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At least 109 records · Page 6

Portable Laser Spectrometer for Airborne and Ground-Based Remote Sensing of Geological CO2 Emissions

A 24 kilogram, suitcase-sized, CW (Continuous Wave) Laser Remote Sensing Spectrometer (LARSS) with an approximately 2-kilometer range has been developed. It has demonstrated its flexibility in measuring both atmospheric CO2 from an airborne platform and terrestrial emission of CO2 from a remote mud volcano, Bledug Kuwu, Indonesia, from a ground-based sight. This system scans the CO2 absorption line with 20 discrete wavelengths, as opposed to the typical two-wavelength online-offline instrument. This multi-wavelength approach offers an effective quality control, bias control, and confidence estimate of measured CO2 concentrations via spectral fitting. The simplicity, ruggedness, and flexibility in the design allow for easy transportation and use on different platforms with a quick setup in some of the most challenging climatic conditions. While more refinement is needed, the results represent a stepping stone towards widespread use of active one-sided gas remote sensing in the earth sciences.

_______________________↗

A Decade of Global Volcanic SO2 Emissions Measured from Space

The global flux of sulfur dioxide (SO2) emitted by passive volcanic degassing is a key parameter that constrains the fluxes of other volcanic gases (including carbon dioxide, CO2) and toxic trace metals (e.g., mercury). It is also a required input for atmospheric chemistry and climate models, since it impacts the tropospheric burden of sulfate aerosol, a major climate-forcing species. Despite its significance, an inventory of passive volcanic degassing is very difficult to produce, due largely to the patchy spatial and temporal coverage of ground-based SO2 measurements. We report here the first volcanic SO2 emissions inventory derived from global, coincident satellite measurements, made by the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite in 2005-2015. The OMI measurements permit estimation of SO2 emissions from over 90 volcanoes, including new constraints on fluxes from Indonesia, Papua New Guinea, the Aleutian Islands, the Kuril Islands and Kamchatka. On average over the past decade, the volcanic SO2 sources consistently detected from space have discharged a total of approximately 63 kt/day SO2 during passive degassing, or approximately 23 +/- 2 Tg/yr. We find that approximately 30% of the sources show significant decadal trends in SO2 emissions, with positive trends observed at multiple volcanoes in some regions including Vanuatu, southern Japan, Peru and Chile.

Carn, S. A.↗

Connecting Indonesian Fires and Drought With the Type of El Niño and Phase of the Indian Ocean Dipole During 1979-2016

This study advances the previous understanding of the role of climate variability on Indonesian fire activity, by considering (i) the presence of different types of El Niño and (ii) the interaction between El Niño and the Indian Ocean Dipole (IOD). We classify 12 El Niño events during 1979-2016 into Eastern Pacific (EP) and Central Pacific (CP) types (four and eight El Niño events, respectively) and analyze observational data of sea surface temperature, precipitation, drought code, biomass burning carbon emission, visibility, and aerosol optical depth accordingly. We find that more intense and prolonged Indonesian drought and fires occur in the EP type, during which the emitted carbon amounts almost double those in the CP type. By further separating the CP type El Niño according to the phase of the IOD, that is, positive and negative, we show that fire seasons with less burning intensity and shorter duration are predominantly associated with weakly positive or even negative phase of the IOD phenomena. Moreover, fire intensity exhibits geographic diversity: fires are always more intensive in southern Kalimantan than in southern Sumatra in all El Niño events, although it is less dry in the former region. The outcome of this study can be applied to drought early warning, fire management, and air quality forecast in Indonesia and adjacent areas by identifying the type of El Niño and the phase of the IOD in advance.

IOD phenomena↗

A41a-0017: Using TES Retrievals of HCN to Determine Fire Influence of Aura-TES Footprints

Hydrogen cyanide (HCN) has successfully been used as a tracer of biomassburning in the context of aircraft campaigns. We show HCN observations fromAura-TES for a major fire in Indonesia in 2006, and globally over differentseasons. We develop a fire-influence flag for TES observations and show howthis relates to enhancements of other TES products, such as PAN, carbonmonoxide, and ozone.

ozone↗

AERONET Remotely Sensed Measurements and Retrievals of Biomass Burning Aerosol Optical Properties During the 2015 Indonesian Burning Season

