climatic and non-climatic variables was examined. State-specific regression models were developed to quantify the relationship between energy use and climatic variables using degree days. We found that model parameters and base temperatures for estimating heating and cooling days varied by state and energy sector, mainly depending on climate conditions, infrastructure, economic factors, and seasonal change in energy use. In the second step, we applied these models to predict future energy demand using output data generated by the Community Climate System Model (CCSM) for the SRES A1B scenario used in the IPCC AR-4. The annual demands of electricity and natural gas were predicted for each state from 2010 to 2061. The model results indicate that the average annual electricity demand will increase 3%-5% for the southern states and 1%-3% for the northern states in the region by 2061 and that the demand for natural gas is expected to be reduced in all states. A seasonal analysis of energy distribution in response to climate variables identifies a significant peak in demand in July-August (11%-16% in southern states and 6%-10% in the northern states). These findings suggest that the energy sector is vulnerable to climate change even in the northern Midwest region of the US. Furthermore, we demonstrate that a state-level assessment can help to better identify adaptation strategies for future regional energy sector changes.

Evaluation of surface water budget and assessment the global water cycle for the IPCC AR4 A1B scenario simulations

NASA Astrophysics Data System (ADS)

Baek, H.; Park, E.; Kwon, W.

2009-12-01

Water balance calculations are becoming increasingly important for earth-system studies, because humans require water for their survival. Especially, the relationship between climate change and freshwater resources is of primary concern to human society and also has implications for all living species. The goal of this study is to assess the closure and annual variations of the water cycles based on the multi-model ensemble approach. In this study, the projection results of the previous works focusing on global and six sub-regions are updated using sixteen atmosphere-ocean general circulation model (AOGCM) simulations based on the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. Before projecting future climate, model performances are evaluated on the simulation of the present-day climate. From the result, we construct and use mainly multi-model ensembles (MMEs), which is referred to as MME9, defined from nine selected AOGCMs of higher performance. Analyzed variables include annual and seasonal precipitation, evaporation, and runoff. The overall projection results from MME9 show that most regions will experience warmer and wetter climate at the end of 21st century. The evaporation shows a very similar trend to precipitation, but not in the runoff projection. The internal and inter-model variabilities are larger in the runoff than both precipitation and evaporation. Moreover, the runoff is notably reduced in Europe at the end of 21st century.

Confronting the demand and supply of snow seasonal forecasts for ski resorts : the case of French Alps

NASA Astrophysics Data System (ADS)

Dubois, Ghislain

2017-04-01

Alpine ski resorts are highly dependent on snow, which availability is characterized by a both a high inter-annual variability and a gradual diminution due to climate change. Due to this dependency to climatic resources, the ski industry is increasingly affected by climate change: higher temperatures limit snow falls, increase melting and limit the possibilities of technical snow making. Therefore, since the seventies, managers drastically improved their practices, both to adapt to climate change and to this inter-annual variability of snow conditions. Through slope preparation and maintenance, snow stock management, artificial snow making, a typical resort can approximately keep the same season duration with 30% less snow. The ski industry became an activity of high technicity The EUPORIAS FP7 (www.euporias.eu) project developed between 2012 and 2016 a deep understanding of the supply and demand conditions for the provision of climate services disseminating seasonal forecasts. In particular, we developed a case study, which allowed conducting several activities for a better understanding of the demand and of the business model of future services applied to the ski industry. The investigations conducted in France inventoried the existing tools and databases, assessed the decision making process and data needs of ski operators, and provided evidences that some discernable skill of seasonal forecasts exist. This case study formed the basis of the recently funded PROSNOW H2020 project. We will present the main results of EUPORIAS project for the ski industry.

Temporal Variation of NDVI and the Drivers of Climate Variables in the Arctic Tundra Transition Zone

NASA Astrophysics Data System (ADS)

Lee, J.; Ryu, Y.; Lee, Y. K.

2016-12-01

The Arctic is a sensitive region to temperature, which is drastically increasing with climate change. Vegetation in transition zones of the sub-arctic tundra biome are most sensitive to the warming climate, as temperature in the Arctic ecosystem is one of important limiting factors of vegetation growth and decomposition. Previous research in the transition zone show that there is a difference of sensible heat flux (21 Wm-2), Leaf Area Index increase from 0.58 - 2.76 and canopy height from 0.1 - 6.1m across dwarf and tall shrubs to forest, however, we lack understanding of NDVI trend of this zone. To better understand the vegetation in transition zones of the arctic ecosystem, we analyze the long-term trend of NDVI (AVHRR 3g GIMMs data), temperature and precipitation (Climate Research Unit data) trend from 1982 - 2010 in Council, Alaska that is a region where arctic tundra is transitioning to boreal forest. We also analyze how the climatic factors, temperature or precipitation, affect NDVI. Annual precipitation had the highest interannual variability compared to temperature and NDVI. There was an overall decreasing trend of annual maximum NDVI (y = -0.0019x+4.7). During 1982 to 2003, NDVI and temperature had a similar pattern, but when temperature suddenly jumped to 13.2°C in 2004, NDVI and precipitation declined. This study highlights that temperature increase does not always lead to greening, but after a certain threshold they may cause damage to sub-arctic tundra vegetation.

Climatic-Induced Shifts in the Distribution of Teak ( Tectona grandis) in Tropical Asia: Implications for Forest Management and Planning

NASA Astrophysics Data System (ADS)

Deb, Jiban Chandra; Phinn, Stuart; Butt, Nathalie; McAlpine, Clive A.

2017-09-01

Modelling the future suitable climate space for tree species has become a widely used tool for forest management planning under global climate change. Teak ( Tectona grandis) is one of the most valuable tropical hardwood species in the international timber market, and natural teak forests are distributed from India through Myanmar, Laos and Thailand. The extents of teak forests are shrinking due to deforestation and the local impacts of global climate change. However, the direct impacts of climate changes on the continental-scale distributions of native and non-native teak have not been examined. In this study, we developed a species distribution model for teak across its entire native distribution in tropical Asia, and its non-native distribution in Bangladesh. We used presence-only records of trees and twelve environmental variables that were most representative for current teak distributions in South and Southeast Asia. MaxEnt (maximum entropy) models were used to model the distributions of teak under current and future climate scenarios. We found that land use/land cover change and elevation were the two most important variables explaining the current and future distributions of native and non-native teak in tropical Asia. Changes in annual precipitation, precipitation seasonality and annual mean actual evapotranspiration may result in shifts in the distributions of teak across tropical Asia. We discuss the implications for the conservation of critical teak habitats, forest management planning, and risks of biological invasion that may occur due to its cultivation in non-native ranges.

Making the best of climatic variability: options for upgrading rainfed farming in water scarce regions.

PubMed

Rockström, J

2004-01-01

Coping with climatic variability for livelihood security is part of everyday life for rural communities in semi-arid and dry sub-humid savannas. Water scarcity caused by rainfall fluctuations is common, causing meteorological droughts and dry spells. However, this paper indicates, based on experiences in sub-Saharan Africa and India, that the social impact on rural societies of climatically induced droughts is exaggerated. Instead, water scarcity causing food deficits is more often caused by management induced droughts and dry spells. A conceptual framework to distinguish between manageable and unmanageable droughts is presented. It is suggested that climatic droughts require focus on social resilience building instead of land and water resource management. Focus is then set on the manageable part of climatic variability, namely the almost annual occurrence of dry spells, short 2-4 week periods of no rainfall, affecting farmer yields. On-farm experiences in savannas of sub-Saharan Africa of water harvesting systems for dry spell mitigation are presented. It is shown that bridging dry spells combined with soil fertility management can double and even triple on-farm yield levels. Combined with innovative systems to ensure maximum plant water availability and water uptake capacity, through adoption of soil fertility improvement and conservation tillage systems, there is a clear opportunity to upgrade rainfed farming systems in vulnerable savanna environments, through appropriate local management of climatic variability.

