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At least 289 records · Page 16

A Spectralon BRF data base for MISR calibration applications

The Multi-angle Imaging SpectroRadiometer (MISR) is an Earth-observing sensor which provides global retrievals of aerosols, clouds, and land surface parameters. Instrument specifications require an accurate absolute calibration, as well as accurate camera-to-camera, band-to-band, and pixel-to-pixel relative response determinations. In order to achieve these requirements, MISR makes use of an on-board calibrator (OBC), as well as vicarious calibration (VC) experiments.

Satellite↗

The MISR Calibration Program

The Multi-angle Imaging SpectroRadiometer (MISR) is currently under development for NASA's Earth Observing System (EOS). The instrument consists of nine pushbroom cameras, each with four spectral bands in the visible and near-infrared. Detailed are the MISR preflight characteristics, design of the On-Board Calibrator, and the radiance product processing. Detailed specifications and test plans are given.

multi-angle↗

State of The Art Radiometer Standards For NASA'S Earth Observing System

The Multi-Angle Imaging SpectroRadiometer (MISR), to be launched in 1998, is one of five instruments on NASA's first Earth Observing System (EOS) platform. The 3% absolute radiometric calibration requirement is considered challenging, particularly since it must be maintained through the five-year mission life. The Instrument requirements have led to the development of an On-Board Calibrator (OBC) consisting of diffuse panels and photodiode-based radiometric standards.

SpectroRadiometer↗

Response Versus Scan-Angle Assessment of MODIS Reflective Solar Bands in Collection 6.1 Calibration

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard the Aqua and Terra satellites have been operated for nearly two decades, producing high-quality earth observation data sets suitable for a broad range of scientific studies regarding the earth’s land, ocean, and atmospheric processes. The high radiometric accuracy of MODIS reflective solar band (RSB) calibration has also served as benchmark measurements for on-orbit cross-calibration studies. As the two MODIS instruments have operated well beyond their design lifespan of six years, the measurements from the onboard calibrators alone become inadequate to characterize the sensor’s response at all scan angles, as evinced by long-term drifts observed at certain scan positions of the Aqua-MODIS 0.64- and 0.86-μm bands in Collection 6 (C6) data set. The latest MODIS Level 1B C6.1 data set incorporates earth-view response trending from invariant desert sites as supplemental inputs to characterize the scan-angle calibration dependencies for all RSB. This article presents a deep convective cloud (DCC)-based calibration approach for an independent evaluation of the MODIS RSB response versus scan-angle (RVS) performance in C6.1. The long-term calibration stability and RVS differences in C6.1 have been significantly improved for Aqua-MODIS RSB. The observed RVS differences of more than 2% in Aqua-MODIS C6 bands 1 and 2 have been reduced to within 1% in C6.1. Some RSBs of Terra-MODIS have suffered temporal drifts up to ~2% and calibration shifts up to 3%, particularly around 2016 when the Terra satellite entered into safe mode. The DCC approach has been found very effective in tracking the on-orbit RVS changes over time.

Clouds and the Earth’s Radiant Energy System (CERE↗

Estimating Wildfire-Generated Ozone Over North America Using Ozonesonde Profiles and a Differential Back Trajectory Technique

An objective method, employing HYSPLIT back-trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire observations, is developed to estimate ozone enhancement in air transported from regions of active forest fires at 18 ozone sounding sites located across North America. The Differential Back Trajectory (DBT) method compares mean differences between ozone concentrations associated with fire-affected and fire-unaffected parcels. It is applied to more than 1100 ozonesonde profiles collected from these sites during the summer months June to August, 2006, 2008, 2010 and 2011. Layers of high ozone associated with low humidity were first removed from the ozonesonde profiles to minimize the potential effects of stratospheric intrusions on the calculations. No significant influence on average ozone levels by North American fires was found for stations located at Arctic latitudes. The ozone enhancement for stations nearer large fires, such as Trinidad Head and Bratt’s Lake, was up to 324.8% of the TTOC (Total Tropospheric Ozone Column). Fire ozone accounted for up to 8.3% of TTOC at downwind sites such as Yarmouth, Sable Island, Narragansett, and Walsingham. The results are consistent with other studies that have reported an increase in ozone production with the age of the smoke plume.

