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NASA NTRS2006

Precipitation Measurements from Space: Why Do We Need Them?

Water is fundamental to the life on Earth and its phase transition between the gaseous, liquid, and solid states dominates the behavior of the weather/climate/ecological system. Precipitation, which converts atmospheric water vapor into rain and snow, is central to the global water cycle. It regulates the global energy balance through interactions with clouds and water vapor (the primary greenhouse gas), and also shapes global winds and dynamic transport through latent heat release. Surface precipitation affects soil moisture, ocean salinity, and land hydrology, thus linking fast atmospheric processes to the slower components of the climate system. Precipitation is also the primary source of freshwater in the world, which is facing an emerging freshwater crisis in many regions. Accurate and timely knowledge of global precipitation is essential for understanding the behavior of the global water cycle, improving freshwater management, and advancing predictive capabilities of high-impact weather events such as hurricanes, floods, droughts, and landslides. With limited rainfall networks on land and the impracticality of making extensive rainfall measurements over oceans, a comprehensive description of the space and time variability of global precipitation can only be achieved from the vantage point of space. This presentation will examine current capabilities in space-borne rainfall measurements, highlight scientific and practical benefits derived from these observations to date, and provide an overview of the multi-national Global Precipitation Measurement (GPM) Mission scheduled to be launched in the early next decade.

Hou, Arthur Y.↗

NASA NTRS2007

Precipitation Measurements from Space: The Global Precipitation Measurement Mission

Hou, Arthur Y.↗

NASA NTRS2013

File Specification for GEOS-5 FP (Forward Processing)

The GEOS-5 FP Atmospheric Data Assimilation System (GEOS-5 ADAS) uses an analysis developed jointly with NOAA's National Centers for Environmental Prediction (NCEP), which allows the Global Modeling and Assimilation Office (GMAO) to take advantage of the developments at NCEP and the Joint Center for Satellite Data Assimilation (JCSDA). The GEOS-5 AGCM uses the finite-volume dynamics (Lin, 2004) integrated with various physics packages (e.g, Bacmeister et al., 2006), under the Earth System Modeling Framework (ESMF) including the Catchment Land Surface Model (CLSM) (e.g., Koster et al., 2000). The GSI analysis is a three-dimensional variational (3DVar) analysis applied in grid-point space to facilitate the implementation of anisotropic, inhomogeneous covariances (e.g., Wu et al., 2002; Derber et al., 2003). The GSI implementation for GEOS-5 FP incorporates a set of recursive filters that produce approximately Gaussian smoothing kernels and isotropic correlation functions. The GEOS-5 ADAS is documented in Rienecker et al. (2008). More recent updates to the model are presented in Molod et al. (2011). The GEOS-5 system actively assimilates roughly 2 × 10(exp 6) observations for each analysis, including about 7.5 × 10(exp 5) AIRS radiance data. The input stream is roughly twice this volume, but because of the large volume, the data are thinned commensurate with the analysis grid to reduce the computational burden. Data are also rejected from the analysis through quality control procedures designed to detect, for example, the presence of cloud. To minimize the spurious periodic perturbations of the analysis, GEOS-5 FP uses the Incremental Analysis Update (IAU) technique developed by Bloom et al. (1996). More details of this procedure are given in Appendix A. The assimilation is performed at a horizontal resolution of 0.3125-degree longitude by 0.25- degree latitude and at 72 levels, extending to 0.01 hPa. All products are generated at the native resolution of the horizontal grid. The majority of data products are time-averaged, but four instantaneous products are also available. Hourly data intervals are used for two-dimensional products, while 3-hourly intervals are used for three-dimensional products. These may be on the model's native 72-layer vertical grid or at 42 pressure surfaces extending to 0.1 hPa. This document describes the gridded output files produced by the GMAO near real-time operational FP, using the most recent version of the GEOS-5 assimilation system. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary. Documentation about the current access methods for products described in this document can be found on the GMAO products page: http://gmao.gsfc.nasa.gov/products/.

