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At least 1,531 records · Page 85

Parametric Mass Modeling for Mars Entry, Descent and Landing System Analysis Study

This paper provides an overview of the parametric mass models used for the Entry, Descent, and Landing Systems Analysis study conducted by NASA in FY2009-2010. The study examined eight unique exploration class architectures that included elements such as a rigid mid-L/D aeroshell, a lifting hypersonic inflatable decelerator, a drag supersonic inflatable decelerator, a lifting supersonic inflatable decelerator implemented with a skirt, and subsonic/supersonic retro-propulsion. Parametric models used in this study relate the component mass to vehicle dimensions and mission key environmental parameters such as maximum deceleration and total heat load. The use of a parametric mass model allows the simultaneous optimization of trajectory and mass sizing parameters.

Samareh, Jamshid A.↗

Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the other uses the daily SPoRT/MODIS GVFs. Finally, snapshots of the LIS land surface fields are used to initialize two different simulations of the NU-WRF, one running with climatology LIS and GVFs, and the other running with experimental LIS and NASA/SPoRT GVFs. In this paper/presentation, case study results will be highlighted in regions with significant differences in GVF between the NCEP climatology and SPoRT product during severe weather episodes.

Case, Jonathan L.↗

Implementing belowground controls on nutrient uptake in ELMv2-SPRUCE improves representation of a boreal peatland ecosystem

Boreal peatlands store 13 %–32 % of the global soil carbon (C) stock, a service dependent on plant-mycorrhizal fungi associations. In these nutrient poor systems, ectomycorrhizal and ericoid mycorrhizal fungi supply up to >80 % of the nutrient requirements of their plant hosts, partly with mined nitrogen (N) and phosphorus (P) from soil organic matter that are otherwise inaccessible to plants. Despite the ecological significance, mycorrhizal associations are only represented in a few land surface or ecosystem models. We modify the peatland branch of version 2 of the Energy Exascale Earth System Land Model (ELMv2-SPRUCE) to replace the default photosynthesis-driven inorganic N and P (NP) uptake process with a more realistic representation of the process via three pathways: (1) direct inorganic NP uptake by uncolonized fine roots, (2) indirect inorganic NP acquisition and (3) indirect NP acquisition from organic sources by mycorrhizal roots. We systematically evaluated the performance of the default and modified models with field observations from a whole ecosystem warming and carbon dioxide fertilization experimental site: Spruce and Peatland Responses Under Changing Environment (SPRUCE), in northern Minnesota, USA. The modified model reduces the underestimation of the growth response of shrubs in the default model to warming from 40 %–80 % to 17 %–35 % and reduces the overall relative absolute error on C fluxes from 1.61 to 1.54 in calibration. Improvements on modeled shrub growths and shrub-moss community net ecosystem exchanges are also seen in validation. The improved growth response of shrubs to warming is accompanied by several-fold increase in direct inorganic NP uptake and decrease in fungal colonization rate. The modified model simulates a smaller magnitude of transition of the ecosystem from C sink to C source under warming due to alleviation of plant nutrient limitation. Equifinality analysis shows the newly added parameters in the modified model can be constrained by the observed C fluxes. Sensitivity analysis shows the newly added parameters have stronger statistical interactions than the preexisting parameters in the default model. Overall, the modified model is an improvement over the default ELMv2-SPRUCE and will be a useful tool for understanding boreal peatland change.

Wang, Yaoping [Oak Ridge National Laboratory (ORNL↗

An Integrated Physics-Based Risk Model for Assessing the Asteroid Threat

Although most asteroids and other near-Earth objects (NEOs) do not pose a threat to Earth’s inhabitants, impacts from objects that are just tens of meters in diameter can cause significant damage if they occur over a populated area. This paper forms the foundation of an effort at NASA Ames Research Center to quantify these risks and identify the greatest risk-driving parameters and uncertainties. An integrated risk model that couples dynamic probabilistic simulations of strike occurrences with physics-based models of NEO impact damage factors has been developed to generate casualty estimates for a range of NEO impact properties. Currently, the model focuses on the risk due to blast overpressure damage from airbursts and impacts on land. The model is first used to reproduce results from established sources, and then is extended to perform sensitivity studies that yield greater insights into risk driving parameters. Results show that meteor strength and entry angle play a role for small to mid-size NEOs, and that accounting for the specific target location significantly affects casualty estimates and dominates the risk. Future work will continue to refine and expand the models to better characterize key impact risk factors, include additional types of threats such as tsunamis and climate effects, and ultimately support assessments of potential asteroid mitigation strategies.

