Radiosonde Observation Data Research Articles

Analysis of Extreme Weather Causes of Flooding in Manado North Sulawesi

On January 27 and 28 2023, Manado City was hit by heavy rain which caused several areas to experience significant flooding. The high intensity of rain during that period reached extreme levels, resulting in the inundation of several areas and submerging hundreds of residents' houses in 22 villages or sub-districts and 7 sub-districts in Manado. In studying this event, this research investigates the factors that influence extreme weather in Manado, observing sea surface temperature data, streamlines, air observations, the Southern Oscillation Index (SOI), and the Indian Ocean Dipole (IOD). The analysis shows that the positive SOI and negative IOD phenomena significantly impact extreme weather in the region. Cumulonimbus (Cb) clouds drove the atmospheric conditions formed on January 27 and 28 2023 and air flows from the Indian Ocean which brought wet air masses into Indonesian territory. High sea surface temperatures, reaching 28-29°C, also play a role in the intensive growth of rain clouds. Based on atmospheric conditions seen from radiosonde observation data, the stability index value shows that unstable conditions trigger heavy rain which causes flooding

Evaluation of fused multisource data of air temperature based on dropsonde and satellite observation

Continuous vertical air temperature (AT) from in-situ observation is of crucial importance for understanding the atmospheric environment, but the satellite data that have complete spatial coverage lacked vertical in-situ observation data, and the vertical dropsonde data from in-situ observations only were single-point observations. Therefore, this article introduced machine learning algorithms for fusing in-situ observation and multi-satellite data to achieve spatial continuity of vertical data on a large scale. Specially, random forest (RF), support vector regression (SVR), artificial neural network (ANN) and recurrent neural network (RNN) were employed to capture the non-linear relationships between the variables and estimated AT. The pre-training process and fine-tuning process ensured the prediction of AT spatiotemporal distribution. The four models were implemented for three-dimensional AT estimating across China. Additionally, we used the radiosonde observation data to evaluate the accuracy of estimated AT data under conventional weather and typhoon conditions. Our results revealed that the RF model performed the best with the R of 0.9992, the MAE of 0.70 °C, and the RMSE of 1.04 °C at the national scale, followed by the SVR and ANN models. The RNN model exhibited promising results under typhoon conditions, which will be valuable insights for further research on the applicability of machine learning models under different weather conditions. Besides, having a larger sample size does not necessarily result in reduced errors. For instance, the MAE value for SVR in the pressure height range of 100–200 hPa was larger than that in the pressure height range of 300–400 hPa, but the former sample size was 16,324, which was 7433 higher than the latter.

The Fusion of ERA5 and MERRA-2 Atmospheric Temperature Profiles with Enhanced Spatial Resolution and Accuracy

Accurate high-resolution atmospheric temperature profiles are essential for precisely characterizing the evolution of the atmosphere and developing numerical forecasts. Atmospheric datasets, such as ERA5 (the fifth-generation ECMWF Reanalysis) and MERRA-2 (the Modern-Era Retrospective Analysis for Research and Applications, Version 2), provide global and continuous temperature profiles, with fine vertical distribution and horizontal resolution. RAOB (Radiosonde Observation) sounding data have high confidence and representativeness and are usually used for data accuracy verification. Due to the difficulty of updating existing products, and the scarcity of research on mesospheric temperature profiles, this work maximizes the high observation accuracy of RAOB data, combines the benefits of ERA5’s horizontal resolution and MERRA-2’s vertical distribution, and employs the optimal interpolation method to combine the data, in order to produce a fused result with high spatial resolution. After converting all of the data to the same spatial distribution, the optimal interpolation method was used to combine the two datasets from separate places and different pressure layers in order to produce the fused results, which had a vertical distribution of 45 layers and a spatial resolution of 0.25°. The fused data’s RMSE and MAE were 6.0 K and 5.0 K lower than those of the MERRA-2 temperature profile data, respectively, and 0.3 K and 0.4 K lower than those of the ERA5 temperature profile data, respectively. The validation, using data from 2019, showed that the fused data exhibits better correlation and data accuracy than the other two datasets, which demonstrated that the fused algorithm can potentially be used to generate reliable datasets for future meteorological research.

