The ERA-Interim reanalysis: configuration and performance of the data assimilation system

ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF

Vertical propagation of information in a middle atmosphere data assimilation system by gravity-wave drag feedbacks

The mesospheric response to the 2002 Antarctic Stratospheric Sudden Warming (SSW) is analysed using the Canadian Middle Atmosphere Model Data Assimilation System (CMAM-DAS), where it represents a vertical propagation of information from the observations into the data-free mesosphere. The CMAM-DAS simulates a cooling in the lowest part of the mesosphere which is accomplished by resolved motions, but which is extended to the mid- to upper mesosphere by the response of the model's non-orographic gravity-wave drag parameterization to the change in zonal winds. The basic mechanism is that elucidated by Holton consisting of a net eastward wave-drag anomaly in the mesosphere during the SSW, although in this case there is a net upwelling in the polar mesosphere. Since the zonal-mean mesospheric response is shown to be predictable, this demonstrates that variations in the mesospheric state can be slaved to the lower atmosphere through gravity-wave drag.

An Earth Observation Land Data Assimilation System (EO-LDAS)

Current methods for estimating vegetation parameters are generally sub-optimal in the way they exploit information and do not generally consider uncertainties. We look forward to a future where operational dataassimilation schemes improve estimates by tracking land surface processes and exploiting multiple types of observations. Dataassimilation schemes seek to combine observations and models in a statistically optimal way taking into account uncertainty in both, but have not yet been much exploited in this area. The EO-LDAS scheme and prototype, developed under ESA funding, is designed to exploit the anticipated wealth of data that will be available under GMES missions, such as the Sentinel family of satellites, to provide improved mapping of land surface biophysical parameters. This paper describes the EO-LDAS implementation, and explores some of its core functionality. EO-LDAS is a weak constraint variational dataassimilationsystem. The prototype provides a mechanism for constraint based on a prior estimate of the state vector, a linear dynamic model, and EarthObservationdata (top-of-canopy reflectance here). The observation operator is a non-linear optical radiative transfer model for a vegetation canopy with a soil lower boundary, operating over the range 400 to 2500 nm. Adjoint codes for all model and operator components are provided in the prototype by automatic differentiation of the computer codes. In this paper, EO-LDAS is applied to the problem of daily estimation of six of the parameters controlling the radiative transfer operator over the course of a year (> 2000 state vector elements). Zero and first order process model constraints are implemented and explored as the dynamic model. The assimilation estimates all state vector elements simultaneously. This is performed in the context of a typical Sentinel-2 MSI operating scenario, using synthetic MSI observations simulated with the observation operator, with uncertainties typical of those achieved by optical sensors supposed for the data. The experiments consider a baseline state vector estimation case where dynamic constraints are applied, and assess the impact of dynamic constraints on the a posteriori uncertainties. The results demonstrate that reductions in uncertainty by a factor of up to two might be obtained by applying the sorts of dynamic constraints used here. The hyperparameter (dynamic model uncertainty) required to control the assimilation are estimated by a cross-validation exercise. The result of the assimilation is seen to be robust to missing observations with quite large data gaps.

Programmable data acquisition system for research measurements from meteorological radiosondes

A programmable data acquisition system to allow novel use of meteorological radiosondes for atmospheric science measurements is described. In its basic form it supports four analogue inputs at 16 bit resolution, and up to two further inputs at lower resolution configurable instead for digital instruments. It also provides multiple instrument power supplies (+8V, +16V, +5V and -8V) from the 9V radiosonde battery. During a balloon flight encountering air temperatures from +17°C to -66°C, the worst case voltage drift in the 5V unipolar digitisation circuitry was 20mV. The system liberates a new range of low cost atmospheric research measurements, by utilising radiosondes routinely launched internationally for weather forecasting purposes. No additional receiving equipment is required. Comparisons between the specially instrumented and standard meteorological radiosondes show negligible effect of the additional instrumentation on the standard meteorological data.