Asteroid Threat↗

Version 8 of the SMAP Level-4 Soil Moisture Data Assimilation Product

The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface (0-5 cm) and root-zone (0-100 cm) soil moisture from April 2015 to present with a mean latency of 2.5 days from the time of observation. The product is based on the assimilation of SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observations-based precipitation forcing. This presentation discusses the improvements in the forthcoming Version 8 of L4_SM, including updates in the precipitation forcing, the Catchment model parameters, and the L-band microwave radiative transfer model (mwRTM). The precipitation observations used in L4_SM Version 8 outside of North America and the high latitudes are from the latest (Version 7) NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement mission (IMERG) products. Moreover, occasionally excessive precipitation rates in earlier versions of L4_SM along certain longitudes in North America were eliminated by a bug fix in the precipitation corrections algorithm. The Catchment model in L4_SM Version 8 uses climatological snow albedo values based on observations from the Moderate Resolution Imaging Spectroradiometer, replacing the look-up table parameterization of earlier versions. Additionally, corrected soil parameters were implemented for a small region in Argentina that had erroneously been classified as peat because of an error in the ancillary soil data. Finally, the mwRTM in L4_SM Version 8 uses the Mironov soil mixing approach and updated values of the L-band scattering albedo, soil roughness, and vegetation opacity climatology obtained from the latest (Release 19) SMAP Level-2 dual-channel soil moisture retrieval product. During the development of L4_SM Version 8, the change in the mwRTM parameterization resulted in a reduced unbiased RMSE of surface soil moisture when verified against in situ measurements. It also reduced the standard deviation of the Tb observation-minus-forecast residuals by ~0.15 K, highlighting the importance of the mwRTM for successful data assimilation. The bug fixes in the precipitation corrections algorithm and the Catchment model soil parameters in the Argentina region result in locally large improvements of the simulated land surface states. In summary, the ongoing refinements of the L4_SM product continue to improve its science quality and performance for global soil moisture monitoring

Rolf Reichle↗

Probabilistic Modeling of Settlement Risk at Land Disposal Facilities - 12304

The long-term reliability of land disposal facility final cover systems - and therefore the overall waste containment - depends on the distortions imposed on these systems by differential settlement/subsidence. The evaluation of differential settlement is challenging because of the heterogeneity of the waste mass (caused by inconsistent compaction, void space distribution, debris-soil mix ratio, waste material stiffness, time-dependent primary compression of the fine-grained soil matrix, long-term creep settlement of the soil matrix and the debris, etc.) at most land disposal facilities. Deterministic approaches to long-term final cover settlement prediction are not able to capture the spatial variability in the waste mass and sub-grade properties which control differential settlement. An alternative, probabilistic solution is to use random fields to model the waste and sub-grade properties. The modeling effort informs the design, construction, operation, and maintenance of land disposal facilities. A probabilistic method to establish design criteria for waste placement and compaction is introduced using the model. Random fields are ideally suited to problems of differential settlement modeling of highly heterogeneous foundations, such as waste. Random fields model the seemingly random spatial distribution of a design parameter, such as compressibility. When used for design, the use of these models prompts the need for probabilistic design criteria. It also allows for a statistical approach to waste placement acceptance criteria. An example design evaluation was performed, illustrating the use of the probabilistic differential settlement simulation methodology to assemble a design guidance chart. The purpose of this design evaluation is to enable the designer to select optimal initial combinations of design slopes and quality control acceptance criteria that yield an acceptable proportion of post-settlement slopes meeting some design minimum. For this specific example, relative density, which can be determined through field measurements, was selected as the field quality control parameter for waste placement. This technique can be extended to include a rigorous performance-based methodology using other parameters (void space criteria, debris-soil mix ratio, pre-loading, etc.). As shown in this example, each parameter range, or sets of parameter ranges can be selected such that they can result in an acceptable, long-term differential settlement according to the probabilistic model. The methodology can also be used to re-evaluate the long-term differential settlement behavior at closed land disposal facilities to identify, if any, problematic facilities so that remedial action (e.g., reinforcement of upper and intermediate waste layers) can be implemented. Considering the inherent spatial variability in waste and earth materials and the need for engineers to apply sound quantitative practices to engineering analysis, it is important to apply the available probabilistic techniques to problems of differential settlement. One such method to implement probability-based differential settlement analyses for the design of landfill final covers has been presented. The design evaluation technique presented is one tool to bridge the gap from deterministic practice to probabilistic practice. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Root Dynamics Mitigate Warm and Dry Biases over the Central United States

