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120 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Developing and testing capabilities for simulating cases with heterogeneous land/water surfaces in a novel atmospheric large eddy simulation code

Large eddy simulations (LES) are the primary computational tool used to simulate high Reynolds number three-dimensional turbulent flows. In the context of earth system sciences, particularly atmospheric science, LES are uniquely able to resolve the scales of atmospheric motion that are key for building process-level understanding of boundary layer turbulence, atmosphere-surface interaction, clouds, and cloud-aerosol-chemistry interaction, and are a core limited-area modeling capability. Increasing demands are being placed on LES code bases as growing high performance computing resources allow LES to address a wider range of scientific problems. In addition, LES are emerging as a source of high-quality machine learning training data. These demands necessitate an agile and extensible code base that allows the model to quickly adapt to emergent needs. However, LES have largely relied on legacy Fortran code bases that lack flexibility. A new, Python-based LES capability called Predicting INteractions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) has been developed as part of the Department of Energy’s Earth System Model Development (ESMD) program area’s Enabling Aerosol-cloud interactions at Global convection-permitting scalES (EAGLES) project. PINACLES was developed from the ground up with a philosophy of maximizing scientific throughput, by attempting to optimize for both model throughput and software extensibility. The initial development of PINACLES delivered a state-of-the-art idealized LES capability solving the non-hydrostatic anelastic equations of motion with doubly periodic boundary conditions and idealized homogenous surface boundary conditions. Here we provide a final report on the outcomes of a fiscal year 2021 Seed Laboratory Directed Research Project that extended PINACLES in two key ways. First, PINACLES was coupled to a state-of-the-art land surface model enabling it to simulate spatially inhomogeneous land-atmosphere interactions that are known to control key atmospheric processes. Second, the dynamical core of PINACLES was modified to permit non-periodic boundary conditions. This model enhancement enables simulation of realistic cases with boundary conditions prescribed from atmospheric reanalysis and enables nested simulations conducted on a hierarchy of computational domains with increasing resolution. Together, these extensions to PINACLES make it a formidable modeling capability and expand its potential application to diverse components of DOE’s atmospheric science portfolio.

42 ENGINEERING↗
DOE OSTI2023

Science Plan for the Deployment of the Third ARM Mobile Facility to the Southeastern United States at the Bankhead National Forest, Alabama (AMF3 BNF)

In 2018, the U.S. Department of Energy (DOE) held a workshop for the Atmospheric Radiation Measurement (ARM) (Mather and Voyles 2013) user facility to discuss critical climate challenges and locations where key ARM Mobile Facility (AMF) observational assets could impact Earth system modeling (ESM). As an outcome, the southeast United States (SE U.S.) was identified as a high-priority region to target climate-process studies that promote a deeper understanding of the climate system and bolster ARM interactions with the community to drive ESM advancement. The DOE ARM user facility is a globally recognized leader in deploying and operating strategically located observation sites around the world for studying the properties of aerosols and clouds and their interaction with radiation, precipitation, and the Earth’s surface. In partnering with the DOE Atmospheric System Research (ASR) program, ARM solicited a multi-agency Site Science Team approach to provide input and close interaction with ARM management towards a successful SE U.S. deployment of the ARM third Mobile Facility (AMF3) (Miller et al. 2016). These efforts included identifying key locations, science drivers and instruments, and measurement strategies to address the wider climate-process needs and ESM improvement. Community input served a vital role in establishing, refining, and informing the relevant drivers and decisions regarding this AMF3 deployment. The team has identified Northern Alabama (N. AL) as regionally representative to unlock the key opportunities that will improve our understanding and model representation of aerosol, cloud, and land-surface processes and their couplings in the SE U.S. A defining aspect of the AMF3 deployment is its commitment to long-term (anticipated five-year) observations to mitigate potential seasonal-to-annual variability that often limits appropriate attribution of phenomena to local or larger-scale processes. The proposed location may leverage nearby surface networks and multi-agency and partner assets to enrich this multi-year deployment. One motivation is to understand the role of spatiotemporal variability (thermodynamic, land-surface) across aspects of the climate system, with our AMF3 team anticipating future demands on characterizing the relationships between local-to-regional cloud development and surface processes across a diverse patchwork of natural, managed, and urban landscapes as found throughout the N. AL regions. The main site targets an intact, representative, forested region – the Bankhead National Forest (BNF) – underscoring further team commitment to regionally important land-atmosphere two-way interactive studies “from the canopy to the clouds”, with enhanced tower instrumentation augmenting traditional ARM capabilities adjacent to this site. Multiple supplemental sites will also be distributed across this region, prioritizing added needs for biodiversity. Anticipated high-priority cloud science themes will target N. AL as a regional SE U.S. hotbed for high-impact weather, convective cloud onset, and shallow-to-deep cloud transitioning. Anticipated aerosol drivers will focus on chemical processes that control the evolution of organic aerosol, the seasonality and spatial distribution of water vapor and particle-phase water, and its role on aerosol optical properties. Anticipated land-atmosphere drivers consider the two-way feedbacks between surface influence on aerosols, clouds, and precipitation properties and the associated radiative impacts on plant physiology and canopy-scale fluxes. Emphasis will include the study of the impact of surface processes on aerosols via precursor emission, and on clouds via moisture flux and thermal development.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Variance and Predictability of Precipitation at Seasonal-to-Interannual Timescales

