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Weather Prediction (weather + prediction)
Kinds of Weather Prediction Terms modified by Weather Prediction Selected AbstractsThe Next Generation Road Weather Information System: A New Paradigm for Road and Rail Severe Weather Prediction in the UKGEOGRAPHY COMPASS (ELECTRONIC), Issue 4 2008John Thornes The use of road weather information systems for the winter maintenance of roads is now widespread around the world. However, road weather forecasts are normally only made available for a limited number of road sensor sites in a region. For example, in Birmingham, UK, there is one forecast site for 26 salting routes. XRWIS is the next generation road weather information system that forecasts for every 20 m along each salting route (typically 50 km long) using a geographical information system, sky-view factor analysis and mesoscale weather forecasts. Treatment requirements for each salting route are then visualised in simple ,traffic-light' style colours. In a recent winter-long trial in Devon, UK, up to 78 salting runs on six salting routes could have been prevented saving up to Ł80,000 in labour and materials. Other potential applications of XRWIS include the prediction of low rail adhesion in winter, due to ice, frost and snow, and track buckling in summer. [source] Modeling and predicting complex space,time structures and patterns of coastal wind fieldsENVIRONMETRICS, Issue 5 2005Montserrat Fuentes Abstract A statistical technique is developed for wind field mapping that can be used to improve either the assimilation of surface wind observations into a model initial field or the accuracy of post-processing algorithms run on meteorological model output. The observed wind field at any particular location is treated as a function of the true (but unknown) wind and measurement error. The wind field from numerical weather prediction models is treated as a function of a linear and multiplicative bias and a term which represents random deviations with respect to the true wind process. A Bayesian approach is taken to provide information about the true underlying wind field, which is modeled as a stochastic process with a non-stationary and non-separable covariance. The method is applied to forecast wind fields from a widely used mesoscale numerical weather prediction (NWP) model (MM5). The statistical model tests are carried out for the wind speed over the Chesapeake Bay and the surrounding region for 21 July 2002. Coastal wind observations that have not been used in the MM5 initial conditions or forecasts are used in conjunction with the MM5 forecast wind field (valid at the same time that the observations were available) in a post-processing technique that combined these two sources of information to predict the true wind field. Based on the mean square error, this procedure provides a substantial correction to the MM5 wind field forecast over the Chesapeake Bay region. Copyright © 2005 John Wiley & Sons, Ltd. [source] A 10 year cloud climatology over Scandinavia derived from NOAA Advanced Very High Resolution Radiometer imageryINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2003Karl-Göran Karlsson Abstract Results from a satellite-based method to compile regional cloud climatologies covering the Scandinavian region are presented. Systematic processing of multispectral image data from the NOAA Advanced Very High Resolution Radiometer (AVHRR) instrument has been utilized to provide monthly cloud climatologies covering the period 1991,2000. Considerable local-scale variation of cloud amounts was found in the region. The inland Baltic Sea and adjacent land areas exhibited a large-amplitude annual cycle in cloudiness (high cloud amounts in winter, low cloud amounts in summer) whereas a weak-amplitude reversed annual cycle (high cloud amounts with a weak maximum in summer) was found for the Scandinavian mountain range. As a contrast, conditions over the Norwegian Sea showed high and almost unchanged cloud amounts during the course of the year. Some interesting exceptions to these patterns were also seen locally. The quality of the satellite-derived cloud climatology was examined through comparisons with climatologies derived from surface cloud observations, from the International Satellite Cloud Climatology Project (ISCCP) and from the European Centre for Medium-range Weather Forecasts ERA-40 data set. In general, cloud amount deviations from surface observations were smaller than 10% except for some individual winter months, when the separability between clouds and snow-covered cold land surfaces is often poor. The ISCCP data set showed a weaker annual cycle in cloudiness, generally caused by higher summer-time cloud amounts in the region. Very good agreement was found with the ERA-40 data set, especially for the summer season. However, ERA-40 showed higher cloud amounts than SCANDIA and ISCCP during the winter season. The derived cloud climatology is affected by errors due to temporal AVHRR sensor degradation, but they appear to be small for this particular study. The data set is proposed as a valuable data set for validation of cloud description in numerical weather prediction and regional climate simulation models. Copyright © 2003 Royal Meteorological Society [source] Assessing the spatial and temporal variation in the skill of precipitation forecasts from an NWP modelMETEOROLOGICAL APPLICATIONS, Issue 1 2008Nigel Roberts Abstract It is becoming increasingly important to be able to verify the spatial accuracy of precipitation