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All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Diagonally Implicit Runge-Kutta Methods for Ordinary Differential Equations. A Review

A review of diagonally implicit Runge-Kutta (DIRK) methods applied to rst-order ordinary di erential equations (ODEs) is undertaken. The goal of this review is to summarize the characteristics, assess the potential, and then design several nearly optimal, general purpose, DIRK-type methods. Over 20 important aspects of DIRKtype methods are reviewed. A design study is then conducted on DIRK-type methods having from two to seven implicit stages. From this, 15 schemes are selected for general purpose application. Testing of the 15 chosen methods is done on three singular perturbation problems. Based on the review of method characteristics, these methods focus on having a stage order of two, sti accuracy, L-stability, high quality embedded and dense-output methods, small magnitudes of the algebraic stability matrix eigenvalues, small values of aii, and small or vanishing values of the internal stability function for large eigenvalues of the Jacobian. Among the 15 new methods, ESDIRK4(3)6L[2]SA is recommended as a good default method for solving sti problems at moderate error tolerances.

Kennedy, Christopher A.↗
NASA NTRS1995

Satellite Snow-Cover Mapping: A Brief Review

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

Hall, Dorothy K.↗
NASA NTRS1982

Stereoscopic observations of hurricanes and tornadic thunderstorms from geosynchronous satellites

Results are presented which show the application of GOES stereoscopy to the investigation of hurricanes and tornadic thunderstorms. Stereo cloud top height contour maps were constructed to observe the structural evolution of two hurricanes, Frederic on September 12, 1979 and Allen on August 8, 1980, and a tornadic thunderstorm complex over Oklahoma on May 2-3, 1979. Stereo height contours of Hurricane Allen reveal a very intense and symmetric storm with a circular shaped central dense overcast with an average height of 16.5 km. Contours of Hurricane Frederic reveal a preferred region for convection with an explosive exhaust tower attaining a maximum height of 17.8 km. Also presented is a technique for estimating tropical cyclone intensity using GOES stereo height and IR temperature information. Results indicate vertical motions ranging from 4.4 m/s for a moderate storm to 7.7 m/s for an intense storm.

Mack, R.↗
NASA NTRS1994

On the X-ray spectrum of Kepler's supernova remnant

We have devised a method to do nonequilibrium ionization calculations on the results of two-dimensional hydrodynamical simulations, based on the algorithm of Hughes & Helfand (1985). We have calculated the ionization structure and X-ray emission for a two-dimensional numerical hydrodynamical simulation for the remnant of Kepler's supernova (SN); the hydrodynamical model was presented in a previous paper. In this model, the progenitor of Kepler's SN is assumed to have been a massive runaway star ejected from the Galactic plane. In its red supergiant stage, its dense stellar wind was distorted and compressed into a bow shock by the ram pressure of the tenuous interstellar medium. The subsequent interaction of the supernova ejecta with this asymmetric circumstellar matter produced a strongly asymmetric supernova remnant (SNR). In this paper, we present calculated X-ray spectra for this hydrodynamical model. A comparison with observations implies a moderate overabundance of Fe in Kepler's SNR (only 50% larger than its cosmic value), in contrast to a large (6 to 15) Fe overabundance derived previously. However, we confirm earlier conclusions that Si and S abundances are 2 to 3 times solar. These modest enhancements of Si, S, and Fe may be attributed either to heavy-element enriched SN ejecta or to the initial chemical abundances of the SN progenitor, which originated in the metal-rich inner Galaxy. The comparison of our models with the observed spectra confirm theoretical predictions that moderate electron heating occurs at strong collisionless shock fronts, with the implied electron/mean temperature ratio of approximately 0.5.

Borkowski, Kazimierz J.↗
NASA NTRS1986

Magnetic field in molecular cloud cores: Limits on field strengths and linewidths

Preliminary observations by others indicate that the magnetic field strength in dense molecular cloud cores is on the order of 30 micro G, much closer to the background field strength than to the flux-freezing prediction for this density. This result implies that some process must exist to decrease the magnetic field strength in these regions to much less than its flux-frozen value, e.g., ambipolar diffusion. At these moderate field strengths, magnetohydrodynamic waves in the cores provide a good explanation of observed supra-thermal molecular linewidths.

