nasa-gesdisc/es-publications-researchareas huggingface dataset:
Satellite observations of forest resilience to hurricanes along the northern Gulf of Mexico (2020)

As one of the most destructive natural disasters, hurricanes pose a great threat to forest ecosystems, particularly in the coastal areas. A better understanding of forest resilience to hurricane disturbances is essential for reducing hazard risks as well as sustaining forests in a time of increasing climate disasters. Although hurricane-induced forest damage has been extensively studied at both local and regional levels, the lack of large-scale assessment of post-hurricane recovery still limits our understanding of forest resilience to hurricane disturbances. In this study, we utilized four remotely sensed vegetation indices (VIs), including the normalized difference infrared index (NDII), enhanced vegetation index (EVI), leaf area index (LAI), and solar-induced chlorophyll fluorescence (SIF), to examine the forest resilience to hurricanes of different strengths by quantifying the resistance, net change, and recovery of the forest after hurricanes that made landfall along the northern Gulf of Mexico from 2001 to 2015. The results revealed that the NDII was superior in monitoring the large-scale forest resilience. SIF exhibited a performance similar to that of the EVI. Wind speed was found to be the leading factor affecting forest damage and post-hurricane recovery. The impacted forest canopy began to recover approximately one month after the landfall. Woody wetlands exhibited less VI reduction and shorter recovery time than evergreen forests for the same category of hurricanes. For regions dominated by evergreen forests, NDII values lower than the multi-year average were observed across all seasons during the year after being impacted by a major hurricane. The widespread drought of 2006/2007 has aggravated the VI decrease and substantially extended the recovery period after hurricanes Ivan and Katrina. Overall, our findings derived from satellite observations provide essential information for understanding forest resilience to hurricanes as well as implementing efficient post-hurricane forest restoration.

Research areas: Severe Storms
The impacts of multi-physics parameterization on forecasting heavy rainfall induced by weak landfalling Typhoon Rumbia (2018) (2022)

The weak and sustained tropical cyclone (TC) Rumbia (2018) and its associated heavy precipitation after landfall are simulated by the Weather Research and Forecasting model using three microphysics parameterizations (MP) and two planetary boundary layer (PBL) schemes. Key factors regulating the heavy rainfall distribution of landed TC at three stages (landfall, inland slow-moving and recurving stage) and their sensitivities to multi-physics parameterizations are examined. Results show that heavy rainfall distribution is largely regulated by the intensity of TC itself at landfall, but more affected by environmental factors at the two inland stages, including the environmental vertical wind shear, the associated upper-level wind divergence and low-level moisture convergence. Different MP and PBL schemes mainly affect the simulation of TC thermodynamic structure and key environmental factors, leading to their different forecast skills at three stages. Specifically, the Yonsei University (YSU) PBL scheme systematically outperforms the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme in simulating stronger TC and heavy rainfall intensity. With the advantageous YSU PBL scheme, the Ferrier MP scheme only shows a slight advantage in simulating the intensity of TC and heavy rainfall at landfall. However, the WRF single-moment 6-class (WSM6) and Thompson scheme produce more graupel or snow, and better simulate the key environmental factors, showing their respective advantages in simulating the heavy rainfall structure and location at the two inland stages. This implies that the use of nonlocal YSU PBL scheme and the MP schemes with sophisticated ice processes shows superiority in simulating the postlandfall heavy rainfall induced by weak TCs.

Research areas: Severe Storms
Earth observation and geospatial data can predict the relative distribution of village level poverty in the Sundarban Biosphere Reserve, India (2022)

There is increasing interest in leveraging Earth Observation (EO) and geospatial data to predict and map aspects of socioeconomic conditions to support survey and census activities. This is particularly relevant for the frequent monitoring required to assess progress towards the UNs' Sustainable Development Goals (SDGs). The Sundarban Biosphere Reserve (SBR) is a region of international ecological importance, containing the Indian portion of the world's largest mangrove forest. The region is densely populated and home to over 4.4 million people, many living in chronic poverty with a strong dependence on nature-based rural livelihoods. Such livelihoods are vulnerable to frequent natural hazards including cyclone landfall and storm surges. In this study we examine associations between environmental variables derived from EO and geospatial data with a village level multidimensional poverty metric using random forest machine learning, to provide evidence in support of policy formulation in the field of poverty reduction. We find that environmental variables can predict up to 78% of the relative distribution of the poorest villages within the SBR. Exposure to cyclone hazard was the most important variable for prediction of poverty. The poorest villages were associated with relatively small areas of rural settlement (50%) and moderate to high cyclone hazard. The poorest villages were also associated with less productive agricultural land than the wealthiest. Analysis suggests villages with access to more diverse livelihood options, and a smaller dependence on agriculture may be more resilient to cyclone hazard. This study contributes to the understanding of poverty-environment dynamics within Low-and middle-income countries and the associations found can inform policy linked to socio-environmental scenarios within the SBR and potentially support monitoring of work towards SDG1 (No Poverty) across the region.

