Atmospheric water vapour and its effect on aerosol Extinction at a coastal station – Visakhapatnam

Integrated atmospheric water vapour content. has been evaluated from the spectral optical depths around the PaT band of water vapour by making directly transmitted solar flux measurements at 800, 935 and 1025 nm. The temporal variation of the total precipitable water vapour shows significant seasonal variation with maximum during~ pre-monsoon and monsoon months and minimum during winter months. The integrated content shows a positive correlation with surface humidity parameters and the correlation is better during monsoon months compared to other seasons. The experimentally derived variations of water vapour are compared with the model variations formulated using radiosonde data. The aerosol extinctions derived from the, multi-spectral solar flux measurements in the visible and near IR regions increase with increasing atmospheric water vapour and this increase shows .a seasonal dependence the surface temperature also seems to affect the, aerosol extinction probably through Its effect on the mixing heights.

Water Vapour Assessment Using GNSS and Radiosondes over Polar Regions and Estimation of Climatological Trends from Long-Term Time Series Analysis

The atmospheric humidity in the Polar Regions is an important factor for the global budget of water vapour, which is a significant indicator of Earth’s climate state and evolution. The Global Navigation Satellite System (GNSS) can make a valuable contribution in the calculation of the amount of Precipitable Water Vapour (PW). The PW values retrieved from Global Positioning System (GPS), hereafter PWGPS, refer to 20-year observations acquired by more than 40 GNSS geodetic stations located in the polar regions. For GNSS stations co-located with radio-sounding stations (RS), which operate Vaisala radiosondes, we estimated the PW from RS observations (PWRS). The PW values from the ERA-Interim global atmospheric reanalysis were used for validation and comparison of the results for all the selected GPS and RS stations. The correlation coefficients between times series are very high: 0.96 for RS and GPS, 0.98 for RS and ERA in the Arctic; 0.89 for RS and GPS, 0.97 for RS and ERA in Antarctica. The Root-Mean-Square of the Error (RMSE) is 0.9 mm on average for both RS vs. GPS and RS vs. ERA in the Arctic, and 0.6 mm for RS vs. GPS and 0.4 mm for RS vs. ERA in Antarctica. After validation, long-term trends, both for Arctic and Antarctic regions, were estimated using Hector scientific software. Positive PWGPS trends dominate at Arctic sites near the borders of the Atlantic Ocean. Sites located at higher latitudes show no significant values (at 1σ level). Negative PWGPS trends were observed in the Arctic region of Greenland and North America. A similar behaviour was found in the Arctic for PWRS trends. The stations in the West Antarctic sector show a general positive PWGPS trend, while the sites on the coastal area of East Antarctica exhibit some significant negative PWGPS trends, but in most cases, no significant PWRS trends were found. The present work confirms that GPS is able to provide reliable estimates of water vapour content in Arctic and Antarctic regions too, where data are sparse and not easy to collect. These preliminary results can give a valid contribution to climate change studies.

Microwave Limb Sounder (MLS) observations of biomass burning products in the stratosphere from Canadian forest fires in August 2017

Forest fires in British Columbia in August 2017 caused a pyrocumulonimbus event that injected a polluted air mass into the lower stratosphere. The Microwave Limb Sounder (MLS) on the Aura satellite first observed the polluted air mass on 14 August 2017 and continued to observe it for 60 d (100 d in water vapour). We estimate the mass of CO injected into the stratosphere to be 2400 Gg. Events in which a fire injects its burning products directly into the stratosphere are rare: this is the third of four such events in the 16 years since the launch of Aura, the second largest of the four events, and the only one in the Northern Hemisphere. The other three events occurred in Australia in December 2006, February 2009 and from December 2019 to January 2020. Unlike the 2006 and 2009 events, but like the 2019–2020 event, the polluted air mass described here had a clearly elevated water vapour content: between 2.5 and 5 times greater than that in the surrounding atmosphere. We describe the evolution of the polluted air mass, showing that it rose to an altitude of about 24 km (31 hPa) and divided into several identifiable parts. In addition to CO and H2O, we observe enhanced amounts of HCN, CH3CN, CH3Cl and CH3OH with mixing ratios in the range to be expected from a variety of measurements in other biomass burning plumes. We use back trajectories and plume-dispersion modelling to demonstrate that the pollutants observed by MLS originated in the British Columbia fires, the likeliest source being at 53.2∘ N, 121.8∘ W at 05:20 UTC on 13 August 2017.

