The Impact of Surface Wind Data Assimilation on the Predictability of Near-Surface Plume Advection in the Case of the Fukushima Nuclear Accident

Abstract In this paper, the Weather Research and Forecasting (WRF) Model with the three-dimensional variational data assimilation (WRF-3DVAR) system is used to investigate the impact on the near-surface wind forecast of assimilating both conventional data and Advanced Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (ATOVS) radiances compared with assimilating conventional data only. The results show that the quality of the initial field and the forecast performance of wind in the lower atmosphere are improved in both assimilation cases. Assimilation results capture the spatial distribution of the wind speed, and the observation data assimilation has a positive effect on near-surface wind forecasts. Although the impacts of assimilating ATOVS radiances on near-surface wind forecasts are limited, the fine structure of local weather systems illustrated by the WRF-3DVAR system suggests that assimilating ATOVS radiances has a positive effect on the near-surface wind forecast under conditions that ATOVS radiances in the initial condition are properly amplified. Assimilating conventional data is an effective approach for improving the forecast of the near-surface wind.

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The Impact of Aircraft Dropsonde and Satellite Wind Data on Numerical Simulations of Two Landfalling Tropical Storms during the Tropical Cloud Systems and Processes Experiment

Weather and Forecasting ◽

10.1175/2007waf2007006.1 ◽

2008 ◽

Vol 23 (1) ◽

pp. 62-79 ◽

Cited By ~ 42

Author(s):

Zhaoxia Pu ◽

Xuanli Li ◽

Christopher S. Velden ◽

Sim D. Aberson ◽

W. Timothy Liu

Keyword(s):

High Resolution ◽

Tropical Cyclone ◽

Data Assimilation ◽

Wrf Model ◽

Wind Data ◽

Tropical Storms ◽

Track Forecast ◽

Near Surface ◽

Cloud Systems ◽

The Impact

Abstract Dropwindsonde, Geostationary Operational Environmental Satellite-11 (GOES-11) rapid-scan atmospheric motion vectors, and NASA Quick Scatterometer (QuikSCAT) near-surface wind data collected during NASA’s Tropical Cloud Systems and Processes (TCSP) field experiment in July 2005 were assimilated into an advanced research version of the Weather Research and Forecasting (WRF) model using its three-dimensional variational data assimilation (3DVAR) system. The impacts of the mesoscale data assimilation on WRF numerical simulation of Tropical Storms Cindy and Gert (2005) near landfall are examined. Sensitivity of the forecasts to the assimilation of each single data type is investigated. Specifically, different 3DVAR strategies with different analysis update cycles and resolutions are compared in order to identify the better methodology for assimilating the data from research aircraft and satellite for tropical cyclone study. The results presented herein indicate the following. 1) Assimilation of dropwindsonde and satellite wind data into the WRF model improves the forecasts of the two tropical storms up to the landfall time. The QuikSCAT wind information is very important for improving the storm track forecast, whereas the dropwindsonde and GOES-11 wind data are also necessary for improved forecasts of intensity and precipitation. 2) Data assimilation also improves the quantitative precipitation forecasts (QPFs) near landfall of the tropical storms. 3) A 1-h rapid-update analysis cycle at high resolution (9 km) provides more accurate tropical cyclone forecasts than a regular 6-h analysis cycle at coarse (27 km) resolution. The high-resolution rapidly updated 3DVAR analysis cycle might be a practical way to assimilate the data collected from tropical cyclone field experiments.

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Impact of Satellite Data Assimilation in Atmospheric Reanalysis on the Marine Wind and Wave Climate

Journal of Climate ◽

10.1175/jcli-d-16-0056.1 ◽

2016 ◽

Vol 29 (17) ◽

pp. 6351-6361 ◽

Cited By ~ 3

Author(s):

Wataru Sasaki

Keyword(s):

Wind Speed ◽

Data Assimilation ◽

Southern Ocean ◽

Satellite Data ◽

North Pacific ◽

Surface Wind ◽

Surface Wind Speed ◽

Surface Winds ◽

Near Surface ◽

The Impact

Abstract This study investigated the impact of assimilating satellite data into atmospheric reanalyses on trends in ocean surface winds and waves. Two experiments were performed using a numerical wave model forced by near-surface winds: one derived from the Japanese 55-year Reanalysis (JRA-55; experiment A) and the other derived from JRA-55 using assimilated conventional observations only (JRA-55C; experiment B). The results showed that the satellite data assimilation reduced upward trends of the annual mean of wave energy flux (WEF) in the midlatitude North Pacific and southern ocean (30°–60°S), south of Australia, from 1959 to 2012. It was also found that the assimilation of scatterometer winds reduced the near-surface wind speed in the midlatitude North Pacific after the mid-1990s, which resulted in the reduced trend in WEF from 1959 to 2012. By contrast, assimilation of the satellite radiances for 1973–94 increased near-surface wind speed in the southern ocean, south of Australia, whereas the assimilation of the scatterometer winds after the mid-1990s reduced wind speed. The latter led to the reduced trend in WEF south of Australia from 1959 to 2012.