Moderate Resolution Imaging Spectroradiometer (MOD↗

Success of Montreal Protocol Demonstrated by Comparing High-Quality UV Measurements with “World Avoided” Calculations from Two Chemistry-Climate Models

The Montreal protocol on Substances that Deplete the ozone Layer has been hailed as the most successful environmental treaty ever (https://www.unenvironment.org/news-and-stories/story/montreal-protocol-triumph-treaty). Yet, although our main concern about ozone depletion is the subsequent increase in harmful solar UV radiation at the earth’s surface, no studies to date have demonstrated its effectiveness in that regard. Here we use long-term UV Index (UVI) data derived from high-quality UV spectroradiometer measurements to demonstrate its success in curbing increases in UV radiation. Without this landmark agreement, UVi values would have increased at mid-latitude locations by approximately 20% between the early 1990s and today and would approximately quadruple at mid-latitudes by 2100. In contrast, an analysis of UVI data from multiple clean-air sites shows that maximum daily UVI values have remained essentially constant over the last ~20 years in all seasons, and may even have decreased slightly in the southern hemisphere, especially in Antarctica, where effects of ozone depletion were larger. Reconstructions of the UVi from total ozone data show evidence of increasing UVI levels in the 1980s, but unfortunately, there are no high-quality UV measurements available prior to the early 1990s to confirm these increases with direct observations.

UV Index (UVI) data derived from high-quality UV s↗

Retrievals of Aerosol Optical Depth Over the Western North Atlantic Ocean During ACTIVATE

Aerosol optical depth was retrieved from two airborne remote sensing instruments, the Research Scanning Polarimeter (RSP) and Second Generation High Spectral Resolution Lidar (HSRL-2), during the National Aeronautics and Space Administration (NASA) Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE). The field campaign offers a unique opportunity to evaluate an extensive 3-year dataset under a wide range of meteorological conditions from two instruments on the same platform. However, a long-standing issue in atmospheric field studies is that there is a lack of reference datasets for properly validating field measurements and estimating their uncertainties. Here we address this issue by using the triple collocation method, in which a third collocated satellite dataset from the Moderate Resolution Imaging Spectroradiometer (MODIS) is introduced for comparison. HSRL-2 is found to provide a more accurate retrieval than RSP over the study region. The error standard deviation of HSRL-2 with respect to the ground truth is 0.027. Moreover, this approach enables us to develop a simple, yet efficient, quality control criterion for RSP data. The physical reasons for the differences in two retrievals are determined to be cloud contamination, aerosols near the surface, multiple aerosol layers, absorbing aerosols, non-spherical aerosols, and simplified retrieval assumptions. These results demonstrate the pathway for optimal aerosol retrievals by combining information from both lidars and polarimeters for future airborne and satellite missions.

Aerosol optical depth↗

Approximation of ice phenology of Maine lakes using Aqua MODIS surface temperature data

Studies of lake ice phenology have historically relied on limited in situ data. Relatively few observations exist for ice out and fewer still for ice in, both of which are necessary to determine the temporal extent of ice cover. Satellite data provide an opportunity to better document patterns of ice phenology across landscapes and relate them to the climatological drivers behind changing ice phenology. We developed a model, the Cumulative Sum Method (CSM), that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Earth-observing Aqua satellite to approximate ice in (the onset of ice cover) and ice out from training datasets of 13 and 58 Maine lakes, respectively, during the 2002/2003 through 2017/2018 ice seasons. Ice in was signaled by reaching a threshold of cumulative negative degrees following the first day of the season below 0°C. Ice out was signaled by reaching a threshold of cumulative positive degrees following the first day of the year above 0°C. The comparison of observed and remotely sensed ice-in dates showed relative agreement with a correlation coefficient of 0.71 and a mean absolute error (MAE) of 9.8 days. Ice-out approximations had a correlation coefficient of 0.67 and an MAE of 8.8 days. Lakes smaller in surface area and nearer the Atlantic coast had the greatest error in approximation. Application of the CSM to 20 additional lakes in Maine produced a comparable ice-out MAE of 8.9 days. Ice-out model performance was weaker for the warmest years; there was a larger MAE of 12.0 days when the model was applied to the years 2019–2023 for the original 58 lakes. The development of this model, which utilizes daily satellite data, demonstrates the promise of remote sensing for quantifying ice phenology over short, temporal scales, and wider geographic regions than can be observed in situ, and allows exploration of the influence of surface temperature patterns on the process and timing of ice in and ice out.

