UMBC Joint Center for Earth Systems Technology (JCET)
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The Joint Center for Earth Systems Technology (JCET) was formed under a Cooperative agreement between the Earth Science Division of NASA Goddard Space Flight Center (GSFC) and the University of Maryland, Baltimore County (UMBC) in 1995. The JCET family consists of its business staff, students, research faculty, GSFC Sponsors, appointed fellows and affiliated tenured/tenure-track faculty. JCET is an innovative center where these scientists interact in a seamless fashion with the support of an efficient business and administrative unit.
Recent Submissions
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AIRS L1c Frequency Calibration
(2019-11-03)This document summarizes the observed frequency drifts in the AIRS L1b radiances and then describes how they are corrected in the AIRS L1c product that should be available at the NASA Goddard DISC in early 2010. The ... -
Daytime Top-of-the-Atmosphere Cirrus Cloud Radiative Forcing Properties at Singapore
(National Aeronautics and Space Administration, 2017) -
Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm
(MDPI, 2019-12-24)Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for ... -
Evaporation From the Southern Ocean Estimatedon the Basis of AIRS Satellite Data
(American Geophysical Union, 2019-12-19)Evaporation plays an important role in the global water and energy cycles and, hence, in climate change. Evaporation over the Southern Ocean, where the Antarctic sea ice coverage has a large annual cycle, is poorly quantified. ... -
Assessing NO2 Concentration and Model Uncertainty with High Spatiotemporal Resolution across the Contiguous United States Using Ensemble Model Averaging
(ACS Publications, 2019-12-18)NO₂ is a combustion byproduct that has been associated with multiple adverse health outcomes. To assess NO₂ levels with high accuracy, we propose the use of an ensemble model to integrate multiple machine learning algorithms, ... -
Applying the Dark Target aerosol algorithm with Advanced Himawari Imager observations during the KORUS-AQ field campaign
(EGU, 2019-12-11)For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly ... -
Anthropogenic control over wintertime oxidation of atmospheric pollutants
(American Geophysical Union, 2019-12-13)During winter in the midlatitudes, photochemical oxidation is significantly slower than in summer and the main radical oxidants driving formation of secondary pollutants, such as fine particulate matter and ozone, remain ... -
Transitioning the NASA SLR network to Event Timing Mode for reduced systematics, improved stability and data precision
(Springer Berlin Heidelberg, 2019-11-21)NASA’s legacy Satellite Laser Ranging (SLR) network produces about one-third of the global SLR data to support space geodesy. This network of globally distributed stations has been using Time Interval Units (TIU) for range ... -
Understanding the Various Perspectives of Earth Science Observational Data Uncertainty
(2019-08-11)Information about the uncertainty associated with Earth science observational data is fundamental to use, re-use, and overall evaluation of the data being used to produce science and support decision making. The associated ... -
Evaluating the impact of spatial resolution on tropospheric NO2 column comparisons within urban areas using high-resolution airborne data
(EGU, 2019-11-22)NASA deployed the GeoTASO airborne UV–visible spectrometer in May–June 2017 to produce high-resolution (approximately 250 m×250 m) gapless NO₂ datasets over the western shore of Lake Michigan and over the Los Angeles Basin. ... -
Asian and Trans‐Pacific Dust: A Multimodel and Multiremote Sensing Observation Analysis
(American Geophysical Union, 2019-12-06)Dust is one of the dominant aerosol types over Asia and the North Pacific Ocean, but quantitative estimation of dust distribution and its contribution to the total regional aerosol load from observations is challenging due ... -
Systematic errors in SLR data and their impact on the ILRS products
(Springer Berlin Heidelberg, 2019-11-19)The satellite laser ranging (SLR) technique has the potential to make extremely precise measurements to retrorefector arrays on orbiting satellites, with normal point range precision at a level of 1 mm for the core tracking ... -
Dust Detection in Satellite Data using Convolutional Neural Networks
(HPCF UMBC, 2019)Atmospheric dust is known to cause health ailments and impacts earth’s climate and weather patterns. Due to the many issues atmospheric dust contributes to, it is important to study dust patterns and how it enters the ... -
Clarifying linkages between canopy solar induced fluorescence (SIF) and physiological function for high latitude vegetation
(National Aeronautics and Space Administration, 2018)Remote sensing of Solar-Induced Fluorescence (SIF) is a growing and dynamic research field that has the potential to provide innovative tools for monitoring plant status and photosynthetic function and transform global ... -
Benchmarking Parallel K-Means Cloud Type Clustering from Satellite Data
(Springer, Cham, 2019-10-08)The study of clouds, i.e., where they occur and what are their characteristics, plays a key role in the understanding of climate change. Clustering is a common machine learning technique used in atmospheric science to ... -
Reply to “A comment on “A test of general relativity using the LARES and LAGEOS satellites and a GRACE Earth gravity model, by I. Ciufolini et al.””
(Springer Berlin Heidelberg, 2018-10-30)In 2016, we published “A test of general relativity using the LARES and LAGEOS satellites and a GRACE Earth’s gravity model. Measurement of Earth’s dragging of inertial frames [1]”, a measurement of frame-dragging, a ... -
Preface to the second special issue on Laser Ranging
(Springer Berlin Heidelberg, 2019-10-10)
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