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NASA NTRS2000

Atlas of Seasonal Means Simulated by the NSIPP 1 Atmospheric GCM

This atlas documents the climate characteristics of version 1 of the NASA Seasonal-to-Interannual Prediction Project (NSIPP) Atmospheric General Circulation Model (AGCM). The AGCM includes an interactive land model (the Mosaic scheme), and is part of the NSIPP coupled atmosphere-land-ocean model. The results presented here are based on a 20-year (December 1979-November 1999) "ANIIP-style" integration of the AGCM in which the monthly-mean sea-surface temperature and sea ice are specified from observations. The climate characteristics of the AGCM are compared with the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasting (ECMWF) reanalyses. Other verification data include Special Sensor Microwave/Imager (SSNM) total precipitable water, the Xie-Arkin estimates of precipitation, and Earth Radiation Budget Experiment (ERBE) measurements of short and long wave radiation. The atlas is organized by season. The basic quantities include seasonal mean global maps and zonal and vertical averages of circulation, variance/covariance statistics, and selected physics quantities.

Suarez, Max J.↗

NASA NTRS2003

The NASA Short-term Prediction Research and Transition (SPoRT) Center: A Collaborative Model for Accelerating Research into Operations

The NASA Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama was created to accelerate the infusion of NASA earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The principal focus of experimental products is on the regional scale with an emphasis on forecast improvements on a time scale of 0-24 hours. The SPoRT Center research is aligned with the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues ranging from convective initiation to 24-hr quantitative precipitation forecasting. The SPoRT Center, together with its other interagency partners, universities, and the NASA/NOAA Joint Center for Satellite Data Assimilation, provides a means and a process to effectively transition NASA Earth Science Enterprise observations and technology to National Weather Service operations and decision makers at both the global/national and regional scales. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future.

Goodman, S. J.↗

NASA NTRS2003

Global Changes of the Water Cycle Intensity

In this study, we evaluate numerical simulations of the twentieth century climate, focusing on the changes in the intensity of the global water cycle. A new diagnostic of atmospheric water vapor cycling rate is developed and employed, that relies on constituent tracers predicted at the model time step. This diagnostic is compared to a simplified traditional calculation of cycling rate, based on monthly averages of precipitation and total water content. The mean sensitivity of both diagnostics to variations in climate forcing is comparable. However, the new diagnostic produces systematically larger values and more variability than the traditional average approach. Climate simulations were performed using SSTs of the early (1902-1921) and late (1979- 1998) twentieth century along with the appropriate C02 forcing. In general, the increase of global precipitation with the increases in SST that occurred between the early and late twentieth century is small. However, an increase of atmospheric temperature leads to a systematic increase in total precipitable water. As a result, the residence time of water in the atmosphere increased, indicating a reduction of the global cycling rate. This result was explored further using a number of 50-year climate simulations from different models forced with observed SST. The anomalies and trends in the cycling rate and hydrologic variables of different GCMs are remarkably similar. The global annual anomalies of precipitation show a significant upward trend related to the upward trend of surface temperature, during the latter half of the twentieth century. While this implies an increase in the hydrologic cycle intensity, a concomitant increase of total precipitable water again leads to a decrease in the calculated global cycling rate. An analysis of the land/sea differences shows that the simulated precipitation over land has a decreasing trend while the oceanic precipitation has an upward trend consistent with previous studies and the available observations. The decreasing continental trend in precipitation is located primarily over tropical land regions, with some other regions, such as North America experiencing an increasing trend. Precipitation trends are diagnosed further using the water tracers to delineate the precipitation that occurs because of continental evaporation, as opposed to oceanic evaporation. These diagnostics show that over global land areas, the recycling of continental moisture is decreasing in time. However, the recycling changes are not spatially uniform so that some regions, most notably over the United States, experience continental recycling of water that increases in time.

