A benchmarking protocol for SAR colorization: From regression to deep learning approaches.

Synthetic aperture radar (SAR) images are widely used in remote sensing. Interpreting SAR images can be challenging due to their intrinsic speckle noise and grayscale nature. To address this issue, SAR colorization has emerged as a research direction to colorize gray scale SAR images while preserving the original spatial information and radiometric information. However, this research field is still in its early stages, and many limitations can be highlighted. In this paper, we propose a full research line for supervised learning-based approaches to SAR colorization. Our approach includes a protocol for generating synthetic color SAR images, several baselines, and an effective method based on the conditional generative adversarial network (cGAN) for SAR colorization. We also propose numerical assessment metrics for the problem at hand. To our knowledge, this is the first attempt to propose a research line for SAR colorization that includes a protocol, a benchmark, and a complete performance evaluation. Our extensive tests demonstrate the effectiveness of our proposed cGAN-based network for SAR colorization. The code is available at https://github.com/shenkqtx/SAR-Colorization-Benchmarking-Protocol.

Is the Air Too Polluted for Outdoor Activities? Check by Using Your Photovoltaic System as an Air-Quality Monitoring Device.

Over the past few decades, the concentrating photovoltaic systems, a source of clean and renewable energy, often fully integrated into the roof structure, have been commonly installed on private houses and public buildings. The purpose of those panels is to transform the incoming solar radiation into electricity thanks to the photovoltaic effect. The produced electric power is affected, in the first instance, by the solar panel efficiency and its technical characteristics, but it is also strictly dependent on site elevation, the meteorological conditions and on the presence of the atmospheric constituents, i.e., clouds, hydrometeors, gas molecules and sub-micron-sized particles suspended in the atmosphere that can scatter and absorb the incoming shortwave solar radiation. The Aerosol Optical Depth (AOD) is an adimensional wavelength-dependent atmospheric column variable that accounts for aerosol concentration. AOD can be used as a proxy to evaluate the concentration of surface particulate matter and atmospheric column turbidity, which in turn affects the solar panel energy production. In this manuscript, a new technique is developed to retrieve the AOD at 550 nm through an iterative process: the atmospheric optical depth, incremented in steps of 0.01, is used as input together with the direct and diffuse radiation fluxes computed by Fu-Liou-Gu Radiative Transfer Model, to forecast the produced electric energy by a photovoltaic panel through a simple model. The process will stop at that AOD value (at 550 nm), for which the forecast electric power will match the real produced electric power by the photovoltaic panel within a previously defined threshold. This proof of concept is the first step of a wider project that aims to develop a user-friendly smartphone application where photovoltaic panel owners, once downloaded it on a voluntary basis, can turn their photovoltaic system into a sunphotometer to continuously retrieve the AOD, and more importantly, to monitor the air quality and detect strong air pollution episodes that pose a threat for population health.

Influence of a weak typhoon on the vertical distribution of air pollution in Hong Kong: A perspective from a Doppler LiDAR network.

High particulate matter (PM) and ozone (O3) concentration in Hong Kong are frequently observed during the summertime typhoon season. Despite the critical effect of a typhoon on air pollution, contributions of vertical wind profile and cloud movement during transboundary air pollution (TAP) on surface PM and O3 concentration have yet to be fully understood. This work is the first study to apply a network of Doppler light detection and ranging (LiDAR) as well as back trajectory analysis to comprehensively analyze the effect of a weak Typhoon (Danas) occurring during 16-19 July 2019 on different variations in PM and O3 concentration. During the typhoon Danas, three types of surface air pollution with five episodes were identified: (1) low PM and high O3 concentration; (2) co-occurring high PM and O3 concentration and (3) high PM and low O3 concentration. Employing our 3D Real-Time Atmospheric Monitoring System (3DREAMs) along with surface observations, we found the important role of TAP in the increases in surface PM and O3 concentration with significant vertical wind shear that transported air pollutants at upper levels, and strong vertical mixing that brought air pollutants to the ground level. Cloud movement related to typhoon periphery, as well as high solar radiation due to sinking motion and remote transport by continental wind, have an impact on local O3 concentration. For the substantial difference in O3 concentration between two air quality measurement sites, the similar vertical aerosol distributions and wind profiles suggest the comparable TAP contributions at the two sites and thus infer the critical role of local O3 photochemical process in the O3 difference. This work comprehensively reveals the influences of a weak typhoon on variations in PM and O3 during the five episodes, providing important references for air quality monitoring and forecast in regions under the influence of typhoon.

