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Atlas, Robert

Publications and source records attributed to Atlas, Robert.

At least 55 records · Page 3

Regional Climate Simulation of the Anomalous Events of 1998 using a Stretched-Grid GCM with Multiple Areas of Interest

The GEOS (Goddard Earth Observing System) stretched-grid (SG) GCM developed and thoroughly tested over the last few years, is used for simulating the major anomalous regional climate events of 1998. The anomalous regional climate events are simulated simultaneously during the 13 months long (November-1997 - December-1998) SG-GCM simulation due to using the new SG-design with multiple (four) areas of interest. The following areas/regions of interest (one at each global quadrant) are implemented: U.S./Northern Mexico, the El-Nino/Brazil area, India-China, and Eastern Indian Ocean/Australia.

Fox-Rabinovitz, M. S.

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Hou, Arthur

Improving Environmental Prediction Using Rainfall Observations from Space

I discuss the need for accurate rainfall observations to improve our knowledge of the atmospheric state and the ability to provide better numerical weather forecasts. I will give an overview of the recent progress in using rainfall data provided by TRMM and other microwave instruments in data assimilation to improve global analyses and shortrange forecasts. In cases of Hurricanes Bonnie and Floyd, results show that assimilation of TRMM and SSM/I rain rates produces initial conditions with better defined tropical storm features that lead to better Hurricane track and quantitative precipitation forecasts. I will outline the current and future research strategies in preparation for the Global Precipitation Mission.

Hou, Arthur Y.

Global Modeling Activities and NAME

In this talk I will review global modeling activities in the United States that could contribute to and benefit from NAME activities. I will present some preliminary results from several global atmospheric general circulation model simulation experiments for the initial NAME model intercomparison project period of May-Oct 1990. These include an ensemble of medium resolution simulations, and a high resolution (one half degree) simulation. I will also discuss possible high resolution global data assimilation experiments that could be used to help validate the model simulations and assimilate planned NAME observations.

Schubert, Siegfried

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann

Sensitivity of Middle Atmospheric Analyses to the Representation of Gravity-Wave Drag in the DAO's Data Assimilation System

The damping of mesoscale gravity waves has important effects on the global circulation, structure, and composition of the atmosphere. A number of assimilation and forecast experiments have been conducted to examine the sensitivity of meteorological analyses and forecasts to the representation of gravity wave impacts in a data assimilation system (DAS). The experiments were conducted with the Finite-Volume (FV) DAS developed at NASA's Data Assimilation Office (DAO), The main purpose of this research is to determine the optimal combination of wave number, phase speed, wavelength, etc. for representing gravity-wave drag (GWD) in FVDAS. The GWD included in FVDAS includes a spectrum of waves, as would be forced by topography and transient motions (e.g., convection) in the troposphere. The sensitivity experiments are performed by modifying several parameters, such as the number of waves allowed, their wavelength, the background stress amplitude, etc. The results show that the assimilated fields are very sensitive to the number of gravity waves represented in the system, especially at high latitudes of the middle and upper stratosphere and mesosphere in winter. The analyzed stratopause temperature varies by up to 10K when the GWD scheme is modified from a multiple-wave scheme (using a stationary wave and waves with phase speeds of 10, 20, 30 and 40 m/s in each direction) to a single, stationary wave. Insight into the reality of the various versions of the GWD can be obtained by examining the "Observation minus Forecast" residuals from the FVDAS.

Li, Shuhua

The Estimation Theory Framework of Data Assimilation

Lecture 1. The Estimation Theory Framework of Data Assimilation: 1. The basic framework: dynamical and observation models; 2. Assumptions and approximations; 3. The filtering, smoothing, and prediction problems; 4. Discrete Kalman filter and smoother algorithms; and 5. Example: A retrospective data assimilation system

Cohn, S.

Global Modeling Activities and NAME

In this talk I will review global modeling activities in the United States that could contribute to and benefit from NAME activities. I will present some preliminary results from several global atmospheric general circulation model simulation experiments for the initial NAME model intercomparison project period of May-Oct 1990. These include an ensemble of medium resolution simulations, and a high resolution (one half degree) simulation. I will also discuss possible high resolution global data assimilation experiments that could be used to help validate the model simulations and assimilate planned NAME observations.

Schubert, Siegfried

Elementary Theory of Covariance Modeling

The contents include: 1. State space, spectral space, and observation space; 2. Variances and correlations; 3. Isotropic and anisotropic correlation modeling on the sphere; 4. Operational ozone data assimilation; and 5. Kalman filtering for trace constituents.

Cohn, S.

