Search NASA⌕ Search

SEARCH · Search NASA

Results for “Satellite-Observed Data”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3

Interannual variability and climatic noise in satellite-observed outgoing longwave radiation

Upwelling-IR observations of the North Pacific by polar orbiters NOAA 3, 4, 5, and 6 and TIROS-N from 1974 to 1981 are analyzed statistically in terms of interannual variability (IAV) in monthly averages and climatic noise due to short-term weather fluctuations. It is found that although the daily variance in the observations is the same in summer and winter months, and although IAV in winter is smaller than that in summer, the climatic noise in winter is so much smaller that a greater fraction of winter anomalies are statistically significant. The smaller winter climatic noise level is shown to be due to shorter autocorrelation times. It is demonstrated that increasing averaging area does not reduce the climatic noise level, suggesting that continuing collection of high-resolution satellite IR data on a global basis is necessary if better models of short-term variability are to be constructed.

Short, D. A.↗

Interpretation of satellite-observed thunderstorm anvil structure

The radiative characteristics of an anvil plume sensed by satellite radiometers are studied to discern the reason for an observed 'V' pattern of colder temperatures and a corresponding internal warm region. The measured black body temperature is affected by the ice water content and particle distributions in the cloud layer. Attention is given to 'V' anvil structure examined by Haynesfield et al. (1979). The GOES satellite IR data are treated with a plane parallel geometric radiative transfer model and a particle trajectory model is used to simulate ice particle concentrations downwind from a strongly divergent cloud top. Output from the two models indicate the 'V' pattern arises from divergence in the storm anvil. The particle concentration was elevated within the V-shaped region, causing lower temperatures in the V arms. The V is produced by strong upper level flow as well as strong mass and moisture divergence in the storm outflow.

Heymsfield, G. M.↗

Satellite-observed characteristics of midwest severe thunderstorm anvils

The cloud top and anvil structure of severe thunderstorms observed by the GOES satellite are analyzed for five SESAME cases in 1979 and four non-SESAME cases in 1980-1982. The data is compared with previous models and hypotheses, paying particular attention to the V feature and thermal couplets in the IR observations. The characteristics of the cases are examined and related to the upper-level temperature and wind conditions. It is found that the warm points downwind of the cloud top are due to subsidence. The anaylsis suggests the presence of subsidence due to mountainlike waves. A model in which the close-in warm point is produced by both internal cloud air motions and stratospheric flow around and over the cloud top. It is suggested that the distant warm point is due to either a wave perturbation from air flowing over the cloud top, or air flowing horizonatlly around the elevated portion of the cloud top and anvil.

Heymsfield, Gerald M.↗

Cloud parameters derived from GOES during the 1987 marine stratocumulus FIRE Intensive Field Observation (IFO) period

The Geostationary Operational Environmental Satellite (GOES) is well suited for observations of the variations of clouds over many temporal and spatial scales. For this reason, GOES data taken during the Marine Stratocumulus Intensive Field Observations (IFO) (June 29 to July 19, 1987, Kloessel et al.) serve several purposes. One facet of the First ISCCP Regional Experiment (FIRE) is improvement of the understanding of cloud parameter retrievals from satellite-observed radiances. This involves comparisons of coincident satellite cloud parameters and high resolution data taken by various instruments on other platforms during the IFO periods. Another aspect of FIRE is the improvement of both large- and small-scale models of stratocumulus used in general circulation models (GCMs). This may involve, among other studies, linking the small-scale processes observed during the IFO to the variations in large-scale cloud fields observed with the satellites during the IFO and Extended Time Observation (ETO) periods. Preliminary results are presented of an analysis of GOES data covering most of the IFO period. The large scale cloud-field characteristics are derived, then related to a longer period of measurements. Finally, some point measurements taken from the surface are compared to regional scale cloud parameters derived from satellite radiances.

Young, David F.↗

Effect of cloud boundaries on reflected radiation

The effects of cloud boundaries on cloud reflectivity are evaluated by comparing satellite-observed reflectivities for layered clouds that are uniform over scales that are large compared with the field of view of the satellite radiometer and those of the same clouds where they are broken on scales which are small compared with the field of view. Results are given for 1 km AVHRR data. The reflectivities are compared at 0.63 micron for which droplets in stratiform water clouds are nonabsorbing, and at 3.7 microns where the single-scattering albedo of the droplets is typically about 0.9 micron.