Bosilovich, Michael G.↗

NASA NTRS2004

Improving the Transition of Earth Satellite Observations from Research to Operations

There are significant gaps between the observations, models, and decision support tools that make use of new data. These challenges include: 1) Decreasing the time to incorporate new satellite data into operational forecast assimilation systems, 2) Blending in-situ and satellite observing systems to produce the most accurate and comprehensive data products and assessments, 3) Accelerating the transition from research to applications through national test beds, field campaigns, and pilot demonstrations, and 4) Developing the partnerships and organizational structures to effectively transition new technology into operations. At the Short-term Prediction Research and Transition (SPORT) Center in Huntsville, Alabama, a NASA-NOAA-University collaboration has been developed to accelerate the infusion of NASA Earth science observations, data assimilation and modeling research into NWS forecast operations and decision-making. The SPoRT Center research focus is to improve forecasts through new observation capability and the regional prediction objectives of the US Weather Research Program dealing with 0-1 day forecast issues such as convective initiation and 24-hr quantitative precipitation forecasting. The near real-time availability of high-resolution experimental products of the atmosphere, land, and ocean from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Infrared Spectroradiometer (AIRS), and lightning mapping systems provide an opportunity for science and algorithm risk reduction, and for application assessment prior to planned observations from the next generation of operational low Earth orbiting and geostationary Earth orbiting satellites. This paper describes the process for the transition of experimental products into forecast operations, current products undergoing assessment by forecasters, and plans for the future. The SPoRT Web page is at (http://www.ghcc.msfc.nasa.gov/sport).

Goodman, Steven J.↗

NASA NTRS2005

Challenges of cloud-prone and rainy areas remote sensing

Provide, from space, the first global survey of cloud profiles (height, thickness) and cloud physical properties (water, ice, precipitation) needed to evaluate and improve the way clouds, moisture and energy are represented in global models used for weather forecasts and climate prediction.

remote sensing↗

NASA NTRS2007

Solutions Network Formulation Report. The Potential Contributions of the Global Precipitation Measurement Mission to Estuary Management in Acadia National Park

This candidate solution suggests the use of GPM precipitation observations to enhance the Acadia National Park NLERDSS. Simulated GPM data should provide measurements that would enable analysis of how precipitation affects runoff and nutrient load in the park?s wetlands. This solution benefits society by aiding park and resource managers in making predictions based on hypothetical changes and in identifying effective mitigation scenarios. This solution supports the Coastal Management, Water Management, and Ecological Forecasting National Applications.

Anderson, Daniel↗

NASA NTRS2012

Impact of Calibrated Land Surface Model Parameters on the Accuracy and Uncertainty of Land-Atmosphere Coupling in WRF Simulations

Land-atmosphere (L-A) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface temperature and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. Recent efforts to quantify the strength of L-A coupling in prediction models have produced diagnostics that integrate across both the land and PBL components of the system. In this study, we examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled WRF forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. Southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through the use of a new optimization and uncertainty estimation module in NASA's Land Information System (LIS-OPT/UE), whereby parameter sets are calibrated in the Noah land surface model and classified according to a land cover and soil type mapping of the observation sites to the full model domain. The impact of calibrated parameters on the a) spinup of the land surface used as initial conditions, and b) heat and moisture states and fluxes of the coupled WRF simulations are then assessed in terms of ambient weather and land-atmosphere coupling along with measures of uncertainty propagation into the forecasts. In addition, the sensitivity of this approach to the period of calibration (dry, wet, average) is investigated. Finally, tradeoffs of computational tractability and scientific validity, and the potential for combining this approach with satellite remote sensing data are also discussed.

Santanello, Joseph A., Jr.↗

NASA NTRS2017

Short-Term Forecasts Using NU-WRF for the Winter Olympics 2018

The NASA Unified-Weather Research and Forecasting model (NU-WRF) will be included for testing and evaluation in the forecast demonstration project (FDP) of the International Collaborative Experiment −PyeongChang 2018 Olympic and Paralympic (ICE-POP) Winter Games. An international array of radar and supporting ground based observations together with various forecast and now-cast models will be operational during ICE-POP. In conjunction with personnel from NASA's Goddard Space Flight Center, the NASA Short-term Prediction Research and Transition (SPoRT) Center is developing benchmark simulations for a real-time NU-WRF configuration to run during the FDP. ICE-POP observational datasets will be used to validate model simulations and investigate improved model physics and performance for prediction of snow events during the research phase (RDP) of the project The NU-WRF model simulations will also support NASA Global Precipitation Measurement (GPM) Mission ground-validation physical and direct validation activities in relation to verifying, testing and improving satellite-based snowfall retrieval algorithms over complex terrain.

forecasting↗

NASA NTRS2018

A Satellite-Based Estimate of Combustion Aerosol Cloud Microphysical Effects over the Arctic Ocean

Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (~10W/sq.m) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

