Meteorological Observation System Research Articles

Enhancing meteorological data reliability: An explainable deep learning method for anomaly detection.

Accurate meteorological observation data is of great importance to human production activities. Meteorological observation systems have been advancing toward automation, intelligence, and informatization. Yet, instrumental malfunctions and unstable sensor node resources could cause significant deviations of data from the actual characteristics it should reflect. To achieve greater data accuracy, early detections of data anomalies, continuous collections and timely transmissions of data are essential. While obvious anomalies can be readily identified, the detection of systematic and gradually emerging anomalies requires further analyses. This study develops an interpretable deep learning method based on an autoencoder (AE), SHapley Additive exPlanations (SHAP) and Bayesian optimization (BO), in order to facilitate prompt and accurate anomaly detections of meteorological observational data. The proposed method can be unfolded into four parts. Firstly, the AE performs anomaly detections based on multidimensional meteorological datasets by marking the data that shows significant reconstruction errors. Secondly, the model evaluates the importance of each meteorological element of the flagged data via SHapley Additive exPlanation (SHAP). Thirdly, a K-sigma based threshold automatic delineation method is employed to obtain reasonable anomaly thresholds that are subject to the data characteristics of different observation sites. Finally, the BO algorithm is adopted to fine-tune difficult hyperparameters, enhancing the model's structure and thus the accuracy of anomaly detection. The practical implication of the proposed model is to inform agricultural production, climate observation, and disaster prevention.

Investigation into the Motion Characteristics and Impact Loads of Buoy Water Entry Under the Influence of Combined Waves and Currents

As a crucial component in marine monitoring, meteorological observation, and navigation systems, studying the motion characteristics and impact loads of buoy water entry is vital for their long-term stability and reliability. When deployed, buoys undergo a complex motion process, including the impact of entering the water and a stable floating stage. During the water entry impact phase, the motion characteristics and impact loads involve interactions between the buoy and the water, the trajectory of motion, and dynamic water pressure, among other factors. In this paper, the VOF model is used to calculate the buoy’s water entry motion characteristics, and then the STAR-CCM+&ABAQUS bidirectional fluid–structure interaction (FSI) method is used to calculate the water entry impact load of the buoy under different water surface conditions and different initial throwing conditions, considering the influence of the flow field on the structure and the influence of the structure deformation on the flow field. The study finds that under the influence of wave and current impacts, changes in wave height significantly affect the buoy’s heave motions. Under different parametric conditions, due to the specific direction of wave and current impacts, the buoy’s pitch amplitude is relatively more intense compared to its roll amplitude, yet both pitch and roll motions exhibit periodic patterns. The buoy’s pitch motion is sensitive to changes in the entry angle; even small changes in this angle result in significant differences in pitch motion. Additionally, the entry angle significantly impacts the peak vertical overload on the buoy. Instantaneous stress increases sharply at the moment of water entry, particularly at the joints between the crossplate and the upper and lower panels, and where the mast connects to the upper panel, creating peak stress concentrations. In these concentrated stress areas, as the entry speed and angle increase, the maximum equivalent stress peak at the monitoring points rises significantly.

Significant East‐West Electron Density Differences Occurring in Less Than 30° Longitude Over the Ocean During the Recovery Phase of a Strong Geomagnetic Storm in Solar Minimum

AbstractWe conducted observational studies of ionospheric responses to the geomagnetic storm on 12 May 2021. We selected three cases that the electron density altitude profiles observed by Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (COSMIC‐2) exhibited significant longitudinal differences in less than 30° longitudes. These cases occurred over the Atlantic Ocean and during the storm's recovery phase. All three cases show relatively weaker variations on the west side between disturbed and quiet time (<10%), while displaying pronounced positive/negative electron density variations on the east side (as large as 100%). GOLD and ICON observations illustrate that the thermospheric composition plays a minor role in the longitudinal differences, while neutral winds and disturbed electric fields make major contributions. Furthermore, significant longitudinal differences in E×B drift and neutral winds have also been observed, which will be part of the future work. This study provides unique insights into ionospheric responses within 30‐degree longitude range over the ocean.

