Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Sun, Qiang; Vihma, Timo; Jonassen, Marius O.; Zhang, Zhanhai

doi:10.1007/s00376-020-9213-8

Cited by 21 publications

(22 citation statements)

References 50 publications

(66 reference statements)

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“…The increasing use of UAVs in all science disciplines, whereby multiple types of sensors can be easily deployed over relatively large areas, also provides us with plenty of opportunities to assimilate high-resolution data at intermediate scales. Assimilation of UAV-collected data is becoming common in weather modeling (Sun et al, 2020;Jensen et al, 2021) and crop modeling (Yu et al, 2019;Peng et al, 2021). However, incorporation of UAV data in physics-based hydrological modeling is still largely unexplored.…”

Section: Intermediate-scale Sensing Technologiesmentioning

confidence: 99%

Recent advances and opportunities in data assimilation for physics-based hydrological modeling

Camporese

Girotto

2022

Front. Water

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Data assimilation applications in integrated surface-subsurface hydrological models (ISSHMs) are generally limited to scales ranging from the hillslope to local or meso-scale catchments. This is because ISSHMs resolve hydrological processes in detail and in a physics-based fashion and therefore typically require intensive computational efforts and rely on ground-based observations with a small spatial support. At the other end of the spectrum, there is a vast body of literature on remote sensing data assimilation for land surface models (LSMs) at the continental or even global scale. In LSMs, some hydrological processes are usually represented with a coarse resolution and in empirical ways, especially groundwater lateral flows, which may be very important and yet often neglected. Starting from the review of some recent progress in data assimilation for physics-based hydrological models at multiple scales, we stress the need to find a common ground between ISSHMs and LSMs and suggest possible ways forward to advance the use of data assimilation in integrated hydrological models.

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Section: Intermediate-scale Sensing Technologiesmentioning

confidence: 99%

Recent advances and opportunities in data assimilation for physics-based hydrological modeling

Camporese

Girotto

2022

Front. Water

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“…In order to calculate background errors matrix, the analysis-ensemble method was used [45] and the R matrix was taken to be diagonal. In this study the assimilated data was limited only by the GPS derived IWV, in contrast to many other studies, for example [46,47], where frequent and dense radiosonde data was also assimilated. The Israel Meteorological Service (IMS) radiosonde data in Israel is available two times per day, however, there is only one radiosonde location (see Figure 3).…”

Section: Wrf Data Assimilation Technique and Implementationmentioning

confidence: 99%

On the Potential of Improving WRF Model Forecasts by Assimilation of High-Resolution GPS-Derived Water-Vapor Maps Augmented with METEOSAT-11 Data

2020

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Improving the accuracy of numerical weather predictions remains a challenging task. The absence of sufficiently detailed temporal and spatial real-time in-situ measurements poses a critical gap regarding the proper representation of atmospheric moisture fields, such as water vapor distribution, which are highly imperative for improving weather predictions accuracy. The estimated amount of the total vertically integrated water vapor (IWV), which can be derived from the attenuation of global positioning systems (GPS) signals, can support various atmospheric models at global, regional, and local scales. Currently, several existing atmospheric numerical models can estimate the IWV amount. However, they do not provide accurate results compared with in-situ measurements such as radiosondes. Here, we present a new strategy for assimilating 2D IWV regional maps estimations, derived from combined GPS and METEOSAT satellite imagery data, to improve Weather Research and Forecast (WRF) model predictions accuracy in Israel and surrounding areas. As opposed to previous studies, which used point measurements of IWV in the assimilation procedure, in the current study, we assimilate quasi-continuous 2D GPS IWV maps, combined with METEOSAT-11 data. Using the suggested methodology, our results indicate an improvement of more than 30% in the root mean square error (RMSE) of WRF forecasts after assimilation relative standalone WRF, when both are compared to the radiosonde measured data near the Mediterranean coast. Moreover, significant improvements along the Jordan Rift Valley and Dead Sea Valley areas are obtained when compared to 2D IWV regional maps estimations. Improvements in these areas suggest the impact of the assimilated high resolution IWV maps, with initialization times which coincide with the Mediterranean Sea Breeze propagation from the coastline to highland stations, as the distance to the Mediterranean Sea shore, along with other features, dictates its arrival times.

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“…To determine the value of using a UAS in meteorology, several studies have incorporated data gathered from UASs into meteorological forecasts. Sun et al (2020) incorporated UAS sounding data from an RV Polarstern cruise in the Weddell Sea and evaluated their impact on the Polar Weather Research Forecasting model. This work was limited to the bottom 1 and 2 km of the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

High-altitude vertical wind profile estimation using multirotor vehicles

McConville

Richardson

2023

Front. Robot. AI

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Capturing vertical profiles of the atmosphere and measuring wind conditions can be of significant value for weather forecasting and pollution monitoring however, collecting such data can be limited by current approaches using balloon-based radiosondes and expensive ground-based sensors. Multirotor vehicles can be significantly affected by the local wind conditions, and due to their under-actuated nature, the response to the flow is visible in the changes in the orientation. From these changes in orientation, wind speed and direction estimates can be determined, allowing accurate estimation with no additional sensors. In this work, we expand on and improve this method of wind speed and direction estimation and incorporate corrections for climbing flight to improve estimation during vertical profiling. These corrections were validated against sonic anemometer data before being used to gather vertical profiles of the wind conditions around Volcan De Fuego in Guatemala up to altitudes of 3000 m Above Ground Level (AGL). From the results of this work, we show we can improve the accuracy of multirotor wind estimation in vertical profiling through our improved model and some of the practical limitations of radiosondes that can be overcome through the use of UAS in this application.

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Impact of Assimilation of Radiosonde and UAV Observations from the Southern Ocean in the Polar WRF Model

Cited by 21 publications

References 50 publications

Recent advances and opportunities in data assimilation for physics-based hydrological modeling

Recent advances and opportunities in data assimilation for physics-based hydrological modeling

On the Potential of Improving WRF Model Forecasts by Assimilation of High-Resolution GPS-Derived Water-Vapor Maps Augmented with METEOSAT-11 Data

High-altitude vertical wind profile estimation using multirotor vehicles

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