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The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric generator↗

The Mars Science Laboratory (MSL) MMRTG In-Flight: A Power Update

The MSL Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) was fueled on October 28, 2008 by the Department Of Energy (DOE) in preparation for a late 2009 launch. Shortly after, the MSL launch was delayed approximately 2 years until 2011. The fueled MMRTG was placed in storage to await the new date for liftoff. Occasional measurements of the MMRTG's power output were taken and compared with power predictions that pre-dated fueling. An error in the predictive models was quickly recognized and remedied. The resultant predictions, while improved, carried significant uncertainty. This uncertainty did not deter the launch of MSL, but did alter the planned mission on the surface of Mars. Once launched, the MSL spacecraft provided a hi-fidelity telemetry stream measuring the generator's electrical and thermal performance. These data were used to update the predictive models and a new prediction of the performance of the MMRTG on the surface of Mars was run just before Entry, Descent, and Landing (EDL) at Mars. The MSL MMRTG is working extremely well, providing power above predictions and operating within its flight allowable temperature limits. The generator was producing approximately 114 W at the beginning of the surface mission. This paper will elaborate on power modeling for the MSL MMRTG along with a review of some of the data recorded from the MSL cruise to Mars, EDL, and the early days of the surface mission.

thermoelectric↗

Propagation of the MJO and Associated Moist Dynamics, and the Advantages of Enhanced Resolution in NASA’s GEOS-S2S Forecast System

This presentation explores how reliably the NASA’s new subseasonal to seasonal (S2S) forecast system represents the key features of the Madden-Julian Oscillation (MJO). This system is a fully coupled global model that includes the components of atmosphere, ocean, land, and sea ice. The model runs at an approximate spatial resolution of 0.5 degree for the atmosphere and 0.25 degree for the ocean. It employs a two-moment cloud microphysics to enable aerosol-cloud interaction and implements a novel atmosphere-ocean interface layer to enhance the representation of the diurnal warm and cool-skin layer.

Young-Kwon Lim↗

Propagation of the MJO and Associated Moist Dynamics, and the Advantages of Enhanced Resolution in NASA’s GEOS-S2S Forecast System

This presentation explores how reliably the NASA’s new subseasonal to seasonal (S2S) forecast system represents the key features of the Madden-Julian Oscillation (MJO). This system is a fully coupled global model that includes the components of atmosphere, ocean, land, and sea ice. The model runs at an approximate spatial resolution of 0.5 degree for the atmosphere and 0.25 degree for the ocean. It employs a two-moment cloud microphysics to enable aerosol-cloud interaction and implements a novel atmosphere-ocean interface layer to enhance the representation of the diurnal warm and cool-skin layer.

Young-Kwon Lim↗

An Assessment of the Potential Predictability of Drought Over the United States Based on Climate Model Simulations with Specified SST

The USCLIV AR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-l, NCEP/GFS, GFDLlAM2, and NCAR CCM3 and CAM3.5. Specific questions that the runs are designed to address include: What are mechanisms that maintain drought across the seasonal cycle and from one year to the next. To what extent can droughts develop independently of ocean variability due to year-to-year memory that may be inherent to the land. What is the role of the different ocean basins? Here we focus on the potential predictability of drought conditions over the United States. Specific issues addressed include the seasonality and regionality of the signal-to-noise ratios associated with Pacific and Atlantic SST forcing, and the sensitivity of the results to the climatological stationary waves simulated by the different AGCMs.

Schubert, Siegfried↗

Transitioning Enhanced Land Surface Initialization and Model Verification Capabilities to the Kenya Meteorological Department (KMD)

