scholarly journals An Observing System Simulation Experiment (OSSE) to Assess the Impact of Doppler Wind Lidar (DWL) Measurements on the Numerical Simulation of a Tropical Cyclone

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Lei Zhang ◽  
Zhaoxia Pu
Keyword(s):  
Numerical Simulation ◽  
Tropical Cyclone ◽  
Mesoscale Model ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Wrf Model ◽  
Wind Lidar ◽  
Wind Profiles ◽  
The Impact ◽  
Doppler Wind Lidar

The importance of wind observations has been recognized for many years. However, wind observations—especially three-dimensional global wind measurements—are very limited. A satellite-based Doppler Wind Lidar (DWL) is proposed to measure three-dimensional wind profiles using remote sensing techniques. Assimilating these observations into a mesoscale model is expected to improve the performance of the numerical weather prediction (NWP) models. In order to examine the potential impact of the DWL three-dimensional wind profile observations on the numerical simulation and prediction of tropical cyclones, a set of observing simulation system experiments (OSSEs) is performed using the advanced research version of the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3DVAR) data assimilation system. Results indicate that assimilating the DWL wind observations into the mesoscale numerical model has significant potential for improving tropical cyclone track and intensity forecasts.

scholarly journals Impact of Lidar Data Assimilation on Low-Level Wind Shear Simulation at Lanzhou Zhongchuan International Airport, China: A Case Study

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1342
Author(s):  
Lanqian Li ◽  
Ningjing Xie ◽  
Longyan Fu ◽  
Kaijun Zhang ◽  
Aimei Shao ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Wind Shear ◽  
Three Dimensional ◽  
Wrf Model ◽  
Lidar Data ◽  
Positive Role ◽  
Low Level ◽  
Wind Lidar ◽  
The Impact ◽  
Doppler Wind Lidar

Doppler wind lidar has played an important role in alerting low-level wind shear (LLW). However, these high-resolution observations are underused in the model-based analysis and forecasting of LLW. In this regard, we employed the Weather Research and Forecasting (WRF) model and its three-dimensional variational (3D-VAR) system to investigate the impact of lidar data assimilation (DA) on LLW simulations. Eight experiments (including six assimilation experiments) were designed for an LLW process as reported by pilots, in which different assimilation intervals, assimilation timespans, and model vertical resolutions were examined. Verified against observations from Doppler wind lidar and an automated weather observing system (AWOS), the introduction of lidar data is helpful for describing the LLW event, which can represent the temporal and spatial features of LLW, whereas experiments without lidar DA have no ability to capture LLW. While lidar DA has an obviously positive role in simulating LLW in the 10–20 min after the assimilation time, this advantage cannot be maintained over a longer time. Therefore, a smaller assimilation interval is favorable for improving the simulated effect of LLW. In addition, increasing the vertical resolution does not evidently improve the experimental results, either with or without assimilation.

scholarly journals Improvement of mesoscale numerical weather prediction WRF-ARW in the Republic of Belarus by assimilation of radar wind and reflectivity data

2020 ◽  
pp. 3-13
Author(s):  
Palina A. Zaiko ◽  
Aliaksandr N. Krasouski ◽  
Siarhei K. Barodka
Keyword(s):  
Mesoscale Model ◽  
Forecast Error ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Wrf Model ◽  
Radar Data ◽  
False Alarms ◽  
Strong Wind ◽  
Number Of False Alarms ◽  
Circulation Types

The forecasts of severe weather events obtained with the WRF numerical mesoscale model with the adapted system for assimilation of reflectivity and radial velocity data from the network of Belarusian Doppler weather radars used in Belhydromet in 2019 are analysed. A description of the system for the echo quality control based on the radar dual-polarisation characteristics and the method for three-dimensional variational assimilation (3D-VAR) used to assimilate data in the WRF model are described. The results of case studies on the simulation of precipitation and strong wind for various circulation types in Belarus with and without radar data assimilation are given. The statistical and object-oriented verification of these forecasts is provided. The results of the comprehensive assessment reveal a decrease in the forecast error for 10-m wind speed for the early forecast hours (+6 h) by 1.34 m/s, as well as a more accurate forecast of the location, orientation of the cloud systems and precipitation zones, and a decrease in the number of false alarms in the version with assimilation. A preliminary conclusion on the possibility of using the forecast results in nowcasting systems is also made.

