Influence of the background wind on the local soil moisture-precipitation feedback

The importance of soil moisture anomalies on airmass convection over semiarid regions has been recognized in several studies. The underlying mechanisms remain partly unclear. An open question is why wetter soils can result in either an increase or a decrease of precipitation (positive or negative soil moisture–precipitation feedback, respectively). Here an idealized cloud-resolving modeling framework is used to explore the local soil moisture–precipitation feedback. The approach is able to replicate both positive and negative feedback loops, depending on the environmental parameters. The mechanism relies on horizontal soil moisture variations, which may develop and intensify spontaneously. The positive expression of the feedback is associated with the initiation of convection over dry soil patches, but the convective cells then propagate over wet patches where they strengthen and preferentially precipitate. The negative feedback may occur when the wind profile is too weak to support the propagation of convective features from dry to wet areas. Precipitation is then generally weaker and falls preferentially over dry patches. The results highlight the role of the midtropospheric flow in determining the sign of the feedback. A key element of the positive feedback is the exploitation of both low convective inhibition (CIN) over dry patches (for the initiation of convection) and high CAPE over wet patches (for the generation of precipitation).

Impact of solar versus volcanic activity variations on tropospheric temperatures and precipitation during the Dalton Minimum

The aim of this work is to elucidate the impact of changes in solar irradiance and energetic particles versus volcanic eruptions on tropospheric global climate during the Dalton Minimum (DM, AD 1780–1840). Separate variations in the (i) solar irradiance in the UV-C with wavelengths λ < 250 nm, (ii) irradiance at wavelengths λ > 250 nm, (iii) in energetic particle spectrum, and (iv) volcanic aerosol forcing were analyzed separately, and (v) in combination, by means of small ensemble calculations using a coupled atmosphere–ocean chemistry–climate model. Global and hemispheric mean surface temperatures show a significant dependence on solar irradiance at λ > 250 nm. Also, powerful volcanic eruptions in 1809, 1815, 1831 and 1835 significantly decreased global mean temperature by up to 0.5 K for 2–3 years after the eruption. However, while the volcanic effect is clearly discernible in the Southern Hemispheric mean temperature, it is less significant in the Northern Hemisphere, partly because the two largest volcanic eruptions occurred in the SH tropics and during seasons when the aerosols were mainly transported southward, partly because of the higher northern internal variability. In the simulation including all forcings, temperatures are in reasonable agreement with the tree ring-based temperature anomalies of the Northern Hemisphere. Interestingly, the model suggests that solar irradiance changes at λ < 250 nm and in energetic particle spectra have only an insignificant impact on the climate during the Dalton Minimum. This downscales the importance of top–down processes (stemming from changes at λ < 250 nm) relative to bottom–up processes (from λ > 250 nm). Reduction of irradiance at λ > 250 nm leads to a significant (up to 2%) decrease in the ocean heat content (OHC) between 0 and 300 m in depth, whereas the changes in irradiance at λ < 250 nm or in energetic particles have virtually no effect. Also, volcanic aerosol yields a very strong response, reducing the OHC of the upper ocean by up to 1.5%. In the simulation with all forcings, the OHC of the uppermost levels recovers after 8–15 years after volcanic eruption, while the solar signal and the different volcanic eruptions dominate the OHC changes in the deeper ocean and prevent its recovery during the DM. Finally, the simulations suggest that the volcanic eruptions during the DM had a significant impact on the precipitation patterns caused by a widening of the Hadley cell and a shift in the intertropical convergence zone.