GSI↗

NASA NTRS2016

The Calibration of the DSCOVR EPIC Multiple Visible Channel Instrument Using MODIS and VIIRS as a Reference

The Deep Space Climate Observatory (DSCOVR), launched on 11 February 2015, is a satellite positioned near the Lagrange-1 (L1) point, carrying several instruments that monitor space weather, and Earth-view sensors designed for climate studies. The Earth Polychromatic Imaging Camera (EPIC) onboard DSCOVR continuously views the sun-illuminated portion of the Earth with spectral coverage in the UV, VIS, and NIR bands. Although the EPIC instrument does not have any onboard calibration abilities, its constant view of the sunlit Earth disk provides a unique opportunity for simultaneous viewing with several other satellite instruments. This arrangement allows the EPIC sensor to be inter-calibrated using other well-characterized satellite instrument reference standards. Two such instruments with onboard calibration are MODIS, flown on Aqua and Terra, and VIIRS, onboard Suomi-NPP. The MODIS and VIIRS reference calibrations will be transferred to the EPIC instrument using both all-sky ocean and deep convective clouds (DCC) ray-matched EPIC and MODIS/VIIRS radiance pairs. An automated navigation correction routine was developed to more accurately align the EPIC and MODIS/VIIRS granules. The automated navigation correction routine dramatically reduced the uncertainty of the resulting calibration gain based on the EPIC and MODIS/VIIRS radiance pairs. The SCIAMACHY-based spectral band adjustment factors (SBAF) applied to the MODIS/ VIIRS radiances were found to successfully adjust the reference radiances to the spectral response of the specific EPIC channel for over-lapping spectral channels. The SBAF was also found to be effective for the non-overlapping EPIC channel 10. Lastly, both ray-matching techniques found no discernable trends for EPIC channel 7 over the year of publically released EPIC data.

Haney, Conor↗

NASA NTRS2018

The GeoCarb Mission: One Tool in the Evolving Understanding of Methane and Carbon Monoxide Budgets

NASA plans to operate an instrument in geostationary orbit over the Americas beginning in 2022. This mission allows a coordinated study of climate-determining carbon species. Prime focus is on CO2 fluxes, but the reactive species CO and CH4 are particularly relevant to IGAC. Measurements of solar-induced fluorescence will describe plant photosynthesis contemporaneous with emissions. To outline the technology: Grating mapping spectrometery, using a single slit and four focal planes set at 0.76, 1.60, 2.07, and 2.32 microns and ~17000 resolving power. Retrieval profiting from the rich heritage of OCO-2, GOSAT, TropOMI, and GOME/SCIAMACHY. Column concentrations of CO2, CH4, and CO, with finest resolution at 3 km x 6 km. A selection of scans allowing appreciable refinement in fluxes of CO2 and CH4. Rapid re-pointing allowing at least one synoptic observation of all North and South America daily, and 3 observations through the day for selected areas.This presentation is an appeal to IGAC community to use GeoCarb to help improve the attribution of fluxes by sector and by geography. Cost constraints allow GeoCarb only limited listed goals. For example, GeoCarb aspires to constrain CH4 emissions for the whole US, closing the ~60% gap between US EPA estimation and 3-d models. Detailed CO measurements should also aid photochemical and aerosol studies. NASA's TEMPO (UV-Vis geostationary) instrument will overlap GeoCarb. Consequently, HCHO, NO2, aerosol, and CO may be intercompared, allowing elucidation of chemical sources and also transformation timescales. We expect that Sentinel-5P's TropOMI will lead the way here; geostationary imaging will allow diurnal views and reduced cloud obscuration of interesting areas. Analysis of current data suggests interesting questions: (a) puzzling XCH4 diel variations in the Amazonian rainforest; (b) time-varying CO/NO2 relationships in urban plumes. We also urge the suite of airborne and small-sat measurements needed to complete the story at fine scales.