An extreme biomass-burning event occurred in Indonesia from September through October 2015 due to severe drought conditions, partially caused by a major El Nino event, thereby allowing for significant burning of peatland that had been previously drained. This event had the highest sustained aerosol optical depths (AOD) ever monitored by the global Aerosol Robotic Network (AERONET). The newly developed AERONET Version 3 algorithms retain high AOD at the longer wavelengths when associated with high Angstrom Exponents (AEs), which thereby allowed for measurements of AOD at 675 nanometers as high as approximately 7, the upper limit of Sun photometry. Measured AEs at the highest monitored AOD levels were subsequently utilized to estimate instantaneous values of AOD at 550 nanometers in the range of 11 to 13, well beyond the upper measurement limit. Additionally, retrievals of complex refractive indices, size distributions, and single scattering albedos (SSA) were obtained at much higher AOD levels than possible from almucantar scans due to the ability to perform retrievals at smaller solar zenith angles with new hybrid sky radiance scans. For retrievals made at the highest AOD levels the fine mode volume median radii were approximately 0.25 to 0.30 microns, which are very large particles for biomass burning. Very high SSA values (approximately 0.975 from 440 to 1020 nanometers) are consistent with the domination by smoldering combustion of peat burning. Estimates of the percentage peat contribution to total biomass burning aerosol based on retrieved SSA and laboratory measured peat SSA were approximately 80-85 percent, in excellent agreement with independent estimates.

Eck, T. F.↗

A Fortnightly Atmospheric 'Tide' at Bali Caused by Oceanic Tidal Mixing in Lombok Strait

Strong tidal currents in and around the narrow straits of the Lesser Sunda Islands, Indonesia, affect ocean sea surface temperatures (SST) via non-linear tide-induced mixing. A fortnightly spring–neap cycle in tidal currents can induce a similar cycle in SST, which has been observed to occur in and south of Lombok Strait. Here we report on an atmospheric response to the fortnightly SST cycle which is detected in relative humidity and air temperature measurements at Bali. The fortnightly cycles in both the ocean SST and the Bali atmospheric data have a strong seasonal cycle, with peak signals occurring during boreal summer.

Spring–neap cycle↗

Detecting Nighttime Fire Combustion Phase by Hybrid Application of Visible and Infrared Radiation from Suomi NPP VIIRS

An accurate estimation of biomass burning emissions is 1 partially limited by the lack of knowledge of fire burning phase (smoldering vs. flaming). In recent years, several fire detection products have been developed to provide information of fire radiative power (FRP), location, size, and temperature of fire pixels, but no information regarding fire burning phase is retrieved. The Day-Night band (DNB) aboard Visible Infrared Imaging Radiometer Suite (VIIRS) is sensitive to visible light from flaming fires in nighttime scenes. In contrast, VIIRS 4 m moderate resolution band #13 (M13), though capable of detecting fires at all phases, has no direct sensitivity for discerning fire phase. However, the hybrid usage of VIIRS DNB and M-bands data is hampered by their different scanning technology and spatial resolution. In this study, we present a novel method to rapidly and accurately resample DNB pixel radiances to the footprint of M-band pixels, accounting for onboard detector aggregation schemes and bowtie effect removals. The visible energy fraction (VEF) is subsequently introduced as an indicator of fire burning phase VEF is calculated as the ratio of visible light power (VLP) to FRP for each fire pixel retrieved from the VIIRS 750 m active fire product. A global distribution of VEF values, and thereby the fire phase, is quantitatively obtained, showing smaller VEF values in regions with mostly smoldering wildfires, such as peatland fires in Indonesia, larger VEF values in regions with flaming wildfires over grasslands and savannas in the sub-Sahelian region, and the largest VEF values associated with gas flaring in the Middle East. Mean VEF for different land cover types or regions is highly correlated with modified combustion efficiency (MCE). These results, together with a case study of the 2018 California Camp Fire, show that the VEF has the potential to be an indicator of fire combustion phase for each fire pixel, appropriate for estimating emission factors at the satellite pixel level.

