Realization of Self-Preserving Size Distribution Theory for the Evolution of Tropospheric Atmospheric Aerosols Through an Inverse Gaussian Distribution

The inverse Gaussian distributed method of moments (IGDMOM; J. Atmospheric Sci. 77 (9): 3011-3031, 2020) was developed to analytically solve the kinetic collection equation (KCE) for the first time. Using the IGDMOM, we obtained both new analytical and asymptotic solutions to the KCE. This is shown for both the free molecular and continuum regime collision frequency functions. The new analytical solutions are highly suitable for demonstrating the self-preserving size distribution (SPSD) theory. The SPSD theory is considered one of the most elegant research works in atmospheric science for aerosols or small cloud droplets. It was initially discovered by Friedlander (J. Meteorology 17 (5): 479-483, 1960) and then developed by Lee (J. Colloid Interface Sci. 92 (2): 315-325, 1983) with an assumption of the time-dependent lognormal size distribution function. In this study, we demonstrate that the SPSD theory of coagulating atmospheric aerosols can be presented in a simpler and more rigorous theoretical way, which is realized through the introduction of the IGDMOM for describing aerosol size distributions. Using the IGDMOM, the new formulas for the SPSD, as well as the time required for aerosols to reach the SPSD, are analytically provided and verified. Furthermore, we discover that the SPSD of atmospheric aerosols undergoing coagulation is only determined using a shape factor variable, 𝛺, which is composed of the first three moments at an initial stage. This study has critical implications for developing tropospheric atmospheric aerosol or small cloud droplet dynamics models and further verifies the SPSD theory from the viewpoint of theoretical analysis.

Estimation of Methods of Calculation of Values of Total Solar Radiation for Different Time Intervals

The article presents the results of evaluation of a number of methods for calculating total, scattered and direct radiation. The methods were tested on actinometric data of eight stations of the former USSR, located in different climatic and latitudinal zones, in order to clarify the spatial boundaries of their application and the time interval for which it is possible to carry out calculations with an error of not more than 10 %. It is established that the accuracy of calculations is influenced by the location of the station in relation to the seas and lakes. In addition, a number of methods do not take into account the tier and shape of the cloud, so at the same amount of cloud observed different amounts of total radiation, which in turn leads to errors in the calculation of the amounts of radiation. For stations with high atmospheric transparency and low air humidity, the calculation methods provide understated data compared to full-scale ones. For stations with high dust content of the surface layer of the atmosphere, the calculated data are overstated. For marine and lake stations, overestimation of the calculated data is caused by increased humidity throughout the year and as a result, even with a small cloud cover, incoming solar radiation is significantly weakened by water vapor. The considered calculation methods can be used to calculate monthly amounts of total radiation with an accuracy of 10-12 %. Calculation for shorter time intervals leads to an increase in calculation errors. Using the method of calculating the total radiation components gives an error in the calculation of monthly amounts from 10 to 30 %, depending on the latitude. Performing calculations using this method for time intervals less than a month leads to a sharp increase in the size of errors.

TROPOMI NO2 retrieval: December 2020 (v1.4) and April 2021 (v2.2) upgrades, and comparisons with OMI and ground-based remote sensing

<p>The Tropospheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor (S5P) satellite is a unique instrument, combining daily global coverage, very high signal-to-noise, a broad spectral range and very small pixels up to 3.5 x 5.5 km<sup>2</sup>. Retrievals are available for a large number of species, including NO<sub>2</sub>. Due to the very small pixels and daily revisit, TROPOMI provides detailed information on individual sources and source sectors like individual power plants, industrial complexes, cities and suburbs, highways, and even individual ships. The TROPOMI Level-2 NO<sub>2</sub> product is available from 30 April 2018 onwards.</p><p>Validation exercises of TROPOMI v1.2 & v1.3 data (2018-2020) with OMI and ground-based remote sensing observations have shown that TROPOMI's tropospheric NO<sub>2</sub> column are low by up to 50% over highly polluted areas compared to independent data. In contrast, the underlying slant columns of TROPOMI agree well with OMI and independent SAOZ observations. Differences between OMI and TROPOMI have been mainly attributed to the different cloud height retrieval, using the O<sub>2</sub>-O<sub>2</sub> versus O<sub>2</sub>-A bands respectively.</p><p>In our presentation we discuss recent improvements in the TROPOMI NO<sub>2</sub> retrieval and the impact these have on the tropospheric columns and on the comparisons with OMI and ground-based remote-sensing data.</p><p>Version v1.4, which became operational on 2 December 2020, entails a major improvement in the cloud height retrieval, based on a modification of the FRESCO-S cloud retrieval using the O<sub>2</sub>-A band observations. In particular the cloud height over scenes with a small cloud coverage have increased, resulting in larger tropospheric columns in the retrievals over polluted areas.</p><p>Version v2.2, to become operational in April/May 2021, includes similar cloud retrieval modifications. Furthermore, it provides a better treatment of saturation issues and transients, is using improved (ir)radiance measurements (level-1b v2 spectra) including degradation corrections, and includes a new albedo treatment.</p><p>The TROPOMI NO<sub>2</sub> retrievals are compared with OMI retrievals (from the QA4ECV product) and to ground-based observations with MAXDOAS and PANDORA instruments.</p>

