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At least 1,603 records · Page 89

Quantification of the Land Surface and Brown Ocean Influence on Tropical Cyclone Intensification Over Land

An investigation of TC Kelvin in February 2018 over northeast Australia was conducted to understand the mechanisms of the Brown Ocean effect (BOE), and to develop a comprehensive analysis framework for landfalling tropical cyclones (TCs) in the process. NASA’s Land Information System (LIS) coupled to the NASA Unified WRF (NU-WRF) system was employed as the numerical model framework for 12 land/soil moisture perturbation experiments. Impacts of soil moisture and surface enthalpy flux conditions on TC Kelvin were investigated by closely evaluating simulated track and intensity, midlevel atmospheric thermodynamic properties, vertical wind shear, total precipitable water (TPW), and surface moisture flux. The results suggest that there were recognized differentiations among the sensitivity simulations as a result of land surface (e.g., soil moisture and texture) conditions. However, the intensification of TC Kelvin over land was more strongly related to atmospheric moisture advection and the diurnal cycle of solar radiation (i.e., radiative cooling) than to overall soil moisture conditions or surface fluxes. The analysis framework employed here for TC Kelvin can serve as a foundation to specifically quantify the factors governing the BOE. It also demonstrates that the BOE is not a binary influence (i.e. all or nothing), but instead operates in a continuum from largely to minimally influential such that it could be utilized to help improve prediction of inland effects for all landfalling TCs.

Brown Ocean Effect↗

GCM simulations of the tropical hydrogen distribution observed by Mars Odyssey

The age and nature of the tropical hydrogen deposits on Mars remain uncertain. Competing theories sugges that the deposits are composed of either ancient, hydrated minerals or recently emplaced water ice. We use the GFDL Mars GCM with a fully coupled atmosphere-regolith water cycle to explore which of these hypotheses is best supported by model results.

Richardson, M. I.↗

On the Evolution-Dynamics of Tropical Ocean-Atmosphere Annual-Cycle Variability

The structure of ocean-atmosphere annual-cycle variability across the global tropics is extracted from the Comprehensive Ocean-Atmosphere Data Set (COADS) surface winds and SSTs, and oceanic heat-content simulation from a nonlinear shallow water model (forced by COADS wind stress) using the co-variance based rotated principal component analysis technique.

COADS↗

Laminae in the Tropical Middle Stratosphere: Origin and Age Estimation

Isentropic transport of stratospheric air from mid-latitudes into the tropics has been a subject of considerable interest recently. This exchange process is important for the understanding of the distribution of trace gases and ozone, and for the prediction of the exhaust dispersion of a proposed fleet of high speed civil transport aircraft (HSCT), which would operate in the 15 to 20 km altitude range.

middle↗

Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory

Quantifying tropical aboveground biomass (agb) is an outstanding challenge that requires knowledge on the 3D structure of forests. Recent studies suggest that the uncertainty in estimating agb of large trees is significantly reduced if tree height and crown size are accounted for in addition to the traditional trunk diameter and wood density. Due to the fact that field inventory techniques are not adapted to characterize the 3D forest structure, crown size metrics (e.g. height and radius) are commonly estimated as a function of trunk diameter using allometric models with limitations in explaining crown variability. Airborne lidar techniques have the potential for characterizing tree height and crown size but are not adapted to estimate trunk diameter, which is a strong predictor of agb. Here, we investigate the synergy of field inventory and airborne lidar techniques to characterize the forest structure by assessing the uncertainty introduced by the field-based allometric models in the estimation of agb at the tree-level. We focus in 1454 large individual trees (trunk diameter > 60 cm) located within the La Selva Biological Station for which we dispose of field observations (trunk diameter and wood density) and lidar derived metrics (tree height and crown radius). We show that the field-based allometric models overestimate tree height and underestimate crown radius. As a result, the allometric approach overestimates the tree-level agb in 0.8 Mg when considering the 1454 individuals and the errors can reach more than 50% of the agb of individual trees. These errors on the large trees agb highly impact on the plot-level results and then propagate to the estimation of carbon stocks at the regional and national-levels.