A series of atmospheric general circulation model (AGCM) simulations, spanning a total of several thousand years, is used to assess the impact of land-surface and ocean boundary conditions on the seasonal-to-interannual variability and predictability of precipitation in a coupled modeling system. In the first half of the analysis, which focuses on precipitation variance, we show that the contributions of ocean, atmosphere, and land processes to this variance can be characterized, to first order, with a simple linear model. This allows a clean separation of the contributions, from which we find: (1) land and ocean processes have essentially different domains of influence, i.e., the amplification of precipitation variance by land-atmosphere feedback is most important outside of the regions (mainly in the tropics) that are most affected by sea surface temperatures; and (2) the strength of land-atmosphere feedback in a given region is largely controlled by the relative availability of energy and water there. In the second half of the analysis, the potential for seasonal-to-interannual predictability of precipitation is quantified under the assumption that all relevant surface boundary conditions (in the ocean and on land) are known perfectly into the future. We find that the chaotic nature of the atmospheric circulation imposes fundamental limits on predictability in many extratropical regions. Associated with this result is an indication that soil moisture initialization or assimilation in a seasonal-to-interannual forecasting system would be beneficial mainly in transition zones between dry and humid regions.

Koster, Randal D.↗
NASA NTRS1999

Simulation of 1986 South China Sea Monsoon with a Regional Climate Model

A Regional Land-Atmosphere Climate Simulation System (RELACS) project is being developed at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes and in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water/energy cycles in the IndoChina/South China Sea (SCS) region. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model. The original MM5 model (without PLACE) includes the option for either a simple slab soil model or a five-layer soil model (MRF) in which the soil moisture availability evolves over time. However, the MM5 soil models do not include the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are precluded. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. In addition, the Penn State/NCAR MM5 atmospheric modeling system has been: (1) coupled to the Goddard Ice Microphysical scheme; (2) coupled to a turbulent kinetic energy (TKE) scheme; (3) modified to ensure cloud budget balance; and (4) incorporated initialization with the Goddard EOS data sets at NASA/Goddard Laboratory for Atmospheres. The improved MM5 with two nested domains (60 and 20 km horizontal resolution) was used to simulate convective activity over IndoChina and the South China Sea, during the monsoon season, from May 6 to May 20, 1986. The model results captured several dominant observed features, such as twin cyclones, a depression system over the Bay of Bengal, strong south-westerly winds over IndoChina before and during the on-set of convection over the SCS, and a vortex over the SCS. Two additional MM5 runs with different land process models, Blackadar and MRF, were performed, and their results are compared to the run with PLACE. The preliminary results indicate that the MM5 results using PLACE and Blackadar are in very good agreement, but the results using MRF do not contain the south-westerly wind over IndoChina prior to the on-set of convection over the SCS.

