Statistical Characteristics of Atmospheric Conditions related to Radar Beam Propagation using Radiosonde Data in 2005-2006

Abstract Simulation of radar beam propagation is an important component of numerous radar applications in meteorology, including height assignment, quality control, and especially the so-called radar forward operator. Although beam propagation in the atmosphere depends on the refractive index and its vertical variation, which themselves depend on the actual state of the atmosphere, the most common method is to apply the 4/3 earth radius model, based on climatological standard conditions. Serious deviations from the climatological value can occur under so-called ducting conditions, where radar beams at low elevations can be trapped or propagate in a waveguide-like fashion, such that this model is unsuitable in this case. To account for the actual atmospheric conditions, sophisticated methods have been developed in literature. However, concerning the practical implementation of these methods, it was determined that the description in the literature is not always complete with respect to possible pitfalls for practical implementations. In this paper, a revised version of an existing method (one example for the above-mentioned “pitfall” statement) is introduced that exploits Snell’s law for spherically stratified media. From Snell’s law, the correct sign of the local elevation is a priori ambiguous, and the revised method explicitly applies (i) a total reflection criterion and (ii) another ad hoc criterion to solve the problem. Additionally, a new method, based on an ordinary differential equation with respect to range, is proposed in this paper that has no ambiguity. Sensitivity experiments are conducted to investigate the properties of these three methods. The results show that both the revised and new methods are robust under nonstandard conditions. But considering the need to catch an elevation sign ambiguity in the revised method (which cannot be excluded to fail in rare instances), the new method is regarded as more robust and unproblematic, for example, for applications in radar forward operators.

Download Full-text

Radar Quality Index for a Mosaic of Radar Reflectivity over Chao Phraya River Basin, Thailand

Applied Environmental Research ◽

10.35762/aer.2020.42.3.8 ◽

2020 ◽

pp. 92-104

Author(s):

Nattapon Mahavik ◽

Sarintip Tantanee

Keyword(s):

River Basin ◽

Quality Index ◽

Beam Propagation ◽

Weather Radar ◽

Radar Reflectivity ◽

Temporal Information ◽

Radar Beam ◽

Spatio Temporal ◽

Chao Phraya River ◽

Application Fields

The weather radar is one of the tools that can provide spatio-temporal information for nowcast which is useful for hydro-meteorological disasters warning and mitigation system. The ground-based weather radar can provide spatial and temporal information to monitor severe storm over the risky area. However, the usage of multiple radars can provide more effective information over large study area where single radar beam may be blocked by surrounding terrain Even though, the investigation of the sever storm physical characteristics needs the information from multiple radars, the mosaicked radar product has not been available for Thai researcher yet. In this study, algorithm of mosaicked radar reflectivity has been developed by using data from ground-based radar of Thai Meteorological Department over the Chao Phraya river basin in the middle of Thailand. The Python script associated with OpenCV and Wradlib libraries were used in our investigations of the mosaicking processes. The radar quality index (RQI) field has been developed by implementing an equation of a quality radar index to identify the reliability of each mosaicked radar reflectivity pixels. First, the percentage of beam blockage is computed to understand the radar beam propagation obstructed by surrounding topography in order to clarify the limitations of the observed beam on producing radar reflectivity maps. Second, the elevation of beam propagation associated with distance field has been computed. Then, these three parameters and the obtained percentage of beam blockage are utilized as the parameters in the equation of RQI. Finally, the detected radar flare, non-precipitating radar area, has been included to the RQI field. Then, the RQI field has been applied to the extracted radar reflectivity to evaluate the quality of mosaicked radar reflectivity to inform end user in any application fields over the Chao Phraya river basin.

Download Full-text

Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

Atmosphere ◽

10.3390/atmos12121619 ◽

2021 ◽

Vol 12 (12) ◽

pp. 1619

Author(s):

Yingsai Ma ◽

Xianhong Meng ◽

Yinhuan Ao ◽

Ye Yu ◽

Guangwei Li ◽

...

Keyword(s):

Boundary Layer ◽

Soil Moisture ◽

Atmospheric Boundary Layer ◽

Loess Plateau ◽

Atmospheric Stability ◽

Heat Fluxes ◽

Radiosonde Data ◽

Atmospheric Conditions ◽

The Loess Plateau ◽

The Impact

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.