Clark, David↗

Inter-annual variation of tropical cyclones simulated by GEOS-5 AGCM with modified convection scheme

The Goddard Earth Observing System version 5 (GEOS-5) global climate model with a 50-km horizontal resolution is forced by observed sea surface temperature (SST) to examine the fidelity of the seasonal-mean and inter-annual variation of tropical cyclones (TCs) in the western North Pacific (WNP) and the North Atlantic (NATL). The standard Relaxed Arakawa Schubert (RAS) deep convection scheme is modified to improve the representation of TCs, where the scheme implements a stochastic limit of the cumulus entrainment rate. The modification drives mid- and upper-tropospheric cooling and low- to mid-tropospheric drying in the background state, which tends to increase atmospheric instability. This enables the model to increase convective variability on an intra-seasonal timescale and improve the simulation of intense storms. Five-member ensemble runs with the modified RAS scheme for 12 years (1998–2009) exhibit realistic spatial distributions in the climatological-mean TC development area and their pathways over WNP and NATL. The GCM is able to reproduce the inter-annual variation of accumulated cyclone energy (ACE) by prescribing yearly varying observed SST even though the individual TC intensity is still underpredicted. A sensitivity of TC activity to El Niño–Southern Oscillation (ENSO) phase is also reproduced realistically over WNP in terms of the spatial pattern changes in the main development region and TC pathways. However, the model exhibits a notable deficiency in NATL in reproducing the observed inter-annual variation of TC activity and the sensitivity to the ENSO.

accumulated cyclone energy↗

GOES-16 Observations of Rapidly-Intensifying Tropical Cyclones: Hurricanes Harvey (2017), Maria (2017), And Michael (2018)

This study utilizes brightness temperatures (Tb’s) observed by the infrared longwave window band (Ch 14; 11.2 m) from the Geostationary Operational Environmental Satellite-16 (GOES-16) to examine the structure of Hurricanes Harvey, Maria, and Michael throughout their lifetimes. During the times leading up to their rapid intensifications (RI), two-dimensional inner-core structures are examined to analyze the strength and location of the developing convection. Moderate vertical wind shear in the environments of Harvey and Michael induced a pronounced convective asymmetry prior to RI, followed by a rapid axisymmetrization that occurred essentially in conjunction with RI. The evolutions of the tropical cyclones’ (TCs’) coldest Tb’s indicate that the inner-core convective activity began to increase in the 12 h prior to RI onset, primarily in 2–4-h substantial “bursts”, while substantial convection dominated essentially the entirety of the region within 100 km of the surface center within 12 h of the onset of intensification. Azimuthally averaged Tb evolutions illustrate the development of each TCs’ eye and eyewall, the variability of the radial extent of the central dense overcast associated with the diurnal cycle, as well as details of the evolving convective structures throughout intensification. Hövmoller diagrams of data at constant radii reveal areas of cold Tb’s propagating around the TCs on timescales of 2–3-h. The examination of these features in a deep-layer shear-relative sense reveals that they initiate primarily downshear of the TCs’ surface centers. As RI is reached, these areas of convection are able to propagate into the upshear quadrants, which helps facilitate the onset of more substantial intensification.

Hurricanes↗

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high‐resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED‐2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED‐2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

Marcos Longo↗

The NASA AfriSAR Campaign: Airborne SAR and Lidar Measurements of Tropical Forest Structure and Biomass in Support of Current and Future Space Missions

