Diagnosing observation error correlations for Doppler radar radial winds in the Met Office UKV model using observation-minus-background and observation-minus-analysis statistics

With the development of convection-permitting numerical weather prediction the efficient use of high resolution observations in data assimilation is becoming increasingly important. The operational assimilation of these observations, such as Dopplerradar radial winds, is now common, though to avoid violating the assumption of un- correlated observation errors the observation density is severely reduced. To improve the quantity of observations used and the impact that they have on the forecast will require the introduction of the full, potentially correlated, error statistics. In this work, observation error statistics are calculated for the Doppler radar radial winds that are assimilated into the Met Office high resolution UK model using a diagnostic that makes use of statistical averages of observation-minus-background and observation-minus-analysis residuals. This is the first in-depth study using the diagnostic to estimate both horizontal and along-beam correlated observation errors. By considering the new results obtained it is found that the Doppler radar radial wind error standard deviations are similar to those used operationally and increase as the observation height increases. Surprisingly the estimated observation error correlation length scales are longer than the operational thinning distance. They are dependent on both the height of the observation and on the distance of the observation away from the radar. Further tests show that the long correlations cannot be attributed to the use of superobservations or the background error covariance matrix used in the assimilation. The large horizontal correlation length scales are, however, in part, a result of using a simplified observation operator.

Continental and global scale flood forecasting systems

Floods are the most frequent of natural disasters, affecting millions of people across the globe every year. The anticipation and forecasting of floods at the global scale is crucial to preparing for severe events and providing early awareness where local flood models and warning services may not exist. As numerical weather prediction models continue to improve, operational centres are increasingly using the meteorological output from these to drive hydrological models, creating hydrometeorological systems capable of forecasting river flow and flood events at much longer lead times than has previously been possible. Furthermore, developments in, for example, modelling capabilities, data and resources in recent years have made it possible to produce global scale flood forecasting systems. In this paper, the current state of operational large scale flood forecasting is discussed, including probabilistic forecasting of floods using ensemble prediction systems. Six state-of-the-art operational large scale flood forecasting systems are reviewed, describing similarities and differences in their approaches to forecasting floods at the global and continental scale. Currently, operational systems have the capability to produce coarse-scale discharge forecasts in the medium-range and disseminate forecasts and, in some cases, early warning products, in real time across the globe, in support of national forecasting capabilities. With improvements in seasonal weather forecasting, future advances may include more seamless hydrological forecasting at the global scale, alongside a move towards multi-model forecasts and grand ensemble techniques, responding to the requirement of developing multi-hazard early warning systems for disaster risk reduction.

A systematic method of parameterisation estimation using data assimilation

In numerical weather prediction, parameterisations are used to simulate missing physics in the model. These can be due to a lack of scientific understanding or a lack of computing power available to address all the known physical processes. Parameterisations are sources of large uncertainty in a model as parameter values used in these parameterisations cannot be measured directly and hence are often not well known; and the parameterisations themselves are also approximations of the processes present in the true atmosphere. Whilst there are many efficient and effective methods for combined state/parameter estimation in data assimilation (DA), such as state augmentation, these are not effective at estimating the structure of parameterisations. A new method of parameterisation estimation is proposed that uses sequential DA methods to estimate errors in the numerical models at each space-time point for each model equation. These errors are then fitted to pre-determined functional forms of missing physics or parameterisations that are based upon prior information. We applied the method to a one-dimensional advection model with additive model error, and it is shown that the method can accurately estimate parameterisations, with consistent error estimates. Furthermore, it is shown how the method depends on the quality of the DA results. The results indicate that this new method is a powerful tool in systematic model improvement.

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

The role of evaporating showers in the transfer of sting-jet momentum to the surface

The most damaging winds in a severe extratropical cyclone often occur just ahead of the evaporating ends of cloud filaments emanating from the so-called cloud head. These winds are associated with low-level jets (LLJs), sometimes occurring just above the boundary layer. The question then arises as to how the high momentum is transferred to the surface. An opportunity to address this question arose when the severe ‘St Jude's Day’ windstorm travelled across southern England on 28 October 2013. We have carried out a mesoanalysis of a network of 1 min resolution automatic weather stations and high-resolution Doppler radar scans from the sensitive S-band Chilbolton Advanced Meteorological Radar (CAMRa), along with satellite and radar network imagery and numerical weather prediction products. We show that, although the damaging winds occurred in a relatively dry region of the cyclone, there was evidence within the LLJ of abundant precipitation residues from shallow convective clouds that were evaporating in a localized region of descent. We find that pockets of high momentum were transported towards the surface by the few remaining actively precipitating convective clouds within the LLJ and also by precipitation-free convection in the boundary layer that was able to entrain evaporatively cooled air from the LLJ. The boundary-layer convection was organized in along-wind rolls separated by 500 to about 3000 m, the spacing varying according to the vertical extent of the convection. The spacing was greatest where the strongest winds penetrated to the surface. A run with a medium-resolution version of the Weather Research and Forecasting (WRF) model was able to reproduce the properties of the observed LLJ. It confirmed the LLJ to be a sting jet, which descended over the leading edge of a weaker cold-conveyor-belt jet.

