A5084473263- Meteorological Phenomena and Simulations
- Atmospheric aerosols and clouds
- Atmospheric and Environmental Gas Dynamics
- Solar Radiation and Photovoltaics
- Climate variability and models
- Atmospheric chemistry and aerosols
- Air Quality Monitoring and Forecasting
- Impact of Light on Environment and Health
- Geophysics and Gravity Measurements
- Geochemistry and Geologic Mapping
- demographic modeling and climate adaptation
- Economic and Technological Innovation
- Advanced Neural Network Applications
- Aeolian processes and effects
- Remote-Sensing Image Classification
- Energy Load and Power Forecasting
Leipzig University
2021-2024
Abstract Many different emission pathways exist that are compatible with the Paris climate agreement, and many more possible miss target. While some of most complex Earth System Models have simulated a small selection Shared Socioeconomic Pathways, it is impractical to use these expensive models fully explore space possibilities. Such explorations therefore mostly rely on one‐dimensional impulse response models, or simple pattern scaling approaches approximate physical given scenario. Here...
Abstract. Clouds are a crucial regulator in the Earth's energy budget through their radiative properties, both at top-of-the-atmosphere and surface, hence determining key factors like vertical extent is of essential interest. While cloud top height commonly retrieved by satellites, base difficult to estimate from satellite remote sensing data. Here we present novel method leveraging spatially resolved properties MODIS instrument retrieve over marine areas. A machine learning model built with...
Many different emission pathways exist that are compatible with the Paris climate agreement, and many more possible miss target. While some of most complex Earth System Models have simulated a small selection Shared Socioeconomic Pathways, it is impractical to use these expensive models fully explore space possibilities. Such explorations therefore mostly rely on one-dimensional impulse response models, or simple pattern scaling approaches approximate physical given scenario. Here we present...
Clouds are key regulators of the Earth’s energy budget. Their microphysical and optical properties lead to vastly disparate radiative properties. Retrieving information about clouds is thus crucial reduce uncerntainties in our estimation climate change. In this study, we present a common approach retrieval cloud type base height (CBH), two useful aspects characterise their effects.We leverage surface observations these characterictics from network made available by UK Met Office,...
Abstract. Clouds are a crucial regulator in the Earth's energy budget through their radiative properties, both at top of atmosphere and surface; hence, determining key factors like vertical extent is essential interest. While cloud height commonly retrieved by satellites, base difficult to estimate from satellite remote sensing data. Here, we present novel method called ORABase (Ordinal Regression Auto-encoding Base), leveraging spatially resolved properties Moderate Resolution Imaging...
Abstract. Clouds constitute, through their interactions with incoming solar radiation and outgoing terrestrial radiation, a fundamental element of the Earth’s climate system. Different cloud types show wide variety in microphysical or optical properties, phase, vertical extent temperature among others, thus disparate radiative effects. Both observational model datasets, classifying is also large importance since different respond differently to current future anthropogenic change. Cloud have...
Clouds are classified into types, classes, or regimes. The World Meteorological Organization distinguishes stratus and cumulus clouds three altitude layers. Cloud types exhibit very different radiative properties interact in numerous ways with aerosol particles the atmosphere. However, it has proven difficult to define cloud regimes objectively from remote sensing data, hindering understanding we have of processes adjustments involved.Building on method previously developed, combine synoptic...
<p>Exploration of future emissions scenarios mostly relies on one-dimensional impulse response models, or simple pattern scaling approaches to approximate the physical climate a given scenario. Such are unable reliably predict variables which respond non-linearly forcing (such as precipitation) and must rely heavily simplified representations e.g., aerosol, neglecting important spatial dependencies.</p><p>Here we present ClimateBench - benchmark...
<p>Cloud base height (CBH) is an important geometric parameter of a cloud and shapes its radiative properties. The CBH also further practical interest in the aviation community regarding pilot visibility aircraft icing hazards. While cloud-top has been successfully derived from passive imaging radiometers on satellites during recent years, derivation remains more difficult challenge with these same retrievals.</p><p>In our study we combine surface...
Estimating the amount of electricity that can be produced by rooftop photovoltaic systems is a time-consuming process requires on-site measurements, difficult task to achieve on large scale. In this paper, we present an approach estimate solar potential rooftops based their location and architectural characteristics, as well radiation they receive annually. Our technique uses computer vision semantic segmentation roof sections objects one hand, machine learning model structured building...
Earth and Space Science Open Archive This preprint has been submitted to is under consideration at Journal of Advances in Modeling Systems (JAMES). ESSOAr a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing an older version [v1]Go new versionClimateBench: A benchmark dataset data-driven climate projectionsAuthorsDuncanWatson-ParrisiDYuhanRaoDirkOliviéØyvindSelandPeer...