Radiosonde Values Research Articles

Assessment of reanalysis datasets against radiosonde observation over the Eastern Mediterranean region

Four meteorological components (geopotential height Z, air temperature T, dew point temperature Td, and relative humidity RH) collected from ERA-5 and ERA-Interim were compared with the observations of nine radiosonde stations with different climatic changes, at different isobaric levels (850, 700, 500, and 200 hPa) during the period 2000–2017, in order to assess the accuracy of the aforementioned reanalysis datasets. The results showed that both reanalysis datasets have a strong correlation with the observed variables, except with dew point temperature and relative humidity in the upper troposphere. The mean values of geopotential height and temperature from both grid dataset are generally consistent with the radiosonde values, whereas considerable bias in the mean Td and RH exists and increases upwards. The study clearly proved that the reanalysis datasets can be used to compensate for the lack of radiosonde observation. Furthermore, air temperature (during 1959–2021) showed an increasing trend from the surface to the lower troposphere, while the temperature decreased in the upper troposphere and lower stratosphere. Finally in this study, the impact of the North Atlantic Oscillation Index (NAOI) on the air temperature was also examined, and a negative relationship was found between NAOI and temperature at the levels: surface, 850, 700, and 500 hPa, while a positive relationship was found, only in winter, at 200 hPa. At the level of 100 hPa, the correlation is positive for both seasons.

Validation of Aeolus wind products above the Atlantic Ocean

Abstract. In August 2018, the first Doppler wind lidar in space called Atmospheric Laser Doppler Instrument (ALADIN) was launched on board the satellite Aeolus by the European Space Agency (ESA). Aeolus measures profiles of one horizontal wind component (i.e., mainly the west–east direction) 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 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 in 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 prove that Aeolus is able to measure horizontal wind speeds in the nearly west–east direction. Good agreements with the radiosonde observations 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 and 3.3 m s−1, respectively, when compared to radiosonde values averaged to the vertical resolution of Aeolus. For the Mie winds, a systematic and random error of about 1 m s−1 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 2 months after launch, led to an underestimation of the maximum wind speed in the jet stream regions. In summary, promising first results of the first wind lidar space mission are shown and prove the concept of Aeolus for global wind observations.

Surface-Based Microwave Humidity Retrievals over the Equatorial Indian Ocean: Applications and Challenges

AbstractThe interactions between equatorial convection and humidity as a function of height, at a range of time scales, remain an important research frontier. The ability of surface-based microwave radiometry to contribute to such research is assessed using retrievals of the vertical structure of atmospheric humidity above the equatorial Indian Ocean, developed as part of the Dynamics of Madden–Julian Oscillation field campaign. The optimally estimated humidity retrievals are based on radiances at five frequencies spanning 20–30 GHz and are constrained by radiometer-derived water vapor paths that compare well to radiosonde values except in highly convective conditions. The moisture retrievals possess a robust 2 degrees of freedom, allowing the atmosphere to be treated as two independent layers. A mean bias of 1 g kg−1 contains a vertical structure that is removed in the assessments. The retrieved moisture profiles are able to capture humidity variability within two layer averages at intraseasonal, synoptic, and daily time scales. The retrieved humidity profiles at hourly scales are qualitatively correct under synoptically suppressed conditions but with an exaggerated vertical bimodality. The retrievals do not match radiosonde profiles within most of the day prior to/after convection. This analysis serves to better delineate applications for radiometers. Radiometers can usefully augment more expensive radiosonde networks for longer-term monitoring given careful cross-instrument calibration. At shorter time scales, a synergism with additional instruments can likely increase the realism of the retrievals.