Coakley, James A., Jr.↗

Toward a dynamic-thermodynamic assimilation of satellite surface temperature in numerical atmospheric models

An assimilation technique is described in which satellite-observed surface skin temperature tendencies are used in a model surface energy budget so that the predicted rate of temperature change in the model more closely agrees with the satellite observations. Both visible and infrared GOES satellite data are used in the assimilation. The technique is based on analytically recovering surface moisture from similarity expressions derived from an evapotranspiration residual obtained as a difference between the unadjusted model evapotranspiration and the satellite-inferred evapotranspiration. The technique has application in regional-scale models where surface parameters such as root zone moisture, soil moisture, etc., are unknown. It is assumed that the largest error in the surface energy budget is in the evapotranspiration term. Two tests are given for the technique, first, a one-dimensional test against FIFE data and, second, a three-dimensional test over Oklahoma. In these cases the technique appears to correctly adjust the model response to agree better with observations.

Mcnider, Richard T.↗

Comparison of cloud fields from atmospheric general circulation model, in situ and satellite measurements

This paper focuses on the comparison of cloud amounts derived from an atmospheric general circulation model (AGCM), Satellite-observed clouds, and Ground-based cloud observations. Unlike Earth Radiation Budget Experiment (ERBE)-type comparisons it does not mix potential errors in the cloud amount with those in the radiation code embedded in the model. Long term cloud climatologies were used to compare global cloud amounts and regional seasonal cycles. The AGCM successfully reproduced the signatures of the warm pool and North Pacific seasonal cycle cloudiness but failed in the low stratus region off the coast of South America, a known problem for AGCMs. The data sets also reproduced the anomaly signature associated with El Nino in the warm pool region, but the model amounts were lower. Global results had a similar success rate, with the model generally producing lower total cloud compared to the satellite and in situ measurements. To compare cloud vertical distributions the cloud height may need to be validated using the corresponding radiation fields. Unfortunately there were also some large discrepancies between the two observed cloud data sets. While tremendously improved over the last decade the character of the observed cloud data sets, must be substantially enhanced before they will be useful in validating AGCMs by any but the crudest levels of comparison.

Haskins, Robert D.↗

Global equatorial ionospheric vertical plasma drifts measured by the AE-E satellite

Ion drift meter observations from the Atmosphere Explorer E (AE-E) satellite during the period of January 1977 to December 1979 are used to study the dependence of equatorial (dip latitudes less than or equal to 7.5 deg) F region vertical plasma drifts (east-west electric fields) on solar activity, season, and longitude. The satellite-observed ion drifts show large day-to-day and seasonal variations. Solar cycle effects are most pronounced near the dusk sector with a large increase of the prereversal velocity enhancement from solar minimum to maximum. The diuurnal, seasonal, and solar cycle dependence of the logitudinally averaged drifts are consistent with results from the Jicamarca radar except near the June solstice when the AE-E nighttime downward velocities are significantly smaller than those observed by the radar. Pronounced presunrise downward drift enhancements are often observed over a large longituudinal range but not in the Peruvian equatorial region. The satellite data indicate that longitudinal variations are largest near the June solstice, particularly near dawn and dusk but are virtually absent during equinox. The longitudinal dependence of the AE-E vertical drifts is consistent with results from ionosonde data. These measurements were also used to develop a description of equatorial F region vertical drifts in four longitudinal sectors.

Fejer, B. G.↗

Assimilation of Goes-Derived Skin Temperature Tendencies into Mesoscale Models to Improve Forecasts of near Surface Air Temperature and Mixing Ratio

A technique has been developed for assimilating GOES-FR skin temperature tendencies into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature chance closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. An advantage of this technique for short-range forecasts (0-48 h) is that it does not require a complex land-surface formulation within the atmospheric model. As a result, the need to specify poorly known soil and vegetative characteristics is eliminated. The GOES assimilation technique has been incorporated into the PSU/NCAR MM5. Results will be presented to demonstrate the ability of the assimilation scheme to improve short- term (0-48h) simulations of near-surface air temperature and mixing ratio during the warm season for several selected cases which exhibit a variety of atmospheric and land-surface conditions. In addition, validation of terms in the simulated surface energy budget will be presented using in situ data collected at the Southern Great Plains (SGP) Cloud And Radiation Testbed (CART) site as part of the Atmospheric Radiation Measurements Program (ARM).