54 ENVIRONMENTAL SCIENCES↗

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗

Photosynthesis phenology, as defined by solar-induced chlorophyll fluorescence, is overestimated by vegetation indices in the extratropical Northern Hemisphere

Vegetation phenology is highly sensitive to climate change, although the data and methods used to estimate key phenological states can influence this sensitivity. Because of its direct relation to leaf photosynthetic carbon uptake, remotely sensed solar-induced chlorophyll fluorescence (SIF) can provide new insight assessing changes in vegetation phenology. In this work, we investigated the potential of using a SIF time series product named contiguous SIF (CSIF) to estimate spring, summer, and autumn phenology in the extratropical Northern Hemisphere (>30°N) and compared the results with those based on Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) for the period 2001–2018. Overall, we found similar spatial patterns in phenological states. However, specific dates of key phenological events differed when using CSIF vs. MODIS NDVI data. NDVI data indicated that the growing season started earlier (by 10.1 days on average) and ended later (11.5 days on average) relative to CSIF data. This implies that actual periods for photosynthetic activity are shorter (by 21.6 days on average) than those estimated from vegetation indices more directly related to changes in canopy structure. These large differences between results from NDVI and that from CSIF suggest that vegetation indices such as NDVI seem to overestimate the period for active photosynthesis over the extratropical Northern Hemisphere. Furthermore, while phenology of the early growing season is dominated by temperature for both NDVI and CSIF data, phenology of the late growing season is mainly controlled by temperature for NDVI but by precipitation for CSIF. Our findings were further confirmed by other SIF (GOME-2 SIF) and vegetation index (MODIS EVI) datasets. Phenology modes in Earth system modelling are often parameterized using leaf unfolding and senescence from either station or satellite observations. Our results imply that canopy structure-based parameterization schemes may have overestimated photosynthesis active period, and thus productivity responses. We conclude that SIF data offers a novel and unique approach for assessing phenological change - one that is more directly tied to the carbon cycle and how it is being influenced by climate change.

54 ENVIRONMENTAL SCIENCES↗

Spectroradiometric detection of competitor diatoms and the grazer Poteriochromonas in algal cultures

To address challenges in early detection of pond pests, we have extended a spectroradiometric monitoring method, initially demonstrated for measurement of pigment optical activity and biomass, to the detection of algal competitors and grazers. The method relies upon measurement and interpretation of pond reflectance spectra spanning from the visible into the near-infrared. Reflectance spectra are acquired every 5 min with a multi-channel, fiber-coupled spectroradiometer, providing monitoring of algal pond conditions with high temporal frequency. The spectra are interpreted via numerical inversion of a reflectance model, in which the above-water reflectance is expressed in terms of the absorption and backscatter coefficients of the cultured species, with additional terms accounting for the pigment fluorescence features and for the water-surface reflection of sunlight and skylight. With this method we demonstrate detection of diatoms and the predator Poteriochromonas in outdoor cultures of Nannochloropsis oceanica and Chlorella vulgaris, respectively. Further, the relative strength of these signatures is compared to microscopy and sequencing analysis. Spectroradiometric detection of diatoms is then further assessed on beaker-contained mixtures of Microchloropsis salina with Phaeodactylum tricornutum, Thalassiosira weissflogii, and Thalassiosira pseudonana, respectively, providing an initial evaluation of the sensitivity and specificity of detecting pond competitors.

09 BIOMASS FUELS↗

Analysis of contrasting aerosol indirect effects in liquid water clouds over the northern part of Arabian Sea

The extensive daily statistics of aerosol properties, cloud properties, and their mutual correlations provide crucial information for better assessing future climate change. Here, in this paper, 14 years (2010–2023) of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are analyzed over the northern part of Arabian Sea (Latitude: 21°–25° N and Longitude: 62°–68° E) to assess the characteristics of aerosols and clouds and their relationships under different meteorological conditions. When aerosol optical depth (AOD) is less than ~0.7, the observations exhibit a positive correlation between AOD and cloud droplet effective radius (CDR) but negative correlations between AOD and cloud droplet number concentration (CDNC), between AOD and cloud optical depth (COD), between AOD and cloud liquid water path (CLWP), and between AOD and cloud geometrical thickness (H). The corresponding aerosol-cloud correlations change signs when the AOD values are larger than 0.7. However, the single folded positive AOD-cloud fraction (CF) relationship is observed in both AOD regimes. Similar correlations are also observed between precipitable water vapor (PWV) and CDR, CDNC, COD, H, CF and CLWP, together with a positive correlation between PWV and AOD. Further isolation of the environmental effects from aerosol effects by stratifying AOD and cloud data into different LTS and PWV bins shows that the signature of the well-known Twomey effect is observed under high LTS-high PWV conditions, while an opposite effect (anti-Twomey) is observed under low PWV conditions, regardless of LTS values. Additionally, negative correlations between AOD and COD, AOD and CLWP, and AOD and H are observed under low LTS, regardless of PWV conditions, with a slight positive correlation when AOD >0.4 under high LTS and PWV conditions.