Evaluation of Five Grid Datasets against Radiosonde Data over the Eastern and Downstream Regions of the Tibetan Plateau in Summer

In this study, horizontal wind (U and V), air temperature (T), and relative humidity (RH) modelled by the European Centre for Medium-Range Weather Forecasts Reanalysis Interim (ERA-Interim), the National Aeronautics and Space Administration (NASA) Modern Era Retrospective Analysis for Research and Applications (MERRA), the Japanese 55-year Reanalysis (JRA-55), the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), and the NCEP Final Operational Global Analysis data and the NCEP Final Operational Global Analysis data (NCEP-FNL) products have been compared with observations at 11 radiosonde stations over the eastern and downstream regions of the Tibetan Plateau (TP) from late June until the end of July during 2011 to 2015. The mean bias of all variables for the five gridded datasets (GDs) in the Sichuan Basin (SCB) is larger than that for the TP. The mean values of U, V, and T from each grid dataset are generally consistent with the radiosonde values, whereas considerable bias in the mean RH exists at upper levels. The diurnal variation of the mean bias and root-mean-square (RMS) error in the basin are stronger than those in the TP and the negative/positive peak usually occurs at 06:00 UTC and 18:00 UTC in the basin or at 12:00 UTC in the TP. The inter-annual variations in the basin are significantly stronger, and the maximum values of the variations usually occur at upper levels or near the surface, except for V. The weather conditions have a crucial influence on the performance of the gridded datasets. The mean bias and RMS error of T in the TP on cloudy days are obviously larger than those during sunny conditions. Considerable but unsteady differences occur in the mean bias and RMS error of U and V in different weather conditions. On average, the four variables in the TP are more sensible to the weather conditions.

Forecast indices from a ground-based microwave radiometer for operational meteorology

Abstract. Today, commercial microwave radiometer profilers (MWRPs) are robust and unattended instruments providing real-time, accurate atmospheric observations at ~ 1 min temporal resolution under nearly all weather conditions. Common commercial units operate in the 20–60 GHz frequency range and are able to retrieve profiles of temperature, vapour density, and relative humidity. Temperature and humidity profiles retrieved from MWRP data are used here to feed tools developed for processing radiosonde observations to obtain values of forecast indices (FIs) commonly used in operational meteorology. The FIs considered here include K index, total totals, KO index, Showalter index, T1 gust, fog threat, lifted index, S index (STT), Jefferson index, microburst day potential index (MDPI), Thompson index, TQ index, and CAPE (convective available potential energy). Values of FIs computed from radiosonde and MWRP-retrieved temperature and humidity profiles are compared in order to quantitatively demonstrate the level of agreement and the value of continuous FI updates. This analysis is repeated for two sites at midlatitude, the first one located at low altitude in central Europe (Lindenberg, Germany) and the second one located at high altitude in North America (Whistler, Canada). It is demonstrated that FIs computed from MWRPs well correlate with those computed from radiosondes, with the additional advantage of nearly continuous updates. The accuracy of MWRP-derived FIs is tested against radiosondes, taken as a reference, showing different performances depending upon index and environmental situation. Overall, FIs computed from MWRP retrievals agree well with radiosonde values, with correlation coefficients usually above 0.8 (with few exceptions). We conclude that MWRP retrievals can be used to produce meaningful FIs, with the advantage (with respect to radiosondes) of nearly continuous updates.

Raman Lidar for Meteorological Observations, RALMO – Part 2: Validation of water vapor measurements

Abstract. The Raman Lidar for Meteorological Observations (RALMO) was installed at the MeteoSwiss Regional Center of Payerne, Switzerland, in summer 2008. One of its aims is to provide continuous vertical profiles of tropospheric water vapor during day and night at a high temporal resolution. Twelve months (October 2009–September 2010) of lidar data are analyzed. During this period of time, the lidar produced 9086 profiles, representing 52.6% of the time (this figure reached 63.2% for the first 6 months of 2011). Under cloud-free conditions, half of the profiles reached more than 8610 m above ground level at night, and 4050 m during the day. In order to validate the capabilities of the instrument, the year of lidar data was compared to the collocated radiosondes. On average, lidar water vapor mixing ratio was found to be within 5 to 10% of radiosonde values up to 8 km at night, and within 3% up to 3 km during the day. Relative humidity results show an agreement within 2 and 5% for day and night, respectively. An integrated water vapor comparison also shows a good correlation with both radiosondes and GPS measurements: the lidar had a 4.2% dry bias compared to radiosondes and a 5.3% wet bias compared to GPS. These results validate the performance of the lidar and the humidity profiles with a 30 min time resolution.