In 2015 and 2016, the AfriSAR campaign was carried out as a collaborative effort among international space and National Park agencies (ESA, NASA, ONERA, DLR, ANPN and AGEOS) in support of the upcoming ESA BIOMASS, NASA-ISRO Synthetic Aperture Radar (NISAR) and NASA Global Ecosystem Dynamics Initiative (GEDI) missions. The NASA contribution to the campaign was conducted in 2016 with the NASA LVIS (Land Vegetation and Ice Sensor) Lidar, the NASA L-band UAVSAR (Uninhabited Aerial Vehicle Synthetic Aperture Radar). A central motivation for the AfriSAR deployment was the common AGBD estimation requirement for the three future spaceborne missions, the lack of sufficient airborne and ground calibration data covering the full range of ABGD in tropical forest systems, and the intercomparison and fusion of the technologies. During the campaign, over 7000 km2 of waveform Lidar data from LVIS and 30000 km2 of UAVSAR data were collected over 10 key sites and transects. In addition, field measurements of forest structure and biomass were collected in sixteen 1 hectare sized plots. The campaign produced gridded Lidar canopy structure products, gridded aboveground biomass and associated uncertainties, Lidar based vegetation canopy cover profile products, Polarimetric Interferometric SAR and Tomographic SAR products and field measurements. Our results showcase the types of data products and scientific results expected from the spaceborne Lidar and SAR missions; we also expect that the AfriSAR campaign data will facilitate further analysis and use of waveform Lidar and multiple baseline polarimetric SAR datasets for carbon cycle, biodiversity, water resources and more applications by the greater scientific community.

AfriSAR↗

Assimilation of Hyperspectral Infrared Radiances from the Cloud-Clearing Methodology: Results from the 2017 Atlantic Tropical Cyclone Season

Assimilation of cloud-affected radiances has the potential to dramatically improve numerical weather prediction systems, as has already been widely shown by use of all-sky microwave radiances. Assimilation of cloudy infrared (IR) radiances, however, lags far behind and only clear-sky radiances are used operationally, leaving data voids in dynamically sensitive areas, such as around tropical cyclones. This team has previously shown the positive benefit of assimilating cloud-cleared IR radiances from hyperspectral sensors (CCRs) and in this work applies the cloud-clearing methodology to generate fully customizable CCRs using an algorithm designed to be portable and reduce latency. These data are successfully assimilated in the Goddard Earth Observing System (GEOS) data assimilation system (DAS) for the 2017 Atlantic Hurricane season.

E L Mcgrath-Spangler↗

Regional Variations in the Diurnal Cycle of Tropical Precipitation as Represented by IMERG, ERA5, and Spaceborne Ku Radar

The diurnal cycle of precipitation is highly regional and is typically a product of multiple competing effects that can be highly localized. The diurnal cycle in high precipitation regions such as the Amazon and the Maritime Continent are of particular interest, especially due to the complex coastal effects which take place over the Maritime Continent. The high spatial and temporal resolution provided by the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) dataset, is used in this study to examine the fine-scale features of the diurnal cycle in these regions. Using an 18-year (2000 – 2018) record of IMERG precipitation observations, diurnal and semidiurnal phase and amplitude are calculated using a fast Fourier transform (FFT) method on precipitation averaged for each half-hour of the day at 0.1°x0.1° spatial resolution. We first introduce an objective method of identifying locations where the diurnal signals are robust and strong. Clear patterns of precipitation phase propagation with distance from shore are shown over both regions, with the diurnal phase and amplitude exhibiting a strong dependence on the distance from the coastline. Semidiurnal cycles are generally weaker than the diurnal cycle except in some isolated locations. Similar analysis is also conducted on the ERA5 reanalysis data in order to evaluate the model’s representation of the precipitation diurnal cycle. The model captures the broad scale patterns of diurnal variability but does not capture all the fine scale patterns nor the exact timing that is observed by IMERG. Comparisons are also made to a long record Ku radar dataset created by combining Tropical Rainfall Measuring Mission (TRMM) and GPM observations, thus providing an additional point of comparison for the timing of the ERA5 precipitation peak, since the timing precipitation can be different, even in between observational datasets.