Jun Wang↗

Mapping Mangrove Extent and Change: A Globally Applicable Approach

This study demonstrates a globally applicable method for monitoring mangrove forest extent at high spatial resolution. A 2010 mangrove baseline was classified for 16 study areas using a combination of ALOS PALSAR and Landsat composite imagery within a random forests classifier. A novel map-to-image change method was used to detect annual and decadal changes in extent using ALOS PALSAR/JERS-1 imagery. The map-to-image method presented makes fewer assumptions of the data than existing methods, is less sensitive to variation between scenes due to environmental factors (e.g., tide or soil moisture) and is able to automatically identify a change threshold. Change maps were derived from the 2010 baseline to 1996 using JERS-1 SAR and to 2007, 2008 and 2009 using ALOS PALSAR. This study demonstrated results for 16 known hotspots of mangrove change distributed globally, with a total mangrove area of 2,529,760 ha. The method was demonstrated to have accuracies consistently in excess of 90% (overall accuracy: 92.2–93.3%, kappa: 0.86) for mapping baseline extent. The accuracies of the change maps were more variable and were dependent upon the time period between images and number of change features. Total change from 1996 to 2010 was 204,850 ha (127,990 ha gain, 76,860 ha loss), with the highest gains observed in French Guiana (15,570 ha) and the highest losses observed in East Kalimantan, Indonesia (23,003 ha). Changes in mangrove extent were the consequence of both natural and anthropogenic drivers, yielding net increases or decreases in extent dependent upon the study site. These updated maps are of importance to the mangrove research community, particularly as the continual updating of the baseline with currently available and anticipated spaceborne sensors. It is recommended that mangrove baselines are updated on at least a 5-year interval to suit the requirements of policy makers.

Thomas, Nathan↗

The interactive global fire module pyrE (v1.0)

Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS (Goddard Institute for Space Studies) interactive fire emissions *module. The pyrE module is driven by environmental variables like flammability and cloud-to-ground lightning, calculated by the GISS ModelE ESM, and parameterized by anthropogenic impacts based on population density data. Fire emissions are generated from the flaming phase in pyrE (active fires). Using pyrE, we examine fire occurrence, regional fire suppression, burned area, fire emissions, and how it all affects atmospheric composition. To do so, we evaluate pyrE by comparing it to satellite-based datasets of fire count, burned area, fire emissions, and aerosol optical depth (AOD). We demonstrate pyrE’s ability to simulate the daily and seasonal cycles of open fires and resulting emissions. Our results indicate that interactive fire emissions are biased low by 32 %–42 %, depending on emitted species, compared to the GFED4s (Global Fire Emissions Database) inventory. The bias in emissions drives underestimation in column densities, which is diluted by natural and anthropogenic emissions sources and production and loss mechanisms. Regionally, the resulting AOD of a simulation with interactive fire emissions is underestimated mostly over Indonesia compared to a simulation with GFED4s emissions and to MODIS AOD. In other parts of the world pyrE’s performance in terms of AOD is marginal to a simulation with prescribed fire emissions.

Fires↗

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗

Kibo Robot Programming Challenge Final Activity Report

On October 8th, 2020 the Kibo Robot Programming Challenge (RPC) Finals Event took place. Student teams from Australia, Indonesia, Japan, Singapore, Taiwan, Thailand, and UAE were the finalists of the competition and became the first students to ever upload APKs to an Astrobee robot (Bumble) on the ISS. This was the culmination of a joint effort between JAXA’s Int-Ball developing team in Tsukuba, Japan and NASA’s Astrobee Facility team at NASA Ames Research Center\ in California, USA. The collaboration between JAXA and NASA started in late 2017. Throughout this time mutual visits by the engineering and management teams were organized. In July 2019 the Kibo RPC concept was formally defined and the competition started. Hundreds of students across the Asia Pacific region participated and during the final event they did so in real time with the participation of NASA’s astronaut, Chris Cassidy. Chris interacted with the students, JAXA personnel and with the robot during the activity. This report aims to summarize the lessons learned from the several crew and non-crew tended activities, the evaluations performed on ground, the coordination of resources both in the ground and at the International Space Station (ISS) as well as operations. It identifies the issues the teams faced and the solutions put in place to mitigate them.

