The Role of Analysis Error in the Convergence of Reanalysis Production Streams in MERRA-2

2021 ◽  
Vol 149 (4) ◽  
pp. 1041-1054
Author(s):  
Amal El Akkraoui ◽  
David Carvalho ◽  
Ronald M. Errico ◽  
Nikki C. Privé ◽  
Michael G. Bosilovich
Keyword(s):  
Data Assimilation ◽  
Error Statistics ◽  
Time Period ◽  
Comparison Results ◽  
Parallel Streams ◽  
Assimilation Process ◽  
Analysis Error ◽  
The Impact ◽  
Historical Periods

ABSTRACTDue to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.

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.

scholarly journals What Kind Of Capitalism For Azerbaijan? A Comparative Analysis From Economic View

2011 ◽  
Vol 10 (6) ◽  
pp. 57
Author(s):  
Ayhan Guney ◽  
Ilkin M. Sabiroglu ◽  
Cihan Bulut
Keyword(s):  
Market Economy ◽  
Capital Accumulation ◽  
Agricultural Sector ◽  
Free Market ◽  
Open Market ◽  
Before And After ◽  
Major Factors ◽  
The Impact ◽  
Historical Periods

Every country has experienced various capital accumulation processes due to their own specific conditions. Differences in these conditions have ensured various countries to enter the process of economic development in dissimilar historical periods. Due to the central characteristics of the previous command economic system and the impact of powerful heritage from the USSR on the bureaucratic administration, Azerbaijan is still having difficulties in transitioning to a free-market economy. Today, the transition to an open market economy for Azerbaijan is not completely realized. This research attempts to investigate the major factors of the formation process of the capitalist economic structure in Azerbaijan before and after the demise of the Soviet Union.It focused on the fundamental role of oil and relatively, the agricultural sector and also looked into the types of capitalism the country is currently experiencing based upon certain criteria and statistical indicators.

scholarly journals Improvements in Forecasting Intense Rainfall: Results from the FRANC (Forecasting Rainfall Exploiting New Data Assimilation Techniques and Novel Observations of Convection) Project

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 125 ◽  
Author(s):  
Sarah Dance ◽  
Susan Ballard ◽  
Ross Bannister ◽  
Peter Clark ◽  
Hannah Cloke ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Doppler Radar ◽  
Weather Prediction ◽  
Observation Error ◽  
Error Statistics ◽  
Convective Rainfall ◽  
Background Error ◽  
Spatially Correlated ◽  
Operational Forecasts ◽  
The Impact

The FRANC project (Forecasting Rainfall exploiting new data Assimilation techniques and Novel observations of Convection) has researched improvements in numerical weather prediction of convective rainfall via the reduction of initial condition uncertainty. This article provides an overview of the project’s achievements. We highlight new radar techniques: correcting for attenuation of the radar return; correction for beams that are over 90% blocked by trees or towers close to the radar; and direct assimilation of radar reflectivity and refractivity. We discuss the treatment of uncertainty in data assimilation: new methods for estimation of observation uncertainties with novel applications to Doppler radar winds, Atmospheric Motion Vectors, and satellite radiances; a new algorithm for implementation of spatially-correlated observation error statistics in operational data assimilation; and innovative treatment of moist processes in the background error covariance model. We present results indicating a link between the spatial predictability of convection and convective regimes, with potential to allow improved forecast interpretation. The research was carried out as a partnership between University researchers and the Met Office (UK). We discuss the benefits of this approach and the impact of our research, which has helped to improve operational forecasts for convective rainfall events.

scholarly journals Impact of variational assimilation using multivariate background error covariances on the simulation of monsoon depressions over India

2016 ◽  
Vol 34 (2) ◽  
pp. 187-201 ◽  
Author(s):  
M. Dhanya ◽  
A. Chandrasekar
Keyword(s):  
Data Assimilation ◽  
Rainfall Simulation ◽  
Initial Time ◽  
Temperature Structure ◽  
Error Statistics ◽  
Background Error ◽  
Skill Scores ◽  
Correlation Information ◽  
Monsoon Depressions ◽  
The Impact

