Models of everywhere revisited: a technological perspective

The concept ‘models of everywhere’ was first introduced in the mid 2000s as a means of reasoning about the environmental science of a place, changing the nature of the underlying modelling process, from one in which general model structures are used to one in which modelling becomes a learning process about specific places, in particular capturing the idiosyncrasies of that place. At one level, this is a straightforward concept, but at another it is a rich multi-dimensional conceptual framework involving the following key dimensions: models of everywhere, models of everything and models at all times, being constantly re-evaluated against the most current evidence. This is a compelling approach with the potential to deal with epistemic uncertainties and nonlinearities. However, the approach has, as yet, not been fully utilised or explored. This paper examines the concept of models of everywhere in the light of recent advances in technology. The paper argues that, when first proposed, technology was a limiting factor but now, with advances in areas such as Internet of Things, cloud computing and data analytics, many of the barriers have been alleviated. Consequently, it is timely to look again at the concept of models of everywhere in practical conditions as part of a trans-disciplinary effort to tackle the remaining research questions. The paper concludes by identifying the key elements of a research agenda that should underpin such experimentation and deployment

Using a Grid-Enabled Wireless Sensor Network for Flood Management

Flooding is becoming an increasing problem. As a result there is a need to deploy more sophisticated sensor networks to detect and react to flooding. This paper outlines a demonstration that illustrates our proposed solution to this problem involving embedded wireless hardware, component based middleware and overlay networks

Behavioral Health and Performance Operations During the Space Shuttle Program

Prior to the Columbia STS 107 disaster in 2003, the Johnson Space Center s Behavioral Health and Performance Group (BHP) became involved in Space Shuttle Operations on an as needed basis, occasionally acting as a consultant and primarily addressing crew-crew personality conflicts. The BHP group also assisted with astronaut selection at every selection cycle beginning in 1991. Following STS 107, an event that spawned an increased need of behavioral health support to STS crew members and their dependents, BHP services to the Space Shuttle Program were enhanced beginning with the STS 114 Return to Flight mission in 2005. These services included the presence of BHP personnel at STS launches and landings for contingency support, a BHP briefing to the entire STS crew at L-11 months, a private preflight meeting with the STS Commander at L-9 months, and the presence of a BHP consultant at the L-1.5 month Family Support Office briefing to crew and family members. The later development of an annual behavioral health assessment of all active astronauts also augmented BHP s Space Shuttle Program specific services, allowing for private meetings with all STS crew members before and after each mission. The components of each facet of these BHP Space Shuttle Program support services will be presented, along with valuable lessons learned, and with recommendations for BHP involvement in future short duration space mission

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

Hyperresolution information and hyperresolution ignorance in modelling the hydrology of the land surface

There is a strong drive towards hyperresolution earth system models in order to resolve finer scales of motion in the atmosphere. The problem of obtaining more realistic representation of terrestrial fluxes of heat and water, however, is not just a problem of moving to hyperresolution grid scales. It is much more a question of a lack of knowledge about the parameterisation of processes at whatever grid scale is being used for a wider modelling problem. Hyperresolution grid scales cannot alone solve the problem of this hyperresolution ignorance. This paper discusses these issues in more detail with specific reference to land surface parameterisations and flood inundation models. The importance of making local hyperresolution model predictions available for evaluation by local stakeholders is stressed. It is expected that this will be a major driving force for improving model performance in the future. Keith BEVEN, Hannah CLOKE, Florian PAPPENBERGER, Rob LAMB, Neil HUNTE

NASA Astronaut Selection 2009: Behavioral Overview

NASA's multi-phase U.S. astronaut selection process seeks to identify the most qualified astronaut candidates from a large number of applicants. With the approaching retirement of the Space Shuttle, NASA focused on selecting those individuals who were most suited to the unique demands of long-duration spaceflight. In total, NASA received 3,535 applications for the 2009 astronaut selection cycle. Of these, 123 were invited to NASA Johnson Space Center (JSC) for Round 1 initial screening and interviews, which consisted of an Astronaut Selection Board (ASB) preliminary interview, medical review, and psychological testing. Of these, 48 individuals were invited to return for Round 2. This round consisted of medical testing, further behavioral assessments, and a second ASB interview. Following this, nine astronaut candidates (ASCANs) were ultimately chosen to go forward to basic training. The contents, benefits, and lessons learned from implementing this phased process will be discussed. The lessons learned can benefit the future selection of space flyers, whether they are NASA or commercial. Learning Objective: 1) Familiarization with the 2009 NASA behavioral screening process for astronaut applicants

Legacy of Operational Space Medicine During the Space Shuttle Program

The Johnson Space Center s Medical Science Division branches were involved in preparing astronauts for space flight during the 30 year period of the Space Shuttle Program. These branches included the Flight Medicine Clinic, Medical Operations and the Behavioral Health Program. The components of each facet of these support services were: the Flight Medicine Clinic s medical selection process and medical care; the Medical Operations equipment, training, procedures and emergency medical services; and the Behavioral Health and Performance operations. Each presenter will discuss the evolution of its operations, implementations, lessons learned and recommendations for future vehicles and short duration space missions

Technical Note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty

There is a general trend for increasing inclusion of uncertainty estimation in the environmental modelling domain. We present the CREDIBLE Uncertainty Estimation (CURE) Toolbox, an open source MATLABTM toolbox for uncertainty estimation aimed at scientists and practitioners that are not necessarily experts in uncertainty estimation. The toolbox focusses on environmental simulation models and hence employs a range of different Monte Carlo methods for forward and conditioned uncertainty estimation. The methods included span both formal statistical and informal approaches, which are demonstrated using a range of modelling applications set up as workflow scripts. The workflow scripts provide examples of how to utilise toolbox functions for a variety of modelling applications and hence aid the user in defining their own workflow: additional help is provided by extensively commented code. The toolbox implementation aims to increase the uptake of uncertainty estimation methods within a framework designed to be open and explicit, in a way that tries to represent best practice in applying the methods included. Best practice in the evaluation of modelling assumptions and choices, specifically including epistemic uncertainties, is also included by the incorporation of a condition tree that allows users to record assumptions and choices made as an audit trail log.</p