Study of the dependence of long-term stratospheric ozone trends on local solar time

Reliable ozone trends after 2000 are essential to detect early ozone recovery. However, the long-term ground-based and satellite ozone profile trends reported in the literature show a high variability. There are multiple reasons for variability in the reported long-term trends such as the measurement timing and the dataset quality. The Payerne Switzerland microwave radiometer (MWR) ozone trends are significantly positive at 2 % to 3 % per decade in the upper stratosphere (5–1 hPa, 35–48 km), with a high variation with altitude. This is in accordance with the Northern Hemisphere (NH) trends reported by other ground-based instruments in the SPARC LOTUS project. In order to determine what part of the variability between different datasets comes from measurement timing, Payerne MWR and SOCOL v3.0 chemistry–climate model (CCM) trends were estimated for each hour of the day with a multiple linear regression model. Trends were quantified as a function of local solar time (LST). In the middle and upper stratosphere, differences as a function of LST are reported for both the MWR and simulated trends for the post-2000 period. However, these differences are not significant at the 95 % confidence level. In the lower mesosphere (1–0.1 hPa, 48–65 km), the 2010–2018 day- and nighttime trends have been considered. Here again, the variation in the trend with LST is not significant at the 95 % confidence level. Based on these results we conclude that significant trend differences between instruments cannot be attributed to a systematic temporal sampling effect. The dataset quality is of primary importance in a reliable trend derivation, and multi-instrument comparison analyses can be used to assess the long-term stability of data records by estimating the drift and bias of instruments. The Payerne MWR dataset has been homogenized to ensure a stable measurement contribution to the ozone profiles and to take into account the effects of three major instrument upgrades. At each instrument upgrade, a correction offset has been calculated using parallel measurements or simultaneous measurements by an independent instrument. At pressure levels smaller than 0.59 hPa (above ∼50 km), the homogenization corrections to be applied to the Payerne MWR ozone profiles are dependent on LST. Due to the lack of reference measurements with a comparable measurement contribution at a high time resolution, a comprehensive homogenization of the sub-daily ozone profiles was possible only for pressure levels larger than 0.59 hPa. The ozone profile dataset from the Payerne MWR, Switzerland, was compared with profiles from the GROMOS MWR in Bern, Switzerland, satellite instruments (MLS, MIPAS, HALOE, SCHIAMACHY, GOMOS), and profiles simulated by the SOCOL v3.0 CCM. The long-term stability and mean biases of the time series were estimated as a function of the measurement time (day- and nighttime). The homogenized Payerne MWR ozone dataset agrees within ±5 % with the MLS dataset over the 30 to 65 km altitude range and within ±10 % of the HARMonized dataset of OZone profiles (HARMOZ, limb and occultation measurements from ENVISAT) over the 30 to 65 km altitude range. In the upper stratosphere, there is a large nighttime difference between Payerne MWR and other datasets, which is likely a result of the mesospheric signal aliasing with lower levels in the stratosphere due to a lower vertical resolution at that altitude. Hence, the induced bias at 55 km is considered an instrumental artifact and is not further analyzed.

UAV-based Multispectral & Thermal dataset for exploring the diurnal variability, radiometric & geometric accuracy for precision agriculture

To explore the diurnal variations, radiometric and geometric accuracy of UAV-based data for precision agriculture, a comprehensive dataset was created in a one-day field campaign (21 June 2017). The multi-sensor data set covers wheat, barley & potato experimental fields, located in Wageningen University and Research (WUR) farm maintained by Unifarm. UAV-based images were collected with several sensors over the experimental area, starting from 7:25am and ending at 20:00pm local solar time. The dataset consists of images collected by 9 flights with senseFly MSP4C, 9 with Parrot Sequoia, 2 with Slant Range P3, 5 with DJI Zenmuse X3 NIR, 4 with the senseFly Thermo-map and 1 with the RGB Sony WX-220. Additionally, validation measurements at radiometric calibration plates and plant sample locations were taken with a Cropscan handheld spectrometer and a tec5 Handyspec spectrometer. The dataset consists of the validation measurements, the raw images and the processed orthomosaics (both with and without geometric correction).

Study of the dependence of stratospheric ozone long-term trends on local solar time