Flooding, severe weather, and drought are key forecasting challenges for the Kenya Meteorological Department (KMD), based in Nairobi, Kenya. Atmospheric processes leading to convection, excessive precipitation and/or prolonged drought can be strongly influenced by land cover, vegetation, and soil moisture content, especially during anomalous conditions and dry/wet seasonal transitions. It is thus important to represent accurately land surface state variables (green vegetation fraction, soil moisture, and soil temperature) in Numerical Weather Prediction (NWP) models. The NASA SERVIR and the Short-term Prediction Research and Transition (SPoRT) programs in Huntsville, AL have established a working partnership with KMD to enhance its regional modeling capabilities. SPoRT and SERVIR are providing experimental land surface initialization datasets and model verification capabilities for capacity building at KMD. To support its forecasting operations, KMD is running experimental configurations of the Weather Research and Forecasting (WRF; Skamarock et al. 2008) model on a 12-km/4-km nested regional domain over eastern Africa, incorporating the land surface datasets provided by NASA SPoRT and SERVIR. SPoRT, SERVIR, and KMD participated in two training sessions in March 2014 and June 2015 to foster the collaboration and use of unique land surface datasets and model verification capabilities. Enhanced regional modeling capabilities have the potential to improve guidance in support of daily operations and high-impact weather and climate outlooks over Eastern Africa. For enhanced land-surface initialization, the NASA Land Information System (LIS) is run over Eastern Africa at ~3-km resolution, providing real-time land surface initialization data in place of interpolated global model soil moisture and temperature data available at coarser resolutions. Additionally, real-time green vegetation fraction (GVF) composites from the Suomi-NPP VIIRS instrument is being incorporated into the KMD-WRF runs, using the product generated by NOAA/NESDIS. Model verification capabilities are also being transitioned to KMD using NCAR's Model *Corresponding author address: Jonathan Case, ENSCO, Inc., 320 Sparkman Dr., Room 3008, Huntsville, AL, 35805. Email: Jonathan.Case-1@nasa.gov Evaluation Tools (MET; Brown et al. 2009) software in conjunction with a SPoRT-developed scripting package, in order to quantify and compare errors in simulated temperature, moisture and precipitation in the experimental WRF model simulations. This extended abstract and accompanying presentation summarizes the efforts and training done to date to support this unique regional modeling initiative at KMD. To honor the memory of Dr. Peter J. Lamb and his extensive efforts in bolstering weather and climate science and capacity-building in Africa, we offer this contribution to the special Peter J. Lamb symposium. The remainder of this extended abstract is organized as follows. The collaborating international organizations involved in the project are presented in Section 2. Background information on the unique land surface input datasets is presented in Section 3. The hands-on training sessions from March 2014 and June 2015 are described in Section 4. Sample experimental WRF output and verification from the June 2015 training are given in Section 5. A summary is given in Section 6, followed by Acknowledgements and References.

land surface modeling↗

Expansion of the Real-time Sport-land Information System for NOAA / National Weather Service Situational Awareness and Local Modeling Applications

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, AL (Jedlovec 2013; Ralph et al. 2013; Merceret et al. 2013) is running a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework (hereafter referred to as the "SPoRT-LIS"). Output from the real-time SPoRT-LIS is used for (1) initializing land surface variables for local modeling applications, and (2) displaying in decision support systems for situational awareness and drought monitoring at select NOAA/National Weather Service (NWS) partner offices. The SPoRT-LIS is currently run over a domain covering the southeastern half of the Continental United States (CONUS), with an additional experimental real-time run over the entire CONUS and surrounding portions of southern Canada and northern Mexico. The experimental CONUS run incorporates hourly quantitative precipitation estimation (QPE) from the National Severe Storms Laboratory Multi- Radar Multi-Sensor (MRMS) product (Zhang et al. 2011, 2014), which will be transitioned into operations at the National Centers for Environmental Prediction (NCEP) in Fall 2014. This paper describes the current and experimental SPoRT-LIS configurations, and documents some of the limitations still remaining through the advent of MRMS precipitation analyses in the SPoRT-LIS land surface model (LSM) simulations. Section 2 gives background information on the NASA LIS and describes the realtime SPoRT-LIS configurations being compared. Section 3 presents recent work done to develop a training module on situational awareness applications of real-time SPoRT-LIS output. Comparisons between output from the two SPoRT-LIS runs are shown in Section 4, including a documentation of issues encountered in using the MRMS precipitation dataset. A summary and future work in given in Section 5, followed by acknowledgements and references.

Case, Jonathan L.↗

Comparison of Four Precipitation Forcing Datasets in Land Information System Simulations over the Continental U.S.

