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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

CSAPR2 Optimized Convective Cell Tracking Data during TRACER

One of the challenges in analyzing convective cell properties is to observe the quick evolution of individual convective cells. While the operational radar data provide a volumetric data set to analyze radar observables of convective precipitation clouds, previous studies also suggested the quick evolution of cell life cycle that might not be captured by conventional radar volume scan strategies that take ~5-7 minutes. Aiming at enhancing our understanding of the links between convective cloud kinematic and microphysical processes as well as life cycles, the Tracking Aerosol Convection Interactions ExpeRiment (TRACER; Jensen et al. 2019) was conducted at Houston, Texas, in 2022. The TRACER campaign deployed the 2nd generation C-band Scanning ARM Precipitation Radar (CSAPR2), which performed frequent updates of range height indicator (RHI) and sector plan position indicator (PPI) scans to track individual convective cells every < 2 minutes, guided by a new cell tracking framework, Multisensor Agile Adaptive Sampling (MAAS; Kollias et al. 2020). This allows for capturing fast-evolving radar observables. We provide the processed CSAPR2 cell tracking data in CfRadial format collected during the TRACER field campaign from June to September 2022. The data files include processed radar variables: noise-masked reflectivity and differential reflectivity corrected for rain attenuation and systematic biases, noise-masked dealiased radial velocity, specific differential phase, locations of target cells (latitude, longitude, radar range), and radar-echo classification. Figure 1 provides an example of a 3D image of CSAPR2 reflectivity from the lowest PPI scan and an RHI scan after data processing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Characterization of shallow oceanic precipitation using profiling and scanning radar observations at the Eastern North Atlantic ARM observatory

Shallow oceanic precipitation variability is documented using three second-generation radar systems located at the Atmospheric Radiation Measurement (ARM) Eastern North Atlantic observatory: ARM zenith radar (KAZR2), the Ka-band scanning ARM cloud radar (KaSACR2) and the X-band scanning ARM precipitation radar (XSAPR2). First, the radar systems and measurement post-processing techniques, including sea-clutter removal and calibration against colocated disdrometer and Global Precipitation Mission (GPM) observations are described. Then, we present how a combination of profiling radar and lidar observations can be used to estimate adaptive (in both time and height) parameters that relate radar reflectivity (Z) to precipitation rate (R) in the form Z=αR β , which we use to estimate precipitation rate over the domain observed by XSAPR2. Furthermore, constant altitude plan position indicator (CAPPI) gridded XSAPR2 precipitation rate maps are also constructed. Hourly precipitation rate statistics estimated from the three radar systems differ because KAZR2 is more sensitive to shallow virga and XSAPR2 suffers from less attenuation than KaSACR2 and as such is best suited for characterizing intermittent and mesoscale-organized precipitation. Further analysis reveals that precipitation rate statistics obtained by averaging 12 h of KAZR2 observations can be used to approximate that of a 40 km radius domain averaged over similar time periods. However, it was determined that KAZR2 is unsuitable for characterizing domain-averaged precipitation rate over shorter periods. But even more fundamentally, these results suggest that these observations cannot produce an objective domain precipitation estimate and that the simultaneous use of forward simulators is desirable to guide model evaluation studies.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Photodissociation regions

Photodissociation regions are interstellar regions of predominantly neutral gas where the FUV radiation field plays a significant role in the chemistry and/or the heating. Photodissociation, grain attenuation of the FUV flux and grain photoelectric heating lead to copious emission of C II (158 microns), O I (63 microns), Si II (35 microns), C I (370,609 microns), H2 vibrotational and CO rotational transitions, and IR continuum. Theoretical models compared with observations diagnose such physical parameters as the density and temperature structure, the elemental abundances, and the FUV radiation field. Applications are made to Orion, M17 and galactic nuclei. Theoretical photodissociation models can explain the correlation in the C II (158 microns) and CO J = 1-0 emission and the correlation of the CO J = 1-0 luminosity with the molecular mass. Theoretical models also point to feedback mechanisms which may control the rate of star formation in galaxies and which may regulate the column density through giant molecular clouds.