forecasts, especially with the advent of high-resolution numerical weather prediction (NWP) models. In this article, the fractions skill score (FSS) approach has been used to perform a scale-selective evaluation of precipitation forecasts during 2003 from the Met Office mesoscale model (12 km grid length). The investigation shows how skill varies with spatial scale, the scales over which the data assimilation (DA) adds most skill, and how the loss of that skill is dependent on both the spatial scale and the rainfall coverage being examined. Although these results come from a specific model, they demonstrate how this verification approach can provide a quantitative assessment of the spatial behaviour of new finer-resolution models and DA techniques. Copyright © 2008 Royal Meteorological Society [source] Assimilation of radar reflectivity into the LM COSMO model with a high horizontal resolutionMETEOROLOGICAL APPLICATIONS, Issue 4 2006Z. Sokol Abstract An assimilation of radar reflectivity into a numerical weather prediction (NWP) model with a horizontal resolution of 2.8 km is presented and applied to three severe convective events. The suggested assimilation method takes into account differences between the model and radar-derived precipitation in modifying vertical profiles of water vapour mixing ratio in each model time step by the nudging approach. Version 3.9 of the LM COSMO (Local Model COSMO) ,NWP model used in this study includes the explicit formulation of the cloud and rain processes involved. Two variants of the assimilation technique are designed and outputs of their implementation are compared. The first variant makes use of the ground data only, while the second utilises vertical profiles of precipitation water. Both variants provide an improvement of precipitation forecast in comparison with outputs of the control run without assimilation procedures applied. When the assimilated radar data indicate initial precipitation near an expected storm, the NWP model is capable of forecasting basic features of the storm development two to three hours ahead. Three case studies are presented. In one, the assimilation method that takes into account the vertical structure of the precipitation water yields better results than the others which utilise ground data only. However, for the remaining two case studies both types of the assimilation method produce comparable results. Copyright © 2006 John Wiley & Sons, Ltd. [source] Numerical prediction of severe convection: comparison with operational forecastsMETEOROLOGICAL APPLICATIONS, Issue 1 2003Milton S. Speer The prediction of severe convection is a major forecasting problem in Australia during the summer months. In particular, severe convection in the Sydney basin frequently produces heavy rain or hail, flash flooding, and destructive winds. Convective activity is a forecasting challenge for the Sydney basin, mainly from October to April. Currently, there is a need for improved numerical model guidance to supplement the official probabilistic convective outlooks, issued by the operational forecasters. In this study we assess the performance of a very high resolution (2 km) numerical weather prediction (NWP) model in terms of how well it performed in providing guidance on heavy rainfall and hail, as well as other mesoscale features such as low level convergence lines. Two cases are described in which the operational forecasts were incorrect on both occasions. Non-severe thunderstorms were predicted on 1 December 2000 but severe convection occurred. Severe convection was predicted on 8 December 2000, but no convection was reported. In contrast, the numerical model performed well, accurately predicting severe convection on 1 December and no convection on 8 December. These results have encouraged a program aimed at providing an enhanced numerical modelling capability to the operational forecasters for the Sydney basin. Copyright © 2003 Royal Meteorological Society [source] Statistical interpretation of NWP products in IndiaMETEOROLOGICAL APPLICATIONS, Issue 1 2002Parvinder Maini Although numerical weather prediction (NWP) models provide an objective forecast, poor representation of local topography and other features in these models, necessitates statistical interpretation (SI) of NWP products in terms of local weather. The Perfect Prognostic Method (PPM) is one of the techniques for accomplishing this. At the National Center for Medium Range Weather Forecasting, PPM models for precipitation (quantitative, probability, yes/no) and maximum/minimum temperatures are developed for monsoon season by using analyses from the European Centre for Medium-Range Weather Forecasts. The SI forecast is then obtained by using these PPM models and output from the operational NWP model at the Center. Direct model output (DMO) obtained from the NWP model and the SI forecast are verified against the actual observations. The present study shows the verification scores obtained during the 1997 monsoon season for 10 locations in India. The results show that the SI forecast has good skill and is an improvement over DMO. Copyright © 2002 Royal Meteorological Society. [source] Modeling and Simulation of Notional Future Radar in Non-Standard Propagation Environments Facilitated by Mesoscale Numerical Weather Prediction ModelingNAVAL ENGINEERS JOURNAL, Issue 4 2008ROBERT E. MARSHALL Normal near surface radio-frequency (RF) propagation in the littorals across the land,sea boundary is rare due to the land,sea temperature difference, coastline shape, ground cover, urban