scholarly journals Diagnostic Analysis of Various Observation Impacts in the 3DVAR Assimilation System of Global GRAPES

2018 ◽  
Vol 146 (10) ◽  
pp. 3125-3142 ◽  
Author(s):  
Lihong Zhang ◽  
Jiandong Gong ◽  
Ruichun Wang
Keyword(s):  
Northern Hemisphere ◽  
Weather Prediction ◽  
Motion Vector ◽  
Diagnostic Technique ◽  
Diagnostic Techniques ◽  
Equatorial Region ◽  
Radiosonde Data ◽  
Prediction System ◽  
Research Attention ◽  
Proper Mass

Abstract Observation impact studies have received increasing amounts of research attention. The impacts of observations on numerical weather prediction (NWP) are highly dependent on assimilation algorithm, prediction system, and observation source. Therefore, the major NWP centers worldwide have each developed their own diagnostic techniques to assess observation impacts. However, similar diagnostic techniques have not yet been developed in China. In this study, a diagnostic technique was exploited with the randomized perturbation method in the Global/Regional Assimilation and Prediction System (GRAPES) 3DVAR system, and then applied to evaluate observation impacts for various regions of the world. It was found that a reasonable and stable estimation could be obtained when the number of perturbations was greater than 15. Because of differences in observations in the Northern and Southern Hemispheres, refractivity data from GNSS radio occultation (GNSS-RO), satellite radiance, and atmospheric motion vector data had more impact in the Southern Hemisphere than in the Northern Hemisphere. However, radiosonde data, aircraft, and surface data were more important in the Northern Hemisphere. Low-impact observation points were located in data-rich areas, whereas high-impact observation points were located in data-poor areas. In the equatorial region, the contributions of observations to the analysis were smaller than those in the nonequatorial regions because of the lack of proper mass–wind balance relationship. Radiosondes contributed the largest impact in China and its surrounding regions, with contributions of radiosondes and GNSS-RO data exceeding 60% of the total contributions, except for wind speed below 700 hPa.

Inter-comparison of wind vectors derived from geostationary satellites with the Aeolus/ALADIN

2021 ◽  
Author(s):  
Hyemin Shin ◽  
Myoung-Hwan Ahn ◽  
Jisoo Kim ◽  
Jae-Gwan Kim ◽  
Joon-Tae Choi
Keyword(s):  
Quality Control ◽  
Lower Layer ◽  
Weather Prediction ◽  
Motion Vector ◽  
Radiosonde Data ◽  
Data Quality Control ◽  
Geostationary Satellites ◽  
Time Space ◽  
Comparison Results ◽  
Hemisphere Winter

<p>Wind information obtained from various means ​​play an important role in data assimilation of numerical weather prediction. Atmospheric Motion Vector (AMV) obtained from the geostationary satellites provide a high spatio-temporal resolution wind information over the whole glove. An accurate quality control is one of the key factor that needs for a better utilization of AMV. Here, we use Aeolus/Atmospheric Laser Doppler Instrument (ALADIN) data to analyze the error characteristics of AMV derived from a newly commissioned geostationary satellite, Geostationary Korea Multi Purpose Satellite-2A (GK2A), stationed over 128.2<sup>o </sup>E. As majority of the GK2A AMV data are obtained over the ocean where the radiosonde data (used for the reference wind measurement for the error analysis of AMV) is sparse, the ALADIN data could play an important contribution. Data obtained from December 2019 to February 2020 (northern hemisphere winter) are collocated with time, space, and altitude criteria of ±15 min, 0.9<sup> o</sup>, and 50hPa. For the quality control data, only AMV data with a Quality Index (QI) of 0.85 or higher are used. In case of the ALADIN data, quality control is performed using the observation type (clear and cloudy) and error estimation value of the ALADIN data. The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 39971 which gives the root mean square difference (RMSD) of 3.88 m/s. The lower layer (lower than 700 hPa altitude) RMSD shows slightly better comparison, 3.35 m/s vs. 4.17 m/s, while the correlation coefficient is better for the upper and middle layers of 0.98 compared to the 0.94 of the lower layer. In the conference, detailed analysis of the comparison results and additional AMV data, including visible channel and water vapor channel along with the extended time period are going to be presented.</p>

Assessment of the Impact of Observations on Analyses Derived from Observing System Experiments

2012 ◽  
Vol 140 (1) ◽  
pp. 245-257 ◽  
Author(s):  
Cristina Lupu ◽  
Pierre Gauthier ◽  
Stéphane Laroche
Keyword(s):  
North America ◽  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Prediction System ◽  
Numerical Weather ◽  
Amount Of Information ◽  
The North ◽  
The Impact ◽  
Assimilation System