Hollenbach, David J.↗
NASA NTRSDate not supplied

Convective precipitation retrievals from space-borne dual frequency (Ka- and W-band) radar observations

The 2017 Decadal Survey highlighted Earth System Science themes, science and application questions that led to the inclusion aerosols (A), clouds, convection, and precipitation (CCP) in the list of designated observables (DOs) to be pursued within the decade following the survey. Multiple observing system architectures were considered during the NASA A-CCP study, and dual frequency Ka-W band radars have been identified as components of the most likely architectures due to their ability to significantly contribute to the achievement of the science objectives and their synergy with other essential instruments. We present an algorithm to estimate convective precipitation from dual frequency, Ka- and W-band, observations applicable to the observing system architectures considered in the A-CCP study. The algorithm is based on the radar profiling algorithm used within the operational NASA GPM combined algorithm but features an additional module that makes the retrieval problem well-posed in cases of severe attenuation and potential loss of signal below the freezing level. The additional module is developed from GPM combined retrievals and consists of a procedure that generates an ensemble of potential retrievals consistent with the portions of the Ka-band and W-band observation profiles above the noise level. The ensemble solution is refined based on estimates of Path Integrated Attenuation (PIA) from the Surface Reference Technique (SRT) and radiometric observations.

Mircea Grecu↗
NASA NTRS2011

An Overview of the GEOS-5 Aerosol Reanalysis

GEOS-5 is the latest version of the NASA Global Modeling and Assimilation Office (GMAO) earth system model. GEOS-5 contains components for atmospheric circulation and composition (including data assimilation), ocean circulation and biogeochemistry, and land surface processes. In addition to traditional meteorological parameters, GEOS-5 includes modules representing the atmospheric composition, most notably aerosols and tropospheric/stratospheric chemical constituents, taking explicit account of the impact of these constituents on the radiative processes of the atmosphere. MERRA is a NASA meteorological reanalysis for the satellite era (1979-present) using GEOS-5. This project focuses on historical analyses of the hydrological cycle on a broad range of weather and climate time scales. As a first step towards an integrated Earth System Analysis (IESA), the GMAO is extending MERRA with reanalyses for other components of the earth system: land, ocean, bio-geochemistry and atmospheric constituents. In this talk we will present results from the MERRA-driven aerosol reanalysis covering the Aqua period (2003-present). The assimilation of Aerosol Optical Depth (AOD) in GEOS-5 involves very careful cloud screening and homogenization of the observing system by means of a Neural Net scheme that translates MODIS radiances into AERONET calibrated AOD. These measurements are further quality controlled using an adaptive buddy check scheme, and assimilated using the Local Displacement Ensemble (LDE) methodology. For this reanalysis, GEOS-5 runs at a nominal 50km horizontal resolution with 72 vertical layers (top at approx. 8Skm). GEOS-5 is driven by daily biomass burning emissions derived from MODIS fire radiative power retrievals. We will present a summary of our efforts to validate such dataset. The GEOS-5 assimilated aerosol fields are first validated by comparison to independent in-situ measurements (AERONET and PM2.5 surface concentrations). In order to asses aerosol absorption on a global scale, we perform a detailed radiative transfer calculation to simulate the UV aerosol index, comparing our results to OMI measurements. By simulating aerosol attenuated backscatter, we use CALIPSO measurements to evaluate the vertical structure of our aerosol estimates, in particular in regions where we have larger discrepancies with OMI. Finally, the consistency of our AOD estimates with estimates from MISR, MODIS/Deep Blue, OMI and PARASOL will be briefly discussed.

da Silva, Arlindo↗
DOE OSTI2023

Numerical Modeling of Air-Blast Suppression as a Function of Explosive-Charge Burial Depth