Cold Surge Effect on Vertical Profile Atmosphere over Meteorological Station of Ranai Natuna: Case Study Asian Winter Monsoon 2019/2020

During the Asian Winter season, which spans from November to February, the phenomenon of cold surge often occurs, leading to increased convective activity over the western Indonesian Maritime Continent. The location of Natuna Island, situated in the southern part of the South China Sea, is of particular importance for studying cold surges due to their propagation over this area. In this study, the vertical structure of the atmosphere was analyzed using radiosonde observation data collected at the Meteorological Station of Ranai Natuna. The analysis focused on physical parameters such as air temperature and relative humidity, atmospheric kinematics including wind direction and speed, as well as atmospheric thermodynamic parameters such as Lifting Condensation Level (LCL), Level of Free Convection (LFC), Equilibrium Level (EL), Convective Available Potential Energy (CAPE), and Convective Inhibition (CIN). The results indicate that during the passage of a cold surge, air temperature (T) tends to be higher in the lower troposphere, including at the surface, but lower in the middle and upper troposphere. Relative humidity (RH) also tends to be higher during cold surges, with a significant increase in the middle and upper troposphere. In the lower troposphere, the wind direction shifts from east to northeast at a higher speed compared to when a cold surge is absent. Furthermore, the LCL and LFC heights are elevated during the presence of a cold surge, while the EL height shows an insignificant decrease. It is worth noting that intense rainfall occurs, particularly when the cold surge is more pronounced, even though the values of CAPE and CIN do not change significantly.

Visualization of Aerological Diagram and Analysis of Atmospheric Sounding Information Using Raob with Model Data During Low Visibility Conditions at Cengkareng Meteorological Station

The limitations of in-situ observations of the upper air are one of the obstacles in analyzing the weather. The use of data models can be one solution. The purpose of this study was to determine the accuracy of the data model in providing upper air information using RAOB as a visualization tool for aerological diagrams and sounding information analyzers. The data used are radiosonde observation data from the Cengkareng meteorological station and 1000 – 100 mb ECMWF pressure level models at the same location as the in-situ observations. The time chosen is when the haze and mist occur at the observation time 00 UTC for 5 events each. The method used is pearson correlation and simple visual verification. The results obtained that the correlation of the significant point plot data diagram when the mist occurs is 0.76 and when the haze occurs is 0.67 and visually as a whole show that the model data is quite close to the observation data. Correlation of 59 sounding information as a whole produces a value of 0.85 – 0.99 when the Mist occurs and a value of 0.89 – 0.99 when the Haze occurs. It is hoped that these results can be used as a consideration for the use of data models in filling in the gaps in radiosonde observation data. Keywords: Sounding Information, RAOB, Radiosonde, ECMWF Models

Characteristics of the atmospheric boundary layer's structure and heating (cooling) rate in summer over the Northern Tibetan Plateau

The atmospheric boundary layer (ABL) is one of the most fundamental yet complex components of the Earth's atmosphere. Hence, studying the ABL has important theoretical value and practical significance. In this paper, the structural characteristics and heating (cooling) rate of the ABL in summer over the Northern Tibetan Plateau (NTP) were analysed using radiosonde observation data from the Amdo and Nagqu regions. The results indicate that the summertime ABL height over the NTP exhibited obvious diurnal variations, with the ABL height during the dry season being greater than that during the rainy season. The maximum convective boundary layer (CBL) height during the daytime reached 3200 m and 2500 m in the dry and rainy seasons, respectively, and the mean maximum CBL height was approximately 2500 m; the maximum stable boundary layer (SBL) height at night reached 900 m, and the mean maximum SBL height was approximately 500 m. The wind speed dominated by westerly wind in the dry season was greater than that dominated by easterly wind in the rainy season, and the zonal (meridional) wind speed (shear) on sunny days was greater than that on cloudy days. The inverse humidity phenomenon occurred in both Amdo and Nagqu, and the strong humidity inversion occurred mainly at midnight on sunny days and at noon on cloudy days. The heating (cooling) rate of the ABL displayed obvious diurnal variations, with the rates being greater on sunny days and lower on cloudy and rainy days. Furthermore, the mean values of the daytime heating rate and nighttime cooling rate of the ABL were relatively equal, indicating that the atmospheric energy budget was, for the most part, balanced.