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Phenology of Honey Bee Swarm Departure in New Jersey, United States.

PubMed

Gilley, D C; Courtright, T J; Thom, C

2018-03-31

Departure of swarms from honey bee (Apis mellifera Linnaeus (Hymenoptera: Apidae)) nests is an important reproductive event for wild honey bee colonies and economically costly in managed bee colonies. The seasonal timing of swarm departure varies regionally and annually, creating challenges for honey bee management and emphasizing the potential for swarming behavior to be affected by plant-pollinator phenological mismatch. In this study, we first document variability in the timing of swarm departure across the large and heterogeneous geographical area of New Jersey over 4 years using 689 swarm-cluster observations. Second, hypothesizing that honey bee colonies adaptively tune the timing of swarm departure to match floral food-resource availability, we predicted that growing degree-days could be used to account for regional and annual variability. To test this idea, we used local weather records to determine the growing degree-day on which each swarm cluster was observed and tested for differences among climate regions and years. The state-wide mean swarm cluster date was May 15 (± 0.6 d), with moderate but significant differences among the state's five climate regions and between years. Use of degree-day information suggests that local heat accumulation can account for some climate-region differences in swarm-departure timing. Annual variation existed on a scale of only several days and was not accounted for by growing degree-days, suggesting little adaptive tuning of swarm-departure timing with respect to local heat accumulation.

A Study of Spatio-Temporal Variability in Future Wind Energy over the Korean Peninsula Using Regional Climate Model Ensemble Projections

NASA Astrophysics Data System (ADS)

KIM, Y.; Lim, Y. J.; Kim, Y. H.; Kim, B. J.

2015-12-01

The impacts of climate change on wind speed, wind energy density (WED), and potential electronic production (PEP) over the Korean peninsula have been investigated by using five regional climate models (HadGEM3-RA, RegCM, WRF, GRIMs and MM5) ensemble projection data. HadGEM2-AO based two RCP scenarios (RCP4.5/8.5) data have been used for initial and boundary condition to all RCMs. Wind energy density and its annual and seasonal variability have been estimated based on monthly near-surface wind speeds, and the potential electronic production and its change have been also analyzed. As a result of comparison ensemble models based annual mean wind speed for 25-yr historical period (1981-2005) to the ERA-interim, it is shown that all RCMs overestimate near-surface wind speed compared to the reanalysis data but the results of HadGEM3-RA are most comparable. The changes annual and seasonal mean of WED and PEP for the historical period and comparison results to future projection (2021-2050) will be presented in this poster session. We also scrutinize the changes in mean sea level pressure and mean sea level pressure gradient in driving GCM/RCM as a factor inducing the variations. Our results can be used as a background data for devising a plan to develop and operate wind farm over the Korean Peninsula.

Climatic controls of vegetation vigor in four contrasting forest types of India--evaluation from National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer datasets (1990-2000).

PubMed

Prasad, V Krishna; Anuradha, E; Badarinath, K V S

2005-09-01

Ten-day advanced very high resolution radiometer images from 1990 to 2000 were used to examine spatial patterns in the normalized difference vegetation index (NDVI) and their relationships with climatic variables for four contrasting forest types in India. The NDVI signal has been extracted from homogeneous vegetation patches and has been found to be distinct for deciduous and evergreen forest types, although the mixed-deciduous signal was close to the deciduous ones. To examine the decadal response of the satellite-measured vegetation phenology to climate variability, seven different NDVI metrics were calculated using the 11-year NDVI data. Results suggested strong spatial variability in forest NDVI metrics. Among the forest types studied, wet evergreen forests of north-east India had highest mean NDVI (0.692) followed by evergreen forests of the Western Ghats (0.529), mixed deciduous forests (0.519) and finally dry deciduous forests (0.421). The sum of NDVI (SNDVI) and the time-integrated NDVI followed a similar pattern, although the values for mixed deciduous forests were closer to those for evergreen forests of the Western Ghats. Dry deciduous forests had higher values of inter-annual range (RNDVI) and low mean NDVI, also coinciding with a high SD and thus a high coefficient of variation (CV) in NDVI (CVNDVI). SNDVI has been found to be high for wet evergreen forests of north-east India, followed by evergreen forests of the Western Ghats, mixed deciduous forests and dry deciduous forests. Further, the maximum NDVI values of wet evergreen forests of north-east India (0.624) coincided with relatively high annual total precipitation (2,238.9 mm). The time lags had a strong influence in the correlation coefficients between annual total rainfall and NDVI. The correlation coefficients were found to be comparatively high (R2=0.635) for dry deciduous forests than for evergreen forests and mixed deciduous forests, when the precipitation data with a lag of 30 days was correlated against NDVI. Using multiple regression approach models were developed for individual forest types using 16 different climatic indices. A high proportion of the temporal variance (>90%) has been accounted for by three of the precipitation parameters (maximum precipitation, precipitation of the wettest quarter and driest quarter) and two of the temperature parameters (annual mean temperature and temperature of the coldest quarter) for mixed deciduous forests. Similarly, in the case of deciduous forests, four precipitation parameters and three temperature parameters explained nearly 83.6% of the variance. These results suggest differences in the relationship between NDVI and climatic variables based upon the time of growing season, time interval and climatic indices over which they were summed. These results have implications for forest cover mapping and monitoring in tropical regions of India.

Paleoclimatological perspective on the hydrometeorology of the Mekong Basin

NASA Astrophysics Data System (ADS)

Räsänen, T. A.; Lehr, C.; Mellin, I.; Ward, P. J.; Kummu, M.

2012-11-01

During recent decades the Mekong River has experienced substantial interannual variations between droughts and major floods. The causes of these variations have been sought in climate change and dam construction. However, so far little research has addressed whether these recent variations are significantly different to long-term variations in the past. Hence, the aim of our paper is to place the recent variations between droughts and floods into a historical and paleoclimatological context. To achieve this we analysed the Mekong's meteorological conditions over the period 1300-2005 with a basin scale approach by using the Monsoon Asia Drought Atlas (MADA), which is a Palmer Drought Severity Index (PDSI) dataset derived from tree-ring growth records. The correlation analyses, both in time and frequency domains, showed correlation between MADA and the Mekong's discharge over the period 1910-2005 which suggests that MADA can be used as proxy for the hydrometeorology of the Mekong Basin. We found that the meteorological conditions of the Mekong varied at multi-annual, decadal and centennial scales over the study period. We found two especially distinct features: firstly, multi-annual and decadal variation between prolonged wet and dry epochs; and secondly, epochs with higher or lower interannual variability between very dry and wet years. Furthermore we found two epochs with exceptionally large interannual variability, one at the beginning of 17th century and the other in the post 1950 epoch. Both epochs are characterized by distinct increases in variability between very wet and dry years. The variability in the post 1950 epoch is much higher compared to any of the other epochs included in this study. Thus, during recent decades the climate in the Mekong has exhibited features that have not been experienced for at least several centuries. These findings call for further climate research, particularly regarding increased climate variability, and resilient adaptation and development approaches in the basin.

Climatic variability in the eastern United States over the past millenium from Chesapeake Bay sediments

USGS Publications Warehouse

Cronin, T.; Willard, D.; Karlsen, A.; Ishman, S.; Verardo, S.; McGeehin, J.; Kerhin, R.; Holmes, C.; Colman, S.; Zimmerman, A.

