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At least 433 records · Page 24

An Evaluation of Antarctica as a Calibration Target for Passive Microwave Satellite Missions

Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.

Kim, Edward↗

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗

Utilizing Chamber Data for Developing and Validating Climate Change Models

Controlled environment chambers (e.g. growth chambers, SPAR chambers, or open-top chambers) are useful for measuring plant ecosystem responses to climatic variables and CO2 that affect plant water relations. However, data from chambers was found to overestimate responses of C fluxes to CO2 enrichment. Chamber data may be confounded by numerous artifacts (e.g. sidelighting, edge effects, increased temperature and VPD, etc) and this limits what can be measured accurately. Chambers can be used to measure canopy level energy balance under controlled conditions and plant transpiration responses to CO2 concentration can be elucidated. However, these measurements cannot be used directly in model development or validation. The response of stomatal conductance to CO2 will be the same as in the field, but the measured response must be recalculated in such a manner to account for differences in aerodynamic conductance, temperature and VPD between the chamber and the field.

Monje, Oscar↗

An Alternative Inter-Satellite Calibration of the UMD HIRS OLR Retrievals

Outgoing Longwave Radiation (OLR) at the top-of-atmosphere (TOA) is a fundamental component of Earth's energy balance and represents the heat energy in the thermal bands rejected to space by the planet. Determination of OLR from satellites has a long and storied history, but the observational record remains largely fragmented with gaps in satellite measurements over the past three decades. Perhaps the most semi-continuous set of retrievals comes from the University of Maryland (UMD) algorithm that uses four HIRS (High Resolution Infrared Sounder) channels on the NOAA polar orbiting satellites to estimate OLR. This data set shows great promise in helping to bridge the discontinuous ERBS (Earth Radiation Budget Satellite) and CERES (Clouds and the Earth s Radiant Energy System) measurements. However, significant satellite inter-calibration biases persist with the present UMD data, principally outside the tropics. Difficulties relate to the combination of drift of the satellite equator crossing time through the diurnal cycle and changes in HIRS channel response function design. Here we show how an ad hoc recalibration of the UMD retrievals among the different satellites removes much of the remaining uncertainty due to diurnal drift of the satellite orbit. The adjusted HIRS data (using no other external information) show much better agreement with OLR from the European Center Interim Reanalysis (EC-Int), longer-term signals in the Global Energy and Water Cycle Experiment / Surface Radiation Budget (GEWEX/SRB) retrievals, and also agree well with ERBS and CERES OLR measurements. These results augur well for narrowing the uncertainties in multi-decadal estimates of this important climate variable.

Robertson, Franklin R.↗

A History of Vegetation, Sediment and Nutrient Dynamics at Tivoli North Bay, Hudson Estuary, New York

We conduct a stratigraphic paleoecological investigation at a Hudson River National Estuarine Research Reserve (HRNERR) site, Tivoli Bays, spanning the past 1100 years. Marsh sediment cores were analyzed for ecosystem changes using multiple proxies, including pollen, spores, macrofossils, charcoal, sediment bulk chemistry, and stable carbon and nitrogen isotopes. The results reveal climatic shifts such as the warm and dry Medieval Warm Period (MWP) followed by the cooler Little Ice Age (LIA), along with significant anthropogenic influence on the watershed ecosystem. A five-fold expansion of invasive species, including Typha angustifolia and Phragmites australis, is documented along with marked changes in sediment composition and nutrient input. During the last century, a ten-fold sedimentation rate increase due to land-use changes is observed. The large magnitude of shifts in vegetation, sedimentation, and nutrients during the last few centuries suggest that human activities have made the greatest impact to the marshes of the Hudson Estuary during the last millennium. Climate variability and ecosystem changes similar to those observed at other marshes in northeastern and mid-Atlantic estuaries, attest to the widespread regional signature recorded at Tivoli Bays.

