On the convergence of adaptive sequential Monte Carlo methods

In several implementations of Sequential Monte Carlo (SMC) methods it is natural and important, in terms of algorithmic efficiency, to exploit the information of the history of the samples to optimally tune their subsequent propagations. In this article we provide a carefully formulated asymptotic theory for a class of such adaptive SMC methods. The theoretical framework developed here will cover, under assumptions, several commonly used SMC algorithms [Chopin, Biometrika 89 (2002) 539–551; Jasra et al., Scand. J. Stat. 38 (2011) 1–22; Schäfer and Chopin, Stat. Comput. 23 (2013) 163–184]. There are only limited results about the theoretical underpinning of such adaptive methods: we will bridge this gap by providing a weak law of large numbers (WLLN) and a central limit theorem (CLT) for some of these algorithms. The latter seems to be the first result of its kind in the literature and provides a formal justification of algorithms used in many real data contexts [Jasra et al. (2011); Schäfer and Chopin (2013)]. We establish that for a general class of adaptive SMC algorithms [Chopin (2002)], the asymptotic variance of the estimators from the adaptive SMC method is identical to a “limiting” SMC algorithm which uses ideal proposal kernels. Our results are supported by application on a complex high-dimensional posterior distribution associated with the Navier–Stokes model, where adapting high-dimensional parameters of the proposal kernels is critical for the efficiency of the algorithm

Estimating the effect of rainfall on the surface temperature of a tropical lake

We make use of a unique high-quality, long-term observational dataset on a tropical lake to assess the effect of rainfall on lake surface temperature. The lake in question is Lake Kivu, one of the African Great Lakes, and was selected for its remarkably uniform climate and availability of multi-year over-lake meteorological observations. Rain may have a cooling effect on the lake surface by lowering the near-surface air temperature, by the direct rain heat flux into the lake, by mixing the lake surface layer through the flux of kinetic energy and by convective mixing of the lake surface layer. The potential importance of the rainfall effect is discussed in terms of both heat flux and kinetic energy flux. To estimate the rainfall effect on the mean diurnal cycle of lake surface temperature, the data are binned into categories of daily rainfall amount. They are further filtered based on comparable values of daily mean net radiation, which reduces the influence of radiative-flux differences. Our results indicate that days with heavy rainfall may experience a reduction in lake surface temperature of approximately 0.3&thinsp;K by the end of the day compared to days with light to moderate rainfall. Overall this study highlights a new potential control on lake surface temperature and suggests that further efforts are needed to quantify this effect in other regions and to include this process in land surface models used for atmospheric prediction.</p

Evaluating and improving the Community Land Model's sensitivity to land cover

Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate

Modelling the water balance of Lake Victoria (East Africa) – Part 1: Observational analysis

Lake Victoria is the largest lake in Africa and one of the two major sources of the Nile river. The water level of Lake Victoria is determined by its water balance, consisting of precipitation on the lake, evaporation from the lake, inflow from tributary rivers and lake outflow, controlled by two hydropower dams. Due to a scarcity of in situ observations, previous estimates of individual water balance terms are characterized by substantial uncertainties, which means that the water balance is often not closed independently. In this first part of a two-paper series, we present a water balance model for Lake Victoria, using state-of-the-art remote sensing observations, high-resolution reanalysis downscaling and outflow values recorded at the dam. The uncalibrated computation of the individual water balance terms yields lake level fluctuations that closely match the levels retrieved from satellite altimetry. Precipitation is the main cause of seasonal and interannual lake level fluctuations, and on average causes the lake level to rise from May to July and to fall from August to December. Finally, our results indicate that the 2004–2005 drop in lake level can be about half attributed to a drought in the Lake Victoria Basin and about half to an enhanced outflow, highlighting the sensitivity of the lake level to human operations at the outflow dam.</p

Modelling the water balance of Lake Victoria (East Africa) – Part 2: Future projections