Research areas: Habitat Conversion/Fragmentation
Comparative climatology of outer tropical cyclone size using radial wind profiles (2021)

In this study was performed a comparative climatology of outer tropical cyclone (TCs) size using radial wind profiles. A wind speed of 2 ms1 (4 kt) was taken as the threshold to define the TC size. The method proposed by Willoughby et al. (2006) (W06) to determine the wind profile showed the least variance and the smallest coefficient of variation of all profiles. W06 correctly described the radial wind structure of storms such as Hurricane Irma (2017) and Cyclone Giri (2010), compared with the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data. Thus, W06 was used to develop the climatological TC size (TCSize) database. It was found that the tropical cyclones are largest when the maximum wind speed ranges between 20 and 40 ms1 and they most frequently reach a size between 700 and 800 km. The TCs exhibit their maximum size when they are in extratropical latitudes, while the smallest are observed in the low latitudes of both hemispheres. The global mean size is 748.7 km with a 95% confidence interval of [748.2,749.2] km. Median storm size is largest in the North Atlantic basin and smallest in the North Indian Ocean. The method proposed here is designed to be an objective metric that can be quickly applied to any TC when its position, maximum wind speed, and minimum central pressure are known. As a result, a TCSize database was created for all ocean basins, which could be useful for many applications, including different risk analyses.

Research areas: Severe Storms
Multiple satellite observations of cloud cover in extratropical cyclones (2013)

cloud observations from NASA Moderate Resolution Imaging Spectroradiometer, Multiangle Imaging Spectroradiometer, and CloudSat-CALIPSO, composites of cloud fraction in southern and northern hemisphere extratropical cyclones are obtained for cold and warm seasons between 2006 and 2010, to assess differences between these three data sets, and between summer and winter cyclones. In both hemispheres and seasons, over the open ocean, the cyclone-centered cloud fraction composites agree within 5% across the three data sets, but behind the cold fronts, or over sea ice and land, the differences are much larger. To supplement the data set comparison and learn more about the cyclones, we also examine the differences in cloud fraction between cold and warm season for each data set. The difference in cloud fraction between cold and warm season southern hemisphere cyclones is small for all three data sets, but of the same order of magnitude as the differences between the data sets. The cold-warm season contrast in northern hemisphere cyclone cloud fractions is similar for all three data sets: in the warm sector, the cold season cloud fractions are lower close to the low, but larger on the equator edge than their warm season counterparts. This seasonal contrast in cloud fraction within the cyclones warm sector seems to be related to the seasonal differences in moisture flux within the cyclones. Our analysis suggests that the three different data sets can all be used confidently when studying the warm sector and warm frontal zone of extratropical cyclones but caution should be exerted when studying clouds in the cold sector.

Research areas: Severe Storms
Spatial characteristics of rain fields associated with tropical cyclones landfalling over the western Gulf of Mexico and Caribbean Sea (2018)

Abstract The western Gulf Coast and Caribbean coast are regions that are highly vulnerable to precipitation associated with tropical cyclones (TCs). Defining the spatial dimensions of TC rain fields helps determine the timing and duration of rainfall for a given location. Therefore, this study measured the area, dispersion, and displacement of light and moderate rain fields associated with 35 TCs making landfalls in this region and explored conditions contributing to their spatial variability. The spatial patterns of satellite-estimated rain rates are determined through hot spot analysis. Rainfall coverage is largest as TCs approach the western Caribbean coast, and smaller as TCs move over the Gulf of Mexico (GM) after making landfall over the Yucatan Peninsula. The rain fields are displaced eastward and northward over the western and central Caribbean Sea and the central GM. Rainfall fields have more displacement toward the west and south, which is over land, when TCs move over the southern GM, possibly as a result of the influence of Central American gyres. The area and dispersion of rainfall are significantly correlated with storm intensity and total precipitable water. The displacement of rainfall is significantly correlated with vertical wind shear. Over the Bay of Campeche, TC precipitation extends westward, which may be related to the convergence of moisture above the boundary layer from the Pacific Ocean and near-surface convergence enhanced by land. Additionally, half of the storms produce rainfall over land about 48 h before landfall. TCs may produce light rainfall over land for more than 72 h in this region.

