scholarly journals An Assessment of Satellite Radiance Data Assimilation in RMAPS

2018 ◽  
Vol 11 (1) ◽  
pp. 54 ◽  
Author(s):  
Yanhui Xie ◽  
Shuiyong Fan ◽  
Min Chen ◽  
Jiancheng Shi ◽  
Jiqin Zhong ◽  
...  
Keyword(s):  
North China ◽  
Initial Temperature ◽  
Initial Conditions ◽  
Positive Impact ◽  
Skill Score ◽  
Limited Area ◽  
Accumulated Rainfall ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
The Impact

Due to the availability of observations and the effectiveness of bias correction, it is still a challenge to assimilate data from the polar orbit satellites into a limited-area and frequently updated model. This study assessed the initial application of satellite radiance data from multiple platforms in the Rapid-refresh Multi-scale Analysis and Prediction System (RMAPS). Satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) were used. Two 12-day retrospective runs were conducted to evaluate the impact of assimilating satellite radiance data on 0–24 h forecasts using RMAPS. The forecasts, initialized from analyses with and without satellite radiance data, were verified against observations. The results showed that satellite radiance data from AMSU-A and MHS had a positive impact on the initial conditions and the forecasts of RMAPS, even over the relatively data-rich area of North China. Compared to the control run that only assimilated conventional observations, an improvement of about 36.8% can be obtained for the temperature bias between 300 hPa and 850 hPa and 0.65% for the average RMSE. Satellite radiance observations from 1200 UTC contribute relatively significantly (77.8%) to the bias improvement of the initial temperature field. For the wind at 10 m, the bias and root-mean-square error (RMSE) both had a reduction for the 0–12 h forecast range. An improvement can be also found for the skill score of the 3-h accumulated rainfall below 10.0 mm in the first 12 h of the forecast range. There was a slight improvement in the skill score of the 6-h accumulated rainfall above 50 mm over North China, with a 20.7% improvement for the first 12 h of the forecast. The inclusion of satellite radiance observations was found to be beneficial for the initial temperature, which consequently improved the forecast skill of the 0–12 h range in the RMAPS.

scholarly journals Impacts of Assimilating ATMS Radiances on Heavy Rainfall Forecast in RMAPS-ST

2020 ◽  
Vol 12 (7) ◽  
pp. 1147
Author(s):  
Yanhui Xie ◽  
Min Chen ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Jing He ◽  
...  
Keyword(s):  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Added Value ◽  
Rainfall Forecast ◽  
Hourly Rainfall ◽  
Radiance Data ◽  
The Impact

The Advanced Technology Microwave Sounder (ATMS) mounted on the Suomi National Polar-Orbiting Partnership (NPP) satellite can provide both temperature and humidity information for a weather prediction model. Based on the rapid-refresh multi-scale analysis and prediction system—short-term (RMAPS-ST), we investigated the impact of ATMS radiance data assimilation on strong rainfall forecasts. Two groups of experiments were conducted to forecast heavy precipitation over North China between 18 July and 20 July 2016. The initial conditions and forecast results from the two groups of experiments have been compared and evaluated against observations. In comparison with the first group of experiments that only assimilated conventional observations, some added value can be obtained for the initial conditions of temperature, humidity, and wind fields after assimilating ATMS radiance observations in the system. For the forecast results with the assimilation of ATMS radiances, the score skills of quantitative forecast rainfall have been improved when verified against the observed rainfall. The Heidke skill score (HSS) skills of 6-h accumulated precipitation in the 24-h forecasts were overall increased, more prominently so for the heavy rainfall above 25 mm in the 0–6 h of forecasts. Assimilating ATMS radiance data reduced the false alarm ratio of quantitative precipitation forecasting in the 0–12 h of the forecast range and thus improved the threat scores for the heavy rainfall storm. Furthermore, the assimilation of ATMS radiances improved the spatial distribution of hourly rainfall forecast with observations compared with that of the first group of experiments, and the mean absolute error was reduced in the 10-h lead time of forecasts. The inclusion of ATMS radiances provided more information for the vertical structure of features in the temperature and moisture profiles, which had an indirect positive impact on the forecasts of the heavy rainfall in the RMAPS-ST system. However, the deviation in the location of the heavy rainfall center requires future work.