Goodman, A. A.↗
NASA NTRSDate not supplied

Detecting Volcanic Co2 Emissions Hidden in Tropical Volcanic Forests Using Fixed-Wing sUAS

CO2 emissions are among the earliest indicators of subsurface state change and reactivation of volcanic systems and these deep signals reflect in faint diffuse emissions variations on volcanic flanks. Monitoring vast areas of rainforests covering tropical volcanoes is challenging, and space-borne sensors like OCO-2 are not sensitive enough. Fortunately, trees exposed to mild enhancements of CO2 may experience fertilization and build excess CO2 into excess biomass (Cawse-Nicholson, et al. 2018, Biogeosciences). They also process excess CO2 through photosynthesis, measurable by fluorescence (Bogue et al., 2019, Biogeosciences). Furthermore, spaceborne remote sensing instruments have demonstrated increasing NDVI months to years before eruptions, unexplained by other factors (e.g., Houlie et al. 2006, EPSL; Seiler et al. 2017, PLoS One). By providing a means to map large areas of above-canopy CO2 variations over tropical rainforest on the flanks of actively degassing volcanoes, we enable to interpret the signals plants provide in response to excess CO2 with airborne and spaceborne hyperspectral remote sensing methods, including a possible future Surface Biology and Geology (SBG) NASA satellite mission.As a critical step to mature and test this concept, we deployed small unmanned aerial systems (sUAS) using a fixed-wing sUAS designed for autonomous operations and long endurance in extreme environments, without causing significant disturbance of the sampled air. We integrated an in-situ sensor to record the CO2 enhancement field above the forest canopy. Test flight results on the flanks of Turrialba volcano in Costa Rica above forest canopies covering known moderate gas seeps demonstrate the sUAS-borne detection and mapping capabilities of above-canopy elevated CO2 gradients. The strong detection capabilities and high detector signal stability resulted from key system design elements including RF shielding, mechanical stabilization, and calibration procedures. This highly robust system is readily applied for diffuse volcanic CO2 emission studies on active volcanoes covered by dense vegetation.

Volcanic↗
NASA NTRS2026

Using Satellite Surface Temperature Data to Monitor Urban Heat Island

Exposure to heat is a growing concern nationwide. Temperatures can be elevated in cities compared to surrounding rural areas, referred to as an “urban heat island” (UHI) effect, which is intensified during heat waves. The lack of dense networks of air temperature measurements results in few studies on urban heat. Now, a vast amount of high spatial and temporal satellite data on land surface temperature is available. We identified satellite datasets with the longest surface temperature records but different spatial and temporal resolutions: Landsat (1985-current, biweekly at 60 m and 100 m spatial resolution) and the Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellites (2000-current, daily at 1 km spatial resolution). We investigated how satellites with different spatial and temporal resolutions detect UHI effects differently. We hypothesized that 1) a dataset’s spatial resolution impacts the precision of detected UHIs spatially, since high spatial resolution Landsat data better captures spatial variability in temperature, and 2) daily surface temperature data can detect temporal patterns of UHIs and heatwave frequencies. We analyzed Landsat and MODIS satellite data in the Washington, D.C. and Baltimore region. We found that Landsat describes higher spatial variability of the UHI effect than MODIS data. However, MODIS data shows more consistent seasonal surface temperature patterns than Landsat when compared to in situ air temperature measurements. MODIS data was also able to consistently measure the frequency of heat waves. This study demonstrates the value of NASA satellite data for urban heat and climate change studies.

landsat↗
NASA NTRS2023

Evaluating MODIS Snow Products Using an Extensive Wildlife Camera Network

Snow covers a maximum of 47 million km 2 of Earth's northern hemisphere each winter and is an important component of the planet's energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1,181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500m (MOD10A1) Collection 6 product (R 2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1's corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.

Validation↗
NASA NTRS2012

Improving the Accuracy of the AFWA-NASA (ANSA) Blended Snow-Cover Product over the Lower Great Lakes Region

The Air Force Weather Agency (AFWA) -- NASA blended snow-cover product, called ANSA, utilizes Earth Observing System standard snow products from the Moderate- Resolution Imaging Spectroradiometer (MODIS) and the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) to map daily snow cover and snow-water equivalent (SWE) globally. We have compared ANSA-derived SWE with SWE values calculated from snow depths reported at ~1500 National Climatic Data Center (NCDC) co-op stations in the Lower Great Lakes Basin. Compared to station data, the ANSA significantly underestimates SWE in densely-forested areas. We use two methods to remove some of the bias observed in forested areas to reduce the root-mean-square error (RMSE) between the ANSA- and station-derived SWE. First, we calculated a 5- year mean ANSA-derived SWE for the winters of 2005-06 through 2009-10, and developed a five-year mean bias-corrected SWE map for each month. For most of the months studied during the five-year period, the 5-year bias correction improved the agreement between the ANSA-derived and station-derived SWE. However, anomalous months such as when there was very little snow on the ground compared to the 5-year mean, or months in which the snow was much greater than the 5-year mean, showed poorer results (as expected). We also used a 7-day running mean (7DRM) bias correction method using days just prior to the day in question to correct the ANSA data. This method was more effective in reducing the RMSE between the ANSA- and co-op-derived SWE values, and in capturing the effects of anomalous snow conditions.