Sritrairat, Sanpisa↗

Impact of Sensor Degradation on the MODIS NDVI Time Series

Time series of satellite data provide unparalleled information on the response of vegetation to climate variability. Detecting subtle changes in vegetation over time requires consistent satellite-based measurements. Here, the impact of sensor degradation on trend detection was evaluated using Collection 5 data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on the Terra and Aqua platforms. For Terra MODIS, the impact of blue band (Band 3, 470 nm) degradation on simulated surface reflectance was most pronounced at near-nadir view angles, leading to a 0.001-0.004 yr−1 decline in Normalized Difference Vegetation Index (NDVI) under a range of simulated aerosol conditions and surface types. Observed trends in MODIS NDVI over North America were consistentwith simulated results,with nearly a threefold difference in negative NDVI trends derived from Terra (17.4%) and Aqua (6.7%) MODIS sensors during 2002-2010. Planned adjustments to Terra MODIS calibration for Collection 6 data reprocessing will largely eliminate this negative bias in detection of NDVI trends.

NDVI↗

Tree Line Structure and Dynamics at the Northern Limit of the Larch Forest: Anabar Plateau, Siberia, Russia

The goal of the study was to provide an analysis of climate impact before, during, and after the Little Ice Age (LIA) on the larch (Larix gmelinii) tree line at the northern extreme of Siberian forests. Recent decadal climate change impacts on the tree line, regeneration abundance, and age structure were analyzed. The location of the study area was within the forest-tundra ecotone (elevation range 170-450 m) in the Anabar Plateau, northern Siberia. Field studies were conducted along elevational transects. Tree natality/mortality and radial increment were determined based on dendrochronology analyses. Tree morphology, number of living and subfossil trees, regeneration abundance, and age structure were studied. Locations of pre-LIA, LIA, and post-LIA tree lines and refugia boundaries were established. Long-term climate variables and drought index were included in the analysis. It was found that tree mortality from the 16th century through the beginning of the 19th century caused a downward tree line recession. Sparse larch stands experienced deforestation, transforming into tundra with isolated relict trees. The maximum tree mortality and radial growth decrease were observed to have occurred at the beginning of 18th century. Now larch, at its northern boundary in Siberia, is migrating into tundra areas. Upward tree migration was induced by warming in the middle of the 19th century. Refugia played an important role in repopulation of the forest-tundra ecotone by providing a seed source and shelter for recruitment of larch regeneration. Currently this ecotone is being repopulated mainly by tree cohorts that were established after the 1930s. The last two decades of warming did not result in an acceleration of regeneration recruitment because of increased drought conditions. The regeneration line reached (but did not exceed) the pre-LIA tree line location, although contemporary tree heights and stand densities are comparatively lower than in the pre-LIA period. The mean rate of tree line upward migration has been about 0.35 m/yr (with a range of 0.21-0.58), which translates to a tree line response to temperature of about 55 m/deg C.

Northern Limit↗

State of the Art in Large-Scale Soil Moisture Monitoring

Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

Review↗

Prediction of the Arctic Oscillation in Boreal Winter by Dynamical Seasonal Forecasting Systems

This study assesses the prediction skill of the boreal winter Arctic Oscillation (AO) in the state-of-the-art dynamical ensemble prediction systems (EPSs): the UKMO GloSea4, the NCEP CFSv2, and the NASA GEOS-5. Long-term reforecasts made with the EPSs are used to evaluate representations of the AO, and to examine skill scores for the deterministic and probabilistic forecast of the AO index. The reforecasts reproduce the observed changes in the large-scale patterns of the Northern Hemispheric surface temperature, upper-level wind, and precipitation according to the AO phase. Results demonstrate that all EPSs have better prediction skill than the persistence prediction for lead times up to 3-month, suggesting a great potential for skillful prediction of the AO and the associated climate anomalies in seasonal time scale. It is also found that the deterministic and probabilistic forecast skill of the AO in the recent period (1997-2010) is higher than that in the earlier period (1983-1996).

