49 research outputs found
Using ESA’s MERIS as a Proxy for DSCOVR-EPIC
Medium Spectral Resolution Imaging Spectrometer (MERIS) oxygen A band
measurements were used as a proxy for the Earth Polychromatic Imaging Camera
(EPIC),to be launched on NASA’s Deep Space Climate Observatory (DSCOVR). The
high spatial resolution of MERIS (1 × 1 km2) is exploited to study the effects
of subscale spatialheterogeneity of clouds on the cloud-top pressure retrieved
at the coarser spatial resolutionof EPIC (10 × 10 km2). In general, for a sub-
scale cloud fraction less than 1, a shift of cloud-top pressure toward the
middle atmosphere is found, with a low-bias for highclouds and a high-bias for
low clouds. In addition, the deviation is found to be a function of surface
reflectance. The subscale variability of fully clouded EPIC pixels causes a
weak underestimation of cloud-top pressure, when compared to averaged high-
resolution retrievals. View Full-Tex
Spatiotemporal Patterns and Phenology of Tropical Vegetation Solar-Induced Chlorophyll Fluorescence across Brazilian Biomes Using Satellite Observations
Solar-induced fluorescence (SIF) has been empirically linked to gross primary productivity (GPP) in multiple ecosystems and is thus a promising tool to address the current uncertainties in carbon fluxes at ecosystem to continental scales. However, studies utilizing satellite-measured SIF in South America have concentrated on the Amazonian tropical forest, while SIF in other regions and vegetation classes remain uninvestigated. We examined three years of Orbiting Carbon Observatory-2 (OCO-2) SIF data for vegetation classes within and across the six Brazilian biomes (Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa, and Pantanal) to answer the following: (1) how does satellite-measured SIF differ? (2) What is the relationship (strength and direction) of satellite-measured SIF with canopy temperature (T can), air temperature (T air), and vapor pressure deficit (VPD)? (3) How does the phenology of satellite-measured SIF (duration and amplitude of seasonal integrated SIF) compare? Our analysis shows that OCO-2 captures a significantly higher mean SIF with lower variability in the Amazon and lower mean SIF with higher variability in the Caatinga compared to other biomes. OCO-2 also distinguishes the mean SIF of vegetation types within biomes, showing that evergreen broadleaf (EBF) mean SIF is significantly higher than other vegetation classes (deciduous broadleaf (DBF), grassland (GRA), savannas (SAV), and woody savannas (WSAV)) in all biomes. We show that the strengths and directions of correlations of OCO-2 mean SIF to T can , T air , and VPD largely cluster by biome: negative in the Caatinga and Cerrado, positive in the Pampa, and no correlations were found in the Pantanal, while results were mixed for the Amazon and Atlantic Forest. We found mean SIF most strongly correlated with VPD in most vegetation classes in most biomes, followed by T can. Seasonality from time series analysis reveals that OCO-2 SIF measurements capture important differences in the seasonal timing of SIF for different classes, details masked when only examining mean SIF differences. We found that OCO-2 captured the highest base integrated SIF and lowest seasonal pulse integrated SIF in the Amazon for all vegetation classes, indicating continuous photosynthetic activity in the Amazon exceeds other biomes, but with small seasonal increases. Surprisingly, Pantanal EBF SIF had the highest total integrated SIF of all classes in all biomes due to a large seasonal pulse. Additionally, the length of seasons only accounts for about 30% of variability in total integrated SIF; thus, integrated SIF is likely captures differences in photosynthetic activity separate from structural differences. Our results show that satellite measurements of SIF can distinguish important functioning and phenological differences in vegetation classes and thus has the potential to improve our understanding of productivity and seasonality in the tropics
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Spatial and temporal variability of snowfall over Greenland from CloudSat observations
