radiosonde observation
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2022 ◽  
Vol 14 (2) ◽  
pp. 387
Author(s):  
Yeonjin Lee ◽  
Myoung-Hwan Ahn ◽  
Su Jeong Lee

Early warning of severe weather caused by intense convective weather systems is challenging. To help such activities, meteorological satellites with high temporal and spatial resolution have been utilized for the monitoring of instability trends along with water vapor variation. The current study proposes a retrieval algorithm based on an artificial neural network (ANN) model to quickly and efficiently derive total precipitable water (TPW) and convective available potential energy (CAPE) from Korea’s second geostationary satellite imagery measurements (GEO-KOMPSAT-2A/Advanced Meteorological Imager (AMI)). To overcome the limitations of the traditional static (ST) learning method such as exhaustive learning, impractical, and not matching in a sequence data, we applied an ANN model with incremental (INC) learning. The INC ANN uses a dynamic dataset that begins with the existing weight information transferred from a previously learned model when new samples emerge. To prevent sudden changes in the distribution of learning data, this method uses a sliding window that moves along the data with a window of a fixed size. Through an empirical test, the update cycle and the window size of the model are set to be one day and ten days, respectively. For the preparation of learning datasets, nine infrared brightness temperatures of AMI, six dual channel differences, temporal and geographic information, and a satellite zenith angle are used as input variables, and the TPW and CAPE from ECMWF model reanalysis (ERA5) data are used as the corresponding target values over the clear-sky conditions in the Northeast Asia region for about one year. Through the accuracy tests with radiosonde observation for one year, the INC NN results demonstrate improved performance (the accuracy of TPW and CAPE decreased by approximately 26% and 26% for bias and about 13% and 12% for RMSE, respectively) when compared to the ST learning. Evaluation results using ERA5 data also reveal more stable error statistics over time and overall reduced error distribution compared with ST ANN.


MAUSAM ◽  
2021 ◽  
Vol 63 (2) ◽  
pp. 291-298
Author(s):  
S.M. METRI

Meteorological Radiosonde in the past used to apply navigation system to rout to determine the upper air pressure, temperature, humidity and the wind data through Radars. In this paper GPS Radiosonde test has been recently introduced in IMD is studied. The observations taken from M2K2 Radiosonde have been discussed. GPS Radiosonde obtains wind data as well.


2021 ◽  
Author(s):  
avinash parde ◽  
Prakash Pithani ◽  
Sachin D. Ghude ◽  
Narendra G. Dhangar ◽  
Chinmay Jena ◽  
...  

Abstract Three major sequential widespread dust events were experienced in the northern parts of India in May 2018. A significant impact of these pre-monsoon dust storms on the aerosol characteristics over the Indian National capital region (NCR) has been studied using remotely sensed ceilometer and ground-based measurements at Indira Gandhi International (IGI) airport, New Delhi, India. From the results, it is noticed that after each consecutive dust activity, the significant inclusion of dust aerosols loaded in the Free Troposphere (FT). Consequently, the direct impact on the lower atmospheric parameters like increase in daily average temperature (by 4–5 K), stepped up (stepped down) diurnal cycles of longwave fluxes (shortwave fluxes) has been recorded within 15 days of dust span. Mainly, the adverse meteorological and radiation features noticed before first dust storm (DS1), which pinpoints the sudden intrusion of dust over NCR, Delhi. However, this dust storm has extensively impacted in terms of the vertical dust loading, surface boundary layer mechanisms, and socioeconomic way. Therefore, the detailed analysis of vertical dust distribution and its interaction with middle tropospheric processes has been carried by using the vertical normalized attenuated backscatter coefficients accompanying the radiosonde observation. The aloft floating dust layer up to 3–4 km has been noticed even after shallow rainfall and persisted at almost the same height for the next 34 hrs due to low-level clouds. Meanwhile, the sub dust layer below 1 km is formed due to local activity, which also sustains for a long time. Moreover, the cumulative losses in terms of the impediment in airline operations (delay and diversion), live causalities, and deaths were estimated at US$1.3 million over these dust period.