Establishing the skill of climate field reconstruction techniques for precipitation with pseudoproxy experiments

This study aims at assessing the skill of several climate field reconstruction techniques (CFR) to reconstruct past precipitation over continental Europe and the Mediterranean at seasonal time scales over the last two millennia from proxy records. A number of pseudoproxy experiments are performed within the virtual reality ofa regional paleoclimate simulation at 45 km resolution to analyse different aspects of reconstruction skill. Canonical Correlation Analysis (CCA), two versions of an Analog Method (AM) and Bayesian hierarchical modeling (BHM) are applied to reconstruct precipitation from a synthetic network of pseudoproxies that are contaminated with various types of noise. The skill of the derived reconstructions is assessed through comparison with precipitation simulated by the regional climate model. Unlike BHM, CCA systematically underestimates the variance. The AM can be adjusted to overcome this shortcoming, presenting an intermediate behaviour between the two aforementioned techniques. However, a trade-off between reconstruction-target correlations and reconstructed variance is the drawback of all CFR techniques. CCA (BHM) presents the largest (lowest) skill in preserving the temporal evolution, whereas the AM can be tuned to reproduce better correlation at the expense of losing variance. While BHM has been shown to perform well for temperatures, it relies heavily on prescribed spatial correlation lengths. While this assumption is valid for temperature, it is hardly warranted for precipitation. In general, none of the methods outperforms the other. All experiments agree that a dense and regularly distributed proxy network is required to reconstruct precipitation accurately, reflecting its high spatial and temporal variability. This is especially true in summer, when a specifically short de-correlation distance from the proxy location is caused by localised summertime convective precipitation events.

Synoptic drivers of 400 years of summer temperature and precipitation variability on Mt. Olympus, Greece

The Mediterranean region has been identified as a global warming hotspot, where future climate impacts are expected to have significant consequences on societal and ecosystem well-being. To put ongoing trends of summer climate into the context of past natural variability, we reconstructed climate from maximum latewood density (MXD) measurements of Pinus heldreichii (1521–2010) and latewood width (LWW) of Pinus nigra (1617–2010) on Mt. Olympus, Greece. Previous research in the northeastern Mediterranean has primarily focused on inter-annual variability, omitting any low-frequency trends. The present study utilizes methods capable of retaining climatically driven long-term behavior of tree growth. The LWW chronology corresponds closely to early summer moisture variability (May–July, r = 0.65, p < 0.001, 1950–2010), whereas the MXD-chronology relates mainly to late summer warmth (July–September, r = 0.64, p < 0.001; 1899–2010). The chronologies show opposing patterns of decadal variability over the twentieth century (r = −0.68, p < 0.001) and confirm the importance of the summer North Atlantic Oscillation (sNAO) for summer climate in the northeastern Mediterranean, with positive sNAO phases inducing cold anomalies and enhanced cloudiness and precipitation. The combined reconstructions document the late twentieth—early twenty-first century warming and drying trend, but indicate generally drier early summer and cooler late summer conditions in the period ~1700–1900 CE. Our findings suggest a potential decoupling between twentieth century atmospheric circulation patterns and pre-industrial climate variability. Furthermore, the range of natural climate variability stretches beyond summer moisture availabilityobserved in recent decades and thus lends credibility to the significant drying trends projected for this region in current Earth System Model simulations.

Climatology of Vb cyclones, physical mechanisms and their impact on extreme precipitation over Central Europe

Cyclones, which develop over the western Mediterranean and move northeastward are a major source of extreme weather and known to be responsible for heavy precipitation over the northern side of the Alpine range and Central Europe. As the relevant processes triggering these so-called Vb events and their impact on extreme precipitation are not yet fully understood, this study focuses on gaining insight into the dynamics of past events. For this, a cyclone detection and tracking tool is applied to the ERA-Interim reanalysis (1979–2013) to identify prominent Vb situations. Precipitation in the ERA-Interim and the E-OBS data sets is used to evaluate case-to-case precipitation amounts and to assess consistency between the two data sets. Both data sets exhibit high variability in precipitation amounts among different Vb events. While only 23 % of all Vb events are associated with extreme precipitation, around 15 % of all extreme precipitation days (99 percentile) over the northern Alpine region and Central Europe are induced by Vb events, although Vb cyclones are rare events (2.3 per year). To obtain a better understanding of the variability within Vb events, the analysis of the 10 heaviest and lowest precipitation Vb events reveals noticeable differences in the state of the atmosphere. These differences are most pronounced in the geopotential height and potential vorticity field, indicating a much stronger cyclone for heavy precipitation events. The related differences in wind direction are responsible for the moisture transport around the Alps and the orographical lifting along the northern slopes of the Alps. These effects are the main reasons for a disastrous outcome of Vb events, and consequently are absent in the Vb events associated with low precipitation. Hence, our results point out that heavy precipitation related to Vb events is mainly related to large-scale dynamics rather than to thermodynamic processes.