Improving numerical simulation of typhoon LEKIMA(2019) through assimilating ATMS radiance data

2020 ◽  
Author(s):  
Lei Zhang ◽  
Baode Chen
Keyword(s):  
Numerical Simulation ◽  
Data Assimilation ◽  
Inner Core ◽  
Weather Prediction ◽  
Advanced Technology ◽  
Limited Area ◽  
Numerical Weather ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
The Impact

<p>Lacking of high-resolution observations over oceans is one of the major problems for the numerical simulation of the tropical cyclones (TC), especially for the tropical cyclone inner-core structure’s simulation. Satellite observations plays an important role in improving the forecast skills of numerical weather prediction (NWP) systems. Many studies have suggested that the assimilation of satellite radiance data can substantially improve the numerical weather forecast skills for global model. However, the performance of satellite radiance data assimilation in limited-area modeling systems is still controversial.</p><p>This study attempts to investigate the impact of assimilation of the Advanced Technology Microwave Sounder (ATMS) satellite radiances data and its role to improve the model initial condition and forecast of typhoon LEKIMA(2019) using a regional mesoscale model. In this study, detailed analysis of the data impact will be presented, also the results from different data assimilation methods and different data usage schemes will be discussed.</p>

scholarly journals Development of a hybrid variational-ensemble data assimilation technique for observed lightning tested in a mesoscale model

2014 ◽  
Vol 21 (5) ◽  
pp. 1027-1041 ◽  
Author(s):  
K. Apodaca ◽  
M. Zupanski ◽  
M. DeMaria ◽  
J. A. Knaff ◽  
L. D. Grasso
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
New Information ◽  
Forecasting System ◽  
Maximum Likelihood Ensemble Filter ◽  
The Impact

Abstract. Lightning measurements from the Geostationary Lightning Mapper (GLM) that will be aboard the Geostationary Operational Environmental Satellite – R Series will bring new information that can have the potential for improving the initialization of numerical weather prediction models by assisting in the detection of clouds and convection through data assimilation. In this study we focus on investigating the utility of lightning observations in mesoscale and regional applications suitable for current operational environments, in which convection cannot be explicitly resolved. Therefore, we examine the impact of lightning observations on storm environment. Preliminary steps in developing a lightning data assimilation capability suitable for mesoscale modeling are presented in this paper. World Wide Lightning Location Network (WWLLN) data was utilized as a proxy for GLM measurements and was assimilated with the Maximum Likelihood Ensemble Filter, interfaced with the Nonhydrostatic Mesoscale Model core of the Weather Research and Forecasting system (WRF-NMM). In order to test this methodology, regional data assimilation experiments were conducted. Results indicate that lightning data assimilation had a positive impact on the following: information content, influencing several dynamical variables in the model (e.g., moisture, temperature, and winds), and improving initial conditions during several data assimilation cycles. However, the 6 h forecast after the assimilation did not show a clear improvement in terms of root mean square (RMS) errors.

scholarly journals Impact of Radiance Data Assimilation on the Prediction of Heavy Rainfall in RMAPS: A Case Study

2018 ◽  
Vol 10 (9) ◽  
pp. 1380 ◽  
Author(s):  
Yanhui Xie ◽  
Jiancheng Shi ◽  
Shuiyong Fan ◽  
Min Chen ◽  
Youjun Dou ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Heavy Rainfall ◽  
Precipitation Forecast ◽  
Observation Data ◽  
Rainfall Events ◽  
Satellite Radiance Data ◽  
Radiance Data ◽  
The Impact ◽  
Heavy Rainfall Events