The central United States frequently exhibits warm and dry biases in simulations of summertime conditions, a persistent feature that remains unresolved. While previous studies linked these biases to misrepresented surface energy exchanges, the role of belowground processes remains poorly understood. Here, we demonstrate that inadequate representation of root water uptake in land surface models contributes to this bias. Using both offline Noah-MP and coupled WRF-Noah-MP simulations with static and dynamic root water uptake schemes, we show that the inclusion of dynamic root processes reduces 2-m air temperature biases and enhances precipitation, primarily by increasing the rain rate of convective systems. Offline and coupled simulations further reveal that the cooling effects and precipitation increases are amplified through positive land-atmosphere feedback, active only in the coupled model. These findings highlight an important role of root in modulating land-atmosphere interactions and underscore the need to refine root-zone processes to improve regional atmospheric simulations.

Yang, Zhao (ORCID:0000000288027130)↗

Drought Variability over the Conterminous United States for the past century

We examine the drought variability over the Conterminous United States (CONUS) for 1915-2018 using the Noah-MP land-surface model. We examine different model options on drought reconstruction including optional representation of groundwater and dynamic vegetation phenology. Over our 104-year reconstruction period, we identify 12 great droughts that each covered at least 36% of CONUS and lasted for at least 5 months. The great droughts tend to have smaller areas when groundwater and/or dynamic vegetation are included in the model configuration. We detect a small decreasing trend in dry area coverage over CONUS in all configurations. We identify 45 major droughts in the baseline (with a dry area coverage greater than 23.6% of CONUS) that are, on average, somewhat less severe than great droughts. We find that representation of groundwater tends to increase drought duration for both great and major droughts, primarily by leading to earlier drought onset (some due to short-lived recovery from a previous drought) or later demise (groundwater anomalies lag precipitation anomalies). In contrast, representation of dynamic vegetation tends to shorten major droughts duration, primarily due to earlier drought demise ( closed stoma or dead vegetation reduces ET loss during droughts). On a regional basis, the U.S. Southwest (Southeast) has the longest (shortest) major drought durations. Consistent with earlier work, dry area coverage in all subregions except the Southwest has decreased. The effects of groundwater and dynamic vegetation vary regionally due to differences in groundwater depths (hence connectivity with the surface) and vegetation types.

drought↗

Real-Time Assimilation of Goes-Derived Products into A Mesoscale Model and It's Impact on Short-Term (06-36hr) Forecasts from 17 October 1998 through the Present