Lake Victoria, the second largest freshwater lake in the world, is one of the major sources of the Nile river. The outlet to the Nile is controlled by two hydropower dams of which the allowed discharge is dictated by the Agreed Curve, an equation relating outflow to lake level. Some regional climate models project a decrease in precipitation and an increase in evaporation over Lake Victoria, with potential important implications for its water balance and resulting level. Yet, little is known about the potential consequences of climate change for the water balance of Lake Victoria. In this second part of a two-paper series, we feed a new water balance model for Lake Victoria presented in the first part with climate simulations available through the COordinated Regional Climate Downscaling Experiment (CORDEX) Africa framework. Our results reveal that most regional climate models are not capable of giving a realistic representation of the water balance of Lake Victoria and therefore require bias correction. For two emission scenarios (RCPs 4.5 and 8.5), the decrease in precipitation over the lake and an increase in evaporation are compensated by an increase in basin precipitation leading to more inflow. The future lake level projections show that the dam management scenario and not the emission scenario is the main controlling factor of the future water level evolution. Moreover, inter-model uncertainties are larger than emission scenario uncertainties. The comparison of four idealized future management scenarios pursuing certain policy objectives (electricity generation, navigation reliability and environmental conservation) uncovers that the only sustainable management scenario is mimicking natural lake level fluctuations by regulating outflow according to the Agreed Curve. The associated outflow encompasses, however, ranges from 14&thinsp;m3&thinsp;day−1 (−85&thinsp;%) to 200&thinsp;m3&thinsp;day−1 (+100&thinsp;%) within this ensemble, highlighting that future hydropower generation and downstream water availability may strongly change in the next decades even if dam management adheres to he Agreed Curve. Our results overall underline that managing the dam according to the Agreed Curve is a key prerequisite for sustainable future lake levels, but that under this management scenario, climate change might potentially induce profound changes in lake level and outflow volume.</p

Un nouvel indicateur intégré d’évaluation des dégâts occasionnés aux grappes par des bioagresseurs majeurs au vignoble

Communication faite au cours du colloque DinABio2013, 13 et 14 novembre 2013; Tours, FranceAn original and integrative evaluation indicator has been developed to quantify the cumulated damage from major pests and diseases affecting grape bunches: downy mildew, powdery mildew, gray mould and tortricid moths. It made it possible to estimate the associated crop losses and to relate them to the plant protection strategy in different modes of production (organic farming, in-transition, conventional). Thus, overall plant losses were higher in 2012 than in 2011. The in-transition growers’ strategy, with reduced copper doses but increased numbers of sprays, led to a 20% increase in average severity on bunches (essentially due to Downy mildew). The more pragmatic approach of experienced organic growers and conventional ones (higher doses and fewer sprays) reduced the yield losses. The proposed indicator is used for two purposes, i) evaluating the quantitative losses due to pest attacksand ii) differentiating them from other non-pest ones. A more detailed analysis including the impact on performance will be achieved and published soon.Un indicateur d’évaluation, l’IEDG (Indicateur d’Evaluation des Dégâts sur Grappes), a été mis au point pour quantifier les dégâts cumulés dus aux principaux bioagresseurs affectant les grappes de raisin : mildiou, oïdium, pourriture grise et tordeuses. Il permet d’estimer la perte de récolte imputable au cortège parasitaire et de faire le lien avec la stratégie phytosanitaire adoptée (caractérisée ici par l’IFT) et le mode de production (AB, conversion, conventionnel). Ainsi, les pertes sanitaires ont été supérieures en 2012 par rapport à 2011. La stratégie phytosanitaire des viticulteurs en conversion, basée sur des réductions de dose de cuivre de près de 80% et des passages plus nombreux dans les parcelles, n’a pas été efficiente en 2012 avec des sévérités proches de 20% sur grappe, essentiellement dues au mildiou. L’utilisation de doses d’applications supérieures et moins de passages dans les parcelles limite les dommages chez les autres viticulteurs. L’indicateur proposé permet d’évaluer les pertes quantitatives générées par les attaques de bioagresseurs et de les différencier des autres pertes non parasitaires. Une analyse plus fine incluant l’effet région et l’impact sur le rendement devra être réalisée