scholarly journals ESA’s spaceborne lidar mission ADM-Aeolus; project status and preparations for launch

2018 ◽  
Vol 176 ◽  
pp. 04007 ◽  
Author(s):  
Anne Grete Straume ◽  
Anders Elfving ◽  
Denny Wernham ◽  
Frank de Bruin ◽  
Thomas Kanitz ◽  
...  
Keyword(s):  
Optical Properties ◽  
Weather Prediction ◽  
Atmospheric Dynamics ◽  
The Novel ◽  
Aerosol Optical Properties ◽  
Climate Research ◽  
Wind Lidar ◽  
Core Mission ◽  
Wind Profiles ◽  
Doppler Wind Lidar

ESA’s Doppler Wind lidar mission, the Atmospheric Dynamics Mission (ADM-Aeolus, hereafter abbreviated to Aeolus), was chosen as an Earth Explorer Core mission within the Living Planet Programme in 1999. It shall demonstrate the potential of space-based Doppler Wind lidars for operational measurements of wind profiles and their use in Numerical Weather Prediction (NWP) and climate research. Spin-off products are profiles of cloud and aerosol optical properties. Aeolus carries the novel Doppler Wind lidar instrument ALADIN. The mission prime is Airbus Defence & Space UK (ADS-UK), and the instrument prime is Airbus Defence & Space France (ADS-F).

scholarly journals Linkage between an advanced air quality model and a mechanistic watershed model

2010 ◽  
Vol 3 (3) ◽  
pp. 1503-1548 ◽  
Author(s):  
K. Vijayaraghavan ◽  
J. Herr ◽  
S.-Y. Chen ◽  
E. Knipping
Keyword(s):  
South Carolina ◽  
Air Quality ◽  
Mesoscale Model ◽  
Three Dimensional ◽  
Wrf Model ◽  
Air Quality Model ◽  
Watershed Model ◽  
Quality Model ◽  
Particulate Nitrogen ◽  
The Impact

Abstract. An offline linkage between two advanced multi-pollutant air quality and watershed models is presented. The models linked are (1) the Advanced Modeling System for Transport, Emissions, Reactions and Deposition of Atmospheric Matter (AMSTERDAM) (a three-dimensional Eulerian plume-in-grid model derived from the Community Multiscale Air Quality (CMAQ) model) and (2) the Watershed Analysis Risk Management Framework (WARMF). The pollutants linked include gaseous and particulate nitrogen, sulfur and mercury compounds. The linkage may also be used to obtain meteorological fields such as precipitation and air temperature required by WARMF from the outputs of the meteorology chemistry interface processor (MCIP) that processes meteorology simulated by the fifth generation Mesoscale Model (MM5) or the Weather Research and Forecast (WRF) model for input to AMSTERDAM. The linkage is tested in the Catawba River basin of North and South Carolina for ammonium, nitrate and sulfate. Modeled air quality and meteorological fields transferred by the linkage can supplement the conventional measurements used to drive WARMF and may be used to help predict the impact of changes in atmospheric emissions on water quality.

scholarly journals Initial Assessment of the Performance of the First Wind Lidar in Space on Aeolus

2020 ◽  
Vol 237 ◽  
pp. 01010 ◽  
Author(s):  
Oliver Reitebuch ◽  
Christian Lemmerz ◽  
Oliver Lux ◽  
Uwe Marksteiner ◽  
Stephan Rahm ◽  
...  
Keyword(s):  
Current Knowledge ◽  
Weather Prediction ◽  
Systematic Errors ◽  
Global Scale ◽  
Initial Assessment ◽  
Horizontal Wind ◽  
Successful Launch ◽  
Wind Lidar ◽  
Wind Profiles ◽  
Doppler Wind Lidar

Soon after its successful launch in August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) on-board ESA’s Earth Explorer satellite Aeolus has demonstrated to provide atmospheric wind profiles on a global scale. Being the first ever Doppler Wind Lidar (DWL) instrument in space, ALADIN contributes to the improvement in numerical weather prediction (NWP) by measuring one component of the horizontal wind vector. The performance of the ALADIN instrument was assessed by a team from ESA, DLR, industry, and NWP centers during the first months of operation. The current knowledge about the main contributors to the random and systematic errors from the instrument will be discussed. First validation results from an airborne campaign with two wind lidars on-board the DLR Falcon aircraft will be shown.