density, coastal topography, and soil moisture content. The resulting frequent existence of coastal non-standard vertical profiles of refractivity and the resulting RF propagation has a profound impact on the performance of Navy ship-borne radars operating within 100 nm of the shore. In addition, these non-standard RF propagation conditions are spatio-temporally inhomogeneous. These spatial and time dependent propagation conditions and the resulting radar engineering implications cannot be revealed by a single vertical profile of refractivity taken near the ship borne radar. The results from single profile analysis techniques provide no spatiotemporal information and may lead to overly conservative radar design. Mesoscale numerical weather prediction (NWP) is a rapidly maturing technology with a strong operational Navy history that can provide a vertical profile of refractivity every 1 km in the battle space and every hour, up to 48 h, in the future. The Sensor Division at NSWCDD has applied mesoscale NWP for the last 2 years to better understand the performance of prototype radar in realistic four-dimensional (4D) coastal environments. Modern RF parabolic equation models are designed to model specific radar designs and to employ 3D refractivity fields from mesoscale NWP models. This allows for a radar design to be tested in realistic littoral non-standard atmospheres produced by stable internal boundary layers, sea breeze events, and the more rare sub-refractive events. Mesoscale NWP is currently qualitative for this purpose, but a research and development program focused on sea testing of prototype radars is described with the purpose of developing a more quantitative mesoscale NWP technology to support radar acquisition, testing, and operations. [source] Estimates of spatial and interchannel observation-error characteristics for current sounder radiances for numerical weather prediction.THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 649 2010I: Methods, application to ATOVS data Abstract This is the first part of a two-part article that uses three methods to estimate observation errors and their correlations for clear-sky sounder radiances used in the European Centre for Medium-Range Weather Forecasts (ECMWF) assimilation system. The analysis is based on covariances derived from pairs of first-guess and analysis departures. The methods used are the so-called Hollingsworth/Lönnberg method, a method based on subtracting a scaled version of mapped assumed background errors from first-guess departure covariances and the Desroziers diagnostic. The present article reports the results for the three Advanced TIROS Operational Vertical Sounder (ATOVS) instruments: the Advanced Microwave Sounding Unit (AMSU)-A, High-Resolution Infrared Radiation Sounder (HIRS) and Microwave Humidity Sounder (MHS). The findings suggest that all AMSU-A sounding channels show little or no interchannel or spatial observation-error correlations, except for surface-sensitive channels over land. Estimates for the observation error are mostly close to the instrument noise. In contrast, HIRS temperature-sounding channels exhibit some interchannel error correlations, and these are stronger for surface-sensitive channels. There are also indications for stronger spatial-error correlations for the HIRS short-wave channels. There is good agreement between the estimates from the three methods for temperature-sounding channels. Estimating observation errors for humidity-sounding channels of MHS and HIRS appears more difficult. A considerable proportion of the observation error for humidity-sounding channels appears correlated spatially for short separation distances, as well as between channels. Observation error estimates for humidity channels are generally considerably larger than the instrument noise. Observation error estimates from this study are consistently lower than those assumed in the ECMWF assimilation system. As error correlations are small for AMSU-A, the study suggests that the current use of AMSU-A data in the ECMWF system in terms of observation-error or thinning-scale choices is fairly conservative. Copyright © 2010 Royal Meteorological Society [source] Ensemble data assimilation with the CNMCA regional forecasting systemTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 646 2010Massimo Bonavita Abstract The Ensemble Kalman Filter (EnKF) is likely to become a viable alternative to variational methods for the next generation of meteorological and oceanographic data assimilation systems. In this work we present results from real-data assimilation experiments using the CNMCA regional numerical weather prediction (NWP) forecasting system and compare them to the currently operational variational-based analysis. The set of observations used is the same as the one ingested in the operational data stream, with the exception of satellite radiances and scatterometer winds. Results show that the EnKF-based assimilation cycle is capable of producing analyses and forecasts of consistently superior skill in the root mean square error metric than CNMCA operational 3D-Var. One of the most important issues in EnKF implementations lies in the filter tendency to become underdispersive for practical ensemble sizes. To combat this problem a number of different parametrizations of the model error unaccounted for in the assimilation cycle have been proposed. In the CNMCA system a combination of adaptive multiplicative and additive background covariance inflations has been found to give adequate results and to be capable