Characteristics of Sporadic E Layer Occurrence in a Global Chemistry‐Climate Model: A Comparison With COSMIC‐Derived Data

AbstractThis study presents an analysis of sporadic‐E (Es) structures within WACCM‐X (the Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension), including electrodynamical transport of metallic ions. A set of selection criteria have been developed to identify Es layers in WACCM‐X output based on the total metal ion density in each model grid box. These criteria are used to create a climatology of Es, which is compared to Es occurrence rates derived from FORMOSAT/COSMIC‐1 (Constellation Observing System for Meteorology, Ionosphere, and Climate) radio‐occultation measurements. The novel identification algorithm analyses 2‐week time slices between altitudes of 90–150 km, with Es layer events identified where the three selection criteria are met. Distinct seasonal distributions in Es occurrence were observed that are consistent with previous studies, with peaks during summer and reduced frequencies during winter, alignment of Es with geomagnetic contours, and layers descending in altitude as a function of local time. While discrepancies exist between WACCM‐X and COSMIC data (WACCM‐X occurrence rates are a factor of ∼2 lower than COSMIC‐derived occurrence rates at mid‐latitudes), highlighting the ongoing challenges in modeling Es layers, this study enhances the modeling capabilities of sporadic Es and deepens our understanding of their formation; it establishes a basis for their enhanced integration into global climate models and facilitates further investigation of Es behavior under different atmospheric conditions, paving the way to improved prediction of the occurrence of Es.

The Semidiurnal Tidal Response of the Low Latitude Ionosphere to Northern Hemisphere Polar Vortex Strength (2020–2023) From COSMIC‐2 Global Ionospheric Specification

AbstractThis paper investigates the day‐to‐day global tidal variability in the ionosphere/thermosphere system due to fluctuations in the strength of the northern hemisphere stratospheric polar vortex. Using COSMIC‐2 (Constellation Observing System for Meteorology, Ionosphere, and Climate‐2) Global Ionospheric Specification data, ionospheric tides are derived, with the Northern Annular Mode (NAM) index indicating polar vortex variability. The semidiurnal migrating solar tide shows the largest response, with relative electron density in the F‐region significantly higher ( 60%) under a weak vortex and lower ( 20%) under a strong vortex, correlated at −0.58 with the NAM index. The study compares solar/geomagnetic forcing and vortex impacts using SD‐WACCM‐X (Specified Dynamics Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension) model runs. Findings suggest tidal modulation of the E‐region dynamo as the coupling mechanism. Our study can potentially improve ionospheric space weather predictability because the NAM index can be known a few days in advance.

Global Distribution of Ionospheric Topside Diffusive Flux and Midlatitude Electron Density Enhancement in Winter Nighttime

AbstractIonospheric topside diffusive flux is derived using Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occultation data, to investigate its global distribution and also its role in winter nighttime enhancement (WNE) of electron density. The flux of the winter hemisphere maintains downward throughout the night. It is much larger between and geomagnetic latitudes and keeps increasing until 22:00–00:00 LT. It peaks at W and E–E geographic longitudes during the December solstice, and at E during the June solstice. These features are similar to those of WNE in NmF2. Furthermore, the derived flux is applied as the upper boundary condition to run the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM). The simulated spatial‐temporal variations of WNE are consistent with the observations. The results indicate that downward plasma diffusion from the plasmasphere is the major mechanism of WNE, and the simulation quantifies its contribution.

Evaluation of Satellite-Derived Atmospheric Temperature and Humidity Profiles and Their Application as Precursors to Severe Convective Precipitation