Herein, a case study on the impact of assimilating satellite radiance observation data into the rapid-refresh multi-scale analysis and prediction system (RMAPS) is presented. This case study targeted the 48 h period from 19–20 July 2016, which was characterized by the passage of a low pressure system that produced heavy rainfall over North China. Two experiments were performed and 24 h forecasts were produced every 3 h. The results indicated that the forecast prior to the satellite radiance data assimilation could not accurately predict heavy rainfall events over Beijing and the surrounding area. The assimilation of satellite radiance data from the advanced microwave sounding unit-A (AMSU-A) and microwave humidity sounding (MHS) improved the skills of the quantitative precipitation forecast to a certain extent. In comparison with the control experiment that only assimilated conventional observations, the experiment with the integrated satellite radiance data improved the rainfall forecast accuracy for 6 h accumulated precipitation after about 6 h, especially for rainfall amounts that were greater than 25 mm. The average rainfall score was improved by 14.2% for the 25 mm threshold and by 35.8% for 50 mm of rainfall. The results also indicated a positive impact of assimilating satellite radiances, which was primarily reflected by the improved performance of quantitative precipitation forecasting and higher spatial correlation in the forecast range of 6–12 h. Satellite radiance observations provided certain valuable information that was related to the temperature profile, which increased the scope of the prediction of heavy rainfall and led to an improvement in the rainfall scoring in the RMAPS. The inclusion of satellite radiance observations was found to have a small but beneficial impact on the prediction of heavy rainfall events as it relates to our case study conditions. These findings suggest that the assimilation of satellite radiance data in the RMAPS can provide an overall improvement in heavy rainfall forecasting.

scholarly journals The 23–26 September 2012 U.K. Floods: Using PV Surgery to Quantify Sensitivity to Upper-Level Forcing

2017 ◽  
Vol 145 (10) ◽  
pp. 4055-4079 ◽  
Author(s):  
Sam Hardy ◽  
David M. Schultz ◽  
Geraint Vaughan
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Extreme Event ◽  
Initial Conditions ◽  
Initial Position ◽  
River Flooding ◽  
The United Kingdom ◽  
Accumulated Rainfall ◽  
Upper Level ◽  
The Impact

Major river flooding affected the United Kingdom in late September 2012 as a slow-moving extratropical cyclone brought over 150 mm of rain to parts of northern England and north Wales. The cyclone deepened over the United Kingdom on 24–26 September as a potential vorticity (PV) anomaly approached from the northwest, elongated into a PV streamer, and wrapped around the cyclone. The strength and position of the PV anomaly is modified in the initial conditions of Weather Research and Forecasting Model simulations, using PV surgery, to examine whether different upper-level forcing, or different phasing between the PV anomaly and cyclone, could have produced an even more extreme event. These simulations reveal that quasigeostrophic (QG) forcing for ascent ahead of the anomaly contributed to the persistence of the rainfall over the United Kingdom. Moreover, weakening the anomaly resulted in lower rainfall accumulations across the United Kingdom, suggesting that the impact of the event might be proportional to the strength of the upper-level QG forcing. However, when the anomaly was strengthened, it rotated cyclonically around a large-scale trough over Iceland rather than moving eastward as in the verifying analysis, with strongly reduced accumulated rainfall across the United Kingdom. A similar evolution developed when the anomaly was moved farther away from the cyclone. Conversely, moving the anomaly nearer to the cyclone produced a similar solution to the verifying analysis, with slightly increased rainfall totals. These counterintuitive results suggest that the verifying analysis represented almost the highest-impact scenario possible for this flooding event when accounting for sensitivity to the initial position and strength of the PV anomaly.

scholarly journals The Contribution of Ex–Tropical Cyclone Gert (1999) toward the Weakening of a Midlatitude Cyclogenesis Event

2008 ◽  
Vol 136 (6) ◽  
pp. 2091-2111 ◽  
Author(s):  
Anna Agustí-Panareda
Keyword(s):  
Tropical Cyclone ◽  
Vertical Velocity ◽  
Initial Conditions ◽  
Negative Impact ◽  
Positive Impact ◽  
Extratropical Cyclone ◽  
Synoptic Scale ◽  
Extratropical Transition ◽  
Peak Intensity ◽  
The Impact