54 ENVIRONMENTAL SCIENCES↗

Intra-annual variations of regional total column ozone, aerosol optical depth, and water vapor from ground-based, satellite-based and model-based observations

The Microtops II ozonometer has been deployed to continuously measure the total column ozone (TCO), pre-cipitable water content (PWC) and aerosol optical thickness (AOT) at Atigre village (16.74° N, 74.37° E, 604 m above sea level, masl) located on the southeastern slope of Indian western Ghats. The Microtops II ozonometer measurements during the period from September 2017 to June 2018 were analyzed along with the retrieved products of Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's Terra satellites and also the ERA-interim reanalysis model. We found that the TCO (or PWC) data from the OMI (or MODIS) and the ERA reanalysis model data products are in good agreement. The mea-surements showed strong seasonal variability such that TCO was lowest in the winter season but increased in the summer season, and both PWC and AOT were lowest in the post-monsoon season and increased in the summer season. In continuous ERA-interim reanalysis TCO observations, we found the three types of periodicities in the daily mean TCO as well as PWC (i) The weekly (7 days), (ii) quasi-biweekly (14 to 16 days), (iii) Madden Julian Oscillations (MJO) (30–60 days) oscillations. These oscillations depend on the periodic weather changes in the troposphere. We also observe that the average day to day variability in daily mean TCO observations in the observational period is about 1.4%, 1.1%, 2.62% in the Microtops II ozonometer, ERA-interim reanalysis, and OMI data respectively. We found the positive correlation between daily mean AOT and PWC in all seasons (except monsoon), which is maximum in the winter season, showing the hygroscopic nature of aerosols. The sources of water vapor and aerosol at our location are also studied using back-trajectory analysis.

Nade, Dada R.↗

Multi-channel Imager Algorithm (MIA): A novel cloud-top phase classification algorithm

The current Geostationary Operational Environmental Satellites (GOES-16 and 17) cloud-top phase classification algorithm is based primarily on empirical thresholds at multiple wavelengths that have varying absorption capabilities for water and ice. The performance of current GOES-16 cloud-top phase product largely depends on the accuracy of the selection of reflectance ratios. Here this study aims at presenting a novel cloud-top phase classification algorithm (the Multi-channel Imager Algorithm, MIA) that provides a more judicious selection of relationships between channels using a supervised K-mean clustering method on multi-channel Red-Green-Blue images. The K-mean clustering method works analogously to how human eyes separate different colors in a microphysical color rendering set of satellite images, which differentiates water, ice and unclassified thin clouds. For water phase, cloud-top temperature information is used to further distinguish supercooled water. To evaluate the performance of the MIA, an extensive comparison with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Moderate Resolution Imaging Spectroradiometer, and current GOES-16 cloud-top phase products is conducted, using CALIOP as the benchmark. Compared to the current GOES-16 cloud-top phase product, MIA demonstrates a substantial improvement in phase classification, where hit rate increases from 69% to 76% over the Continental United States and 58% to 66% over the full disk domain.

54 ENVIRONMENTAL SCIENCES↗

Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters

Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗

On the relationship between eastern China aerosols and western North Pacific tropical cyclone activity

How aerosols affect the weather and climate system has received increasing attention. This study finds a significant negative correlation between March–May eastern China aerosol optical depth (AOD) and July–November western North Pacific (WNP) tropical cyclone (TC) frequency during 2003–2020. This time period spans when several aerosol reanalyses are available and both Terra and Aqua Moderate Resolution Imaging Spectroradiometer AOD retrievals are assimilated therein. Composite analyses and budget analyses of dynamical genesis potential indices indicate the importance of large-scale environmental factors, especially vertical velocity and vertical wind shear, associated with changes in AOD that in turn modulate changes in WNP TC frequency. Increased eastern China AOD may facilitate negative Pacific meridional mode development via modulation of the westerly jet, which then forces an anticyclonic circulation over the WNP basin. Increased AOD can also directly decrease the inter-hemispheric temperature differential and increases the intra-hemispheric temperature differential between the equator and the mid-latitudes, thus weakening ascending motion and enhancing vertical wind shear over the WNP, especially the southeastern portion of the basin. Further, all of these large-scale environment changes induced by increased eastern China AOD tend to suppress WNP TCs. This study highlights the potential influence of eastern China aerosol loadings on WNP TCs, thus improving our understanding of TC climate variability over the WNP.

54 ENVIRONMENTAL SCIENCES↗