Coupled Models↗

Amazon Forests Maintain Consistent Canopy Structure and Greenness During the Dry Season

The seasonality of sunlight and rainfall regulates net primary production in tropical forests. Previous studies have suggested that light is more limiting than water for tropical forest productivity, consistent with greening of Amazon forests during the dry season in satellite data.We evaluated four potential mechanisms for the seasonal green-up phenomenon, including increases in leaf area or leaf reflectance, using a sophisticated radiative transfer model and independent satellite observations from lidar and optical sensors. Here we show that the apparent green up of Amazon forests in optical remote sensing data resulted from seasonal changes in near-infrared reflectance, an artefact of variations in sun-sensor geometry. Correcting this bidirectional reflectance effect eliminated seasonal changes in surface reflectance, consistent with independent lidar observations and model simulations with unchanging canopy properties. The stability of Amazon forest structure and reflectance over seasonal timescales challenges the paradigm of light-limited net primary production in Amazon forests and enhanced forest growth during drought conditions. Correcting optical remote sensing data for artefacts of sun-sensor geometry is essential to isolate the response of global vegetation to seasonal and interannual climate variability.

dry season↗

Assessing Disparities of Dengue Virus Transmission Risk across the US-Mexican Border Using a Climate Driven Vector-Epidemiological Model

Dengue fever is a mosquito‐borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Although transmission regularly occurs along the border region in Mexico, dengue virus transmission in bordering Arizona has not occurred. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input and Daymet for temperature and supplemental precipitation input, we modeled dengue transmission along a US‐Mexico transect using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Model runs were performed for 5 cities in Sonora, Mexico and southern Arizona. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. For cities with reported dengue case data, the top model simulations that best reproduced dengue case numbers were retained and their parameter values were extracted for comparison. These parameter values were used to run simulations in areas where dengue virus transmission does not occur or where dengue fever case data was unavailable. Additional model runs were performed to reveal how changes in climate or parameter values could alter transmission risk along the transect. The relative influence of climate variability and model parameters on dengue virus transmission is assessed to help public health workers prepare location specific infection prevention strategies.

Morin, Cory↗

Laboratory for Hydrospheric Processes 1997 Publications

This document is a compilation of publications of the Goddard Space Flight Center Laboratory for Hydrospheric Processes for calendar year 1997. Each two-page entry is a cut-and-pasted extraction from a 1997 published journal article, book chapter, symposium or conference proceedings, or technical memorandum. This provides a quick, inexpensive way to communicate our research. If you wish further information, or a reprint, please contact the author of the article or the publisher. There are two sections, the first consisting of 76 journal articles and book chapters which are arranged according to the science priorities of NASA's Earth Science Enterprise: Land-Cover Change and Global Productivity Seasonal-to-Interannual Climate Prediction Natural Hazards Long-Term Climate Variability Atmospheric Ozone, and an additional category Sensor/Algorithm Development. * Each of these sections is preceded by a foreword. A second section, consisting of 52 other contributions (e.g. conference/symposium proceedings and technical memoranda), provides additional scientific information to the outside community. This document was initiated within the Earth Sciences Directorate at the NASA/Goddard Space Flight Center to provide internal communication. We anticipate it will prove useful to visitors and other people interested in our research. This is our fifth annual document. The Laboratory for Hydrospheric Processes is one of the major elements of the Earth Sciences Directorate at NASA's Goddard Space Flight Center. Scientific investigations within the Division range from theoretical to experimental research dealing with oceanic/physical oceanography, hydrologic, and cryospheric sciences. The Laboratory currently has a staff of 60 civil servants and approximately 138 visiting scientists, postdoctoral fellows, and contractors. At various times throughout the year, the Laboratory hosts additional personnel through NASA and Goddard sponsored enrichment programs for high school, undergraduate and graduate students, and high school and university faculty. For further information see our web site at http://neptune.gsfc.nasa.gov.

Busalacchi, Antonio J.↗

Impact of Source Region on the delta18 O signal in snow: A case study from Mount Wrangell Alaska

The stable isotopic composition of water in ice cores is an important source of information on past climate variability. At its simplest level, the underlying assumption is that there is an empirical relationship between the normalized difference in the concentration for these stable isotopes and a specified local temperature at the ice core site. There are, however, nonlocal processes, such as a change in source region or a change in the atmospheric pathway, which can impact the stable isotope signal, thereby complicating its use as a proxy for temperature. In this paper, the importance of these nonlocal processes are investigated through the analysis of the synoptic-scale circulation during a snowfall event at the summit of Mount Wrangell (62 deg N, 144 deg W; 4300 m MSL) in south-central Alaska. During this event there was, over a 1-day period in which the local temperature was approximately constant, a change in delta18 O that exceeded half that normally seen to occur in the region between summer and winter. As shall be shown, this arose from a change in the source region, from the subtropical eastern Pacific to northeastern Asia, for the snow that fell on Mount Wrangell during the event.