This study evaluated the reliability of satellite-derived atmospheric temperature and humidity profiles derived from occultations of Fengyun-3D (FY-3D), the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), the Meteorological Operational Satellite program (METOP), and the microwave observations of NOAA Polar Orbital Environmental Satellites (POES) using various conventional sounding datasets from 2020 to 2021. Satellite-derived profiles were also used to explore the precursors of severe convective precipitations in terms of the atmospheric boundary layer (ABL) characteristics and convective parameters. It was found that the satellite-derived temperature profiles exhibited high accuracy, with RMSEs from 0.75 K to 2.68 K, generally increasing with the latitude and decreasing with the altitude. Among these satellite-derived profile sources, the COSMIC-2-derived temperature profiles showed the highest accuracy in the middle- and low-latitude regions, while the METOP series had the best performance in high-latitude regions. Comparatively, the satellite-derived relative humidity profiles had lower accuracy, with RMSEs from 13.72% to 24.73%, basically increasing with latitude. The METOP-derived humidity profiles were overall the most reliable among the different data sources. The ABL temperature and humidity structures from these satellite-derived profiles showed different characteristics between severe precipitation and non-precipitation regions and could reflect the evolution of ABL characteristics during a severe convective precipitation event. Furthermore, some convective parameters calculated from the satellite-derived profiles showed significant and rapid changes before the severe precipitation, indicating the feasibility of using satellite-derived temperature and humidity profiles as precursors to severe convective precipitation.

Investigating Tropical Cyclone Warm Core and Boundary Layer Structures with Constellation Observing System for Meteorology, Ionosphere, and Climate 2 Radio Occultation Data

The Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC-2) collects data covering latitudes primarily between 40 degrees north and south, providing abundant data for tropical cyclone (TC) research. The radio occultation data provide valuable information on the boundary layer. However, quality control of the data within the boundary layer remains a challenging issue. The aim of this study is to obtain a more accurate COSMIC-2 radio occultation (RO) dataset through quality control (QC) and use this dataset to validate warm core structures and explore the planetary boundary layer (PBL) structures of TCs. In this study, COSMIC-2 data are used to analyze the distribution of the relative local spectral width (LSW) and the confidence parameter characterizing the random error of the bending angle. An LSW less than 20% is set as a data QC threshold, and the warm core and PBL composite structures of TCs at three intensities in the Northwest Pacific Ocean are investigated. We reproduce the warm core intensity and warm core height characteristics of TCs. In the radial direction of the typhoon eyewall, the impact height of the PBL increases from 3.45 km to 4 km, with the tropopause ranging from 160 hPa to 100 hPa. At the bottom of the troposphere, the variations in the positive and negative bias between the RO-detected and background field bending angles correspond well to the PBL heights, and the variations in the positive bias between the RO-detected and background field refractivity reach 14%. This research provides an effective QC method and reveals that the bending angle is sensitive to the PBL height.

Speed and accuracy investigations of neural network algorithms for ionospheric modelling at an equatorial region

Neural networks are very efficient tools for modeling, including ionospheric modeling. The training algorithm is important for achieving the optimum performance of the trained network. This research is therefore meant to evaluate and compare the performances of ten neural network training algorithms based on their prediction accuracies, and the duration/times taken by each of the algorithms to establish the optimum result. The neural networks were trained using electron density measurements by Radio Occultation (RO) technique from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites. Data for the period 2006 through 2021 was used. The networks were trained using about 2.9 million data points collected from the Kano region, Nigeria (5-degree rectangular region around geographic: 12.00° N, 8.59° E) after performing data quality control. The training algorithms considered in the work include: Bayesian Regularization (BR); Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFG); Conjugate Gradient with Powell/Beale (CGB); Fletcher-Reeves Conjugate Gradient (CGF); Gradient descent with momentum and adaptive learning rate (GDX); Levenberg Marquardt (LM); One Step Secant (OSS); Polak-Ribiére Conjugate Gradient (CGP); Resilient Backpropagation (RP); and Scaled Conjugate Gradient (SCG). The results showed that the BR and the LM algorithms gave the best performances in minimizing the errors of prediction (the mean RMSEs are respectively 112 and 114 ×103 electrons/cm3), but the RP algorithm, which came third in terms of accuracy, was significantly faster than both the LM and BR algorithms. The worst-performing algorithm in terms of accuracy was the GDX algorithm, although it was the fastest algorithm. The BFG algorithm was the worst-performing algorithm in terms of a combination of speed and accuracy. The developed neural network model was validated using ionosonde electron density measurements obtained from Ilorin, Nigeria (geographic: 8.5° N, 4.5° E; geomagnetic: 1.8° S). A comparison of the neural network, the NeQuick, and the IRI model predictions relative to the ionosonde measurements indicate that the neural network model was the best-performing model; the NN model predictions minimized the mean absolute errors (MAEs) in ∼44% of 399 ionosonde profiles investigated, the IRI model did so in ∼32%, and the NeQuick did so in ∼24%. The MAEs of the NeQuick however exhibited the best (least) variance. In overall, the NN model gave the least (best) mean of the MAEs (∼73 × 103 cm−3), compared to ∼82 × 103 cm−3 given by both the NeQuick and the IRI models, further supporting the idea that neural networks are excellent for present-day ionospheric modeling.