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Evaluation of HRCLDAS and ERA5 Datasets for Near-Surface Wind over Hainan Island and South China Sea

Atmosphere ◽

10.3390/atmos12060766 ◽

2021 ◽

Vol 12 (6) ◽

pp. 766

Author(s):

Yi Jiang ◽

Shuai Han ◽

Chunxiang Shi ◽

Tao Gao ◽

Honghui Zhen ◽

...

Keyword(s):

South China Sea ◽

South China ◽

Surface Wind ◽

Hainan Island ◽

The South China Sea ◽

Wind Data ◽

The South ◽

Near Surface ◽

China Sea

Near-surface wind data are particularly important for Hainan Island and the South China Sea, and there is a wide range of wind data sources. A detailed understanding of the reliability of these datasets can help us to carry out related research. In this study, the hourly near-surface wind data from the High-Resolution China Meteorological Administration (CMA) Land Data Assimilation System (HRCLDAS) and the fifth-generation ECMWF atmospheric reanalysis data (ERA5) were evaluated by comparison with the ground automatic meteorological observation data for Hainan Island and the South China Sea. The results are as follows: (1) the HRCLDAS and ERA5 near-surface wind data trend was basically the same as the observation data trend, but there was a smaller bias, smaller root-mean-square errors, and higher correlation coefficients between the near-surface wind data from HRCLDAS and the observations; (2) the quality of HRCLDAS and ERA5 near-surface wind data was better over the islands of the South China Sea than over Hainan Island land. However, over the coastal areas of Hainan Island and island stations near Sansha, the quality of the HRCLDAS near-surface wind data was better than that of ERA5; (3) the quality of HRCLDAS near-surface wind data was better than that of ERA5 over different types of landforms. The deviation of ERA5 and HRCLDAS wind speed was the largest along the coast, and the quality of the ERA5 wind direction data was poorest over the mountains, whereas that of HRCLDAS was poorest over hilly areas; (4) the accuracy of HRCLDAS at all wind levels was higher than that of ERA5. ERA5 significantly overestimated low-grade winds and underestimated high-grade winds. The accuracy of HRCLDAS wind ratings over the islands of the South China Sea was significantly higher than that over Hainan Island land, especially for the higher wind ratings; and (5) in the typhoon process, the simulation of wind by HRCLDAS was closer to the observations, and its simulation of higher wind speeds was more accurate than the ERA5 simulations.

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Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0083.1 ◽

2020 ◽

Vol 21 (12) ◽

pp. 2829-2853 ◽

Cited By ~ 1

Author(s):

Marouane Temimi ◽

Ricardo Fonseca ◽

Narendra Nelli ◽

Michael Weston ◽

Mohan Thota ◽

...

Keyword(s):

Eddy Covariance ◽

Soil Texture ◽

Land Surface ◽

Surface Wind ◽

Surface Fluxes ◽

Abu Dhabi ◽

Horizontal Wind ◽

Cold Bias ◽

Near Surface ◽

The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

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The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales

Hydrology and Earth System Sciences ◽

10.5194/hess-19-4831-2015 ◽

2015 ◽

Vol 19 (12) ◽

pp. 4831-4844 ◽

Cited By ~ 19

Author(s):

C. Draper ◽

R. Reichle

Keyword(s):

