Building a Land Data Assimilation Community to Tackle Technical Challenges in Quantifying and Reducing Uncertainty in Land Model Predictions
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Use of Forecast Atmosphere for Earth Entry, Descent, and Landing Modeling
Flight mechanics simulations are used to characterize the performance of Earth entry, descent, and landing vehicles. Atmospheric prediction models are often a key component of these simulations. Global atmospheric models are used for both engineering design due to their ability to define atmospheric properties over a large swath of locations and times as well as used for the availability of atmospheric uncertainties in the models that can be used in statistical performance analysis. However for day-of-flight operations, the use of forecast atmospheres based on more current measurements are beneficial to the accuracy of the performance prediction, including landing locations. Reanalysis of these forecasts can also be used for post-flight analysis, including trajectory reconstruction. This paper describes how forecast atmospheres can be beneficial for Earth entry, descent, and landing analysis and ways these models can be implemented in simulations.
Soumyo Dutta↗
Failure detection by pilots during automatic landing: Models and experiments
A model of the pilot as a monitor of instrument failures during automatic landing is proposed. The failure detection model consists of two stages: a linear estimator (Kalman Filter) and a decision mechanism which is based on sequential analysis. The filter equations are derived from a simplified version of the linearized dynamics of the airplane and the control loop. The perceptual observation noise is modelled to include the effects of the partition of attention among the several instruments. The final result is a simple model consisting of a high pass filter to produce the observation residuals, and a decision function which is a pure integration of the residuals minus a bias term. The dynamics of a Boeing 707 were used to simulate the fully coupled final approach in a fixed base simulator which also included failures in the airspeed, glideslope, and localizer indicators. Subjects monitored the approaches and detected the failures; their performance was compared with the predictions of the model with good agreement between the experimental data and the model.
Gai, E. G.↗
Southern Bhutan Ecological Forecasting II: Utilizing NASA Earth Observations to Model Land Cover Change and Elephant Wildlife Corridors in Southern Bhutan
The diverse landscapes of Bhutan host a rich biodiversity of animal and plant species. Asian elephants (Elephas maximus) are a flagship keystone wildlife species whose conservation is essential for the functioning of Bhutan’s forest ecosystems. Despite this, increasing habitat loss and human-elephant conflict continue to be detrimental to the survival of Asian elephants. The lack of information on Bhutan’s elephants and land use and land cover (LULC) trends present major challenges for Bhutan in modeling locations with suitable habitat and biological corridors for elephants. The DEVELOP Southern Bhutan Ecological Forecasting II team at NASA Goddard Space Flight Center partnered with the Bhutan Foundation, Bhutan Tiger Center, and Bhutan Ecological Society to help address this problem. The team mapped LULC in Bhutan for 2010 and 2015 by utilizing NASA Earth observations, including Landsat 5 Thematic Mapper (TM) and Landsat 8 Operational Land Imager (OLI) to acquire information on historical LULC patterns and view apparent land cover change. The team used the Linkage Pathways Tool of the Linkage Mapper Toolbox in ArcMap to derive biological corridor maps from habitat suitability model outputs of the previous term and known locations of protected areas in Bhutan. The corridor maps were used to view and assess corridor suitability and connectivity between protected parks. Project results are being provided to partners to help make informed decisions on the placement and conservation of elephant movement corridors.
Thinley Yidzin Wangden↗
Failure detection by pilots during automatic landing - Models and experiments
A model is proposed to describe the pilot as a monitor of automatic landing systems. The failures treated are equivalent to the addition of a dynamic change in the mean of the observation process. The failure detection model of the pilot consists of two stages: a linear estimator (Kalman filter) and a decision mechanism based on sequential analysis. The filter equations are derived from a simplified version of the linearized dynamics of the airplane and the control loop. The perceptual observation noise is modified to include the effects of allocation of attention among the several instruments. The final result is a simple model consisting of a high-pass filter to produce the observation residuals and a decision function which is a pure integration of the residuals minus a bias term. The dynamics of a Boeing 707 were used to simulate the fully coupled final approach in a fixed-base simulator. Observers monitored the approaches and detected the failures; their performance was compared with the predictions of the model.