Research areas: Severe Storms
Failure criteria for porous dome rocks and lavas: a study of Mt. Unzen, Japan (2018)

Abstract. The strength and macroscopic deformation mode (brittle vs. ductile) of rocks is generally related to the porosity and pressure conditions, with occasional considerations of strain rate. At high temperature, molten rocks abide by Maxwell's viscoelasticity and their deformation mode is generally defined by strain rate or reciprocally by comparing the relaxation timescale of the material (for a given condition) to the observation timescale  a dimensionless ratio known as the Deborah (De) number. Volcanic materials are extremely heterogeneous, with variable concentrations of crystals, glassmelt, and vesicles (of different sizes), and a complete description of the conditions leading to flow or rupture as a function of temperature, stress and strain rate (or timescale of observation) eludes us. Here, we examined the conditions which lead to the macroscopic failure of variably vesicular (0.090.35), crystal-rich ( 75 vol %), pristine and altered dome rocks (at ambient temperature) and lavas (at 900 C) from Mt. Unzen volcano, Japan. We found that the strength of the dome rocks decreases with porosity and is commonly independent of strain rate; when comparing pristine and altered rocks, we found that the precipitation of secondary mineral phases in the original pore space caused minor strengthening. The strength of the lavas (at 900 C) also decreases with porosity. Importantly, the results demonstrate that these dome rocks are weaker at ambient temperatures than when heated and deformed at 900 C (for a given strain rate resulting in brittle behaviour). Thermal stressing (by heating and cooling a rock up to 900 C at a rate of 4 C min1, before testing its strength at ambient temperature) was found not to affect the strength of rocks.In the magmatic state (900 C), the rheology of the dome lavas is strongly strain rate dependent. Under conditions of low experimental strain rate ( 104 s1), ductile deformation dominated (i.e. the material sustained substantial, pervasive deformation) and displayed a non-Newtonian shear thinning behaviour. In this regime, the apparent viscosities of the dome lavas were found to be essentially equivalent, independent of vesicularity, likely due to the lack of pore pressurisation and efficient pore collapse during shear. At high experimental strain rates (  104 s1) the lavas displayed an increasingly brittle response (i.e. deformation resulted in failure along localised faults); we observed an increase in strength and a decrease in strain to failure as a function of strain rate. To constrain the conditions leading to failure of the lavas, we analysed and compared the critical Deborah number at failure (Dec) of these lavas to that of pure melt (Demelt = 103102; Webb and Dingwell, 1990). We found that the presence of crystals decreases Dec to between 6.6104 and 1104. The vesicularity (), which dictates the strength of lavas, further controls Dec following a linear trend. We discuss the implications of these findings for the case of magma ascent and lava dome structural stability.

Research areas: Volcanic Eruptions
The Mesoscale Gravity Wave Response to the 2022 Tonga Volcanic Eruption: AIRS and MLS Satellite Observations and Source Backtracing (2022)

On 15 January 2022, the Hunga Tonga-Hunga Ha'apai volcano erupted violently. This exceptional event excited a manifold of atmospheric waves. Here, we focus on the mesoscale part of the wave spectrum. About 8.5 hr after the eruption a strong atmospheric gravity wave (GW) was observed in the stratosphere by the satellite instruments Atmospheric Infrared Sounder (AIRS) and Microwave Limb Sounder (MLS) in the vicinity of Tonga. By ray-tracing, we confirm the eruption as the source of this GW event. We determine the wave characteristics of the GW in terms of horizontal and vertical wavelengths and GW momentum flux. The strength of the GW is compared to the usual Southern Hemisphere flux values during this week. The event is comparable to the strongest convective events considering MLS, and exceptionally strong considering AIRS, which observes faster waves only.

Research areas: Volcanic Eruptions
A multi-sensor satellite-based archive of the largest SO2 volcanic eruptions since 2006 (2020)

Abstract. We present a multi-sensor archive collecting spatial and temporal information about volcanic SO2 clouds generated by the 11 largest eruptions of this century. The detection and monitoring of volcanic clouds are an important topic for aviation management, climate issues and weather forecasts. Several studies focusing on single eruptive events exist, but no archive available at the moment combines quantitative data from as many instruments. We archived and collocated the SO2 vertical column density estimations from three different satellite instruments (AIRS, IASI and GOME-2), atmospheric parameters as vertical profiles from the Global Navigation Satellite Systems (GNSS) Radio Occultations (RO), and the cloud-top height and aerosol type from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Additionally, we provide information about the cloud-top height from three different algorithms and the atmospheric anomaly due to the presence of the cloud. The dataset is gathering 206 d of SO2 data, collocated with 44 180 backscatter profiles and 64 764 radio occultation profiles. The modular structure of the archive allows an easy collocation of the datasets according to the users' needs, and the cross-comparison of the datasets shows different consistency of the parameters estimated with different sensors and algorithms, according to the sensitivity and resolution of the instruments. The data described here are published with a DOI at https://doi.org/10.5880/fidgeo.2020.016 (Tournigand et al., 2020a).