Soil Moisture ◽

Data Assimilation ◽

Surface Soil ◽

Root Zone ◽

Surface Model ◽

Surface Soil Moisture ◽

Near Surface ◽

In Situ Observations ◽

The Impact

Abstract. A 9 year record of Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E) soil moisture retrievals are assimilated into the Catchment land surface model at four locations in the US. The assimilation is evaluated using the unbiased mean square error (ubMSE) relative to watershed-scale in situ observations, with the ubMSE separated into contributions from the subseasonal (SMshort), mean seasonal (SMseas), and inter-annual (SMlong) soil moisture dynamics. For near-surface soil moisture, the average ubMSE for Catchment without assimilation was (1.8 × 10−3 m3 m−3)2, of which 19 % was in SMlong, 26 % in SMseas, and 55 % in SMshort. The AMSR-E assimilation significantly reduced the total ubMSE at every site, with an average reduction of 33 %. Of this ubMSE reduction, 37 % occurred in SMlong, 24 % in SMseas, and 38 % in SMshort. For root-zone soil moisture, in situ observations were available at one site only, and the near-surface and root-zone results were very similar at this site. These results suggest that, in addition to the well-reported improvements in SMshort, assimilating a sufficiently long soil moisture data record can also improve the model representation of important long-term events, such as droughts. The improved agreement between the modeled and in situ SMseas is harder to interpret, given that mean seasonal cycle errors are systematic, and systematic errors are not typically targeted by (bias-blind) data assimilation. Finally, the use of 1-year subsets of the AMSR-E and Catchment soil moisture for estimating the observation-bias correction (rescaling) parameters is investigated. It is concluded that when only 1 year of data are available, the associated uncertainty in the rescaling parameters should not greatly reduce the average benefit gained from data assimilation, although locally and in extreme years there is a risk of increased errors.

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Field measurements of windbreak effects on airflow, turbulent exchanges and microclimates

Australian Journal of Experimental Agriculture ◽

10.1071/ea02004 ◽

2002 ◽

Vol 42 (6) ◽

pp. 665 ◽

Cited By ~ 19

Author(s):

H. A. Cleugh

Keyword(s):

Wind Speed ◽

Water Vapour ◽

Incident Angle ◽

Surface Wind ◽

Field Measurements ◽

Experimental Program ◽

Near Surface ◽

Speed Reduction ◽

Temperature And Humidity ◽

The Impact

While there has been considerable research into airflow around windbreaks, the interaction of this airflow with the exchanges of heat and water vapour has received far less attention. Yet, the effects of windbreaks on microclimates, water use and agricultural productivity depend, in part, on this interaction. A field and wind tunnel experimental program was conducted to quantify the effects of windbreaks on microclimates and evaporation fluxes. This paper describes the field measurements, which were conducted over a 6-week period at a tree windbreak site located in undulating terrain in south-east Australia. The expected features of airflow around porous windbreaks were observed despite the less than ideal nature of the site. As predicted from theory, the air temperature and humidity were elevated, by day, in the quiet zone and the location of the peak increase in temperature and humidity coincided with the location of the minimum wind speed. However, this increase in temperature and humidity was small in size and restricted to the zone within 10 windbreak heights (H) of the windbreak. This pattern contrasts with that for the near surface wind speeds, which were reduced by up to 80% in a sheltered zone that extended from 5 H upwind to over 25 H downwind of the windbreak. Similar differences were found between the turbulent scalar (heat, water vapour) and velocity terms. While both are reduced in the quiet zone, the turbulent scalar terms near the surface were substantially enhanced at the location where the wake zone begins. Here the mean wind speed is reduced by 50% and the turbulent velocity terms return to their upwind values. Wind speed reductions varied linearly with [cos (90 – α)], where α is the incident angle of the wind, for sites located 6 H downwind. This means that the spatial pattern of wind speed reduction applies to all wind directions, provided that distance downwind is expressed in terms of streamwise distance. However, shelter in the near-break region is slightly increased as the wind blows more obliquely towards the windbreak. The atmospheric demand in the quiet zone was reduced when the humidity of the upwind air was low. In such conditions, windbreaks can 'protect' growing crops from the impact of dry air with high atmospheric demand. The corollary is that in humid conditions, the atmospheric demand in the quiet zone can be increased as a result of shelter.

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Assessing Sensitivity of Observations in Source Term Estimation for Nuclear Accidents

Volume 2: Plant Systems, Structures, and Components; Safety and Security; Next Generation Systems; Heat Exchangers and Cooling Systems ◽

10.1115/icone20-power2012-54491 ◽

2012 ◽

Author(s):

Yuanwei Ma ◽

Dezhong Wang ◽

Wenji Tan ◽

Zhilong Ji ◽

Kuo Zhang

Keyword(s):