Atmospheric Models Applied to DGPS and RTK Network in Brazil: Preliminary Results

Several positioning techniques have been developed to explore the GPS capability to provide precise coordinates in real time. However, a significant problem to all techniques is the ionosphere effect and the troposphere refraction. Recent researches in Brazil, at São Paulo State University (UNESP), have been trying to tackle these problems. In relation to the ionosphere effects it has been developed a model named Mod_Ion. Concerning tropospheric refraction, a model of Numerical Weather Prediction(NWP) has been used to compute the zenithal tropospheric delay (ZTD). These two models have been integrated with two positioning methods: DGPS (Differential GPS) and network RTK (Real Time Kinematic). These two positioning techniques are being investigated at São Paulo State University (UNESP), Brazil. The in-house DGPS software was already finalized and has provided very good results. The network RTK software is still under development. Therefore, only preliminary results from this method using the VRS (Virtual Reference Station) concept are presented.

Assimilação do IWV-GPS no Brasil: otimização das estimativas do atraso zenital troposférico em tempo real

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Avaliação das previsões do atraso zenital troposférico para a América do Sul, obtidas usando modelo de previsão numérica de tempo com alta resolução espacial

A Center for Weather Forecast and Climatic Studies of National Institute for Space Research (CPTEC/INPE) has provided to the Brazilian Geodetic community, since 2004, an alternative to correct the GNSS observables from the tropospheric refraction. Numerical Weather Prediction (NWP) Model is used to generate Zenital Tropospheric Delay (ZTD). For the version 1, it was developed a model with horizontal resolution of 100 km, which was updated with Eta model, with resolution of 20 km. This paper provides the most significative details of the current version, as well an evaluation of its quality, using for such ZTD estimates from GPS data collect at RBMC. Comparing to the old version, considerable improvement could be observed from the new model, mainly in Brasilia and Curitiba, reaching up to 55% improvement. When all stations were used in the quality control, almost null bias and RMS of about 4 to 5 cm could be observed.

Modelagem neutrosférica sobre a América do Sul baseada em PNT e assimilação de dados locais e robusta avaliação utilizando observações GNSS

Pós-graduação em Ciências Cartográficas - FCT

Posicionamento GPS utilizando o conceito de estação virtual

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimativas do IWV utilizando receptores GPS em bases terrestres no Brasil: sinergia entre a geodésia e a meteorologia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Modelo OLAM (ocean-land-atmosphere-model): descrição, aplicações, e perspectivas

O modelo OLAM foi desenvolvido com objetivo de estender a capacidade de representar os fenômenos de escala global e regional simultaneamente. Este modelo apresenta inovações quanto aos processos dinâmicos, configuração de grade, estrutura de memória e técnicas de solução numérica das equações prognósticas. As equações de Navier-Stokes são resolvidas através da técnica de volumes finitos que conservam massa, momento e energia. No presente trabalho, apresenta-se uma descrição sucinta do OLAM e alguns resultados de sua aplicação em simulações climáticas da precipitação mensal para a região norte da América do Sul, bem como em rodadas para previsão numérica de tempo regional. Os resultados mostram que o modelo consegue representar bem os aspectos meteorológicos de grande escala. Em geral, seu desempenho melhora quando são adotadas grades de maior resolução espacial, nas quais se verificam melhorias significativas tanto na estimativa da precipitação mensal regional, quanto na previsão numérica de tempo.

Análise de modelos troposféricos no posicionamento baseado em redes usando o conceito de VRS

In the past few years several GPS (Global Position System) positioning techniques have been develope and/or improved with the goal of obtaining high accuracy and productivity in real time. The reference station network concept besides to enabling quality and reliability in positioning for scientific and civil GPS community, allows studies concerning tropospheric refraction modeling in the network region. Moreover, among the network corrections transmission methods available to users, there is the VRS (Virtual Reference Station) concept. In this method, the data of a virtual station are generated near the rover receiver (user). This provides a short baseline and the user has the possibility of using a single frequency receiver to accomplish the relative positioning. In this paper, the methodology applied to generate VRS data, using different tropospheric models is described. Thus, comparative tests were conducted in the four seasons with the NWP/INPE (Numerical Weather Prediction/National Institute for Space Research) and Hopfield tropospheric models. In order to analyse the VRS data quality, it was used the Precise Point Positioning (PPP) method, where satisfactory results were found. Mean differences between PNT/INPE and Hopfield models of 9.75% and 24.2% for the hydrostatic and wet days, respectively were obtained.

AVALIAÇÃO ROBUSTA DA MODELAGEM NEUTROSFÉRICA SOBRE O TERRITÓRIO BRASILEIRO BASEADA EM MODELOS DE PREVISÃO NUMÉRICA DE TEMPO DA AMÉRICA DO SUL

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Potential impacts of polar fronts on sedimentation processes at Abrolhos coral reef (South-West Atlantic Ocean/Brazil)

Several reefs of the world have undergone changes in community due to sedimentation processes. It has been suggested that Abrolhos reefs (Brazil/South-West Atlantic) are subjected to a steady coastal influence, although there is still little information regarding this assumption. In this work, we have analyzed a set of environmental parameters concerning sedimentation characteristics at the Abrolhos reefs, near 18 degrees S-39 degrees W. The analysis included remote sensing, model and in situ data to provide a three-dimensional quantitative description of the processes that influence sediment apportionment to the reefs. Mineralogy and natural radioactivity of sediment trapped at three reef sites in a transect perpendicular to the coastline were used in conjunction with numerical weather prediction model and remote sensing databases. We have observed an increase of around 100% of sediment flux during the summer compared to the winter season. A comparison of regional rainfall regime, sediment plume dynamics and a year-around monitoring of polar fronts trajectories and surface wind showed that the wind-driven resedimentation due to polar front activity is the major contributor to the intensification of sedimentation processes at the offshore area of Abrolhos reefs, despite river runoff from mainland. (C) 2007 Elsevier Ltd. All rights reserved.