Differences among the total electron content derived by radio occultation, global ionospheric maps and satellite altimetry

In recent years, significant progress has been in ionospheric modeling research through data ingestion and data assimilation from a variety of sources, including ground-based global navigation satellite systems, space-based radio occultation and satellite altimetry (SA). Given the diverse observing geometries, vertical data coverages and intermission biases among different measurements, it is imperative to evaluate their absolute accuracies and estimate systematic biases to determine reasonable weights and error covariances when constructing ionospheric models. This study specifically investigates the disparities among the vertical total electron content (VTEC) derived from SA data of the Jason and Sentinel missions, the integrated VTEC from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) and global ionospheric maps (GIMs). To mitigate the systematic bias resulting from differences in satellite altitudes, the vertical ranges of various VTECs are mapped to a standardized height. The results indicate that the intermission bias of SA-derived VTEC remains relatively stable, with Jason-1 serving as a benchmark for mapping other datasets. The mean bias between COSMIC and SA-derived VTEC is minimal, suggesting good agreement between these two space-based techniques. However, COSMIC and GIM VTEC exhibit remarkable seasonal discrepancies, influenced by the solar activity variations. Moreover, GIMs demonstrate noticeable hemispheric asymmetry and a degradation in accuracy ranging from 0.7 to 1.7 TECU in the ocean-dominant Southern Hemisphere. While space-based observations effectively illustrate phenomena such as the Weddell Sea anomaly and longitudinal ionospheric characteristics, GIMs tend to exhibit a more pronounced mid-latitude electron density enhancement structure.

Research on integrated LiDAR and multi-parameter detection of atmospheric transmittance, turbulence, and wind

An integrated LiDAR system has been reported, which can be used for simultaneous detection of atmospheric transmittance, turbulence, and wind along the same path. Through the integrated design of optics and mechanics, the size and weight of the system were effectively reduced. The comprehensive detection distance of atmospheric transmittance, atmospheric coherence length, and radial wind had also been achieved at least 4 kilometers. Comparative experiments have demonstrated that the detection results of the integrated LiDAR system and the near-surface meteorological observation system have standard deviations of less than 0.03 km−1 for extinction coefficient, 0.2 m/s for wind velocity, and 7.15 × 10−14 m−2/3 for C 2 n (atmospheric refractive index structure parameter), thus verifying the accuracy of the system detection. The reliability of the integrated LiDAR system was validated through six consecutive nights of continuous detection experiments, measuring three parameters simultaneously. Through analysis, the influence laws among atmospheric transmittance, coherence length, and wind were preliminarily explored. Significant variations in wind velocity can induce substantial fluctuations in atmospheric coherence length, and it is positively correlated with atmospheric transmittance. The integrated LiDAR system can provide a variety of reliable real-time detection data for further research on the laser transmission process in the atmosphere.

Investigation of the global climatologic performance of ionospheric models utilizing in-situ Swarm satellite electron density measurements

