Characterization and Corrections of Relative Humidity Measurement from Meteomodem M10 Radiosondes at Midlatitude Stations

Jean-Charles Dupont,Damien Vignelles,Gaelle Clain,Christophe Raux,Martial Haeffelin,Jordi Badosa

doi:10.1175/jtech-d-18-0205.1

Abstract

AbstractMeasurement of water vapor or humidity in the atmosphere is fundamental for many applications. Relative humidity measurements with a capacitive sensor in radiosondes are affected by several factors that need to be assessed and corrected. This work aims to address corrections for the main effects for the Meteomodem M10 radiosonde as a step to meet the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) requirements. The considered corrections are 1) the calibration correction; 2) a slow regime due to the slow diffusion of molecules through the sensor, especially at very high and very low relative humidity conditions; 3) the relative humidity sensor dependence on the gradient of temperature; and 4) the time lag at cold temperatures, which affects measurements in regions of strong relative humidity gradients. These corrections were tested for 26 nighttime and 25 daytime radiosondes in two midlatitude locations for which both Meteomodem M10 and Vaisala RS92 measurements were available. The results show that, after correcting for the four effects, M10 relative humidity measurements are, on average, consistent with the Vaisala RS92 relative humidity values within 2% RH at all altitudes for the nighttime launches (against 6% RH before the correction) and within 5% RH at all altitudes for the daytime launches (against 9% RH before the correction).

Highlights

Measurement of water vapor or humidity in the atmosphere is fundamental for many applications (Bojinski et al 2014)
To account for the instantaneous effect of clouds, solar fluxes and convection effect that are shown on Fig. 5, we consider in this study the instantaneous value of the temperature difference between the air and the relative humidity sensor (RHS) rather than daily or annual parametrical model
The corrections applied on the dataset are the following: 1) a correction for calibration, applied to the raw data of the Observatoire de Haute Provence (OHP) campaign, 2) a slow-regime correction, based on the observed behavior of the sensor when responding to a step change in RH, FIG. 8

Summary

Introduction

Measurement of water vapor or humidity in the atmosphere is fundamental for many applications (Bojinski et al 2014). Accurate humidity measurements from the ground to the top of the troposphere and lower stratosphere are necessary to prevent spurious drying or moistening of the atmosphere simulated in numerical weather prediction models (Seidel et al 2009). Such measurements are necessary to better understand the role of water vapor in climate feedback, to study the life cycle of anthropogenic clouds such as contrails, and to quantify the state of deliquescence of atmospheric aerosols, just to name a few among many other fields of investigation. Vertical profiles of temperature and humidity can be used to calibrate (error and uncertainty) different types of satellites with active and passive remote sensing instruments (Zou et al 2013).

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