Download Full-text

Tropopause and jetlet characteristics in relation to thunderstorm development over Cyprus

Advances in Geosciences ◽

10.5194/adgeo-23-113-2010 ◽

2010 ◽

Vol 23 ◽

pp. 113-117

Author(s):

A. Orphanou ◽

K. Nicolaides ◽

D. Charalambous ◽

P. Lingis ◽

S. C. Michaelides

Keyword(s):

Wind Direction ◽

The Other ◽

Statistical Characteristics ◽

Radiosonde Data ◽

Data Sets ◽

Other Hand ◽

The One

Abstract. In the present study, the monthly statistical characteristics of jetlet and tropopause in relation to the development of thunderstorms over Cyprus are examined. For the needs of the study the 12:00 UTC radiosonde data obtained from the Athalassa station (33.4° E, 35.1° N) for an 11-year period, from 1997 till 2007, were employed. On the basis of this dataset, the height and the temperature of the tropopause, as well as the height, wind direction and speed of the jetlet were estimated. Additionally, the days in the above period with observed thunderstorms were selected and the aforementioned characteristics of the jetlet and tropopause were noted. The two data sets were subsequently contrasted in an attempt to identify possible relations between thunderstorm development, on the one hand, and tropopause and jetlet characteristics, on the other hand.

Download Full-text

Antarctic Low-Tropospheric Humidity Inversions: 10-Yr Climatology

Journal of Climate ◽

10.1175/jcli-d-12-00446.1 ◽

2013 ◽

Vol 26 (14) ◽

pp. 5205-5219 ◽

Cited By ~ 21

Author(s):

Tiina Nygård ◽

Teresa Valkonen ◽

Timo Vihma

Keyword(s):

Water Vapor ◽

Climate Models ◽

Weather Prediction ◽

Temperature Inversion ◽

Statistical Characteristics ◽

The Arctic ◽

Radiosonde Data ◽

Atmospheric Moisture Budget ◽

Temperature Inversions ◽

The Antarctic

Abstract Humidity inversions are nearly permanently present in the coastal Antarctic atmosphere. This is shown based on an investigation of statistical characteristics of humidity inversions at 11 Antarctic coastal stations using radiosonde data from the Integrated Global Radiosonde Archive (IGRA) from 2000 to 2009. The humidity inversion occurrence was highest in winter and spring, and high atmospheric pressure and cloud-free conditions generally increased the occurrence. A typical humidity inversion was less than 200 m deep and 0.2 g kg−1 strong, and a typical humidity profile contained several separate inversion layers. The inversion base height had notable seasonal variations, but generally the humidity inversions were located at higher altitudes than temperature inversions. Roughly half of the humidity inversions were associated with temperature inversions, especially near the surface, and humidity and temperature inversion strengths as well as depths correlated at several stations. On the other hand, approximately 60% of the humidity inversions were accompanied by horizontal advection of water vapor increasing with height, which is also a probable factor supporting humidity inversions. The spatial variability of humidity inversions was linked to the topography and the water vapor content of the air. Compared to previous results for the Arctic, the most striking differences in humidity inversions in the Antarctic were a much higher frequency of occurrence in summer, at least under clear skies, and a reverse seasonal cycle of the inversion height. The results can be used as a baseline for validation of weather prediction and climate models and for studies addressing changes in atmospheric moisture budget in the Antarctic.

Download Full-text

Retrieval of upper tropospheric water vapor and upper tropospheric humidity from AMSU radiances

Atmospheric Chemistry and Physics ◽

10.5194/acp-5-2019-2005 ◽

2005 ◽

Vol 5 (8) ◽

pp. 2019-2028 ◽

Cited By ~ 3

Author(s):

A. Houshangpour ◽

V. O. John ◽

S. A. Buehler

Keyword(s):

Water Vapor ◽

Synthetic Data ◽

Weighted Average ◽

Radiosonde Data ◽

Atmospheric Conditions ◽

Data Set ◽

Microwave Sounding Unit ◽

Upper Tropospheric Humidity ◽

Microwave Sounding ◽

Average Relative Humidity

Abstract. A regression method was developed to retrieve upper tropospheric water vapor (UTWV in kg/m2) and upper tropospheric humidity (UTH in % RH) from radiances measured by the Advanced Microwave Sounding Unit (AMSU). In contrast to other UTH retrieval methods, UTH is defined as the average relative humidity between 500 and 200hPa, not as a Jacobian weighted average, which has the advantage that the UTH altitude does not depend on the atmospheric conditions. The method uses AMSU channels 6-10, 18, and 19, and should achieve an accuracy of 0.48 kg/m2 for UTWV and 6.3% RH for UTH, according to a test against an independent synthetic data set. This performance was confirmed for northern mid-latitudes by a comparison against radiosonde data from station Lindenberg in Germany, which yielded errors of 0.23 kg/m2 for UTWV and 6.1% RH for UTH.