This paper and poster presented a description of the current real-time SPoRT-LIS run over the southeastern CONUS to provide high-resolution, land surface initialization grids for local numerical model forecasts at NWS forecast offices. The LIS hourly output also offers a supplemental dataset to aid in situational awareness for convective initiation forecasts, assessing flood potential, and monitoring drought at fine scales. It is a goal of SPoRT and several NWS forecast offices to expand the LIS to an entire CONUS domain, so that LIS output can be utilized by NWS Western Region offices, among others. To make this expansion cleanly so as to provide high-quality land surface output, SPoRT tested new precipitation datasets in LIS as an alternative forcing dataset to the current radar+gauge Stage IV product. Similar to the Stage IV product, the NMQ product showed comparable patterns of precipitation and soil moisture distribution, but suffered from radar gaps in the intermountain West, and incorrectly set values to zero instead of missing in the data-void regions of Mexico and Canada. The other dataset tested was the next-generation GOES-R QPE algorithm, which experienced a high bias in both coverage and intensity of accumulated precipitation relative to the control (NLDAS2), Stage IV, and NMQ simulations. The resulting root zone soil moisture was substantially higher in most areas.

Case, Jonathan L.↗

Use of MODIS Land and Sea Surface Temperatures to Initialize Mesoscale Models

As computer power continues to increase, mesoscale models are initialized at all hours of the day and continue to be run at higher and higher spatial resolutions. As a result, initializing land surface temperature can be problematic. The majority of research-based models are initialized at 00 and 12 UTC when upper air observations and reanalysis fields are available. The landsea surface temperatures are then set equal to the two-meter air temperature produced by the preprocessor analysis system. This particular procedure might be valid in the early morning hours just prior to sunrise, but it becomes less valid during the remainder of the diurnal cycle. Operational models, such as the Rapid Update Cycle run at the National Centers for Environmental Prediction (NCEP), are initialized every hour on a daily basis. This presents a unique challenge to the initial specification of the land temperature, especially during the first several hours of the solar heating cycle when land and overlying air temperatures are far from being the same. Another issue that needs to be addressed is the spatial variability of land surface temperature. By early next year, the NCEP operational Eta model will be employed at 8 km resolution. Methods to accurately specify the initial land surface temperature at such high resolution need to be explored. This paper presents the results of using data from the NASA Moderate Imaging Sensor aboard the TERRA Satellite to initialize land and sea surface temperatures within the Pennsylvania State University/National Center for Atmospheric Research (PSU/NCAR) 5'th generation Mesoscale Model (MM5). We have simulated a northern Gulf Coast sea breeze case to demonstrate the utility of using the MODIS data to initialize both the land and sea surface temperature fields. Model grid configurations of 12-, 4-, and l-km are employed.

Arnold, James E.↗

Is land use producing robust signals in future projections from Earth system models, all else being equal?

Abstract We use six Earth system models (ESMs) run under SSP3-7.0, a scenario characterized by a relatively large land use change (LUC) over the 21st century, and under a variant of the same scenario where a significantly different pattern of LUC, taken from SSP1-2.6, was used, all else being equal. Our goal is to identify changes in climate extremes between the two scenarios that are statistically significant and robust across the ESMs. The motivation for this study is to test a long-held assumption of the shared socio-economic pathway-representative concentration pathway (SSP-RCP) scenario framework: that the signal from LUC can be safely disregarded when pairing different SSPs to the compatible RCPs, where compatibility only considers global radiative forcing, predominantly determined by well-mixed greenhouse gasses emissions. We analyze extremes of daily minimum and maximum temperatures and precipitation, after fitting non-stationary generalized extreme value distributions in a way that borrows strength along the length of the simulation (2015–2100) and across initial condition ensembles. We consider changes in the 20 year return levels (RL20s) of these metrics by 2100, and focus on eight locations where LUC is large within each scenario, and strongly differs between scenarios, averaging the RL20s over a neighborhood characterized by the same LUC to enhance the signal to noise. We find that precipitation extremes do not show significant differences attributable to LUC differences. For temperature extremes (cold and hot) results are mixed, with some location-index combination showing significant results for some of the ESMs but not all, and not many coherent changes appearing for indices across regions, or regions across indices. These ESMs are representative of what is typically adopted as the source of climate information for impact studies, when the SSP-RCP framework is put to use. Overall, our analysis suggests that the hypothesis to pair SSPs to RCPs in a flexible fashion is overall defensible. However, the appearance of some coherence in a few locations and for some indices invites further investigation.

54 ENVIRONMENTAL SCIENCES↗

Landing performance of an air cushion landing system installed on a 1/10-scale dynamic model on the C-8 Buffalo airplane

An experimental study was conducted to evaluate the landing behavior of a 1/10-scale dynamic model of the C-8 Buffalo airplane equipped with an air-cushion landing system (ACLS) on a variety of surfaces including both calm and rough water and a smooth hard surface. Taxi runs were made on the hard surface over several obstacles. Landings were made with the model at various pitch and roll attitudes and vertical velocities and at one nominal horizontal velocity. Data from the landings include time histories of the trunk and air-cushion pressures and accelerations at selected locations on the model.