Data Assimilation ◽

Source Term ◽

Dynamic Models ◽

Source Parameters ◽

Nuclear Accident ◽

Fukushima Nuclear Accident ◽

Observation Data ◽

Source Terms ◽

Highly Nonlinear ◽

Assimilation System

In the Fukushima nuclear accident, due to the lack of field observations and the complexity of source terms, researchers failed to estimate the source term accurately immediately. Data assimilation methods to estimate source terms have many good features: they works well with highly nonlinear dynamic models, no linearization in the evolution of error statistics, etc. This study built a data assimilation system using the ensemble Kalman Filter for real-time estimates of source parameters. The assimilation system uses a Gaussian puff model as the atmospheric dispersion model, assimilating forward with the observation data. Considering measurement error, numerical experiments were carried on to verify the stability and accuracy of the scheme. Then the sensitivity of observation configration is tested by the twin experiments. First, the single parameter release rate of the source term is estimated by different sensor grid configurations. In a sparse sensors grid, the error of estimation is about 10%, and in a 11*11 grid configuration, the error is less than 1%. Under the analysis of the Fukushima nuclear accident, ahead for the actual situation, four parameters are estimated at the same time, by 2*2 to 11*11 grid configurations. The studies showed that the radionuclides plume should cover as many sensors as possible, which will lead a to successful estimation.

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Prediction of Tornado-Like Vortex (TLV) Embedded in the 8 May 2003 Oklahoma City Tornadic Supercell Initialized from the Subkilometer Grid Spacing Analysis Produced by the Dual-Resolution GSI-Based EnVar Data Assimilation System

Monthly Weather Review ◽

10.1175/mwr-d-19-0179.1 ◽

2020 ◽

Vol 148 (7) ◽

pp. 2909-2934

Author(s):

Yongming Wang ◽

Xuguang Wang

Keyword(s):

Data Assimilation ◽

Initial Conditions ◽

Potential Temperature ◽

Intensity Variation ◽

Oklahoma City ◽

Grid Spacing ◽

Near Surface ◽

Low Level ◽

Cold Pools ◽

The Impact

Abstract Explicit forecasts of a tornado-like vortex (TLV) require subkilometer grid spacing because of their small size. Most previous TLV prediction studies started from interpolated kilometer grid spacing initial conditions (ICs) rather than subkilometer grid spacing ICs. The tornadoes embedded in the 8 May 2003 Oklahoma City tornadic supercell are used to understand the impact of IC resolution on TLV predictions. Two ICs at 500-m and 2-km grid spacings are, respectively, produced through an efficient dual-resolution (DR) and a single-coarse-resolution (SCR) EnVar ingesting a 2-km ensemble. Both experiments launch 1-h forecasts at 500-m grid spacing. Diagnostics of data assimilation (DA) cycling reveal DR produces stronger and broader rear-flank cold pools, more intense downdrafts and updrafts with finer scales, and more hydrometeors at high altitudes through accumulated differences between two DA algorithms. Relative differences in DR, compared to SCR, include the integration from higher-resolution analyses, the update for higher-resolution backgrounds, and the propagation of ensemble perturbations along higher-resolution model trajectory. Predictions for storm morphology and cold pools are more realistic in DR than in SCR. The DR-TLV tracks match better with the observed tornado tracks than SCR-TLV in timing of intensity variation, and in duration. Additional experiments suggest 1) the analyzed kinematic variables strongly influence timing of intensity variation through affecting both low-level rear-flank outflow and midlevel updraft; 2) potential temperature analysis by DR extends the second track’s duration consistent with enhanced low-level stretching, delayed broadening large-scale downdraft, and (or) increased near-surface baroclinic vorticity supply; and 3) hydrometeor analyses have little impact on TLV predictions.

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Visual Communication in Times of Crisis: The Fukushima Nuclear Accident

Leonardo ◽

10.1162/leon_a_00276 ◽

2012 ◽

Vol 45 (2) ◽

pp. 113-118 ◽

Cited By ~ 2

Author(s):

Rama C. Hoetzlein

Keyword(s):

News Media ◽

Visual Communication ◽

Large Data ◽

Nuclear Accident ◽

Large Data Sets ◽

Fukushima Nuclear Accident ◽

Data Sets ◽

On Line ◽

The Impact ◽

Information Aesthetics

This paper follows the development of visual communication through information visualization in the wake of the Fukushima nuclear accident in Japan. While information aesthetics are often applied to large data sets retrospectively, the author developed new works concurrently with an ongoing crisis to examine the impact and social aspects of visual communication while events continued to unfold. The resulting work, Fukushima Nuclear Accident—Radiation Comparison Map, is a reflection of rapidly acquired data, collaborative on-line analysis and reflective criticism of contemporary news media, resolved into a coherent picture through the participation of an on-line community.

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