of avoiding filter divergence in extended assimilation trials. The additive component of the covariance inflation has been implemented through the use of scaled forecast differences. Following suggestions that ensemble square-root filters can violate the gaussianity assumption when used with nonlinear prognostic models, the statistical distribution of the forecast and analysis ensembles has been studied. No sign of the ensemble collapsing onto one or a few model states has been found, and the forecast and analysis ensembles appear to stay remarkably close to the assumed probability distribution functions. Copyright © 2010 Royal Meteorological Society [source] 4D-Var assimilation of MERIS total column water-vapour retrievals over landTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 644 2009Peter Bauer Abstract Experiments with the active assimilation of total column water-vapour retrievals from Envisat MERIS observations have been performed at the European Centre for Medium-Range Weather Forecasts (ECMWF), focusing on the summer 2006 African Monsoon Multidisciplinary Analysis (AMMA) field campaign period. A mechanism for data quality control, observation error definition and variational bias correction has been developed so that the data can be safely treated within 4D-Var, like other observations that are currently assimilated in the operational system. While data density is limited due to the restriction to daylight and cloud-free conditions, a systematic impact on mean moisture analysis was found, with distinct regional and seasonal features. The impact can last 1--2 days into the forecast but has little effect on forecast accuracy in terms of both moisture and dynamics. This is mainly explained by the weak dynamic activity in the areas of largest data impact. Analysis and short-range forecast evaluation with radiosonde observations revealed a strong dependence on radiosonde type. Compared with Vaisala RS92 observations, the addition of MERIS total column water-vapour observations produced neutral to positive impact, while contradictory results were obtained when all radiosonde types were used in generating the statistics. This highlights the issue of radiosonde moisture biases and the importance of sonde humidity bias correction in numerical weather prediction (NWP). Copyright © 2009 Royal Meteorological Society [source] The characteristics of Hessian singular vectors using an advanced data assimilation schemeTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 642 2009A. R. Lawrence Abstract Initial condition uncertainty is a significant source of forecast error in numerical weather prediction. Singular vectors of the tangent linear propagator can identify directions in phase-space where initial errors are likely to make the largest contribution to forecast-error variance. The physical characteristics of these singular vectors depend on the choice of initial-time metric used to represent analysis-error covariances: the total-energy norm serves as a proxy to the analysis-error covariance matrix, whereas the Hessian of the cost function of a 4D-Var assimilation scheme represents a more sophisticated estimate of the analysis-error covariances, consistent with observation and background-error covariances used in the 4D-Var scheme. This study examines and compares the structure of singular vectors computed with the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System using these two types of initial metrics. Unlike earlier studies that use background errors derived from lagged forecast differences (the NMC method), the background-error covariance matrix in the Hessian metric is based on statistics from an ensemble of 4D-Vars using perturbed observations, which produces tighter correlations of background-error statistics than in previous formulations. In light of these new background-error statistics, this article re-examines the properties of Hessian singular vectors (and their relationship to total-energy singular vectors) using cases from different periods between 2003 and 2005. Energy profiles and wavenumber spectra reveal that the total-energy singular vectors are similar to Hessian singular vectors that use all observation types in the operational 4D-Var assimilation. This is in contrast to the structure of Hessian singular vectors without observations. Increasing the observation density tends to reduce the spatial scale of the Hessian singular vectors. Copyright © 2009 Royal Meteorological Society [source] The potential of variational retrieval of temperature and humidity profiles from Meteosat Second Generation observationsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 638 2009F. Di Giuseppe Abstract The quality of temperature and humidity retrievals from the infrared Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one-dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high-resolution regional-scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO in the ARPA-SIMC operational configuration is used to provide background fields. Only clear-sky observations over sea are processed. An optimized one-dimensional variational set-up comprised of two water-vapour and three window channels is selected. It maximizes the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1Dvar retrieval quality is first quantified in relative terms, employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed by comparing the analysis with independent radiosonde observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the use of the retrieved profiles generated by the 1Dvar