Gai, E. G.↗
Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches
Quantifying the net carbon flux from land use and land cover changes (fLULCC) is critical for understanding the global carbon cycle and, hence, to support climate change mitigation. However, large-scale fLULCC is not directly measurable and has to be inferred from models instead, such as semi-empirical bookkeeping models and process-based dynamic global vegetation models (DGVMs). By definition, fLULCC estimates are not directly comparable between these two different model types. As an important example, DGVM-based fLULCC in the annual global carbon budgets is estimated under transient environmental forcing and includes the so-called loss of additional sink capacity (LASC). The LASC results from the impact of environmental changes on land carbon storage potential of managed land compared to potential vegetation and accumulates over time, which is not captured in bookkeeping models. The fLULCC from transient DGVM simulations, thus, strongly depends on the timing of land use and land cover changes mainly because LASC accumulation is cut off at the end of the simulated period. To estimate the LASC, the fLULCC from pre-industrial DGVM simulations, which is independent of changing environmental conditions, can be used. Additionally, DGVMs using constant present-day environmental forcing enable an approximation of bookkeeping estimates. Here, we analyse these three DGVM-derived fLULCC estimations (under transient, pre-industrial, and present-day forcing) for 12 models within 18 regions and quantify their differences as well as climate- and CO2-induced components and compare them to bookkeeping estimates. Averaged across the models, we find a global fLULCC (under transient conditions) of 2.0±0.6 PgC/yr for 2009–2018, of which ∼40 % are attributable to the LASC (0.8±0.3 PgC/yr). From 1850 onward, the fLULCC accumulated to 189±56 PgC with 40±15 PgC from the LASC. Around 1960, the accumulating nature of the LASC causes global transient fLULCC estimates to exceed estimates under present-day conditions, despite generally increased carbon stocks in the latter. Regional hotspots of high cumulative and annual LASC values are found in the USA, China, Brazil, equatorial Africa, and Southeast Asia, mainly due to deforestation for cropland. Distinct negative LASC estimates in Europe (early reforestation) and from 2000 onward in the Ukraine (recultivation of post-Soviet abandoned agricultural land), indicate that fLULCC estimates in these regions are lower in transient DGVM compared to bookkeeping approaches. Our study unravels the strong dependence of fLULCC estimates on the time a certain land use and land cover change event happened to occur and on the chosen time period for the forcing of environmental conditions in the underlying simulations. We argue for an approach that provides an accounting of the fLULCC that is more robust against these choices, for example by estimating a mean DGVM ensemble fLULCC and LASC for a defined reference period and homogeneous environmental changes (CO2 only).
land use and land cover change↗
Mars 2020 Surface Mission Modeling Landing Site Thermal Environments
This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into six thermal environment bins. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.
Lange, Robert D.↗
Mars 2020 Surface Mission Modeling Landing Site Thermal Environments
This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into six thermal environment bins. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.
Lange, Robert D.↗
DAVINCI Venus Entry, Descent, and Landing Modeling and Simulation
The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission will launch in June 2029 and explore Venus via two flybys and a probe landing scheduled for June 2031. The goals of the mission are to study the origin, evolution, and current state of Venus and to understand if it was habitable at a point in the past. The entry, descent, and landing (EDL) concept of operations of the probe leverages on the successful Pioneer Venus large probe mission. The science objectives of the mission levy certain requirements on the EDL system, such as landing in the scientifically important Alpha Regio Tessera and telemetering several gigabytes of instrumentation data to the orbiting relay spacecraft before the probe impacts the surface. In order to optimize the EDL sequence of the lander and to verify key driving requirements, a six degree of freedom EDL flight mechanics simulation has been created based on the best available aerodynamic and atmospheric models valid for Venus. This paper describes the EDL modeling and simulation and summarizes the current flight mechanics results for the mission.
Soumyo Dutta↗
DAVINCI Venus Entry, Descent, and Landing Modeling and Simulation
The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission will launch in June 2029 and explore Venus via two flybys and a probe landing scheduled for June 2031. The goals of the mission are to study the origin, evolution, and current state of Venus and to understand if it was habitable at a point in the past. The entry, descent, and landing (EDL) concept of operations of the probe leverages on the successful Pioneer Venus large probe mission. The science objectives of the mission levy certain requirements on the EDL system, such as landing in the scientifically important Alpha Regio Tessera and telemetering several gigabytes of instrumentation data to the orbiting relay spacecraft before the probe impacts the surface. In order to optimize the EDL sequence of the lander and to verify key driving requirements, a six degree of freedom EDL flight mechanics simulation has been created based on the best available aerodynamic and atmospheric models valid for Venus. This paper describes the EDL modeling and simulation and summarizes the current flight mechanics results for the mission.