Asymptotic Analysis of the Random-walk Metropolis Algorithm on Ridged Densities

We study the asymptotic behavior of the Random-Walk Metropolis algorithm on ‘ridged’ probability densities where most of the probability mass is distributed along some key directions. Such class of probability measures arise in various applied contexts including for instance Bayesian inverse problems where the posterior measure concentrates on a manifold when the noise variance goes to zero. When the target measure concentrates on a linear manifold, we derive analytically a diffusion limit for the Random-Walk Metropolis Markov chain as the scale parameter goes to zero. In contrast to the existing works on scaling limits, our limiting Stochastic Differential Equation does not in general have a constant diffusion coefficient. Our results show that in some cases, the usual practice of adapting the step-size to control the acceptance probability might be sub-optimal as the optimal acceptance probability is zero (in the limit)

Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of local climate zones (LCZs) for modeling malaria prevalence rate (PfPR2-10) and studying malaria prevalence in urban settings across nine sub-Saharan African cities. Using a random forest classification algorithm over a set of 365 malaria surveys we: (i) identify a suitable set of covariates derived from open-source earth observations; and (ii) depict the best buffer size at which to aggregate them for modeling PfPR2-10. Our results demonstrate that geographical models can learn from LCZ over a set of cities and be transferred over a city of choice that has few or no malaria surveys. In particular, we find that urban areas systematically have lower PfPR2-10 (5%-30%) than rural areas (15%-40%). The PfPR2-10 urban-to-rural gradient is dependent on the climatic environment in which the city is located. Further, LCZs show that more open urban environments located close to wetlands have higher PfPR2-10. Informal settlements - represented by the LCZ 7 (lightweight lowrise) - have higher malaria prevalence than other densely built-up residential areas with a mean prevalence of 11.11%. Overall, we suggest the applicability of LCZs for more exploratory modeling in urban malaria studies. © 2020 The Author(s). Published by IOP Publishing Ltd.info:eu-repo/semantics/publishe

Phosphoproteomics Screen Reveals Akt Isoform-Specific Signals Linking RNA Processing to Lung Cancer

The three Akt isoforms are functionally distinct. Here we show that their phosphoproteomes also differ, suggesting that their functional differences are due to differences in target specificity. One of the top cellular functions differentially regulated by Akt isoforms is RNA processing. IWS1, an RNA processing regulator, is phosphorylated by Akt3 and Akt1 at Ser720/Thr721. The latter is required for the recruitment of SETD2 to the RNA Pol II complex. SETD2 trimethylates histone H3 at K36 during transcription, creating a docking site for MRG15 and PTB. H3K36me3-bound MRG15 and PTB regulate FGFR-2 splicing, which controls tumor growth and invasiveness downstream of IWS1 phosphorylation. Twenty-one of the twenty-four non-small-cell-lung carcinomas we analyzed express IWS1. More importantly, the stoichiometry of IWS1 phosphorylation in these tumors correlates with the FGFR-2 splicing pattern and with Akt phosphorylation and Akt3 expression. These data identify an Akt isoform-dependent regulatory mechanism for RNA processing and demonstrate its role in lung cancer

A semi-schematic model for the center of mass dynamics in supercooled molecular liquids

We introduce a semi-schematic mode-coupling model to describe the slow dynamics in molecular liquids, retaining explicitly only the description of the center of mass degrees of freedom. Angular degrees of freedom are condensed in a q-vector independent coupling parameter. We compare the time and q-dependence of the density fluctuation correlators with numerical data from a 250 ns long molecular dynamics simulation. Notwithstanding the choice of a network-forming liquid as a model for comparing theory and simulation, the model describes the main static and dynamic features of the relaxation in a broad q-vector range.Comment: Revtex, 2 figure