Abstract. The background error covariance structure influences a variational data assimilation system immensely. The simulation of a weather phenomenon like monsoon depression can hence be influenced by the background correlation information used in the analysis formulation. The Weather Research and Forecasting Model Data assimilation (WRFDA) system includes an option for formulating multivariate background correlations for its three-dimensional variational (3DVar) system (cv6 option). The impact of using such a formulation in the simulation of three monsoon depressions over India is investigated in this study. Analysis and forecast fields generated using this option are compared with those obtained using the default formulation for regional background error correlations (cv5) in WRFDA and with a base run without any assimilation. The model rainfall forecasts are compared with rainfall observations from the Tropical Rainfall Measurement Mission (TRMM) and the other model forecast fields are compared with a high-resolution analysis as well as with European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis. The results of the study indicate that inclusion of additional correlation information in background error statistics has a moderate impact on the vertical profiles of relative humidity, moisture convergence, horizontal divergence and the temperature structure at the depression centre at the analysis time of the cv5/cv6 sensitivity experiments. Moderate improvements are seen in two of the three depressions investigated in this study. An improved thermodynamic and moisture structure at the initial time is expected to provide for improved rainfall simulation. The results of the study indicate that the skill scores of accumulated rainfall are somewhat better for the cv6 option as compared to the cv5 option for at least two of the three depression cases studied, especially at the higher threshold levels. Considering the importance of utilising improved flow-dependent correlation structures for efficient data assimilation, the need for more studies on the impact of background error covariances is obvious.

scholarly journals Assessing the Impact of Corporate Governance on Non-Performing Loans: Empirical Analysis of the Listed Commercial Banks of Pakistan

2019 ◽  
Vol IV (III) ◽  
pp. 188-196
Author(s):  
Ihtesham Khan ◽  
Muhammad Ilyas ◽  
Shehzad Khan
Keyword(s):  
Corporate Governance ◽  
Banking Industry ◽  
Annual Reports ◽  
Governance System ◽  
Nonperforming Loans ◽  
Time Period ◽  
Corporate Governance System ◽  
The Impact ◽  
Code Compliance

Financial crisis shows the ambiguous role of the corporate governance system. Hence, the main purpose of this paper is to assess the impact of corporate governance on Non-performing loans of the banking industry of Pakistan. The time period selected from 2006 to 2016 and source of data is annual reports of respective banks and the World Bank. In order to explain the relationship between the governance system and non-performing loans used descriptive, correlational and panel data analyses. The results revealed a negative and significant effect of corporate governance on nonperforming loans of sample firms of the study. Therefore, suggested for the banking industry of Pakistan to implement and make sure their reports according to corporate governance code compliance to control non-performing loans.

scholarly journals An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture–data assimilation

2017 ◽  
Vol 44 ◽  
pp. 89-100 ◽  
Author(s):  
Luca Cenci ◽  
Luca Pulvirenti ◽  
Giorgio Boni ◽  
Marco Chini ◽  
Patrick Matgen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Hydrological Model ◽  
High Spatial Resolution ◽  
Flash Flood ◽  
Soil Moisture Data ◽  
Time Period ◽  
The Impact

Abstract. The assimilation of satellite-derived soil moisture estimates (soil moisture–data assimilation, SM–DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM–DA in recent years (e.g. the Advanced SCATterometer – ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM–DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014–February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM–DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM–DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further research activities, we believe this research is timely in order to enhance our understanding of the potential contribution of the S1 data within the SM–DA framework for flash flood risk mitigation.

Meal fatty acids and postprandial vascular reactivity

2007 ◽  
Vol 35 (3) ◽  
pp. 451-453 ◽  
Author(s):  
K.G. Jackson ◽  
C.K. Armah ◽  
A.M. Minihane
Keyword(s):  
Fatty Acids ◽  
Vascular Reactivity ◽  
Vascular Dysfunction ◽  
Postprandial Lipaemia ◽  
Fasted State ◽  
Important Target ◽  
Time Period ◽  
The Impact ◽  
Progression Of Atherosclerosis

With increasing recognition of the pivotal role of vascular dysfunction in the progression of atherosclerosis, the vasculature has emerged as an important target for dietary therapies. Recent studies have indicated that chronic fatty acid manipulation alters vascular reactivity, when measured after an overnight fast. However, individuals spend a large proportion of the day in the postprandial (non-fasted) state. Several studies have shown that high fat meals can impair endothelial function within 3–4 h, a time period often associated with peak postprandial lipaemia. Although the impact of meal fatty acids on the magnitude and duration of the postprandial lipaemic response has been extensively studied, very little is known about their impact on vascular reactivity after a meal.

scholarly journals Assimilation with an Ensemble Kalman Filter of Synthetic Radial Wind Data in Anisotropic Turbulence: Perfect Model Experiments