in the COSMO nudging scheme can locally reduce forecast errors. Copyright © 2009 Royal Meteorological Society [source] A simple model of coupled synoptic waves in the land surface and atmosphere of the northern SahelTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 637 2008Douglas J. Parker Abstract A simple dynamic model is developed to describe the observed interactions between the atmosphere and the soil moisture patterns of the northern Sahel. In the model, the atmosphere follows quasi-geostrophic dynamics, while land-atmosphere coupling is described by simple linear relationships. Dry surfaces heat the atmospheric boundary layer, while wet surfaces cool the boundary layer, relative to the equilibrium state of the atmosphere and land surface. In turn, cloud processes, which are assumed to maximise in the cool, humid phase of an atmospheric disturbance, cool the land surface through wetting (rainfall) and reduction of the incoming solar flux. These assumptions lead to a linear system which can be solved numerically to obtain modal solutions, and the adjoints (optimal excitation) of these. Moist convective influences on the atmospheric state are not explored in detail. The coupling with the land surface leads to the existence of unstable modes, which do not exist in the atmosphere-only part of the system. Solutions can be easterly or westerly propagating, according to wave number, with the longer waves tending to be easterly. Propagation relies on a favourable configuration between the atmospheric and soil moisture anomalies: easterly propagation requires the surface temperature pattern to be shifted to the east of the atmospheric temperature pattern. In contrast, optimal excitation of the fastest-growing mode occurs when the atmospheric pattern has a thermal anomaly lying to the east of a strong surface temperature (and moisture) anomaly. These results have value for weather prediction, and indicate the usefulness of soil moisture data for forecasters. Copyright © 2008 Royal Meteorological Society [source] The optimal density of atmospheric sounder observations in the Met Office NWP systemTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 629 2007M. L. Dando Abstract Large numbers of satellite observations are discarded from the numerical weather prediction (NWP) process because high-density observations may have a negative impact on the analysis. In current assimilation schemes, the observation error covariance matrix R is usually represented as a diagonal matrix, which assumes there are no correlations in the observation errors and that each observation is an independent piece of information. This is not the case when there are strong error correlations and this can lead to a degraded analysis. The experiments conducted in this study were designed to identify the optimal density and to determine if there were circumstances when exceeding this density might be beneficial to forecast skill. The global optimal separation distance of Advanced TIROS Operational Vertical Sounder (ATOVS) observations was identified by comparing global forecast errors produced using different densities of ATOVS. The global average of the absolute forecast error produced by each different density was found for a 3-week period from December 2004 to January 2005. The results showed that, when using the Met Office NWP system with a horizontal model resolution of ,60 km, the lowest global forecast errors were produced when using separation distances of 115,154 km. However, localized regions of the atmosphere containing large gradients such as frontal regions may benefit from thinning distances as small as 40 km and therefore the global optimal separation distance is not necessarily applicable in these circumstances. Copyright © 2007 Royal Meteorological Society [source] Variable cirrus shading during CSIP IOP 5.THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 628 2007I: Effects on the initiation of convection Abstract Observations from the Convective Storm Initiation Project (CSIP) show that on 29 June 2005 (Intensive Observation Period 5) cirrus patches left over from previous thunderstorms reduced surface sensible and latent heat fluxes in the CSIP area. Large-eddy model (LEM) simulations, using moving positive surface-flux anomalies, show that we expect the observed moving gaps in the cirrus cover to significantly aid convective initiation. In these simulations, the timing of the CI is largely determined by the amount of heat added to the boundary layer, but weak convergence at the rear edge of the moving anomalies is also significant. Meteosat and rain-radar data are combined to determine the position of convective initiation for all 25 trackable showers in the CSIP area. The results are consistent with the LEM simulations, with showers initiating at the rear edge of gaps, at the leading edge of the anvil, or in clear skies, in all but one of the cases. The initiation occurs in relatively clear skies in all but two of the cases, with the exceptions probably linked to orographic effects. For numerical weather prediction, the case highlights the importance of predicting and assimilating cloud cover. The results show that in the absence of stronger forcings, weak forcings, such as from the observed cirrus shading, can determine the precise location and timing of convective initiation. In such cases, since the effects of shading by cirrus anvils from previous convective storms are relatively unpredictable, this is expected to limit the predictability of the convective initiation. Copyright © 