Precipitable Water Vapor Retrieval Over Land From GCOM-W/AMSR2 Based on a New Integrated Method

Precipitable water vapor (PWV) is an important parameter reflecting atmospheric water vapor, which plays an important role in the global hydrological cycle. At present, brightness temperatures (Tbs) at frequencies of 18 and 23 GHz from the Advanced Microwave Scanning Radiometer 2 (AMSR2) are commonly applied in PWV data retrieval. Two tools are usually employed to perform the retrieval: physical models and neural networks. In this article, we creatively deduced a more universal physical equation and verified the consistency between theoretical and experimental equations both theoretically and numerically. Then, we fully considered the defects of these two tools and proposed a new integrated method that combines the physical model with a neural network. The Tbs in horizontal and vertical polarizations from AMSR2 and GNSS-derived PWV (GNSS-PWV) data from the SuomiNet global network were used to build the physical model. In the construction of the neural network, we also introduced the related surface parameters from GNSS stations as inputs. Validation results obtained with GNSS-PWV data showed that the accuracy of the test set can reach 2.38 and 2.37 mm in the ascending and descending orbit cases, respectively. Compared with the traditional physical model and neural network model, the improvements of the test set were 24.4% and 17.4% in the ascending orbit and 26.4% and 19.4% in the descending orbit. Radiosonde observation (RAOB) data were applied to carry out another external independent verification, and the accuracy of the test set reached 2.70 and 3.54 mm based on the RAOB data.

Is There Interdecadal Variation in the South Asian High?

AbstractThe decadal intensification of the South Asian high (SAH) after the late 1970s, which is determined based on the geopotential height (H), is suspicious due to the lifting effect upon H caused by global warming. The updated reanalysis datasets ERA5 and JRA-55 indicate that the anticyclone in the upper troposphere over the Tibetan Plateau is relatively weak during 1980–2018 compared to that during 1950–79. This decadal weakening of the SAH after 1979 can also be observed in the radiosonde observation data. Correspondingly, the SAH defined by eddy geopotential height (H′) reflects a consistent decadal weakening variation. The decadal weakening of SAH detected from H′ after the late 1970s matches with a decadal southward shift of the East Asian westerly jet, causing ascending motions over the Yangtze River valley and descending motions over North China. Moreover, the decadal weakening and westward shift of the SAH is accompanied with positive relative vorticity anomalies over the northwest Pacific in the upper troposphere, which implies a declining and eastward shift of the western Pacific subtropical high (WPSH) and a weakened East Asian summer monsoon (EASM). Hence, the decadal weakening of the SAH after the late 1970s may contribute to the Yangtze River flooding/North China drought pattern through its connection with other circulation systems of EASM.

Improving the Retrieval of Cloudy Atmospheric Profiles from Brightness Temperatures Observed with a Ground-Based Microwave Radiometer