As a chemical explosion is buried, the mechanism for acoustic wave generation transitions from fully gas-generated at the surface to completely spall-induced at full containment depth. The fully gas-generated and completely spall-induced signals in the acoustic waveform are well described; however, the transition between these two end-members eludes numerical modeling because of the complex phenomena that are involved. The phenomena of crater formation and explosive cloud evolution are simulated using an Eulerian hydrocode that incorporates geomaterials with strength and porosity. Having accurately modeled these phenomena, we can confidently predict the propagation and relative strength of the gas-generated and spall-induced pulses in the recorded acoustic waveform. The numerical predictions agree with observations from the historical Stagecoach experiment as well as modern recordings from the Source Physics Experiment. In particular, the peak pressure p generated by an explosion is initially due to the gas-generated mechanism and decays with scaled depth of burial d s (depth d scaled by the cube-root of explosive yield w 1/3 ) as exp(-d s ) but then transitions near a scaled depth of 6 m/ton 1/3 to the spall-generated mechanism in which the decay is d$_{s}^{-7/4}$. This decay form is related to the strong ground-motion attenuation relationship that affects spall strength. So these results can improve seismoacoustic inverse models for the explosive source that need to account for the gas-generated and spall-induced signals and their effect on peak pressures and other acoustic signal features.

58 GEOSCIENCES↗
NASA NTRS2005

Improvement of Raman lidar algorithm for quantifying aerosol extinction

Aerosols are particles of different composition and origin and influence the formation of clouds which are important in atmospheric radiative balance. At the present there is high uncertainty on the effect of aerosols on climate and this is mainly due to the fact that aerosol presence in the atmosphere can be highly variable in space and time. Monitoring of the aerosols in the atmosphere is necessary to better understanding many of these uncertainties. A lidar (an instrument that uses light to detect the extent of atmospheric aerosol loading) can be particularly useful to monitor aerosols in the atmosphere since it is capable to record the scattered intensity as a function of altitude from molecules and aerosols. One lidar method (the Raman lidar) makes use of the different wavelength changes that occur when light interacts with the varying chemistry and structure of atmospheric aerosols. One quantity that is indicative of aerosol presence is the aerosol extinction which quantifies the amount of attenuation (removal of photons), due to scattering, that light undergoes when propagating in the atmosphere. It can be directly measured with a Raman lidar using the wavelength dependence of the received signal. In order to calculate aerosol extinction from Raman scattering data it is necessary to evaluate the rate of change (derivative) of a Raman signal with respect to altitude. Since derivatives are defined for continuous functions, they cannot be performed directly on the experimental data which are not continuous. The most popular technique to find the functional behavior of experimental data is the least-square fit. This procedure allows finding a polynomial function which better approximate the experimental data. The typical approach in the lidar community is to make an a priori assumption about the functional behavior of the data in order to calculate the derivative. It has been shown in previous work that the use of the chi-square technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. We note that the a priori choice of a model itself can lead to larger uncertainties as compared to the method that is validated here. In this manuscript, the chi-square technique that determines the most likely functional behavior is validated through numerical simulation and by application to a large body of Raman lidar measurements. In general, we show that the chi-square approach to evaluate aerosol extinction yields lower extinction uncertainty than the traditional technique. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the use of the chi-square technique.

Russo, Felicita↗
NASA NTRS1985

First meeting of the Working Group on the Shuttle Microwave Precipitation Radiometer (SMPR)

The working group agreed that the first (primary) objective should be the determination of methods for the accurate measurement of total rain water and total cloud water with passive microwave methods. There was no argument on the points concerning nonlinear relationships between T sub B and rain rate (R) over the range of important rain rates (half of oceanic rainfall occurs at rates greater than 15 mm h-1), such that variations in rain rate within a footprint lead to an incorrect measurement of the average rate for that footprint, and one cannot determine the characteristics of the sensed rain area. This is especially true near 18 GHz, where the dynamic range above 15 mm h-1 is very small because this frequency does not clearly fall in either a scattering regime or emissive regime at these wavelengths. It is also not clear whether very low frequency (emissive) techniques will be the best at measuring rain processes, or high frequency (scattering) techniques, where precipitation-size ice plays a major role in the signal attenuation. It is still not known what signal of rain is at certain rates on an observational basis because of the many different conditions that can exist within a single satellite observed footprint.

