The local climate impact of an African city during clear‐sky conditions—Implications of the recent urbanization in Kampala (Uganda)

2020 ◽  
Vol 40 (10) ◽  
pp. 4586-4608 ◽  
Author(s):  
Oscar Brousse ◽  
Hendrik Wouters ◽  
Matthias Demuzere ◽  
Wim Thiery ◽  
Jonas Van de Walle ◽  
...  
Keyword(s):  
Climate Impact ◽  
African City ◽  
Local Climate ◽  
Clear Sky ◽  
Sky Conditions

scholarly journals Measuring Landscape Albedo Using Unmanned Aerial Vehicles

2018 ◽  
Vol 10 (11) ◽  
pp. 1812 ◽  
Author(s):  
Chang Cao ◽  
Xuhui Lee ◽  
Joseph Muhlhausen ◽  
Laurent Bonneau ◽  
Jiaping Xu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Surface Albedo ◽  
Near Infrared ◽  
Surface Energy Balance ◽  
Landsat Image ◽  
Local Climate ◽  
Clear Sky ◽  
Aerial Vehicles ◽  
Albedo Change ◽  
Sky Conditions

Surface albedo is a critical parameter in surface energy balance, and albedo change is an important driver of changes in local climate. In this study, we developed a workflow for landscape albedo estimation using images acquired with a consumer-grade camera on board unmanned aerial vehicles (UAVs). Flight experiments were conducted at two sites in Connecticut, USA and the UAV-derived albedo was compared with the albedo obtained from a Landsat image acquired at about the same time as the UAV experiments. We find that the UAV estimate of the visibleband albedo of an urban playground (0.037 ± 0.063, mean ± standard deviation of pixel values) under clear sky conditions agrees reasonably well with the estimates based on the Landsat image (0.047 ± 0.012). However, because the cameras could only measure reflectance in three visible bands (blue, green, and red), the agreement is poor for shortwave albedo. We suggest that the deployment of a camera that is capable of detecting reflectance at a near-infrared waveband should improve the accuracy of the shortwave albedo estimation.

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

Efficient downscaling of satellite oceanographic data with convolutional neural networks

2021 ◽  
Vol 12 (3) ◽  
pp. 46-47
Author(s):  
Nikita Saxena
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Convolutional Neural Networks ◽  
Super Resolution ◽  
Sea Surface ◽  
Clear Sky ◽  
Oceanographic Data ◽  
Computationally Expensive ◽  
Sky Conditions ◽  
Data Inference

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.

scholarly journals Urban Climates and Climate Change

2020 ◽  
Vol 45 (1) ◽  
pp. 411-444 ◽  
Author(s):  
Valéry Masson ◽  
Aude Lemonsu ◽  
Julia Hidalgo ◽  
James Voogt
Keyword(s):  
Climate Change ◽  
Climate Modeling ◽  
Regional Climate ◽  
Urban Climate ◽  
Regional Climate Modeling ◽  
Climate Impact ◽  
Local Climate ◽  
Urban Climatology ◽  
Recent Developments ◽  
Global Agenda

Cities are particularly vulnerable to extreme weather episodes, which are expected to increase with climate change. Cities also influence their own local climate, for example, through the relative warming known as the urban heat island (UHI) effect. This review discusses urban climate features (even in complex terrain) and processes. We then present state-of-the-art methodologies on the generalization of a common urban neighborhood classification for UHI studies, as well as recent developments in observation systems and crowdsourcing approaches. We discuss new modeling paradigms pertinent to climate impact studies, with a focus on building energetics and urban vegetation. In combination with regional climate modeling, new methods benefit the variety of climate scenarios and models to provide pertinent information at urban scale. Finally, this article presents how recent research in urban climatology contributes to the global agenda on cities and climate change.

Intra-Day DNI Forecasting Under Clear Sky Conditions Using ANFIS

2014 ◽  
Vol 47 (3) ◽  
pp. 10361-10366 ◽  
Author(s):  
Rémi Chauvin ◽  
Julien Nou ◽  
Stéphane Thil ◽  
Stéphane Grieu
Keyword(s):  
Clear Sky ◽  
Sky Conditions

scholarly journals A Blended Sea Ice Concentration Product from AMSR2 and VIIRS

2021 ◽  
Vol 13 (15) ◽  
pp. 2982
Author(s):  
Richard Dworak ◽  
Yinghui Liu ◽  
Jeffrey Key ◽  
Walter N. Meier
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Infrared Imaging ◽  
High Spatial Resolution ◽  
Sea Ice Concentration ◽  
Clear Sky ◽  
Ice Concentration ◽  
Best Linear Unbiased ◽  
The Individual ◽  
Sky Conditions

An effective blended Sea-Ice Concentration (SIC) product has been developed that utilizes ice concentrations from passive microwave and visible/infrared satellite instruments, specifically the Advanced Microwave Scanning Radiometer-2 (AMSR2) and the Visible Infrared Imaging Radiometer Suite (VIIRS). The blending takes advantage of the all-sky capability of the AMSR2 sensor and the high spatial resolution of VIIRS, though it utilizes only the clear sky characteristics of VIIRS. After both VIIRS and AMSR2 images are remapped to a 1 km EASE-Grid version 2, a Best Linear Unbiased Estimator (BLUE) method is used to combine the AMSR2 and VIIRS SIC for a blended product at 1 km resolution under clear-sky conditions. Under cloudy-sky conditions the AMSR2 SIC with bias correction is used. For validation, high spatial resolution Landsat data are collocated with VIIRS and AMSR2 from 1 February 2017 to 31 October 2019. Bias, standard deviation, and root mean squared errors are calculated for the SICs of VIIRS, AMSR2, and the blended field. The blended SIC outperforms the individual VIIRS and AMSR2 SICs. The higher spatial resolution VIIRS data provide beneficial information to improve upon AMSR2 SIC under clear-sky conditions, especially during the summer melt season, as the AMSR2 SIC has a consistent negative bias near and above the melting point.