Thompson, W. C.↗

Representation of atmosphere-induced heterogeneity in land–atmosphere interactions in E3SM–MMFv2

In the Energy Exascale Earth System Model (E3SM) Multi-scale Modeling Framework (MMF), where parameterizations of convection and turbulence are replaced by a 2-D cloud-resolving model (CRM), there are multiple options to represent land–atmosphere interactions. Here, we propose three different coupling strategies, namely the (1) coupling of a single land surface model to the global grid (MMF), (2) coupling a single land copy directly to the embedded CRM (SFLX2CRM), and (3) coupling a single copy of land model to each column of the CRM grid (MAML). In the MAML (Multi-Atmosphere Multi-Land) framework, a land model is coupled to CRM at the CRM-grid scale by coupling an individual copy of a land model to each CRM grid. Therefore, we can represent intra-CRM heterogeneity in the land–atmosphere interaction processes. There are 5-year global simulations run using these three coupling strategies, and we find some regional differences but overall small changes with respect to whether a land model is coupled to CRM or a global atmosphere. In MAML, the spatial heterogeneity within CRM induces stronger turbulence, which leads to the changes in soil moisture, surface heat fluxes, and precipitation. However, the differences in the MAML from the other two cases are rather weak, suggesting that the impact of using MAML does not justify the increase in cost.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

An Integrated Snow Radiance and Snow Physics Modeling Framework for Cold Land Surface Modeling

Recent developments in forward radiative transfer modeling and physical land surface modeling are converging to allow the assembly of an integrated snow/cold lands modeling framework for land surface modeling and data assimilation applications. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. Together these form a flexible framework for self-consistent remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. Each element of this framework is modular so the choice of element can be tailored to match the emphasis of a particular study. For example, within our framework, four choices of a FRTM are available to simulate the brightness temperature of snow: Two models are available to model the physical evolution of the snowpack and underlying soil, and two models are available to handle the water/energy balance at the land surface. Since the framework is modular, other models-physical or statistical--can be accommodated, too. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster at the NASA Goddard Space Flight Center. The advantages of such an integrated modular framework built on the LIS will be described through examples-e.g., studies to analyze snow field experiment observations, and simulations of future satellite missions for snow and cold land processes.

Kim, Edward J.↗

Topographic Controls on the Distribution of Summer Monsoon Precipitation over South Asia

In this work, we use a high-resolution (9 km) one-way nested regional climate modeling framework to systematically evaluate individual and aggregate roles of various components of topography in the precipitation distribution during South Asian Summer Monsoon (SASM). While it is not the arrival but the north-northwestward extent of summer monsoon precipitation that is regulated by the presence of elevated surfaces in South Asia, both the thermal and mechanical topographic forcing play a role. Topography not only provides mechanical uplifting and prevents dry air entrainment, it also helps regulate the strength of upper level anticyclone and tropical easterly jet, all of which are necessary to sustain a conducive environment for monsoon precipitation in the South Asian summer. In turn, precipitation feedbacks positively by accelerating the tropospheric diabatic warming through atmospheric latent heating and by maintaining the moisture supply through local recycling. Modifications in the topography, particularly the removal of the Tibetan Plateau, substantially modulates the moist flow in the lower troposphere and the anticyclonic circulation in the upper troposphere to an extent that the northern branch of SASM becomes substantially weaker. These changes give way to negative precipitation anomalies and eventually to an environment where the cycle of feedbacks that runs the process of monsoon progression over land becomes inefficient. The design of topographic modification experiments can influence precipitation response; therefore, we advise caution in the interpretation of these and previously reported results.

54 ENVIRONMENTAL SCIENCES↗

An Assessment of the Potential Predictability of Interannual and Decadal Variability Based on Climate Model Simulations with Specified SST

The USCLIVAR working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land-atmosphere feedbacks on regional drought. The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3.5. Here we focus on the potential predictability associated with the leading patterns of inter-annual and decadal Pacific SST variability. Specific issues addressed include the nature of the seasonality and regionality of the signal, the noise, and the signal-to-noise ratios, as well as the dependence of the results on the models.