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Lin, Shian-Jiann

A Variable-Resolution Stretched-Grid General Circulation Model and Data Assimilation System with Multiple Areas of Interest: Studying the Anomalous Regional Climate Events of 1998

The new stretched-grid design with multiple (four) areas of interest, one at each global quadrant, is implemented into both a stretched-grid GCM (general circulation model) and a stretched-grid data assimilation system (DAS). The four areas of interest include: the U.S./Northern Mexico, the El Nino area/Central South America, India/China, and the Eastern Indian Ocean/Australia. Both the stretched-grid GCM and DAS annual (November 1997 through December 1998) integrations are performed with 50 km regional resolution. The efficient regional down-scaling to mesoscales is obtained for each of the four areas of interest while the consistent interactions between regional and global scales and the high quality of global circulation, are preserved. This is the advantage of the stretched-grid approach. The global variable resolution DAS incorporating the stretched-grid GCM has been developed and tested as an efficient tool for producing regional analyses and diagnostics with enhanced mesoscale resolution. The anomalous regional climate events of 1998 that occurred over the U.S., Mexico, South America, China, India, African Sahel, and Australia are investigated in both simulation and data assimilation modes. Tree assimilated products are also used, along with gauge precipitation data, for validating the simulation results. The obtained results show that the stretched-grid GCM and DAS are capable of producing realistic high quality simulated and assimilated products at mesoscale resolution for regional climate studies and applications.

Fox-Rabinovitz, Michael S.

On the Choice of Variable for Atmospheric Moisture Analysis

The implications of using different control variables for the analysis of moisture observations in a global atmospheric data assimilation system are investigated. A moisture analysis based on either mixing ratio or specific humidity is prone to large extrapolation errors, due to the high variability in space and time of these parameters and to the difficulties in modeling their error covariances. Using the logarithm of specific humidity does not alleviate these problems, and has the further disadvantage that very dry background estimates cannot be effectively corrected by observations. Relative humidity is a better choice from a statistical point of view, because this field is spatially and temporally more coherent and error statistics are therefore easier to obtain. If, however, the analysis is designed to preserve relative humidity in the absence of moisture observations, then the analyzed specific humidity field depends entirely on analyzed temperature changes. If the model has a cool bias in the stratosphere this will lead to an unstable accumulation of excess moisture there. A pseudo-relative humidity can be defined by scaling the mixing ratio by the background saturation mixing ratio. A univariate pseudo-relative humidity analysis will preserve the specific humidity field in the absence of moisture observations. A pseudorelative humidity analysis is shown to be equivalent to a mixing ratio analysis with flow-dependent covariances. In the presence of multivariate (temperature-moisture) observations it produces analyzed relative humidity values that are nearly identical to those produced by a relative humidity analysis. Based on a time series analysis of radiosonde observed-minus-background differences it appears to be more justifiable to neglect specific humidity-temperature correlations (in a univariate pseudo-relative humidity analysis) than to neglect relative humidity-temperature correlations (in a univariate relative humidity analysis). A pseudo-relative humidity analysis is easily implemented in an existing moisture analysis system, by simply scaling observed-minus background moisture residuals prior to solving the analysis equation, and rescaling the analyzed increments afterward.

Dee, Dick P.

Large 0/12 GMT Differences of US Vaisala RS80 Observations

The daily differences between the temperatures and heights taken at 0 GMT and 12 GMT by Vaisala RS80 rawinsondes have been calculated. The observations were obtained during selected months from 1998 - 2002 over North America, Europe and Australia. The daily differences are defined by the formula, Delta T = Delta T(sub 0) - 0.5(T(sub -12) - T(sub +12)) where AT is the 0/12 GMT difference, T(sub 0) is the 0 GMT observation and T(sub -12) and T(sub +12) are the 12 GMT observations taken just prior and after the 0 GMT synoptic time. If T(sub +12) is missing then Delta T = T(sub 0) - T(sub -12). A similar expression is used if T(sub -12) is missing. Monthly averages of the increments at each station that launch RS80 rawinsondes are then calculated. The results show positive systematic differences in the stratosphere with values as high as 5 K and 150 m at 10 hPa over the central United States. The values remain generally positive and gradually decrease as the levels descend into the upper troposphere but are still significant. In addition, the maximum at each level is just westward of 90 W at the highest levels and just eastward in the troposphere with smaller values along both coasts. In Canada as well as in Europe and Australia the differences are much smaller with no systematic patterns similar to those that exist over the contiguous United States. Time-series plots of the temperatures and heights at select stations in the United States show that the observed values taken at 0 GMT are consistently higher than those at 12 GMT. Over Canada the differences become much less apparent and some cases non-existent. The observations were obtained through National Centers for Environmental Prediction (NCEP) but were checked with data from other sources to verify that no modifications were made other than those at the stations. Since the data from outside the the United States exhibit no large systematic differences, the preliminary conclusion is that the large differences are artificial and probably originate from the post-processing software at the observing stations.

