scholarly journals Opportunistic sensing with recreational hot-air balloon flights

2020 ◽  
pp. 1
Author(s):  
Evert I.F. de Bruijn ◽  
Fred C. Bosveld ◽  
Siebren de Haan ◽  
Albert A.M. Holtslag
Keyword(s):  
Positive Impact ◽  
Weather Prediction ◽  
Third Party ◽  
Wind Profiler ◽  
Meteorological Tower ◽  
Mountain Valley ◽  
Hot Air ◽  
Wind Measurements ◽  
New Type ◽  
Nwp Model

AbstractWe report about a new third party observation, namely wind measurements derived from Hot-Air Balloon (HAB) tracks. At first we compare the HAB winds with wind measurements from a meteorological tower and a radio acoustic wind profiler, both situated at the topographically flat Cabauw observatory in the Netherlands. To explore the potential of this new type of wind observation in other topographies, we present an intriguing HAB flight in Austria with a spectacular mountain-valley circulation. Subsequently, we compare the HAB data with a Numerical Weather Prediction (NWP) model during 2011-2013 and the standard deviation of the wind speed is 2.3 ms−1. Finally we show results from a data-assimilation feasibility experiment that reveals that HAB wind information can have a positive impact on a hindcasted NWP trajectory.

The POWER Experiment: Impact of Assimilation of a Network of Coastal Wind Profiling Radars on Simulating Offshore Winds in and above the Wind Turbine Layer

2016 ◽  
Vol 31 (4) ◽  
pp. 1071-1091 ◽  
Author(s):  
Irina V. Djalalova ◽  
Joseph Olson ◽  
Jacob R. Carley ◽  
Laura Bianco ◽  
James M. Wilczak ◽  
...  
Keyword(s):  
New England ◽  
Gulf Of Maine ◽  
Negative Impact ◽  
Positive Impact ◽  
Weather Prediction ◽  
Department Of Energy ◽  
Offshore Wind ◽  
Model Skill ◽  
Nwp Model ◽  
The Impact

Abstract During the summer of 2004 a network of 11 wind profiling radars (WPRs) was deployed in New England as part of the New England Air Quality Study (NEAQS). Observations from this dataset are used to determine their impact on numerical weather prediction (NWP) model skill at simulating coastal and offshore winds through data-denial experiments. This study is a part of the Position of Offshore Wind Energy Resources (POWER) experiment, a Department of Energy (DOE) sponsored project that uses National Oceanic and Atmospheric Administration (NOAA) models for two 1-week periods to measure the impact of the assimilation of observations from 11 inland WPRs. Model simulations with and without assimilation of the WPR data are compared at the locations of the inland WPRs, as well as against observations from an additional WPR and a high-resolution Doppler lidar (HRDL) located on board the Research Vessel Ronald H. Brown (RHB), which cruised the Gulf of Maine during the NEAQS experiment. Model evaluation in the lowest 2 km above the ground shows a positive impact of the WPR data assimilation from the initialization time through the next five to six forecast hours at the WPR locations for 12 of 15 days analyzed, when offshore winds prevailed. A smaller positive impact at the RHB ship track was also confirmed. For the remaining three days, during which time there was a cyclone event with strong onshore wind flow, the assimilation of additional observations had a negative impact on model skill. Explanations for the negative impact are offered.

From InSAR derived relative tropospheric Slant Total Delay maps to absolute Zenith Total Delay maps: comparisons between tropospheric delay products to define a strategy for meteorological applications.

2020 ◽  
Author(s):  
Stefano Barindelli ◽  
Andrea Gatti ◽  
Martina Lagasio ◽  
Marco Manzoni ◽  
Alessandra Mascitelli ◽  
...  
Keyword(s):  
Positive Impact ◽  
Weather Prediction ◽  
Circulation Model ◽  
Tropospheric Delay ◽  
Total Delay ◽  
Zenith Total Delay ◽  
Iterative Interpolation ◽  
Physically Based ◽  
The Difference ◽  
Nwp Model