Abstract Observing system experiments (OSEs) are commonly used to quantify the impact of different observation types on forecasts produced by a specific numerical weather prediction system. Recently, methods based on degree of freedom for signal (DFS) have been implemented to diagnose the impact of observations on the analyses. In this paper, the DFS is used as a diagnostic to estimate the amount of information brought by subsets of observations in the context of OSEs. This study is interested in the evaluation of the North American observing networks applied to OSEs performed at the Meteorological Service of Canada for the period of January and February 2007. The relative values of the main observing networks over North America derived from DFS calculations are compared with those from OSEs in which aircraft or radiosonde data have been removed. The results show that removing some observation types from the assimilation system influences the effective weight of the remaining assimilated observations, which may have an increased impact to compensate for the removal of other observations. The response of the remaining observations when a given set of observations is denied is illustrated comparing DFS calculations with the observations’ impact estimated from OSEs.

scholarly journals Interannual variability of precipitable water

1996 ◽  
Vol 14 (4) ◽  
pp. 464-467 ◽  
Author(s):  
R. P. Kane
Keyword(s):  
Interannual Variability ◽  
Southern Hemisphere ◽  
Northern Hemisphere ◽  
Precipitable Water ◽  
Radiosonde Data ◽  
High Latitudes ◽  
Zonal Winds ◽  
Low Latitudes ◽  
Linear Trends

Abstract. The 12-month running means of the surface-to-500 mb precipitable water obtained from analysis of radiosonde data at seven selected locations showed three types of variability viz: (1) quasi-biennial oscillations; these were different in nature at different latitudes and also different from the QBO of the stratospheric tropical zonal winds; (2) decadal effects; these were prominent at middle and high latitudes and (3) linear trends; these were prominent at low latitudes, up trends in the Northern Hemisphere and downtrends in the Southern Hemisphere.

scholarly journals Southern High-Latitude Ensemble Data Assimilation in the Antarctic Mesoscale Prediction System

2005 ◽  
Vol 133 (12) ◽  
pp. 3431-3449 ◽  
Author(s):  
D. M. Barker
Keyword(s):  
Data Assimilation ◽  
Sampling Error ◽  
Forecast Error ◽  
Weather Prediction ◽  
Forecast Errors ◽  
Prediction System ◽  
Spatial Covariance ◽  
Ensemble Data Assimilation ◽  
Ensemble Data ◽  
The Antarctic

Abstract Ensemble data assimilation systems incorporate observations into numerical models via solution of the Kalman filter update equations, and estimates of forecast error covariances derived from ensembles of model integrations. In this paper, a particular algorithm, the ensemble square root filter (EnSRF), is tested in a limited-area, polar numerical weather prediction (NWP) model: the Antarctic Mesoscale Prediction System (AMPS). For application in the real-time AMPS, the number of model integrations that can be run to provide forecast error covariances is limited, resulting in an ensemble sampling error that degrades the analysis fit to observations. In this work, multivariate, climatologically plausible forecast error covariances are specified via averaged forecast difference statistics. Ensemble representations of the “true” forecast errors, created using randomized control variables of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) three-dimensional variational (3DVAR) data assimilation system, are then used to assess the dependence of sampling error on ensemble size, data density, and localization of covariances using simulated observation networks. Results highlight the detrimental impact of ensemble sampling error on the analysis increment structure of correlated, but unobserved fields—an issue not addressed by the spatial covariance localization techniques used to date. A 12-hourly cycling EnSRF/AMPS assimilation/forecast system is tested for a two-week period in December 2002 using real, conventional (surface, rawinsonde, satellite retrieval) observations. The dependence of forecast scores on methods used to maintain ensemble spread and the inclusion of perturbations to lateral boundary conditions are studied.

scholarly journals Verification of Forecast Weather Surface Variables over Vietnam Using the National Numerical Weather Prediction System

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Tien Du Duc ◽  
Lars Robert Hole ◽  
Duc Tran Anh ◽  
Cuong Hoang Duc ◽  
Thuy Nguyen Ba
Keyword(s):  
Numerical Weather Prediction ◽  
Weather Prediction ◽  
Model Performance ◽  
Wrf Model ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Regional Models ◽  
Global Spectral Model ◽  
Numerical Weather ◽  
The Us

