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At least 271 records · Page 15

An assessment of the impact of system spectral response parameters on spectral shape and algal bloom detection for the GeoXO ocean color instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A large dataset in-situ spectra, from a variety of locations and water cases collected with an above water spectrometer, was used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX.

Monica Cook↗

Simulation of Continental Shallow Cumulus Populations Using an Observation-Constrained Cloud-System Resolving Model

Continental shallow cumulus (ShCu) clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign are simulated by using an observation-constrained cloud-system resolving model. On this day, ShCu forms over Oklahoma and southern Kansas and some of these clouds transition to deeper, precipitating convection during the afternoon. We apply a four-dimensional ensemble-variational (4DEnVar) hybrid technique in the Community Gridpoint Statistical Interpolation (GSI) system to assimilate operational data sets and unique boundary layer measurements including a Raman lidar, radar wind profilers, radiosondes, and surface stations collected by the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) atmospheric observatory into the Weather Research and Forecasting (WRF) model to ascertain how improved environmental conditions can influence forecasts of ShCu populations and the transition to deeper convection. Independent observations from aircraft, satellite, as well as ARM's remote sensors are used to evaluate model performance in different aspects. Several model experiments are conducted to identify the impact of data assimilation (DA) on the prediction of clouds evolution. The analyses indicate that ShCu populations are more accurately reproduced after DA in terms of cloud initiation time and cloud base height, which can be attributed to an improved representation of the ambient meteorological conditions and the convective boundary layer. Extending the assimilation to 18 UTC (local noon) also improved the simulation of shallow-to-deep transitions of convective clouds.

54 ENVIRONMENTAL SCIENCES↗

Convective Entrainment Rates Estimated from Aura CO and CloudSat/CALIPSO Observations and Comparison with GEOS-5

Entrainment rate (λ) in convective parameterizations remains a sensitive parameter with much uncertainty in model simulations. This study estimates λ using carbon monoxide (CO) measurements jointly from the Microwave Limb Sounder (MLS) and Tropospheric Emission Spectrometer (TES) onboard the Aura satellite, associated with deep convective cases identified by CloudSat and CALIPSO observations. CO is treated as a conserved quantity over convective transport time scales and a simple entraining-plume model is used to derive entrainment rates. The relationships of the observational estimates of λ as a function of convective height, environmental relative humidity and convective available potential energy (CAPE) derived from Atmospheric Infrared Sounder (AIRS) data are compared with those from Goddard Earth Observing System Model (GEOS-5) simulations. Bulk statistics of λ show that the values of λ are predominately below 20% km(exp-1) for deep convection and the occurrence frequency of any λ decreases with increasing λ. Composite λ values are generally lower in the tropics compared to northern mid-latitudes in both observations and the GEOS-5 model. A decrease of λ with increasing convective height is found in both observations and model simulations. We also find that λ tends to decrease with increasing CAPE in the observation-based λ’s and plume-based GEOS-5 λ’s, although the model given λ’s have a non-monotonic relation with CAPE. The observed λ’s have a weak relation with lower-to-mid tropospheric RH, while both GEOS-5 plume-based and given λ increases with increasing RH.

Ryan E Stanfield↗

An Initial Assessment of the Impact of System Spectral Response Parameters on Driving Ocean Color Applications for the GeoXO Ocean Color Instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A dataset of high resolution (1 nm spectral sampling) in-situ spectra of red tide collected with an above water spectrometer, and associated K. brevis cell concentrations, were used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX. Future work will seek to expand this analysis to include a larger dataset that considers additional water cases.

Monica Cook↗

An Initial Assessment of the Impact of System Spectral Response Parameters on Driving Ocean Color Applications for the GeoXO Ocean Color Instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A dataset of high resolution (1 nm spectral sampling) in-situ spectra of red tide collected with an above water spectrometer, and associated K. brevis cell concentrations, were used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX. Future work will seek to expand this analysis to include a larger dataset that considers additional water cases.

M. Cook↗

Effects of Greenhouse Gas Increase and Stratospheric Ozone Depletion on Stratospheric Mean Age of Air in 1960-2010

The relative impacts of greenhouse gas (GHG) increase and stratospheric ozone depletion on stratospheric mean age of air in the 1960-2010 period are quantified using the Goddard Earth Observing System Chemistry-Climate Model. The experiment compares controlled simulations using a coupled atmosphere-ocean version of the Goddard Earth Observing System Chemistry-Climate Model, in which either GHGs or ozone depleting substances, or both factors evolve over time. The model results show that GHGs and ozone-depleting substances have about equal contributions to the simulated mean age decrease, but GHG increases account for about two thirds of the enhanced strength of the lower stratospheric residual circulation. It is also found that both the acceleration of the diabatic circulation and the decrease of the mean age difference between downwelling and upwelling regions are mainly caused by GHG forcing. The results show that ozone depletion causes an increase in the mean age of air in the Antarctic summer lower stratosphere through two processes: (1) a seasonal delay in the Antarctic polar vortex breakup that inhibits young midlatitude air from mixing with the older air inside the vortex, and (2) enhanced Antarctic downwelling that brings older air from middle and upper stratosphere into the lower stratosphere.