Atmospheric temperature and humidity retrievals from ground-based microwave remote sensing are useful in a variety of meteorological and environmental applications. Though the influence of clouds is usually considered in current retrieval algorithms, the resulting temperature and humidity estimates are still biased high in overcast conditions compared to radiosonde observations. Therefore, there is a need to improve the quality of retrievals in cloudy conditions. This paper presents an approach to make brightness temperature (TB) correction for cloud influence before the data can be used in the inversion of vertical profiles of atmospheric temperature and humidity. A three-channel method is proposed to make cloud parameter estimation, i.e., of the total 22 channels of the ground-based radiometer, three are adopted to set up a relationship between cloud parameters and brightness temperatures, so that the observations from the three channels can be used to estimate cloud thickness and water content and complete the cloud correction for the rest of the channels used in the retrieval. Based on two years of data from the atmosphere in Beijing, a comparison of the retrievals with radiosonde observations (RAOB) shows: (1) the temperature retrievals from this study have a higher correlation with RAOB and are notably better than in the vendor-provided LV2. The bias of the temperature retrievals from this study is close to zero at all heights, and the RMSE is greatly reduced from >5 °C to <2 °C in the layer, from about 1.5 km up to 5 km. The temperature retrievals from this study have higher correlation with RAOB data compared to the vendor-provided LV2, especially at and above a 2 km height. (2) The bias of the water vapor density profile from this study is near to zero, while the LV2 has a positive bias as large as 4 g/m3. The RMSE of the water vapor density profile from this study is <2 g/m3, while the RMSE for LV2 is as large as 10 g/m3. That is, both the bias and RMSE from this study are evidently less than the LV2, with a greater improvement in the lower troposphere below 5 km. Correlation with RAOB is improved even more for the water vapor density. The correlation of the retrievals from this study increases to one within the boundary layer, but the correlation of LV2 with RAOB is only 0.8 at 0.5 km height, 0.7 at 1 km, and even less than 0.5 at 2 km. (3) A parameter named the Cloud Impact index, determined by cloud water concentration and cloud thickness, together with the cloud base height, has been defined to show that both BIAS and RMSE of “high-CI subsample” are larger than those of the “low-CI subsample”, indicating that high-CI cloud has a higher impact on the retrievals and the correction for cloud influence is more necessary.

Performance of Forecasts of Hurricanes with and without Upper-Level Troughs over the Mid-Latitudes

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.

A study of gravity wave activities based on intensive radiosonde observations at Bengkulu during YMC-Sumatra 2017

Gravity waves are generated from local regions such as convection, topography, jet stream and fronts. It is important to understand their activities because the quasi-biennial oscillation and general circulation in middle atmosphere are affected by their activities. However, the scale of gravity waves is too broad to understand their characters and activities in detail. The purpose of this study is to clarify three-dimensional dynamical circulation driven by gravity waves around the equatorial region. The Campaign of Years of Maritime Continent-Sumatra (YMC-Sumatra) has been operated since 2017 to expedite the progress of improving understanding and prediction of local multi-scale variability of the maritime continent weather-climate system and its global impact. We use intensified radiosonde observation data at Bengkulu during December 2017 and examine the relation between gravity wave activities and background state. The results showed that the heat flux of the gravity waves is proportional to the vertical shear of the background zonal wind. From the relation between gravity wave energy and Richardson number, it is suggested that the gravity waves having large amplitude modify the background state around 15 km.

A Simplified Model to Predict Oxygen Attenuation on Earth-Space Links

A simplified yet accurate model to predict oxygen attenuation for Earth-space applications (10–350 GHz range) is presented in this contribution. The model is developed by taking advantage of an extensive set of high-resolution radiosonde observations (RAOBS) collected in several sites worldwide. It predicts the statistics of oxygen attenuation along the path by retaining the accurate formulation for the specific oxygen attenuation included in the Liebe MPM93 model, but it relies on simplified meteorological input values (namely the mean yearly ground temperature and the statistics of the ground water vapor content), rather than on full atmospheric vertical profile. Tested against attenuation estimates obtained from Liebe MPM93 model coupled with the mentioned RAOBS data, the model provides a very good prediction accuracy in the full 10–350 GHz range, which turns out to be almost independent of the considered site.

