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NASA NTRS2018

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

AMSR2; passive microwave soil moisture; soil moist↗
NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_TRMM-PFM-VIRS_Edition2A)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

ICE WATER PATH↗
NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

LONGWAVE UNFILTERED RADIANCE↗
NASA NTRS1996

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Lerner, Jeffrey A.↗
NASA NTRS2013

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

spectral mixing analysis↗
NASA NTRS1994

Space observations for global and regional studies of the biosphere

The capability to make space-based measurements of Earth at high spatial and temporal resolutions, which would not otherwise be economically or practically feasible, became available just in time to contribute to scientific understanding of the interactive processes governing the total Earth system. Such understanding has now become essential in order to take practical steps which would counteract or mitigate the pervasive impact of the growing human population on the future habitability of the Earth. The paper reviews the rationale for using space observations for studies of climate and terrestrial ecosystems at global and regional scales, as well as the requirements for such observations for studies of climate and ecosystem dynamics. The present status of these developments is reported along with initiatives under way to advance the use of satellite observations for Earth system studies. The most important contribution of space observations is the provision of physical or biophysical parameters for models representing various components of the Earth system. Examples of such parameters are given for climatic and ecosystem studies.

Cihlar, J.↗
NASA NTRS2017

Chapter 15: Potential Surprises: Compound Extremes and Tipping Elements

The Earth system is made up of many components that interact in complex ways across a broad range of temporal and spatial scales. As a result of these interactions the behavior of the system cannot be predicted by looking at individual components in isolation. Negative feedbacks, or self-stabilizing cycles, within and between components of the Earth system can dampen changes (Ch. 2: Physical Drivers of Climate Change). However, their stabilizing effects render such feedbacks of less concern from a risk perspective than positive feedbacks, or self-reinforcing cycles. Positive feedbacks magnify both natural and anthropogenic changes. Some Earth system components, such as arctic sea ice and the polar ice sheets, may exhibit thresholds beyond which these self-reinforcing cycles can drive the component, or the entire system, into a radically different state. Although the probabilities of these state shifts may be difficult to assess, their consequences could be high, potentially exceeding anything anticipated by climate model projections for the coming century.

Kopp, R. E.↗
NASA NTRS2005

Coronal Current Sheet Evolution in the Aftermath of a CME

We report on SOHO-UVCS observations of coronal restructuring following a Coronal Mass Ejection (CME) on November 26, 2002, at the time of a SOHO-Ulysses quadrature campaign. Starting about 3 hours after the CME, which was directed towards Ulysses, UVCS began taking spectra at 1.7 solar radii, covering emission from both cool and hot plasma. Observations continued, with occasional gaps, for more than 2 days. Emission in the 974.8 Angstrom line of [Fe XVIII], indicating temperatures above 6x10(6) K, was observed throughout the campaign in a spatially limited location. Comparison with EIT images shows the [Fe XVIII] emission to overlie a growing post-flare loop system formed in the aftermath of the CME. The emission most likely originates in a current sheet overlying the arcade. Analysis of the [Fe XVIII] emission allows us to infer the evolution of physical parameters in the current sheet over the entire span of our observations: in particular, we give the temperature vs. time in the current sheet and estimate the density. Ulysses was directly above the location of the CME and intercepted the ejecta. High ionization state Fe was detected by SWICS throughout the magnetic cloud associated with the CME, although the rapid temporal variation suggests bursty, rather than smooth, reconnection in the coronal current sheet. Both the remote and in situ observations are compared with predictions of theoretical CME models.

Bemporad, A.↗
NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_Aqua-FM4_Edition2)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

TOTAL DETECTOR OUTPUT↗
NASA NTRS2011

A Global Climatology of Tropospheric and Stratospheric Ozone Derived from Aura OMI and MLS Measurements

A global climatology of tropospheric and stratospheric column ozone is derived by combining six years of Aura Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) ozone measurements for the period October 2004 through December 2010. The OMI/MLS tropospheric ozone climatology exhibits large temporal and spatial variability which includes ozone accumulation zones in the tropical south Atlantic year-round and in the subtropical Mediterranean! Asia region in summer months. High levels of tropospheric ozone in the northern hemisphere also persist in mid-latitudes over the eastern North American and Asian continents extending eastward over the Pacific Ocean. For stratospheric ozone climatology from MLS, largest ozone abundance lies in the northern hemisphere in the latitude range 70degN-80degN in February-April and in the southern hemisphere around 40degS-50degS during months August-October. The largest stratospheric ozone abundances in the northern hemisphere lie over North America and eastern Asia extending eastward across the Pacific Ocean and in the southern hemisphere south of Australia extending eastward across the dateline. With the advent of many newly developing 3D chemistry and transport models it is advantageous to have such a dataset for evaluating the performance of the models in relation to dynamical and photochemical processes controlling the ozone distributions in the troposphere and stratosphere.