Hall, Dorothy K.↗
NASA NTRS2015

A Particle Batch Smoother Approach to Snow Water Equivalent Estimation

This paper presents a newly proposed data assimilation method for historical snow water equivalent SWE estimation using remotely sensed fractional snow-covered area fSCA. The newly proposed approach consists of a particle batch smoother (PBS), which is compared to a previously applied Kalman-based ensemble batch smoother (EnBS) approach. The methods were applied over the 27-yr Landsat 5 record at snow pillow and snow course in situ verification sites in the American River basin in the Sierra Nevada (United States). This basin is more densely vegetated and thus more challenging for SWE estimation than the previous applications of the EnBS. Both data assimilation methods provided significant improvement over the prior (modeling only) estimates, with both able to significantly reduce prior SWE biases. The prior RMSE values at the snow pillow and snow course sites were reduced by 68%-82% and 60%-68%, respectively, when applying the data assimilation methods. This result is encouraging for a basin like the American where the moderate to high forest cover will necessarily obscure more of the snow-covered ground surface than in previously examined, less-vegetated basins. The PBS generally outperformed the EnBS: for snow pillows the PBSRMSE was approx.54%of that seen in the EnBS, while for snow courses the PBSRMSE was approx.79%of the EnBS. Sensitivity tests show relative insensitivity for both the PBS and EnBS results to ensemble size and fSCA measurement error, but a higher sensitivity for the EnBS to the mean prior precipitation input, especially in the case where significant prior biases exist.

EnBS↗
NASA NTRS1991

Optically thin cirrus clouds over oceans and possible impact on sea surface temperature of warm pool in western Pacific

Over the convectively active tropical ocean regions, the measurement made from space in the IR and visible spectrum have revealed the presence of optically thin cirrus clouds, which are quite transparent in the visible and nearly opaque in the IR. The Nimbus-4 IR Interferometer Spectrometer (IRIS), which has a field of view (FOV) of approximately 100 km, was utilized to examine the IR optical characteristics of these cirrus clouds. From the IRIS data, it was observed that these optically thin cirrus clouds prevail extensively over the warm pool region of the equatorial western Pacific, surrounding Indonesia. It is found that the seasonal cloud cover caused by these thin cirrus clouds exceeds 50 percent near the central regions of the warm pool. For most of these clouds, the optical thickness in the IR is less than or = 2. It is deduced that the dense cold anvil clouds associated with deep convection spread extensively and are responsible for the formation of the thin cirrus clouds. This is supported by the observation that the coverage of the dense anvil clouds is an order of magnitude less than that of the thin cirrus clouds. From these observations, together with a simple radiative-convective model, it is inferred that the optically thin cirrus can provide a greenhouse effect, which can be a significant factor in maintaining the warm pool. In the absence of fluid transports, it is found that these cirrus clouds could lead to a runaway greenhouse effect. The presence of fluid transport processes, however, act to moderate this effect. Thus, if a modest 20 W/sq m energy input is considered to be available to warm the ocean, then it is found that the ocean mixed-layer of a 50-m depth will be heated by approximately 1 C in 100 days.

Prabhakara, C.↗
NASA NTRS2000

An Explorer-Class Astrobiology Mission

In this paper we describe a potential new Explorer-class space mission, the AstroBiology Explorer (ABE), consisting of a relatively modest dedicated space observatory having a 50 cm aperture primary mirror which is passively cooled to T less than 65 K, resides in a low-background orbit (heliocentric orbit at 1 AU, Earth drift-away), and is equipped with a suite of three moderate order (m approx. 10) dispersive spectrographs equipped with first-order cross-dispersers in an "echellette" configuration and large format (1024xl024 pixel) near- and mid-IR detector arrays cooled by a modest amount of cryogen. Such a system would be capable of addressing outstanding problems in Astrochemistry and Astrophysics that are particularly relevant to Astrobiology and addressable via astronomical observation. The observational program of this mission would make fundamental scientific progress in each of the key areas of the cosmic history of molecular carbon, the distribution and chemistry of organic compounds in the diffuse and dense interstellar media, and the evolution of ices and organic matter in young planetary systems. ABE could make fundamental progress in all of these areas by conducting an approximately one year mission to obtain a coordinated set of infrared spectroscopic observations over the 2.5-20 micrometers spectral range at spectral resolutions of R greater than or equal to 1000 of approximately 1000 galaxies, stars, planetary nebulae, and young star planetary systems.