2000-01-01

Salinity oscillations caused by multidecadal climatic variability had major impacts on the Chesapeake Bay estuarine ecosystem during the past 1000 yr. Microfossils from sediments dated by radiometry (14C, 137Cs, 210Pb) and pollen stratigraphy indicate that salinity in mesohaline regions oscillated 10-15 ppt during periods of extreme drought (low fresh-water discharge) and wet climate (high discharge). During the past 500 yr, 14 wet-dry cycles occurred, including sixteenth and early seventeenth century megadroughts that exceeded twentieth century droughts in their severity. These droughts correspond to extremely dry climate also recorded in North American tree-ring records and by early colonists. Wet periods occurred every ~60-70 yr, began abruptly, lasted <20 yr, and had mean annual rainfall ~25%-30% and fresh-water discharge ~40%-50% greater than during droughts. A shift toward wetter regional climate occurred in the early nineteenth century, lowering salinity and compounding the effects of agricultural land clearance on bay ecosystems.

Wildland fire and climate variability impacts on annual streamflow in watersheds across the continental United States: Regional patterns and attribution analysis

NASA Astrophysics Data System (ADS)

Hallema, D. W.; Sun, G.; Caldwell, P. V.; Norman, S. P.; Cohen, E. C.; Liu, Y.; McNulty, S. G.

2016-12-01

The magnitude of wildland fire impacts on water resources varies regionally depending on fire severity, topography, vegetation and climate. An assessment of the potential threat that wildland fire poses to water supplies across the conterminous United States (CONUS) is critically important because forests supply 50% of consumed water. In our assessment, we first performed a double mass analysis of streamflow (GAGES-II) vs. precipitation (PRISM) data from 170 burned watersheds to identify changes in average water yield in the first five years following wildland fire (MTBS burn severity dataset), which were positive in 52 watersheds (Chow test p<0.1), negative in 69 (p<0.1), and not significant in 49 (p>0.1). Subsequently, we separated the respective contributions of fire and climate variability to changes in annual runoff (dQ) by fitting linear climate elasticity models (CEMs), yielding acceptable CEMs (coefficient p<0.1) for 106 watersheds. Median dQ (MdQ) for 62 watersheds with a burned area to drainage area ratio (BAR) <10% declined by -12%, mostly attributed to lower annual precipitation (P) (-16%) associated with regional climate trends, which was a common response in watersheds in the eastern states with low severity prescribed (Rx) or wildfires. MdQ increased by +11% in 44 watersheds with BAR >10%, notwithstanding overall declining P. These watersheds were for the greatest part located in the western CONUS, where dQ was correlated with burn severity (R2>0.53, variable per severity class) and PET (R2=0.73). The most severe impacts were observed in Arizona (2005 Cave Creek Complex, 2004 Edge Complex and 2004 Willow Fires), with BARs >39% and dQ>+160%, while hydrologic response in the east was much less extreme with only 10 cases where post-fire dQ increased >+10%. The clear regional patterns in post-fire Q together with evidence showing that downward trends in P can mask flow enhancing effects of fire disturbance (24 watersheds), underline the importance of the combined analysis of wildland fire and climate impacts in national scale assessments. Research funded by the USDA Forest Service Southern Research Station, Joint Fire Science Program (#14-1-06-18), and Oak Ridge Institute for Science and Education (U.S. Department of Energy).

An assessment of global climate model-simulated climate for the western cordillera of Canada (1961-90)

NASA Astrophysics Data System (ADS)

Bonsal, Barrie R.; Prowse, Terry D.; Pietroniro, Alain

2003-12-01

Climate change is projected to significantly affect future hydrologic processes over many regions of the world. This is of particular importance for alpine systems that provide critical water supplies to lower-elevation regions. The western cordillera of Canada is a prime example where changes to temperature and precipitation could have profound hydro-climatic impacts not only for the cordillera itself, but also for downstream river systems and the drought-prone Canadian Prairies. At present, impact researchers primarily rely on global climate models (GCMs) for future climate projections. The main objective of this study is to assess several GCMs in their ability to simulate the magnitude and spatial variability of current (1961-90) temperature and precipitation over the western cordillera of Canada. In addition, several gridded data sets of observed climate for the study region are evaluated.Results reveal a close correspondence among the four gridded data sets of observed climate, particularly for temperature. There is, however, considerable variability regarding the various GCM simulations of this observed climate. The British, Canadian, German, Australian, and US GFDL models are superior at simulating the magnitude and spatial variability of mean temperature. The Japanese GCM is of intermediate ability, and the US NCAR model is least representative of temperature in this region. Nearly all the models substantially overestimate the magnitude of total precipitation, both annually and on a seasonal basis. An exception involves the British (Hadley) model, which best represents the observed magnitude and spatial variability of precipitation. This study improves our understanding regarding the accuracy of GCM climate simulations over the western cordillera of Canada. The findings may assist in producing more reliable future scenarios of hydro-climatic conditions over various regions of the country. Copyright

Indices and Dynamics of Global Hydroclimate Over the Past Millennium from Data Assimilation

NASA Astrophysics Data System (ADS)

Steiger, N. J.; Smerdon, J. E.

2017-12-01

Reconstructions based on data assimilation (DA) are at the forefront of model-data syntheses in that such reconstructions optimally fuse proxy data with climate models. DA-based paleoclimate reconstructions have the benefit of being physically-consistent across the reconstructed climate variables and are capable of providing dynamical information about past climate phenomena. Here we use a new implementation of DA, that includes updated proxy system models and climate model bias correction procedures, to reconstruct global hydroclimate on seasonal and annual timescales over the last millennium. This new global hydroclimate product includes reconstructions of the Palmer Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and global surface temperature along with dynamical variables including the Nino 3.4 index, the latitudinal location of the intertropical convergence zone, and an index of the Atlantic Multidecadal Oscillation. Here we present a validation of the reconstruction product and also elucidate the causes of severe drought in North America and in equatorial Africa. Specifically, we explore the connection between droughts in North America and modes of ocean variability in the Pacific and Atlantic oceans. We also link drought over equatorial Africa to shifts of the intertropical convergence zone and modes of ocean variability.

Varve-based Reconstruction of Seasonal Hydroclimate from Nar Gölü, Turkey over the last 2.6 ka BP

NASA Astrophysics Data System (ADS)

Primmer, N.; Jones, M.; Metcalfe, S. E.; Eastwood, W.; Brauer, A.; Roberts, C. N.

2017-12-01

In south-west Asia, the wet-dry seasonality and semi-arid climatology increases societal vulnerability to drought. Long, continuous records of such droughts from the region are therefore important to put recent extremes in context, to benchmark natural variability in water availability. We present the longest annual record of south-west Asian climate to date, spanning the entirety of the Common Era. We reconstruct seasonal hydrological change from a climatically sensitive lake, Nar Gölü, Turkey over the past 2,589 years using varve sedimentology. Organic-calcareous varve deposition is driven by the climatic wet-dry seasonality, where varve microfacies analysis has developed an inter- and intra-annual record of the resultant limnological variability. Calibration using modern meteorological data identified that the March-May evaporation/precipitation ratio as the primary control on carbonate sublayer thickness. Combining these analyses with previous stable isotope, pollen and diatom records from the same cores further develops a holistic environmental record of palaeoseasonality able to gauge past and present hydrology, including drought severity. Two threshold hydrological changes to the spring growing season are well-dated at 535 and 1406 AD, thus coinciding with the onset of the Late Antiquity Little Ice Age (LALIA) and Little Ice Age (LIA) respectively. Carbonate mineralogy indicates generally fresher water conditions during the intermediary 871-year long period, with an inferred dry period at 850 AD possibly marking the start of regional, long-term aridification. By reconstructing high resolution hydroclimate, this well constrained annual record of past water availability provides a unique context for understanding climate change and its potential impact in this vulnerable region.