Source record↗
NASA NTRS1973

Use of Polarization Lidar for Investigation of Meteorological Formations

This paper presents the results of theoretical and experimental, investigations of depolarization characteristics of different meteorological formations. Experimental investigations are carried out with a monostatic lidar. The ruby laser radiation is polarized in a vertical plane. The radiation reflected is accepted by a lens system of 150 rom in diameter and a viewing angle of 12' and further it is divided by Wollaston prism into the components polarized orthogonally. In this case the principal plane of the prism is exposed parallel with the laser polarization plane. Investigations show the degree of radiation polarization, reflected from water clouds, to be changed within 1/0.7 (seldom up to 0.6) depending on their density. In most cases a signal reflected from the cloud leading edge is polarized completely. The time shift is observed between polarized and crosspolarized components of a Fignal, reflected from a cloud, depending on the density of a meteorological object. While penetrating into the cloud depth a degree of polarization decreases up to 0.8-0.7, and the character of this decrease is different for various types of clouds. For crystal clouds the shift between the components of the reflected signal is not observed and the magnitude of polarization degree amounts to 0.1/0.3 in comparison with water clouds. The polarization degree of radiation reflected by fog is not less than 0.6, and that in the rains of average intensity (about 5 mm/h) is always about 1. The authors have suggested an algorithm of numerical solution of nonstationary transfer equation in the vector form to forecast the influence of multiple scattering effects on polarization characteristics of the lidar light signal. The method of statistical simulation (Monte-Carlo technique) forms the basis of the algorithm. Numerical estimates obtained for a model of stratocumulus at lambda = 0.6943 microns under boundary conditions close to the conditions of natural experiment being discussed proved to be in a good agreement with the results of observation. Specifically, Fig. 1 shows the profiles of polarization (p) versus depth (L) of the following drop formations: fog (curve 1) with horizontal meteorological visibility of 4 km two stratocumulus at a height of 1100 m with the attenuation factors delta = 0.01m(exp -1) (curve 2) and delta = 0.05m(exp -1) (curve 3). Curve 3 shows the results of numerical estimates and the value of their statistical error.

Balin, Yu. S.↗
NASA NTRS2005

Mapping of ice layer extent and snow accumulation in the percolation zone of the Greenland ice sheet

The Greenland ice sheet underwent record extensive melt in 2002 and prolonged melt in 2003. The severe melting created a significant and extensive ice layer over the Greenland ice sheet. An innovative approach is developed to detect the ice layer formation using data acquired by the SeaWinds scatterometer on the QuikSCAT satellite. QuikSCAT backscatter together with in situ data from automatic weather stations of the Greenland Climate Network are used to map the extent of ice layer formation. The results reveal areas of extensive ice layer formed by the 2002 melt, which is consistent with the maximum melt extent in 2002. Moreover, during freezing seasons, QuikSCAT data show a linear decrease in backscatter (in decibels or dB) that is related to the amount of snow accumulation in the ice layer formation region. This snow accumulation signature is caused by the attenuation of radar waves in the snow layer, accumulating since the last major melt event, whose thickness appears as an exponential function in relation to the backscatter signature. We use the Greenland Climate Network data to calibrate the QuikSCAT accumulation rate in order to estimate and map snow accumulation. QuikSCAT results capture the extreme snowfall in mid-April 2003, which deposited more than 0.5 m of snow in a day as measured by the automated weather station at the NASA South East site. Large-scale QuikSCAT results show an anomalous increase of snow accumulation over the southeast region of Greenland during the 2002-2003 freezing season.