Temperature and precipitation effects on δ13C depth profiles in SOM under temperate beech forests

Enrichment of 13C in SOM with soil depth is related to interacting processes influenced by temperature and precipitation. Our objectives were to derive climate effects on patterns of vertical δ13C values of soil organic matter (SOM) while minimizing the effect of confounding variables. We investigated vertical changes in δ13C values of SOM in 1-cm depth intervals in silvicultural mature beech (Fagus sylvatica L.) forest ecosystems in northern Rhineland-Palatinate across gradients of MAT (7.9 to 9.7 °C mean annual temperature) and MAP (607 to 1085 mm mean annual precipitation) in winter 2011. Forest stands (n = 10) were chosen based on data sets provided by the Rhineland-Palatinate Forest Administration so that variations in these gradients occurred while other environmental factors like physico-chemical soil properties, tree species, stand age, exposition and precipitation (for the temperature gradient) or temperature (for the precipitation gradient) did not differ among study sites. From litter down to the mineral soil at 10 cm depth, soil organic carbon (SOC) content decreased (47.5 ± SE 0.1% to 2.5 ± 0.1%) while the δ13C values increased (− 29.4 ± 0.1‰ to − 26.1 ± 0.1‰). Litter of sites under higher MAP/lower MAT had lower δ13C values which was in line with literature data on climate driven plant physiological process. To compare the dimension of the vertical 13C enrichment, δ13C values were regressed linearly against log-transformed carbon contents yielding absolute values of these slopes (beta). Beta values ranged between 0.6 and 4.5 (range of r from − 0.7 to − 1.0; p < 0.01). Due to an assumed decay continuum and similar variations of δ13C values in litter and in 10 cm depth, we conclude that effects on isotope composition in the Oi layer continue vertically and therefore, δ13C values in litter do not solely control beta values. Beta values decreased with increasing MAT (r = − 0.83; p < 0.05). Reduced soil moisture and therefore both, reduced microbial activity and reduced downward transport of microbial cycled DOM (=13C enriched) might be responsible for less pronounced δ13C depth profiles in case of high temperatures. Greater C:N ratios (lower degradability) of the litter under higher temperatures likely contributed to these depth trends. Beta values increased with increasing MAP (r = 0.73; p < 0.05). We found decreasing C:N ratios in the mineral soil that possibly indicates higher decomposition under higher precipitation. Exclusion of the organic layers from linear regressions indicated a stronger impact of MAP on the development of δ13C depth profiles. Our results confirm temperature and precipitation effects on δ13C depth profiles and indicate stronger 13C enrichment under lower MAT/higher MAP. Therefore, time series of vertical δ13C depth profiles might provide insights into climate change effects.

Inference of evolutionary forces acting on human biological pathways

Because natural selection is likely to act on multiple genes underlying a given phenotypic trait, we study here the potential effect of ongoing and past selection on the genetic diversity of human biological pathways. We first show that genes included in gene sets are generally under stronger selective constraints than other genes and that their evolutionary response is correlated. We then introduce a new procedure to detect selection at the pathway level based on a decomposition of the classical McDonald–Kreitman test extended to multiple genes. This new test, called 2DNS, detects outlier gene sets and takes into account past demographic effects and evolutionary constraints specific to gene sets. Selective forces acting on gene sets can be easily identified by a mere visual inspection of the position of the gene sets relative to their two-dimensional null distribution. We thus find several outlier gene sets that show signals of positive, balancing, or purifying selection but also others showing an ancient relaxation of selective constraints. The principle of the 2DNS test can also be applied to other genomic contrasts. For instance, the comparison of patterns of polymorphisms private to African and non-African populations reveals that most pathways show a higher proportion of nonsynonymous mutations in non-Africans than in Africans, potentially due to different demographic histories and selective pressures.