Chatfield, Robert B.↗

NASA NTRS1988

Far Ultraviolot Space Telescope (FAUST)

The Far Ultraviolet Space Telescope is a compact, wide field-of-view, far ultraviolet instrument designed for observations of extended and point sources of astronomical interest. It was originally used in sounding rocket work by both French and American investigators. The instrument was modified for flight on the space shuttle and flew on the Spacelab 1 mission as a joint effort between the Laboratoire d'Astronomie Spatiale and the University of California, Berkeley. The prime experiment objective of this telescope on the Atmospheric Laboratory Applications and Science (ATLAS 1) NASA mission is to observe faint astronomical sources in the far ultraviolet with sensitivities far higher than previously available. The experiment will cover the 1300 to 1800 A band, which is inaccessible to observers on earth. The observing program during the mission consists of obtaining deep sky images during spacecraft nighttime. The targets will include hot stars and nebulae in our own galaxy, faint diffuse galactic features similar to the cirrus clouds seen by the Infrared Astronomical Satellite (IRAS), large nearby galaxies, nearby clusters of galaxies, and objects of cosmological interest such as quasars and the diffuse far ultraviolet background.

Bowyer, S.↗

NASA NTRS2013

File Specification for GEOS-5 FP-IT (Forward Processing for Instrument Teams)

The GEOS-5 FP-IT Atmospheric Data Assimilation System (GEOS-5 ADAS) uses an analysis developed jointly with NOAA's National Centers for Environmental Prediction (NCEP), which allows the Global Modeling and Assimilation Office (GMAO) to take advantage of the developments at NCEP and the Joint Center for Satellite Data Assimilation (JCSDA). The GEOS-5 AGCM uses the finite-volume dynamics (Lin, 2004) integrated with various physics packages (e.g, Bacmeister et al., 2006), under the Earth System Modeling Framework (ESMF) including the Catchment Land Surface Model (CLSM) (e.g., Koster et al., 2000). The GSI analysis is a three-dimensional variational (3DVar) analysis applied in grid-point space to facilitate the implementation of anisotropic, inhomogeneous covariances (e.g., Wu et al., 2002; Derber et al., 2003). The GSI implementation for GEOS-5 FP-IT incorporates a set of recursive filters that produce approximately Gaussian smoothing kernels and isotropic correlation functions. The GEOS-5 ADAS is documented in Rienecker et al. (2008). More recent updates to the model are presented in Molod et al. (2011). The GEOS-5 system actively assimilates roughly 2 × 10(exp 6) observations for each analysis, including about 7.5 × 10(exp 5) AIRS radiance data. The input stream is roughly twice this volume, but because of the large volume, the data are thinned commensurate with the analysis grid to reduce the computational burden. Data are also rejected from the analysis through quality control procedures designed to detect, for example, the presence of cloud. To minimize the spurious periodic perturbations of the analysis, GEOS-5 FP-IT uses the Incremental Analysis Update (IAU) technique developed by Bloom et al. (1996). More details of this procedure are given in Appendix A. The analysis is performed at a horizontal resolution of 0.625-degree longitude by 0.5-degree latitude and at 72 levels, extending to 0.01 hPa. All products are generated at the native resolution of the horizontal grid. The majority of data products are time-averaged, but four instantaneous products are also available. Hourly data intervals are used for two-dimensional products, while 3-hourly intervals are used for three-dimensional products. These may be on the model's native 72-layer vertical grid or at 42 pressure surfaces extending to 0.1 hPa. This document describes the gridded output files produced by the GMAO near real-time operational GEOS-5 FP-IT processing in support of the EOS instrument teams. Additional details about variables listed in this file specification can be found in a separate document, the GEOS-5 File Specification Variable Definition Glossary.