Radiosonde humidity corrections and potential Atmospheric Infrared Sounder moisture accuracy

Although there are a number of sources of radiosonde data for validation of observations from other atmospheric sensors, routine operational sondes remain the main source for a large volume of data. In this study radiosonde moisture profiles are renormalized using Global Positioning System (GPS) Integrated Precipitable Water (IPW) vapor. The GPS‐adjusted radiosonde humidity profiles are then compared to the Atmospheric Infrared Sounder (AIRS) measurements. As a check, AIRS measurements are also compared with unadjusted radiosonde moisture profiles. It is shown that the GPS‐adjusted values are in better agreement with the AIRS measurements. On the basis of this result, the GPS‐adjusted radiosondes are used to assess the AIRS potential accuracy. This is valid because the errors in the AIRS measurements and the adjustments are independent. The GPS‐based renormalization of radiosonde humidity measurements produced a significant improvement in the agreement between AIRS and Vaisala RS 57 H type radiosondes in the lower troposphere, where much of the atmospheric water vapor resides. The adjustment also resulted in improved agreement between AIRS and radiosonde IPW estimates. The results showed a day/night bias in the radiosonde values as compared to the GPS and the AIRS values, demonstrating the potential use of the technique for evaluating and correcting this bias. Established corrections for humidity errors also have been applied to some operational radiosonde observations, specifically the published temperature correction developed for the Vaisala RS80 H type radiosonde. This correction produced a much smaller effect than the GPS adjustment.

Prediction of air pollution concentration using an in situ real time mixing height model

Mixing height (MH), which represents the dispersion depth of the atmospheric boundary layer, is a crucial input parameter in air pollution models. However, there is enormous uncertainty in its estimation since it is not a directly measurable variable. Generally, MH is estimated from the twice daily radiosonde measurements from the nearest meteorological station, especially in developing countries. But, these extrapolated values cause severe errors in prediction since MH is site and time dependent. In this paper, a simple in situ mixing height growth (IMG) model, which can estimate onsite real time values of MH from readily available surface measurements of wind and temperature, is applied to some commonly used air pollution prediction models. Box models (BM) are often used for large-scale predictions, but assume a constant lid height, though their accuracy is highly dependant upon its variation. IMG was applied to a photochemical box model, since ozone formation is strongly dependent upon insolation and is controlled by real time values of MH. The ozone concentrations predicted by IMG–BM showed a 13% improvement as compared to those estimated from the usual extrapolated radiosonde values. Further, gaussian diffusion model (GDM) is recommended in India and many other countries for regulatory use. Application of IMG to GDM for industries showed that the IMG model considerably improves the prediction accuracy and can be used in a cost effective manner.

Chlorine activation during the early 1995–1996 Arctic winter

The coupling of temperature, aerosol area density, and chlorine activation is studied by comparing values from a three‐dimensional chemical transport model with observed temperature, aerosol area density, and ClO data in the Arctic for the time period December 1, 1995, to January 9, 1996. The three‐dimensional model uses United Kingdom Meteorological Office (UKMO) winds and temperatures, run on pressure surfaces between 316 and 0.31 hPa, and the model results are examined at 100, 68, 46, 31, and 21 hPa. Radiosonde values are compared to individual UKMO temperature values to assess the impact of model temperature errors upon heterogeneous chemistry reaction probabilities. Polar Ozone and Aerosol Measurement (POAM II) aerosol extinction values are transformed into area density values and compared to model daily averaged time trends. The model is run with gas phase chemistry only, gas phase plus sulfate aerosol chemistry, and the case where gas phase, sulfate aerosol, and polar stratospheric cloud reactions are active. Results from these calculations are used to examine the sensitivity of chlorine activation to temperature biases, area density uncertainties, and the effects of the reaction paths OH + ClO → HCl + O2 (4% yield) and HO2 + ClO → HCl + O3 (4% yield). Sulfate aerosol is demonstrated to be very effective in activating chlorine in the Arctic polar vortex. Time trends of five‐day averages of model and Upper Atmosphere Research Satellite (UARS) Microwave Limb Sounder (MLS) version 4 ClO over extended regions inside and outside the vortex at 21 and 46 hPa agree within the experimental error.