scholarly journals Recent developments in the data assimilation of AROME/HU numerical weather prediction model

Időjárás ◽  
2021 ◽  
Vol 125 (4) ◽  
pp. 521-553
Author(s):  
Helga Tóth ◽  
Viktória Homonnai ◽  
Máté Mile ◽  
Anikó Várkonyi ◽  
Zsófia Kocsis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Mesoscale Model ◽  
Interpolation Method ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Numerical Weather Prediction Model ◽  
Optimal Interpolation ◽  
Surface Data ◽  
Recent Developments ◽  
The Impact

A local three-dimensional variational data assimilation (DA) system was implemented operationally in AROME/HU (Application of Research to Operations at Mesoscale) non-hydrostatic mesoscale model at the Hungarian Meteorological Service (OMSZ) in 2013. In the first version, rapid update cycling (RUC) approach was employed with 3-hour frequency in local upper-air DA using conventional observations only. Optimal interpolation method was adopted for the surface data assimilation later in 2016. This paper describes the current developments showing the impact of more conventional and remote-sensing observations assimilated in this system, which reveals the benefit of additional local high-resolution observations. Furthermore, it is shown that an hourly assimilation-forecast cycle outperforms the 3-hourly updated system in our DA. Besides the upper-air assimilation developments, a simplified extended Kalman filter (SEKF) was also tested for surface data assimilation, showing promising performance on both the analyses and the forecasts of AROME/HU system.

scholarly journals On the relationship between wind observation accuracy and the ascending node of sun-synchronous orbit for the Aeolus-type spaceborne Doppler wind lidar

2020 ◽  
Author(s):  
Chuanliang Zhang ◽  
Xuejin Sun ◽  
Wen Lu ◽  
Yingni Shi ◽  
Naiying Dou ◽  
...  
Keyword(s):  
Laser Pulse ◽  
Pulse Energy ◽  
Laser Pulse Energy ◽  
Weather Prediction ◽  
The Sun ◽  
Wind Observation ◽  
Wind Lidar ◽  
The Impact ◽  
The Relationship ◽  
Doppler Wind Lidar

Abstract. The launch and operation of first spaceborne Doppler wind lidar (DWL) Aeolus is of great significance in observing global wind field. Aeolus operates on the sun-synchronous dawn-dusk orbit to minimize the negative impact of solar background radiation (SBR) on wind observation accuracy. For that the future spaceborne DWLs may not operate on sun-synchronous dawn-dusk orbits due to their observation purposes, the impact of the local time of ascending node (LTAN) crossing of sun-synchronous orbits on the wind observation accuracy was studied in this paper by proposing two added Aeolus-type spaceborne DWLs operated on the sun-synchronous orbits with LTAN of 15:00 and 12:00 combined with Aeolus. On the two new orbits, the increments of averaged SBR received by the new spaceborne DWLs range from 39 to 56 mW m−2 sr−1 nm−1 under clear skies, which will lead to the increment of averaged wind observation uncertainties from 0.3 to 0.4 m/s in the troposphere and from 0.9 to 1.4 m/s in the stratosphere. Increasing laser pulse energy of the new spaceborne DWLs is used to lower the wind observation uncertainties. Furthermore, a method to quantitatively design the laser pulse energy according to specific accuracy requirements is given in this paper based on the relationship between the signal noise ratio and the uncertainty of response function of Rayleigh channel of Aeolus-type spaceborne DWLs. The laser pulse energy of the two new spaceborne DWLs is set to 80 mJ based on the statistical results according to the method, meanwhile other instrument parameters are the same as those of Aeolus. Based on the parameter proposal, the accuracy of above 85 % bins of the new spaceborne DWLs would meet the accuracy requirements of European Space Agency (ESA) for Aeolus, which would improve the forecast results of Numerical Weather Prediction. And the averaged observation uncertainties show the high consistence in observation accuracy of the three spaceborne DWLs, which can be used for joint observation.

