scholarly journals The Use of an Ensemble Approach to Study the Background Error Covariances in a Global NWP Model

2006 ◽  
Vol 134 (9) ◽  
pp. 2466-2489 ◽  
Author(s):  
Margarida Belo Pereira ◽  
Loïk Berre
Keyword(s):  
Positive Impact ◽  
Ensemble Method ◽  
Atmospheric Variability ◽  
Error Statistics ◽  
Background Error ◽  
Perfect Model ◽  
Data Density ◽  
The Ensemble Method ◽  
Nwp Model ◽  
Spatially Varying

Abstract The estimation of the background error statistics is a key issue for data assimilation. Their time average is estimated here using an analysis ensemble method. The experiments are performed with the nonstretched version of the Action de Recherche Petite Echelle Grande Echelle global model, in a perfect-model context. The global (spatially averaged) correlation functions are sharper in the ensemble method than in the so-called National Meteorological Center (NMC) method. This is shown to be closely related to the differences in the analysis step representation. The local (spatially varying) variances appear to reflect some effects of the data density and of the atmospheric variability. The resulting geographical contrasts are found to be partly different from those that are visible in the operational variances and in the NMC method. An economical estimate is also introduced to calculate and compare the local correlation length scales. This allows for the diagnosis of some existing heterogeneities and anisotropies. This information can also be useful for the modeling of heterogeneous covariances based, for example, on wavelets. The implementation of the global covariances and of the local variances, which are provided by the ensemble method, appears moreover to have a positive impact on the forecast quality.

scholarly journals Assimilation of Infrared Radiance Observations with Sensitivity to Land Surfaces in the Canadian Ensemble–Variational System

2016 ◽  
Vol 55 (3) ◽  
pp. 561-578 ◽  
Author(s):  
S. K. Dutta ◽  
L. Garand ◽  
S. Heilliette
Keyword(s):  
Positive Impact ◽  
Surface Emissivity ◽  
Error Statistics ◽  
Variational System ◽  
Background Error ◽  
Infrared Radiance ◽  
Forecast Lead Time ◽  
Surface Skin Temperature ◽  
Land Surfaces ◽  
The Impact

AbstractThis study highlights recent progress at the Canadian Meteorological Centre in the assimilation of Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) radiance observations that are sensitive to land surfaces. The assimilation is carried out using the Canadian global ensemble–variational system. That system benefits from flow-dependent background-error statistics that include covariances between surface skin temperature and atmospheric variables. Up to 142 channels from both AIRS and IASI are assimilated. A detailed database of spectral surface emissivity is used. Forecasts are evaluated against ERA-Interim analyses, own-cycle analyses, and radiosonde observations. A conservative approach is taken, with restrictive conditions on topography and surface emissivity. From 2-month assimilation experiments, a significant positive impact is obtained in the Northern Hemisphere extratropics beyond day 2 from the surface to the upper troposphere. The impact is mixed in other regions, depending on level or forecast lead time. Causes for these mixed results are examined in view of future experiments and eventual operational implementation.

scholarly journals Effect of Adding Hydrometeor Mixing Ratios Control Variables on Assimilating Radar Observations for the Analysis and Forecast of a Typhoon

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 415 ◽  
Author(s):  
Dongmei Xu ◽  
Feifei Shen ◽  
Jinzhong Min
Keyword(s):  
Cost Function ◽  
Positive Impact ◽  
Precipitation Forecast ◽  
Track Forecast ◽  
Error Statistics ◽  
Control Variables ◽  
Background Error ◽  
Mixing Ratios ◽  
The Cost ◽  
Assimilation Scheme

The variational data assimilation (DA) method seeks the optimal analyses by minimizing a cost function with respect to control variables (CVs). CVs are extended in this study to include hydrometeor mixing ratios related variables besides the widely used sets of CVs (momentum fields, surface pressure, temperature, and pseudo-relative humidity). The impacts of the extra CVs are investigated in terms of hydrometeor mixing ratios to the assimilation of radar radial velocity (Vr) and reflectivity (RF) for the analysis and prediction of Typhoon Chanthu (2010). It is found that the background error statistics of the extended CVs from the National Meteorological Center (NMC) method is reliable. The track forecast is improved significantly by including hydrometeor mixing ratios as CVs to assimilate radar Vr and RF. The DA experiments using the hydrometer CVs show much improved intensity analysis and forecast. It also improves the precipitation forecast skills to some extent. The positive impact is significant using a direct RF assimilation scheme, when Vr and RF data are applied together. It suggests that when we applying an indirect RF assimilation scheme, the fitting of more hydrometers in the cost function will tend to cause a slight degradation for other variables such as the wind and temperature.