Snow↗

The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El Niño-Southern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850 CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium. An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records. Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the "amount effect". During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

Colose, Christopher M.↗

Supplement of: The Influence of Volcanic Eruptions on the Climate of Tropical South America During the Last Millennium in an Isotope-Enabled General Circulation Model

Currently, little is known on how volcanic eruptions impact large-scale climate phenomena such as South American paleo-intertropical Convergence Zone (ITCZ) position and summer monsoon behavior. In this paper, an analysis of observations and model simulations is employed to assess the influence of large volcanic eruptions on the climate of tropical South America. This problem is first considered for historically recent volcanic episodes for which more observations are available but where fewer events exist and the confounding effects of El NioSouthern Oscillation (ENSO) lead to inconclusive interpretation of the impact of volcanic eruptions at the continental scale. Therefore, we also examine a greater number of reconstructed volcanic events for the period 850CE to present that are incorporated into the NASA GISS ModelE2-R simulation of the last millennium.An advantage of this model is its ability to explicitly track water isotopologues throughout the hydrologic cycle and simulating the isotopic imprint following a large eruption. This effectively removes a degree of uncertainty associated with error-prone conversion of isotopic signals into climate variables, and allows for a direct comparison between GISS simulations and paleoclimate proxy records.Our analysis reveals that both precipitation and oxygen isotope variability respond with a distinct seasonal and spatial structure across tropical South America following an eruption. During austral winter, the heavy oxygen isotope in precipitation is enriched, likely due to reduced moisture convergence in the ITCZ domain and reduced rainfall over northern South America. During austral summer, however, more negative values of the precipitation isotopic composition are simulated over Amazonia, despite reductions in rainfall, suggesting that the isotopic response is not a simple function of the amount effect. During the South American monsoon season, the amplitude of the temperature response to volcanic forcing is larger than the rather weak and spatially less coherent precipitation signal, complicating the isotopic response to changes in the hydrologic cycle.

Colose, Christopher↗

Overview of Global Monitoring of Terrestrial Chlorophyll Fluorescence from Space

Despite the critical importance of photosynthesis for the Earth system, understanding how it is influenced by factors such as climate variability, disturbance history, and water or nutrient availability remains a challenge because of the complex interactions and the lack of GPP measurements at various temporal and spatial scales. Space observations of the sun-induced chlorophyll fluorescence (SIF) electromagnetic signal emitted by plants in the 650-850nm spectral range hold the promise of providing a new view of vegetation photosynthesis on a global basis. Global retrievals of SIF from space have recently been achieved from a number of spaceborne spectrometers originally intended for atmospheric research. Despite not having been designed for land applications, such instruments have turned out to provide the necessary spectral and radiometric sensitivity for SIF retrieval from space. The first global measurements of SIF were achieved in 2011 from spectra acquired by the Japanese GOSAT mission launched in 2009. The retrieval takes advantage of the high spectral resolution provided by GOSATs Fourier Transform Spectrometer (FTS) which allows the evaluation of the in-filling of solar Fraunhofer lines by SIF. Unfortunately, GOSAT only provides a sparse spatial sampling with individual soundings separated by several hundred kilometers. Complementary, the Global Ozone Monitoring Experiment-2 (GOME-2) instruments onboard MetOp-A and MetOp-B enable SIF retrievals since 2007 with a continuous and global spatial coverage. GOME-2 measures in the red and near-infrared (NIR) spectral regions with a spectral resolution of 0.5 nm and a pixel size of up to 40x40 km2. Most recently, another global and spatially continuous data set of SIF retrievals at 740 nm spanning the 2003-2012 time frame has been produced from ENVISATSCIAMACHY. This observational scenario has been completed by the first fluorescence data from the NASA-JPL OCO-2 mission (launched in July 2014) and the upcoming Copernicus' Sentinel 5-Precursor to be launched in early 2016. OCO-2 and TROPOMI offer the possibility of monitoring SIF globally with a 100-fold improvement in spatial and temporal resolution with respect to the current measurements from the GOSAT, GOME-2 and SCIAMACHY missions. In this contribution, we will provide an overview of existing global SIF data sets derived from space-based atmospheric spectrometers and will demonstrate the potential of such data to improve our knowledge of vegetation photosynthesis and gross primary production at the synoptic scale. We will show examples of ongoing research exploiting SIF data for an improved monitoring of photosynthetic activity in different ecosystems, including large crop belts worldwide, the Amazon rainforest and boreal evergreen forests.