Astrobee↗

The impacts of warming on rapidly retreating high-altitude, low-latitude glaciers and ice core-derived climate records

Alpine glaciers in the low- and mid-latitudes respond more quickly than large polar ice sheets to changes in temperature, precipitation, cloudiness, humidity, and radiation. Many high-altitude glaciers are monitored by ground observations, aerial photography, and satellite-borne sensors. Regardless of latitude and elevation, nearly all nonpolar glaciers and ice caps are undergoing mass loss, which compromises the records of past climate preserved within them. Almost without exception, the retreat of these ice fields is persistent, and a very important driver is the recent warming of the tropical troposphere and oceans. Here we present data on the decrease in the surface area of four glaciers from low- to mid-latitude mountainous regions: the Andes of Peru and northern Bolivia, equatorial east Africa, equatorial Papua, Indonesia, and the western Tibetan Plateau. Climate records based on oxygen isotopic ratios (δ18O) measured in ice cores drilled from several glaciers in these regions reveal that the records from elevations below ~6000 m above sea level have been substantially modified by seasonal melting and the movement of meltwater through porous upper firn layers. Fortunately, δ18O records recovered from higher altitude sites still contain well-preserved seasonal variations to the surface; however, the projected increase in the rate of atmospheric warming implies that climate records from higher elevation glaciers will eventually also be degraded. A long-term ice core collection program on the Quelccaya ice cap in Peru, Earth's largest tropical ice cap, illustrates that the deterioration of its climate record is concomitant with the increase in mid-troposphere temperatures. The melting ice and resulting growth of proglacial lakes presents an imminent hazard to nearby communities. The accelerating melting of glaciers, if sustained, ensures the eventual loss of unique and irreplaceable climate histories, as well as profound economic, agricultural, and cultural impacts on local communities.

Low-latitude glaciers↗

Capturing the Footprints of Ground Motion in the Spatial Distribution of Rainfall-Induced Landslides

The coupled effect of earthquakes and rainfall is rarely investigated in landslide susceptibility assessments although it could be crucial to predict landslide occurrences. This is even more critical in the context of early warning systems and especially in cases of extreme precipitation regimes in post-seismic conditions, where the rock masses are already damaged due to the ground shaking. Here, we investigate this concept by accounting for the legacy of seismic ground shaking in rainfall-induced landslide (RFIL) scenarios. We do this to identify whether ground shaking plays a role in the susceptibility to post-seismic rainfall-induced landslides and to identify whether this legacy effect persists through time. With this motivation, we use binary logistic regression and examine time series of landslides associated with four earthquakes occurred in Indonesia: 2012 Sulawesi (M(sub w) = 6.3), 2016 Reuleut (M(sub w) = 6.5), 2017 Kasiguncu (M(sub w) = 6.6) and 2018 Palu (M(sub w) = 7.5) earthquakes. The dataset includes one co-seismic and three post-seismic landslide inventories for each earthquake. We use the peak ground acceleration map of the last strongest earthquake in each case as a predisposing factor of landslides representing the effect of ground shaking. We observe that, at least for the study areas under consideration and in a probabilistic context, the earthquake legacy contributes to increase the post-seismic RFIL susceptibility. This positive contribution decays through time. Specifically, we observe that ground motion is a significant predisposing factor controlling the spatial distribution of RFIL in the post-seismic period 110 days after an earthquake. We also show that this effect dissipates within 3 years at most.

Landslides↗

The Role of Fire in Global Forest Loss Dynamics

Fires, among other forms of natural and anthropogenic disturbance, play a central role in regulating the location, composition and biomass of forests. Understanding the role of fire in global forest loss is crucial in constraining land-use change emissions and the global carbon cycle. We analysed the relationship between forest loss and fire at 500 m resolution based on satellite-derived data for the 2003–2018 period. Satellite fire data included burned area and active fire detections, to best account for large and small fires, respectively. We found that, on average, 38 ± 9% (± range) of global forest loss was associated with fire, and this fraction remained relatively stable throughout the study period. However, the fraction of fire-related forest loss varied substantially on a regional basis, and showed statistically significant trends in key tropical forest areas. Decreases in the fraction of fire-related forest loss were found where deforestation peaked early in our study period, including the Amazon and Indonesia while increases were found for tropical forests in Africa. The inclusion of active fire detections accounted for 41%, on average, of the total fire-related forest loss, with larger contributions in small clearings in interior tropical forests and human-dominated landscapes. Comparison to higher-resolution fire data with resolutions of 375 and 20 m indicated that commission errors due to coarse resolution fire data largely balanced out omission errors due to missed small fire detections for regional to continental-scale estimates of fire-related forest loss. Besides an improved understanding of forest dynamics, these findings may help to refine and separate fire-related and non-fire-related land-use change emissions in forested ecosystems.