<p>InSAR derived Atmospheric Phase Screens (APSs) contain the difference between the atmospheric delay along the SAR sensor line-of-sight of two acquisition epochs: the slave and the master epochs. Using estimates of the atmospheric state at the master epoch, coming from independent sources, the APSs can be transformed into maps of tropospheric Zenith Total Delay (ZTD), that is related to the columnar atmospheric water vapor content. Assimilation experiments of such products into numerical weather prediction (NWP) models have shown a positive impact in the prediction of convective storms.</p><p>In this work, a systematical comparison between various APS and ZTD products aims at determining the optimal procedure to go from APSs to InSAR-derived absolute ZTD maps, i.e. to estimate the master delay map. Two different approaches are compared.</p><p>The first is based on a stack of ZTD maps produced with the assimilation of GNSS ZTD observations into an NWP model. This acts as a physically based interpolator of the GNSS values, which have a spatial resolution much coarser than the InSAR APS one.</p><p>The second is based on a stack of ZTD maps derived by an Iterative Tropospheric Decomposition (ITD) model, as implemented in the GACOS service. In this case, the high-resolution ZTD maps are obtained by an iterative interpolation of a global atmospheric circulation model values and GNSS values where available.</p><p>The results of the comparisons and sensitivity tests on the number of ZTD maps needed to derive the unknown master delay map are shown.</p><p> </p><p> </p><p> </p><p><strong> </strong></p><p><strong> </strong></p>

Assimilation of Multinational Radar Reflectivity Data in a Mesoscale Model: A Proof of Concept

2017 ◽  
Vol 56 (6) ◽  
pp. 1739-1751 ◽  
Author(s):  
Martin Ridal ◽  
Mats Dahlbom
Keyword(s):  
Mesoscale Model ◽  
Positive Impact ◽  
Weather Prediction ◽  
Radar Reflectivity ◽  
Proof Of Concept ◽  
Volume Data ◽  
Radar Observations ◽  
Set Up ◽  
Nwp Model ◽  
Reflectivity Data

AbstractRadar reflectivity observations have proven to be beneficial for improving the skill of numerical weather prediction (NWP) models. A few countries around the world use radar reflectivity observations in their operational runs. The majority of experiments and usage are still only including the local radar observations from the country in which the forecasts are made. The model domains, on the other hand, cover areas far greater than this, and therefore observations from surrounding countries need to be included. As of today there is no central collection and redistribution of volume data in Europe. In recent years, there has been an initiative to collect and harmonize European radar observations, but the redistribution of data for this purpose has only been of centrally constructed composites. This study describes the efforts to collect volume reflectivity data from several data providers and make them available for use in an NWP model. A preprocessing of the reflectivity data has been set up to handle the different incoming data and to make a first data reduction for the NWP models to be able to include the new observations. Assimilation experiments have been performed that prove it is possible to assimilate operational radar reflectivity data from several countries, with a neutral to positive impact.

scholarly journals Global Forecast Impact of Low Data Latency Infrared and Microwave Sounders Observations from Polar Orbiting Satellites

2020 ◽  
Vol 12 (14) ◽  
pp. 2193
Author(s):  
Young-Chan Noh ◽  
Agnes H. N. Lim ◽  
Hung-Lung Huang ◽  
Mitchell D. Goldberg
Keyword(s):  
Positive Impact ◽  
Weather Prediction ◽  
Surface Wind ◽  
Atmospheric Temperature ◽  
Time Frame ◽  
Satellite Measurements ◽  
The World ◽  
Nwp Model ◽  
Environmental Prediction ◽  
Data Latency

The Direct Broadcast Network (DBNet) provides near-real-time delivery of low-earth-orbiting (LEO) meteorological satellites to operational numerical weather prediction (NWP) systems that need short data cut-off times to allow for the assimilation of the most recent satellite measurements. The NWP model requires timely delivery of observations including atmospheric temperature, humidity, and surface wind vectors. The World Meteorological Organization (WMO) Space Program (WSP) recommends the data latency of no more than 20 min for the satellite measurements. Currently, not all DBNet stations are delivering satellite data within the 20-min time frame. In this study, the forecast impact of the observations of LEO satellite sounders with data latency of 20 min or less was evaluated using the National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS). Reducing the data latency up to 5 min increases the number of LEO infrared (IR) and microwave (MW) sounder observations delivered to the NCEP GFS data assimilation system by more than 20%. Overall, this study demonstrates a positive impact on the global weather forecasts when the IR and MW sounder data are delivered by 20 min anywhere in the world. Additional forecast benefits are not obvious for shorter data latency. Results from this study support the WSP recommendation of 20–minute data latency.

scholarly journals Use of Microwave Radiances from Metop-C and Fengyun-3 C/D Satellites for a Northern European Limited-area Data Assimilation System

2021 ◽  
Author(s):  
Magnus Lindskog ◽  
Adam Dybbroe ◽  
Roger Randriamampianina
Keyword(s):  
Data Assimilation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Implementation Process ◽  
Satellite System ◽  
Limited Area ◽  
Global Navigation Satellite ◽  
Microwave Radiances ◽  
Data Assimilation System ◽  
Assimilation System

