Engineering topics

A Shiklomanov

Publications and source records attributed to A Shiklomanov.

3 records

NASA NTRS2024

On-Orbit Spatial Performance Characterization for Thermal Infrared Imagers of Landsat 7, 8, and 9, ECOSTRESS and CTI

In this analysis of the spatial resolving power of thermal imagery products we focus on four satellite instruments that are used in research and applications, for example to monitor land surface temperature and derive evapotranspiration. These are thermal imagers on Landsat 7, Landsat 8, and Landsat 9, as well as the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS). We compiled sets of close-in-time, day-time images of bridges surrounded by open water bodies, captured by each of the satellite imagers during cloud-free moments. Where possible, we also included some images captured by the Compact Thermal Imager (CTI), a technology demonstrator that was co-located with ECOSTRESS on the International Space Station in 2019. Bridges were found to provide a sufficient thermal contrast with the water surface to quantify the line-spread function of satellite-based thermal products. The full-width-at-half-max of a gaussian beam model fitted to this transect quantifies the on-orbit spatial resolution of different imagers. The results show some loss of spatial resolving power in the final product delivered to end-users as compared to the at-sensor characterization of spatial resolution. For Landsat 7, 8 and 9, the spatial resolution of the thermal bands is 1.5 times the ground sampling distance of 60 m and 100 m respectively. For the ECOSTRESS the difference is up to twice the sampling distance of 78 by 69 m2. Since spatial resolution is a main driver for instrument design it is important to understand and communicate this discrepancy between pre-flight design parameters and the characteristics of the surface imagery delivered to the user community. The goal of this research is to facilitate an improved fusion of current and future satellite observations into harmonized products with superior temporal and spatial characteristics.

thermal infrared↗

NASA NTRS2021

Reduced Complexity Model Intercomparison Project Phase 2: Synthesizing Earth System Knowledge for Probabilistic Climate Projections

Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state-of-the-art knowledge in an internally self-consistent modelling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain-specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low-emissions SSP1-1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850-1900, using an observationally-based historical warming estimate of 0.8°C between 1850-1900 and 1995-2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above pre-industrial in the long-term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

Climate↗

NASA NTRSDate not supplied

An Analytic Collaborative Framework for the Earth System Observatory

NASA's Earth System Observatory groundbreaking observations will provide critical measurements to address societal relevant problems in climate change, natural hazard mitigation, fighting forest fires, and improving real-time agricultural processes. Central to the ESO vision is the notion of Open-Source Science (OSS), a collaborative culture enabled by technology that promotes the open sharing of data, information, and knowledge aiming to facilitate and accelerate scientific understanding, and the agile development of applications for the benefit of society. The larger vision of an Earth System Digital Twin (ESDT) calls for integrated Earth science frameworks that mirror the Earth by a proxy digital construct that includes km-scale resolution Earth system models and data assimilation systems along with an integrated set of analytic tools to enable the next generation of science discoveries and evidence-based decision making. The goal of this project is to develop an Analytic Collaborative Framework for ESO missions, based on realistic, science-based observing system simulations and the Program of Record (PoR). Tying it all together is a cloud-based cyberinfrastructure that will enable each uniquely designed satellite in the Earth System Observatory to work in tandem to create a 3D, holistic view of Earth. In this presentation, we lay the technological groundwork for enabling such a vision. Our approach consists of the 3 main interconnected building blocks: 1. Cloud-optimized representative datasets for ESO missions and the PoR to serve as basis for developing and prototyping an Analytic Collaborative Framework. 2. An Algorithm Workbench for enabling experimentation and exploration of synergistic algorithms not only for instruments within a mission, but also including the PoR and other ESO missions. 3. A series of concrete Open-Source Science demonstrations including use cases that span science discovery and end-user applications with direct societal impact. While our ultimate goal is to include all of the main missions comprising the Earth System Observatory, in our initial 2 years we will focus on AOS and SBG, two missions for which specific synergisms have been identified in a recent workshop. In this presentation we will describe our approach and discuss some illustrative examples of our framework.

Arlindo da SIlva↗