Download Full-text

IASI temperature and water vapor retrievals – error assessment and validation

Atmospheric Chemistry and Physics ◽

10.5194/acp-9-6453-2009 ◽

2009 ◽

Vol 9 (17) ◽

pp. 6453-6458 ◽

Cited By ~ 73

Author(s):

N. Pougatchev ◽

T. August ◽

X. Calbet ◽

T. Hultberg ◽

O. Oduleye ◽

...

Keyword(s):

Water Vapor ◽

Assessment Model ◽

Statistical Characteristics ◽

Radiosonde Data ◽

Statistical Validation ◽

Data Set ◽

Error Covariance ◽

Recent Version ◽

Level 2 ◽

Good Agreement

Abstract. The METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI) Level 2 products comprise retrievals of vertical profiles of temperature and water vapor. The error covariance matrices and biases of the most recent version (4.3.1) of the L2 data were assessed, and the assessment was validated using radiosonde data for reference. The radiosonde data set includes dedicated and synoptic time launches at the Lindenberg station in Germany. For optimal validation, the linear statistical Validation Assessment Model (VAM) was used. The VAM uses radiosonde profiles as input and provides optimal estimate of the nominal IASI retrieval by utilizing IASI averaging kernels and statistical characteristics of the ensembles of the reference radiosondes. For temperatures above 900 mb and water retrievals above 700 mb, level expected and assessed errors are in good agreement. Below those levels, noticeable excess in assessed error is observed, possibly due to inaccurate surface parameters and undetected clouds/haze.

Download Full-text

The performance of Aeolus in heterogeneous atmospheric conditions using high-resolution radiosonde data

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-1393-2014 ◽

2014 ◽

Vol 7 (2) ◽

pp. 1393-1455

Author(s):

X. J. Sun ◽

R. W. Zhang ◽

G. J. Marseille ◽

A. Stoffelen ◽

D. Donovan ◽

...

Keyword(s):

Optical Properties ◽

High Resolution ◽

Relative Humidity ◽

Weather Prediction ◽

Error Variance ◽

Radiosonde Data ◽

Atmospheric Conditions ◽

Wind Profiles ◽

Height Assignment ◽

Aerosol Backscatter

Abstract. The ESA Aeolus mission aims to measure wind profiles from space. In preparation for launch we aim to assess the expected bias in retrieved winds from the Mie and Rayleigh channel signals induced by atmospheric heterogeneity. Observation biases are known to be detrimental when gone undetected in Numerical Weather Prediction (NWP). Aeolus processing equipment should therefore be prepared to detect heterogeneous atmospheric scenes and take measures, e.g., reject or reduce the weight of observations when used in NWP. Radiosondes provide the wind vector at about 10 m resolution. We present a method to simulate co-located cloud and aerosol optical properties from radiosonde observations. We show that cloud layers can be detected along the radiosonde path from radiosonde measured relative humidity and temperature. A parameterization for aerosol backscatter and extinction along the radiosonde path is presented based on a climatological aerosol backscatter profile and radiosonde relative humidity. The resulting high-resolution database of atmospheric wind and optical properties serves as input for Aeolus wind simulations. It is shown that Aeolus wind error variance grows quadratically with bin size and the wind-shear over the bin. Strong scattering aerosol or cloud layers may cause biases exceeding 1ms−1 for typical tropospheric conditions and 1 km Mie channel bin size, i.e., substantially larger than the mission bias requirement of 0.4 ms−1. Advanced level-2 processing of Aeolus winds including estimation of atmosphere optical properties is needed to detect regions with large heterogeneity, potentially yielding biased winds. Besides applicable for Aeolus the radiosonde database of co-located high-resolution wind and cloud information can be used for the validation of atmospheric motion wind vectors (AMV) or to correct their height assignment errors.