Research areas: Volcanic Eruptions
What contributes to the inter‐annual variability in tropical lower stratospheric temperatures? (2022)

The inter-annual variability in mid and lower stratospheric temperatures for the period 1984-2019 is decomposed into dynamical and radiative contributions using a radiative calculation perturbed with changes in dynamical heating, trace gases and aerosol optical depth. The temperature timeseries obtained is highly correlated with the de-seasonalized ERA5 temperature (r<SUP>2</SUP> &gt; 0.6 in the region 15 to 70 hPa, 1992 to 2019-after the Pinatubo volcanic eruption). Ozone and dynamical heating contributions are found to be equally important, with water vapor, stratospheric aerosols, and carbon dioxide playing smaller roles. Prominent aspects of the temperature timeseries are closely reproduced, including the 1991 Pinatubo volcanic eruption, the year-2000 water vapor drop, and the 2016 Quasi-biennial oscillation (QBO) disruption. Below 20 hPa, ozone is primarily controlled by transport and is positively correlated to the upwelling. This ozone-transport feedback acts to increase the temperature response to a change in upwelling by providing an additional ozone-induced radiative temperature change. This can be quantified as an enhancement of the dynamical heating of about 20% at 70 hPa. A Principal Oscillation Pattern (POP) analysis is used to estimate the contribution of the ozone QBO (±1 K at 70 hPa). The non-QBO ozone variability is also shown to be significant. Using the QBO leading POP timeseries as representative of the regular QBO signal, the QBO 2016 disruption is shown to have an anomalously large radiative impact on temperature due to the ozone change (&gt; 3 K$ &gt; 3\hspace*{.5em}\mathrm{K}$ at 70 hPa).

Research areas: Volcanic Eruptions
Quantifying Stratospheric Temperature Signals and Climate Imprints From (2019)

Small volcanic eruptions and their effects have recently come into research focus. While large eruptions are known to strongly affect stratospheric temperature, the impacts of smaller eruptions are hard to quantify because their signals are masked by natural variability. Here, we quantify the temperature signals from small volcanic eruptions between 2002 and 2016 using new vertically resolved aerosol data and precise temperature observations from radio occultation. We find characteristic space-time signals that can be associated with specific eruptions. In the lower stratosphere, robust warming signals are observed, while in the midstratosphere also cooling signals of some eruptions appear. We find that the volcanic contribution to the temperature trend is up to 20%, depending on latitude and altitude. We conclude that detailed knowledge of the vertical structure of volcanic temperature impacts is crucial for comprehensive trend analysis in order to separate natural from anthropogenic temperature changes.

Research areas: Volcanic Eruptions
Sediment connectivity changes in an Andean catchment affected by volcanic eruption (2019)

River systems are continuously affected by multiple natural and anthropogenic phenomena. Among major natural disturbances, volcanic eruptions have the capability to overthrow the forms and to modify dramatically the morphological setting and sediment connectivity of the system. Moreover, the input of sediments in the channel network can lead to active channel widening, bed aggradation and river scouring, which in turn may affect downstream human settlements. In this context, the present research aims to investigate sediment connectivity by means of a geomorphometric index in a catchment affected by an explosive volcanic eruption in order to assess its variation before and after the disturbance. We developed a workflow exploiting the use of open source data (i.e., Global Digital Elevation Models, satellite imagery) to represent the impedance to the sediment fluxes and to apply the Index of Connectivity (IC) in this context characterized by the lack of high-resolution topographic data. The study area is the Blanco River basin, southern Chile, which was heavily affected by the eruption of Chaiten volcano (20082009) that caused the partial destruction of the forest and the profound alteration of Blanco River's morphology. The application of the IC on different land cover scenarios, derived by combining field observations and satellite image classification techniques, showed an increase in sediment connectivity after the volcanic eruption. In addition, the results highlighted different patterns of connectivity according to the expansion of the active channel induced by the massive input of pyroclastic material. The approach proposed in this study case offers a methodology to investigate sediment connectivity in a river catchment affected by natural disturbance where high-resolution data are not available. The results of the study help to improve knowledge on the effect of volcanic eruptions in the hydrologic catchment and to improve watershed management strategies in such kind of environment.

Research areas: Volcanic Eruptions
Optical depths and vertical profiles of stratospheric aerosol based on multi-year polarization measurements of the twilight sky (2019)

The method of detection of light scattering on stratospheric aerosol particles on the twilight sky background is considered. It is based on the data on sky intensity and polarization in the solar vertical at zenith distances of up to 50 from the sunset till the moment of the Sun depression to 8 below the horizon. The measurements conducted in central Russia since 2011 had shown the negative trend of stratospheric aerosol content, this can be related with the relaxation of the stratosphere after the number of volcanic eruptions during the first decade of XXI century.

Research areas: Validation