The Swarm constellation is a triplet of satellites, flying, since their final configuration reached in April 2014, at altitudes of about 420 to 490 km (the lower pair) and about 500 to 530 km (the upper satellite). All the three satellites provide in-situ measurements of the plasma density in the topside ionosphere using Langmuir Probe sensors onboard the Electrical Field Instrument. The present study is a comprehensive investigation into the climatologic performance of three ionospheric models when compared to the Swarm satellite in-situ measurements. The models are the International Reference Ionosphere (IRI) model, a quick run ionospheric electron density model (NeQuick), and a 3-dimensional electron density model based on artificial neural network training of COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites radio occultation measurements (3D-NN). The mean monthly quiet-time latitudinal profile of Swarm measurements was computed by binning the Swarm electron density measurements in 15-degree longitudes starting from longitude −180° in steps of 15° to 180°, and corresponding model predictions were obtained. The data used in the study covers the years 2014, 2016, 2019, and 2022, capturing various phases of the solar activity cycle. Results from the study show that modelled electron density predictions from all three climatologic models are fairly good representations of the Swarm satellite measurements, with some exceptions in which the models underestimate or overestimate the Swarm satellite values. The IRI model performed best at the northern hemisphere mid latitude, and it overestimated the Swarm measurements at altitudes of ∼ 450 km, especially at the southern hemisphere mid and high latitudes. The NeQuick performed best during the night times, and it overestimated the Swarm measurements, especially at the mid latitudes. The NeQuick was also observed to overestimate the Swarm measurements during the winter solstices at both hemispheres, which is June solstice in the southern hemisphere and December solstice in the northern hemisphere. Overall, the 3D-NN model most often performed better than the IRI model and the NeQuick, especially during the day times and during the high solar activity year (2014), but it underestimated the Swarm measurements, especially at the low and mid latitudes. For all categories explored in the study, the 3D-NN consistently performed better than the other two models. The NeQuick performed better than the IRI model at altitude of satellite B, while the IRI model performed slightly better than the NeQuick at altitude of satellites A and C. The NeQuick also performed better than the IRI model in the local time category, whereas the IRI model performed better than the NeQuick in categories of season, solar activity, and longitudinal sector.

Seasonal–Longitudinal Variability of Equatorial Plasma Bubbles Observed by FormoSat-7/Constellation Observing System for Meteorology Ionosphere and Climate II and Relevant to the Rayleigh–Taylor Instability

The FormoSat-7/Constellation Observing System for Meteorology, Ionosphere, and Climate II (FS7/COSMIC2) program has acquired over three hundred thousand equatorial plasma bubble (EPB) observations from 2019 to 2023 in the equatorial and near low-latitude regions. The huge FS7/COSMIC2 database offers an opportunity to perform statistical inspections of the proposed hypothesis on seasonal versus longitudinal variability of EPB occurrence rates relevant to the Rayleigh–Taylor (R-T) instability. The detected EPBs are distributed along the magnetic equator with a half width of ~20° in geomagnetic latitude. The obtained EPB occurrence rates in local time (LT) rose rapidly after sunsets, and could be deconstructed into two overlapped Gaussian distributions resembling a major peak around 23:00 LT and a minor peak around 20:20 LT. The two groups of Gaussian-distributed EPBs in LT were classified as first- and second-type EPBs, which could be caused by different mechanisms such as sporadic E (Es) instabilities and pre-reversal enhancement (PRE) fields. The obtained seasonal–longitudinal distributions of both types of EPBs presented two diffused traces of high occurrence rates, which happened near the days and longitudes when and where the angle between the two lines of magnetic declination and solar terminator at the magnetic equator was equal to zero. Finally, we analyzed the climatological and seasonal–longitudinal variability of EPB occurrences and compared the results with the physical R-T instability model controlled by Es instabilities and/or PRE fields.

Evaluation of the retrieved temperature and specific humidity from COSMIC-2 and FY-3D with Radiosonde, reanalysis data, and MetOp

The Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), as the follow-on mission to COSMIC, commenced observations from 25 June 2019. COSMIC-2, with its high signal-to-noise ratio (SNR) and excellent stability, is expected to outperform COSMIC in detecting atmospheric parameters while penetrating the lower atmosphere.Therefore, to verify and analyze the detection capability of COSMIC-2 occultation in the neutral atmosphere, we retrieved temperature and specific humidity from COSMIC-2 and FY-3D based on the Able integral and the one-dimensional variational method. The evaluations are carried out on retrieval parameters at different altitudes using official RO products, radiosonde, reanalysis data, and MetOp. A detailed analysis of errors in the evaluation process is provided. The RMSEs for COSMIC-2 temperature and specific humidity are less than 1.5 K and 36 % respectively when radiosonde as validation data. Compared to FY-3D, accuracy improved by 11.1 % and 18.5 % respectively. FY-3D shows better consistency in the evaluation of the RO official products and radiosonde. Temporal and spatial analysis reveals minimal seasonal differences but significant latitude influence on evaluation outcomes. In the evaluation of reanalysis data, COSMIC-2 temperature and NCEP performed well in the troposphere, with a correlation coefficient greater than 0.9. The RMSE of the COSMIC-2 temperature and specific humidity in the MERRA-2 evaluation increased by 50.59 % and 16.65 % over FY-3D. Besides, derived parameters are more consistent with MetOp than radiosonde. Moreover, the co-localization threshold and resampling have less than 0.1 K and 5 % impact on the accuracy of evaluating temperature and specific humidity.