European GNSS troposphere monitoring for meteorological applications

Near real-time GNSS double-difference network processing is a traditional method still used within the EUMETNET EIG GNSS Water Vapour Programme (E-GVAP) for the atmosphere water vapour content monitoring in support of Numerical Weather Prediction. The standard production relies on estimating zenith tropospheric path delays (ZTDs) for GNSS ground stations with a 1-hour time resolution and a latency of 90 minutes. The Precise Point Positioning (PPP) method in real-time mode has reached the reliability and the accuracy comparable to the near real-time solution. The effectiveness of the PPP method relies on exploiting undifferenced observations from individual receivers, thus optimal use of all tracked systems, observations and signal bands, possible in-situ processing, high temporal resolution of estimated parameters and almost without any latency. The solution may implicitly include horizontal tropospheric gradients and slant tropospheric path delays for enabling the monitoring of a local asymmetry of the troposphere around each individual site. We have been estimating ZTD and gradients in real-time continuously since 2015 with a limited number of stations. Recently, the solution has been extended to a pan-European and global production consisting of approximately 200 stations. The real-time product has been assessed cross-comparing ZTDs and horizontal gradients at 11 collocated stations and by validating real-time ZTDs with respect to the final post-processing products.

A Model for the Relationship between Rainfall, GNSS-Derived Integrated Water Vapour, and CAPE in the Eastern Central Andes

Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.

Emissivity Retrievals with FORUM's End-to-end Simulator: Challenges and Recommendations

Spectral emissivity is a key property of the Earth surface of which only very few measurements exist so far in the far-infrared (FIR) spectral region, even though recent work has shown its FIR contribution is important for accurate modelling of global climate. The European Space Agency's 9th Earth Explorer, FORUM (Far-infrared Outgoing Radiation Understanding and Monitoring) will provide the first global spectrally resolved measurements of the Earth's top-of-the-atmosphere (TOA) spectrum in the FIR. In clear-sky conditions with low water vapour content, these measurements will provide a unique opportunity to retrieve spectrally resolved FIR surface emissivity. In preparation for the FORUM mission with an expected launch in 2026, this study takes the first steps towards the development of an operational emissivity retrieval for FORUM by investigating the sensitivity of the emissivity product of a full spectrum optimal estimation retrieval method to different physical and operational parameters. The tool used for the sensitivity tests is the FORUM mission's end-to-end simulator. These tests show that spectral emissivity of most surface types can be retrieved for dry scenes in the 350–600 cm−1 region with an uncertainty ranging from 0.005 to 0.01. In addition, the quality of retrieval is quantified with respect to the precipitable water vapour content of the scene, and the uncertainty caused by the correlation of emissivity with surface temperature is investigated. Two main recommendations are made based on these investigations: (1) As the extent of TOA sensitivity to the surface in the FIR depends on the atmospheric state, the spectral region of the emissivity product should be decided using a so-called information quantifier, calculated from the ratio of the retrieval uncertainty to the a-priori uncertainty. (2) Depending on retrieval input parameters, the correlation of emissivity with surface temperature allows for retrieved emissivities within a small range around the true emissivity. Thus the impact of this correlation on the uncertainty estimates of the product should be quantified in detail during further development of the operational retrieval.

Detection of Alpine Foehn in GNSS-ZWD time series: An innovative application of GNSS Meteorology

<p>The atmospheric delay experienced by a signal of the Global Navigation Satellite System (GNSS) is proportional to the water vapour content along the signal path. This fact is typically exploited in GNSS Meteorology by introducing GNSS derived atmospheric parameters like the Zenith Wet Delay (ZWD) in data assimilation schemes. In numerous studies, the positive impact on the (especially precipitation) forecast has been demonstrated. However, while mostly precipitation-related studies represent the current focus of research, other meteorological phenomena might also be investigated by means of GNSS.</p><p>The present study represents an initial investigation on the detection of another important meteorological phenomena using GNSS time series: Foehn winds. Foehn denotes a gusty, warm fall wind occurring in mountainous regions worldwide, leading to a relatively mild climate in affected areas. On the other hand, Foehn can also be characterized as severe weather leading to disasters, due to the high wind speeds frequently encountered.</p><p>The proposed detection method of Foehn in ZWD time series is based on the significant drying/wetting effects on the lee/luv side of an affected mountain range associated with Foehn. The comparison of ZWD from stations on both sides of the main Alpine ridge reveals characteristic features like distinctive ZWD minima/maxima and significant decrease in correlation between the stations.</p><p>In this study we investigate a number of well-documented Foehn events in the Swiss Alps (therefore called Alpine Foehn) using ZWD time series from the Automated GNSS Network Switzerland (AGNES) station network, operated by the Swiss Federal Office of Topography (swisstopo). Based on these case studies, an assessment of the usability of GNSS-ZWD for Foehn detection is presented and possible strengths and weaknesses will be analysed. Finally, an outlook on possible improvements and innovative extensions to the presented approach is given. These range from embedment of ZWD data in operational Foehn classification and the application of Machine-Learning techniques for detection, to the establishment of collocated GNSS/weather stations, which come with a number of scientific benefits - not only for Foehn investigations but GNSS Meteorology in general.</p>

USING GENERATIVE ADVERSARIAL NETWORKS FOR EXTRACTION OF INSAR SIGNALS FROM LARGE-SCALE SENTINEL-1 INTERFEROGRAMS BY IMPROVING TROPOSPHERIC NOISE CORRECTION