snow↗
DOE OSTI2021

The Diurnal Variation of the Aerosol Optical Depth at the ARM SGP Site

Abstract This study examines the diurnal variation of the aerosol optical depth (AOD) at 355 nm observed by Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site under both clear and cloudy‐sky conditions. Here only cloudy‐skies when the lidar signal is not fully attenuated are considered. The daytime AOD and its variation from the RL showed an excellent agreement with the Aerosol Robotic Network, demonstrating that the RL‐retrieved AOD is not affected by solar background contamination. The climatological annual‐mean daytime‐mean AOD is only slightly larger than the nighttime‐mean AOD (by 1%–3%). However, day‐to‐day variations are observed such that the daytime‐ and nighttime‐mean AOD difference for a given day can be large (about 95% of days have differences within 0.2). The seasonal AOD diurnal range (i.e., the difference between the maximum and minimum values) relative to the mean was 10%–15% except in the winter when it was 44%. The seasonal‐mean cloudy‐sky AOD diurnal variation is similar to that for clear‐sky, except that the AODs are larger (the annual‐mean cloudy‐sky AOD is larger than the clear‐sky by 24%). The aerosol lidar ratio diurnal variations are also examined, which are 10%–20% for all seasons with a minimum near 9 a.m. to 15 p.m. for all seasons except winter. Also presented is the annual‐mean AOD from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite at SGP site: its daytime AOD is about 0.1 smaller than nighttime AOD because of daytime solar background contamination.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

An Atmospheric Tape Recorder: The Imprint of Tropical Tropopause Temperatures on Stratospheric Water Vapor

We describe observations of tropical stratospheric water vapor q that show clear evidence of large-scale upward advection of the signal from annual fluctuations in the effective 'entry mixing ratio' q(sub E) of air entering the tropical stratosphere. In other words, air is 'marked,' on emergence above the highest cloud tops, like a signal recorded on an upward moving magnetic tape. We define q(sub E) as the mean water vapor mixing ratio, at the tropical tropopause, of air that will subsequently rise and enter the stratospheric 'overworld' at about 400 K. The observations show a systematic phase lag, increasing with altitude, between the annual cycle in q(sub E) and the annual cycle in q at higher altitudes. The observed phase lag agrees with the phase lag calculated assuming advection by the transformed Eulerian-mean vertical velocity of a q(sub E) crudely estimated from 100-hPa temperatures, which we use as a convenient proxy for tropopause temperatures. The phase agreement confirms the overall robustness of the calculation and strongly supports the tape recorder hypothesis. Establishing a quantitative link between q(sub E) and observed tropopause temperatures, however, proves difficult because the process of marking the tape depends subtly on both small- and large-scale processes. The tape speed, or large-scale upward advection speed, has a substantial annual variation and a smaller variation due to the quasi-biennial oscillation, which delays or accelerates the arrival of the signal by a month or two in the middle stratosphere. As the tape moves upward, the signal is attenuated with an e-folding time of about 7 to 9 months between 100 and 50 hPa and about 15 to 18 months between 50 and 20 hPa, constraining possible orders of magnitude both of vertical diffusion K(sub z) and of rates of mixing in from the extratropics. For instance, if there were no mixing in, then K(sub z) would be in the range 0.03-0.09 m(exp 2)/s; this is an upper bound on K(sub z).