Statistical analysis on orographic atmospheric gravity wave and sporadic E layer

In this study, we present the statistical features of gravity wave (GW) and sporadic E layer (ES) by using the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) data aboard the Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) satellite and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) radio occulation measurements during 2007–2018. Statistical analysis of occurrences of GW and ES shows that daytime GW and ES are frequently observed on the eastern sides of the Tibetan plateau during summer, while less consistency between nighttime GW and ES occurrences was presented in our observations. The concurrence of GW and ES shows that nearly 60% ES occurred simultaneously with local strong GW occurrence. These results provide observational evidence suggesting that the effect of strong GW activities is significant in the generation of ES.

GNSS signal ray-tracing algorithm for the simulation of satellite-to-satellite excess phase in the neutral atmosphere

Traditionally, GNSS space-based and ground-based estimates of tropospheric conditions are performed separately. It leads to limitations in the horizontal (e.g., a single space-based radio occultation profile covers a 300 km slice of the troposphere) and vertical resolution (e.g., ground-based estimates of troposphere conditions have spacing equal to stations’ distribution) of the tropospheric products. The first stage to achieve an integrated model is to create an effective 3D ray-tracing algorithm for the satellite-to-satellite (radio occultation) path reconstruction. We verify the consistency of the simulated data with the RO observations from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1) Data Analysis and Archive Center (CDAAC) in terms of excess phase and bending angle. The results show that our solution provides an effective RO excess phase, with a relative error varying from 35% at the height of 25–30 km (1.0–1.5 m) to 0.5% at heights 5–10 km (0.1–1 m) and 14 to 2% at heights below 5 km (2–14 m). The bending angle retrieval on simulated data attained for high-resolution ray-tracing, bias lower than 2% with respect to the observed bending angle. The optimal solution takes about 1 s for one transmitter–receiver pair with a tangent point below 5 km altitude. The high-resolution processing solution takes 3 times longer.

Intermittency of Gravity Wave Potential Energy Generated by Mountains Revealed from COSMIC-2 Observations

The intermittency of gravity wave potential energy (GWPE) in the upper troposphere and stratosphere was investigated using the Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2) temperature data over three typical mountains (Tibetan Plateau, Rocky Mountains, and Andes). These typical mountains have high sea level elevations but different land–sea contrast. The probability density function (PDF) of GWPE has the independent variable of GWPE and dependent variable of occurrence probability of GWPE over a region. Our analysis showed that the PDFs of GWPE over these three mountains roughly followed lognormal distributions in all heights and months. But, the key parameters (mean value and standard deviation) of lognormal distribution varied with heights and months. Above each mountain, the two key parameters exhibited similar temporal and spatial distributions. They had the largest values around the tropopause region, smaller values in the lower stratosphere (~20–30 km), and larger values in the upper stratosphere (~35–45 km). The intermittency of GWs is represented as the ratio of the GWPE at 50th percentile to the GWPE at 90th percentile. The weakest intermittency was at ~20–30 km (above the zonal mean winds of zero) over the Tibetan Plateau and Rocky Mountains in all months and over the Andes from November to March, respectively. Generally, the weakest intermittency (~0.4) occurred in the region where the key parameters were the smallest around summer. The key parameters of lognormal distribution were dominated by annual variation over the Andes throughout the height range, 8–50 km. However, the semiannual variations are also significant in the lower stratosphere over the Tibetan Plateau and Rocky Mountains. The seasonal variations in the intermittency were not as obvious as those of the key parameters. The lognormal distributions and the intermittencies derived here provide an observational constraint on the tunable parameters in GW parameterization schemes.