Download Full-text

Evaluation of retrieval methods for planetary boundary layer height based on radiosonde data

Atmospheric Measurement Techniques ◽

10.5194/amt-14-5977-2021 ◽

2021 ◽

Vol 14 (9) ◽

pp. 5977-5986

Author(s):

Hui Li ◽

Boming Liu ◽

Xin Ma ◽

Shikuan Jin ◽

Yingying Ma ◽

...

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Temperature Profile ◽

Planetary Boundary Layer ◽

Gradient Method ◽

Potential Temperature ◽

Radiosonde Data ◽

Atmospheric Conditions ◽

Wind Speed Profile ◽

Neutral Boundary Layer

Abstract. Radiosonde (RS) is widely used to detect the vertical structures of the planetary boundary layer (PBL), and numerous methods have been proposed for retrieving PBL height (PBLH) from RS data. However, an algorithm that is suitable under all atmospheric conditions does not exist. This study evaluates the performance of four common PBLH algorithms under different thermodynamic stability conditions based on RS data collected from nine sites in January–December 2019. The four RS algorithms are the potential temperature gradient method (GMθ), relative humidity (RH) gradient method (GMRH), parcel method (PM) and Richardson number method (RM). Atmospheric conditions are divided into convective boundary layer (CBL), neutral boundary layer (NBL) and stable boundary layer (SBL) on the basis of the potential temperature profile. Results indicate that SBL is dominant at nighttime, whilst CBL dominates at daytime. Under all and SBL classifications, PBLH retrieved by RM is typically higher than those retrieved using the other methods. On the contrary, the PBLH result retrieved by PM is the lowest. Under CBL and NBL classifications, PBLH retrieved by PM is the highest. PBLH retrieved by GMθ and GMRH is relatively low under all classifications. Moreover, the uncertainty analysis shows that the consistency of PBLH retrieved by different algorithms is more than 80 % under CBL and NBL classifications. By contrast, the consistency of PBLH is less than 60 % under SBL classification. The average profiles and standard deviations of wind speed and potential temperature under consistent and inconsistent conditions are also investigated. The results indicate that consistent cases are typically accompanied by evident atmospheric stratification, such as a large gradient in the potential temperature profile or a low-level jet in the wind speed profile. These results indicate that the reliability of the PBLH results retrieved from RS data is affected by the structure of the boundary layer. Overall, GMθ and RM are appropriate for CBL condition. GMθ and PM are recommended for NBL condition. GMθ and GMRH are robust for SBL condition. This comprehensive comparison provides a reference for selecting the appropriate algorithm when retrieving PBLH from RS data.

Download Full-text

Derivation of Clear-Air Turbulence Parameters from High-Resolution Radiosonde Data

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-16-0046.1 ◽

2017 ◽

Vol 34 (2) ◽

pp. 277-293 ◽

Cited By ~ 6

Author(s):

E. Martini ◽

A. Freni ◽

F. Cuccoli ◽

L. Facheris

Keyword(s):

Refractive Index ◽

High Resolution ◽

Potential Temperature ◽

Structure Constant ◽

Thin Layers ◽

Index Structure ◽

Radiosonde Data ◽

Atmospheric Conditions ◽

Air Turbulence ◽

The Impact

AbstractThe knowledge of atmospheric refractive index structure constant () profiles is fundamental to determine the intensity of turbulence, and hence the impact of the scintillation impairment on the signals propagating in the troposphere. However, their relation with atmospheric variables is not straightforward, and profiles based on statistical considerations are normally employed. This can be a shortcoming when performing simulations for which scintillation disturbances need to be consistent with the assumed atmospheric conditions. To overcome this limitation, this work describes a procedure to obtain an estimate of the refractive index structure constant profile of clear-air turbulence under given atmospheric conditions. The procedure is based on the application of the vertical gradient approach to high-resolution radiosonde data. Since turbulence is known to be confined to vertically thin layers, a preliminary identification of turbulent layers is required. This is accomplished by analyzing the profiles of the Richardson number. The value of the outer scale length is estimated using the Thorpe length calculated from the potential temperature profile. The procedure is applied to high-resolution radiosonde data that have been acquired from the Stratosphere–Troposphere Processes and their Role in Climate (SPARC) Data Center, and the obtained results are consistent with measured profiles previously published in the literature.

Download Full-text