2007 Royal Meteorological Society [source] Modelling suppressed and active convection.THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 626 2007Comparing a numerical weather prediction, cloud-resolving, single-column model Abstract This paper describes the design of and basic results from a case study to compare simulations of convection over the Tropical West Pacific. Simulations are carried out using a cloud-resolving model (CRM), a global numerical weather prediction (NWP) model and a single-column version of the NWP model (SCM). The experimental design for each model type is discussed and then results are compared. The periods simulated each include a regime with strong convective activity, a much more suppressed regime with far less convection, as well as the transition between these regimes. The description of the design and basic results from this study are given in some detail, as a study including all these model types is relatively new. Comparing the local forcing due to the dynamics in the NWP model with the observed forcing used to drive the CRM and SCM it is found that there is good agreement for one period chosen but significant differences for another. This is also seen in fields such as rain rate and top-of-atmosphere radiation. Using the period with good agreement we are able to identify examples of biases in the NWP model that are also reproduced in the SCM. Also discussed are examples of biases in the NWP simulation that are not reproduced in the SCM. It is suggested that understanding which biases in the SCM are consistent with the full NWP model can help focus the use of an SCM in this framework. © Crown Copyright 2007. Reproduced with the permission of the Controller of HMSO. Published by John Wiley & Sons, Ltd [source] Effects of data selection and error specification on the assimilation of AIRS data,THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 622 2007J. Joiner Abstract The Atmospheric InfraRed Sounder (AIRS), flying aboard NASA's Aqua satellite with the Advanced Microwave Sounding Unit-A (AMSU-A) and four other instruments, has been providing data for use in numerical weather prediction and data assimilation systems for over three years. The full AIRS data set is currently not transmitted in near-real-time to the prediction/assimilation centres. Instead, data sets with reduced spatial and spectral information are produced and made available within three hours of the observation time. In this paper, we evaluate the use of different channel selections and error specifications. We achieve significant positive impact from the Aqua AIRS/AMSU-A combination during our experimental time period of January 2003. The best results are obtained using a set of 156 channels that do not include any in the H2O band between 1080 and 2100 cm,1. The H2O band channels have a large influence on both temperature and humidity analyses. If observation and background errors are not properly specified, the partitioning of temperature and humidity information from these channels will not be correct, and this can lead to a degradation in forecast skill. Therefore, we suggest that it is important to focus on background error specification in order to maximize the impact from AIRS and similar instruments. In addition, we find that changing the specified channel errors has a significant effect on the amount of data that enters the analysis as a result of quality control thresholds that are related to the errors. However, moderate changes to the channel errors do not significantly impact forecast skill with the 156 channel set. We also examine the effects of different types of spatial data reduction on assimilated data sets and NWP forecast skill. Whether we pick the centre or the warmest AIRS pixel in a 3 × 3 array affects the amount of data ingested by the analysis but does not have a statistically significant impact on the forecast skill. Copyright © Published in 2007 by John Wiley & Sons, Ltd. [source] Fibonacci grids: A novel approach to global modellingTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 619 2006Richard Swinbank Abstract Recent years have seen a resurgence of interest in a variety of non-standard computational grids for global numerical prediction. The motivation has been to reduce problems associated with the converging meridians and the polar singularities of conventional regular latitude,longitude grids. A further impetus has come from the adoption of massively parallel computers, for which it is necessary to distribute work equitably across the processors; this is more practicable for some non-standard grids. Desirable attributes of a grid for high-order spatial finite differencing are: (i) geometrical regularity; (ii) a homogeneous and approximately isotropic spatial resolution; (iii) a low proportion of the grid points where the numerical procedures require special customization (such as near coordinate singularities or grid edges); (iv) ease of parallelization. One family of grid arrangements which, to our knowledge, has never before been applied to numerical weather prediction, but which appears to offer several technical advantages, are what we shall refer to as ,Fibonacci grids'. These grids possess virtually uniform and isotropic resolution, with an equal area for each grid point. There are only two compact singular regions on a sphere that require customized numerics. We demonstrate the practicality of this type of grid in shallow-water simulations, and discuss the prospects for efficiently using these frameworks in three-dimensional weather