Abstract Tropical Cyclone Gert (1999) experienced an extratropical transition while it merged with an extratropical cyclone upstream. The upstream extratropical cyclone had started to intensify before it merged with the transitioning tropical cyclone, and it continued intensifying afterward (12 hPa in 12 h, according to the Met Office analysis). The question addressed in this paper is the following: what was the impact of the transitioning tropical cyclone on this intensification of the upstream extratropical cyclone? Until now, in the literature, tropical cyclones that experience extratropical transition have been found to have either no impact or a positive impact on the development of extratropical cyclogenesis events. The positive impact involves either a triggering of the development of the extratropical cyclone or simply a contribution to its deepening. However, the case studied here proves to have a negative impact on the developing extratropical cyclone upstream by diminishing its intensification. Forecasts are performed with and without the tropical cyclone in the initial conditions. They show that when Gert is not present in the initial conditions, the peak intensity of the cyclone upstream occurs 9 h earlier and it is 10 hPa deeper than when Gert is present. Thus, Gert acts to weaken the development by contributing to the filling of the extratropical surface low upstream. Quasigeostropic (QG) diagnostics show that the negative impact on the extratropical development is linked to the fact that the transitioning tropical cyclone interacts with a warm front inducing a negative QG vertical velocity over the developing extratropical low upstream. This interpretation is consistent with other contrasting cases in which the transitioning tropical cyclone interacts with a cold front and induces a positive QG vertical velocity over the developing low upstream, thus enhancing its development. The results are also in agreement with idealized experiments in the literature that are aimed at studying the predictability of extratropical storms. These idealized experiments yielded similar results using synoptic-scale and mesoscale vortices as perturbations on warm and cold fronts.

scholarly journals Hybrid variational-ensemble assimilation of lightning observations in a mesoscale model

2014 ◽  
Vol 1 (1) ◽  
pp. 917-952
Author(s):  
K. Apodaca ◽  
M. Zupanski ◽  
M. DeMaria ◽  
J. A. Knaff ◽  
L. D. Grasso
Keyword(s):  
Data Assimilation ◽  
Prediction Models ◽  
Mesoscale Model ◽  
Initial Conditions ◽  
Positive Impact ◽  
Weather Prediction ◽  
New Information ◽  
Forecasting System ◽  
Maximum Likelihood Ensemble Filter ◽  
The Impact

Abstract. Lightning measurements from the Geostationary Lightning Mapper (GLM) that will be aboard the Goestationary Operational Environmental Satellite – R Series will bring new information that can have the potential for improving the initialization of numerical weather prediction models by assisting in the detection of clouds and convection through data assimilation. In this study we focus on investigating the utility of lightning observations in mesoscale and regional applications suitable for current operational environments, in which convection cannot be explicitly resolved. Therefore, we examine the impact of lightning observations on storm environment. Preliminary steps in developing a lightning data assimilation capability suitable for mesoscale modeling are presented in this paper. World Wide Lightning Location Network (WWLLN) data was utilized as a proxy for GLM measurements and was assimilated with the Maximum Likelihood Ensemble Filter, interfaced with the Nonhydrostatic Mesoscale Model core of the Weather Research and Forecasting system (WRF-NMM). In order to test this methodology, regional data assimilation experiments were conducted. Results indicate that lightning data assimilation had a positive impact on the following: information content, influencing several dynamical variables in the model (e.g., moisture, temperature, and winds), improving initial conditions, and partially improving WRF-NMM forecasts during several data assimilation cycles.

scholarly journals Impact of Atmospheric and Aerosol Optical Depth Observations on Aerosol Initial Conditions in a strongly-coupled data assimilation system

2019 ◽  
Author(s):  
Milija Zupanski ◽  
Anton Kliewer ◽  
Ting-Chi Wu ◽  
Karina Apodaca ◽  
Qijing Bian ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Initial Conditions ◽  
Positive Impact ◽  
Storm Event ◽  
Strongly Coupled ◽  
Atmospheric Observations ◽  
Coupled Data Assimilation ◽  
The Impact

Abstract. Strongly coupled data assimilation frameworks provide a mechanism for including additional information about aerosols through the coupling between aerosol and atmospheric variables, effectively utilizing atmospheric observations to change the aerosol analysis. Here, we investigate the impact of these observations on aerosol using the Maximum Likelihood Ensemble Filter (MLEF) algorithm with Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) which includes the Godard Chemistry Aerosol Radiation and Transport (GOCART) module. We apply this methodology to a dust storm event over the Arabian Peninsula and examine in detail the error covariance and in particular the impact of atmospheric observations on improving the aerosol initial conditions. The assimilated observations include conventional atmospheric observations and Aerosol Optical Depth (AOD) retrievals. Results indicate a positive impact of using strongly coupled data assimilation and atmospheric observations on the aerosol initial conditions, quantified using Degrees of Freedom for Signal.