Evaluation of model‐generated vertical profiles of meteorological variables: method and initial results

ABSTRACTMeteorological centres compare global and large‐scale regional model output versus radiosonde data more or less continuously for specific models and also make inter‐model comparisons. They normally provide comparisons of meteorological variables at standard pressure levels, and similar comparisons for finer‐scale models may be found as output from field tests and other experiments. Additional means to evaluate vertical profiles derived from model output more fully should help provide a more complete evaluation of model output compared with observations. Here, two versions of a program to produce vertical profiles of meteorological variables in terms of user input heights or pressure levels are developed, and integrated mean value profiles of the variables for layers defined by those heights or pressures are generated. Output profiles were entered into spreadsheets for calculation of the derived variables of density and vector wind speed. The level and mean layer values from the Weather Research and Forecasting model (version 3.6.1) were compared with co‐incident World Meteorological Organization radiosonde observation data and the differences were computed for several variables. The methods developed here may be used for a variety of model‐generated and observed vertical profiles with only minimal changes, primarily to the input function.

Improving the Accuracy in Predicting Water-Vapor Attenuation at Millimeter-Wave for Earth-Space Applications

This contribution focuses on improving the accuracy of the simplified method currently recommended by the ITU-R for the prediction of water-vapor attenuation at millimeter-wave on Earth-space links (Annex 2, paragraph 2.3 of recommendation ITU-R P.676-10), which receives as input only the local integrated water-vapor content $V$ . The main improvement to such model originates from taking into account the dependence of the water-vapor mass absorption coefficient $a_{V}$ on the reference site altitude, which is investigated by taking advantage of an extensive set of radiosonde observations (RAOBS) collected in several sites worldwide and characterized by high accuracy and reliability. Tested against attenuation estimates obtained from the mass absorption models coupled with the mentioned RAOBS data, the model’s prediction accuracy turns out to improve significantly with respect to the current recommendation and to be less dependent both on the operational frequency (20–100 GHz range) and on the considered site.

Using NWP Reanalysis Data for Radiometric Calibration in Electromagnetic Wave Propagation Experiments

Extensive datasets distributed by the European Centre for Medium-range Weather Forecast (ECMWF) are used to calculate retrieval coefficients for dual-channel radiometers in 14 sites spread across Europe, where databases of high-resolution RAdiosonde OBServations (RAOBSs) are available. RAOBSs are employed as the reference to assess the results obtained from ECMWF products, both in terms of single radiometric coefficients and in terms of statistics of integrated water vapor, integrated liquid water, and total atmospheric attenuation retrieved from radiometric measurements collected in one site close to Milan, Italy. The findings suggest that NWP products can be successfully used to calibrate radiometers when no appropriate RAOBS data are available.

Effectiveness of multisite diversity schemes to support optical systems in scientific missions

This contribution investigates the effectiveness of optical communication links in enabling high-speed data transfer from deep-space (DS) probes directly to Earth ground stations. In particular, the propagation impairments induced by clouds are estimated by exploiting long-term radiosonde observation data collected in some European sites. The impact of different cloud types on optical links operating at 1.55 μm is first quantified in terms of total path attenuation, and afterward, the implementation of multisite diversity schemes is discussed to counteract the extremely high attenuation levels caused by clouds. Results show that a three-site diversity system with target availability of 90% allows reduction of the link margin to counteract cloud attenuation from at least 40 dB to ∼6 dB, which makes optical communications a viable option also for DS missions.