We use the CloudSat 2006–2016 data record to estimate snowfall over the Greenland Ice Sheet (GrIS). We first evaluate CloudSat snowfall retrievals with respect to remaining ground-clutter issues. Comparing CloudSat observations to the GrIS topography (obtained from airborne altimetry measurements during IceBridge) we find that at the edges of the GrIS spurious high-snowfall retrievals caused by ground clutter occasionally affect the operational snowfall product. After correcting for this effect, the height of the lowest valid CloudSat observation is about 1200 m above the local topography as defined by IceBridge. We then use ground-based millimeter wavelength cloud radar (MMCR) observations obtained from the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit, Greenland (ICECAPS) experiment to devise a simple, empirical correction to account for precipitation processes occurring between the height of the observed CloudSat reflectivities and the snowfall near the surface. Using the height-corrected, clutter-cleared CloudSat reflectivities we next evaluate various Z–S relationships in terms of snowfall accumulation at Summit through comparison with weekly stake field observations of snow accumulation available since 2007. Using a set of three Z–S relationships that best agree with the observed accumulation at Summit, we then calculate the annual cycle snowfall over the entire GrIS as well as over different drainage areas and compare the derived mean values and annual cycles of snowfall to ERA-Interim reanalysis. We find the annual mean snowfall over the GrIS inferred from CloudSat to be 34±7.5 cm yr−1 liquid equivalent (where the uncertainty is determined by the range in values between the three different Z–S relationships used). In comparison, the ERA-Interim reanalysis product only yields 30 cm yr−1 liquid equivalent snowfall, where the majority of the underestimation in the reanalysis appears to occur in the summer months over the higher GrIS and appears to be related to shallow precipitation events. Comparing all available estimates of snowfall accumulation at Summit Station, we find the annually averaged liquid equivalent snowfall from the stake field to be between 20 and 24 cm yr−1, depending on the assumed snowpack density and from CloudSat 23±4.5 cm yr−1. The annual cycle at Summit is generally similar between all data sources, with the exception of ERA-Interim reanalysis, which shows the aforementioned underestimation during summer months.
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Ash Deposition Triggers Phytoplankton Blooms at Nishinoshima Volcano, Japan
Volcanoes that deposit eruptive products into the ocean can trigger phytoplankton blooms near the deposition area. Phytoplankton blooms impact the global carbon cycle, but the specific conditions and mechanisms that facilitate volcanically triggered blooms are not well understood, especially in low nutrient ocean regions. We use satellite remote sensing to analyze the chlorophyll response to an 8-month period of explosive and effusive activity from Nishinoshima volcano, Japan. Nishinoshima is an ocean island volcano in a low nutrient low chlorophyll region of the Northern Pacific Ocean. From June to August 2020, during explosive activity, satellite-derived chlorophyll-a was detectable with amplitudes significantly above the long-term climatological value. After the explosive activity ceased in mid-August 2020, these areas of heightened chlorophyll concentration decreased as well. In addition, we used aerial observations and satellite imagery to demonstrate a spatial correlation between blooms and ash plume direction. Using a sun-induced chlorophyll-a fluorescence satellite product, we confirmed that the observed chlorophyll blooms are phytoplankton blooms. Based on an understanding of the nutrients needed to supply blooms, we hypothesize that blooms of nitrogen-fixing phytoplankton led to a 1010–1012 g drawdown of carbon. Thus, the bloom could have significantly mediated the output of carbon from the explosive phase of the eruption but is a small fraction of anthropogenic CO2 stored in the ocean or the global biological pump. Overall, we provide a case study of fertilization of a nutrient-poor ocean with volcanic ash and demonstrate a scenario where multi-month scale deposition triggers continuous phytoplankton blooms across 1,000s of km2
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Next generation aerosol-cloud microphysics for advanced high-resolution climate predictions
The three top-level project goals are: -We proposed to develop, test, and run a new, physically based, scale-independent microphysical scheme for those cloud processes that most strongly affect greenhouse gas scenarios, i.e. warm cloud microphysics. In particular, we propsed to address cloud droplet activation, autoconversion, and accretion. -The new, unified scheme was proposed to be derived and tested using the University of Hawaii's IPRC Regional Atmospheric Model (iRAM). -The impact of the new parameterizations on climate change scenarios will be studied. In particular, the sensitivity of cloud response to climate forcing from increased greenhouse gas concentrations will be assessed
Next generation aerosol-cloud microphysics for advanced high-resolution climate predictions