Ziemke, J.R.↗
NASA NTRS1973

A New GaAs Laser Radar for Atmospheric Measurements

A special GaAs lidar using fiber coupled diode lasers was constructed for the purpose of measuring the extinction coefficient distribution within a large atmospheric volume at a rate compatible with atmospheric kinematics. The technique is based on taking backscatter signature ratios over spatial increments after the returns are normalized by pulse integration. Essential aspects of the lidar design are beam pulse power, repetition rate, detection system dynamic range and decay linearity. It was necessary to preclude the possibility of eye hazard under any operating conditions, including directly viewing the emitting aperture at close distance with a night-adapted eye. The electronic signal processing and control circuits were built to allow versatile operations. Extinction coefficient measurements were made in fog and clouds using a low-power laboratory version of the lidar, demonstrating feasibility. Data are presented showing range squared corrected backscatter profiles converted to extinction coefficient profiles, temporal signal fluctuations, and solar induced background noise. These results aided in the design of the lidar which is described. Functional tests of this lidar and the implications relevant to the design of a prototype model are discussed. This work was jointly sponsored by Sperry Rand Corporation under its Independent Research and Development program; the Air Force Avionics Laboratory, Wright Field, Dayton, Ohio; and the Naval Ammunition Depot, Crane, Indiana.

Brown, R. T.↗
NASA NTRS2019

Long-Term Impacts of Selective Logging on Amazon Forest Dynamics from Multi-Temporal Airborne LiDAR

Forest degradation is common in tropical landscapes, but estimates of the extent and duration of degradation impacts are highly uncertain. In particular, selective logging is a form of forest degradation that alters canopy structure and function, with persistent ecological impacts following forest harvest. In this study, we employed airborne laser scanning in 2012 and 2014 to estimate three-dimensional changes in the forest canopy and understory structure and aboveground biomass following reduced-impact selective logging in a site in Eastern Amazon. Also, we developed a binary classification model to distinguish intact versus logged forests. We found that canopy gap frequency was significantly higher in logged versus intact forests even after 8 years (the time span of our study). In contrast, the understory of logged areas could not be distinguished from the understory of intact forests after 6–7 years of logging activities. Measuring new gap formation between LiDAR acquisitions in 2012 and 2014, we showed rates 2 to 7 times higher in logged areas compared to intact forests. New gaps were spatially clumped with 76 to 89% of new gaps within 5 m of prior logging damage. The biomass dynamics in areas logged between the two LiDAR acquisitions was clearly detected with an average estimated loss of -4.14 +/- 0.76 MgC/hay. In areas recovering from logging prior to the first acquisition, we estimated biomass gains close to zero. Together, our findings unravel the magnitude and duration of delayed impacts of selective logging in forest structural attributes, confirm the high potential of airborne LiDAR multitemporal data to characterize forest degradation in the tropics, and present a novel approach to forest classification using LiDAR data.

Pinage, Ekena Rangel↗
NASA NTRS2022

An Earth System Digital Twin for Flood Prediction and Analysis

An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observation data, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions. The NASA’s Advanced Information Systems Technology (AIST)’s Integrated Digital Earth Analysis System (IDEAS) project is to establish an extensible architectural solution to develop digital twins of our physical environment for Earth Science. IDEAS delivers a formal system architecture with mechanisms for the outputs of one model to feed into others; for driving models with observation data; and for harmonizing observation data and model outputs for analysis. To validate and demonstrate the IDEAS architecture, this project collaborates with the Space Climate Observatory (SCO)’s FloodDAM project and the Centre National d’Etudes Spatiales (CNES) to focus on floods detection, prediction and their impacts.