CONCEPTUAL PROVISIONS OF THE STATE POLICY OF ENSURING THE ECONOMIC SECURITY OF UKRAINE IN THE CONDITIONS OF MODERN THREATS AND DIGITALIZATION

2021 ◽  
Vol 298 (5 Part 1) ◽  
pp. 280-286
Author(s):  
Olga GARAFONOVA ◽  
◽  
Liydmyla POLISHCHUK ◽  
Liudmyla DYKHNYCH ◽  
Inna YASHCHENKO ◽  
...  
Keyword(s):  
National Economy ◽  
State Policy ◽  
Structural Changes ◽  
Initial Conditions ◽  
Positive Impact ◽  
Economic Security ◽  
The State ◽  
Practical Significance ◽  
External Threats ◽  
The Impact

The article focuses on the relevance of identification and typology of modern risks and threats to the economic security of Ukraine. According to the nature of modern risks and threats, they are classified as hybrid. The hybrid nature of modern threats to Ukraine’s economic security necessitates the application of new approaches to the formation and implementation of state policy to ensure the economic security of Ukraine’s national economy. It is shown that the economic security of the state is a complex dynamic system that requires constant monitoring and management of resilience to internal and external threats in order to ensure a positive impact on socio-economic development, improve macroeconomic development, ensure quality and necessary structural changes and institutional reforms. formation of the system of competitiveness of the national economy. Under such conditions, the general goal of state policy should be to improve Ukraine’s economic security system, ensure a higher level of its resistance to the impact of hybrid risks and threats, factors and conditions of globalization and the world order. The elements of the state policy of economic security of Ukraine are determined, namely – the initial conditions, the purpose of state policy, goals and principles of policy, directions of formation of the system of counteraction to security threats, financial-resource and organizational-managerial support. The practical significance of the research results is that the immaturity of the integral system of economic security of the state is identified, which is due to the imperfection of the institutional environment, the imbalance of its structure, the predominance of the role of informal institutions over formal ones. The scientific novelty of the study is to substantiate the conceptual provisions of state policy to ensure the economic security of the state in the face of non-standard hybrid risks and threats.

scholarly journals Impact of radar data assimilation using WRF three-dimensional variational system, for the simulation of a heavy rainfall case in Central Italy

2013 ◽  
Vol 6 (4) ◽  
pp. 7315-7353
Author(s):  
I. Maiello ◽  
R. Ferretti ◽  
S. Gentile ◽  
M. Montopoli ◽  
E. Picciotti ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Radial Velocity ◽  
Heavy Rainfall ◽  
Initial Conditions ◽  
Positive Impact ◽  
Central Italy ◽  
Three Dimensional ◽  
Warm Start ◽  
The Impact ◽  
Dwr Data

Abstract. This work is a first assessment of the role of Doppler Weather radar (DWR) data in a mesoscale model for the prediction of a heavy rainfall. The study analyzes the event occurred during 19–22 May 2008 in the urban area of Rome. The impact of the radar reflectivity and radial velocity acquired from Monte Midia Doppler radar, on the assimilation into the Weather Research Forecasting (WRF) model version 3.2, is discussed. The goal is to improve the WRF high resolution initial condition by assimilating DWR data and using ECMWF analyses as First Guess thus improving the forecast of surface rainfall. Several experiments are performed using different set of Initial Conditions (ECMWF analyses and warm start or cycling) and a different assimilation strategy (3 h-data assimilation cycle). In addition, 3DVAR (three-dimensional variational) sensitivity tests to outer loops are performed for each of the previous experiment to include the non-linearity in the observation operators. In order to identify the best ICs, statistical indicators such as forecast accuracy, frequency bias, false alarm rate and equitable threat score for the accumulated precipitation are used. The results show that the assimilation of DWR data has a positive impact on the prediction of the heavy rainfall of this event, both assimilating reflectivity and radial velocity, together with conventional observations. Finally, warm start results in more accurate experiments as well as the outer loops strategy.

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