3D Var↗

NASA NTRS2007

Synchronous NDVI and Surface Air Temperature Trends in Newfoundland: 1982 to 2003

The northern regions of the earth are currently experiencing rapid change in temperature and precipitation. This region contains -40% of carbon stored in the world's soil which has accumulated from the last ice age (over 10,000 years ago). The carbon has remained to this point due to reduced decomposition from the short growing seasons and subfreezing temperatures. The influence of climate upon plant growth can have significant consequences to the carbon cycle balance in this region and could potentially alter and release this long term store of carbon to the atmosphere, resulting in a negative feedback enhancing climate warming. These changes have the potential to alter ecosystems processes, which impact human well being. This paper investigated a global satellite record of increases in vegetation growth from 1982 to 2003 developed at GSFC. It was found that, Newfoundland's vegetation growth during the 1990s exceeded global measurements. A number of potential causes were investigated to understand the mechanistic environmental drivers that could alter the productivity of this ecosystem. Possible drivers of change included: human influence of land use change on vegetation cover; changes in precipitation; temperature; cloud cover; snow cover; and growing season length. We found that humans had a minimal influence on vegetation growth in Newfoundland. Less than 6% of the island was logged during the investigation. We found a strong correlation of vegetation growth to a lengthening of the growing season of -9 and -17 days from 1982-1990 and 1991-1999. A distinct drop in plant growth and air temperature was found in 1990 to 1991 from the volcanic eruption of Mt. Pinatubo that reduced global surface air temperatures. These results document the influences of air temperature upon northern forest plant growth and the cooling effects of major volcanic eruptions in this ecological system.

Neigh, C. S. R.↗

NASA NTRS1998

Upper tropospheric water vapor: A field campaign of two Raman lidars, Airborne hygrometers, and Radiosondes

Water vapor in the atmosphere plays an important role in radiative transfer and the process of radiative balance so critical for understanding global change. It is the principal ingredient in cloud formation, one of the most difficult atmospheric processes to model, and the most variable component of the Earth-atmosphere albedo. And as a free molecule, it is the most active infrared absorber and emitter, thus, the most important greenhouse gas. The radiative impact of water vapor is important at all levels of the atmosphere. Even though moisture decreases by several orders-of-magnitude from the Earth's surface to the tropopause, recent research has shown that, from a radiative standpoint, a small percentage change in water vapor at any level is nearly equivalent. Therefore accurate and precise measurements of this important atmospheric constituent are needed at all levels to evaluate the full radiative impact. The need for improved measurements in the upper troposphere is particularly important because of the generally hostile (very dry and cold) conditions encountered. Because of the importance of water vapor to the understanding of radiative transfer, the Department of Energy's Atmospheric Radiation Measurements (ARM) program initiated a series of measurement campaigns at the Cloud And Radiation Testbed (CART) site in Oklahoma, especially focused on atmospheric water vapor. Three water vapor intensive observation period (water vapor IOP) campaigns were planned. Two of the water vapor IOP campaigns have been completed: the first IOP was held during the fall of 1996 with a focus on boundary layer water vapor measurements, and the second was conducted during the fall of 1997 with a focus on both boundary layer moisture e and moisture in the upper troposphere. This paper presents a review of the intercomparisons of water vapor measurements in the upper troposphere aquired during the second water vapor IOP. Data to be presented include water vapor measurements ements from: two Raman Lidars, the NASA Goddard Scanning Raman Lidar (SRL) and the CART Raman Lidar (CARL), a number of Vaisala radiosondes launched during the IOP campaign, and a dew point hygrometer flown on the University of North Dakota Cessna Citation Aircraft.

Melfi, S. Harvey↗

NASA NTRS2000

Hurricane Wind Field Measurements with Scanning Airborne Doppler Lidar During CAMEX-3