Mote, Philip W.↗
NASA NTRS2016

Inland and Near Shore Water Profiles Derived from the High Altitude Multiple Altimeter Beam Experimental Lidar (MABEL)

The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission is a six beam, low energy, high repetition rate, 532 nm laser transmitter with photon counting detectors. Although designed primarily for detecting height changes in icecaps, sea ice and vegetation, the polar-orbital satellite will observe global surface water during its designed three year life span, including inland water bodies, coasts, and open oceans. In preparation for the mission, an ICESat-2 prototype or the Multiple Altimeter Beam Experimental Lidar (MABEL), was built and flown on high altitude aircraft experiments over a range of inland and near-shore targets. The purpose was to test the ATLAS concept and to provide a database for developing an algorithm that detects along track surface water height and light penetration under a range of atmospheric and water conditions. The current analysis examines the datasets of three MABEL transects observed from 20 km above ground of coastal and inland waters conducted in 2012 and 2013. Transects ranged from about 2 to 12 km in length and included the middle Chesapeake Bay, the near shore Atlantic coast at Virginia Beach, and Lake Mead. Results indicate MABEL's high capability for retrieving surface water height statistics with a mean height precision of approximately 5-7 cm per 100m segment length. Profiles of attenuated subsurface backscatter, characterized using a Signal to Background Ratio written in Log10 base, or LSBR0, were observed over a range of 1.3 to 9.3 meters depending on water clarity and atmospheric background. Results indicate that observable penetration depth, although primarily dependent on water properties, was greatest when solar background rate was low. Near shore bottom reflectance was detected only at the Lake Mead site down to maximum of 10 m under a clear night sky and low turbidity of approximately 1.6 Nephelometric Turbidity Units (NTU). The overall results suggest that the feasibility of retrieving operational surface water height statistics from space-based photon counting systems such as ATLAS is very high for resolutions down to about 100m, even in partly cloudy conditions. The capability to observe subsurface backscatter profiles is achievable but requires much longer transects of several hundreds of meters.

Topographic↗
NASA NTRS2016

Inland and Near-Shore Water Profiles Derived from the High-Altitude Multiple Altimeter Beam Experimental Lidar (MABEL)

The Advanced Topographic Laser Altimeter System (ATLAS) on the Ice, Cloud, and Land Elevation Satellite (ICESat-2) mission is a six beam, low energy, high repetition rate, 532-nanometer laser transmitter with photon counting detectors. Although designed primarily for detecting height changes in ice caps, sea ice, and vegetation, the polar-orbiting satellite will observe global surface water during its designed three-year life span, including inland waterbodies, coasts, and open oceans. In preparation for the mission, an ICESat-2 prototype, the Multiple Altimeter Beam Experimental Lidar (MABEL), was built and flown on high-altitude aircraft experiments over a range of inland and near-shore targets. The purpose was to test the ATLAS concept and to provide a database for developing an algorithm that detects along track surface water height and light penetration under a range of atmospheric and water conditions. The current analysis examines the data sets of three MABEL transects observed from 20 kilometers above ground of coastal and inland waters conducted in 2012 and 2013. Transects ranged from about 2 to 12 kilometers in length and included the middle Chesapeake Bay, the near-shore Atlantic coast at Virginia Beach, and Lake Mead. Results indicate MABEL's high capability for retrieving surface water height statistics with a mean height precision ofapproximately 5-7 centimeters per 100-meter segment length. Profiles of attenuated subsurface backscatter, characterized using a Signal to Background Ratio written in Log10 base, or LSBR (sub 0), were observed over a range of 1.3 to 9.3 meters, depending on water clarity and atmospheric background. Results indicate that observable penetration depth, although primarily dependent on water properties, was greatest when the solar background rate was low. Near-shore bottom reflectance was detected only at the Lake Mead site down to a maximum of 10 meters under a clear night sky and low turbidity of approximately 1.6 Nephelometric Turbidity Units (NTU). The overall results suggest that the feasibility of retrieving operational surface water height statistics from space-based photon counting systems such as ATLAS is very high for resolutions down to about 100 meters, even in partly cloudy conditions. The capability to observe subsurface backscatterprofiles is achievable but requires much longer transects of several hundreds of meters.