Dan van Wees↗

Potential impacts of climate change on agriculture and fisheries production in 72 tropical coastal communities

Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (> 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.

Climate change↗

The Global Water Monitor: Wetland surface height dynamics for Ecology, Conservation, and Resource Management

The Global Water Monitor (GWM) offers surface water-related products for lakes, river reaches and wetland zones. The surface elevation change products are derived from satellite radar altimeters, such as the Jason/Sentinel series, and can span multiple decades. While the current instruments are profiling, they offer surface water height at specific locations, thus contributing to parallel observation of wetland surface water extent. GWM wetland products are “operational” with routine updates within 1-2days of satellite overpass. There is also assurance of product continuity to at least the end of 2030. Currently, the GWM holds products for a small selection (~40) of diverse wetlands for objectives that focus on conservation and water/fisheries resource monitoring. These sites have been requested by various organizations also looking to the effects of climate change and anthropogenic influences. Many of the current GWM wetland regions are in National Parks such as the Everglades (USA), the Wasur (Rep. Indonesia), and the Kakadu marshes (Australia). They also include coastal river deltas of the Danube, Mekong, Amazon, Orinoco and Ganges Rivers, and the internal Okavango Delta in Botswana. The preliminary set also ensures a diverse range of wetlands e.g., the shallow pot-hole lake region of the Sand Hills and the coastal Black Swamp of the USA, the peat fields of Malaysia and rice growing fields of Yilinzhen in China. Extensive wetlands in Brazil (the Pantanal), South Sudan (the Sudd Marshes) and Belarus (the Pinsk) are also featured, as are the mangrove regions of the Sundarbans (India) and the Laguna Terminos (Mexico). The Usangu wetland (Tanzania) is also included, a focus region where wetland ecology strongly competes with demands from irrigation, livestock, and the needs of downstream hydro-electric power. The nadir-pointing altimeter instruments record height variations regardless of vegetation or canopy cover, and height dynamics at 10-day or monthly resolution reveal seasonal and inter-annual variations as well as longer-term declining or re-charging trends. These products provide a unique, multi-decadal data set that can stand-alone or serve with cross-validation or image-fusion efforts.

Charon Birkett↗

Mangrove Canopy Height Globally Related to Precipitation and Cyclone Frequency

Mangrove wetlands are among the most productive and carbon-dense ecosystems in the world. Their structural attributes vary considerably across spatial scales, yielding large uncertainties in regional and global estimates of carbon stocks. Here, we present a global analysis of mangrove canopy height gradients and aboveground carbon stocks based on remotely sensed measurements and field data. Our study highlights that precipitation, temperature and cyclone frequency explain 74% of the global trends in maximum canopy height, with other geophysical factors influencing the observed variability at local and regional scales. We find the tallest mangrove forests in Gabon, equatorial Africa, where stands attain 62.8 m. The total global mangrove carbon stock (above- and belowground biomass, and soil) is estimated at 5.03 Pg, with a quarter of this value stored in Indonesia. Our analysis implies sensitivity of mangrove structure to climate change, and offers a baseline to monitor national and regional trends in mangrove carbon stocks.

Carbon cycle↗

Atmospheric Formaldehyde Trend and Its Source Attributions in the Recent Decades

Formaldehyde (CH 2 O) is one of the most important reactive trace gases in the atmosphere with an important role in tropospheric chemistry and in the control of surface air quality. Sources of CH 2 O includes direct emissions and in situ production from the oxidation of volatile organic compounds (VOCs). In this study, we investigate spatial-temporal variations in atmospheric CH 2 O and how changes in CH 2 O couple with tropospheric ozone variability during the past two decades using recently available retrievals from the Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite and the RefD1 simulation from the NASA Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). Our initial analysis provides evidence of significant increases in atmospheric CH 2 O concentrations over several of the world’s major anthropogenic regions, including China, India, and the Middle East, and several biomass burning regions, including South America, southern Africa, boreal regions and Indonesia. We furthermore will identify regional source contributions to CH 2 O trends, including anthropogenic VOCs emissions, biogenic isoprene emissions and open fires. In particular, we will focus on anthropogenic emission regions to examine the role of changing anthropogenic VOC emissions on CH 2 O abundance.

Atmospheric Formaldehyde↗