Abstract

Abstract. The new ground-based 22 GHz spectrometer, VESPA-22 (water Vapor Emission Spectrometer for Polar Atmosphere at 22 GHz) measures the 22.23 GHz water vapor emission line with a bandwidth of 500 MHz and a frequency resolution of 31 kHz. The integration time for a measurement ranges from 6 to 24 h, depending on season and weather conditions. Water vapor spectra are collected using the beam-switching technique. VESPA-22 is designed to operate automatically with little maintenance; it employs an uncooled front-end characterized by a receiver temperature of about 180 K and its quasi-optical system presents a full width at half maximum of 3.5∘. Every 30 min VESPA-22 measures also the sky opacity using the tipping curve technique. The instrument calibration is performed automatically by a noise diode; the emission temperature of this element is estimated twice an hour by observing alternatively a black body at ambient temperature and the sky at an elevation of 60∘. The retrieved profiles obtained inverting 24 h integration spectra present a sensitivity larger than 0.8 from about 25 to 75 km of altitude during winter and from about 30 to 65 km during summer, a vertical resolution from about 12 to 23 km (depending on altitude), and an overall 1σ uncertainty lower than 7 % up to 60 km altitude and rapidly increasing to 20 % at 75 km. In July 2016, VESPA-22 was installed at the Thule High Arctic Atmospheric Observatory located at Thule Air Base (76.5∘ N, 68.8∘ W), Greenland, and it has been operating almost continuously since then. The VESPA-22 water vapor mixing ratio vertical profiles discussed in this work are obtained from 24 h averaged spectra and are compared with version 4.2 of concurrent Aura/Microwave Limb Sounder (MLS) water vapor vertical profiles. In the sensitivity range of VESPA-22 retrievals, the intercomparison from July 2016 to July 2017 between VESPA-22 dataset and Aura/MLS dataset convolved with VESPA-22 averaging kernels shows an average difference within 1.4 % up to 60 km altitude and increasing to about 6 % (0.2 ppmv) at 72 km.

Highlights

  • The polar atmosphere is a very complex system in which water vapor plays an important role

  • In July 2016, during the Study of the water VApor in the polar AtmosPhere (SVAAP) measurements campaign, a key part of a research effort devoted to the study of the impact of water vapor and clouds on the radiation budget at the ground, VESPA-22 was installed at the Thule High Arctic Atmospheric Observatory (THAAO) located at Thule Air Base (76.5◦ N, 68.8◦ W), Greenland

  • The uncertainty characterizing VESPA-22 retrieved profiles can be divided into four major contributions: (1) the uncertainty due to the linear approximation used in the optimal estimation, (2) the uncertainty due to the various parameters used in the spectra calibration and pre-processing, (3) the uncertainty due to spectral noise and potential artifacts, and (4) the uncertainty introduced by the use of the second-order polynomial in the retrieval process

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Summary

Introduction

The polar atmosphere is a very complex system in which water vapor plays an important role. About 10 % of the surface warming measured during the last two decades can be ascribed to stratospheric water vapor, as shown by Solomon et al (2010). The characterization of the water vapor profile, in the stratosphere and mesosphere, is important to understand many chemical processes. The processes that lead to long-term variations in stratospheric and mesospheric water vapor are not completely understood. The comprehension of the change in climate that affects the Arctic and the peculiar characteristics of this region’s atmosphere calls for long-term measurements. For this task, ground-based microwave remote sensing is a powerful tool to measure water vapor profiles and total amount of precipitable water vapor (PWV). The instrument general features, the measurement physics and technique, a comparison between VESPA22 and the Aura/Microwave Limb Sounder (MLS) (Waters et al, 2006) version 4.2 datasets are discussed in this work

Instrumental setup
Measurement technique
Atmospheric opacity
Beam-switching technique
Calibration scheme
Tipping curve procedure
Retrieval process
Forward model and a priori profiles
Retrieval example
Retrieval uncertainty
Findings
Summary
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