The national numerical weather prediction system of Vietnam is presented and evaluated. The system is based on three main models, namely, the Japanese Global Spectral Model, the US Global Forecast System, and the US Weather Research and Forecasting (WRF) model. The global forecast products have been received at 0.25- and 0.5-degree horizontal resolution, respectively, and the WRF model has been run locally with 16 km horizontal resolution at the National Center for Hydro-Meteorological Forecasting using lateral conditions from GSM and GFS. The model performance is evaluated by comparing model output against observations of precipitation, wind speed, and temperature at 168 weather stations, with daily data from 2010 to 2014. In general, the global models provide more accurate forecasts than the regional models, probably due to the low horizontal resolution in the regional model. Also, the model performance is poorer for stations with altitudes greater than 500 meters above sea level (masl). For tropical cyclone performance validations, the maximum wind surface forecast from global and regional models is also verified against the best track of Joint Typhoon Warning Center. Finally, the model forecast skill during a recent extreme rain event in northeast Vietnam is evaluated.

scholarly journals On the Sensitivity of the Simulated Diurnal Cycle of Precipitation to 3-Hourly Radiosonde Assimilation: A Case Study over the Western Maritime Continent

2021 ◽  
Vol 149 (10) ◽  
pp. 3449-3468
Author(s):  
Joshua Chun Kwang Lee ◽  
Anurag Dipankar ◽  
Xiang-Yu Huang
Keyword(s):  
Diurnal Cycle ◽  
High Frequency ◽  
Initial Conditions ◽  
Rainfall Variability ◽  
Weather Prediction ◽  
Radiosonde Data ◽  
Western Coast ◽  
Maritime Continent ◽  
Model Biases ◽  
Diurnal Cycle Of Precipitation

AbstractThe diurnal cycle is the most prominent mode of rainfall variability in the tropics, governed mainly by the strong solar heating and land–sea interactions that trigger convection. Over the western Maritime Continent, complex orographic and coastal effects can also play an important role. Weather and climate models often struggle to represent these physical processes, resulting in substantial model biases in simulations over the region. For numerical weather prediction, these biases manifest themselves in the initial conditions, leading to phase and amplitude errors in the diurnal cycle of precipitation. Using a tropical convective-scale data assimilation system, we assimilate 3-hourly radiosonde data from the pilot field campaign of the Years of Maritime Continent, in addition to existing available observations, to diagnose the model biases and assess the relative impacts of the additional wind, temperature, and moisture information on the simulated diurnal cycle of precipitation over the western coast of Sumatra. We show how assimilating such high-frequency in situ observations can improve the simulated diurnal cycle, verified against satellite-derived precipitation, radar-derived precipitation, and rain gauge data. The improvements are due to a better representation of the sea breeze and increased available moisture in the lowest 4 km prior to peak convection. Assimilating wind information alone was sufficient to improve the simulations. We also highlight how during the assimilation, certain multivariate background error constraints and moisture addition in an ad hoc manner can negatively impact the simulations. Other approaches should be explored to better exploit information from such high-frequency observations over this region.

scholarly journals Climatology of migrating and non-migrating tides observed by three meteor radars in the southern equatorial region

2021 ◽  
Author(s):  
Jianyuan Wang ◽  
Wen Yi ◽  
Jianfei Wu ◽  
Tingdi Chen ◽  
Xianghui Xue ◽  
...  
Keyword(s):  
Harmonic Analysis ◽  
Northern Hemisphere ◽  
Climate Model ◽  
Equatorial Region ◽  
Stratospheric Sudden Warming ◽  
Tidal Model ◽  
Community Climate Model ◽  
Zonal Wavenumber ◽  
Climatic Features ◽  
Community Climate

Abstract. We present a study of migrating and non-migrating tidal winds observed simultaneously by three meteor radars situated in the southern equatorial region. The radars are located at Cariri (7.4° S, 36.5° W), Brazil, Kototabang (0.2° S, 100.3° E), Indonesia and Darwin (12.3° S, 130.8° E), Australia. Harmonic analysis was used to obtain amplitudes and phases for diurnal and semidiurnal solar migrating and non-migrating tides between 80 and 100 km altitude during the period 2005 to 2008. They include the important tidal components of diurnal westward-propagating zonal wavenumber 1 (DW1), diurnal eastward-propagating zonal wavenumber 3 (DE3), semidiurnal westward-propagating zonal wavenumber 2 (SW2), and semidiurnal eastward-propagating zonal wavenumber 2 (SE2). In addition, we also present a climatology of these wind tides and analyze the reliability of the fitting through the reference to Whole Atmosphere Community Climate Model (WACCM) winds. The analysis suggests that the migrating tides could be well fitted by the three different radars, but the non-migrating tides might be overestimated. The results based on observations were also compared with the Climatological Tidal Model of the Thermosphere (CTMT). In general, climatic features between observations and model migrating tides were satisfactory in both wind components. However, the features of the DW1, DE3 and SW2 amplitudes in both wind components were slightly different from the results of the CTMT models. This result is probably because tides could be enhanced by the 2006 northern hemisphere stratospheric sudden warming (NH-SSW) event.

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