Zamora, Lauren M.↗

DOE OSTI2023

Uncertainty in Simulating Twentieth Century West African Precipitation Trends: The Role of Anthropogenic Aerosol Emissions

Anthropogenic aerosol emissions from North America and Europe have strong effects on the decadal variability of the West African monsoon (WAM). Anthropogenic aerosol effective radiative forcing is model dependent, but the impact of such uncertainty on the simulation of long-term WAM variability is unknown. We use an ensemble of simulations with HadGEM3-GC3.1 that span the most recent estimates in simulated anthropogenic aerosol effective radiative forcing. We show that uncertainty in anthropogenic aerosol radiative forcing leads to significant uncertainty at simulating multi-decadal trends in West African precipitation. At the large scale, larger forcing leads to a larger decrease in the interhemispheric temperature gradients, in temperature over both the North Atlantic Ocean and northern Sahara. There are also differences in dynamic changes specific to the WAM (locations of the Saharan heat low and African Easterly Jet, of the strength of the West African westerly jet, and of African Easterly Wave activity). We also assess effects on monsoon precipitation characteristics and temperature. We show that larger aerosol forcing results in a decrease of the number of rainy days and of heavy and extreme precipitation events and warm spells. However, simulated changes in onset and demise dates do not appear to be sensitive to the magnitude of aerosol forcing. Our results demonstrate the importance of reducing the uncertainty in anthropogenic aerosol forcing for understanding and predicting multi-decadal variability in the WAM.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Fine-root dynamics vary with soil depth and precipitation in a lown-utrient tropical forest in the Central Amazonia

A common assumption in tropical ecology is that root systems respond rapidly to climatic cues but that most of that response is limited to the uppermost layer of the soil, with relatively limited changes in deeper layers. However, this assumption has not been tested directly, preventing models from accurately predicting the response of tropical forests to environmental change. We measured seasonal dynamics of fine roots in a Central Amazonia mature forest using minirhizotrons to 90 cm depth, which were calibrated with fine roots extracted from soil cores. Root productivity and mortality in superficial soil layers were positively correlated with precipitation, whereas root standing length was greater during the dry periods at the deeper layers. Contrary to historical assumptions, a large fraction of fine-root standing biomass (46%) and productivity (41%) were found in soil layers deeper than 30 cm. Furthermore, root turnover decreased linearly with soil depth. Our findings demonstrate a strong relationship between fine-root dynamics and precipitation regimes in Central Amazonia. Our results also emphasize the importance of deep roots for accurate estimates of primary productivity and the interaction between roots and carbon, water, and nutrients.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

On High-Fluence Irradiation Hardening of Nine RPV Surveillance Steels in the UCSB ATR-2 Experiment: Implications for Extended-Life Embrittlement Predictions

Nine archival reactor pressure vessel (RPV) surveillance steels from commercial nuclear power plants were irradiated in the University of California, Santa Barbara Advanced Test Reactor 2 (ATR-2) experiment to evaluate irradiation embrittlement under low-flux surveillance capsule versus higher flux test reactor (ATR-2) conditions. The postirradiation measurements of irradiation hardening, measured as increases in yield stress (Δσy), and corresponding conversions of Δσy to Charpy V-notch 41-J transition temperature shifts (ΔTc) are compared with various embrittlement trend curve (ETC) model predictions for the nine steels. Tensile and converted shear punch and microhardness measurements of Δσy generally show a continuing increase between intermediate and high ATR-2 fluences. The Eason-Odette-Nanstad-Yamamoto and ASTM E900 ETC models underpredict embrittlement at the ATR-2 irradiation condition: irradiation temperature (Ti) of 292°C, neutron fluence (ϕt) of 1.4 × 1020 n/cm2 (E > 1 MeV), and neutron flux (ϕ) of 3.68 × 1012 n/cm2-s. On average, the French FIS and Japanese JAEC ETCs slightly overpredict the ATR-2 data. The increase in Δσy with higher fluence is primarily due to Ni-Mn-Si precipitates, which slowly evolve in both nearly copper-free and copper-bearing steels. Finally, a new Odette-Wells-Almirall-Yamamoto embrittlement model is shown that yields good predictions for the nine steels at high fluences (ϕt > 5.5 × 1019 n/cm2).

