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At least 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Simulation of the Impact of New Aircraft- and Satellite-Based Ocean Surface Wind Measurements on H*Wind Analyses and Numerical Forecasts

The Hurricane Imaging Radiometer (HIRAD) is a new airborne microwave remote sensor for hurricane observations that is currently under development by NASA Marshall Space Flight Center, NOAA Hurricane Research Division, the University of Central Florida and the University of Michigan. HIRAD is being designed to enhance the realtime airborne ocean surface winds observation capabilities of NOAA and USAF Weather Squadron hurricane hunter aircraft using the operational airborne Stepped Frequency Microwave Radiometer (SFMR). Unlike SFMR, which measures wind speed and rain rate along the ground track directly beneath the aircraft, HIRAD will provide images of the surface wind and rain field over a wide swath (~ 3 x the aircraft altitude). The present paper describes a set of Observing System Simulation Experiments (OSSEs) in which measurements from the new instrument as well as those from existing instruments (air, surface, and space-based) are simulated from the output of a detailed numerical model, and those results are used to construct H*Wind analyses. The H*Wind analysis, a product of the Hurricane Research Division of NOAA s Atlantic Oceanographic and Meteorological Laboratory, brings together wind measurements from a variety of observation platforms into an objective analysis of the distribution of wind speeds in a tropical cyclone. This product is designed to improve understanding of the extent and strength of the wind field, and to improve the assessment of hurricane intensity. See http://www.aoml.noaa.gov/hrd/data_sub/wind.html. Evaluations will be presented on the impact of the HIRAD instrument on H*Wind analyses, both in terms of adding it to the full suite of current measurements, as well as using it to replace instrument(s) that may not be functioning at the future time the HIRAD instrument is implemented. Also shown will be preliminary results of numerical weather prediction OSSEs in which the impact of the addition of HIRAD observations to the initial state on numerical forecasts of the hurricane intensity and structure is assessed.

Miller, Timothy↗
NASA NTRSDate not supplied

Effect of Rain-Adjusted Satellite Sea Surface Salinity on ENSO Predictions from the GMAO S2S Forecast System

ENSO has a significant impact on climate variability throughout the world and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of altimetry and in situ data lead to improved short-term forecasts of the coupled system. However, few studies have focused on improving the near-surface density/mixing through assimilation of satellite sea surface salinity (SSS). For expediency, most projects that do assimilate SSS do so as if these data were observed at the top model layer instead of at the surface. In rainy regions where buoyant water sits as a fresh lens at the surface, this assumption is likely invalid. Therefore, we adjust SSS so that it more accurately represents the salinity at the first model layer. The Rain Impact Model (RIM) uses a simple diffusion model to determine the near surface salinity gradient (i.e., 1 cm to 5 m). Satellite SSS data are modified using this near-surface salinity gradient, so the salinity values are now valid at the first model layer (we call this SSS@5m). We assess the impact of satellite SSS observations for near-surface dynamics within ocean reanalyses and how these impact dynamical ENSO forecasts using the NASA GMAO S2S coupled system. For all reanalysis experiments, all available along-track sea level and in situ observations are assimilated for 2011 to 2020 using the LETKF scheme (Penny et al., 2013). One reanalysis assimilates Aquarius /SMAP SSS as before. An additional reanalysis is performed assimilating the SSS@5m data. Validation statistics are compared for experiments that assimilate SSS (sub-optimally as before) versus the SSS@5m. We also compare results of coupled forecasts that are initialized from these reanalyses in spring. For all but the big La Niña in 2017, all NINO3.4 forecasts were improved by using the RIM. We will show that improved SSS estimates upgrades density and near-surface mixing leading to more accurate coupled air/sea interaction and better forecasts.

ENSO↗
DOE OSTI2020

Projecting Antarctica's contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)

Abstract. The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4 mm of global sea level rise, with a standard deviation of 3.7 mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 ∘C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles. We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Seasonal Variations of the Earth's Gravitational Field: An Analysis of Atmospheric Pressure, Ocean Tidal, and Surface Water Excitation

Monthly mean gravitational field parameters (denoted here as C(sub even)) that represent linear combinations of the primarily even degree zonal spherical harmonic coefficients of the Earth's gravitational field have been recovered using LAGEOS I data and are compared with those derived from gridded global surface pressure data of the National meteorological center (NMC) spanning 1983-1992. The effect of equilibrium ocean tides and surface water variations are also considered. Atmospheric pressure and surface water fluctuations are shown to be the dominant cause of observed annual C(sub even) variations. Closure with observations is seen at the 1sigma level when atmospheric pressure, ocean tide and surface water effects are include. Equilibrium ocean tides are shown to be the main source of excitation at the semiannual period with closure at the 1sigma level seen when both atmospheric pressure and ocean tide effects are included. The inverted barometer (IB) case is shown to give the best agreement with the observation series. The potential of the observed C(sub even) variations for monitoring mass variations in the polar regions of the Earth and the effect of the land-ocean mask in the IB calculation are discussed.