Sandford, Scott↗
NASA NTRS2013

MODIS 3 Km Aerosol Product: Applications over Land in an Urban/suburban Region

MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

MODIS↗
NASA NTRS2016

Radiative Characteristics of Clouds Embedded in Smoke Derived from Airborne Multiangular Measurements

Clouds in the presence of absorbing aerosols result in their apparent darkening, observed at the top of atmosphere (TOA), which is associated with the radiative effects of aerosol absorption. Owing to the large radiative effect and potential impacts on regional climate, above-cloud aerosols have recently been characterized in multiple satellite-based studies. While satellite data are particularly useful in showing the radiative impact of above-cloud aerosols at the TOA, recent literature indicates large uncertainties in satellite retrievals of above-cloud aerosol optical depth (AOD) and single scattering albedo (SSA), which are among the most important parameters in the assessment of associated radiative effects. In this study, we analyze radiative characteristics of clouds in the presence of wildfire smoke using airborne data primarily from NASA's Cloud Absorption Radiometer, collected during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites campaign in Canada during the 2008 summer season. We found a strong positive reflectance (R) gradient in the UV-visible (VIS)-near infrared (NIR) spectrum for clouds embedded in dense smoke, as opposed to an (expected) negative gradient for cloud-free smoke and a flat spectrum for smoke-free cloud cover. Several cases of clouds embedded in thick smoke were found, when the aircraft made circular/spiral measurements, which not only allowed the complete characterization of angular distribution of smoke scattering but also provided the vertical distribution of smoke and clouds (within 0.5-5 km). Specifically, the largest darkening by smoke was found in the UV/VIS, with R(sub 0.34 microns) reducing to 0.2 (or 20%), in contrast to 0.8 at NIR wavelengths (e.g., 1.27 microns). The observed darkening is associated with large AODs (0.5-3.0) and moderately low SSA (0.85-0.93 at 0.53 microns), resulting in a significantly large instantaneous aerosol forcing efficiency of 254 +/- 47 W/sq m/τ. Our observations of smoke-cloud radiative interactions were found to be physically consistent with theoretical plane-parallel 1-D and Monte Carlo 3-D radiative transfer calculations, capturing the observed gradient across UV-VIS-NIR. Results from this study offer insights into aerosol-cloud radiative interactions and may help in better constraining satellite retrieval algorithms.

absorbing aerosols↗
NASA NTRS2002

Infrared Emission From Interstellar PAHs, New Probes of the Interstellar Medium

Tremendous strides have been made in the understanding of interstellar material over the past twenty years thanks to significant, parallel developments in two closely related areas: observational IR astronomy and laboratory astrophysics. Twenty years ago the composition of interstellar dust was largely unknown and the notion of abundant, gas phase, polycyclic aromatic hydrocarbons (PAHs) anywhere in the interstellar medium (ISM) considered impossible. Today the dust composition of the diffuse and dense ISM is reasonably well constrained and the spectroscopic case for interstellar PAHs, impossibly large molecules by early interstellar chemistry standards, is very strong. PAH spectral features are now being used as new probes of the ISM. PAH ionization states reflect the ionization balance of the medium while PAH size and structure reflect the energetic and chemical history of the medium. Aromatic carbon-rich materials ranging in size from PAHs and PAH nanoclusters, to sub-micron and micron-sized dust grains represent an important component of the ISM. These species: (1) dominate the heating and cooling of interstellar clouds via energetic photoelectron ejection and infrared (IR) emission; (2) moderate the ionization balance in photodissociation regions and molecular clouds; (3) moderate the composition of the gas phase and play an important role in determining the chemistry of the ISM; (4) contribute to the interstellar extinction in the near IR, visible, and UV spectral regions; and (5) convert UV, visible, and near-IR radiation to mid- and far-IR radiation in the ISM and, as such, are responsible for the well known, widespread family of mid-IR emission features with major components near 3.3, 6.2, 7.7, 8.6, and 11.3 microns.