Nanstad, Randy K.↗

DOE OSTI2023

On High-Fluence Irradiation Hardening of Nine RPV Surveillance Steels in the UCSB ATR-2 Experiment: Implications for Extended-Life Embrittlement Predictions

Nanstad, Randy↗

NASA NTRS1990

Potential evapotranspiration and the likelihood of future drought

The possibility that the greenhouse warming predicted by the GISS general-circulation model and other GCMs could lead to severe droughts is investigated by means of numerical simulations, with a focus on the role of potential evapotranspiration E(P). The relationships between precipitation (P), E(P), soil moisture, and vegetation changes in GCMs are discussed; the empirically derived Palmer drought-intensity index and a new supply-demand index (SDDI) based on changes in P - E(P) are described; and simulation results for the period 1960-2060 are presented in extensive tables, graphs, and computer-generated color maps. Simulations with both drought indices predict increasing drought frequency for the U.S., with effects already apparent in the 1990s and a 50-percent frequency of severe droughts by the 2050s. Analyses of arid periods during the Mesozoic and Cenozoic are shown to support the use of the SDDI in GCM drought prediction.

Rind, D.↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 kilometers, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-kilometer scales are resolved in horizontal domains as large as 10,000 kilometers in two dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2005

A New Approach to Using a Cloud-resolving Model to Study the Interactions Between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as l0,OOO km in two-dimensions, and 1,OOO x 1,OOO km2 in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗

NASA NTRS2000

A Plan for Measuring Climatic Scale Global Precipitation Variability: The Global Precipitation Mission

The outstanding success of the Tropical Rainfall Measuring Mission (TRMM) stemmed from a near flawless launch and deployment, a highly successful measurement campaign, achievement of all original scientific objectives before the mission life had ended, and the accomplishment of a number of unanticipated but important additional scientific advances. This success and the realization that satellite rainfall datasets are now a foremost tool in the understanding of decadal climate variability has helped motivate a comprehensive global rainfall measuring mission, called 'The Global Precipitation Mission' (GPM). The intent of this mission is to address looming scientific questions arising in the context of global climate-water cycle interactions, hydrometeorology, weather prediction, the global carbon budget, and atmosphere-biosphere-cryosphere chemistry. This paper addresses the status of that mission currently planed for launch in the early 2007 time frame. The GPM design involves a nine-member satellite constellation, one of which will be an advanced TRMM-like 'core' satellite carrying a dual-frequency Ku-Ka band radar (df-PR) and a TMI-like radiometer. The other eight members of the constellation can be considered drones to the core satellite, each carrying some type of passive microwave radiometer measuring across the 10.7-85 GHz frequency range, likely based on both real and synthetic aperture antenna technology and to include a combination of new lightweight dedicated GPM drones and both co-existing operational and experimental satellites carrying passive microwave radiometers (i.e., SSM/l, AMSR, etc.). The constellation is designed to provide a minimum of three-hour sampling at any spot on the globe using sun-synchronous orbit architecture, with the core satellite providing relevant measurements on internal cloud precipitation microphysical processes. The core satellite also enables 'training' and 'calibration' of the drone retrieval process. Additional information is contained in the original extended abstract.

Smith, Eric A.↗

NASA NTRS2005

A New Approach to using a Cloud-Resolving Model to Study the Interactions between Clouds, Precipitation and Aerosols

Numerical cloud models, which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Because cloud-scale dynamics are treated explicitly, uncertainties stemming from convection that have to be parameterized in (hydrostatic) large-scale models are obviated, or at least mitigated, in cloud models. Global models will use the non-hydrostatic framework when their horizontal resolution becomes about 10 km, the theoretical limit for the hydrostatic approximation. This juncture will be reached one to two decades from now. Over the past generation, voluminous datasets on atmospheric convection have been accumulated from radar, instrumented aircraft, satellites, and rawinsonde measurements in field campaigns, enabling the detailed evaluation of models. Improved numerical methods have resulted in more accurate and efficient dynamical cores in models. Improvements have been made in the parameterizations of microphysical processes, radiation, boundary-layer effects, and turbulence; however, microphysical parameterizations remain a major source of uncertainty in all classes of atmospheric models. In recent years, exponentially increasing computer power has extended cloud-resolving-model integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 square kilometers in three-dimensions. Cloud models now provide statistical information useful for developing more realistic physically-based parameterizations for climate models and numerical weather prediction models. A review of developments and applications of cloud models in the past, present and future will be presented in this talk. In particular, a new approach to using cloud-resolving models to study the interactions between clouds, precipitation and aerosols will be presented.

Tao, Wei-Kuo↗