vegetation agriculture satellite↗

Large Gain in Air Quality Compared to an Alternative Anthropogenic Emissions Scenario

During the last 30 years, significant effort has been made to improve air quality through legislation for emissions reduction. Global three-dimensional chemistrytransport simulations of atmospheric composition over the past 3 decades have been performed to estimate what the air quality levels would have been under a scenario of stagnation of anthropogenic emissions per capita as in 1980, accounting for the population increase (BA1980) or using the standard practice of neglecting it (AE1980), and how they compare to the historical changes in air quality levels. The simulations are based on assimilated meteorology to account for the yearto- year observed climate variability and on different scenarios of anthropogenic emissions of pollutants. The ACCMIP historical emissions dataset is used as the starting point. Our sensitivity simulations provide clear indications that air quality legislation and technology developments have limited the rapid increase of air pollutants. The achieved reductions in concentrations of nitrogen oxides, carbon monoxide, black carbon, and sulfate aerosols are found to be significant when comparing to both BA1980 and AE1980 simulations that neglect any measures applied for the protection of the environment. We also show the potentially large tropospheric air quality benefit from the development of cleaner technology used by the growing global population. These 30-year hindcast sensitivity simulations demonstrate that the actual benefit in air quality due to air pollution legislation and technological advances is higher than the gain calculated by a simple comparison against a constant anthropogenic emissions simulation, as is usually done. Our results also indicate that over China and India the beneficial technological advances for the air quality may have been masked by the explosive increase in local population and the disproportional increase in energy demand partially due to the globalization of the economy.

Law (Jurisprudence)↗

Impact of Spatial Sampling on Continuity of MODIS-VIIRS Land Surface Reflectance Products: A Simulation Approach

With the increasing need to construct long-term climate-quality data records to understand, monitor, and predict climate variability and change, it is vital to continue systematic satellite measurements along with the development of new technology for more quantitative and accurate observations. The Suomi National Polar-orbiting Partnership mission provides continuity in monitoring the Earths surface and its atmosphere in a similar fashion as the heritage MODIS instruments onboard the National Aeronautics and Space Administrations Terra and Aqua satellites. In this paper, we aim at quantifying the consistency of Aqua MODIS and Suomi-NPP Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Reflectance (LSR) and NDVI products as related to their inherent spatial sampling characteristics. To avoid interferences from sources of measurement and/or processing errors other than spatial sampling, including calibration, atmospheric correction, and the effects of the bidirectional reflectance distribution function, the MODIS and VIIRSLSR products were simulated using the Landsat-8s Operational Land Imager (OLI) LSR products. The simulations were performed using the instruments point spread functions on a daily basis for various OLI scenes over a 16-day orbit cycle. It was found that the daily mean differences due to discrepancies in spatial sampling remain below 0.0015 (1) in absolute surface reflectance at subgranule scale (i.e., OLI scene size).We also found that the MODISVIIRS product intercomparisons appear to be minimally impacted when differences in the corresponding view zenith angles (VZAs) are within the range of -15deg to -35deg (VZA(sub v) - VZA(sub m)), where VIIRS and MODIS footprints resemble in size. In general, depending on the spatial heterogeneity of the OLI scene contents, per-grid-cell differences can reach up to 20.Further spatial analysis of the simulated NDVI and LSR products revealed that, depending on the user accuracy requirements for product intercomparisons, spatial aggregations may be used. It was found that if per-grid-cell differences on the order of 10(in LSR or NDVI) are tolerated, the product intercomparisons are expected to be immune from differences in spatial sampling.

VIIRS↗