A simple method for integrating a complex model into an ensemble data assimilation system using MPI

This paper details a strategy for modifying the source code of a complex model so that the model may be used in a data assimilation context, {and gives the standards for implementing a data assimilation code to use such a model}. The strategy relies on keeping the model separate from any data assimilation code, and coupling the two through the use of Message Passing Interface (MPI) {functionality}. This strategy limits the changes necessary to the model and as such is rapid to program, at the expense of ultimate performance. The implementation technique is applied in different models with state dimension up to $2.7 \times 10^8$. The overheads added by using this implementation strategy in a coupled ocean-atmosphere climate model are shown to be an order of magnitude smaller than the addition of correlated stochastic random errors necessary for some nonlinear data assimilation techniques.

Data information system to promote the organization data of collections - modeling considerations by the Unified Modelign Language (UML)

Pode-se afirmar que a evolução tecnológica (desenvolvimento de novos instrumentos de medição como, softwares, satélites e computadores, bem como, o barateamento das mídias de armazenamento) permite às Organizações produzirem e adquirirem grande quantidade de dados em curto espaço de tempo. Devido ao volume de dados, Organizações de pesquisa se tornam potencialmente vulneráveis aos impactos da explosão de informações. Uma solução adotada por algumas Organizações é a utilização de ferramentas de sistemas de informação para auxiliar na documentação, recuperação e análise dos dados. No âmbito científico, essas ferramentas são desenvolvidas para armazenar diferentes padrões de metadados (dados sobre dados). Durante o processo de desenvolvimento destas ferramentas, destaca-se a adoção de padrões como a Linguagem Unificada de Modelagem (UML, do Inglês Unified Modeling Language), cujos diagramas auxiliam na modelagem de diferentes aspectos do software. O objetivo deste estudo é apresentar uma ferramenta de sistemas de informação para auxiliar na documentação dos dados das Organizações por meio de metadados e destacar o processo de modelagem de software, por meio da UML. Será abordado o Padrão de Metadados Digitais Geoespaciais, amplamente utilizado na catalogação de dados por Organizações científicas de todo mundo, e os diagramas dinâmicos e estáticos da UML como casos de uso, sequências e classes. O desenvolvimento das ferramentas de sistemas de informação pode ser uma forma de promover a organização e a divulgação de dados científicos. No entanto, o processo de modelagem requer especial atenção para o desenvolvimento de interfaces que estimularão o uso das ferramentas de sistemas de informação.

Venezuela: the Project Data Bank system in Venezuela

Includes bibliography

Collection and uses of hydrological and hydrometeorological data for system operation and planning

Includes bibliography

Data collection system for domestic violence

Includes bibliography

CRS seismic data imaging system: a case study for basib reevaluation

Este trabalho apresenta resultados práticos de uma atenção sistemática dada ao processamento e à interpretação sísmica de algumas linhas terrestres do conjunto de dados do gráben do Tacutu (Brasil), sobre os quais foram aplicadas etapas fundamentais do sistema WIT de imageamento do empilhamento CRS (Superfície de Reflexão Comum) vinculado a dados. Como resultado, esperamos estabelecer um fluxograma para a reavaliação sísmica de bacias sedimentares. Fundamentado nos atributos de frente de onda resultantes do empilhamento CRS, um macro-modelo suave de velocidades foi obtido através de inversão tomográfica. Usando este macro-modelo, foi realizado uma migração à profundidade pré- e pós-empilhamento. Além disso, outras técnicas baseadas no empilhamento CRS foram realizadas em paralelo como correção estática residual e migração de abertura-limitada baseada na zona de Fresnel projetada. Uma interpretação geológica sobre as seções empilhadas e migradas foi esboçada. A partir dos detalhes visuais dos painéis é possível interpretar desconformidades, afinamentos, um anticlinal principal falhado com conjuntos de horstes e grábens. Também, uma parte da linha selecionada precisa de processamento mais detalhado para evidenciar melhor qualquer estrutura presente na subsuperfície.

Comparison of snow data assimilation system with GPS reflectometry snow depth in the Western United States

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Description of atmospheric conditions at the Pierre Auger Observatory using the Global Data Assimilation System (GDAS)

Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.