2021 ◽  
Vol 13 (1) ◽  
pp. 41-53
Author(s):  
Lismalini Lismalini ◽  
Marzuki Marzuki ◽  
Mohammad Ali Shafii

Study on the vertical structure of cloud in Indonesia in terms of climate change is still very limited. We investigated the long-term change in characteristics of cloud vertical structures over Sumatra from three radiosonde observation stations in this work. The cloud base height (CBH), cloud top height (CT), and the number of cloud layers were retrieved using relative humidity (RH) profiles from radiosonde observation. The height of the cloud base is determined by taking the height of the layer with relative humidity (RH) value > 84% with at least a 3% jump in the RH from the ground level. Sumatra’s most frequently observed cloud layer is a one-layer cloud with an average occurrence rate of > 60%, which is slightly larger than the one-layer cloud globally. The percentage of appearance values at the Padang station, Pangkal Pinang, and Medan are 63.58%, 69.50% and 66.05%. The appearance of low-level clouds also dominates in Sumatra compared to other cloud types. CT and CBH increase with the number of years including all seasons. This is in line with the increase in temperature in Indonesia reported by previous researchers. On the other hand, the clouds’ thickness, especially for the cloud with one layer, varies from one location to another. The thickness of clouds decreases at Padang station and does not change at Pangkal Pinang and Medan stations.


2021 ◽  
Vol 5 (3) ◽  
pp. 1-10
Author(s):  
XiaoYan Bai ◽  
◽  
KaiMing Huang ◽  
ShaoDong Zhang ◽  
ChunMing Huang ◽  
...  

2020 ◽  
Vol 12 (24) ◽  
pp. 4099
Author(s):  
Shu-Peng Ho ◽  
Xinjia Zhou ◽  
Xi Shao ◽  
Bin Zhang ◽  
Loknath Adhikari ◽  
...  

A COSMIC-1/FORMOSAT-3 (Constellation Observing System for Meteorology, Ionosphere, and Climate-1 and Formosa Satellite Mission 3) follow-on mission, COSMIC-2/FORMOSAT-7, had been successfully launched into low-inclination orbits on 25 June 2019. COSMIC-2 has a significantly increased Signal-to-Noise ratio (SNR) compared to other Radio Occultation (RO) missions. This study summarized the initial assessment of COSMIC-2 data quality conducted by the NOAA (National Oceanic and Atmospheric Administration) Center for Satellite Applications and Research (STAR). We use validated data from other RO missions to quantify the stability of COSMIC-2. In addition, we use the Vaisala RS41 radiosonde observations to assess the accuracy and uncertainty of the COSMIC-2 neutral atmospheric profiles. RS41 is currently the most accurate radiosonde observation system. The COSMIC-2 SNR ranges from 200 v/v to about 2800 v/v. To see if the high SNR COSMIC-2 signals lead to better retrieval results, we separate the COSMIC-2–RS41 comparisons into different SNR groups (i.e., 0–500 v/v group, 500–1000 v/v group, 1000–1500 v/v group, 1500–2000 v/v group, and >2000 v/v group). In general, the COSMIC-2 data quality in terms of stability, precision, accuracy, and uncertainty of the accuracy is very compatible with those from COSMIC-1. Results show that the mean COSMIC-2–RS41 water vapor difference from surface to 5 km altitude for each SNR groups are equal to −1.34 g/kg (0–500 v/v), −1.17 g/kg (500–1000 v/v), −1.33 g/kg (1000–1500 v/v), −0.93 g/kg (1500–2000 v/v), and −1.52 g/kg (>2000 v/v). Except for the >2000 v/v group, the high SNR measurements from COSMIC-2 seem to improve the mean water vapor difference for the higher SNR group slightly (especially for the 1500–2000 v/v group) comparing with those from lower SNR groups.


2020 ◽  
Vol 12 (21) ◽  
pp. 3497
Author(s):  
Pengfei Xia ◽  
Jingchao Xia ◽  
Shirong Ye ◽  
Caijun Xu

A new concept is proposed for estimating the zenith wet delay (ZWD) and atmospheric weighted average temperature by inputting the temperature, total pressure, and specific humidity from surface weather data. In addition, a new ZWD integral method is described for highly accurate calculation of the ZWD from radiosonde observation. To evaluate the advantages of the new discrete integral formula, we utilized the 8-year radiosonde profiles of 85 stations in China from 2010 to 2017 to validate the accuracy of the radiosonde-derived ZWD. The results showed that the mean accuracy of the ZWD derived from radiosonde data was 4.28 mm. Next, the new ZWD model was assessed using two sets of reference values derived from radiosonde data and GNSS precise point positioning in China. The results confirm that the new development improved the accuracy of the estimation of the tropospheric wet delay from the surface meteorological data. The performance of this new model can be seen as an important step toward accurately correcting the tropospheric delay in Global Navigation Satellite System (GNSS) real-time navigation and positioning. It can also be used in GNSS meteorology for weather forecasting and climate research.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 704
Author(s):  
Hwan-Jin Song ◽  
Sunyoung Kim ◽  
Hyesook Lee ◽  
Ki-Hoon Kim