The three top-level project goals are: -We proposed to develop, test, and run a new, physically based, scale-independent microphysical scheme for those cloud processes that most strongly affect greenhouse gas scenarios, i.e. warm cloud microphysics. In particular, we propsed to address cloud droplet activation, autoconversion, and accretion. -The new, unified scheme was proposed to be derived and tested using the University of Hawaii's IPRC Regional Atmospheric Model (iRAM). -The impact of the new parameterizations on climate change scenarios will be studied. In particular, the sensitivity of cloud response to climate forcing from increased greenhouse gas concentrations will be assessed
Northeast Indian stalagmite records Pacific decadal climate change: Implications for moisture transport and drought in India
This is the final version. It is currently under embargo. It was first published by Wiley at http://onlinelibrary.wiley.com/doi/10.1002/2015GL063826/full.Two types of El Niño events are distinguished by sea surface temperature (SST) anomalies
centered in the central or eastern equatorial Pacific. The Central Pacific El Niño events (CP-El Niño) are
more highly correlated with weakening of the central Indian Summer Monsoon and linked to decadal Pacific
climate variability. We present a 50 year, subannually resolved speleothem δ18O record from northeast India
that exhibits a significant correlation with northern Pacific decadal variability and central equatorial Pacific
SSTs. Accordingly, we suggest that δ18O time series in similar northeast Indian speleothems are effective tools
for investigating preinstrumental changes in Pacific climate, including changes in El Niño dynamics. In
contrast to central India, rainfall amounts in northeast India are relatively unaffected by El Niño. However,
back trajectory analysis indicates that during CP-El Niño events moisture transport distance to northeast India
is reduced, suggesting that variations in moisture transport primarily control δ18O in the region.This work was supported through the BanglaPIRE project (NSF OISE-0968354), an award from the Vanderbilt International Office to JLO and SFMB, and awards from the Cave Research Foundation and the Geological Society of America to CGM. SFMB received financial support from the Schweizer National Fond (SNF), Sinergia grant CRSI22 132646/1
Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model
The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.The global aerosol-climate model ECHAM5-HAM was modified to improve the representation of new particle formation in the boundary layer. Activation-type nucleation mechanism was introduced to produce observed nucleation rates in the lower troposphere. A simple and computationally efficient model for biogenic secondary organic aerosol (BSOA) formation was implemented. Here we study the sensitivity of the aerosol and cloud droplet number concentrations (CDNC) to these additions. Activation-type nucleation significantly increases aerosol number concentrations in the boundary layer. Increased particle number concentrations have a significant effect also on cloud droplet number concentrations and therefore on cloud properties. We performed calculations with activation nucleation coefficient values of 2 x 10(-7) s(-1), 2 x 10(-6) s(-1) and 2 x 10(-5) s(-1) to evaluate the sensitivity to this parameter. For BSOA we have used yields of 0.025, 0.07 and 0.15 to estimate the amount of monoterpene oxidation products available for condensation. The hybrid BSOA formation scheme induces large regional changes to size distribution of organic carbon, and therefore affects particle optical properties and cloud droplet number concentrations locally. Although activation-type nucleation improves modeled aerosol number concentrations in the boundary layer, the use of a global activation coefficient generally leads to overestimation of aerosol number. Overestimation can also arise from underestimation of primary emissions.Peer reviewe
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Ash Deposition Triggers Phytoplankton Blooms at Nishinoshima Volcano, Japan.
Volcanic eruptions can cause organisms known as phytoplankton to multiply and form what is known as a phytoplankton bloom in the ocean. Phytoplankton blooms can impact the life cycle of carbon in the earth system, but it is not always obvious why phytoplankton blooms happen. Using different satellite data, we observe phytoplankton blooms by viewing chlorophyll concentration in the ocean. Nishinoshima is a remote volcano in an area of the Pacific that lacks nutrients necessary for phytoplankton blooms. Nishinoshima erupted in 2019–2020 and deposited lava and ash into the ocean at different times. By looking at the chlorophyll concentration during the time periods lava and ash were deposited into the ocean, we found that chlorophyll concentration increased when ash was deposited into the ocean. These increases in chlorophyll concentration were determined to be phytoplankton blooms. These phytoplankton blooms may utilize nutrients from volcanic ash and the atmosphere, leading to a drawdown of atmospheric carbon