Heritage Connector: A Machine Learning Framework for Building Linked Open Data from Museum Collections

As with almost all data, museum collection catalogues are largely unstructured, variable in consistency and overwhelmingly composed of thin records. The form of these catalogues means that the potential for new forms of research, access and scholarly enquiry that range across multiple collections and related datasets remains dormant. In the project Heritage Connector: Transforming text into data to extract meaning and make connections, we are applying a battery of digital techniques to connect similar, identical and related items within and across collections and other publications. In this paper we describe a framework to create a Linked Open Data knowledge graph (KG) from digital museum catalogues, connect entities within this graph to Wikidata, and create new connections in this graph from text. We focus on the use of machine learning to create these links at scale with a small amount of labelled data, on a mid-range laptop or a small cloud virtual machine. We publish open-source software providing tools to perform the tasks of KG creation, entity matching and named entity recognition under these constraints.

Slow Modes of the Equatorial Waveguide

A recently developed linear model of eastward-propagating disturbances has two separate unstable modes: convectively coupled Kelvin waves destabilized by the wind dependence of the surface enthalpy flux, and slow, MJO-like modes destabilized by cloud–radiation interaction and driven eastward by surface enthalpy fluxes. This latter mode survives the weak temperature gradient (WTG) approximation and has a time scale dictated by the time it takes for surface fluxes to moisten tropospheric columns. Here we extend that model to include higher-order modes and show that planetary-scale low-frequency waves with more complex structures can also be amplified by cloud–radiation interactions. While most of these waves survive the WTG approximation, their frequencies and growth rates are seriously compromised by that approximation. Applying instead the assumption of zonal geostrophy results in a better approximation to the full spectrum of modes. For small cloud–radiation and surface flux feedbacks, Kelvin waves and equatorial Rossby waves are destabilized, but when these feedbacks are strong enough, the frequencies do not lie close to classical equatorial dispersion curves except in the case of higher-frequency Kelvin and Yanai waves. An eastward-propagating n = 1 mode, in particular, has a structure resembling the observed structure of the MJO.

Surface thermal inversion evolution in the bottom of a Pyrenean valley studied by observations and mesoscale simulations

<p>Two experimental campaigns have been carried out in the Cerdanya valley at south side of the Pyrenees (E-W oriented, 35 km long and 9 km wide) during fall 2015 (Cerdanya Cold Pool experiment, CCP’15) and winter 2017 (CCP’17, as a part of the Cerdanya-2017 experiment) to study the cold pool that usually forms there at night. The main site (Das) is placed in the central bottom part of the basin. Conangla et al (2018, IJOC) showed that most cold pool events reported there have a daily cycle, being formed in the evening and destroyed by solar heating of the surface the morning after.</p><p>The availability of vertical soundings performed by a tethered balloon and a WindRASS, together with measured surface fluxes of latent and sensible heat and momentum at the surface layer allows to inspect the establishment and evolution of the surface thermal inversion in Das. This area collects also downslope and downvalley flows accumulating cold air in the valley along the night. The organization of the flow at low levels is studied through mesoscale simulations of some selected Intensive Operational Periods (IOPs) and the surface observations at different locations along and across the valley.</p><p>The selected IOPs comprise nights with only locally-generated winds and small cloud cover, and with variable surface state including grass, fresh snow and patches of old snow. The evolution of the strength and depth of the surface inversion as seen by the model are compared to the available data. Besides, the organization of the flow at low levels and the contribution of the air from the tributary valleys is analyzed in terms of temperature and wind speed budgets to properly characterize the differences in the strength of the cold pool for the selected studied IOPs.</p>