Hudgins, D. M.↗
NASA NTRS2000

Geology of the Smythii and Marginis Region of the Moon: Using Integrated Remotely Sensed Data

We characterized the diverse and complex geology of the eastern limb region of the Moon using a trio of remote-sensing data sets: Clementine, Lunar Prospector, and Apollo. On the basis of Clementine-derived iron and titanium maps we classify the highlands into low-iron (3-6 wt % FeO) and high-iron (6-9 wt % FeO) units. The association of the latter with basalt deposits west of Smythii basin suggests that the highland chemical variation is the result of mixing between basalt and highland lithologies. Mare Smythii and Mare Marginis soils are compositionally similar, containing moderate iron (15-18 wt % FeO) and titanium (2.5-3.5 wt % TiO2). Smythii basin, in addition to the basalt deposits, contains an older, moderate-albedo plains unit. Our investigation reveals that the dark basin plains unit has a distinct albedo, chemistry, and surface texture and formed as a result of impact-mixing between highland and mare lithologies in approximately equal proportions. Clementine iron and maturity maps show that swirls along the northern margin of Mare Marginis have the same iron composition as the surrounding nonswirl material and indicate that the swirl material is bright because of its low agglutinate content. Gravity data for the eastern limb show high, positive Bouguer gravity anomalies for areas of thin basalt cover (e.g., Smythii basin and complex craters Joliot, Lomonosov, and Neper). We deduce that the uplift of dense mantle material is the primary (and mare basaltic fill the secondary) source for generating the concentration of mass beneath large craters and basins.

Gillis, Jeffrey J.↗
NASA NTRS2021

GOES-16 Observations of Rapidly-Intensifying Tropical Cyclones: Hurricanes Harvey (2017), Maria (2017), And Michael (2018)

This study utilizes brightness temperatures (Tb’s) observed by the infrared longwave window band (Ch 14; 11.2 m) from the Geostationary Operational Environmental Satellite-16 (GOES-16) to examine the structure of Hurricanes Harvey, Maria, and Michael throughout their lifetimes. During the times leading up to their rapid intensifications (RI), two-dimensional inner-core structures are examined to analyze the strength and location of the developing convection. Moderate vertical wind shear in the environments of Harvey and Michael induced a pronounced convective asymmetry prior to RI, followed by a rapid axisymmetrization that occurred essentially in conjunction with RI. The evolutions of the tropical cyclones’ (TCs’) coldest Tb’s indicate that the inner-core convective activity began to increase in the 12 h prior to RI onset, primarily in 2–4-h substantial “bursts”, while substantial convection dominated essentially the entirety of the region within 100 km of the surface center within 12 h of the onset of intensification. Azimuthally averaged Tb evolutions illustrate the development of each TCs’ eye and eyewall, the variability of the radial extent of the central dense overcast associated with the diurnal cycle, as well as details of the evolving convective structures throughout intensification. Hövmoller diagrams of data at constant radii reveal areas of cold Tb’s propagating around the TCs on timescales of 2–3-h. The examination of these features in a deep-layer shear-relative sense reveals that they initiate primarily downshear of the TCs’ surface centers. As RI is reached, these areas of convection are able to propagate into the upshear quadrants, which helps facilitate the onset of more substantial intensification.

Hurricanes↗
NASA NTRS2015

Mapping Species Composition of Forests and Tree Plantations in Northeastern Costa Rica with an Integration of Hyperspectral and Multitemporal Landsat Imagery

An efficient means to map tree plantations is needed to detect tropical land use change and evaluate reforestation projects. To analyze recent tree plantation expansion in northeastern Costa Rica, we examined the potential of combining moderate-resolution hyperspectral imagery (2005 HyMap mosaic) with multitemporal, multispectral data (Landsat) to accurately classify (1) general forest types and (2) tree plantations by species composition. Following a linear discriminant analysis to reduce data dimensionality, we compared four Random Forest classification models: hyperspectral data (HD) alone; HD plus interannual spectral metrics; HD plus a multitemporal forest regrowth classification; and all three models combined. The fourth, combined model achieved overall accuracy of 88.5%. Adding multitemporal data significantly improved classification accuracy (p less than 0.0001) of all forest types, although the effect on tree plantation accuracy was modest. The hyperspectral data alone classified six species of tree plantations with 75% to 93% producer's accuracy; adding multitemporal spectral data increased accuracy only for two species with dense canopies. Non-native tree species had higher classification accuracy overall and made up the majority of tree plantations in this landscape. Our results indicate that combining occasionally acquired hyperspectral data with widely available multitemporal satellite imagery enhances mapping and monitoring of reforestation in tropical landscapes.

hyperspectral fusion↗