Lapenta, William M.↗

NOAA/NASA/DOD Workshop on Satellite Data Assimilation

A workshop on the assimilation of satellite sounding information using global forecast and climate models was held at College Park, MD, 23-25 August 1999. Topics discussed included: comparisons of assimilations of satellite retrievals versus satellite-observed radiances, planning for the use of advanced infrared sounders, the use of satellite sounding data affected by land surfaces, radiative transfer issues, and error characteristics of models and observations. The workshop concluded with a number of general and specific recommendations to advance the state of the art of assimilation of satellite sounding data.

Errico, Ronald M.↗

A Unified Satellite-Observation Polar Stratospheric Cloud (PSC) Database for Long-Term Climate-Change Studies

This report summarizes the project team's activity and accomplishments during the period 12 February, 1999 - 12 February, 2000. The primary objective of this project was to create and test a generic algorithm for detecting polar stratospheric clouds (PSC), an algorithm that would permit creation of a unified, long term PSC database from a variety of solar occultation instruments that measure aerosol extinction near 1000 nm The second objective was to make a database of PSC observations and certain relevant related datasets. In this report we describe the algorithm, the data we are making available, and user access options. The remainder of this document provides the details of the algorithm and the database offering.

Fromm, Michael↗

Use of Geostationary Satellite Data to Force Land Surface Schemes within Atmospheric Mesoscale Models

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Lapenta, William M.↗

Assimilation of GOES Land Surface Data into a Mesoscale Models

A technique has been developed for assimilating Geostationary Operational Environmental Satellite (GOES)-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The assimilation technique has been applied to the Oklahoma-Kansas region during the spring-summer 2000 time period when dynamic changes in vegetation cover occur. In April, central Oklahoma is characterized by large NDVI associated with winter wheat while surrounding areas are primarily rangeland with lower NDVI. In July the vegetation pattern reverses as the central wheat area changes to low NDVI due to harvesting and the surrounding rangeland is greener than it was in April. The goal of this study is to determine if assimilating satellite land surface data can improve simulation of the complex spatial distribution of surface energy and water fluxes across this region. The PSU/NCAR NM5 V3 system is used in this study. The grid configuration consists of a 36-km CONUS domain and a 12-km nest over the area of interest. Bulk verification statistics (BIAS and RMSE) of surface air temperature and dewpoint indicates that assimilation of the satellite data results reduces both the bias and RMSE for both state variables. In addition, comparison of model data with ARM/CART EBBR flux observations reveals that the assimilation technique adjusts the bowen ratio in a realistic fashion.

Lapenta, William M.↗

Assimilation of GOES Land Surface Data Within a Rapid Update Cycle Format: Impact on MM5 Warm Season QPF

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The focus of this paper is to examine how the satellite assimilation technique impacts simulations of near-surface meteorology on the 0-to 12-hour time scale when implemented within a local rapid update cycle (LRUC) format. The PSU/NCAR MM5 V34 is used and configured with a 36-km CONUS domain and a 12-km nest centered over the southeastern US. The LRUC format consists of a sequence of 12-hour forecasts initialized every hour between 12 and 18 UTC seven days a week. GOES skin temperature tendencies and solar insolation are assimilated in a 1-hour period prior to the start of each twelve-hour forecast. A unique aspect of the LRUC is the satellite assimilation and the continuous recycling of the adjusted moisture availability field from one forecast cycle to the next. Preliminary results for a seven-day trial period indicate that hourly LST tendencies assimilated in a 1 hour LRUC showed improved simulated air and dewpoint temperatures for all cycles on each day. The LRUC will be used during the 2001 summer months to identify the impact of the assimilation on warm season QPF Results will be presented at the meeting.

Lapenta, William M.↗

Infrared Data for Storm Analysis

The papers in this section include: 1) 'Thunderstorm Top Structure Observed by Aircraft Overflights with an Infrared Radiometer'; 2) 'Thunderstorm Intensity as Determined from Satellite Data'; 3) 'Relation of Satellite-Based Thunderstorm Intensity to Radar-Estimated Rainfall'; 4) 'A Simple Physical Basis for Relating Geosynchronous Satellite Infrared Observations to Thunderstorm Rainfall'; 5) 'Satellite-Observed Cloud-Top Height Changes in Tornadic Thunderstorms'; 6) 'Predicting Tropical Cyclone Intensity Using Satellite-Measured Equivalent Blackbody Temperatures of Cloud Tops'.