AbstractMetCoOp is a Nordic collaboration on operational Numerical Weather Prediction based on a common limited-area km-scale ensemble system. The initial states are produced using a 3-dimensional variational data assimilation scheme utilizing a large amount of observations from conventional in-situ measurements, weather radars, global navigation satellite system, advanced scatterometer data and satellite radiances from various satellite platforms. A version of the forecasting system which is aimed for future operations has been prepared for an enhanced assimilation of microwave radiances. This enhanced data assimilation system will use radiances from the Microwave Humidity Sounder, the Advanced Microwave Sounding Unit-A and the Micro-Wave Humidity Sounder-2 instruments on-board the Metop-C and Fengyun-3 C/D polar orbiting satellites. The implementation process includes channel selection, set-up of an adaptive bias correction procedure, and careful monitoring of data usage and quality control of observations. The benefit of the additional microwave observations in terms of data coverage and impact on analyses, as derived using the degree of freedom of signal approach, is demonstrated. A positive impact on forecast quality is shown, and the effect on the precipitation for a case study is examined. Finally, the role of enhanced data assimilation techniques and adaptions towards nowcasting are discussed.

scholarly journals Evaluation of Operational Monsoon Moisture Surveillance and Severe Weather Prediction Utilizing COSMIC-2/FORMOSAT-7 Radio Occultation Observations

2021 ◽  
Vol 13 (15) ◽  
pp. 2979
Author(s):  
Yu-Chun Chen ◽  
Chih-Chien Tsai ◽  
Yi-Chao Wu ◽  
An-Hsiang Wang ◽  
Chieh-Ju Wang ◽  
...  
Keyword(s):  
Numerical Model ◽  
Data Assimilation ◽  
Water Resource Management ◽  
Radio Occultation ◽  
Positive Impact ◽  
Weather Prediction ◽  
Severe Weather ◽  
Model Experiments ◽  
Typhoon Structure ◽  
Numerical Model Experiments

Operational monsoon moisture surveillance and severe weather prediction is essential for timely water resource management and disaster risk reduction. For these purposes, this study suggests a moisture indicator using the COSMIC-2/FORMOSAT-7 radio occultation (RO) observations and evaluates numerical model experiments with RO data assimilation. The RO data quality is validated by a comparison between sampled RO profiles and nearby radiosonde profiles around Taiwan prior to the experiments. The suggested moisture indicator accurately monitors daily moisture variations in the South China Sea and the Bay of Bengal throughout the 2020 monsoon rainy season. For the numerical model experiments, the statistics of 152 moisture and rainfall forecasts for the 2020 Meiyu season in Taiwan show a neutral to slightly positive impact brought by RO data assimilation. A forecast sample with the most significant improvement reveals that both thermodynamic and dynamic fields are appropriately adjusted by model integration posterior to data assimilation. The statistics of 17 track forecasts for typhoon Hagupit (2020) also show the positive effect of RO data assimilation. A forecast sample reveals that the member with RO data assimilation simulates better typhoon structure and intensity than the member without, and the effect can be larger and faster via multi-cycle RO data assimilation.

scholarly journals Analysis of User Needs on Downloading Behavior of English Vocabulary APPs Based on Data Mining for Online Comments

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1341
Author(s):  
Tinggui Chen ◽  
Lijuan Peng ◽  
Jianjun Yang ◽  
Guodong Cong
Keyword(s):  
Negative Impact ◽  
Positive Impact ◽  
User Needs ◽  
User Requirements ◽  
Functional Requirements ◽  
User Comments ◽  
Online Comments ◽  
Significant Negative Impact ◽  
Negative Effect ◽  
New Type

With highly developed social media, English learning Applications have become a new type of mobile learning resources, and online comments posted by users after using them have not only become an important source of intellectual competition for enterprises, but can also help understand customers’ requirements, thereby improving product functionalities and service quality, and solve the pain points of product iteration and innovation. Based on this, this paper crawled the online user comments of three typical APPs (BaiCiZhan, MoMoBeiDanCi and BuBeiDanCi), through emotion analysis and hotspot mining technology, to obtain user requirements and then the K-means clustering method was used to analyze user requirements. Finally, quantile regression is used to find out which user needs have an impact on the downloads of English vocabulary APPs. The results show that: (1) Positive comments have a more significant impact on users’ downloads behavior than negative online comments. (2) English vocabulary APPs with higher downloads, both the 5-star user ratings and the increase of emotional requirement have a negative effect on the increase in APP downloads, while the enterprise’s service requirement improvement has a positive effect on the increase of APP downloads. (3) Regarding English vocabulary APPs with average or high downloads, improving the adaptability and Appearance requirements have significant negative impact on downloads. (4) The functional requirements to improve products will have a significant positive impact on the increase in downloads of English vocabulary APPs.