During the 1998 Convection and Moisture Experiment (CAMEX-3), the first hurricane wind field measurements with Doppler lidar were achieved. Wind fields were mapped within the eye, along the eyewall, in the central dense overcast, and in the marine boundary layer encompassing the inflow region. Spatial coverage was determined primarily by cloud distribution and opacity. Within optically-thin cirrus slant range of 20- 25 km was achieved, whereas no propagation was obtained during penetration of dense cloud. Measurements were obtained with the Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) on the NASA DC-8 research aircraft. MACAWS was developed and operated cooperatively by the atmospheric lidar remote sensing groups of NOAA Environmental Technology Laboratory, NASA Marshall Space Flight Center, and Jet Propulsion Laboratory. A pseudo-dual Doppler technique ("co-planar scanning") is used to map the horizontal component of the wind at several vertical levels. Pulses from the laser are directed out the left side of the aircraft in the desired directions using computer-controlled rotating prisms. Upon exiting the aircraft, the beam is completely eyesafe. Aircraft attitude and speed are taken into account during real-time signal processing, resulting in determination of the ground-relative wind to an accuracy of about 1 m/s magnitude and about 10 deg direction. Beam pointing angle errors are about 0.1 deg, equivalent to about 17 m at 10 km. Horizontal resolution is about 1 km (along-track) for typical signal processor and scanner settings; vertical resolution varies with range. Results from CAMEX-3 suggest that scanning Doppler wind lidar can complement airborne Doppler radar by providing wind field measurements in regions that are devoid of hydrometeors. At present MACAWS observations are being assimilated into experimental forecast models and satellite Doppler wind lidar simulations to evaluate the relative impact.

Rothermel, Jeffry↗

NASA NTRS2013

Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

Recent studies evaluating the bulk microphysical schemes (BMPs) within cloud resolving models (CRMs) have indicated large uncertainties and errors in the amount and size distributions of snow and cloud ice aloft. The snow prediction is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33‐km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Coldseason Precipitation Experiment (GCPEx) experiment, as well as a few years (15 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku-band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. A Particle Size and Velocity (PARSIVEL) disdrometer was also used to measure the surface size distribution and fall speeds of snow at SBNY. For the 15 cases at SBNY, the WSM6, Morrison (MORR), Thompson (THOM2), and Stony Brook (SBU-YLIN) BMPs were validated. A non-spherical snow assumption (THOM2 and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU-YLIN schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM2 is ~0.25 meters per second too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM2, and MORR schemes were ~0.25 meters per second too slow, while the SBU-YLIN was 0.25 to 0.5 meters per second too fast. Overall, the BMPs simulate a size distribution close to the observed for D < 4 mm in the dendritic, plates, and mixed habit periods. The model BMPs underestimate the size distribution when large aggregates were observed. For D > 6 mm in the dendrites, side planes, and mixed habit periods, the BMPs are likely not simulating enough aggregation to create a larger size distribution, although the MORR (double moment) scheme seemed to perform best. These SBNY results will be compared with some results from GCPEx for a warm frontal snow band observed at 18 February 2012.

Colle, Brian A.↗

NASA NTRS2013

Evaluation of Model Microphysics within Precipitation Bands of Extratropical Cyclones

Recent studies evaluating the bulk microphysical schemes (BMPs) within cloud resolving models (CRMs) have indicated large uncertainties and errors in the amount and size distributions of snow and cloud ice aloft. The snow prediction is sensitive to the snow densities, habits, and degree of riming within the BMPs. Improving these BMPs is a crucial step toward improving both weather forecasting and climate predictions. Several microphysical schemes in the Weather Research and Forecasting (WRF) model down to 1.33‐km grid spacing are evaluated using aircraft, radar, and ground in situ data from the Global Precipitation Mission Coldseason Precipitation Experiment (GCPEx) experiment, as well as a few years (15 winter storms) of surface measurements of riming, crystal habit, snow density, and radar measurements at Stony Brook, NY (SBNY on north shore of Long Island) during the 2009-2012 winter seasons. Surface microphysical measurements at SBNY were taken every 15 to 30 minutes using a stereo microscope and camera, and snow depth and snow density were also recorded. During these storms, a vertically-pointing Ku-band radar was used to observe the vertical evolution of reflectivity and Doppler vertical velocities. A Particle Size and Velocity (PARSIVEL) disdrometer was also used to measure the surface size distribution and fall speeds of snow at SBNY. For the 15 cases at SBNY, the WSM6, Morrison (MORR), Thompson (THOM2), and Stony Brook (SBU-YLIN) BMPs were validated. A non-spherical snow assumption (THOM2 and SBU-YLIN) simulated a more realistic distribution of reflectivity than spherical snow assumptions in the WSM6 and MORR schemes. The MORR, WSM6, and SBU-YLIN schemes are comparable to the observed velocity distribution in light and moderate riming periods. The THOM2 is approx 0.25 m/s too slow with its velocity distribution in these periods. In heavier riming, the vertical Doppler velocities in the WSM6, THOM2, and MORR schemes were approx 0.25 m/s too slow, while the SBU-YLIN was 0.25 to 0.5 m/s too fast. Overall, the BMPs simulate a size distribution close to the observed for D < 4 mm in the dendritic, plates, and mixed habit periods. The model BMPs underestimate the size distribution when large aggregates were observed. For D > 6 mm in the dendrites, side planes, and mixed habit periods, the BMPs are likely not simulating enough aggregation to create a larger size distribution, although the MORR (double moment) scheme seemed to perform best. These SBNY results will be compared with some results from GCPEx for a warm frontal snow band observed at 18 February 2012.