A comparison of annual vertical crustal displacements from GPS and Gravity Recovery and Climate Experiment (GRACE) over Europe

NASA Astrophysics Data System (ADS)

van Dam, T.; Wahr, J.; LavalléE, David

2007-03-01

We compare approximately 3 years of GPS height residuals (with respect to the International Terrestrial Reference Frame) with predictions of vertical surface displacements derived from the Gravity Recovery and Climate Experiment (GRACE) gravity fields for stations in Europe. An annual signal fit to the residual monthly heights, corrected for atmospheric pressure and barotropic ocean loading effects, should primarily represent surface displacements due to long-wavelength variations in water storage. A comparison of the annual height signal from GPS and GRACE over Europe indicates that at most sites, the annual signals do not agree in amplitude or phase. We find that unlike the annual signal predicted from GRACE, the annual signal in the GPS heights is not coherent over the region, displaying significant variability from site to site. Confidence in the GRACE data and the unlikely possibility of large-amplitude small-scale features in the load field not captured by the GRACE data leads us to conclude that some of the discrepancy between the GPS and GRACE observations is due to technique errors in the GPS data processing. This is evidenced by the fact that the disagreement between GPS and GRACE is largest at coastal sites, where mismodeling of the semidiurnal ocean tidal loading signal can result in spurious annual signals.

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

Lopez, Anthony; Maclaurin, Galen; Roberts, Billy

Long-term variability of solar resource is an important factor in planning a utility-scale photovoltaic (PV) generation plant, and annual generation for a given location can vary significantly from year to year. Based on multiple years of solar irradiance data, an exceedance probability is the amount of energy that could potentially be produced by a power plant in any given year. An exceedance probability accounts for long-term variability and climate cycles (e.g., monsoons or changes in aerosols), which ultimately impact PV energy generation. Study results indicate that a significant bias could be associated with relying solely on typical meteorological year (TMY)more » resource data to capture long-term variability. While the TMY tends to under-predict annual generation overall compared to the P50, there appear to be pockets of over-prediction as well.« less

Increased variability of tornado occurrence in the United States.

PubMed

Brooks, Harold E; Carbin, Gregory W; Marsh, Patrick T

2014-10-17

Whether or not climate change has had an impact on the occurrence of tornadoes in the United States has become a question of high public and scientific interest, but changes in how tornadoes are reported have made it difficult to answer it convincingly. We show that, excluding the weakest tornadoes, the mean annual number of tornadoes has remained relatively constant, but their variability of occurrence has increased since the 1970s. This is due to a decrease in the number of days per year with tornadoes combined with an increase in days with many tornadoes, leading to greater variability on annual and monthly time scales and changes in the timing of the start of the tornado season. Copyright © 2014, American Association for the Advancement of Science.

Reconstructing the leading mode of multi-decadal North Atlantic variability over the last two millenia using functional paleoclimate networks

NASA Astrophysics Data System (ADS)

Franke, Jasper G.; Werner, Johannes; Donner, Reik V.

2017-04-01

The increasing availability of high-resolution North Atlantic paleoclimate proxies allows to not only study local climate variations in time, but also temporal changes in spatial variability patterns across the entire region possibly controlled by large-scale coherent variability modes such as the North Atlantic Oscillation (NAO) and Atlantic Multidecadal Oscillation. In this study, we use functional paleoclimate network analysis [1,2] to investigate changes in the statistical similarity patterns among an ensemble of high-resolution terrestrial paleoclimate records from Northern Europe included in the Arctic 2k data base. Specifically, we construct complex networks capturing the mutual statistical similarity of inter-annual temperature variability recorded in tree ring records, ice cores and lake sediments for multidecadal time windows covering the last two millenia. The observed patterns of co-variability are ultimately connected to the North Atlantic atmospheric circulation and most prominently to multidecadal variations of the NAO. Based on the inferred networks, we study the dynamical similarity between regional clusters of archives defined according to present-day inter-annual temperature variations across the study region. This analysis identifies those time-dependent inter-regional linkages that are most informative about the leading-order North Atlantic climate variability according to a recent NAO reconstruction for the last millenium [3]. Based on these linkages, we extend the existing reconstruction to obtain qualitative information on multidecadal to centennial scale North Atlantic climate variability over the last two millenia. In general, we find a tendency towards a dominating positive NAO phase interrupted by pronounced and extended intervals of negative NAO. Relatively rapid transitions between both types of behaviour are present during distinct periods including the Little Ice Age, the Medieval Climate Anomaly and for the Dark Ages Little Ice Age. [1] K. Rehfeld, N. Marwan, S.F.M. Breitenbach, J. Kurths: Late Holocene Asian summer monsoon dynamics from small but complex networks of paleoclimate data. Climate Dynamics 41, 3-19, 2013 [2] J.L. Oster, N.P. Kelley: Tracking regional and global teleconnections recorded by western North American speleothem records. Quaternary Science Reviews 149, 18-33, 2016 [3] P. Ortega, F. Lehner, D. Swingedouw, V. Masson-Delmotte, C.C. Raible, M. Casado, P. Yiou: A model-tested North Atlantic Oscillation reconstruction for the past millenium. Nature 523, 71-74, 2015

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

PubMed

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

2016-01-01

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

Notable shifting in the responses of vegetation activity to climate change in China

NASA Astrophysics Data System (ADS)

Chen, Aifang; He, Bin; Wang, Honglin; Huang, Ling; Zhu, Yunhua; Lv, Aifeng

The weakening relationship between inter-annual temperature variability and vegetation activity in the Northern Hemisphere over the last three decades has been reported by a recent study. However, how and to what extent vegetation activity responds to climate change in China is still unclear. We applied the Pearson correlation and partial correlation methods with a moving 15-y window to the GIMMS NDVI dataset from NOAA/AVHRR and observed climate data to examine the variation in the relationships between vegetation activity and climate variables. Results showed that there was an expanding negative response of vegetation growth to climate warming and a positive role of precipitation. The change patterns between NDVI and climate variables over vegetation types during the past three decades pointed an expending negative correlation between NDVI and temperature and a positive role of precipitation over most of the vegetation types (meadow, grassland, shrub, desert, cropland, and forest). Specifically, correlation between NDVI and temperature (PNDVI-T) have shifted from positive to negative in most of the station of temperature-limited areas with evergreen broadleaf forests, whereas precipitation-limited temperate grassland and desert were characterized by a positive PNDVI-P. This study contributes to ongoing investigations of the effects of climate change on vegetation activity. It is also of great importance for designing forest management strategies to cope with climate change.

Climate and Physiography Predict Mercury Concentrations in Game Fish Species in Quebec Lakes Better than Anthropogenic Disturbances.

PubMed

Lucotte, Marc; Paquet, Serge; Moingt, Matthieu

2016-05-01

The fluctuations of mercury levels (Hg) in fish consumed by sport fishers in North-Eastern America depend upon a plethora of interrelated biological and abiological factors. To identify the dominant factors ultimately controlling fish Hg concentrations, we compiled mercury levels (Hg) during the 1976-2010 period in 90 large natural lakes in Quebec (Canada) for two major game species: northern pike (Esox lucius) and walleye (Sander vitreus). Our statistical analysis included 28 geographic information system variables and 15 climatic variables, including sulfate deposition. Higher winter temperatures explained 36% of the variability in higher walleye growth rates, in turn accounting for 54% of the variability in lower Hg concentrations. For northern pike, the dominance of a flat topography in the watershed explained 31% of the variability in lower Hg concentrations. Higher mean annual temperatures explained 27% of the variability in higher pike Hg concentrations. Pelagic versus littoral preferred habitats for walleye and pike respectively could explain the contrasted effect of temperature between the two species. Heavy logging could only explain 2% of the increase in walleye Hg concentrations. The influence of mining on fish Hg concentrations appeared to be masked by climatic effects.