inland↗
NASA NTRS1999

Radar Observations of Convective Systems from a High-Altitude Aircraft

Reflectivity data collected by the precipitation radar on board the tropical Rainfall Measuring Mission (TRMM) satellite, orbiting at 350 km altitude, are compared to reflectivity data collected nearly simultaneously by a doppler radar aboard the NASA ER-2 flying at 19-20 km altitude, i.e. above even the deepest convection. The TRMM precipitation radar is a scanning device with a ground swath width of 215 km, and has a resolution of about a4.4 km in the horizontal and 250 m in the vertical (125 m in the core swath 48 km wide). The TRMM radar has a wavelength of 217 cm (13.8 GHz) and the Nadir mirror echo below the surface is used to correct reflectivity for loss by attenuation. The ER-2 Doppler radar (EDOP) has two antennas, one pointing to the nadir, 34 degrees forward. The forward pointing beam receives both the normal and the cross-polarized echos, so the linear polarization ratio field can be monitored. EDOP has a wavelength of 3.12 cm (9.6 GHz), a vertical resolution of 37.5 m and a horizontal along-track resolution of about 100 m. The 2-D along track airflow field can be synthesized from the radial velocities of both beams, if a reflectivity-based hydrometer fall speed relation can be assumed. It is primarily the superb vertical resolution that distinguishes EDOP from other ground-based or airborne radars. Two experiments were conducted during 1998 into validate TRMM reflectivity data over convection and convectively-generated stratiform precipitation regions. The Teflun-A (TEXAS-Florida Underflight) experiment, was conducted in April and May and focused on mesoscale convective systems mainly in southeast Texas. TEFLUN-B was conducted in August-September in central Florida, in coordination with CAMEX-3 (Convection and Moisture Experiment). The latter was focused on hurricanes, especially during landfall, whereas TEFLUN-B concentrated on central; Florida convection, which is largely driven and organized by surface heating and ensuing sea breeze circulations. Both TEFLUN-A and B were amply supported by surface data, in particular a dense raingauge network, a polarization radar, wind profilers, a mobile radiosonde system, a cloud physics aircraft penetrating the overflown storms, and a network of 10 cm Doppler radars(WSR-88D). This presentation will show some preliminary comparisons between TRMM, EDOP, and WSR-88D reflectivity fields in the case of an MCS, a hurricane, and less organized convection in central Florida. A validation of TRMM reflectivity is important, because TRMM's primary objective is to estimate the rainfall climatology with 35 degrees of the equator. Rainfall is estimated from the radar reflectivity, as well from TRMM's Microwave Imager, which measures at 10.7, 19.4, 21.3, 37, and 85.5 GHz over a broader swath (78 km). While the experiments lasted about three months the cumulative period of near simultaneous observations of storms by ground-based, airborne and space borne radars is only about an hour long. Therefore the comparison is case-study-based, not climatological. We will highlight fundamental differences in the typical reflectivity profiles in stratiform regions of MCS's, Florida convection and hurricanes and will explain why Z-R relationships based on ground-based radar data for convective systems over land should be different from those for hurricanes. These catastrophically intense rainfall from hurricane Georges in Hispaniola and from Mitch in Honduras highlights the importance of accurate Z-R relationships, It will be shown that a Z-R relationship that uses the entire reflectivity profile (rather than just a 1 level) works much better in a variety of cases, making an adjustment of the constants for different precipitation system categories redundant.