MICRU effective cloud fractions for S-5P/TROPOMI

<pre class="western" lang="en-GB"><span lang="en-GB">We present results of effective cloud fractions retrieved from measurements of the TROPOspheric Monitoring Instrument (TROPOMI) using the Mainz Iterative Cloud Retrieval Utilities (MICRU) algorithm. Cloud fraction (CF) data is used to study the distribution of clouds in general. Furthermore, CF is a crucial input parameter for retrievals of tropospheric trace gases from satellite measurements in the UV/vis spectral region because CF errors may even dominate vertical column density (VCD) retrieval errors of tropospheric trace gases.</span> <span lang="en-GB">The MICRU algorithm has been specifically developed to retrieve small cloud fractions (CF<20%) at high accuracy in order to improve retrievals of tropospheric trace gases. Here, MICRU is applied to TROPOMI data offering a more than 100 times higher spatial resolution compared to GOME-2 (Global Ozone Monitoring Experiment-2), on which it was previously applied. Hence, MICRU CF can be used as an alternative to the operational CF product.</span> <span lang="en-GB">The most important feature of MICRU is the derivation of the minimum reflectance map from the measurements themselves. The algorithm builds on the assumption that the surface is dark compared to clouds, and it is therefore limited to regions not permanently covered by clouds, ice or snow. In particular, the MICRU algorithm applies four parameters to constrain interferences with surface BRDF effects like sun glitter and shadowing. Our approach features a lower threshold map parameterised by time, viewing zenith angle, scattering angle, and reflection angle. </span> <span lang="en-GB">We demonstrate that MICRU, compared to the operational cloud fraction algorithms OCRA and FRESCO, interferences less with viewing angle, solar glitter, and shore lines and, hence, significantly improves the determination of cloud fractions. Furthermore, CF features made visible by the unprecedented spatial resolution of TROPOMI are discussed.</span></pre>

Feasibility of Providers' Coalition in Reverse Auction-Based Cloud Market

Cloud computing has revolutionized the IT world by its benefits. Cloud users can take relational and non-relational databases in the form of services or can run their own database on computing resources provided by the cloud. With evolution of cloud, new challenges are emerging, and the responsibility of the professional is to provide solution to these challenges. Dynamic pricing of computing resources in the cloud is now widely acceptable by its users. But in the current market of cloud, reverse auction (a mechanism to implement dynamic pricing) is not getting the attention from professionals that it deserves. This work is an effort to identify the facts in the cloud market that are responsible for current condition of reverse auction. In this work, from the identified limitations of current cloud market and case study on existing model for reverse auction in cloud, one can observe that coalition of small cloud providers with common interoperability standard in reverse auction is a feasible solution to encourage cloud market for adapting reverse auction-based resource allocation.

FY-4A SATELLITE BASED CLOUD MICROPHYSICAL VARIATION ANALYSIS OF AIRBORNE CLOUD SEEDING OPERATIONS IN SICHUAN BASIN

Based on a satellite retrieval methodology, the cloud microphysical properties of two airborne cloud seeding operations in Sichuan Basin of Southwest China are analyzed in this paper. The methodology for the retrieval of the cloud particle effective radius (Re), cloud temperature (T) and microphysical structure is based on the data from the AGRI onboard the Chinese FY-4A satellite. A microphysical red–green–blue (RGB) composite visualization has been devised to qualitatively highlight the cloud composition. This RGB scheme is displayed by compositing visible 0.65 micron channel, near infrared 2.2 micron channel and infrared 11.0 micron channel. And the vertical structure and development status of the clouds are demonstrated by the T-Re profiles. The results show that after the cloud seeding operation on June 11, 2018, the cloud particle effective radius increases, and the ground observed PM10 and PM2.5 pollutants decrease as well. As for the cloud seeding operation on November, 17, 2018, the satellite inversion shows that the medium and low level clouds are rich in super-cooled water with small cloud particle effective radius. After the cloud seeding operation, the effective radius of the cloud droplets increases significantly. Both of these two cloud seeding operation in Sichuan Basin demonstrate obvious precipitation enhancement results in the seeding impact area.