Dong, D,↗
NASA NTRS1986

A satellite passive 37-GHz scattering-based method for measuring oceanic rain rates

A combination of theory and measurement is used to develop a scattering-based method for quantitatively measuring rainfall over the ocean from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) 37-GHz observations. This technique takes the observed scattering effects of precipitation on 37-GHz brightness temperatures and applies it to the oceanic environment. It requires an estimate of the effective radiating temperature of the cloudy portion of the atmosphere, and a brightness temperature measurement of the cloud-free ocean surface. These two measurements bound all possible combinations of clear and cloudy conditions within a footprint in terms of bipolarized brightness temperatures. Any satellite-observed brightness temperature T(B) lower than these values is assumed to reflect scattering, which at 37 GHz is only due to precipitation-size hydrometeors. Because the technique involves linear transformation between dual polarized brightness temperature and rain rate, there are no nonlinear 'footprint filling' effects and a unique footprint-averaged rain rate results. It is shown that these SMMR-derived rain rates for five cases of convection over the Gulf of Mexico are closely related to simultaneously derived radar rain rates, having a correlation of 0.90. This technique is then applied to a massive squall line over the Gulf of Mexico, and the resulting rain rate distribution reflects features found in cloud top heights and texture inferred from GOES infrared and visible imagery.

Spencer, R. W.↗
NASA NTRS2019

An Ocean-Atmosphere Simulation for Studying Air-Sea Interactions

During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interaction between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. To remove this limitation, we aim to perform a coupled simulation using the km-scale GEOS atmosphere and the km-scale MIT ocean models. The initial attempt at the km-scale coupled simulation resulted in computational issues which will be presented here. As a preliminary step towards the km-scale objective, we present results from a high resolution but not yet km-scale simulation, wherein we have coupled a cubed-sphere-720 (~ 1/8) configuration of the GEOS atmosphere to a lat-lon-cap-1080 (~ 1/12) configuration of the MIT ocean. We compare near-surface diagnostics of this fully coupled ocean-atmosphere set-up to equivalent atmosphere-only and ocean-only simulations. A particular focus of the comparisons is the differences in interactions between Sea Surface Temperature (SST) and ocean surface wind for the coupled and uncoupled simulations. We discuss observed and modeled high temporal variability (~days) SST-wind cycle and how it is represented in the different systems. A mechanism for the cycle, which is driven by SST-wind feedback, is proposed.

Strobach, Ehud↗
NASA NTRS2014

Multi-Decadal Aerosol Variations from 1980 to 2009: A Perspective from Observations and a Global Model

Aerosol variations and trends over different land and ocean regions during 1980-2009 are analyzed with the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and observations from multiple satellite sensors and ground-based networks. Excluding time periods with large volcanic influences, the tendency of aerosol optical depth (AOD) and surface concentration over polluted land regions is consistent with the anthropogenic emission changes.The largest reduction occurs over Europe, and regions in North America and Russia also exhibit reductions. On the other hand, East Asia and South Asia show AOD increases, although relatively large amount of natural aerosols in Asia makes the total changes less directly connected to the pollutant emission trends. Over major dust source regions, model analysis indicates that the dust emissions over the Sahara and Sahel respond mainly to the near-surface wind speed, but over Central Asia they are largely influenced by ground wetness. The decreasing dust trend in the tropical North Atlantic is most closely associated with the decrease of Sahel dust emission and increase of precipitation over the tropical North Atlantic, likely driven by the sea surface temperature increase. Despite significant regional trends, the model-calculated global annual average AOD shows little changes over land and ocean in the past three decades, because opposite trends in different regions cancel each other in the global average. This highlights the need for regional-scale aerosol assessment, as the global average value conceals regional changes, and thus is not sufficient for assessing changes in aerosol loading.

atmopheric aerosols↗
NASA NTRS1975

On the use of the earth resources technology satellite /LANDSAT-1/ in optical oceanography

Observations of the Gulf Stream System in the Gulf of Mexico were obtained in synchronization with LANDSAT-1. Computer enhanced images, which are necessary to extract useful oceanic information, show that the current can be observed by color (diffuse radiance) or sea state (specular radiance) effects associated with the cyclonic boundary even in the absence of a surface thermal signature. The color effect relates to the spectral variations in the optical properties of the water and its suspended particles, and is studied by radiative transfer theory. Significant oceanic parameters identified are: the probability of forward scattering, and the ratio of scattering to total attenuation. Several spectra of upwelling diffuse light are computed as a function of the concentration of particles and yellow substance.