Colle, Brian A.↗

NASA NTRSDate not supplied

Treating gridded geospatial data as point data to simplify analytics

Gridded geospatial remote sensing (satellite) data has traditionally been stored in file-based multidimensional arrays to preserve the locality of data. Measurements from locations that are physically next to each other on earth remain next to each other in the arrays. Maintaining this locality is useful when running calculations like reprojection, but unnecessary for many other calculations. This talk will go through a real world example of a tool redesign at the Goddard Earth Sciences Data and Information Services Center (GES DISC), showing the advantages of using the data frame model for calculating summary statistics, where measurement proximity is unimportant.

Analysis-ready data↗

NASA NTRS1989

New results in the theory of dust grain alignment

Two complementary approaches are used in an attempt to propose an appropriate formulation of the solution to the problem of magnetic alignment of grains in the diffuse and/or the more denser clouds, whatever the mechanism of rotational excitation can be. The interest of such a unified formulation is mainly that the same theoretical expression for polarization can be used everywhere, allowing for easier comparisons between regions where the physical conditions are highly different. The first consists in applying a Monte-Carlo method to a limited number of representative cases, for which all the torques acting on the grain are taken into account: impulsive random torques due to direct collisions with gas atoms, to evaporation of atoms from the surface, and to exo-energetic recombinations forming hydrogen molecules, followed by violent ejections from peculiar sites; magnetic torques. Three characteristic times are associated with these torques: the collisional damping time, the time necessary to change completely the actual sites configuration narrowly bound to the correlation time of the suprathermal torque; and the magnetic damping time. The second approach starts from a heuristic point of view. It consists in a generalization of results (Cugnon, 1983; see also Purcell and Spitzer, 1971; Greenberg, 1978) obtained for thermal alignment to the suprathermal case. It appears indeed that in two extreme cases, the thermal formulation may be used after redefinition of involved times and temperatures.

Cugnon, Pierre↗

NASA NTRS2004

X Persei: The X-Ray Halo and Spectrum of a High-Latitude X-Ray Binary

The observations were completed on February 25,2003. Although the source was in the FOV for 31.4 ksec, only 18.2 ksec of data were usable due to a strong flare in the first part of the observations. We have extracted the X-ray halo from the good portion of the data, and were then faced with the problem of calibrating the far-off-axis point spread function, which is needed only for X-ray halo analysis; the same problem affected Chandra halo observations. We used data from 3C273, MCG 6-30-15, LMC X-1, and Her X-1 to measure the PSF, and found that it is reasonably well fit with a power law of the form PSF(theta) = A theta^-G, where A = 0.0034 arcmin^-2, and G = 3.05 for energies between 1-4 keV. This suggests there are fewer large dust grains along the When fitting the spectrum of X Persei, we found NH = 3e21 cm^-2, as expected. However, the X-ray halo (using a Mathis, Rumpl, Nordsieck 1977 dust model) required at most a column density of 1.4+/-0.1 e21 cm^-2; other models required sightline to X Per than would have been expected. In addition, a smoothly distributed dust model fit the observations better than a single cloud model, also against our expectations. We are in the process of writing a paper to be submitted to ApJ with these results, and will also present them at the 2004 HEAD meeting in New Orleans.