prediction or climate models. © Crown copyright, 2006. Royal Meteorological Society [source] Issues in targeted observingTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 613 2005(Invited paper for the Q. J. R. Meteorol. Abstract This paper summarizes successes and limitations of targeted observing field programmes starting from the Fronts and Atlantic Storm-Track Experiment in 1997 through recent programmes targeting winter storms and tropical cyclones. These field programmes have produced average reductions in short-range forecast errors of about 10 per cent over regional verification areas, and maximum forecast error reductions as large as 50 per cent in certain cases. The majority of targeting cases investigated so far involve sets of dropsondes and other observation data that provide partial coverage of target areas. The primary scientific challenges for targeting include the refinement of objective methods that can identify optimal times and locations for targeted observations, as well as identify the specific types of satellite and in situ measurements that are required for the improvement of numerical weather forecasts. The most advanced targeting procedures, at present, include: the ensemble transform Kalman Filter, Hessian singular vectors, and observation-space targeting using the adjoint of a variational data assimilation procedure. Targeted observing remains an active research topic in numerical weather prediction, with plans for continued refinement of objective targeting procedures, and field tests of new satellite and in situ observing systems. Copyright © 2005 Royal Meteorological Society [source] Adaptive thinning of atmospheric observations in data assimilation with vector quantization and filtering methodsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 613 2005T. Ochotta Abstract In data assimilation for numerical weather prediction, measurements of various observation systems are combined with background data to define initial states for the forecasts. Current and future observation systems, in particular satellite instruments, produce large numbers of measurements with high spatial and temporal density. Such datasets significantly increase the computational costs of the assimilation and, moreover, can violate the assumption of spatially independent observation errors. To ameliorate these problems, we propose two greedy thinning algorithms, which reduce the number of assimilated observations while retaining the essential information content of the data. In the first method, the number of points in the output set is increased iteratively. We use a clustering method with a distance metric that combines spatial distance with difference in observation values. In a second scheme, we iteratively estimate the redundancy of the current observation set and remove the most redundant data points. We evaluate the proposed methods with respect to a geometric error measure and compare them with a uniform sampling scheme. We obtain good representations of the original data with thinnings retaining only a small portion of observations. We also evaluate our thinnings of ATOVS satellite data using the assimilation system of the Deutscher Wetterdienst. Impact of the thinning on the analysed fields and on the subsequent forecasts is discussed. Copyright © 2005 Royal Meteorological Society [source] Validation of precipitable water from ECMWF model analyses with GPS and radiosonde data during the MAP SOPTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 612 2005Olivier Bock Abstract Precipitable water vapour contents (PWCs) from European Centre for Medium-Range Weather Forecasts (ECMWF) analyses have been compared with observations from 21 ground-based Global Positioning System receiving stations (GPS) and 14 radiosonde stations (RS), covering central Europe, for the period of the Mesoscale Alpine Programme experiment special observing period (MAP SOP). Two model analyses are considered: one using only conventional data, serving as a control assimilation experiment, and one including additionally most of the non-operational MAP data. Overall, a dry bias of about ,1 kg m,2 (,5.5% of total PWC), with a standard deviation of ,2.6 kg m,2 (13% of total PWC), is diagnosed in both model analyses with respect to GPS. The bias at individual sites is quite variable: from ,4 to ,0 kg m,2. The largest differences are observed at stations located in mountainous areas and/or near the sea, which reveal differences in representativeness. Differences between the two model analyses, and between these analyses and GPS, are investigated in terms of usage and quality of RS data. Biases in RS data are found from comparisons with both model and GPS PWCs. They are confirmed from analysis feedback statistics available at ECMWF. An overall dry bias in RS PWC of 4.5% is found, compared to GPS. The detection of RS biases from comparisons both with the model and GPS indicates that data screening during assimilation was generally effective. However, some RS bias went into the model analyses. Inspection of the time evolution of PWC from the model analyses and GPS occasionally showed differences of up to 5,10 kg m,2. These were associated with severe weather events, with variations in the amount of RS data being assimilated, and with time lags in the PWCs from the two model analyses. Such large differences contribute strongly to the overall observed standard deviations. Good confidence in GPS PWC estimates is gained through this work, even during periods of heavy rain. These results support the future