New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product

According to the radiance-based (R-based) validation of the collection-5 or version-5 (C5 or V5) Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) land-surface temperature (LST) level-2 products at 42 sites in a wide LST range in different seasons and years, the LST errors are within ±2K (within ±1K in most cases) for all the sites but six bare soil sites. The V5 LSTs are underestimated by more than 2K and up to 4.5K at the desert site near In-salah, Algeria. Three refinements were implemented in the V6.3.0 daily LST Product Generation Executive (PGE)16 code: 1) refine the original viewing angle dependent split-window algorithm by adding two sets of coefficients separately for retrieval of daytime and nighttime LSTs at bare soil pixels in the hot and warm bare soil zone (HAWBSZ) within latitude range from −38° to 49.5°, 2) adjust the emissivity difference in bands 31 and 32 for bare soil pixels in HAWBSZ, and 3) incorporate the new refined split-window algorithm into the day/night algorithm for retrieving surface emissivity and temperature values at 6km grids in HAWBSZ. The V6.3.0 PGE16 code was tested with C6 Aqua and Terra MODIS input data over a period of one year or longer in selected tile regions. The resulting C6 level-2 LST products were evaluated at five bare soil sites in north Africa, where radiosonde observation data for atmospheric temperature and water vapor profiles are available, with 12 R-based validation data sets as follows: the mean LST error is within ±0.6K in 10 validate data sets, 0.8K in one data set (for daytime LSTs at SVU site) and 1.9K in another set (for daytime LSTs at Farafra site). The standard deviation of the C6 LST validation errors is less than 0.5K in all the 12 validation data sets but the data set for daytime LSTs at Farafra site at 0.7K. Statistical and viewing angle dependence analyses of the retrieved surface emissivity values also indicate that the C6 level-3 LST products are much better than the previous C4.1 and C5 products.

The Layered Structure of the Winter Atmospheric Boundary Layer in the Interior of Alaska

AbstractThe high-latitude winter atmospheric boundary layer of interior Alaska continually exhibits a complex layered structure as a result of extreme meteorological conditions. In this paper the occurrence of elevated inversions (EI), surface-based inversions (SBI), and stratified layers in the sub-Arctic from January 2000 to December 2009 is reported. This statistical analysis is based on radiosonde observation data from the Fairbanks National Weather Service station complemented by Winter Boundary Layer Experiment observations in the period 2010–11. This study found that SBIs occurred 64% of the time. An SBI occurred in combination with one, two, three, or four simultaneous EIs 84.86%, 48.49%, 21.23%, and 7.99% of the time, respectively, in 2326 total cases. The calculated mean SBI height was 377 m; EIs occurred at 1231, 2125, 2720, and 3125 m, respectively. This analysis was able to discriminate between locally controlled inversion layers and synoptic-dependent inversions and to identify their formation mechanisms. It was found that, in the presence of an SBI layer, the first EI layer formed 35.8% of the time under anticyclonic conditions at a mean height of 1249 m and 22% of the time in warm-air-advection situations at a mean height of 1049 m. The remaining 23.4% resulted from combined synoptic situations, and 18.8% were unclassified.

Radiosonde Sensors Bias in Precipitable Water Vapor From Comparisons With Global Positioning System Measurements

In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, for the years of 2006, 2008, 2010, and analyzed the radiosonde seasonal, diurnal bias according to radiosonde sensor types. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. Overall, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the nighttime except for 2006 winter, and in comparison for summer, RS92-SGP sensor showed the highest quality.

Analysis of Radiosonde Daily Bias by Comparing Precipitable Water Vapor Obtained from Global Positioning System and Radiosonde

In this study, we compared the precipitable water vapor (PWV) data derived from the radiosonde observation data at Sokcho Observatory and the PWV data at Sokcho Global Positioning System (GPS) Observatory provided by Korea Astronomy and Space Science Institute, from 0000 UTC, June 1, 2007 to 1200 UTC, May 31, 2009, and analyzed the radiosonde bias between the day and the night. In the scatter diagram of the daytime and nighttime radiosonde PWV data and the GPS PWV data, dry bias was found in the daytime radiosonde observation as known in the previous study. In addition, for all the rainfall events, the tendency that the wet bias of the radiosonde PWV increased as the GPS PWV decreased and the dry bias of the radiosonde PWV increased as the GPS PWV increased was significantly less distinctive in nighttime than in daytime. The quantitative analysis of the bias and error of the radiosonde PWV data showed that the mean bias decreased in the second year, regardless of nighttime or daytime rainfall, and the non-rainfall root mean square error (RMSE) was similar to that of the previous studies, while the rainfall RMSE was larger to a certain extent.