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All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

The Geoscience Laser Altimetry/Ranging System (GLARS)

The Geoscience Laser Altimetry Ranging System (GLARS) is a highly precise distance measurement system to be used for making extremely accurate geodetic observations from a space platform. It combines the attributes of a pointable laser ranging system making observations to cube corner retroreflectors placed on the ground with those of a nadir looking laser altimeter making height observations to ground, ice sheet, and oceanic surfaces. In the ranging mode, centimeter-level precise baseline and station coordinate determinations will be made on grids consisting of 100 to 200 targets separated by distances from a few tens of kilometers to about 1000 km. These measurements will be used for studies of seismic zone crustal deformations and tectonic plate motions. Ranging measurements will also be made to a coarser, but globally distributed array of retroreflectors for both precise geodetic and orbit determination applications. In the altimetric mode, relative height determinations will be obtained with approximately decimeter vertical precision and 70 to 100 meter horizontal resolution. The height data will be used to study surface topography and roughness, ice sheet and lava flow thickness, and ocean dynamics. Waveform digitization will provide a measure of the vertical extent of topography within each footprint. The planned Earth Observing System is an attractive candidate platform for GLARS since the GLAR data can be used both for direct analyses and for highly precise orbit determination needed in the reduction of data from other sensors on the multi-instrument platform. (1064, 532, and 355 nm)Nd:YAG laser meets the performance specifications for the system.

Cohen, S. C.↗
NASA NTRS2017

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗
NASA NTRS2007

Cloud Resolving Modeling

One of the most promising methods to test the representation of cloud processes used in climate models is to use observations together with cloud-resolving models (CRMs). CRMs use more sophisticated and realistic representations of cloud microphysical processes, and they can reasonably well resolve the time evolution, structure, and life cycles of clouds and cloud systems (with sizes ranging from about 2-200 km). CRMs also allow for explicit interaction between clouds, outgoing longwave (cooling) and incoming solar (heating) radiation, and ocean and land surface processes. Observations are required to initialize CRMs and to validate their results. This paper provides a brief discussion and review of the main characteristics of CRMs as well as some of their major applications. These include the use of CRMs to improve our understanding of: (1) convective organization, (2) cloud temperature and water vapor budgets, and convective momentum transport, (3) diurnal variation of precipitation processes, (4) radiative-convective quasi-equilibrium states, (5) cloud-chemistry interaction, (6) aerosol-precipitation interaction, and (7) improving moist processes in large-scale models. In addition, current and future developments and applications of CRMs will be presented.

Tao, Wei-Kuo↗
DOE OSTI2023

Measurement report: Understanding the seasonal cycle of Southern Ocean aerosols

Abstract. The remoteness and extreme conditions of the Southern Ocean and Antarctic region have meant that observations in this region are rare, and typically restricted to summertime during research or resupply voyages. Observations of aerosols outside of the summer season are typically limited to long-term stations, such as Kennaook / Cape Grim (KCG; 40.7∘ S, 144.7∘ E), which is situated in the northern latitudes of the Southern Ocean, and Antarctic research stations, such as the Japanese operated Syowa (SYO; 69.0∘ S, 39.6∘ E). Measurements in the midlatitudes of the Southern Ocean are important, particularly in light of recent observations that highlighted the latitudinal gradient that exists across the region in summertime. Here we present 2 years (March 2016–March 2018) of observations from Macquarie Island (MQI; 54.5∘ S, 159.0∘ E) of aerosol (condensation nuclei larger than 10 nm, CN10) and cloud condensation nuclei (CCN at various supersaturations) concentrations. This important multi-year data set is characterised, and its features are compared with the long-term data sets from KCG and SYO together with those from recent, regionally relevant voyages. CN10 concentrations were the highest at KCG by a factor of ∼50 % across all non-winter seasons compared to the other two stations, which were similar (summer medians of 530, 426 and 468 cm−3 at KCG, MQI and SYO, respectively). In wintertime, seasonal minima at KCG and MQI were similar (142 and 152 cm−3, respectively), with SYO being distinctly lower (87 cm−3), likely the result of the reduction in sea spray aerosol generation due to the sea ice ocean cover around the site. CN10 seasonal maxima were observed at the stations at different times of year, with KCG and MQI exhibiting January maxima and SYO having a distinct February high. Comparison of CCN0.5 data between KCG and MQI showed similar overall trends with summertime maxima and wintertime minima; however, KCG exhibited slightly (∼10 %) higher concentrations in summer (medians of 158 and 145 cm−3, respectively), whereas KCG showed ∼40 % lower concentrations than MQI in winter (medians of 57 and 92 cm−3, respectively). Spatial and temporal trends in the data were analysed further by contrasting data to coincident observations that occurred aboard several voyages of the RSV Aurora Australis and the RV Investigator. Results from this study are important for validating and improving our models and highlight the heterogeneity of this pristine region and the need for further long-term observations that capture the seasonal cycles.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2019