L J Hayden↗

Changes in Land Use Enhance the Sensitivity of Tropical Ecosystems to Fire-Climate Extremes

The Pantanal, the largest contiguous wetland in the world with a high diversity of ecosystems and habitat for several endangered species, was impacted by record-breaking wildfires in 2020. In this study, we integrate satellite and modeling data that enable exploration of natural and human contributing factors to the unprecedented 2020 fires. We demonstrate that the fires were fueled by an exceptional multi-year drought, but dry conditions solely could not explain the spatial patterns of burning. Our analysis reveals how human-caused fires exacerbated drought effects on natural ecosystem within the Pantanal, with large burned fractions primarily over natural (52%), and low cattle density areas (44%) in 2020. The post-fire ecosystem and hydrology changes also had strong ecological effects, with vegetation productivity less than − 1.5 σ over more than 30% of the natural and conservation areas. In contrast to more managed areas, there was a clear decrease in evaporation (by ~ 9%) and an increase in runoff (by ~ 5%) over the natural areas, with long-term impacts on ecosystem recovery and fire risk. This study provides the first tropical evidence outside rainforests of the synergy between climate, land management and fires, and the associated impacts on the ecosystem and hydrology over the largest contiguous wetlands in the world.

Sujay Kumar↗

Investigating Lightning Behavior in Rapidly Intensifying Atlantic Tropical Cyclones

Lightning is a useful tool in forecasting and understanding the behavior of tropical cyclones (TCs). The Geostationary Lightning Mapper (GLM) aboard the GOES-16 geostationary satellite measures a multitude of lightning parameters, such as flash extent density (FED), average flash area (AFA) and optical energy for most of North America, South America, and the Pacific Ocean. GLM has brought about an era of spaceborne measurements to track storms many miles off the coasts and has allowed for the study of lightning throughout a TCs entire lifespan. FED has been found to be indicative of strength and intensification in TCs, but optical energy is a relatively new parameter that has not been studied intensively. This presentation analyzes the relationship between rapid intensification (RI) and GLM optical energy, AFA, and FED in Hurricanes Florence (2018) and Laura (2020). Using a 24-hour time interval in which each storm underwent RI, optical energy was analyzed from the innermost 100 kilometers of the eye and then was averaged for each minute to determine if there was a relationship between optical energy, AFA, FED, and intensification. Optical energy, FED, and AFA spiked just before RI began and then fell as the storms intensified more rapidly. These parameters increased again as intensification slowed slightly, while the optical energy peaks much lower in Hurricane Laura and much higher in Hurricane Florence. While these results show a pattern in lightning in these two TCs, further investigation of parameters like updraft strength and charge separation from microwave imagery during these secondary peaks in which optical energy behaves differently than the first peak may provide further insight as to the behavior of these TCs during RI.

Kiahna Mollette↗

Relating Lightning Flash Size and Energy to Tropical Cyclone Structure and Intensity Change

The number and location of lightning flashes within tropical cyclones (TCs) has proven to be a useful predictor of TC intensity change. Generally, a large number of lightning flashes located within the radius of maximum wind indicates a convective structure favorable for intensification. However, weakening TCs can also exhibit numerous lightning flashes, and rapid intensification can occur in the absence of inner-core lightning. It is thus difficult to interpret what the presence or absence of inner-core lightning might mean for a TC’s future evolution. The Geostationary Lightning Mapper (GLM) offers a new capability to observe not only the number and location of lightning flashes, but also the size and optical energy of those flashes. This presentation describes the application of these new metrics to further understand the relationship between lightning and TC structural and intensity evolution. Evidence is presented that flash size and optical energy reveal more about the convective and kinematic structures relevant to intensity change than an analysis of lightning flash count and location alone. We hypothesize that large, energetic lightning flashes are generated when the TC secondary circulation is strongest, an environment which favors increased generation of ice particles in the eyewall updraft and larger charge separation through outward advection of ice in the upper-level outflow. Conversely, smaller, lower-energy lightning flashes tend to occur in more localized turbulent updrafts, which can be forced by a variety of processes – some of which act to weaken the storm. These hypotheses are supported by numerical simulations of TC convection.

Patrick Duran↗