stratospheric ozone depletion↗

Preprocessing: Geocoding of AVIRIS data using navigation, engineering, DEM, and radar tracking system data

Remotely sensed data have geometric characteristics and representation which depend on the type of the acquisition system used. To correlate such data over large regions with other real world representation tools like conventional maps or Geographic Information System (GIS) for verification purposes, or for further treatment within different data sets, a coregistration has to be performed. In addition to the geometric characteristics of the sensor there are two other dominating factors which affect the geometry: the stability of the platform and the topography. There are two basic approaches for a geometric correction on a pixel-by-pixel basis: (1) A parametric approach using the location of the airplane and inertial navigation system data to simulate the observation geometry; and (2) a non-parametric approach using tie points or ground control points. It is well known that the non-parametric approach is not reliable enough for the unstable flight conditions of airborne systems, and is not satisfying in areas with significant topography, e.g. mountains and hills. The present work describes a parametric preprocessing procedure which corrects effects of flight line and attitude variation as well as topographic influences and is described in more detail by Meyer.

Meyer, Peter↗

Cloud model-based simulations of satellite microwave data and their application to an SSM/I rain algorithm

Satellite microwave observations of convective rain systems are simulated using a three-dimensional cloud model and a microwave radiative-transfer model. The simulated data sets are then used as a basis to derive rain estimation algorithms which are tested on actual satellite data. A tropical simulation is discussed, and the algorithms are applied to SSM/I data.

Adler, Robert F.↗

Computer simulations of space-borne meteorological systems on the CYBER 205

Because of the extreme expense involved in developing and flight testing meteorological instruments, an extensive series of numerical modeling experiments to simulate the performance of meteorological observing systems were performed on CYBER 205. The studies compare the relative importance of different global measurements of individual and composite systems of the meteorological variables needed to determine the state of the atmosphere. The assessments are made in terms of the systems ability to improve 12 hour global forecasts. Each experiment involves the daily assimilation of simulated data that is obtained from a data set called nature. This data is obtained from two sources: first, a long two-month general circulation integration with the GLAS 4th Order Forecast Model and second, global analysis prepared by the National Meteorological Center, NOAA, from the current observing systems twice daily.

Halem, M.↗

Design of a nickel-hydrogen battery simulator for the NASA EOS testbed

The hardware and software design of a nickel-hydrogen (Ni-H2) battery simulator (BS) with application to the NASA Earth Observation System (EOS) satellite is presented. The battery simulator is developed as a part of a complete testbed for the EOS satellite power system. The battery simulator involves both hardware and software components. The hardware component includes the capability of sourcing and sinking current at a constant programmable voltage. The software component includes the capability of monitoring the battery's ampere-hours (Ah) and programming the battery voltage according to an empirical model of the nickel-hydrogen battery stored in a computer.

Gur, Zvi↗

High-Resolution NU-WRF Simulations of a Deep Convective-Precipitation System During MC3E: Comparisons Between Goddard Microphysics Schemes and Observations - Part 1

The Goddard microphysics scheme was recently improved by adding a 4th ice class (frozen dropshail). This new 4ICE scheme was implemented and tested in the Goddard Cumulus Ensemble model (GCE) for an intense continental squall line and a moderate,less-organized continental case. Simulated peak radar reflectivity profiles were improved both in intensity and shape for both cases as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified - Weather Research and Forecasting model (NU-WRF) and tested on an intense mesoscale convective system that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). The NU42WRF simulated radar reflectivities, rainfall intensities, and vertical and horizontal structure using the new 4ICE scheme agree as well as or significantly better with observations than when using previous versions of the Goddard 3ICE (graupel or hail) schemes. In the 4ICE scheme, the bin microphysics-based rain evaporation correction produces more erect convective cores, while modification of the unrealistic collection of ice by dry hail produces narrow and intense cores, allowing more slow-falling snow to be transported rearward. Together with a revised snow size mapping, the 4ICE scheme produces a more horizontally stratified trailing stratiform region with a broad, more coherent light rain area. In addition, the NU-WRF 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive open lateral boundaries

Regional Scale Model↗

Quantifying the Observability of CO2 Flux Uncertainty in Atmospheric CO2 Records Using Products from Nasa's Carbon Monitoring Flux Pilot Project