A Case Study of Ionospheric Storm‐Time Altitudinal Differences at Low Latitudes During the May 2021 Geomagnetic Storm

AbstractPrevious studies paid little attention to the ionospheric storm‐time altitudinal differences due to insufficiency of ionospheric measurements. In this work, multiple instrumental observations were used to investigate the ionospheric storm‐time response at low latitudes in the American and Asian‐Australian sectors during the May 2021 geomagnetic storm. The ground‐based Global Navigation Satellite Systems (GNSS) total electron content (TEC) and Low Earth Orbit (LEO) satellite topside TEC presented opposite (positive/negative) variations in the low‐latitude and equatorial region of both sectors during this storm. The electron density profiles from the Constellation Observing System for Meteorology, Ionosphere, and Climate‐2 (COSMIC‐2) and the Sanya Incoherent Scatter Radar showed a good agreement and well explained the opposite variations between GNSS TEC and LEO satellite topside TEC. The F2‐layer peak height (hmF2) and peak density (NmF2) displayed inverse variations, and the feature was present mostly in the regions between equatorial ionization anomaly crests. The combined modulation effects of the storm‐time zonal electric fields and the field‐aligned transports possibly resulted in the contrary variations of hmF2 and NmF2 in the low‐latitude and equatorial region, leading to the storm‐time altitudinal differences during this storm. Relatively, the storm‐time thermospheric composition disturbances might be a minor factor responsible for these differences.

Phenological characteristics of net ecosystem carbon exchange of Stipa krylovii steppe in Inner Mongolia, China and its remote sensing monitoring.

To accurately monitor the phenology of net ecosystem carbon exchange (NEE) in grasslands with remote sensing, we analyzed the variations in NEE and its phenology in the Stipa krylovii steppe and discussed the remote sensing vegetation index thresholds for NEE phenology, with the observational data from the Inner Mongolia Xilinhot National Climate Observatory's eddy covariance system and meteorological gradient observation system during 2018-2021, as well as Sentinel-2 satellite data from January 1, 2018 to December 31, 2021. Results showed that, from 2018 to 2021, NEE exhibited seasonal variations, with carbon sequestration occurring from April to October and carbon emission in other months, resulting in an overall carbon sink. The average Julian days for the start date (SCUP) and the end date (ECUP) of carbon uptake period were the 95th and 259th days, respectively, with an average carbon uptake period lasting 165 days. Photosynthetically active radiation showed a negative correlation with daily NEE, contributing to carbon absorption of grasslands. The optimal threshold for capturing SCUP was a 10% threshold of the red-edge chlorophyll index, while the normalized difference vegetation index effectively reflected ECUP with a threshold of 75%. These findings would provide a basis for remote sensing monitoring of grassland carbon source-sink dynamics.

Calibration of Swarm Ion Density, Drift, and Effective Mass Measurements

AbstractWe calibrate the Swarm Langmuir Probe Ion Drift, Density and Effective Mass (SLIDEM) products using the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC‐1) electron density measurements. SLIDEM combines electric current measurements from the Electric Field Instrument faceplate (situated on the ram‐facing side of the satellite) with ion admittance measurements from a spherical Langmuir probe to estimate ionospheric ion density, bulk ion drift parallel to the satellite trajectory in the polar regions, and effective ion mass at low and middle latitudes. SLIDEM processing includes an eight‐parameter empirical geometry model that expresses the corrections to the effective faceplate area and spherical probe radius arising from satellite‐plasma interactions. Validation of SLIDEM density by conjunctions with COSMIC density altitude profiles reveals systematic errors, with SLIDEM underestimating corresponding COSMIC data by around 10%. Using the same conjunctions to calibrate the SLIDEM density processor, a simple one‐parameter geometry model is obtained, which significantly reduces bias in ion density. This leads to reduced bias in the ion ram speed and in the effective mass, both of which are more consistent with empirical ionospheric models. We examined three models characterizing the variation of probe effective electrode current collection areas. Faceplate geometries are statistically indistinguishable from the physical faceplate cross section. Spherical Langmuir probe radius is effectively reduced by about 10% due to satellite‐plasma interactions. We recommend updating the SLIDEM processor to use a smaller value for the spherical probe's radius.