Multi-instrument comparison analyses are essential to assess the long-term stability of data records by estimating the drift and bias of instruments. The ozone profile dataset from the SOMORA microwave radiometer (MWR) in Payerne, Switzerland, was compared with profiles from the GROMOS MWR in Bern, Switzerland, satellite instruments (MLS, MIPAS, HALOE, SCHIAMACHY, GOMOS), and profiles simulated by the SOCOL v3.0 chemistry-climate model (CCM). The Payerne MWR dataset has been homogenized to ensure a stable measurement contribution to the ozone profiles and to take into account the effects of three major instrument upgrades. At pressure levels smaller than 0.59 hPa (above ~ 50 km), the homogenization corrections to be applied to the Payerne MWR ozone profiles are dependent on local solar time (LST). Due to the lack of reference measurements with a comparable measurement contribution at a high time resolution, a comprehensive homogenization of the sub-daily ozone profiles was possible only for pressure levels larger than 0.59 hPa. The long-term stability and mean biases of the time series were estimated as a function of the measurement time (day- and nighttime). The homogenized Payerne MWR ozone dataset agrees within ± 5 % with the MLS dataset over the 30 to 65 km altitude range and within ± 10 % of HARMOZ datasets over the 30 to 65 km altitude range. In the upper stratosphere, there is a large nighttime difference between Payerne MWR and other datasets, which is likely a result of the mesospheric signal aliasing with lower levels in the stratosphere due to a lower vertical resolution at that altitude. Hence, the induced bias at 55 km is considered an instrumental artefact and is not further analyzed and discussed. In the upper stratosphere (5–1 hPa, 35–48 km), the Payerne MWR trends are significantly positive at 2 to 3 %/decade. This is in accordance with the northern hemisphere (NH) trends reported by other ground-based instruments in the SPARC LOTUS project. The reason for variability in the reported long-term ground-based and satellite ozone profile trends has multiple possibilities. To determine what part of the variability comes from measurement timing, MWR trends were estimated for each hour of the day with a multiple linear regression model to quantify trends as a function of LST. In the mid- and upper stratosphere, differences as a function of LST are reported for both the MWR and simulated trends for the 2000–2016 period. However, these differences are not significant at the 95 % confidence level. In the lower mesosphere (1–0.1 hPa, 48–65 km), the 2010–2018 day- and nighttime trends have been considered. Here again, the variation of the trend with LST is not significant at the 95 % confidence level. Based on these results we conclude that trend differences between instruments cannot to be attributed to a systematic temporal sampling.

Solar-cycle, seasonal, and asymmetric dependencies of thermospheric mass density disturbances due to magnetospheric forcing

Short-term upper atmosphere variations due to magnetospheric forcing are very complex, and neither well understood nor capably modelled due to limited observations. In this paper, mass density variations from 2003–2013 of GRACE observations are isolated through the parameterization of annual, Local-Solar-Time (LST), and solar-cycle fluctuations using a Principal Component Analysis (PCA) technique and investigated in terms of magnetospheric drivers. The magnitude of high-frequency (

On the Solar Cycle Variation of the Solar Diurnal Anisotropy of Multi-TeV Cosmic-ray Intensity Observed with the Tibet Air Shower Array

We analyze the temporal variation of the solar diurnal anisotropy of the multi-TeV cosmic-ray intensity observed with the Tibet air shower array from 2000 to 2009, covering the maximum and minimum of the 23rd solar cycle. We comfirm that a remarkable additional anisotropy component is superposed on the Compton-Getting anisotropy at 4.0 TeV, while its amplitude decreases at higher energy regions. In constrast to the additional anisotropy reported by the Matsushiro experiment at 0.6 TeV, we find the residual component measured by Tibet at multi-TeV energies is consistent with being stable, with a fairly constant amplitude of 0.041% ± 0.003% and a phase at around 07.17 ± 00.16 local solar time at 4.0 TeV. This suggests the additional anisotropy observed by the Tibet experiment could result from mechanisms unrelated to solar activities.

A Solar Tracking System Based on Local Solar Time Integrated to Photovoltaic Systems

The performance of photovoltaic (PV) systems is highly influenced by the tilt angle of PV modules and the incidence of global solar irradiance, which may change the solar to electrical conversion efficiency. Some authors have addressed these uncertainties arising from PV solar generation by using mechanisms and methods in which solar tracking systems are integrated to PV systems. Since the advent of the internet of things (IoT), this solar tracking strategy has yet to meet the requirements of scalable distributed power systems that can seamlessly support the PV solar generation, mainly for remote monitoring and control. In this context, this paper aims at developing a prospective study devoted to examine fundamental concepts to implement solar tracking algorithms based on local solar time by using embedded technology from the IoT platform. Preliminary results evidenced an improvement of up to 38% in power generation performance for algorithm-driven PV modules compared to fixed PV modules.

Seasonal and Local Solar Time Variation of the Meridional Wind at 95 km from Observations of the 11.072-GHz Ozone Line and the 557.7-nm Oxygen Line

Ground-based spectrometers have been deployed to measure the concentration, velocity, and temperature of ozone in the mesosphere and lower thermosphere (MLT), using low-cost satellite television electronics to observe the 11.072-GHz line of ozone. The ozone line was observed at an altitude near 95 km at 38°N, 71°W using three spectrometers located at the Massachusetts Institute of Technology’s Haystack Observatory (Westford, Massachusetts), Chelmsford High School (Chelmsford, Massachusetts), and Union College (Schenectady, New York), each pointed south at 8° elevation. Observations from 2009 through 2014 were used to derive the nightly averaged seasonal variation of the 95-km altitude meridional wind velocity, as well as the seasonally averaged variation of the meridional wind with local solar time. The results indicate a seasonal trend in which the winds at 95 km are directed southward at about 10 m s−1 in the summer of the Northern Hemisphere and northward at about 10 m s−1 in the winter. Nighttime data from −5 to +5 local solar time show a gradual transition of the meridional wind velocity from about −20 to 20 m s−1. These variations correlate well with nighttime wind measurements using 557.7-nm optical airglow observations from the Millstone Hill high-resolution Fábry–Perot interferometer (FPI) in Westford.