As the parameterizations of surface energy budgets in regional models have become more complete physically, models have the potential to be much more realistic in simulations of coupling between surface radiation, hydrology, and surface energy transfer. Realizing the importance of properly specifying the surface energy budget, many institutions are using land-surface models to represent the lower boundary forcing associated with biophysical processes and soil hydrology. However, the added degrees of freedom due to inclusion of such land-surface schemes require the specification of additional parameters within the model system such as vegetative resistances, green vegetation fraction, leaf area index, soil physical and hydraulic characteristics, stream flow, runoff, and the vertical distribution of soil moisture. Spatial heterogeneity of these parameters makes correct specification problematic since measurements are not routinely available. A technique has been developed for assimilating GOES-IR skin temperature tendencies, solar insolation, and surface albedo into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. The technique has been successfully employed in a number of mesoscale models in case-study mode. We have taken the next step and developed a study to determine if assimilating these types of data into mesoscale models in real-time can improve short-term (648h) forecasts of temperature, relative humidity, and QPF on a daily basis over relatively large regions. Therefore, an operational modeling/assimilation system has been developed at the GHCC during the past summer that allows us to produce simulations out to 48 hours in a timely manor. The PSU/NCAR MM5 is used in a nested configuration with a 25 km grid covering the southeastern third of the US. The model has been on-line since 1 July 1998 and forecast products are posted on our web site. The satellite algorithms that generate data to be assimilated came on-line 17 October 1998. Quantitative assessment of the forecast quality is performed via traditional verification statistics. In addition, invaluable qualitative information is obtained through close collaboration with several NWSFO's who are using the MM5 products in real-time on a daily basis. The assimilation technique has been applied in an off-line mode since 17 October. Results based on bulk statistical verification of surface meteorology over the entire Southeastern US show that assimilating the GOES-derived land surface tendencies and solar radiation results in a significant reduction of the shelter air temperature and RH bias on a daily basis. In fact, the assimilation technique has produced improved temperature and RH forecasts for 97% of the 100 simulations performed to date. Work is currently underway to determine the sensitivity of the assimilation procedure to the availability of satellite data, length of assimilation period, model initialization, and synoptic-scale meteorological conditions. In addition, results from a detailed energy budget analysis using the Early Eta, our operational MM5, and the assimilation runs will help us to better understand the satellite assimilation the land-surface energy budge. Research during the spring-summer of 1999 will focus on the impact of the assimilation technique during the warm season where it is hypothesized that it can have a positive impact on QPF during conditions of weak synoptic-scale forcing.

Lapenta, William M.↗

The Contaminant Footprint of Landed Spacecraft: Toward an Inventory and Modelling Framework

All spacecraft generate and carry contaminants, i.e., unwanted and potentially harmful material. When a spacecraft lands and operates in vacuum, as onto Earth’s Moon, it introduces contaminants into its environment that may compromise mission science objectives and engineering performance. Contamination may degrade sites of unique value to planetary science or in situ resource utilization. This presentation will identify and compare source terms and transport vectors for contaminants – in particular, organic material – generated by landed spacecraft. An integrated modeling framework for the organic contamination footprint of spacecraft missions will be described and presented.

Gas Dynamics↗

The Aggregate Representation of Terrestrial Land Covers Within Global Climate Models (GCM)

This project had four initial objectives: (1) to create a realistic coupled surface-atmosphere model to investigate the aggregate description of heterogeneous surfaces; (2) to develop a simple heuristic model of surface-atmosphere interactions; (3) using the above models, to test aggregation rules for a variety of realistic cover and meteorological conditions; and (4) to reconcile biosphere-atmosphere transfer scheme (BATS) land covers with those that can be recognized from space; Our progress in meeting these objectives can be summarized as follows. Objective 1: The first objective was achieved in the first year of the project by coupling the Biosphere-Atmosphere Transfer Scheme (BATS) with a proven two-dimensional model of the atmospheric boundary layer. The resulting model, BATS-ABL, is described in detail in a Masters thesis and reported in a paper in the Journal of Hydrology Objective 2: The potential value of the heuristic model was re-evaluated early in the project and a decision was made to focus subsequent research around modeling studies with the BATS-ABL model. The value of using such coupled surface-atmosphere models in this research area was further confirmed by the success of the Tucson Aggregation Workshop. Objective 3: There was excellent progress in using the BATS-ABL model to test aggregation rules for a variety of realistic covers. The foci of attention have been the site of the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) in Kansas and one of the study sites of the Anglo-Brazilian Amazonian Climate Observational Study (ABRACOS) near the city of Manaus, Amazonas, Brazil. These two sites were selected because of the ready availability of relevant field data to validate and initiate the BATS-ABL model. The results of these tests are given in a Masters thesis, and reported in two papers. Objective 4: Progress far exceeded original expectations not only in reconciling BATS land covers with those that can be recognized from space, but also in then applying remotely-sensed land cover data to map aggregate values of BATS parameters for heterogeneous covers and interpreting these parameters in terms of surface-atmosphere exchanges.