Global Assimilation of L-Band Brightness Temperature Observations from SMAP and SMOS into the Catchment Land Surface Model and Contribution to the Skill of Soil Moisture Estimates

The Soil Moisture Active Passive (SMAP) and Soil Moisture Ocean Salinity (SMOS) missions provide global observations of L-band (1.4 GHz) passive microwave brightness temperature (Tb) observations at a resolution of ~40 km every 2-3 days. These observations have been available since 2015 from SMAP and since 2010 from SMOS.Soil moisture estimates from the separate assimilation of SMAP and SMOS Tb observations into land surface models were previously shown to improve over model-only estimates, thereby demonstrating the value of assimilating L-band Tb observations for soil moisture estimation. The assimilation experiments documented in the literature do not, however, establish whether the joint assimilation of SMAP and SMOS Tbs improves the skill of the resulting soil moisture estimates beyond what can be achieved with either set of observations alone. Moreover, because the published SMAP and SMOS results used different assimilation systems and configurations and applied different evaluation data and procedures, it is unclear whether the assimilation of SMAP-only or SMOS-only Tbs results in better soil moisture skill. In this presentation, we compare the results of three separate assimilation experiments for the period from April 2015 to present. The experiments utilize the SMAP Level-4 Soil Moisture (L4_SM) algorithm, which assimilates L-band Tb observations into the NASA Catchment land surface model using a spatially distributed ensemble Kalman filter. Specifically, the three experiments presented here assimilate (i) SMAP Tbs only, as in the L4_SM product, (ii) SMOS Tbs only, after interpolation of 40° incidence angle, and (iii) both SMAP and SMOS Tbs. In all other respects, the configuration of three experiments is identical, as is the validation of the output. Preliminary results suggest that the joint assimilation of SMAP and SMOS Tbs yields the most skillful soil moisture estimates when compared to independent in situ measurements. Moreover, the skill of the SMAP-only assimilation exceeds that of the SMOS-only assimilation. The presentation provides an in-depth evaluation of the skill of the assimilation estimates vs. independent in situ and satellite measurements and in terms of statistics of the observation-minus-forecast residuals and analysis increments.

Reichle, Rolf↗
DOE OSTI2023

The Effect of Tropical Pacific Air‐Sea Coupling on the Rainfall Response to Quadrupled CO 2 Forcing

We perform quadrupled CO 2 climate simulations with the Community Earth System Model version 1 (CESM1) to study how air-sea coupling affects the response of tropical rainfall under global warming. We use a hierarchy of ocean models to separate the effects of seasonal mixed-layer entrainment, wind-driven Ekman flows directed perpendicular to the wind, and the near-equator frictional flows directed in the same direction as the wind. We show that the Pacific Ocean's enhanced equatorial warming pattern (EEW) and equatorward ITCZ contraction observed in previous climate simulations emerge when the ocean model includes wind-driven Ekman and frictional flows. Furthermore, the near-equator frictional flow contributes more than half of the heat convergence in the equatorial Pacific Ocean. Finally, we show that although Ekman flow and near-equator frictional flow can both result in EEW, their coupled interactions with the Hadley circulation lead to opposite feedbacks on EEW's strength.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Early Spring in Europe: A Result of More Dominant North-Atlantic Southwesterlies?