scholarly journals Seasonal Net Shortwave Radiation of Bare Arable Land in Poland and Israel According to Roughness and Atmospheric Irradiance

2021 ◽  
Vol 13 (10) ◽  
pp. 1897
Author(s):  
Jerzy Cierniewski ◽  
Jean-Louis Roujean ◽  
Jarosław Jasiewicz ◽  
Sławomir Królewicz
Keyword(s):  
Arable Land ◽  
Soil Tillage ◽  
Shortwave Radiation ◽  
Landsat 8 ◽  
Clear Sky ◽  
Spatial Coverage ◽  
Arable Fields ◽  
Model Equations ◽  
Earth’S Climate ◽  
Sky Conditions

Tillage of arable fields, using for instance a smoothing harrow, may increase the magnitude of albedo of such soil surfaces depending on the location, the sun’s illumination and atmospheric components. As these soil surfaces absorb less shortwave radiation compared to plowed soils, the result is an atmospheric cooling and a positive effect on the Earth’s climate. This paper is the follow-on of a previous study aimed at quantifying the seasonal dynamics of net shortwave radiation reflected by bare air-dried arable land areas located in contrasting environments, i.e. Poland and Israel. Soil tillage includes a plow, a disk harrow, and a smoothing harrow. Previous work concentrated on the estimate of net shortwave radiation under clear-sky theoretical scenarios, whereas the present study deals with a realistic atmosphere throughout the year 2014. This latter is characterized by the observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the Meteosat Second Generation (MSG). The variations of the net shortwave radiation for the selected bare arable land areas were assessed in combining observations from Landsat 8 images and digital maps of land use and soil, plus model equations that calculate the diurnal variations of the broadband blue-sky albedo with roughness inclusive. The daily amount of net shortwave radiation for air-dried bare arable land in Poland and Israel for the time their spatial coverage is the largest was found to be about 40–50% and 10% lower, respectively, in cloudy-sky conditions compared to clear-sky conditions.

Aerosol Effects on Temperature Forecast in the COSMO-Ru Model

2021 ◽  
pp. 29-39
Author(s):  
A. A. Poliukhov ◽  
◽  
D. V. Blinov ◽  
◽  
Keyword(s):  
Air Temperature ◽  
Numerical Experiments ◽  
Surface Air Temperature ◽  
European Part ◽  
Clear Sky ◽  
Temperature Forecast ◽  
European Part Of Russia ◽  
Simulated Surface ◽  
Aerosol Effects ◽  
Sky Conditions

Aerosol effects on the forecast of surface temperature, as well as temperature at the levels of 850 and 500 hPa over Europe and the European part of Russia are studied using various aerosol climatologies: Tanre, Tegen, and MACv2. The numerical experiments with the COSMO-Ru model are performed for the central months of the seasons (January, April, July, and October) in 2017. It is found that a change in the simulated surface air temperature over land can reach 1C when using Tegen and MACv2 data as compared to Tanre. At 850 and 500 hPa levels, the changes do not exceed 0.4C. At the same time, it is shown that a decrease in the root-mean-square error of 2-m air temperature forecast at individual stations reaches 0.5C when using Tegen and MACv2 data and 1C for clear-sky conditions in Moscow.

scholarly journals The global 3-D distribution of tropospheric aerosols as characterized by CALIOP

2013 ◽  
Vol 13 (6) ◽  
pp. 3345-3361 ◽  
Author(s):  
D. M. Winker ◽  
J. L. Tackett ◽  
B. J. Getzewich ◽  
Z. Liu ◽  
M. A. Vaughan ◽  
...  
Keyword(s):  
Lower Troposphere ◽  
Aerosol Extinction ◽  
Transport Pathways ◽  
3 Dimensional ◽  
Clear Sky ◽  
Tropospheric Aerosol ◽  
Vertical Distributions ◽  
Dimensional Distribution ◽  
Level 3 ◽  
Sky Conditions

Abstract. The CALIOP lidar, carried on the CALIPSO satellite, has been acquiring global atmospheric profiles since June 2006. This dataset now offers the opportunity to characterize the global 3-D distribution of aerosol as well as seasonal and interannual variations, and confront aerosol models with observations in a way that has not been possible before. With that goal in mind, a monthly global gridded dataset of daytime and nighttime aerosol extinction profiles has been constructed, available as a Level 3 aerosol product. Averaged aerosol profiles for cloud-free and all-sky conditions are reported separately. This 6-yr dataset characterizes the global 3-dimensional distribution of tropospheric aerosol. Vertical distributions are seen to vary with season, as both source strengths and transport mechanisms vary. In most regions, clear-sky and all-sky mean aerosol profiles are found to be quite similar, implying a lack of correlation between high semi-transparent cloud and aerosol in the lower troposphere. An initial evaluation of the accuracy of the aerosol extinction profiles is presented. Detection limitations and the representivity of aerosol profiles in the upper troposphere are of particular concern. While results are preliminary, we present evidence that the monthly-mean CALIOP aerosol profiles provide quantitative characterization of elevated aerosol layers in major transport pathways. Aerosol extinction in the free troposphere in clean conditions, where the true aerosol extinction is typically 0.001 km−1 or less, is generally underestimated, however. The work described here forms an initial global 3-D aerosol climatology which we plan to extend and improve over time.

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