2006 ◽  
Vol 134 (2) ◽  
pp. 618-637 ◽  
Author(s):  
Martin Charron ◽  
P. L. Houtekamer ◽  
Peter Bartello
Keyword(s):  
Kalman Filter ◽  
Vertical Velocity ◽  
Ensemble Kalman Filter ◽  
Grid Point ◽  
Synthetic Data ◽  
Wind Data ◽  
Error Statistics ◽  
Boussinesq Model ◽  
Analysis Error ◽  
The Impact

Abstract The ensemble Kalman filter (EnKF) developed at the Meteorological Research Branch of Canada is used in the context of synthetic radial wind data assimilation at the mesoscale. A dry Boussinesq model with periodic boundary conditions is employed to provide a control run, as well as two ensembles of first guesses. Synthetic data, which are interpolated from the control run, are assimilated and simulate Doppler radar wind measurements. Nine “radars” with a range of 120 km are placed evenly on the horizontal 1000 km × 1000 km domain. These radars measure the radial wind with assumed Gaussian error statistics at each grid point within their range provided that there is sufficient upward motion (a proxy for precipitation). These data of radial winds are assimilated every 30 min and the assimilation period extends over 4 days. Results show that the EnKF technique with 2 × 50 members performed well in terms of reducing the analysis error for horizontal winds and temperature (even though temperature is not an observed variable) over a period of 4 days. However the analyzed vertical velocity shows an initial degradation. During the first 2 days of the assimilation period, the analysis error of the vertical velocity is greater when assimilating radar observations than when scoring forecasts initialized at t = 0 without assimilating any data. The type of assimilated data as well as the localization of the impact of the observations is thought to be the cause of this degradation of the analyzed vertical velocity. External gravity modes are present in the increments when localization is performed. This degradation can be eliminated by filtering the external gravity modes of the analysis increments. A similar set of experiments is realized in which the model dissipation coefficient is reduced by a factor of 10. This shows the level of sensitivity of the results to the kinetic energy power spectrum, and that the quality of the analyzed vertical wind is worse when dissipation is small.

Data Assimilation Using WRFDA Over the Terminal Area of Rio de Janeiro

2021 ◽  
Vol 36 (1) ◽  
pp. 87-96
Author(s):  
Vinícius Albuquerque de Almeida ◽  
Gutemberg Borges França ◽  
Haroldo Fraga de Campos Velho ◽  
Nelson Francisco Favilla Ebecken
Keyword(s):  
Relative Humidity ◽  
Data Assimilation ◽  
Rio De Janeiro ◽  
Wrf Model ◽  
Observation Data ◽  
Local Conditions ◽  
Forecast Data ◽  
Assimilation Process ◽  
The Impact ◽  
Terminal Area

Abstract The impact of the data assimilation process of air temperature and relative humidity from surface meteorological stations and sounding at airports in the terminal area of Rio de Janeiro is evaluated using the Weather Research and Forecast Data Assimilation system. Synthetic data of temperature, relative humidity and wind are generated in the locations of airport sensors by applying a white-noise perturbation in the forecast data. Results show a positive overall impact of the assimilation process with the removal of part of the noise in the observation data but keeping the effect of local conditions in the later timesteps of the simulation. In addition, with the assimilation process there is a global reduction of the error between the analysis data and the observation data. In the future, a neural network will be trained to emulate the data assimilation process to speed-up the assimilation process in the WRF model.

Reassessing the Impact of Risk Management Capabilities on Firm Value: A Stakeholders Perspective

2020 ◽  
Vol 6 (2) ◽  
pp. 81
Author(s):  
Asad Khan ◽  
Muhammad Ibrahim Khan ◽  
Niaz Ahmed Bhutto
Keyword(s):  
Risk Management ◽  
Value Creation ◽  
Firm Value ◽  
Positive Impact ◽  
Financial Firms ◽  
Management Capability ◽  
Time Period ◽  
Management Capabilities ◽  
The Impact

Despite the pivotal role of risk management very limited research is carry out on the issue of firm’s risk management capability and value creation. This study aims to analyze the impact of firms risk management capabilities on firm performance and cost. Using panel data technique a sample of 301 non financial firms was analyzed for the time period on five years starting from 2011 to 2015. We assert that effective risk capabilities have positive impact on all stakeholders. The effective risk management capabilities guarantee more resilience to exogenous and endogenous risks. Our findings will have a significant impact on existing literature, by extending the existing knowledge of firm’s risk management capabilities into the domain of diverse stakeholders and resources adjustment.

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