Climate forcing reconstructions for use in the PMIP simulations of the last millennium

Simulations of climate over the Last Millennium (850–1850 CE) have been incorporated into the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3). The drivers of climate over this period are chiefly orbital, solar, volcanic, changes in land use/land cover and some variation in greenhouse gas levels. While some of these effects can be easily defined, the reconstructions of solar, volcanic and land use-related forcing are more uncertain. We describe here the approach taken in defining the scenarios used in PMIP3, document the forcing reconstructions and discuss likely implications.

Climate forcing reconstructions for use in PMIP simulations of the Last Millennium (v1

We update the forcings for the PMIP3 experiments for the Last Millennium to include new assessments of historical land use changes and discuss new suggestions for calibrating solar activity proxies to total solar irradiance.

A Combinatorial Approach to the Variable Selection in Multiple Linear Regression: Analysis of Selwood et al Data set -A Case Study.

A combinatorial protocol (CP) is introduced here to interface it with the multiple linear regression (MLR) for variable selection. The efficiency of CP-MLR is primarily based on the restriction of entry of correlated variables to the model development stage. It has been used for the analysis of Selwood et al data set [16], and the obtained models are compared with those reported from GFA [8] and MUSEUM [9] approaches. For this data set CP-MLR could identify three highly independent models (27, 28 and 31) with Q2 value in the range of 0.632-0.518. Also, these models are divergent and unique. Even though, the present study does not share any models with GFA [8], and MUSEUM [9] results, there are several descriptors common to all these studies, including the present one. Also a simulation is carried out on the same data set to explain the model formation in CP-MLR. The results demonstrate that the proposed method should be able to offer solutions to data sets with 50 to 60 descriptors in reasonable time frame. By carefully selecting the inter-parameter correlation cutoff values in CP-MLR one can identify divergent models and handle data sets larger than the present one without involving excessive computer time.

DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands

Simulating the spatio-temporal dynamics of inundation is key to understanding the role of wetlands under past and future climate change. Earlier modelling studies have mostly relied on fixed prescribed peatland maps and inundation time series of limited temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based on TOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally efficient TOPMODEL implementation. This approach rests on an empirical, grid-cell-specific relationship between the mean soil water balance and the flooded area. DYPTOP combines the simulated inundation extent and its temporal persistency with criteria for the ecosystem water balance and the modelled peatland-specific soil carbon balance to predict the global distribution of peatlands. We apply DYPTOP in combination with the LPX-Bern DGVM and benchmark the global-scale distribution, extent, and seasonality of inundation against satellite data. DYPTOP successfully predicts the spatial distribution and extent of wetlands and major boreal and tropical peatland complexes and reveals the governing limitations to peatland occurrence across the globe. Peatlands covering large boreal lowlands are reproduced only when accounting for a positive feedback induced by the enhanced mean soil water holding capacity in peatland-dominated regions. DYPTOP is designed to minimize input data requirements, optimizes computational efficiency and allows for a modular adoption in Earth system models.

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

Construcción de repositorios institucionales open source con Software Greenstone

Se aborda la construcción de repositorios institucionales open source con Software Greenstone. Se realiza un recorrido teórico y otro modélico desarrollando en él una aplicación práctica. El primer recorrido, que constituye el marco teórico, comprende una descripción, de: la filosofía open access (acceso abierto) y open source (código abierto) para la creación de repositorios institucionales. También abarca en líneas generales las temáticas relacionadas al protocolo OAI, el marco legal en lo que hace a la propiedad intelectual, las licencias y una aproximación a los metadatos. En el mismo recorrido se abordan aspectos teóricos de los repositorios institucionales: acepciones, beneficios, tipos, componentes intervinientes, herramientas open source para la creación de repositorios, descripción de las herramientas y finalmente, la descripción ampliada del Software Greenstone; elegido para el desarrollo modélico del repositorio institucional colocado en un demostrativo digital. El segundo recorrido, correspondiente al desarrollo modélico, incluye por un lado el modelo en sí del repositorio con el Software Greenstone; detallándose aquí uno a uno los componentes que lo conforman. Es el insumo teórico-práctico para el diseño -paso a paso- del repositorio institucional. Por otro lado, se incluye el resultado de la modelización, es decir el repositorio creado, el cual es exportado en entorno web a un soporte digital para su visibilización. El diseño del repositorio, paso a paso, constituye el núcleo sustantivo de aportes de este trabajo de tesina

Construcción de repositorios institucionales open source con Software Greenstone

Se aborda la construcción de repositorios institucionales open source con Software Greenstone. Se realiza un recorrido teórico y otro modélico desarrollando en él una aplicación práctica. El primer recorrido, que constituye el marco teórico, comprende una descripción, de: la filosofía open access (acceso abierto) y open source (código abierto) para la creación de repositorios institucionales. También abarca en líneas generales las temáticas relacionadas al protocolo OAI, el marco legal en lo que hace a la propiedad intelectual, las licencias y una aproximación a los metadatos. En el mismo recorrido se abordan aspectos teóricos de los repositorios institucionales: acepciones, beneficios, tipos, componentes intervinientes, herramientas open source para la creación de repositorios, descripción de las herramientas y finalmente, la descripción ampliada del Software Greenstone; elegido para el desarrollo modélico del repositorio institucional colocado en un demostrativo digital. El segundo recorrido, correspondiente al desarrollo modélico, incluye por un lado el modelo en sí del repositorio con el Software Greenstone; detallándose aquí uno a uno los componentes que lo conforman. Es el insumo teórico-práctico para el diseño -paso a paso- del repositorio institucional. Por otro lado, se incluye el resultado de la modelización, es decir el repositorio creado, el cual es exportado en entorno web a un soporte digital para su visibilización. El diseño del repositorio, paso a paso, constituye el núcleo sustantivo de aportes de este trabajo de tesina

(Table 1) Summary statistics of in situ sea-ice characteristics of Ice Station Belgica sites Fabra, Patria/Liège and Brussels in October 2007

Three ice type regimes at Ice Station Belgica (ISB), during the 2007 International Polar Year SIMBA (Sea Ice Mass Balance in Antarctica) expedition, were characterized and assessed for elevation, snow depth, ice freeboard and thickness. Analyses of the probability distribution functions showed great potential for satellite-based altimetry for estimating ice thickness. In question is the required altimeter sampling density for reasonably accurate estimation of snow surface elevation given inherent spatial averaging. This study assesses an effort to determine the number of laser altimeter 'hits' of the ISB floe, as a representative Antarctic floe of mixed first- and multi-year ice types, for the purpose of statistically recreating the in situ-determined ice-thickness and snow depth distribution based on the fractional coverage of each ice type. Estimates of the fractional coverage and spatial distribution of the ice types, referred to as ice 'towns', for the 5 km**2 floe were assessed by in situ mapping and photo-visual documentation. Simulated ICESat altimeter tracks, with spot size ~70 m and spacing ~170 m, sampled the floe's towns, generating a buoyancy-derived ice thickness distribution. 115 altimeter hits were required to statistically recreate the regional thickness mean and distribution for a three-town assemblage of mixed first- and multi-year ice, and 85 hits for a two-town assemblage of first-year ice only: equivalent to 19.5 and 14.5 km respectively of continuous altimeter track over a floe region of similar structure. Results have significant implications toward model development of sea-ice sampling performance of the ICESat laser altimeter record as well as maximizing sampling characteristics of satellite/airborne laser and radar altimetry missions for sea-ice thickness.