Soumyo Dutta↗
Mars 2020 Surface Mission Modeling: Landing Site Thermal Environments
This paper presents work done by the Mars 2020 Mission Planning Team to characterize landing site thermal environments. A process was developed to take in ground temperature simulation data for each landing site and efficiently discretize it into a handful of thermal bin environments. The Mars 2020 Thermal Team then performed detailed heater and energy modeling in each of those environments. The heater modeling results were implemented into a Monte Carlo based surface mission model to understand mission performance impacts. The Mars 2020 Instrument Teams used the results to inform their design and to better understand how the thermal conditions at each landing site affected their instruments.
Lange, Robert D.↗
Noise Spectra and Directivity For a Scale-Model Landing Gear
An extensive experimental study has been conducted to acquire detailed noise spectra and directivity data for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. The measurements were conducted in the NASA Langley Quiet Flow Facility using a 41-microphone directional array system positioned at a range of polar and azimuthal observer angles with respect to the model. DAMAS (Deconvolution Approach for the Mapping of Acoustic Sources) array processing as well as straightforward individual microphone processing were employed to compile unique flyover and sideline directivity databases for a range of freestream Mach numbers (0.11 - 0.17) covering typical approach conditions. Comprehensive corrections were applied to the test data to account for shear layer ray path and amplitude variations. This allowed proper beamforming at different measurement orientations, as well as directivity presentation in free-field emission coordinates. Four different configurations of the landing gear were tested: a baseline configuration with and without an attached side door, and a noise reduction concept "toboggan" truck fairing with and without side door. DAMAS noise source distributions were determined. Spectral analyses demonstrated that individual microphones could establish model spectra. This finding permitted the determination of unique, spatially-detailed directivity contours of spectral band levels over a hemispherical surface. Spectral scaling for the baseline model confirmed that the acoustic intensity scaled with the expected sixth-power of the Mach number. Finally, comparison of spectra and directivity between the baseline gear and the gear with an attached toboggan indicated that the toboggan fairing may be of some value in reducing gear noise over particular frequency ranges.
Humphreys, William M., Jr.↗
Comparison of land skin temperature from a land model, remote sensing, and in situ measurement
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Aihui Wang↗
Sources of Uncertainty in Modeled Land Carbon Storage within and across Three MIPs: Diagnosis with Three New Techniques
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Sha Zhou↗
Evaluation of GIS Technology in Assessing and Modeling Land Management Practices
There is an increasing concern of land owners to protect and maintain healthy and sustainable agroecosystems through the implementation of best management practices (BMP). The objectives of this study were: (1) To develop and evaluate the use of a Geographic Information System (GIS) technology for enhancing field-scale management practices; (2) evaluate the use of 2-dimensional displays of the landscape and (3) define spatial classes of variables from interpretation of geostatistical parameters. Soil samples were collected to a depth of 2 m at 15 cm increments. Existing data from topographic, land use, and soil survey maps of the Winfred Thomas Agricultural Research Station were converted to digital format. Additional soils data which included texture, pH, and organic matter were also generated. The digitized parameters were used to create a multilayered field-scale GIS. Two dimensional (2-D) displays of the parameters were generated using the ARC/INFO software. The spatial distribution of the parameters evaluated in both fields were similar which could be attributed to the similarity in vegetation and surface elevation. The ratio of the nugget to total semivariance, expressed as a percentage, was used to assess the degree of spatial variability. The results indicated that most of the parameters were moderate spatially dependent Biophysical constraint maps were generated from the database layers, and used in multiple combination to visualize results of the BMP. Understanding the spatial relationships of physical and chemical parameters that exists within a field should enable land managers to more effectively implement BMP to ensure a safe and sustainable environment.
Archer, F.↗
2016 International Land Model Benchmarking (ILAMB) Workshop Report
As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections.
earth system models (ESMs)↗
Understanding Changes in Modeled Land Surface Characteristics Prior to Lightning-Initiated Holdover Fire Breakout
Lightning initiated wildfires are only 16% of the total number of wildfires within the United States, but account for 56% of the acreage burned. One of the challenges with lightning-initiated wildfires is their ability to "holdover" which means smolder for up to 2+ weeks before breaking out into a full fledged fire. This work helps characterize the percentage of holdover events due to lightning, and helps quantify changes in the land surface characteristics to help understand trends in soil moisture and vegetation stress that potentially contribute to the fire breaking out into a full wildfire.
wildfire↗
Improving Water Level and Soil Moisture Over Peatlands in a Global Land Modeling System
New model structure for peatlands results in improved skill metrics (without any parameter calibration) Simulated surface soil moisture strongly affected by new model, but reliable soil moisture data lacking for validation.
GEOS-↗