Estimating Heterogeneous Treatment Effects and the Effects of Heterogeneous Treatments with Ensemble Methods

2017 ◽  
Vol 25 (4) ◽  
pp. 413-434 ◽  
Author(s):  
Justin Grimmer ◽  
Solomon Messing ◽  
Sean J. Westwood
Keyword(s):  
Treatment Effects ◽  
Ensemble Methods ◽  
Ensemble Method ◽  
Superior Performance ◽  
Accurate Estimation ◽  
Randomized Experiments ◽  
Heterogeneous Treatment Effects ◽  
Data Set ◽  
Heterogeneous Effects ◽  
The Ensemble Method

Randomized experiments are increasingly used to study political phenomena because they can credibly estimate the average effect of a treatment on a population of interest. But political scientists are often interested in how effects vary across subpopulations—heterogeneous treatment effects—and how differences in the content of the treatment affects responses—the response to heterogeneous treatments. Several new methods have been introduced to estimate heterogeneous effects, but it is difficult to know if a method will perform well for a particular data set. Rather than using only one method, we show how an ensemble of methods—weighted averages of estimates from individual models increasingly used in machine learning—accurately measure heterogeneous effects. Building on a large literature on ensemble methods, we show how the weighting of methods can contribute to accurate estimation of heterogeneous treatment effects and demonstrate how pooling models lead to superior performance to individual methods across diverse problems. We apply the ensemble method to two experiments, illuminating how the ensemble method for heterogeneous treatment effects facilitates exploratory analysis of treatment effects.

scholarly journals Interpretation of Adaptive Observing Guidance for Atlantic Tropical Cyclones

2007 ◽  
Vol 135 (12) ◽  
pp. 4006-4029 ◽  
Author(s):  
C. A. Reynolds ◽  
M. S. Peng ◽  
S. J. Majumdar ◽  
S. D. Aberson ◽  
C. H. Bishop ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Total Energy ◽  
Tropical Cyclones ◽  
Error Variance ◽  
Naval Research ◽  
Error Statistics ◽  
Background Error ◽  
Analysis Error ◽  
The Impact ◽  
Perturbation Growth

Abstract Adaptive observing guidance products for Atlantic tropical cyclones are compared using composite techniques that allow one to quantitatively examine differences in the spatial structures of the guidance maps and relate these differences to the constraints and approximations of the respective techniques. The guidance maps are produced using the ensemble transform Kalman filter (ETKF) based on ensembles from the National Centers for Environmental Prediction and the European Centre for Medium-Range Weather Forecasts (ECMWF), and total-energy singular vectors (TESVs) produced by ECMWF and the Naval Research Laboratory. Systematic structural differences in the guidance products are linked to the fact that TESVs consider the dynamics of perturbation growth only, while the ETKF combines information on perturbation evolution with error statistics from an ensemble-based data assimilation scheme. The impact of constraining the SVs using different estimates of analysis error variance instead of a total-energy norm, in effect bringing the two methods closer together, is also assessed. When the targets are close to the storm, the TESV products are a maximum in an annulus around the storm, whereas the ETKF products are a maximum at the storm location itself. When the targets are remote from the storm, the TESVs almost always indicate targets northwest of the storm, whereas the ETKF targets are more scattered relative to the storm location and often occur over the northern North Atlantic. The ETKF guidance often coincides with locations in which the ensemble-based analysis error variance is large. As the TESV method is not designed to consider spatial differences in the likely analysis errors, it will produce targets over well-observed regions, such as the continental United States. Constraining the SV calculation using analysis error variance values from an operational 3D variational data assimilation system (with stationary, quasi-isotropic background error statistics) results in a modest modulation of the target areas away from the well-observed regions, and a modest reduction of perturbation growth. Constraining the SVs using the ETKF estimate of analysis error variance produces SV targets similar to ETKF targets and results in a significant reduction in perturbation growth, due to the highly localized nature of the analysis error variance estimates. These results illustrate the strong sensitivity of SVs to the norm (and to the analysis error variance estimate used to define it) and confirm that discrepancies between target areas computed using different methods reflect the mathematical and physical differences between the methods themselves.