Adler, R.↗

Exploring the Production of NOx by Lightning and Its Impact on Tropospheric Ozone

Our quantitative understanding of free tropospheric (FT) chemistry is quite poor. State-of-the-art regional air quality models (e.g., US EPA's CMAQ) perform very poorly in simulating FT chemistry, with Uniform ozone around 70 ppb throughout the FT in summer, while ozonesonde data show much higher levels of ozone and much spatial-temporal structure. Such models completely neglect lightning-NOx (LNOx) emissions (the most significant source of NOx in the FT), and also contain large uncertainties in the specifications of intercontinental transport, stratosphere-troposphere exchange (STE) and PBLFT exchange (PFTE). Global air chemistry models include LNOx, but in very crude fashion, with the frequency and distribution of lightning being based on modeled cloud parameters (hence large uncertainty), lightning energetics being assumed to be constant for all flashes (literature value, while in reality there is at least a two-orders of magnitude variability from flash-to-flash), and the production of NOx in the surrounding heated air, per Joule of heating, being assumed to be constant also (literature value, while in fact it is a non-linear function of the dissipated heat and local air density, p). This situation is commonly blamed on paucity of pertinent observational data, but for the USA, there is now a wealth of surface- and satellite-based data of lightning available to permit much improved observation-based estimation of LNOx emissions. In the FT, such NOx has a long residence time, and also the ozone production efficiency from NOx there is considerably higher than in the PBL. It is, therefore, of critical importance in FT chemistry. This paper will describe the approach and data products of an ongoing NSSTC project aimed at a much-improved quantification of not only LNOx production on the scale of continental USA based on local and regional lightning observations, but also of intercontinental transport, STE and PFTE, all in upgraded simulations of tropospheric transport and chemistry. In our approach for LNOx, (a) we utilize continuous observed lightning information from the NLDN ground network and from satellite imagers (OTD and LIS) to quantify lightning frequency and distribution at the spatial-temporal scales of models such as CMAQ; (b) we develop new methodologies to quantify flash-specific lightning energy dissipation as heat (epsilon) using data from the research-grade lightning measurement facility at NASA-KSC, and to parameterize epsilon based on regional lightning monitoring data (ground- and satellite-based); and, (c) we develop a new parameterization of NOx production as a function of epsilon and rho. Based on such observation-based information, we are working to develop a gridded, episodic LNOx emissions inventory for the USA for use in models like CMAQ. We are also developing approaches for global(MOZART)- regional(CMAQ) chemistry coupling to improve intercontinental transport and STE. Finally, we are developing new methodologies for assimilation of satellite-observed (GOES) clouds into meteorological modeling (MM5), to improve PFTE and to optimize co-location of cloud convection and observed lightning. We will incorporate these improvements in CMAQ simulations over the USA to better understand FT processes and chemistry, and its impact on ground-level ozone.

Gillani, Noor↗

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗

Satellite imaging reveals increased proportion of population exposed to floods

Flooding affects more people than any other environmental hazard and hinders sustainable development. Investing in flood adaptation strategies may reduce the loss of life and livelihood caused by floods. Where and how floods occur and who is exposed are changing as a result of rapid urbanization4, flood mitigation infrastructure and increasing settlements in floodplains6. Previous estimates of the global flood-exposed population have been limited by a lack of observational data, relying instead on models, which have high uncertainty. Here we use daily satellite imagery at 250-metre resolution to estimate flood extent and population exposure for 913 large flood events from 2000 to 2018. We determine a total inundation area of 2.23 million square kilometres, with 255–290 million people directly affected by floods. We estimate that the total population in locations with satellite-observed inundation grew by 58–86 million from 2000 to 2015. This represents an increase of 20 to 24 per cent in the proportion of the global population exposed to floods, ten times higher than previous estimates. Climate change projections for 2030 indicate that the proportion of the population exposed to floods will increase further. The high spatial and temporal resolution of the satellite observations will improve our understanding of where floods are changing and how best to adapt. The global flood database generated from these observations will help to improve vulnerability assessments, the accuracy of global and local flood models, the efficacy of adaptation interventions and our understanding of the interactions between landcover change, climate and floods.

B.Tellman↗