scholarly journals Implementation of a 3-D-Var system for atmospheric profiling data assimilation into the RAMS model: initial results

2013 ◽  
Vol 6 (2) ◽  
pp. 3581-3610
Author(s):  
S. Federico
Keyword(s):  
Relative Humidity ◽  
Data Assimilation ◽  
Initial Conditions ◽  
Weather Prediction ◽  
Wind Profiler ◽  
Short Term ◽  
Recursive Filters ◽  
Data Assimilation System ◽  
Rams Model ◽  
Assimilation System

Abstract. This paper presents the current status of development of a three-dimensional variational data assimilation system. The system can be used with different numerical weather prediction models, but it is mainly designed to be coupled with the Regional Atmospheric Modelling System (RAMS). Analyses are given for the following parameters: zonal and meridional wind components, temperature, relative humidity, and geopotential height. Important features of the data assimilation system are the use of incremental formulation of the cost-function, and the use of an analysis space represented by recursive filters and eigenmodes of the vertical background error matrix. This matrix and the length-scale of the recursive filters are estimated by the National Meteorological Center (NMC) method. The data assimilation and forecasting system is applied to the real context of atmospheric profiling data assimilation, and in particular to the short-term wind prediction. The analyses are produced at 20 km horizontal resolution over central Europe and extend over the whole troposphere. Assimilated data are vertical soundings of wind, temperature, and relative humidity from radiosondes, and wind measurements of the European wind profiler network. Results show the validity of the analysis solutions because they are closer to the observations (lower RMSE) compared to the background (higher RMSE), and the differences of the RMSEs are consistent with the data assimilation settings. To quantify the impact of improved initial conditions on the short-term forecast, the analyses are used as initial conditions of a three-hours forecast of the RAMS model. In particular two sets of forecasts are produced: (a) the first uses the ECMWF analysis/forecast cycle as initial and boundary conditions; (b) the second uses the analyses produced by the 3-D-Var scheme as initial conditions, then is driven by the ECMWF forecast. The improvement is quantified by considering the horizontal components of the wind, which are measured at a-synoptic times by the European wind profiler network. The results show that the RMSE is effectively reduced at the short range (1–2 h). The results are in agreement with the set-up of the numerical experiment.

UTCI as the NWP model ALADIN (CHMI) output – first experiences

2021 ◽  
Vol 94 (2) ◽  
pp. 237-249
Author(s):  
Martin Novák
Keyword(s):  
Numerical Weather Prediction ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Climate Index ◽  
Basic Information ◽  
Universal Thermal Climate Index ◽  
Numerical Weather ◽  
Weather Forecasters ◽  
Thermal Climate ◽  
Nwp Model

The article includes a summary of basic information about the Universal Thermal Climate Index (UTCI) calculation by the numerical weather prediction (NWP) model ALADIN of the Czech Hydrometeorological Institute (CHMI). Examples of operational outputs for weather forecasters in the CHMI are shown in the first part of this work. The second part includes results of a comparison of computed UTCI values by ALADIN for selected place with UTCI values computed from real measured meteorological data from the same place.

scholarly journals Detection and thermal description of medicanes from numerical simulation

2014 ◽  
Vol 14 (5) ◽  
pp. 1059-1070 ◽  
Author(s):  
M. A. Picornell ◽  
J. Campins ◽  
A. Jansà
Keyword(s):  
Numerical Simulation ◽  
Thermal Structure ◽  
Weather Prediction ◽  
Weather Forecast ◽  
Small Scale ◽  
Medium Range Weather Forecast ◽  
Warm Core ◽  
Strong Winds ◽  
Nwp Model ◽  
Ecmwf Model

Abstract. Tropical-like cyclones rarely affect the Mediterranean region but they can produce strong winds and heavy precipitations. These warm-core cyclones, called MEDICANES (MEDIterranean hurriCANES), are small in size, develop over the sea and are infrequent. For these reasons, the detection and forecast of medicanes are a difficult task and many efforts have been devoted to identify them. The goals of this work are to contribute to a proper description of these structures and to develop some criteria to identify medicanes from numerical weather prediction (NWP) model outputs. To do that, existing methodologies for detecting, characterizating and tracking cyclones have been adapted to small-scale intense cyclonic perturbations. First, a mesocyclone detection and tracking algorithm has been modified to select intense cyclones. Next, the parameters that define the Hart's cyclone phase diagram are tuned and calculated to examine their thermal structure. Four well-known medicane events have been described from numerical simulation outputs of the European Centre for Medium-Range Weather Forecast (ECMWF) model. The predicted cyclones and their evolution have been validated against available observational data and numerical analyses from the literature.

Sign in / Sign up

Export Citation Format

Share Document