Spatiotemporal variations of pressure, temperature, water vapour content in the atmosphere lead to significant delays in interferometric synthetic aperture radar (InSAR) measurements of deformations in the ground. One of the key challenges in increasing the accuracy of ground deformation measurements using InSAR is to produce robust estimates of the tropospheric delay. Tropospheric models like ERA-Interim can be used to estimate the total tropospheric delay in interferograms in remote areas. The problem with using ERA-Interim model for interferogram correction is that after the tropospheric correction, there are still some residuals left in the interferograms, which can be mainly attributed to turbulent troposphere. In this study, we propose a Generative Adversarial Network (GAN) based approach to mitigate the phase delay caused by troposphere. In this method, we implement a noise to noise model, where the network is trained only with the interferograms corrupted by tropospheric noise. We applied the technique over 116 large scale 800 km long interfergrams formed from Sentinel-1 acquisitions covering a period from 25th October, 2014 to 2nd November, 2017 from descending track numbered 108 over Iran. Our approach reduces the root mean square of the phase values of the interferogram 64% compared to those of the original interferogram and by 55% in comparison to the corresponding ERA-Interim corrected version.

Modelling Precipitable Water Vapour (PWV) Over Nigeria from Ground-Based GNSS

Global Navigational Satellite System (GNSS) over the past and present time has shown a great potential in the retrieval of the distribution of water vapour in the atmosphere. Taking the advantage of the effect of the atmosphere on GNSS signal as they travel from the constellation of satellite to ground-based GNSS receivers such that information (water vapour content) about the atmosphere (mostly from the troposphere) can be derived is referred to as GNSS meteorology. This paper presents the spatiotemporal variability of Precipitable Water Vapour (PWV) retrieved from ground–based Global Navigation Satellite System (GNSS) stations over Nigeria for the years 2012 to 2013. In this paper, the GNSS data were processed using GAMIT (ver. 10.70). The GNSS PWV were grouped into daily and monthly averages; the variability of the daily and monthly GNSS PWV were compared and validated with the daily and monthly PWV from National Centre for Environmental Prediction (NCEP) and monthly Rainfall data for the study years respectively. The results revealed that the spatiotemporal variability of PWV across Nigeria is a function of geographic location and seasons. The result shows that there is temporal correlation between GNSS PWV, NCEP PWV and rainfall events. The research also affirms that GNSS PWV could be used to improve weather forecasting/monitoring as well as climate monitoring.

Integrated water vapour content retrievals from ship-borne GNSS receivers during EUREC⁴A

In the framework of the EUREC4A (Elucidating the role of clouds–circulation coupling in climate) campaign that took place in January and February 2020, integrated water vapour (IWV) contents were retrieved over the open tropical Atlantic Ocean using Global Navigation Satellite System (GNSS) data acquired from three research vessels (R/Vs): R/V Atalante, R/V Maria S. Merian and R/V Meteor. This paper describes the GNSS processing method and compares the GNSS IWV retrievals with IWV estimates from the European Centre for Medium-range Weather Forecasts (ECMWF) fifth reanalysis (ERA5), from the Moderate Resolution Imaging Spectroradiometer (MODIS) infrared products and from terrestrial GNSS stations located along the tracks of the ships. The ship-borne GNSS IWV retrievals from R/V Atalante and R/V Meteor compare well with ERA5, with small biases (−1.62 kg m−2 for R/V Atalante and +0.65 kg m−2 for R/V Meteor) and a root mean square (rms) difference of about 2.3 kg m−2. The results for the R/V Maria S. Merian are found to be of poorer quality, with an rms difference of 6 kg m−2, which is very likely due to the location of the GNSS antenna on this R/V prone to multipath effects. The comparisons with ground-based GNSS data confirm these results. The comparisons of all three R/V IWV retrievals with MODIS infrared products show large rms differences of 5–7 kg m−2, reflecting the enhanced uncertainties in these satellite products in the tropics. These ship-borne IWV retrievals are intended to be used for the description and understanding of meteorological phenomena that occurred during the campaign, east of Barbados, Guyana and northern Brazil. Both the raw GNSS measurements and the IWV estimates are available through the AERIS data centre (https://en.aeris-data.fr/, last access: 20 September 2020). The digital object identifiers (DOIs) for R/V Atalante IWV and raw datasets are https://doi.org/10.25326/71 (Bosser et al., 2020a) and https://doi.org/10.25326/74 (Bosser et al., 2020d), respectively. The DOIs for the R/V Maria S. Merian IWV and raw datasets are https://doi.org/10.25326/72 (Bosser et al., 2020b) and https://doi.org/10.25326/75 (Bosser et al., 2020e), respectively. The DOIs for the R/V Meteor IWV and raw datasets are https://doi.org/10.25326/73 (Bosser et al., 2020c) and https://doi.org/10.25326/76 (Bosser et al., 2020f), respectively.