Tao, W. -K.↗
NASA NTRS2001

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/South China Sea (SCS)/China, North America and South America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) land surface model, PLACE allows for the effect A vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1991 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the South China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗
NASA NTRS2002

Mesoscale Convective Systems in SCSMEX: Simulated by a Regional Climate Model and a Cloud Resolving Model

A Regional Land-Atmosphere Climate Simulation (RELACS) System is being developed and implemented at NASA Goddard Space Flight Center. One of the major goals of RELACS is to use a regional scale model with improved physical processes, in particular land-related processes, to understand the role of the land surface and its interaction with convection and radiation as well as the water and energy cycles in Indo-China/ South China Sea (SCS)/China, N. America and S. America. The Penn State/NCAR MM5 atmospheric modeling system, a state of the art atmospheric numerical model designed to simulate regional weather and climate, has been successfully coupled to the Goddard Parameterization for Land-Atmosphere-C loud Exchange (PLACE) land surface model. PLACE allows for the effects of vegetation, and thus important physical processes such as evapotranspiration and interception are included. The PLACE model incorporates vegetation type and has been shown in international comparisons to accurately predict evapotranspiration and runoff over a wide variety of land surfaces. The coupling of MM5 and PLACE creates a numerical modeling system with the potential to more realistically simulate the atmosphere and land surface processes including land-sea interaction, regional circulations such as monsoons, and flash flood events. RELACS has been used to simulate the onset of the South China Sea Monsoon in 1986, 1997 and 1998. Sensitivity tests on various land surface models, cumulus parameterization schemes (CPSs), sea surface temperature (SST) variations and midlatitude influences have been performed. These tests have indicated that the land surface model has a major impact on the circulation over the S. China Sea. CPSs can effect the precipitation pattern while SST variation can effect the precipitation amounts over both land and ocean. RELACS has also been used to understand the soil-precipitation interaction and feedback associated with a flood event that occurred in and around China's Yantz River during 1998. The exact location (region) of the flooding can be effected by the soil-rainfall feedback. Also, the Goddard Cumulus Ensemble (GCE) model which allows for realistic moist processes as well as explicit interactions between cloud and radiation, and cloud and surface processes will be used to simulate convective systems associated with the onset of the South China Sea Monsoon in 1998. The GCE model also includes the same PLACE and radiation scheme used in the RELACS. A detailed comparison between the results from the GCE model and RELACS will be performed.

Tao, W.-K.↗
NASA NTRS2004

Seasonal-to-Interannual Variability and Land Surface Processes

Atmospheric chaos severely limits the predictability of precipitation on subseasonal to interannual timescales. Hope for accurate long-term precipitation forecasts lies with simulating atmospheric response to components of the Earth system, such as the ocean, that can be predicted beyond a couple of weeks. Indeed, seasonal forecasts centers now rely heavily on forecasts of ocean circulation. Soil moisture, another slow component of the Earth system, is relatively ignored by the operational seasonal forecasting community. It is starting, however, to garner more attention. Soil moisture anomalies can persist for months. Because these anomalies can have a strong impact on evaporation and other surface energy fluxes, and because the atmosphere may respond consistently to anomalies in the surface fluxes, an accurate soil moisture initialization in a forecast system has the potential to provide additional forecast skill. This potential has motivated a number of atmospheric general circulation model (AGCM) studies of soil moisture and its contribution to variability in the climate system. Some of these studies even suggest that in continental midlatitudes during summer, oceanic impacts on precipitation are quite small relative to soil moisture impacts. The model results, though, are strongly model-dependent, with some models showing large impacts and others showing almost none at all. A validation of the model results with observations thus naturally suggests itself, but this is exceedingly difficult. The necessary contemporaneous soil moisture, evaporation, and precipitation measurements at the large scale are virtually non-existent, and even if they did exist, showing statistically that soil moisture affects rainfall would be difficult because the other direction of causality - wherein rainfall affects soil moisture - is unquestionably active and is almost certainly dominant. Nevertheless, joint analyses of observations and AGCM results do reveal some suggestions of land-atmosphere feedback in the observational record, suggestions that soil moisture can affect precipitation over seasonal timescales and across certain large continental areas. The strength of this observed feedback in nature is not large but is still significant enough to be potentially useful, e.g., for forecasts. This talk will address all of these issues. It will begin with a brief overview of land surface modeling in atmospheric models but will then focus on recent research - using both observations and models - into the impact of land surface processes on variability in the climate system.