Constraints on barium isotope fractionation during aragonite precipitation by corals

We present a barium (Ba) isotope fractionation study of marine biogenic carbonates (aragonitic corals). The major aim is to provide first constraints on the Ba isotope fractionation between modern surface sea water and coral skele- ton. Mediterranean surface sea water was found to be enriched in the heavy Ba isotopes compared to previously reported values for marine open ocean authi- genic and terrestrial minerals. In aquarium experiments with a continuous sup- ply of Mediterranean surface water, the Ba isotopic composition of the bulk sample originating from cultured, aragonitic scleractinian corals (d137/134Ba between +0.16 +/- 0.12permil and +0.41 +/-0.12permil) were isotopically identical or lighter than that of the ambient Mediterranean surface sea water (d137/134Ba = +0.42 +/- 0.07permil, 2SD), which corresponds to an empirical maximum value of Ba isotope fractionation of D137/134Bacoral-seawater = -0.26 +/- 0.14permil at 25°C. This maximum Ba isotope fractionation is close and identical in direction to previous results from inorganic precipitation experiments with aragonite- structured pure BaCO3 (witherite). The variability in measured Ba concentrations of the cultured corals is at odds with a uniform distribution coefficient, DBa/Ca, thus indicating stronger vital effects on isotope than element discrimination. This observation supports the hypothesis that the Ba isotopic compositions of these corals do not result from simple equilibrium between the skeleton and the bulk sea water. Complementary coral samples from natural settings (tropical shallow-water corals from the Bahamas and Florida and cold- water corals from the Norwegian continental shelf) show an even wider range in d137/134Ba values (+0.14 +/- 0.08permil and +0.77 +/- 0.11permil), most probably due to additional spatial and/or temporal sea water heterogeneity, as indicated by recent publications.

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

On Bayesian seamless phase I-II designs

Early phase clinical trial designs have long been the focus of interest for clinicians and statisticians working in oncology field. There are several standard phse I and phase II designs that have been widely-implemented in medical practice. For phase I design, the most commonly used methods are 3+3 and CRM. A newly-developed Bayesian model-based mTPI design has now been used by an increasing number of hospitals and pharmaceutical companies. The advantages and disadvantages of these three top phase I designs have been discussed in my work here and their performances were compared using simulated data. It was shown that mTPI design exhibited superior performance in most scenarios in comparison with 3+3 and CRM designs. ^ The next major part of my work is proposing an innovative seamless phase I/II design that allows clinicians to conduct phase I and phase II clinical trials simultaneously. Bayesian framework was implemented throughout the whole design. The phase I portion of the design adopts mTPI method, with the addition of futility rule which monitors the efficacy performance of the tested drugs. Dose graduation rules were proposed in this design to allow doses move forward from phase I portion of the study to phase II portion without interrupting the ongoing phase I dose-finding schema. Once a dose graduated to phase II, adaptive randomization was used to randomly allocated patients into different treatment arms, with the intention of more patients being assigned to receive more promising dose(s). Again simulations were performed to compare the performance of this innovative phase I/II design with a recently published phase I/II design, together with the conventional phase I and phase II designs. The simulation results indicated that the seamless phase I/II design outperform the other two competing methods in most scenarios, with superior trial power and the fact that it requires smaller sample size. It also significantly reduces the overall study time. ^ Similar to other early phase clinical trial designs, the proposed seamless phase I/II design requires that the efficacy and safety outcomes being able to be observed in a short time frame. This limitation can be overcome by using validated surrogate marker for the efficacy and safety endpoints.^