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

DOE PAGES

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

2014-11-26

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

The Amazon Basin in transition

Treesearch

Eric A. Davidson; Alessandro C. de Araujo; Paulo Artaxo; Jennifer K. Balch; I. Foster Brown; Mercedes M.C. Bustamente; Michael T. Coe; Ruth S. DeFriess; Michael Keller; Marcos Longo; J. William Munger; Wilfrid Schroeder; Britaldo Soares-Filho; Carlos M. Souza, Jr.; Steven C. Wofsy

2012-01-01

Agricultural expansion and climate variability have become important agents of disturbance in the Amazon basin. Recent studies have demonstrated considerable resilience of Amazonian forests to moderate annual drought, but they also show that interactions between deforestation, fire and drought potentially lead to losses of carbon storage and changes in regional...

Numerical modelling assessment of climate-change impacts and mitigation measures on the Querença-Silves coastal aquifer (Algarve, Portugal)

NASA Astrophysics Data System (ADS)

Hugman, Rui; Stigter, Tibor; Costa, Luis; Monteiro, José Paulo

2017-11-01

Predicted changes in climate will lead to seawater intrusion in the Querença-Silves (QS) coastal aquifer (south Portugal) during the coming century if the current water-resource-management strategy is maintained. As for much of the Mediterranean, average rainfall is predicted to decrease along with increasing seasonal and inter-annual variability and there is a need to understand how these changes will affect the sustainable use of groundwater resources. A density-coupled flow and transport model of the QS was used to simulate an ensemble of climate, water-use and adaptation scenarios from 2010 to 2099 taking into account intra- and inter-annual variability in recharge and groundwater use. By considering several climate models, bias correction and recharge calculation methods, a degree of uncertainty was included. Changes in rainfall regimes will have an immediate effect on groundwater discharge; however, the effect on saltwater intrusion is attenuated by the freshwater-saltwater interfaces' comparatively slow rate of movement. Comparing the effects of adaptation measures demonstrates that the extent of intrusion in the QS is controlled by the long-term water budget, as the effectiveness of both demand and supply oriented measures is proportional to the change in water budget, and that to maintain the current position, average groundwater discharge should be in the order of 50 × 106 m3 yr-1.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

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.

1500 Years of Annual Climate and Environmental Variability as Recorded in Bona-Churchill (Alaska) Ice Cores

NASA Astrophysics Data System (ADS)

Thompson, L. G.; Mosley-Thompson, E. S.; Zagorodnov, V.; Davis, M. E.; Mashiotta, T. A.; Lin, P.

2004-12-01

In 2003, six ice cores measuring 10.5, 11.5, 11.8, 12.4, 114 and 460 meters were recovered from the col between Mount Bona and Mount Churchill (61° 24'N; 141° 42'W; 4420 m asl). These cores have been analyzed for stable isotopic ratios, insoluble dust content and concentrations of major chemical species. Total Beta radioactivity was measured in the upper sections. The 460-meter core, extending to bedrock, captured the entire depositional record at this site where ice temperatures ranged from -24° C at 10 meters to -19.8° C at the ice/bedrock contact. The shallow cores allow assessment of surface processes under modern meteorological conditions while the deep core offers a ˜1500-year climate and environmental perspective. The average annual net balance is ˜~1000 mm of water equivalent and distinct annual signals in dust and calcium concentrations along with δ 18O allow annual resolution over most of the core. The excess sulfate record reflects many known large volcanic eruptions such as Katmai, Krakatau, Tambora, and Laki which allow validation of the time scale in the upper part of the core. The lower part of the core yields a history of earlier volcanic events. The 460-m Bona-Churchill ice core provides a detailed history of the `Little Ice Age' and medieval warm periods for southeastern Alaska. The source of the White River Ash will be discussed in light of the evidence from this core. The 460-m core also provides a long-term history of the dust fall that originates in north-central China. The annual ice core-derived climate records from southeastern Alaska will facilitate an investigation of the likelihood that the high resolution 1500-year record from the tropical Quelccaya Ice Cap (Peru) preserves a history of the variability of both the PDO and the Aleutian Low.

Investigating the Control of Ocean-Atmospheric Oscillations on Global Terrestrial Evaporation

NASA Astrophysics Data System (ADS)

Martens, B.; Waegeman, W.; Dorigo, W.; Verhoest, N.; Miralles, D. G.

2017-12-01

Intra-annual and multi-decadal variability in Earth's climate is strongly driven by periodic oscillations in the coupled state of our atmosphere and ocean. These oscillations do not only impact climate in nearby regions, but can also have an effect on the climate in remote areas, a phenomenon that is often referred to as teleconnection. Because changes in local climate immediately affect terrestrial ecosystems through a series of complex processes, ocean-atmospheric oscillations are expected to influence land evaporation; i.e. the return flux of water from land into the atmosphere. In this presentation, the effects of ocean-atmospheric oscillations on global terrestrial evaporation are analysed. We use multi-decadal, satellite-based observations of different climate variables (air temperature, radiation, precipitation) in combination with a simple supervised learning method - the Least Absolute Shrinkage and Selection Operator - to detect the impact of sixteen leading ocean-atmospheric oscillations on terrestrial evaporation. The latter is retrieved using the Global Land Evaporation Amsterdam Model (GLEAM). The analysis reveals hotspot regions in which more than 30% of the inter-annual variability in terrestrial evaporation can be explained by ocean-atmospheric oscillations. The impact is different per region and season, and can typically be attributed to a small subset of oscillations. For instance, the dynamics in terrestrial evaporation over eastern Australia are substantially impacted by both the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) during Austral spring. Using the same learning method, but targeting terrestrial evaporation based on its local climatic drivers (air temperature, precipitation, and radiation), shows the dominant control of precipitation on terrestrial evaporation in Australia, suggesting that both ENSO and IOD affect the precipitation, in his turn influencing evaporation. The latter is confirmed by regressing precipitation to the ocean-atmospheric oscillations. The results of our study allow for a better understanding of the link between ocean-atmosphere dynamics and terrestrial bio-geochemical cycles, and may help improve the prediction of future changes in the water cycle over the continents.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

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

USGS Publications Warehouse

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Internal variability of a dynamically downscaled climate over North America

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

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 km and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemblemore » during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late 21st century. However, the IV is larger than the projected changes in precipitation for the mid- and late 21st century.« less

Internal variability of a dynamically downscaled climate over North America

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

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble duringmore » the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.« less

Internal variability of a dynamically downscaled climate over North America

NASA Astrophysics Data System (ADS)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2018-06-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Internal variability of a dynamically downscaled climate over North America

NASA Astrophysics Data System (ADS)

Wang, Jiali; Bessac, Julie; Kotamarthi, Rao; Constantinescu, Emil; Drewniak, Beth

2017-09-01

This study investigates the internal variability (IV) of a regional climate model, and considers the impacts of horizontal resolution and spectral nudging on the IV. A 16-member simulation ensemble was conducted using the Weather Research Forecasting model for three model configurations. Ensemble members included simulations at spatial resolutions of 50 and 12 km without spectral nudging and simulations at a spatial resolution of 12 km with spectral nudging. All the simulations were generated over the same domain, which covered much of North America. The degree of IV was measured as the spread between the individual members of the ensemble during the integration period. The IV of the 12 km simulation with spectral nudging was also compared with a future climate change simulation projected by the same model configuration. The variables investigated focus on precipitation and near-surface air temperature. While the IVs show a clear annual cycle with larger values in summer and smaller values in winter, the seasonal IV is smaller for a 50-km spatial resolution than for a 12-km resolution when nudging is not applied. Applying a nudging technique to the 12-km simulation reduces the IV by a factor of two, and produces smaller IV than the simulation at 50 km without nudging. Applying a nudging technique also changes the geographic distributions of IV in all examined variables. The IV is much smaller than the inter-annual variability at seasonal scales for regionally averaged temperature and precipitation. The IV is also smaller than the projected changes in air-temperature for the mid- and late twenty-first century. However, the IV is larger than the projected changes in precipitation for the mid- and late twenty-first century.