Schubert, Siegfried↗

Overview of NASA's Carbon Monitoring System Flux-Pilot Project

NASA's space-based observations of physical, chemical and biological parameters in the Earth System along with state-of-the-art modeling capabilities provide unique capabilities for analyses of the carbon cycle. The Carbon Monitoring System is developing an exploratory framework for detecting carbon in the environment and its changes, with a view towards contributing to national and international monitoring activities. The Flux-Pilot Project aims to provide a unified view of land-atmosphere and ocean-atmosphere carbon exchange, using observation-constrained models. Central to the project is the application of NASA's satellite observations (especially MODIS), the ACOS retrievals of the JAXA-GOSAT observations, and the "MERRA" meteorological reanalysis produced with GEOS-S. With a primary objective of estimating uncertainty in computed fluxes, two land- and two ocean-systems are run for 2009-2010 and compared with existing flux estimates. An transport model is used to evaluate simulated CO2 concentrations with in-situ and space-based observations, in order to assess the realism of the fluxes and how uncertainties in fluxes propagate into atmospheric concentrations that can be more readily evaluated. Finally, the atmospheric partial CO2 columns observed from space are inverted to give new estimates of surface fluxes, which are evaluated using the bottom-up estimates and independent datasets. The focus of this presentation will be on the science goals and current achievements of the pilot project, with emphasis on how policy-relevant questions help focus the scientific direction. Examples include the issue of what spatio-temporal resolution of fluxes can be detected from polar-orbiting satellites and whether it is possible to use space-based observations to separate contributions to atmospheric concentrations of (say) fossil-fuel and biological activity

Pawson, Steven↗

Synergies Between Venus and Exoplanetary Observations

• How can Venus help inform Exoplanetary studies? 1. Volatile Cycling & Weathering on Venus Through Time (Foley, Höning) a) Weathering on Venus : surface water, land area, tectonic state i. Evidence for running water in tesserae? Khawja et al. 2020 ii. D/H Ratio? Hoffman et al. 1980 b) Volcanism & Outgassing: Is SO2 a proxy for on-going volcanism? c) Volatile in-gassing: Does subduction occur today? (Davaille et al.) 2. Venus’ Magnetic Field (O’Rourke) a) Is Venus’ slower interior cooling responsible for lack of magnetic field? b) Lack of a late energetic impactor (Jacobsson et al.): stable density gradients? c) Is mass a factor: larger super-Venus/Earth more likely to have magnetic field?

Exoplanets↗

Super Resolution Image Enhancement for a Flash Lidar: Back Projection Method

In this paper a new image processing technique for flash LIDAR data is presented as a potential tool to enable safe and precise spacecraft landings in future robotic or crewed lunar and planetary missions. Flash LIDARs can generate, in real-time, range data that can be interpreted as a 3-dimensional (3-D) image and transformed into a corresponding digital elevation map (DEM). The NASA Autonomous Landing and Hazard Avoidance (ALHAT) project is capitalizing on this new technology by developing, testing and analyzing flash LIDARs to detect hazardous terrain features such as craters, rocks, and slopes during the descent phase of spacecraft landings. Using a flash LIDAR for this application looks very promising, however through theoretical and simulation analysis the ALHAT team has determined that a single frame, or mosaic, of flash LIDAR data may not be sufficient to build a landing site DEM with acceptable spatial resolution, precision, size, or for a mosaic, in time, to meet current system requirements. One way to overcome this potential limitation is by enhancing the flash LIDAR output images. We propose a new super-resolution algorithm applicable to flash LIDAR range data that will create a DEM with sufficient accuracy, precision and size to meet current ALHAT requirements. The performance of our super-resolution algorithm is analyzed by processing data generated during a series of simulation runs by a high fidelity model of a flash LIDAR imaging a high resolution synthetic lunar elevation map. The flash LIDAR model is attached to a simulated spacecraft by a gimbal that points the LIDAR to a target landing site. For each simulation run, a sequence of flash LIDAR frames is recorded and processed as the spacecraft descends toward the landing site. Each run has a different trajectory profile with varying LIDAR look angles of the terrain. We process the output LIDAR frames using our SR algorithm and the results show that the achieved level of accuracy and precision of the SR generated landing site DEM is more than adequate for detecting hazardous terrain features and identifying safe areas.

Bulyshev, Alexander↗