Mushotzky, Richard↗

NASA NTRS2011

Contributions to Climate Research Using the AIRS Science Team Version-5 Products

This paper compares recent spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLRCLR (Clear Sky OLR) as determined using CERES and AIRS observations over the time period September 2002 through June 2010. We find excellent agreement in OLR anomaly time series of both data sets in almost every detail, down to the 1 x 1 spatial grid point level. This extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper then examines anomaly time series of AIRS derived products over the extended time period September 2002 through April 2011. We show that OLR anomalies during this period are closely in phase with those of an El Nino index, and that recent global and tropical mean decreases in OLR and OLR(sub CLR) are a result of a transition from an El Nino condition at the beginning of the data record to La Nina conditions toward the end of the data period. This relationship can be explained by temporal changes of the distribution of mid-tropospheric water vapor and cloud cover in two spatial regions that are in direct response to El Nino/La Nina activity which occurs outside these spatial regions

Susskind, Joel↗

NASA NTRS2014

CLARREO Approach for Reference Intercalibration of Reflected Solar Sensors: On-Orbit Data Matching and Sampling

The implementation of the Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission was recommended by the National Research Council in 2007 to provide an on-orbit intercalibration standard with accuracy of 0.3% (k = 2) for relevant Earth observing sensors. The goal of reference intercalibration, as established in the Decadal Survey, is to enable rigorous high-accuracy observations of critical climate change parameters, including reflected broadband radiation [Clouds and Earth's Radiant Energy System (CERES)], cloud properties [Visible Infrared Imaging Radiometer Suite (VIIRS)], and changes in surface albedo, including snow and ice albedo feedback. In this paper, we describe the CLARREO approach for performing intercalibration on orbit in the reflected solar (RS) wavelength domain. It is based on providing highly accurate spectral reflectance and reflected radiance measurements from the CLARREO Reflected Solar Spectrometer (RSS) to establish an on-orbit reference for existing sensors, namely, CERES and VIIRS on Joint Polar Satellite System satellites, Advanced Very High Resolution Radiometer and follow-on imagers on MetOp, Landsat imagers, and imagers on geostationary platforms. One of two fundamental CLARREO mission goals is to provide sufficient sampling of high-accuracy observations that are matched in time, space, and viewing angles with measurements made by existing instruments, to a degree that overcomes the random error sources from imperfect data matching and instrument noise. The data matching is achieved through CLARREO RSS pointing operations on orbit that align its line of sight with the intercalibrated sensor. These operations must be planned in advance; therefore, intercalibration events must be predicted by orbital modeling. If two competing opportunities are identified, one target sensor must be given priority over the other. The intercalibration method is to monitor changes in targeted sensor response function parameters: effective offset, gain, nonlinearity, optics spectral response, and sensitivity to polarization. In this paper, we use existing satellite data and orbital simulationmethods to determinemission requirements for CLARREO, its instrument pointing ability, methodology, and needed intercalibration sampling and data matching for accurate intercalibration of RS radiation sensors on orbit.

radiometry↗

NASA NTRS2017

Retrievals of Aerosol Microphysics from Simulations of Spaceborne Multiwavelength Lidar Measurements

In support of the Aerosol, Clouds, Ecosystems mission, simulations of a spaceborne multiwavelength lidar are performed based on global model simulations of the atmosphere along a satellite orbit track. The yield for aerosol microphysical inversions is quantified and comparisons are made between the aerosol microphysics inherent in the global model and those inverted from both the model's optical data and the simulated three backscatter and two extinction lidar measurements, which are based on the model's optical data. We find that yield can be significantly increased if inversions based on a reduced optical dataset of three backscatter and one extinction are acceptable. In general, retrieval performance is better for cases where the aerosol fine mode dominates although a lack of sensitivity to particles with sizes less than 0.1 microns is found. Lack of sensitivity to coarse mode cases is also found, in agreement with earlier studies. Surface area is generally the most robustly retrieved quantity. The work here points toward the need for ancillary data to aid in the constraints of the lidar inversions and also for joint inversions involving lidar and polarimeter measurements.

aerosols↗