A statistical study of underestimates of wind speeds by VHF radar

Abstract. Comparisons are made between horizontal wind measurements carried out using a VHF-radar system at Aberystwyth (52.4°N, 4.1°W) and radiosondes launched from Aberporth, some 50 km to the south-west. The radar wind results are derived from Doppler wind measurements at zenith angles of 6° in two orthogonal planes and in the vertical direction. Measurements on a total of 398 days over a 2-year period are considered, but the major part of the study involves a statistical analysis of data collected during 75 radiosonde flights selected to minimise the spatial separation of the two sets of measurements. Whereas good agreement is found between the two sets of wind direction, radar-derived wind speeds show underestimates of 4–6% compared with radiosonde values over the height range 4–14 km. Studies of the characteristics of this discrepancy in wind speeds have concentrated on its directional dependence, the effects of the spatial separation of the two sets of measurements, and the influence of any uncertainty in the radar measurements of vertical velocities. The aspect sensitivity of radar echoes has previously been suggested as a cause of underestimates of wind speeds by VHF radar. The present statistical treatment and case-studies show that an appropriate correction can be applied using estimates of the effective radar beam angle derived from a comparison of echo powers at zenith angles of 4.2° and 8.5°.

A statistical study of underestimates of wind speeds by VHF radar

Comparisons are made between horizontal wind measurements carried out using a VHF-radar system at Aberystwyth (52.4°N, 4.1°W) and radiosondes launched from Aberporth, some 50 km to the south-west. The radar wind results are derived from Doppler wind measurements at zenith angles of 6° in two orthogonal planes and in the vertical direction. Measurements on a total of 398 days over a 2-year period are considered, but the major part of the study involves a statistical analysis of data collected during 75 radiosonde flights selected to minimise the spatial separation of the two sets of measurements. Whereas good agreement is found between the two sets of wind direction, radar-derived wind speeds show underestimates of 4–6% compared with radiosonde values over the height range 4–14 km. Studies of the characteristics of this discrepancy in wind speeds have concentrated on its directional dependence, the effects of the spatial separation of the two sets of measurements, and the influence of any uncertainty in the radar measurements of vertical velocities. The aspect sensitivity of radar echoes has previously been suggested as a cause of underestimates of wind speeds by VHF radar. The present statistical treatment and case-studies show that an appropriate correction can be applied using estimates of the effective radar beam angle derived from a comparison of echo powers at zenith angles of 4.2° and 8.5°.

An Assessment of VAS-Derived Retrievals and Parameters Used in Thunderstorm Forecasting

VAS satellite retrievals and derived parameters used in forecasting severe local storms were evaluated against corresponding radiosonde values. VAS products were also compared with the first-guess input to the retrieval algorithm. The evaluation methodology was to pair each radiosonde observation with the closest VAS retrieval within 50 km during a four-month period in 1986. VAS temperatures agreed closely with radiosonde values; dewpoints showed less agreement. Sounding differences were poorly correlated with the number of pixels from which the retrievals were prepared. VAS discrepancies usually were not well correlated with first-guess errors. Horizontal gradients of VAS products were stronger than those from radiosondes. VAS precipitable water agreed better with ground truth than did dewpoints at individual levels, but VAS thicknesses were not much improved. Results for severe storms forecasting parameters indicated that discrepancies increased with the amount of manipulation required during computation. The lifted index showed the best agreement; positive bouyant energy showed poor comparisons.