Maul, G. A.↗
DOE OSTI2025

Exploring Causal Relationships and Adjustment Timescales of Aerosol-Cloud Interactions in Geostationary Satellite Observations and CAM6 Using Wavelet Phase Coherence Analysis

We present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead-lag phase difference between cloud-proxy liquid water path (LWP) and aerosol-proxy cloud droplet number concentration ( N d ) in an Eulerian framework using satellite-based observations and climate model outputs. This approach allows us to identify the causality and dominant adjustment timescales governing the correlation between LWP and N d . Satellite observations indicate a more prevalent positive correlation between daytime LWP and N d regardless of whether LWP leads or lags N d . The positive cloud water response, associated with precipitation processes, typically occurs within 1 hr, while the negative response resulting from entrainment drying, usually takes 2–4 hr. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and N d compared to observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Two-Day Westward-Propagating Inertio-Gravity Waves during GoAmazon

The dynamical and thermodynamical features of Amazonian 2-day westward-propagating inertia–gravity (WIG) waves are examined. On the basis of a linear regression analysis of satellite brightness temperature and data from the 2014–15 Observations and Modeling of the Green Ocean Amazon (GoAmazon) field campaign, it is shown that Amazonian WIG waves exhibit structure and propagation characteristics consistent with the n = 1 WIG waves from shallow water theory. These WIG waves exhibit a pronounced seasonality, with peak activity occurring from March to May and a minimum occurring from June to September. Evidence is shown that mesoscale convective systems over the Amazon are frequently organized in 2-day WIG waves. Results suggest that many of the Amazonian WIG waves come from preexisting 2-day waves over the Atlantic, which slow down when coupled with the deeper, more intense convection over tropical South America. In contrast to WIG waves that occur over the ocean, Amazonian 2-day WIG waves exhibit a pronounced signature in surface temperature, moisture, and heat fluxes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Hydrometeor Transport and the Stratiform Water Budget in Amazonian Mesoscale Convective Systems

A significant portion of precipitation falls within the stratiform regions of mesoscale convective systems (MCSs). These regions are formed from convective clouds that have either weakened and formed a horizontally stratified structure or have advected hydrometeors to form a trailing-stratiform region, with further precipitation growth promoted by in situ dynamical and microphysical processes. Green Ocean Amazon 2014/5 (GoAmazon2014/5) field campaign observations are used to quantify the stratiform water budget of six MCSs (three each from the wet and dry seasons) utilizing the framework from Leary and Houze, with an emphasis on the transfer of hydrometeors (C A ) from the convective to the stratiform regions. The storms were predominantly leading-line/trailing-stratiform MCSs, but two had embedded convection in the stratiform region, which can complicate water budget calculations. A pulse-like pattern with a mean interval of 21 min occurs in C A during each storm resulting from a lag between the initial convective updrafts and the subsequent hydrometeor transport and sedimentation in the stratiform region. Here, the peaks in C A were followed by peaks in hydrometeor growth associated with the mesoscale updraft (C mu ) in the stratiform region. Averaged over the six storms, the positive contributions of C A and C mu to the stratiform water budget were roughly equal, although storm-to-storm variations existed. Negative contributions from evaporation below cloud base in the mesoscale downdraft and detrainment from the stratiform region into the nonprecipitating anvil cloud and environment accounted for 53% and 21% of the sum of C A and C mu , respectively, resulting in a mean stratiform region precipitation efficiency of 26%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

ARM data-oriented metrics and diagnostics package for climate model evaluation (ARM-DIAGS-V3) version 3

A Python-based metrics and diagnostics package is currently being developed by the ARM Infrastructure Team at Lawrence Livermore National Laboratory to facilitate the use of long-term high frequency measurements from the ARM program in evaluating the regional climate simulation of clouds, radiation, precipitation, and aerosols. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The CMIP model data sets are also included in the package to enable model inter-comparison as demonstrated in Zhang et al. (2018) and Zhang et al. (2020). The mean of the CMIP model can be served as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, aerosol optical depth, and radiative fluxes, with plan to extend to more fields, such as the evaluation of model simulated aerosol physicochemical properties and cloud microphysics properties. Process-oriented diagnostics focusing on aerosol, cloud, and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. In addition to the Southern Great Plains (SGP), North Slope of Alaska (NSA) and Tropical Western Pacific (TWP) atmospheric observatories in the ARMDIAGS version 2.0, the version 3.0 package have extended to the data collected at the ARM Eastern North Atlantic (ENA) atmospheric observatory and the Observation and Modeling of the Green Ocean Amazon (GOAMAZON) field campaign. The metrics and diagnostics package are currently built upon standard Python libraries and additional Python packages developed by DOE (CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first provide an overview of major metrics in section 2. The input data, which constitutes the core content of the metrics and diagnostics package, is summarized in section 3. A user's guide documenting the workflow/structure of the version 3.0 codes and including step-by-step instruction for running the package is described in section 4.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Morning boundary layer conditions for shallow to deep convective cloud evolution during the dry season in the central Amazon