Variational Assimilation of Cloud Liquid/Ice Water Path and Its Impact on NWP

2015 ◽  
Vol 54 (8) ◽  
pp. 1809-1825 ◽  
Author(s):  
Yaodeng Chen ◽  
Hongli Wang ◽  
Jinzhong Min ◽  
Xiang-Yu Huang ◽  
Patrick Minnis ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Liquid Water ◽  
Weather Prediction ◽  
Wrf Model ◽  
Liquid Water Path ◽  
Cloud Liquid Water ◽  
Water Path ◽  
Ice Water Path ◽  
Ice Water ◽  
The Impact

AbstractAnalysis of the cloud components in numerical weather prediction models using advanced data assimilation techniques has been a prime topic in recent years. In this research, the variational data assimilation (DA) system for the Weather Research and Forecasting (WRF) Model (WRFDA) is further developed to assimilate satellite cloud products that will produce the cloud liquid water and ice water analysis. Observation operators for the cloud liquid water path and cloud ice water path are developed and incorporated into the WRFDA system. The updated system is tested by assimilating cloud liquid water path and cloud ice water path observations from Global Geostationary Gridded Cloud Products at NASA. To assess the impact of cloud liquid/ice water path data assimilation on short-term regional numerical weather prediction (NWP), 3-hourly cycling data assimilation and forecast experiments with and without the use of the cloud liquid/ice water paths are conducted. It is shown that assimilating cloud liquid/ice water paths increases the accuracy of temperature, humidity, and wind analyses at model levels between 300 and 150 hPa after 5 cycles (15 h). It is also shown that assimilating cloud liquid/ice water paths significantly reduces forecast errors in temperature and wind at model levels between 300 and 150 hPa. The precipitation forecast skills are improved as well. One reason that leads to the improved analysis and forecast is that the 3-hourly rapid update cycle carries over the impact of cloud information from the previous cycles spun up by the WRF Model.

scholarly journals Dynamical and Physical Processes Leading to Tropical Cyclone Intensification under Upper-Level Trough Forcing

2013 ◽  
Vol 70 (8) ◽  
pp. 2547-2565 ◽  
Author(s):  
Marie-Dominique Leroux ◽  
Matthieu Plu ◽  
David Barbary ◽  
Frank Roux ◽  
Philippe Arbogast
Keyword(s):  
Angular Momentum ◽  
Tropical Cyclone ◽  
Potential Vorticity ◽  
Weather Prediction ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
Thick Layer ◽  
Limited Area ◽  
Southwest Indian Ocean ◽  
Upper Level

Abstract The rapid intensification of Tropical Cyclone (TC) Dora (2007, southwest Indian Ocean) under upper-level trough forcing is investigated. TC–trough interaction is simulated using a limited-area operational numerical weather prediction model. The interaction between the storm and the trough involves a coupled evolution of vertical wind shear and binary vortex interaction in the horizontal and vertical dimensions. The three-dimensional potential vorticity structure associated with the trough undergoes strong deformation as it approaches the storm. Potential vorticity (PV) is advected toward the tropical cyclone core over a thick layer from 200 to 500 hPa while the TC upper-level flow turns cyclonic from the continuous import of angular momentum. It is found that vortex intensification first occurs inside the eyewall and results from PV superposition in the thick aforementioned layer. The main pathway to further storm intensification is associated with secondary eyewall formation triggered by external forcing. Eddy angular momentum convergence and eddy PV fluxes are responsible for spinning up an outer eyewall over the entire troposphere, while spindown is observed within the primary eyewall. The 8-km-resolution model is able to reproduce the main features of the eyewall replacement cycle observed for TC Dora. The outer eyewall intensifies further through mean vertical advection under dynamically forced upward motion. The processes are illustrated and quantified using various diagnostics.

scholarly journals Impact of Four-Dimensional Variational Data Assimilation of Atmospheric Motion Vectors on Tropical Cyclone Track Forecasts

2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
Mesoscale Model ◽  
State University ◽  
Motion Vectors ◽  
Geostationary Meteorological Satellite ◽  
Atmospheric Motion ◽  
Atmospheric Motion Vectors ◽  
Data Assimilation Technique ◽  
The Impact

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.

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