Shuttleworth, W. James↗

Flow visualization of vortex interactions in multiple vortex wakes behind aircraft

A flow visualization technique was developed which allows the nature of lift-generated wakes behind aircraft models to be investigated. The technique was applied to models being towed underwater in a ship model basin. Seven different configurations of a small-scale model of a 747 transport aircraft were used to allow observation of typical vortex interactions and merging in multiple vortex wakes. It was established that the motion of the wake vortices is often sensitive to small changes in either wing span loading or model attitude. Landing gear deployement was found to cause a far-field reformation of vorticity behind a model configuration which dissipated concentrated vorticity in the near-field wake. Alleviation of wake vorticity is achievable by configuring the wing span loading to cause the wake vortices to move in paths that result in their interactions and merging. The vortices shed from the horizontal stabilizer always moved down rapidly into the wake and merged with the other vortices, primarily the inboard flap vortices.

Ciffone, D. L.↗

Assimilation of Multi-Frequency, Multi-Polarization Passive Microwave Brightness Temperature Observations in North America over Snow-Covered Regions Using Support Vector Machines

Accurately estimating the mass of water within a snowpack (a.k.a. snow water equivalent, or SWE) across regional or continental scales is a challenge. In order to overcome some of the limitations in traditional SWE retrieval algorithms or radiative transfer-based snow emission models, this study explores the use of a support vector machine (SVM) to merge an advanced land surface model within a radiance emission (i.e., brightness temperature) assimilation framework. The goal of direct radiance assimilation is preferable as it avoids inconsistencies in the use of ancillary data between the assimilation system and the independently-generated geophysical retrieval. The impact of assimilating multiple observations simultaneously at different frequency and polarization combinations is then evaluated via comparisons to state-of-the-art SWE and snow depth products as well as available ground-based measurements across North America for the years 2002 through 2011. It is found that assimilation-derived estimates (relative to estimates without assimilation) tend to better agree with state-of-the-art snow products. In addition, an overall improvement in goodness-of-fit statistics for snow estimates is achieved via assimilation when compared against ground-based snow measurements. In addition, these improvements in snow are shown to translate into improvements in streamflow predictions. Specifically, 11 out of the 13 major snow-dominated basins investigated have improved cumulative runoff estimates versus ground-based discharge measurements compared to the no-assimilation scenario. It is proven that a SVM can serve as an efficient and effective observation operator for a snow mass analysis within a radiance assimilation system.

Xue, Yuan↗

Development and Applications of the Community Ice Sheet Model

The initial goals of the project are: (1) create a model for land ice that includes relevant and necessary dynamics, physical processes, and couplings; and (2) apply that model to say something more substantial about SLR in Lme for IPCC AR5 (AR6?).

58 GEOSCIENCES↗

Issues in using landscape indicators to assess land changes

Landscape indicators, when combined with information about environmental conditions (such as habitat potential, biodiversity, carbon and nutrient cycling, and erosion) and socioeconomic forces, can provide insights about changing ecosystem services. They also provide information about opportunities for improving natural resources management. Landscape indicators rely on data regarding land cover, land management and land functionality. Challenges in using landscape indicators to assess change and effects include (1) measures of land management and attributes that are reliable, robust and consistent for all areas on the Earth do not exist, and thus land cover is more frequently utilized; (2) multiple types of land cover and management are often found within a single landscape and are constantly changing, which complicates measurement and interpretation; and (3) while causal analysis is essential for understanding and interpreting changes in indicator values, the interactions among multiple causes and effects over time make accurate attribution among many drivers of change particularly difficult. Because of the complexity, sheer number of variables, and limitations of empirical data on land changes, models are often used to illustrate and estimate values for landscape indicators, and those models have several problems. Recommendations to improve our ability to assess the effects of changes in land management include refinement of questions to be more consistent with available information and the development of data sets based on systematic measurement over time of spatially explicit land qualities such as carbon and nutrient stocks, water and soil quality, net primary productivity, habitat and biodiversity. Well-defined and consistent land-classification systems that are capable of tracking changes in these and other qualities that matter to society need to be developed and deployed. Because landscapes are so dynamic, it is crucial to develop ways for the scientific community to work together to collect data and develop tools that will enable better analysis of causes and effects and to develop robust management recommendations that will increases land s capacity to meet societal needs in a changing world.