Observations of the boundary layer (BL) processes are analyzed statistically for dry seasons of 2 years and in detail, as case studies, for 4 shallow convective days (ShCu) and 4 shallow-to-deep convective days (ShDeep) using a suite of ground-based measurements from the Observation and Modeling of the Green Ocean Amazon (GoAmazon 2014/5) Experiment. The BL stages in ShDeep days, from the nighttime to the cloudy mixing layer stage, are then described in comparison with ShCu days. Atmospheric thermodynamics and dynamics, environmental profiles, and surface turbulent fluxes were employed to compare these two distinct situations for each stage of the BL evolution. Particular attention is given to the morning transition stage, in which the BL changes from stable to unstable conditions in the early morning hours. Results show that the decrease in time duration of the morning transition on ShDeep days is associated with high humidity and well-established vertical wind shear patterns. Higher humidity since nighttime not only contributes to lowering the cloud base during the rapid growth of the BL but also contributes to the balance between radiative cooling and turbulent mixing during nighttime, resulting in higher sensible heat flux in the early morning. The sensible heat flux promotes rapid growth of the well-mixed layer, thus favoring the deeper BL starting from around 08:00 LST (UTC-4 h). Under these conditions, the time duration of morning transition is used to promote convection, having an important effect on the convective BL strength and leading to the formation of shallow cumulus clouds and their subsequent evolution into deep convective clouds. Statistical analysis was used to validate the conceptual model obtained from the case studies. Despite the case-to-case variability, the statistical analyses of the processes in the BL show that the described processes are very representative of cloud evolution during the dry season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Lifecycle of updrafts and mass flux in isolated deep convection over the Amazon rainforest: insights from cell tracking

Long-term observations of deep convective cloud (DCC) vertical velocity and mass flux were collected during the Observations and Modelling of the Green Ocean Amazon (GoAmazon2014/5) experiment. Precipitation echoes from a surveillance weather radar near Manaus, Brazil, are tracked to identify and evaluate the isolated DCC lifecycle evolution during the dry and wet seasons. A radar wind profiler (RWP) provides precipitation and air motion profiles to estimate the vertical velocity, mass flux, and mass transport rates within overpassing DCC cores as a function of the tracked cell lifecycle stage. The average radar reflectivity factor (Z), DCC area (A), and surface rainfall rate (R) increased with DCC lifetime as convective cells were developing, reached a peak as the cells matured, and decreased thereafter as cells dissipated. As the convective cells mature, cumulative DCC properties exhibit stronger updraft behaviors with higher upward mass flux and transport rates above the melting layer (compared with initial and later lifecycle stages). In comparison, developing DCCs have the lowest Z associated with weak updrafts, as well as negative mass flux and transport rates above the melting layer. Over the DCC lifetime, the height of the maximum downward mass flux decreased, whereas the height of the maximum net mass flux increased. During the dry season, the tracked DCCs had higher Z, propagation speed, and DCC area, and were more isolated spatially compared with the wet season. Dry season DCCs exhibit higher Z, mass flux, and mass transport rate while developing, whereas wet season DCCs exhibit higher Z, mass flux, and mass transport rates at later stages.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1969

Biological oceanography

Biological oceanography and ocean food resource development using satellite observation

Ewing, G. C.↗
NASA NTRS1979

Surface observations for the evaluation of geophysical measurements from Seasat

The surface observations used for direct comparison with Seasat-derived values at fixed locations and as input to analyzed fields of pressure, wind, air and sea temperatures, and surface dew point are discussed. These included measurements made by research vessels participating in the Gulf of Alaska Seasat Experiment (GOASEX) and NOAA research platforms in addition to aircraft observations and reports from the World Weather Watch. The application of these observations in describing the synoptic-scale winds over the ocean is discussed, and the sensitivity of the verification statistics to the type of data (observations from buoys, weather ships, and transient vessels with or without anemometers) is considered. Results of a preliminary comparison of wind fields derived from Seasat-A scatterometer observation with winds specified by several types of platforms are presented.

Wilkerson, J. C.↗
NASA NTRS1979

Combination solution for gravity field including altimetry

A previous global solution for the earth's gravitational field and station positions employed a combination of 21 weeks of Doppler tracking data from seven satellites, a complete set of 5-deg mean gravity anomalies, and geometric constraints from the worldwide satellite triangulation network on 17 of the stations. To this is now added geoid heights over the major part of the oceans obtained from GEOS 3 altimeter observations. The solution has a form based on the simple density-layer method and is equivalent to a solution in spherical harmonics to the tenth degree and order. The rms difference of 5-deg mean geoid heights of the new solution with the GEM 10 solution is 5.6 m.

Chovitz, B. H.↗