Background error statistics for aerosols

10.1002/qj.37 ◽  
2007 ◽  
Vol 133 (623) ◽  
pp. 391-405 ◽  
Author(s):  
Angela Benedetti ◽  
Michael Fisher
Keyword(s):  
Error Statistics ◽  
Background Error

scholarly journals Impact of Ground-based GPS PW and MM5-3DVar Background Error Statistics on Forecast of a Convective Case

SOLA ◽  
2005 ◽  
Vol 1 ◽  
pp. 73-76 ◽  
Author(s):  
Y.-R. Guo ◽  
H. Kusaka ◽  
D. M. Barker ◽  
Y.-H. Kuo ◽  
A. Crook
Keyword(s):  
Error Statistics ◽  
Background Error

scholarly journals Simulation of Monsoon Depressions Using WRF-VAR: Impact of Different Background Error Statistics and Lateral Boundary Conditions

2014 ◽  
Vol 142 (10) ◽  
pp. 3586-3613 ◽  
Author(s):  
A. Routray ◽  
S. C. Kar ◽  
P. Mali ◽  
K. Sowjanya
Keyword(s):  
Data Assimilation ◽  
Boundary Conditions ◽  
Initial Conditions ◽  
Variational Data Assimilation ◽  
Error Statistics ◽  
Background Error ◽  
Single Observation ◽  
Monsoon Depressions ◽  
Data Assimilation System ◽  
Assimilation System

Abstract In a variational data assimilation system, background error statistics (BES) spread the influence of the observations in space and filter analysis increments through dynamic balance or statistical relationships. In a data-sparse region such as the Bay of Bengal, BES play an important role in defining the location and structure of monsoon depressions (MDs). In this study, the Indian-region-specific BES have been computed for the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation system. A comparative study using single observation tests is carried out using the computed BES and global BES within the WRF system. Both sets of BES are used in the assimilation cycles and forecast runs for simulating the meteorological features associated with the MDs. Numerical experiments have been conducted to assess the relative impact of various BES in the analysis and simulations of the MDs. The results show that use of regional BES in the assimilation cycle has a positive impact on the prediction of the location, propagation, and development of rainbands associated with the MDs. The track errors of MDs are smaller when domain-specific BES are used in the assimilation cycle. Additional experiments have been conducted using data from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) as initial and boundary conditions (IBCs) in the assimilation cycle. The results indicate that the use of domain-dependent BES and high-resolution ERA-I data as IBCs further improved the initial conditions for the model leading to better forecasts of the MDs.

scholarly journals Application of Boyd’s Periodization and Relaxation Method in a Spectral Atmospheric Limited-Area Model. Part II: Accuracy Analysis and Detailed Study of the Operational Impact

2012 ◽  
Vol 140 (10) ◽  
pp. 3149-3162 ◽  
Author(s):  
Daan Degrauwe ◽  
Steven Caluwaerts ◽  
Fabrice Voitus ◽  
Rafiq Hamdi ◽  
Piet Termonia
Keyword(s):  
Weather Prediction ◽  
Relaxation Method ◽  
Companion Paper ◽  
Water Model ◽  
Limited Area ◽  
Perfect Model ◽  
Depth Study ◽  
Nwp Model ◽  
The Impact ◽  
Operational Impact

Abstract Spectral limited-area models face a particular challenge at their lateral boundaries: the fields need to be made periodic. Boyd proposed a windowing-based method to improve the periodization and relaxation. In a companion paper, the implementation of this windowing method in the operational semi-implicit semi-Lagrangian spectral HARMONIE system was described and some first reproducibility tests, comparing this method to the old existing one, were presented. The present paper provides an in-depth study of the impact of this method for different configurations of the implementation. This is carried out in three steps in well-controlled experimental setups of increasing complexity. First, different aspects of Boyd’s method are analyzed in an idealized perfect-model test using a representative 1D shallow-water model. Second, the implementation is tested in an adiabatic 3D numerical weather prediction (NWP) model with perfect-model experiments. Finally, the impact of using Boyd’s method in a more operational-like NWP context is investigated as well. The presented tests show that, while the implementation of Boyd’s method is neutral in terms of scores, it is superior to the existing spline method in the case of strong dynamical forcings at the lateral boundaries.

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