Establishing a baseline precipitation and temperature regime for the Guianas from observations and reanalysis data

NASA Astrophysics Data System (ADS)

Bovolo, C. Isabella; Pereira, Ryan; Parkin, Geoff; Wagner, Thomas

2010-05-01

The tropical rainforests of the Guianas, north of the Amazon, are home to several Amerindian communities, hold high levels of biodiversity and, importantly, remain some of the world's most pristine and intact rainforests. Not only do they have important functions in the global carbon cycle, but they regulate the local and regional climate and help generate rain over vast distances. Despite their significance however, the climate and hydrology of this region is poorly understood. It is important to establish the current climate regime of the area as a baseline against which any impacts of future climate change or deforestation can be measured but observed historical climate datasets are generally sparse and of low quality. Here we examine the available precipitation and temperature datasets for the region and derive tentative precipitation and temperature maps focussed on Guyana. To overcome the limitations in the inadequate observational data coverage we also make use of a reanalysis dataset from the European Centre for Medium-range Weather Forecasts (ECMWF). The ECMWF ERA40 dataset comprises a spatially consistent global historical climate for the period 1957-2002 at a ~125 km2 (1.125 degree) resolution at the equator and is particularly valuable for establishing the climate of data-poor areas. Once validated for the area of interest, ERA40 is used to determine the precipitation and temperature regime of the Guianas. Grid-cell by grid-cell analysis provides a complete picture of spatial patterns of averaged monthly precipitation variability across the area, vital for establishing a basis from which to compare any future effects of climate change. This is the first comprehensive study of the recent historical climate and its variability in this area, placing a new hydroclimate monitoring and research program at the Iwokrama International Centre for Rainforest Conservation and Development, Guyana, into the broader climate context. Mean differences (biases) and annual average spatial correlations are examined between modelled ERA40 and observed time series comparing the seasonal cycles and the yearly, monthly and monthly anomaly time series. This is to evaluate if the reanalysis data correctly reproduces the areally averaged observed mean annual precipitation, interannual variability and seasonal precipitation cycle over the region. Results show that reanalysis precipitation for the region compares favourably with areally averaged observations where available, although the model underestimates precipitation in some zones of higher elevation. Also ERA40 data is slightly positively biased along the coast and negatively biased inland. Comparisons between observed and modelled data show that although correlations of annual time series are low (<0.6), correlations of monthly time series reach 0.8 demonstrating that the model captures much of the seasonal variation in precipitation. However correlations between monthly precipitation anomalies, where the averaged seasonal cycle has been removed from the comparison, are lower (< 0.6). As precipitation observations are not assimilated into the reanalysis these results provide a good validation of model performance. The seasonal cycle of precipitation is found to be highly variable across the region. Two wet-seasons (June and December) occur in northern Guyana which relate to the twice yearly passage of the inter-tropical convergence zone whereas a single wet season (April-August) occurs in the savannah zone, which stretches from Venezuela through the southern third of Guyana. The climate transition zone lies slightly north of the distinctive forest-savannah boundary which suggests that the boundary may be highly sensitive to future alterations in climate, such as those due to climate change or deforestation.

Observed changes in extremes of daily rainfall and temperature in Jemma Sub-Basin, Upper Blue Nile Basin, Ethiopia

NASA Astrophysics Data System (ADS)

Worku, Gebrekidan; Teferi, Ermias; Bantider, Amare; Dile, Yihun T.

2018-02-01

Climate variability has been a threat to the socio-economic development of Ethiopia. This paper examined the changes in rainfall, minimum, and maximum temperature extremes of Jemma Sub-Basin of the Upper Blue Nile Basin for the period of 1981 to 2014. The nonparametric Mann-Kendall, seasonal Mann-Kendall, and Sen's slope estimator were used to estimate annual trends. Ten rainfall and 12 temperature indices were used to study changes in rainfall and temperature extremes. The results showed an increasing trend of annual and summer rainfall in more than 78% of the stations and a decreasing trend of spring rainfall in most of the stations. An increase in rainfall extreme events was detected in the majority of the stations. Several rainfall extreme indices showed wetting trends in the sub-basin, whereas limited indices indicated dryness in most of the stations. Annual maximum and minimum temperature and extreme temperature indices showed warming trend in the sub-basin. Presence of extreme rainfall and a warming trend of extreme temperature indices may suggest signs of climate change in the Jemma Sub-Basin. This study, therefore, recommended the need for exploring climate induced risks and implementing appropriate climate change adaptation and mitigation strategies.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Impact of change in climate and policy from 1988 to 2007 on environmental and microbial variables at the time series station Boknis Eck, Baltic Sea

NASA Astrophysics Data System (ADS)

Hoppe, H.-G.; Giesenhagen, H. C.; Koppe, R.; Hansen, H.-P.; Gocke, K.

2012-12-01

Phytoplankton and bacteria are sensitive indicators of environmental change. The temporal development of these key organisms was monitored from 1988 to the end of 2007 at the time series station Boknis Eck in the Western Baltic Sea. This period was characterized by the adaption of the Baltic Sea ecosystem to changes in the environmental conditions caused by the collapse and conversion of the political system in the Southern and Eastern Border States, accompanied by the general effects of global climate change. Measured variables were chlorophyll, primary production, bacteria number, -biomass and -production, glucose turnover rate, macro-nutrients, pH, temperature and salinity. Negative trends with time were recorded for chlorophyll, the bacterial variables, nitrate, ammonia, phosphate, silicate, oxygen and salinity while temperature, pH, and the ratio between bacteria numbers and chlorophyll increased. The strongest reductions with time occurred for the annual maximum values, e.g. for chlorophyll during the spring bloom or for nitrate during winter, while the annual minimum values remained more stable. In deep water above sediment the negative trends of oxygen, nitrate, phosphate and bacterial variables as well as the positive trend of temperature were similar to those in the surface while the trends of salinity, ammonia and silicate were opposite to those in the surface. Decreasing oxygen even in the surface layer was of particular interest because it suggested enhanced recycling of nutrients from the deep hypoxic zones to the surface by vertical mixing. In the long run all variables correlated positively with temperature, except chlorophyll and salinity. Salinity correlated negatively with all bacterial variables as well as precipitation and positively with chlorophyll. Surprisingly, bacterial variables did not correlate with chlorophyll which may be inherent with the time lag between the peaks of phytoplankton and bacteria during spring. Compared to the 20-yr averages of the environmental and microbial variables, the strongest negative deviations of corresponding annual averages were measured about ten years after political change for nitrate and bacterial secondary production (~ -60%), followed by chlorophyll (-50%) and bacterial biomass (-40%). Considering the circulation of surface currents in the Baltic Sea we conclude that the improved management of water resources after 1989 together with the trends of the climate variables salinity and temperature were responsible for the observed patterns of the microbial variables at the Boknis Eck time series station.

