scholarly journals A NOVEL PROCEDURE FOR GENERATION OF SAR-DERIVED ZTD MAPS FOR WEATHER PREDICTION: APPLICATION TO SOUTH AFRICA USE CASE

Author(s):  
M. E. Molinari ◽  
M. Manzoni ◽  
N. Petrushevsky ◽  
A. M. Guarnieri ◽  
G. Venuti ◽  
...  

Abstract. The knowledge of tropospheric water vapor distribution can significantly improve the accuracy of Numerical Weather Prediction (NWP) models. The present work proposes an automatic and fast procedure for generating reliable water vapor products from the synergic use of Sentinel-1 Synthetic Aperture Radar (SAR) imagery and Global Navigation Satellite System (GNSS) observations. Moreover, a compression method able to drastically reduce, without significant accuracy loss, the water vapor dataset dimension has been implemented to facilitate the sharing through cloud services. The activities have been carried in the EU H2020 TWIGA project framework, aimed at providing water vapor maps at Technology Readiness Level 7.

2014 ◽  
Vol 53 (3) ◽  
pp. 715-730 ◽  
Author(s):  
Luiz F. Sapucci

AbstractMeteorological application of Global Navigation Satellite System (GNSS) data over Brazil has increased significantly in recent years, motivated by the significant amount of investment from research agencies. Several projects have, among their principal objectives, the monitoring of humidity over Brazilian territory. These research projects require integrated water vapor (IWV) values with maximum quality, and, accordingly, appropriate data from the installed meteorological stations, together with the GNSS antennas, have been used. The model that is applied to estimate the water-vapor-weighted mean tropospheric temperature (Tm) is a source of uncertainty in the estimate of IWV values using the ground-based GNSS receivers in Brazil. Two global models and one algorithm for Tm, developed through the use of radiosondes, numerical weather prediction products, and 40-yr ECMWF Re-Analysis (ERA-40), as well as two regional models, were evaluated using a dataset of ~78 000 radiosonde profiles collected at 22 stations in Brazil during a 12-yr period (1999–2010). The regional models (denoted the Brazilian and regional models) were developed with the use of multivariate statistical analysis using ~90 000 radiosonde profiles launched at 12 stations over a 32-yr period (1961–93). The main conclusion is that the Brazilian model and two global models exhibit similar performance if the complete dataset and the entire period are taken into consideration. However, for seasonal and local variations of the Tm values, the Brazilian model was better than the other two models for most stations. The Tm values from ERA-40 present no bias, but their scatter is larger than that in the other models.


2021 ◽  
Vol 13 (19) ◽  
pp. 3818
Author(s):  
Hao Wang ◽  
Nan Ding ◽  
Wenyuan Zhang

Global Navigation Satellite System (GNSS) water vapor tomography provides a four-dimensional (4-D) distribution of water vapor in the atmosphere for weather monitoring. It has developed into a widely used technique in numerical weather prediction (NWP). Vertical stratification is essential in discretizing the tomographic region. Traditional discretization methods divide the tomographic area into regular voxels with an equal height interval, which ignores the dynamic exponential distribution of water vapor. In recent years, non-uniform stratification methods have been widely validated by tomographic experiments. However, such experiments have not proposed a specific calculation method for stratification thickness. Therefore, in this paper, we introduced an adaptive non-uniform stratification method that follows the exponential distribution of water vapor in the tomographic region and presented the process of iterative calculation to acquire the optimal stratification interval. The proposed approach was applied based on the exponential decreasing trend in water vapor with increasing altitude. Moreover, it could adaptively calculate the interval of stratification height according to water vapor content. The tomographic experiments were performed using Global Positioning System (GPS) data from 19 ground-based stations in the Hong Kong Satellite Positioning Reference Station Network (SatRef) from 1 to 31 August 2019. The results indicated that, compared to the traditional stratification method, the root mean square error derived from the proposed approach was reduced by 0.26 g/m3. Additionally, severe weather can negatively affect the accuracy of the tomographic results. The results also showed that the accuracy of the tomographic results was reduced with increasing altitude. Moreover, the performance of the tomographic water vapor fields below 3000 m was improved by the proposed approach.


2021 ◽  
Vol 295 ◽  
pp. 126426
Author(s):  
Fernando Bruno Dovichi Filho ◽  
York Castillo Santiago ◽  
Electo Eduardo Silva Lora ◽  
José Carlos Escobar Palacio ◽  
Oscar Agustin Almazan del Olmo

Author(s):  
Magnus Lindskog ◽  
Adam Dybbroe ◽  
Roger Randriamampianina

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.