Heymsfield, G.↗
NASA NTRS2018

CALIPSO IIR Version 2 Level 1b Calibrated Radiances: Analysis and Reduction of Residual Biases in the Northern Hemisphere

Version 2 of the Level 1b calibrated radiances of the Imaging Infrared Radiometer (IIR) on board the Cloud-Aerosol Lidar and Infrared Satellite Observation (CALIPSO) satellite has been released recently. This new version incorporates corrections of small but systematic seasonal calibration biases previously revealed in Version 1 data products mostly north of 30° N. These biases – of different amplitudes in the three IIR channels 8.65 µm (IIR1), 10.6 µm (IIR2), and 12.05 µm (IIR3) – were made apparent by a striping effect in images of IIR inter-channel brightness temperature differences (BTDs) and through seasonal warm biases of nighttime IIR brightness temperatures in the 30–60° N latitude range. The latter were highlighted through observed and simulated comparisons with similar channels of the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua spacecraft. To characterize the calibration biases affecting Version 1 data, a semi-empirical approach is developed, which is based on the in-depth analysis of the IIR internal calibration procedure in conjunction with observations such as statistical comparisons with similar MODIS/Aqua channels. Two types of calibration biases are revealed: an equalization bias affecting part of the individual IIR images and a global bias affecting the radiometric level of each image. These biases are observed only when the temperature of the instrument increases, and they are found to be functions of elapsed time since night-to-day transition, regardless of the season. Correction coefficients of Version 1 radiances could thus be defined and implemented in the Version 2 code. As a result, the striping effect seen in Version 1 is significantly attenuated in Version 2. Systematic discrepancies between nighttime and daytime IIR–MODIS BTDs in the 30–60° N latitude range in summer are reduced from 0.2 K in Version 1 to 0.1 K in Version 2 for IIR1–MODIS29. For IIR2–MODIS31 and IIR3–MODIS32, they are reduced from 0.4 K to close to zero, except for IIR3–MODIS32 in June, where the night-minus-day difference is around −0.1 K.

Garnier, Anne↗
NASA NTRS2002

Defining Top-of-Atmosphere Flux Reference Level for Earth Radiation Budget Studies

To estimate the earth's radiation budget at the top of the atmosphere (TOA) from satellite-measured radiances, it is necessary to account for the finite geometry of the earth and recognize that the earth is a solid body surrounded by a translucent atmosphere of finite thickness that attenuates solar radiation differently at different heights. As a result, in order to account for all of the reflected solar and emitted thermal radiation from the planet by direct integration of satellite-measured radiances, the measurement viewing geometry must be defined at a reference level well above the earth s surface (e.g., 100 km). This ensures that all radiation contributions, including radiation escaping the planet along slant paths above the earth s tangent point, are accounted for. By using a field-of- view (FOV) reference level that is too low (such as the surface reference level), TOA fluxes for most scene types are systematically underestimated by 1-2 W/sq m. In addition, since TOA flux represents a flow of radiant energy per unit area, and varies with distance from the earth according to the inverse-square law, a reference level is also needed to define satellite-based TOA fluxes. From theoretical radiative transfer calculations using a model that accounts for spherical geometry, the optimal reference level for defining TOA fluxes in radiation budget studies for the earth is estimated to be approximately 20 km. At this reference level, there is no need to explicitly account for horizontal transmission of solar radiation through the atmosphere in the earth radiation budget calculation. In this context, therefore, the 20-km reference level corresponds to the effective radiative top of atmosphere for the planet. Although the optimal flux reference level depends slightly on scene type due to differences in effective transmission of solar radiation with cloud height, the difference in flux caused by neglecting the scene-type dependence is less than 0.1%. If an inappropriate TOA flux reference level is used to define satellite TOA fluxes, and horizontal transmission of solar radiation through the planet is not accounted for in the radiation budget equation, systematic errors in net flux of up to 8 W/sq m can result. Since climate models generally use a plane-parallel model approximation to estimate TOA fluxes and the earth radiation budget, they implicitly assume zero horizontal transmission of solar radiation in the radiation budget equation, and do not need to specify a flux reference level. By defining satellite-based TOA flux estimates at a 20-km flux reference level, comparisons with plane-parallel climate model calculations are simplified since there is no need to explicitly correct plane-parallel climate model fluxes for horizontal transmission of solar radiation through a finite earth.

Loeb, N. G.↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

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