Millennial to orbital-scale variations of drought intensity in the Eastern Mediterranean

Millennial to orbital-scale rainfall changes in the Mediterranean region and corresponding variations in vegetation patterns were the result of large-scale atmospheric reorganizations. In spite of recent efforts to reconstruct this variability using a range of proxy archives, the underlying physical mechanisms have remained elusive. Through the analysis of a new high-resolution sedimentary section from Lake Van (Turkey) along with climate modeling experiments, we identify massive droughts in the Eastern Med- iterranean for the past four glacial cycles, which have a pervasive link with known intervals of enhanced North Atlantic glacial iceberg calving, weaker Atlantic Meridional Overturning Circulation and Dansgaard-Oeschger cold conditions. On orbital timescales, the topographic effect of large Northern Hemisphere ice sheets and periods with minimum insolation seasonality further exacerbated drought intensities by suppressing both summer and winter precipitation.

Cenozoic oxygen isotopic values for benthic foraminifera from DSDP and ODP low and high latitude marine sediment cores

The climate during the Cenozoic era changed in several steps from ice-free poles and warm conditions to ice-covered poles and cold conditions. Since the 1950s, a body of information on ice volume and temperature changes has been built up predominantly on the basis of measurements of the oxygen isotopic composition of shells of benthic foraminifera collected from marine sediment cores. The statistical methodology of time series analysis has also evolved, allowing more information to be extracted from these records. Here we provide a comprehensive view of Cenozoic climate evolution by means of a coherent and systematic application of time series analytical tools to each record from a compilation spanning the interval from 4 to 61 Myr ago. We quantitatively describe several prominent features of the oxygen isotope record, taking into account the various sources of uncertainty (including measurement, proxy noise, and dating errors). The estimated transition times and amplitudes allow us to assess causal climatological-tectonic influences on the following known features of the Cenozoic oxygen isotopic record: Paleocene-Eocene Thermal Maximum, Eocene-Oligocene Transition, Oligocene-Miocene Boundary, and the Middle Miocene Climate Optimum. We further describe and causally interpret the following features: Paleocene-Eocene warming trend, the two-step, long-term Eocene cooling, and the changes within the most recent interval (Miocene-Pliocene). We review the scope and methods of constructing Cenozoic stacks of benthic oxygen isotope records and present two new latitudinal stacks, which capture besides global ice volume also bottom water temperatures at low (less than 30°) and high latitudes. This review concludes with an identification of future directions for data collection, statistical method development, and climate modeling.

Age model, isotope analyses, geochemical measurements and grain size analyses of sediment core GeoB9508-5 from the Senegal River Mouth

The influence of the large-scale ocean circulation on Sahel rainfall is elusive because of the shortness of the observational record. We reconstructed the history of eolian and fluvial sedimentation on the continental slope off Senegal during the past 57,000 years. Our data show that abrupt onsets of arid conditions in the West African Sahel were linked to cold North Atlantic sea surface temperatures during times of reduced meridional overturning circulation associated with Heinrich Stadials. Climate modeling suggests that this drying is induced by a southward shift of the West African monsoon trough in conjunction with an intensification and southward expansion of the midtropospheric African Easterly Jet.

(Table 1) Age control points of ODP Site 160-968

The astronomical timescale of the Eastern Mediterranean Plio-Pleistocene builds on tuning of sapropel layers to Northern Hemisphere summer insolation maxima. A 3000-year precession lag has become instrumental in the tuning procedure as radiocarbon dating revealed that the midpoint of the youngest sapropel, S1, in the early Holocene occurred approximately 3000 years after the insolation maximum. The origin of the time lag remains elusive, however, because sapropels are generally linked to maximum African monsoon intensities and transient climate modeling results indicate an in-phase behavior of the African monsoon relative to precession forcing. Here we present new high-resolution records of bulk sediment geochemistry and benthic foraminiferal oxygen isotopes from ODP Site 968 in the Eastern Mediterranean. We show that the 3000-year precession time lag of the sapropel midpoints is consistent with (1) the global marine isotope chronology, (2) maximum (monsoonal) precipitation conditions in the Mediterranean region and China derived from radiometrically dated speleothem records, and (3) maximum atmospheric methane concentrations in Antarctica ice cores. We show that the time lag relates to the occurrence of precession-paced North Atlantic cold events, which systematically delayed the onset of strong boreal summer monsoon intensity. Our findings may also explain a non-stationary behavior of the African monsoon over the past 3 million years due to more frequent and intensive cold events in the Late Pleistocene.

Ice-atmosphere interactions and sea ice predictability at multiple resolutions in the Community Earth System Model

Thesis (Master's)--University of Washington, 2016-06

Effet du climat viticole sur la perception sensorielle du vin: éléments méthodologiques pour une modélisation au niveau mondial.

Summary The objective of this study was to develop a methodology capable of modeling the effect of viticultural climate on wine sensory characteristics. The climate was defined by the Géoviticulture Multicriteria Climatic Classification System (Tonietto and Carbonneau, 2004), based on the Heliothermal index (HI), Cool Night index (CI) and Dryness index (DI). The sensory wine description was made according with the methodology established by Zanus and Tonietto (2007). In this study we focused on the 5 principal wine producing regions of Brazil: Serra Gaúcha, Serra do Sudeste, Campanha (Meridional and Central), Planalto Catarinense and Vale do Submédio São Francisco. The results from Principal Component Analysis (PCA) show the HI and CI opposed to the DI. High HI values were associated to a lower perception of acidity, as well as to a lower perception of concentration (palate) and persistence by mouth. For the red wines, high HI values were positively associated with alcohol (palate), conversely to the DI index, which showed high values related to the perception of tanins and acidity. The higher the CI, the lower were the color intensity, tanins, concentration and persistence by mouth. It may be concluded that viticultural climate - expressed by the HI, CI and DI indexes ? adequately explained much of the sensory differences of the wines made in different regions. The methodology proposed and the enlargement of the database it will maybe open the possibility of modeling the part of wine sensory characteristics as dependent variables of the viticultural climate, as defined by the Géoviticulture MCC System. Keywords: viticultural climate, modeling, wine, tipicity.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.

Modeling the vulnerability of an urban groundwater system due to the combined impacts of climate change and management scenarios

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

Stormwater runoff - modeling impacts of urbanization and climate change

Development pressure throughout the coastal areas of the United States continues to build, particularly in the southeast (Allen and Lu 2003, Crossett et al. 2004). It is well known that development alters watershed hydrology: as land becomes covered with surfaces impervious to rain, water is redirected from groundwater recharge and evapotranspiration to stormwater runoff, and as the area of impervious cover increases, so does the volume and rate of runoff (Schueler 1994, Corbett et al. 1997). Pollutants accumulate on impervious surfaces, and the increased runoff with urbanization is a leading cause of nonpoint source pollution (USEPA 2002). Sediment, chemicals, bacteria, viruses, and other pollutants are carried into receiving water bodies, resulting in degraded water quality (Holland et al. 2004, Sanger et al. 2008). (PDF contains 5 pages)

Modeling the Links between Biodiversity, Ecosystem Services and Human Wellbeing in the Context of Climate Change: Results from an Econometric Analysis on the European Forest Ecosystems

25 p.