assimilation of GPS data, both for operational weather prediction and for mesoscale simulation studies. Copyright © 2005 Royal Meteorological Society. [source] Use of the MODIS imager to help deal with AIRS cloudy radiancesTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 610 2005Mohamed Dahoui Abstract The assimilation of the Atmospheric InfraRed Sounder (AIRS) data is expected to improve the quality of NWP products. Currently, operational use of such data is limited to the cloud-free pixels or to the channels far above the clouds for cloudy pixels. This paper focuses on the validation of various cloud-detection schemes applied to AIRS data. The clouds are detected and characterized, in cloud-top and cover, by using the NESDIS, ECMWF, CO2 -slicing and MLEV schemes. These four different AIRS cloud descriptions are evaluated by independent information retrieved with the Météo-France cloud mask applied to MODIS data and taken as our reference. The validation for a ten-day period over the North-east Atlantic is presented. The use of satellite cloudy radiances is a great challenge for numerical weather prediction. Work is in progress to assimilate such data by using enhanced observation operators dealing with clouds. In this work, we try to contribute to this effort by investigating the linearity assumption of an observation operator, with a simple diagnostic cloud scheme, for different cloud types. Copyright © 2005 Royal Meteorological Society [source] The global response to tropical heating in the Madden,Julian oscillation during the northern winterTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 601 2004Adrian J. Matthews Abstract A life cycle of the Madden,Julian oscillation (MJO) was constructed, based on 21 years of outgoing long-wave radiation data. Regression maps of NCEP,NCAR reanalysis data for the northern winter show statistically significant upper-tropospheric equatorial wave patterns linked to the tropical convection anomalies, and extratropical wave patterns over the North Pacific, North America, the Atlantic, the Southern Ocean and South America. To assess the cause of the circulation anomalies, a global primitive-equation model was initialized with the observed three-dimensional (3D) winter climatological mean flow and forced with a time-dependent heat source derived from the observed MJO anomalies. A model MJO cycle was constructed from the global response to the heating, and both the tropical and extratropical circulation anomalies generally matched the observations well. The equatorial wave patterns are established in a few days, while it takes approximately two weeks for the extratropical patterns to appear. The model response is robust and insensitive to realistic changes in damping and basic state. The model tropical anomalies are consistent with a forced equatorial Rossby,Kelvin wave response to the tropical MJO heating, although it is shifted westward by approximately 20° longitude relative to observations. This may be due to a lack of damping processes (cumulus friction) in the regions of convective heating. Once this shift is accounted for, the extratropical response is consistent with theories of Rossby wave forcing and dispersion on the climatological flow, and the pattern correlation between the observed and modelled extratropical flow is up to 0.85. The observed tropical and extratropical wave patterns account for a significant fraction of the intraseasonal circulation variance, and this reproducibility as a response to tropical MJO convection has implications for global medium-range weather prediction. Copyright © 2004 Royal Meteorological Society [source] High-resolution limited-area ensemble predictions based on low-resolution targeted singular vectorsTHE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 582 2002Inger-Lise Frogner Abstract The operational limited-area model, HIRLAM, at the Norwegian Meteorological Institute is used at 0.25° latitude/longitude resolution for ensemble weather prediction over Northern Europe and adjacent parts of the North Atlantic Ocean; this system is called LAMEPS. Initial and lateral boundary perturbations are taken from coarse-resolution European Centre for Medium-Range Weather Forecasts global ensemble members based on targeted singular vectors (TEPS). Five winter and five summer cases in 1997 consisting of 20 ensemble members plus one control forecast are integrated. Two sets of ensembles are generated, one for which both initial and lateral boundary conditions are perturbed, and another with only the initial fields perturbed. The LAMEPS results are compared to those of TEPS using the following measures: r.m.s. ensemble spread of 500 hPa geopotential height; r.m.s. ensemble spread of mean-sea-level pressure; Brier Skill Scores (BSS); Relative Operating Characteristic (ROC) curves; and cost/loss analyses. For forecasts longer than 12 hours, all measures show that perturbing the boundary fields is crucial for the performance of LAMEPS. For the winter cases TEPS has slightly larger ensemble spread than LAMEPS, but this is reversed for the summer cases. Results from BSS, ROC and cost/loss analyses show that LAMEPS performed considerably better than TEPS for precipitation, a result that is promising for forecasting extreme precipitation amounts. We believe this result to be linked to the high predictability of mesoscale flows controlled by complex topography. For two-metre temperature, however, TEPS frequently performed better than LAMEPS. Copyright © 2002 Royal Meteorological Society [source] | |||||||||||||