Conventional radiosondes can be used to measure the relative humidity over liquid (RHL) by assuming a saturated vapor pressure over the liquid. However, this assumption results in significant errors with respect to measurements in the upper troposphere, where the effect of ice is dominant. Therefore, this study presents a novel method that considers the effects of ice to determine the relative humidity from radiosonde RHL data for the last 40 years (1979–2018) over the upper layers of the Korean peninsula. Even though the relative humidity obtained from the reanalysis data was significantly different from the radiosonde-based RHL, the difference was much reduced when relative humidity was calculated using the novel method proposed in this study. Such improvements in the estimated relative humidity could be attributed to the consideration of the ice effect at temperatures above freezing level. Additionally, the validity of the relative humidity estimated in this study was established based on a two-week case analysis of data from Boseong station. Furthermore, two peak relative humidity modes for the lower and upper layers were clearly identified in the mean climatology profiles, which indirectly suggested the absence of mid-level clouds around the 700-hPa level and 500-hPa level in winter and summer, respectively. This study is meaningful as it is the first study to determine the relative humidity distribution over the Korean peninsula using radiosonde observations. The scientific value obtained can potentially be expanded by applying the proposed method to other radiosonde observation networks, which are widely distributed worldwide.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 702
Author(s):  
Kazutoshi Sato ◽  
Jun Inoue ◽  
Akira Yamazaki

We investigated the accuracy of operational medium-range ensemble forecasts for 29 Atlantic hurricanes between 2007 and 2019. Upper-level troughs with strong wind promoted northward movement of hurricanes over the mid-latitudes. For hurricanes with upper-level troughs, relatively large errors in the prediction of troughs result in large ensemble spreads, which result in failure to forecast hurricane track. In contrast, for hurricanes without upper-level troughs, mean central position errors are relatively small in all operational forecasts because of the absence of upper-level strong wind around troughs over the mid-latitudes. Hurricane Irma in September 2017 was accompanied by upper-level strong wind around a trough; errors and ensemble spreads for the predicted upper-level trough are small, contributing to smaller errors and small ensemble spreads in the predicted tracks of Irma. Our observing system experiment reveals that inclusion of additional Arctic radiosonde observation data obtained from research vessel Mirai in 2017 improves error and ensemble spread in upper-level trough with strong wind at initial time for forecast, increasing the accuracy of the forecast of the track of Irma in 2017.


2020 ◽  
Author(s):  
Holger Baars ◽  
Alina Herzog ◽  
Birgit Heese ◽  
Kevin Ohneiser ◽  
Karsten Hanbuch ◽  
...  

Abstract. In August 2018, the first Doppler wind lidar in space called ALADIN was launched on-board the satellite Aeolus by the European Space Agency ESA. Aeolus measures horizontal wind profiles in the troposphere and lower stratosphere on a global basis. Furthermore, profiles of aerosol and cloud properties can be retrieved via the high-spectral-resolution lidar (HSRL) technique. The Aeolus mission is supposed to improve the quality of weather forecasts and the understanding of atmospheric processes. We used the chance of opportunity to perform a unique validation of the wind products of Aeolus by utilizing the RV Polarstern cruise PS116 from Bremerhaven to Cape Town in November/December 2018. Due to concerted course modifications, six direct intersections with the Aeolus ground track could be achieved on the Atlantic Ocean, west of the African continent. For the validation of the Aeolus wind products, we launched additional radiosondes and used the EARLINET/ACTRIS lidar PollyXT for atmospheric scene analysis. The six analyzed cases proof the concept of Aeolus to be able to measure horizontal wind speeds in the nearly West-East direction. Good agreements with the radiosonde observation could be achieved for both Aeolus wind products – the winds observed in clean atmospheric regions called Rayleigh winds and the winds obtained in cloud layers called Mie winds according to the responsible scattering regime. Systematic and statistical errors of the Rayleigh winds were less than 1.5 m/s and 3.3 m/s, respectively, when comparing to radiosonde values averaged to the Aeolus vertical resolution. For the Mie winds, a systematic and random error of about 1 m/s was obtained from the six comparisons in different climate zones. However, it is also shown that the coarse vertical resolution of 2 km in the upper troposphere which was set in this early mission phase two months after launch led to an underestimation of the maximum wind speed in the jet stream regions. Summarizing, promising first results of the first wind lidar space mission are shown and proof the concept of Aeolus for global wind observations.


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