Abstract A 1999 study reports an advancement of spring in Europe by 0.2 days per year in the 30 years since 1960. Our analysis indicates that this trend results directly from a change in the late-winter surface winds over the eastern North Atlantic: the southwesterly direction became more dominant, and the speed of these southwesterlies increased slightly. Splitting the 52-year NCEP reanalysis dataset into the First Half, FH (1948-1973)), and the Second Half, SH (1974-1999), we analyze the wind direction for the February mean at three sites at 45N: site A at 30W, site B at 20W, and site C at 10W. The incidence (number of years) of the southwesterlies in SH Vs. (FH) at these sites respectively increased in SH as follows: 24(18), 19(12), 14(l 1); whereas the incidence of northeasterlies decreased: 0(2), 1(2), and 1(6). When the February mean wind is southwesterly, the monthly mean sensible heat flux from the ocean at these sites takes zero or slightly negative values, that is, the surface air is warmer than the ocean. Analyzing the scenario in the warm late winter 1990, we observe that the sensible heat flux from the ocean surface in February 1990 shows a "tongue" of negative values extending southwest from southern England to 7N. This indicates that the source of the maritime air advected into Europe lies to the south of the "tongue." Streamline analysis suggests that the Southwestern or southcentral North Atlantic is the source. For February 1990, we find strong, ascending motions over Europe at 700 mb, up to -0.4 Pa/s as monthly averages. Associated with the unstable low-levels of the troposphere are positive rain and cloud anomalies. Thus, positive in situ feedback over land in late winter (when shortwave absorption is not significant) apparently further enhances the surface temperature through an increase in the greenhouse effect due to increased water vapor and cloudiness.

Otterman, J.↗
NASA NTRSDate not supplied

From the Interstellar Medium to Ocean Worlds: new challenges for Laboratory Astrophysics

From the Interstellar Medium to Ocean Worlds: new challenges for Laboratory Astrophysics For the past 35+ years, laboratory experiments in Astrophysics have been focusing on identifying and understanding the molecular species and chemistry occurring in interstellar environments, such as the diffuse interstellar medium (ISM) and dense molecular clouds. A significant portion of these laboratory efforts concerns investigations of carbon-based molecules ranging in size from a single carbon atom (e.g., CO, CO2, H2CO) to large polycyclic aromatic hydrocarbon (PAH) molecules potentially consisting of more than one hundred carbon atoms as well as their reactions with H2O and other interstellar species. The laboratory facilities built to conduct these investigations are capable of monitoring the chemistry and measuring the spectra under a wide range of interstellar conditions (e.g., low temperatures and pressures). The past 15 years of space exploration revealed the presence of at least nine other Ocean Worlds, besides Earth, in our Solar System. These worlds include moons and dwarf planets, ice-covered surfaces, subsurface oceans, as well as geysers venting H2O and other compounds, including organics in at least one environment, into space. Although these worlds represent environments that are significantly different from those traditionally considered the realm of Laboratory Astrophysics, their facilities are well situated to provide insight into the chemistry occurring in and around these worlds as well as experimental data for the interpretation of observations from missions visiting these Ocean World. This presentation will discuss the areas where Laboratory Astrophysics can provide experimental data to help understand the chemistry, and mission data of Ocean Worlds, and the challenges research into Ocean Worlds presents to our current facilities and how they can be overcome. Lastly, this presentation will introduce the new ICEE (In-situ Carbon Evolution Experiments) facility at NASA Ames Research Center as an example of how a lab dedicated to Laboratory Astrophysics can adapt itself to also meet the needs for Ocean Worlds research.