2021 ◽  
Vol 18 (3) ◽  
pp. 172988142110121
Author(s):  
David Portugal ◽  
André G Araújo ◽  
Micael S Couceiro

To move out of the lab, service robots must reveal a proven robustness so they can be deployed in operational environments. This means that they should function steadily for long periods of time in real-world areas under uncertainty, without any human intervention, and exhibiting a mature technology readiness level. In this work, we describe an incremental methodology for the implementation of an innovative service robot, entirely developed from the outset, to monitor large indoor areas shared by humans and other obstacles. Focusing especially on the reliability of the fundamental localization system of the robot in the long term, we discuss all the incremental software and hardware features, design choices, and adjustments conducted, and show their impact on the performance of the robot in the real world, in three distinct 24-h long trials, with the ultimate goal of validating the proposed mobile robot solution for indoor monitoring.


2021 ◽  
Vol 13 (3) ◽  
pp. 350
Author(s):  
Rosa Delia García ◽  
Emilio Cuevas ◽  
Victoria Eugenia Cachorro ◽  
Omaira E. García ◽  
África Barreto ◽  
...  

Precipitable water vapor retrievals are of major importance for assessing and understanding atmospheric radiative balance and solar radiation resources. On that basis, this study presents the first PWV values measured with a novel EKO MS-711 grating spectroradiometer from direct normal irradiance in the spectral range between 930 and 960 nm at the Izaña Observatory (IZO, Spain) between April and December 2019. The expanded uncertainty of PWV (UPWV) was theoretically evaluated using the Monte-Carlo method, obtaining an averaged value of 0.37 ± 0.11 mm. The estimated uncertainty presents a clear dependence on PWV. For PWV ≤ 5 mm (62% of the data), the mean UPWV is 0.31 ± 0.07 mm, while for PWV > 5 mm (38% of the data) is 0.47 ± 0.08 mm. In addition, the EKO PWV retrievals were comprehensively compared against the PWV measurements from several reference techniques available at IZO, including meteorological radiosondes, Global Navigation Satellite System (GNSS), CIMEL-AERONET sun photometer and Fourier Transform Infrared spectrometry (FTIR). The EKO PWV values closely align with the above mentioned different techniques, providing a mean bias and standard deviation of −0.30 ± 0.89 mm, 0.02 ± 0.68 mm, −0.57 ± 0.68 mm, and 0.33 ± 0.59 mm, with respect to the RS92, GNSS, FTIR and CIMEL-AERONET, respectively. According to the theoretical analysis, MB decreases when comparing values for PWV > 5 mm, leading to a PWV MB between −0.45 mm (EKO vs. FTIR), and 0.11 mm (EKO vs. CIMEL-AERONET). These results confirm that the EKO MS-711 spectroradiometer is precise enough to provide reliable PWV data on a routine basis and, as a result, can complement existing ground-based PWV observations. The implementation of PWV measurements in a spectroradiometer increases the capabilities of these types of instruments to simultaneously obtain key parameters used in certain applications such as monitoring solar power plants performance.


2020 ◽  
Vol 12 (7) ◽  
pp. 1170 ◽  
Author(s):  
Cintia Carbajal Henken ◽  
Lisa Dirks ◽  
Sandra Steinke ◽  
Hannes Diedrich ◽  
Thomas August ◽  
...  

Passive imagers on polar-orbiting satellites provide long-term, accurate integrated water vapor (IWV) data sets. However, these climatologies are affected by sampling biases. In Germany, a dense Global Navigation Satellite System network provides accurate IWV measurements not limited by weather conditions and with high temporal resolution. Therefore, they serve as a reference to assess the quality and sampling issues of IWV products from multiple satellite instruments that show different orbital and instrument characteristics. A direct pairwise comparison between one year of IWV data from GPS and satellite instruments reveals overall biases (in kg/m 2 ) of 1.77, 1.36, 1.11, and −0.31 for IASI, MIRS, MODIS, and MODIS-FUB, respectively. Computed monthly means show similar behaviors. No significant impact of averaging time and the low temporal sampling on aggregated satellite IWV data is found, mostly related to the noisy weather conditions in the German domain. In combination with SEVIRI cloud coverage, a change of shape of IWV frequency distributions towards a bi-modal distribution and loss of high IWV values are observed when limiting cases to daytime and clear sky. Overall, sampling affects mean IWV values only marginally, which are rather dominated by the overall retrieval bias, but can lead to significant changes in IWV frequency distributions.


2018 ◽  
Vol 178 ◽  
pp. 08006
Author(s):  
Alexei Toca ◽  
Vadim Iaţchevici ◽  
Tatiana Niţulenco ◽  
Nicolae Rusu

Technological transfer is a complex and varied process, being realized out at different stages of technology readiness level. Being essentially a trading, technology transfer is fully subject to market laws. The technology transfer strategy and tactics are strongly influenced by the degree of technology's readiness level, systemic character, functional orientation and universality, technical and economic determination degrees that can be specified and determined in accordance with the stages of technology life cycle.


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