NASAs Carbon Monitoring System (CMS) Flux Pilot Project (FPP) was designed to better understand contemporary carbon fluxes by bringing together state-of-the art models with remote sensing datasets. Here we report on simulations using NASAs Goddard Earth Observing System Model, version 5 (GEOS-5) which was used to evaluate the consistency of two different sets of observationally constrained land and ocean fluxes with atmospheric CO2 records. Despite the strong data constraint, the average difference in annual terrestrial biosphere flux between the two land (NASA Ames CASA and CASA-GFED) models is 1.7 Pg C for 2009-2010. Ocean models (NOBM and ECCO2-Darwin) differ by 35 in their global estimates of carbon flux with particularly strong disagreement in high latitudes. Based upon combinations of terrestrial and ocean fluxes, GEOS-5 reasonably simulated the seasonal cycle observed at northern hemisphere surface sites and by the Greenhouse gases Observing SATellite (GOSAT) while the model struggled to simulate the seasonal cycle at southern hemisphere surface locations. Though GEOS-5 was able to reasonably reproduce the patterns of XCO2 observed by GOSAT, it struggled to reproduce these aspects of AIRS observations. Despite large differences between land and ocean flux estimates, resulting differences in atmospheric mixing ratio were small, typically less than 5 ppmv at the surface and 3 ppmv in the XCO2 column. A statistical analysis based on the variability of observations shows that flux differences of these magnitudes are difficult to distinguish from natural variability, regardless of measurement platform.

FPP↗

ECMWF/NMC/GLAS Joint Simulation Study

Simulation experiments to provide a quantitative assessment of the potential impact of proposed observing systems on large scale numerical weather prediction are conducted. Instruments to be simulated include current conventional and satellite observing systems, advanced passive sounders such as the AMTS and AMSU, and active LIDAR systems for the measurement of wind, temperature and humidity profiles. The potential impact of individual observing systems, the effect of coverage, resolution, accuracy and assimilation methodology are studied.

Atlas, R.↗

Thermodynamic Modeling of a Solid Oxide Fuel Cell to Couple with an Existing Gas Turbine Engine Model

The Controls and Dynamics Technology Branch at NASA Glenn Research Center are interested in combining a solid oxide fuel cell (SOFC) to operate in conjunction with a gas turbine engine. A detailed engine model currently exists in the Matlab/Simulink environment. The idea is to incorporate a SOFC model within the turbine engine simulation and observe the hybrid system's performance. The fuel cell will be heated to its appropriate operating condition by the engine s combustor. Once the fuel cell is operating at its steady-state temperature, the gas burner will back down slowly until the engine is fully operating on the hot gases exhausted from the SOFC. The SOFC code is based on a steady-state model developed by The U.S. Department of Energy (DOE). In its current form, the DOE SOFC model exists in Microsoft Excel and uses Visual Basics to create an I-V (current-voltage) profile. For the project's application, the main issue with this model is that the gas path flow and fuel flow temperatures are used as input parameters instead of outputs. The objective is to create a SOFC model based on the DOE model that inputs the fuel cells flow rates and outputs temperature of the flow streams; therefore, creating a temperature profile as a function of fuel flow rate. This will be done by applying the First Law of Thermodynamics for a flow system to the fuel cell. Validation of this model will be done in two procedures. First, for a given flow rate the exit stream temperature will be calculated and compared to DOE SOFC temperature as a point comparison. Next, an I-V curve and temperature curve will be generated where the I-V curve will be compared with the DOE SOFC I-V curve. Matching I-V curves will suggest validation of the temperature curve because voltage is a function of temperature. Once the temperature profile is created and validated, the model will then be placed into the turbine engine simulation for system analysis.

Brinson, Thomas E.↗

LWS Proposal to Provide Scientific Guidance and Modeling Support for the Ionospheric Mapping Mission

A data assimilation system for specifying the thermospheric density has been developed over the last several years. This system ingests GRACE/CHAMP-type in situ as well as SSULI/SSUSI remote sensing observations while making use of a physical model, the Coupled Thermosphere-Ionosphere Model (CTIM) (Fuller-Rowel1 et al., 1996). The Kalman filter was implemented as the backbone to the data assimilation system, which provides a statistically 'best' estimate as well as an estimate of the error in its state. The system was tested using a simulated thermosphere and observations. CHAMP data were then used to provide the system with a real data source. The results of this study are herein.

Richmond, Arthur D.↗

Reducing Southern Ocean Shortwave Radiation Errors in the ERA5 Reanalysis with Machine Learning and 25 Years of Surface Observations

Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SW down exhibited large errors (mean bias = 54 W m -2 , mean absolute error = 82 W m -2 , root-mean-square error = 132 W m -2 , and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SW down with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SW down using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.

54 ENVIRONMENTAL SCIENCES↗