Andrew Lige Mattioda↗
NASA NTRS2017

CERES S’COOL Project Update: The Evolution and Value of a Long-Running Education Project With a Foundation in NASA Earth Science Missions

In January 1997, the Students’ Cloud Observations On-Line (S’COOL; http://scool.larc.nasa.gov) Project began with NASA scientists visiting rural Gloucester, Virginia to observe clouds with middle school students. In the 19 years since, this educational outreach component of NASA’s Clouds and the Earth’s Radiant Energy System (CERES) mission has collected ~141,000 observations from every continent and ocean basin around the world. Thousands of students and teachers have directly engaged in S’COOL. Beginning in 2008 we invited citizen scientists to participate as well. Over time S’COOL has added more components that engage participants directly with science data analysis, continuing direct ties to CERES research. Whenever possible, the S’COOL team extracts corresponding subsets of CERES data, which are sent to the participant to analyze. Observations can now be matched to images and cloud retrievals from MODIS and measurements from CALIPSO. To date, more than half of S'COOL observation reports correspond to one (or more) CERES overpasses. Comparisons with CERES geostationary satellite cloud retrievals were recently added, making cloud observations at almost any time of day over non-polar regions useful for validation. A thorough analysis of co-located S’COOL and satellite data was conducted during summer 2015. Results show that the S’COOL community provides high quality observations offering useful insights on the strengths and shortcomings of passive cloud remote sensing from space. This reconfirmed the utility of S’COOL observations to the scientific community and provides observers with deeper insight into the challenges associated with validation of space-based cloud property retrievals.

Lin H Chambers↗
NASA NTRS2009

Overview of NASA Earth Observing Systems Terra and Aqua Moderate Resolution Imaging Spectroradiometer Instrument Calibration Algorithms and On-Orbit Performance

Since launch, the Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) instruments have successfully operated on-orbit for more than 9 and 6.5 years, respectively. Iv1ODIS, a key instrument for the NASA's Earth Observing System (EOS) missions, was designed to make continuous observations for studies of Earth's land, ocean, and atmospheric properties and to extend existing data records from heritage earth-observing sensors. In addition to frequent global coverage, MODIS observations are made in 36 spectral bands, covering both solar reflective and thermal emissive spectral regions. Nearly 40 data products are routinely generated from MODIS' observations and publicly distributed for a broad range of applications. Both instruments have produced an unprecedented amount of data in support of the science community. As a general reference for understanding sensor operation and calibration, and thus science data quality, we ;provide an overview of the MODIS instruments and their pre-launch calibration and characterization, and describe their on-orbit calibration algorithms and performance. On-orbit results from both Terra and Aqua MODIS radiometric, spectral, and "spatial calibration are discussed. Currently, both instruments, including their on-board calibration devices, are healthy and are expected to continue operation for several }rears to come.

Xiong, Xiaoxiong↗
NASA NTRS2016

Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave Data

A primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.

Vegetation↗
NASA NTRS2022

Earth System Model Parameter Adjustment Using a Green's Functions Approach

We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

Green's Function↗
NASA NTRS1991

Predictability of a coupled ocean-atmosphere model

A study is presented to determine the limits on the predictability of the coupled ocean-atmosphere system. Following the classical methods developed for atmospheric predictability studies, the model used is one of the simplest that realistically reproduces many of the important features of the observed interannual variability of sea surface temperature in the tropical Pacific Ocean when forced by observed wind stresses. As no reasonable analysis is available for all the fields, initial conditions for these prediction experiments were taken from a model control run in which the ocean model was forced by the observed surface winds. The atmospheric component of the coupled model is not capable of accurately simulating the large-scale components of the observed wind stress.