Impact of meteorological conditions and air pollution on COVID-19 pandemic transmission in Italy.

Italy was the first, among all the European countries, to be strongly hit by the COVID-19 pandemic outbreak caused by the severe acute respiratory syndrome coronavirus 2 (Sars-CoV-2). The virus, proven to be very contagious, infected more than 9 million people worldwide (in June 2020). Nevertheless, it is not clear the role of air pollution and meteorological conditions on virus transmission. In this study, we quantitatively assessed how the meteorological and air quality parameters are correlated to the COVID-19 transmission in two large metropolitan areas in Northern Italy as Milan and Florence and in the autonomous province of Trento. Milan, capital of Lombardy region, it is considered the epicenter of the virus outbreak in Italy. Our main findings highlight that temperature and humidity related variables are negatively correlated to the virus transmission, whereas air pollution (PM2.5) shows a positive correlation (at lesser degree). In other words, COVID-19 pandemic transmission prefers dry and cool environmental conditions, as well as polluted air. For those reasons, the virus might easier spread in unfiltered air-conditioned indoor environments. Those results will be supporting decision makers to contain new possible outbreaks.

Quantifying the direct radiative effect of absorbing aerosols for numerical weather prediction: a case study.

We conceptualize aerosol radiative transfer processes arising from the hypothetical coupling of a global aerosol transport model and a global numerical weather prediction model by applying the US Naval Research Laboratory Navy Aerosol Analysis and Prediction System (NAAPS) and the Navy Global Environmental Model (NAVGEM) meteorological and surface reflectance fields. A unique experimental design during the 2013 NASA Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field mission allowed for collocated airborne sampling by the high spectral resolution Lidar (HSRL), the Airborne Multi-angle SpectroPolarimetric Imager (AirMSPI), up/down shortwave (SW) and infrared (IR) broadband radiometers, as well as NASA A-Train support from the Moderate Resolution Imaging Spectroradiometer (MODIS), to attempt direct aerosol forcing closure. The results demonstrate the sensitivity of modeled fields to aerosol radiative fluxes and heating rates, specifically in the SW, as induced in this event from transported smoke and regional urban aerosols. Limitations are identified with respect to aerosol attribution, vertical distribution, and the choice of optical and surface polarimetric properties, which are discussed within the context of their influence on numerical weather prediction output that is particularly important as the community propels forward towards inline aerosol modeling within global forecast systems.

Daytime Cirrus Cloud Top-of-Atmosphere Radiative Forcing Properties at a Midlatitude Site and their Global Consequence.

One-year of continuous ground-based lidar observations (2012) are analyzed for single-layer cirrus clouds at the NASA Micro Pulse Lidar Network site at the Goddard Space Flight Center to investigate top-of-atmosphere (TOA) annual net daytime radiative forcing properties. A slight positive net daytime forcing is estimated (i.e., warming) : 0.07 - 0.67 W/m2 in relative terms, which reduces to 0.03 - 0.27 W/m2 in absolute terms after normalizing to unity based on approximated 40% midlatitude occurrence frequency rate estimated from satellite. Results are based on bookend solutions for lidar extinction-to-backscatter (20 and 30 sr) and corresponding retrievals for 532 nm cloud extinction coefficient. Uncertainties due to cloud undersampling, attenuation effects, sample selection and lidar multiple scattering are described. A net daytime cooling effect is found from the very thinnest clouds (cloud optical depth ≤ 0.01) that is attributed to relatively high solar zenith angles. A relationship between positive/negative daytime cloud forcing is demonstrated as a function of solar zenith angle and cloud top temperature. These properties, combined with the influence of varying surface albedos, are used to conceptualize how daytime cloud forcing likely varies with latitude and season, with cirrus clouds exerting less positive forcing and potentially net TOA cooling approaching the summer poles (non-ice and snow covered) versus greater warming at the equator. The existence of such a gradient would lead cirrus to induce varying daytime TOA forcing annually and seasonally, making it a far greater challenge than presently believe to constrain daytime and diurnal cirrus contributions to global radiation budgets.