Kettig, Peter↗
NASA NTRS1992

Atmospheric correction of AVIRIS data in ocean waters

Hyperspectral data offers unique capabilities for characterizing the ocean environment. The spectral characterization of the composition of ocean waters can be organized into biological and terrigenous components. Biological photosynthetic pigments in ocean waters have unique spectral ocean color signatures which can be associated with different biological species. Additionally, suspended sediment has different scattering coefficients which result in ocean color signatures. Measuring the spatial distributions of these components in the maritime environments provides important tools for understanding and monitoring the ocean environment. These tools have significant applications in pollution, carbon cycle, current and water mass detection, location of fronts and eddies, sewage discharge and fate etc. Ocean color was used from satellite for describing the spatial variability of chlorophyll, water clarity (K(sub 490)), suspended sediment concentration, currents etc. Additionally, with improved atmospheric correction methods, ocean color results produced global products of spectral water leaving radiance (L(sub W)). Ocean color results clearly indicated strong applications for characterizing the spatial and temporal variability of bio-optical oceanography. These studies were largely the results of advanced atmospheric correction techniques applied to multispectral imagery. The atmosphere contributes approximately 80 percent - 90 percent of the satellite received radiance in the blue-green portion of the spectrum. In deep ocean waters, maximum transmission of visible radiance is achieved at 490nm. Conversely, nearly all of the light is absorbed by the water at wavelengths greater than about 650nm and thus appears black. These spectral ocean properties are exploited by algorithms developed for the atmospheric correction used in satellite ocean color processing. The objective was to apply atmospheric correction techniques that were used for procesing satellite Coastal Zone Color Scanner (CZCS) data to AVIRIS data. Quantitative measures of L(sub W) from AVIRIS are compared with ship ground truth data and input into bio-optical models.

Terrie, Gregory↗
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 NTRS1993

Transmantle flux tectonics

Venus, Earth, and Mars have surfaces that display topographic domes and depressions with quasi-circular planimetric shapes, relief of 0 to several km, and large spatial scales (10(exp 2) to 10(exp 4) km). Our morphostructural mapping reveals hierarchical arrangements of these features. They are explained by a model of long-acting mantle convection, as a particular case of convection in a stratified and random inhomogeneous medium, which develops the form of a hierarchy of different convective pattern scales, each arising from different levels in the mantle. The hypothesis of transmantle flux tectonics parsimoniously explains a diversity of seemingly unrelated terrestrial planetary phenomena, including Earth megaplumes, global resurfacing epochs on Venus, and cyclic ocean formation and global climate change for Mars. All these phenomenon are hypothesized to be parsimoniously explained by a process of transmantle flux tectonics in which long-acting mantle convection generates stresses in blocks of planetary lithosphere to produce distinctive quasi-circular global-hierarchical morphostructure (QGM) patterns. Transmantle flux tectonics differs from plume tectonics in that individual plumes are not considered in isolation. Rather, a wholly interactive process is envisioned in which various spatial and temporal scales of convection operate contemporaneously and hierarchically within other scales. This process of continual change by hierarchical convective cells affects the surface at varying temporal and spatial scales, and its effects are discernable through their relic geological manifestations, the QGM patterns.

Finn, V. J.↗
NASA NTRS1993

Observations on the long-period variability of the Gulf Stream downstream of Cape Hatteras

To examine the long-period variability of the Gulf Stream, sea level residuals relative to a 2-year mean sea level in the Gulf Stream downstream of Cape Hatteras (between 75 deg W and 60 deg W longitude) are used. Residuals, as derived from Geosat altimetry between November 1986 and December 1988, were gridded in space and time at a temporal resolution of 10 days and spatial resolution of 1/4 deg. Complex empirical orthogonal function (CEOF) analysis was applied to the data set to extract the spatially correlated signal with the original data subsampled to 1/2 deg. In addition to determining the space-time scales and propagation characterisitics of the different modes, wavenumber-frequency spectral techniques were used to separate the variability into propagating and stationary components. The CEOF technique applied to the data set indicated that the first four CEOF modes accounted for 60% of the variability and were found to be above the noise leve 99% of the time. CEOF 1 was associated with westward propagation at 5 km/d at a wavelength of 2000 km and eastward propagation at 1-2 km/d centered at a 500-km wavelength. This first CEOF is in good agreement with thin-jet equivalent barotropic models which predict westward propagation for wavelengths greater than 1130 km. A deflection of the wavelike pattern at 65 deg W also indicates a possible topographic effect. A simple scaling of the effect of topography indicates that for length scales longer than the internal Rossby radius of deformation, the topographic term is at least of the same order of magnitude as the beta effect. The second CEOF was more broadbanded in wavenumber space, with eastward propagation occurring in a wavenumber-frequency band between 300 and 1400 km and 0.5 and 2.0 cycles/yr. The third CEOF is similar in structure to the first, but with less energy. CEOF 4 was clearly identifiable with higher frequencies than the first three with westward propagation at 4 km/d. The spatial location of this mode along with the westward propagation indicates possible influences from eddy-stream interactions. Thus topography, Rossby wave dynamics and eddy-stream interactions all appear to have a significant role in determining the space-time scales and propagation properties of the long-period response of sea level in the Gulf Stream.

Vazquez, Jorge↗
NASA NTRS2017

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Priori↗