Goswami, B. N.↗
NASA NTRS1986

High-resolution observations of low contrast phenomena from an advanced geosynchronous platform

Present technology allows radiometric monitoring of the earth, ocean and atmosphere from a geosynchronous platform with good spatial, spectral and temporal resolution. The proposed system could provide a capability for multispectral remote sensing with a 50 m nadir spatial resolution in the visible bands, 250 m in the 4 micron band and 1 km in the 11 micron thermal infrared band. The diffraction limited telescope has a 1 m aperture, a 10 m focal length (with a shorter focal length in the infrared) and linear and area arrays of detectors. The diffraction limited resolution applies to scenes of any brightness but for a dark low contrast scenes, the good signal to noise ratio of the system contribute to the observation capability. The capabilities of the AGP system are assessed for quantitative observations of ocean scenes. Instrument and ground system configuration are presented and projected sensor capabilities are analyzed.

Maxwell, M. S.↗
NASA NTRS1997

Geosat Data Assimilation with Application to the Eastern North Atlantic

An attempt is made to determine the three-dimensional ocean circulation from satellite altimeter measurements by assimilating Geosat sea surface height data into an eddy-resolving QuasiGeostrophic (QG) model of the eastern North Atlantic Ocean. Results are tested against independent information from hydrographic field observations and moored current meter data collected during the Geosat ERM. The comparison supports the concept of inferring aspects of the three-dimensional flow field from sea surface height observations by combining altimetric measurements with the dynamics of ocean circulation models. A Holland-type QG model with open boundaries is set up on a 2000 km X 2000 km domain of the eastern North Atlantic between 25 deg. and 45 deg. N, 32 deg. and 8 deg. W. By using a simple nudging technique, about two years of Geosat altimeter data are assimilated into the model every five days as space-time objective analyses on the model grid. The error information resulting from the analysis is used during the assimilation procedure to account for data uncertainties. Results show an intense eddy field, which in the surface layer interacts with a meandering Azores Front. Compared to Geosat, the model leads to smoothed fields that follow the observations. Model simulations are significantly correlated with hydrographic data from March 1988 and June 1989, both close to the surface and in the subsurface. Good agreement is also found between the model velocity fields and moored current meter data in the top two model layers. The agreement is visually weak in the bottom layer, although a coherence analysis reveals an agreement between the model simulation and current meter data over the full water column at periods exceeding 80 days.

Stammer, Detlef↗
NASA NTRS2018

Biogeochemical Effects of Rising Atmospheric CO2 on Terrestrial and Ocean Systems

Rising carbon dioxide (CO2) has decreased seawater pH at long-term observing stations around the world, including in the open ocean north of Oahu, Hawaii, near Alaska's Aleutian Islands, the Gulf of Maine shore, and on Gray's Reef in the southeastern United States. This ocean acidification process has already affected some marine species and altered fundamental ecosystem processes, and further effects are likely. While atmospheric CO rises at approximately the same rate all over the globe, its non-climate effects on land vary depending on climate and dominant species. In terrestrial ecosystems, rising atmospheric CO concentrations are expected to increase plant photosynthesis, growth, and water-use efficiency, though these effects are reduced when nutrients, drought or other factors limit plant growth. Rising CO would likely change carbon storage and influence terrestrial hydrology and biogeochemical cycling, but concomitant effects on vegetation composition and nutrient feedbacks are challenging to predict, making decadal forecasts uncertain. Consequences of rising atmospheric CO are expected to include difficult-to-predict changes in the ecosystem services that terrestrial and ocean systems provide to humans. For instance, ocean acidification resulting from rising CO has decreased the supply of larvae that sustains commercial shellfish production in the northwestern United States. In addition, CO fertilization (increases) plus warming (decreases) are changing terrestrial crop yields. Continued persistence of uptake of carbon by the land and ocean is uncertain. Climate and environmental change create complex feedbacks to the carbon cycle and it is not clear how feedbacks modulate future effects of rising CO on carbon sinks. These are several mechanisms that could reduce future sink capacity.