Koster, Randal↗
NASA NTRS2008

The US CLIVAR Working Group on Drought: A Multi-Model Assessment of the Impact of SST Anomalies on Regional Drought

The US CLIVAR 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. 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. What is the role of the land? What is the role of the different ocean basins, including the impact of EL Nino/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Atlantic Multi-decadal Oscillation (AMO), and warming trends in the global oceans? The runs were done with several global atmospheric models including NASA/NSIPP-1, NCEP/GFS, GFDL/AM2, and NCAR CCM3 and CAM3. In addition, runs were done with the NCEP CFS (coupled atmosphere-ocean) model by employing a novel adjustment technique to nudge the coupled model towards the imposed SST forcing patterns. This talk provides an overview of the experiments and some initial results.

Schubert, Siegfried↗
NASA NTRS2010

Role of Subsurface Physics in the Assimilation of Surface Soil Moisture Observations

Root zone soil moisture controls the land-atmosphere exchange of water and energy and exhibits memory that may be useful for climate prediction at monthly scales. Assimilation of satellite-based surface soil moisture observations into a land surface model is an effective way to estimate large-scale root zone soil moisture. The propagation of surface information into deeper soil layers depends on the model-specific representation of subsurface physics that is used in the assimilation system. In a suite of experiments we assimilate synthetic surface soil moisture observations into four different models (Catchment, Mosaic, Noah and CLM) using the Ensemble Kalman Filter. We demonstrate that identical twin experiments significantly overestimate the information that can be obtained from the assimilation of surface soil moisture observations. The second key result indicates that the potential of surface soil moisture assimilation to improve root zone information is higher when the surface to root zone coupling is stronger. Our experiments also suggest that (faced with unknown true subsurface physics) overestimating surface to root zone coupling in the assimilation system provides more robust skill improvements in the root zone compared with underestimating the coupling. When CLM is excluded from the analysis, the skill improvements from using models with different vertical coupling strengths are comparable for different subsurface truths. Finally, the skill improvements through assimilation were found to be sensitive to the regional climate and soil types.

Reichle, R. H.↗
NASA NTRS2014

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗
NASA NTRS2019

Capturing Connections Between the Water, Energy, and Carbon Cycles with the NASA GEOS

Studying biosphere-atmosphere interactions is complex as water, energy and carbon cycles and their feedback processes have to be integrated. At NASA GMAO, we investigate these interactions with an Earth system model that allows us to explore and quantify relevant feedbacks associated with the exchanges of carbon, water, and energy fluxes within the atmosphere, within the land, and across the land-atmosphere interface. Current biosphere-atmosphere modeling research at GMAO includes a study to understand the relative contributions of land carbon flux variability and atmospheric dynamics to atmospheric CO2 variability in time and space. For this study, we use a unique capability of the NASA GEOS model, a "replay" mode that forces the model to reproduce the weather systems captured by the MERRA-2 reanalysis. Another study investigates the impact of imposed regional drought on land carbon fluxes and on subsequent atmospheric CO2 concentrations, thereby revealing interactions between the water and carbon cycles. Using the new coupled carbon-climate modeling capability, current GMAO efforts at subseasonal-to-seasonal forecasting are now being expanded, at least in research mode, to include forecasts of carbon and phenological state.

Lee, Eunjee↗
NASA NTRSDate not supplied

Understanding Land-Atmosphere Interactions in Agricultural Areas through Improved Modeling and Monitoring of Irrigation

Irrigation increases soil moisture and evapotranspiration, often leading to cooler and more humid conditions over and downwind of irrigated areas. These changes can affect the evolution of the planetary boundary layer and ultimately influence the development of clouds and precipitation. It is for this reason that there has been a push to include irrigation processes in weather and climate models. This presentation will discuss recent efforts to model irrigation impacts in NASA’s land surface and coupled models, via both improved parameterizations and the incorporation of satellite data from platforms such as SMAP, MODIS, and ECOSTRESS. This work underscores the need to consider human water management impacts when analyzing or predicting components of the water and energy cycles, and the critical roles that NASA observations and models play in this assessment.

Patricia Lawston Parker↗