Kline, Keith L↗

Contribution of environmental forcings to US runoff changes for the period 1950–2010

Runoff in the United States is changing, and this study finds that the measured change is dependent on the geographic region and varies seasonally. Specifically, observed annual total runoff had an insignificant increasing trend in the US between 1950 and 2010, but this insignificance was due to regional heterogeneity with both significant and insignificant increases in the eastern, northern, and southern US, and a greater significant decrease in the western US. Trends for seasonal mean runoff also differed across regions. By region, the season with the largest observed trend was autumn for the east (positive), spring for the north (positive), winter for the south (positive), winter for the west (negative), and autumn for the US as a whole (positive). Based on the detection and attribution analysis using gridded WaterWatch runoff observations along with semi-factorial land surface model simulations from the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we found that while the roles of CO 2 concentration, nitrogen deposition, and land use and land cover were inconsistent regionally and seasonally, the effect of climatic variations was detected for all regions and seasons, and the change in runoff could be attributed to climate change in summer and autumn in the south and in autumn in the west. It was also found that the climate-only and historical transient simulations consistently underestimated the runoff trends, possibly due to precipitation bias in the MsTMIP driver or within the models themselves.

54 ENVIRONMENTAL SCIENCES↗

Advances in Land Data Assimilation at the NASA Goddard Space Flight Center

Research in land surface data assimilation has grown rapidly over the last decade. In this presentation we provide a brief overview of key research contributions by the NASA Goddard Space Flight Center (GSFC). The GSFC contributions to land assimilation primarily include the continued development and application of the Land Information System (US) and the ensemble Kalman filter (EnKF). In particular, we have developed a method to generate perturbation fields that are correlated in space, time, and across variables and that permit the flexible modeling of errors in land surface models and observations, along with an adaptive filtering approach that estimates observation and model error input parameters. A percentile-based scaling method that addresses soil moisture biases in model and observational estimates opened the path to the successful application of land data assimilation to satellite retrievals of surface soil moisture. Assimilation of AMSR-E surface soil moisture retrievals into the NASA Catchment model provided superior surface and root zone assimilation products (when validated against in situ measurements and compared to the model estimates or satellite observations alone). The multi-model capabilities of US were used to investigate the role of subsurface physics in the assimilation of surface soil moisture observations. Results indicate that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Building on this experience, GSFC leads the development of the Level 4 Surface and Root-Zone Soil Moisture (L4_SM) product for the planned NASA Soil-Moisture-Active-Passive (SMAP) mission. A key milestone was the design and execution of an Observing System Simulation Experiment that quantified the contribution of soil moisture retrievals to land data assimilation products as a function of retrieval and land model skill and yielded an estimate of the error budget for the SMAP L4_SM product. Terrestrial water storage observations from GRACE satellite system were also successfully assimilated into the NASA Catchment model and provided improved estimates of groundwater variability when compared to the model estimates alone. Moreover, satellite-based land surface temperature (LST) observations from the ISCCP archive were assimilated using a bias estimation module that was specifically designed for LST assimilation. As with soil moisture, LST assimilation provides modest yet statistically significant improvements when compared to the model or satellite observations alone. To achieve the improvement, however, the LST assimilation algorithm must be adapted to the specific formulation of LST in the land model. An improved method for the assimilation of snow cover observations was also developed. Finally, the coupling of LIS to the mesoscale Weather Research and Forecasting (WRF) model enabled investigations into how the sensitivity of land-atmosphere interactions to the specific choice of planetary boundary layer scheme and land surface model varies across surface moisture regimes, and how it can be quantified and evaluated against observations. The on-going development and integration of land assimilation modules into the Land Information System will enable the use of GSFC software with a variety of land models and make it accessible to the research community.

Reichle, Rolf↗