Biogeochemical↗
NASA NTRS2021

Observation of absorbing aerosols above clouds over the South-East Atlantic Ocean from the geostationary satellite SEVIRI - Part 2: Comparison with MODIS and aircraft measurements from the CLARIFY-2017 field campaign

To evaluate the SEVIRI retrieval for aerosols above clouds presented in Part 1 of the companion paper, the algorithm is applied over the south-east Atlantic Ocean during the CLARIFY-2017 field campaign period. The first step of our analysis compares the retrieved aerosol and cloud properties against equivalent products from the MODIS MOD06ACAERO retrieval (Meyer et al., 2015). While the correlation between the two satellite retrievals of the above-cloud aerosol optical thickness (AOT) is good (R = 0.78), the AOT retrieved by SEVIRI is 20.3 % smaller than that obtained from the MODIS retrieval. This difference in AOT is attributed mainly to the more absorbing aerosol model assumed for the SEVIRI retrieval compared to MODIS. The underlying cloud optical thickness (COT) derived from the two satellites is in good agreement (R = 0.90). The cloud droplet effective radius (CER) retrieved by SEVIRI is consistently smaller than MODIS by 2.2 µm, which is mainly caused by the use of different spectral bands of the satellite instruments. In the second part of our analysis, we compare the forecast water vapour profiles used for the SEVIRI atmospheric correction as well as the aforementioned aerosol and cloud products with in situ measurements made from the Facility for Airborne Atmospheric Measurements (FAAM) aircraft platform during the CLARIFY-2017 campaign. Around Ascension Island, the column water vapour used to correct the SEVIRI signal is overestimated by 3.1 mm in the forecast compared to that measured by dropsondes. However, the evidence suggests that the accuracy of the atmospheric correction improves closer to the African coast. Consistency is observed between the SEVIRI above-cloud AOT and in situ measurements (from cavity ring-down spectroscopy instruments) when the measured single-scattering albedo is close to that assumed in the retrieval algorithm. On the other hand, the satellite retrieval overestimates the AOT when the assumed aerosol model is not absorbing enough. Consistency is also found between the cloud properties retrieved by SEVIRI and the CER measured by a cloud droplet probe and the liquid water path derived from a microwave radiometer. Despite the instrumental limitations of the geostationary satellite, the consistency obtained between SEVIRI, MODIS and the aircraft measurements demonstrates the ability of the retrieval in providing additional information on the temporal evolution of the aerosol properties above clouds.

absorbing aerosols↗
NASA NTRS2001

E-Theatre

Mesoscale/severe storms and results from Terra Fritz Hasler (NASA/Goddard) will show the latest spectacular animations of the hurricanes and tropical storms: Floyd, Georges, Mitch, Bonnie etc. from Geostationary Operational Environmental Satellites (GOES) and Tropical Rain Measuring Mission (TRMM) supported by MMS 3D nested numerical model results. See dust storms in Africa and smoke plumes from fires in Mexico. See how High-Definition Television (HDTV) is revolutionizing entertainment and the way we communicate scientific results. Fly in from space and take a tour of Africa. Drop in on Albuquerque using 1-m Ikonos 'Spy Satellite' technology. See data from the new Earth Observing System (EOS) Terra satellite as well as Landsat 7, and SeaWiFS. See climate change in action with Global Land and Ocean productivity changes over the last 20 years. Remote sensing observations of Sea Surface Temperature (SST), El Nino, height, winds and ocean color from GOES, National Oceanic and Atmosphere Administration Advanced Very High Resolution Radiometer (AVHRR), Special Sensor Microwave Imager (SSMI), and SeaWiFS put in context with ten year LANL global ocean model. Compare the Gulf Stream observed by Terra with the simulations. Additional information is contained in the original extended abstract.

Hasler, Arthur F.↗