Iranian speleothems: Investigating Quaternary climate variability in semi-arid Western Asia

NASA Astrophysics Data System (ADS)

Carolin, Stacy; Morgan, Jacob; Peckover, Emily; Walker, Richard; Henderson, Gideon; Rowe, Peter; Andrews, Julian; Ersek, Vasile; Sloan, Alastair; Talebian, Morteza; Fattahi, Morteza; Nezamdoust, Javad

2016-04-01

Rapid population growth and limited water supply has highlighted the need for vigorous water resource management practices in the semi-arid regions of Western Asia. One significant unknown in this discussion is the future change in rainfall amount due to the consequential effects of today's greenhouse gas forcing on the regional climate system. Currently, there is little paleoclimate proxy data in Western Asia to extend climate records beyond the limits of the instrumental period, leaving scant evidence to investigate the system's response to various climate forcings on different timescales. Here we present a synthesis of speleothem climate records across northern Iran, from the wetter climate of the Alborz and Zagros mountain ranges to the dry northeast, in order to investigate the magnitude of past climate variability and the forcings responsible. The stalagmites collected from the west and north-central mountain ranges, areas with ~200-400mm mean annual precipitation mostly falling within the fall-winter-spring months, all demonstrate growth limited to the interglacial periods of the Quaternary. We present overlapping Holocene stable isotope records with a complementary trace element record to assist in interpreting the isotopic variability. One of the records is sampled at <4yr resolution and spans 3.7-5.3 kyBP, a contested period of catastrophic droughts that allegedly eradicated civilizations in areas of the near East. Imposed upon decadal-scale variability, the record reveals a 1,000-yr gradual trend toward enriched stable oxygen isotope values, interpreted as a trend toward drier conditions, which ends with an abrupt 300-yr cessation in growth beginning at 4.3 kyBP, coincident with the so-called 4.2 kyBP drought event. From the northeast Iranian plateau, we present a new stalagmite record that spans the penultimate deglaciation and Stages 5e-5a. This region presently receives limited rain annually (~100-300mm/yr, regularly falling between November and May), and the record presented is one of the first speleothem climate records to span a deglaciation in West Asia. To improve our interpretation of the speleothem climate proxy timeseries, we use multiple decades of Tehran GNIP data, meteorological data, and isotope-equipped climate model outputs to investigate the large-scale mechanisms forcing isotopic variations in rainwater across northern Iran. We also examine possible transformation of water isotopes during the transition through the karst aquifer based on site properties, measured dripwater isotopes, and simple model experiments.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Variability of the atmospheric energy flux across 70°N computed from the GFDL data set

NASA Astrophysics Data System (ADS)

Overland, James E.; Turet, Philip

The primary energy balance for the arctic atmosphere is through northward advection of moist static energy—sensible heat, potential energy, and latent heat—balanced by long wave radiation to space. Energy flux from sea ice and marginal seas contributes perhaps 20-30% of the outgoing radiation north of 70°N in winter and absorbs a nearly equal amount during summer. Thorndike's toy model shows that extreme climate states with no ice growth or melt can occur by changing the latitudinal energy flux by ±20-30% out of an annual mean flux of 100 W m-2. We extend the previous work on latitudinal energy flux by Nakamura and Oort (NO) to a 25-year record and investigate temporal variability. Our annual latitudinal energy flux was 103 W m-2 compared to the NO value of 98 W m-2 this difference was from greater fluxes during the winter. We found that mean winter (NDJFM) energy flux was 121 W m-2 with a standard deviation of 11 W m-2. There were no large outliers in any year. An analysis of variance showed that interannual variability does not contribute towards explaining monthly variability of northward energy transport for the winter, summer or annual periods. Transient eddy flux of sensible heat into the arctic basin was the largest component of the total energy flux and is concentrated near the longitudes of the Greenland Sea (˜10°W) and the Bering and Chukchi Seas (180°). There is a minimum in atmospheric heating north of Greenland, a known region of thick ice. While there was little interannual variability of energy flux across 70°N, there was considerable month-to-month variability and regional variability in poleward energy flux. Sea ice may playa role in storage and redistribution of energy in the arctic climate.

New climate change scenarios for the Netherlands.

PubMed

van den Hurk, B; Tank, A K; Lenderink, G; Ulden, A van; Oldenborgh, G J van; Katsman, C; Brink, H van den; Keller, F; Bessembinder, J; Burgers, G; Komen, G; Hazeleger, W; Drijfhout, S

2007-01-01

A new set of climate change scenarios for 2050 for the Netherlands was produced recently. The scenarios span a wide range of possible future climate conditions, and include climate variables that are of interest to a broad user community. The scenario values are constructed by combining output from an ensemble of recent General Climate Model (GCM) simulations, Regional Climate Model (RCM) output, meteorological observations and a touch of expert judgment. For temperature, precipitation, potential evaporation and wind four scenarios are constructed, encompassing ranges of both global mean temperature rise in 2050 and the strength of the response of the dominant atmospheric circulation in the area of interest to global warming. For this particular area, wintertime precipitation is seen to increase between 3.5 and 7% per degree global warming, but mean summertime precipitation shows opposite signs depending on the assumed response of the circulation regime. Annual maximum daily mean wind speed shows small changes compared to the observed (natural) variability of this variable. Sea level rise in the North Sea in 2100 ranges between 35 and 85 cm. Preliminary assessment of the impact of the new scenarios on water management and coastal defence policies indicate that particularly dry summer scenarios and increased intensity of extreme daily precipitation deserves additional attention in the near future.

Evaluation of Multi-Scale Climate Effects on Annual Recruitment Levels of the Japanese Eel, Anguilla japonica, to Taiwan

PubMed Central

Tzeng, Wann-Nian; Tseng, Yu-Heng; Han, Yu-San; Hsu, Chih-Chieh; Chang, Chih-Wei; Di Lorenzo, Emanuele; Hsieh, Chih-hao

2012-01-01

Long-term (1967–2008) glass eel catches were used to investigate climatic effects on the annual recruitment of Japanese eel to Taiwan. Specifically, three prevailing hypotheses that potentially explain the annual recruitment were evaluated. Hypothesis 1: high precipitation shifts the salinity front northward, resulting in favorable spawning locations. Hypothesis 2: a southward shift of the position of the North Equatorial Current (NEC) bifurcation provides a favorable larval transport route. Hypothesis 3: ocean conditions (eddy activities and productivity) along the larval migration route influence larval survival. Results of time series regression and wavelet analyses suggest that Hypothesis 1 is not supported, as the glass eel catches exhibited a negative relationship with precipitation. Hypothesis 2 is plausible. However, the catches are correlated with the NEC bifurcation with a one-year lag. Considering the time needed for larval transport (only four to six months), the one-year lag correlation does not support the direct transport hypothesis. Hypothesis 3 is supported indirectly by the results. Significant correlations were found between catches and climate indices that affect ocean productivity and eddy activities, such as the Quasi Biennial Oscillation (QBO), North Pacific Gyre Oscillation (NPGO), Pacific Decadal Oscillation (PDO), and Western Pacific Oscillation (WPO). Wavelet analysis reveals three periodicities of eel catches: 2.7, 5.4, and 10.3 years. The interannual coherence with QBO and the Niño 3.4 region suggests that the shorter-term climate variability is modulated zonally by equatorial dynamics. The low-frequency coherence with WPO, PDO, and NPGO demonstrates the decadal modulation of meridional teleconnection via ocean–atmosphere interactions. Furthermore, WPO and QBO are linked to solar activities. These results imply that the Japanese eel recruitment may be influenced by multi-timescale climate variability. Our findings call for investigation of extra-tropical ocean dynamics that affect survival of eels during transport, in addition to the existing efforts to study the equatorial system. PMID:22383976

Evaluation of multi-scale climate effects on annual recruitment levels of the Japanese eel, Anguilla japonica, to Taiwan.

PubMed

Tzeng, Wann-Nian; Tseng, Yu-Heng; Han, Yu-San; Hsu, Chih-Chieh; Chang, Chih-Wei; Di Lorenzo, Emanuele; Hsieh, Chih-Hao

2012-01-01

Long-term (1967-2008) glass eel catches were used to investigate climatic effects on the annual recruitment of Japanese eel to Taiwan. Specifically, three prevailing hypotheses that potentially explain the annual recruitment were evaluated. Hypothesis 1: high precipitation shifts the salinity front northward, resulting in favorable spawning locations. Hypothesis 2: a southward shift of the position of the North Equatorial Current (NEC) bifurcation provides a favorable larval transport route. Hypothesis 3: ocean conditions (eddy activities and productivity) along the larval migration route influence larval survival. Results of time series regression and wavelet analyses suggest that Hypothesis 1 is not supported, as the glass eel catches exhibited a negative relationship with precipitation. Hypothesis 2 is plausible. However, the catches are correlated with the NEC bifurcation with a one-year lag. Considering the time needed for larval transport (only four to six months), the one-year lag correlation does not support the direct transport hypothesis. Hypothesis 3 is supported indirectly by the results. Significant correlations were found between catches and climate indices that affect ocean productivity and eddy activities, such as the Quasi Biennial Oscillation (QBO), North Pacific Gyre Oscillation (NPGO), Pacific Decadal Oscillation (PDO), and Western Pacific Oscillation (WPO). Wavelet analysis reveals three periodicities of eel catches: 2.7, 5.4, and 10.3 years. The interannual coherence with QBO and the Niño 3.4 region suggests that the shorter-term climate variability is modulated zonally by equatorial dynamics. The low-frequency coherence with WPO, PDO, and NPGO demonstrates the decadal modulation of meridional teleconnection via ocean-atmosphere interactions. Furthermore, WPO and QBO are linked to solar activities. These results imply that the Japanese eel recruitment may be influenced by multi-timescale climate variability. Our findings call for investigation of extra-tropical ocean dynamics that affect survival of eels during transport, in addition to the existing efforts to study the equatorial system.

Roots of forbs sense climate fluctuations in the semi-arid Loess Plateau: Herb-chronology based analysis

NASA Astrophysics Data System (ADS)

Shi, Songlin; Li, Zongshan; Wang, Hao; von Arx, Georg; Lü, Yihe; Wu, Xing; Wang, Xiaochun; Liu, Guohua; Fu, Bojie

2016-06-01

Growth of herbaceous plants responds sensitively and rapidly to climate variability. Yet, little is known regarding how climate warming influences the growth of herbaceous plants, particularly in semi-arid sites. This contrasts with widely reported tree growth decline and even mortality in response to severe water deficits due to climate warming around the world. Here, we use the relatively novel approach of herb-chronology to analyze the correlation between climatic factors and annual ring width in the root xylem of two perennial forb species (Medicago sativa, Potentilla chinensis) in the Loess Plateau of China. We show that warming-induced water deficit has a significant negative effect on the growth of herbaceous plants in the Loess Plateau. Our results indicate that the growth of forbs responds rapidly and sensitively to drought variability, implying that water availability plays a dominant role in regulating the growth of herbaceous plants in semi-arid areas. If warming and drying in the Loess Plateau continue in the future, further affects the growth of herbaceous plants, potentially driving regional changes in the relationship between herbaceous vegetation and climate.

Roots of forbs sense climate fluctuations in the semi-arid Loess Plateau: Herb-chronology based analysis

NASA Astrophysics Data System (ADS)

Shi, S.

2016-12-01

Growth of herbaceous plants responds sensitively and rapidly to climate variability. Yet, little is known regarding how climate warming influences the growth of herbaceous plants, particularly in semi-arid sites. This contrasts with widely reported tree growth decline and even mortality in response to severe water deficits due to climate warming around the world. Here, we use the relatively novel approach of herb-chronology to analyze the correlation between climatic factors and annual ring width in the root xylem of two perennial forb species (Medicago sativa, Potentilla chinensis) in the Loess Plateau of China. We show that warming-induced water deficit has a significant negative effect on the growth of herbaceous plants in the Loess Plateau. Our results indicate that the growth of forbs responds rapidly and sensitively to drought variability, implying that water availability plays a dominant role in regulating the growth of herbaceous plants in semi-arid areas. If warming and drying in the Loess Plateau continue in the future, further affects the growth of herbaceous plants, potentially driving regional changes in the relationship between herbaceous vegetation and climate.

Enhanced future variability during India's rainy season

NASA Astrophysics Data System (ADS)

Menon, Arathy; Levermann, Anders; Schewe, Jacob

2013-04-01

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

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

USGS Publications Warehouse

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

2016-07-06

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

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Sensitivity of annual mass balance gradient and Hypsometry to the changing climate: the case of Dokriani Glacier, central Himalaya, India

NASA Astrophysics Data System (ADS)

Pratap, B.

2015-12-01

The glacier mass balance is undelayed, unfiltered and direct method to assess the impact of climate change on the glaciers. Many studies suggest that some of the Himalayan glaciers have lost their mass at an increased rate during the past few decades. Furthermore, the mass balance gradient and hypsometric analysis are important to understand the glacier response towards climatic perturbations. Our long term in-situ monitoring on the Dokriani Glacier provides great insights to understand the variability in central Himalayan glaciers. We report the relationship between glacier hypsometry and annual mass balance gradient (12 years) to understand the glacier's response towards climate change. Dokriani Glacier in the Bhagirathi basin is a small (7 km2) NNW exposed glacier in the western part of central Himalaya, India. The study analysed the annual balance, mass balance gradient and length changes observed during first decade of 21st century (2007-2013) and compare with the previous observations of 1990s (1992-2000). A large spatial variability in the mass balance gradients of two different periods has been observed. The equilibrium-line altitude (ELA) was fluctuated between 5000 and 5100 m a.s.l. and the derived time averaged ELA (ELAn) and balance budget ELA (ELA0) were 5075 and 4965 m a.s.l respectively during 1992-2013. The observed time-averaged accumulation-area ratio (AARn) and balance budget AAR (AAR0) were 0.67 and 0.72 respectively during 1992-2013. The higher value of AAR comprises due to flat and broader accumulation area (4.50 km2) of the glacier. Although, having larger accumulation area, the glacier has faced strong mass wasting with average annual ablation of -1.82 m w.e. a-1 in the ablation zone as compare to residual average annual accumulation of 0.41 m w.e. a-1. Based on the annual mass balance series (12 years) Dokriani Glacier has continuous negative annual balances with monotonically negative cumulative mass loss of -3.86 m w.e with the average loss of -0.32 m w.e a-1. Dokriani Glacier also showed continues recession from 1992 to present. Snout was ascended 95 m a.s.l. from an elevation of 3870 m a.s.l. in 1992 to an elevation of 3965 m a.s.l. in 2013. The progressive retreat of the glacier affects its extension and volume and covered by continuous enhancement of debris in the lower ablation zone.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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