Redder, Chris

The GEOS Retrospective Data Assimilation System: The 6-hour lag case

The fixed-lag Kalman smoother (FLKS) has been proposed as a framework to construct data assimilation procedures capable of producing high-quality climate research datasets. Fixed-lag Kalman smoother-based systems, referred to as retrospective data assimilation systems, are an extension to three-dimensional filtering procedures with the added capability of incorporating observations not only in the past and present time of the estimate, but also at future times. A variety of simplifications are necessary to render retrospective assimilation procedures practical. In this article, we present an FLKS-based retrospective data assimilation system implementation for the Goddard Earth Observing System (GOES) Data Assimilation System (DAS). The practicality of this implementation comes from the practicality of its underlying (filter) analysis system, i.e., the physical-space statistical analysis system (PSAS). The behavior of two schemes is studied here. The first retrospective analysis (RA) scheme is designed simply to update the regular PSAS analyses with observations available at times ahead of the regular analysis times. Although our GEOS DAS implementation is general, results are only presented for when observations 6-hours ahead of the analysis time are used to update the PSAS analyses and thereby to calculate the so-called lag-1 retrospective analyses. Consistency tests for this RA scheme show that the lag-1 retrospective analyses indeed have better 6-hour predictive skills than the predictions from the regular analyses. This motivates the introduction of the second retrospective analysis scheme which, at each analysis time, uses the 6-hour retrospective analysis to replace the first-guess normally used in the PSAS analysis, and therefore allows the calculation of a revised (filter) PSAS analysis. Since in this scheme the lag-1 retrospective analyses influence the filter results, this procedure is referred to as the retrospective-based iterative analysis (RIA) scheme. Results from the RIA scheme indicate its potential for improving the overall quality of the assimilation.

Zhu, Yan-Qiu

Climatology, Natural Cycles, and Modes of Interannual Variability of the Great Plains Low-Level Jet as Assimilated by the GEOS-1 Data Analysis System

Despite the fact that the low-level jet of the southern Great Plains (the GPLLJ) of the U.S. is primarily a nocturnal phenomenon that virtually vanishes during the daylight hours, it is one of the most persistent and stable features of the low-level continental flow during the warm-season months, May through August. We have first used significant-level data to validate the skill of the GEOS-1 Data Assimilation System (DAS) in realistically detecting this jet and inferring its structure and evolution. We have then carried out a 15-year reanalysis with the GEOS-1 DAS to determine and validate its climatology and mean diurnal cycle and to study its interannual variability. Interannual variability of the GPLLJ is much smaller than mean diurnal and random intraseasonal variability and comparable in magnitude, but not location, to mean seasonal variability. There are three maxima of interannual low-level meridional flow variability of the GPLLJ over the upper Great Plains, southeastern Texas, and the western Gulf of Mexico. Cross-sectional profiles of mean southerly wind through the Texas maximum remain relatively stable and recognizable from year to year with only its eastward flank showing significant variability. This variability, however, exhibits a distinct, biennial oscillation during the first six years of the reanalysis period and only then. Each of the three variability maxima corresponds to a spatially coherent, jet-like pattern of low-level flow interannual variability. There are three prominent modes of interannual. variability. These include the intermittent biennial oscillation (IBO), local to the Texas maximum. Its signal is evident in surface pressure, surface temperature, ground wetness and upper air flow, as well. A larger-scale continental convergence pattern (CCP) of covariance, exhibiting strong anti-correlation between the flow near the Texas and the upper Great Plains variability maxima, is revealed only when the IBO is removed from the interannual time series. A third, subtropical mode of covariance is associated with the Gulf of Mexico variability maximum. Significant interannual anti-correlations of the southeasterly flow over the Arizona/New Mexico region with the CCP and the subtropical mode are enhanced when restricted to the month of July. These anti-correlations may relate to an observed out-of-phase precipitation relationship between the Great Plains and the southwestern U.S.. The typical duration of interannual low-level meridional wind anomalies within a given season increases over the continent with decreasing latitude from two to three weeks over the upper Great Plains to six to seven weeks over eastern Texas.

Helfand, H. M.

Evaluation of the DAO Retrospective Data Assimilation System

We have developed and implemented a retrospective data assimilation system (RDAS) as an upgrade to the operational DAO/Terra data assimilation system. This formulation aims at improving analysis over filter analysis by the dynamically consistent incorporation of observation information past a given analysis time. The current implementation of the RDAS uses the adjoint of the tangent linear model of a simplified version of the Terra general circulation model and extensions to the physical-space statistical analysis system to propagate observation information back in time. The RDAS adopts the same assumptions of the regular data assimilation system, particularly, no explicit propagation of error covariances are involved therefore rendering a procedure that is computationally affordable. In this study, we show results of experiments conducted to investigate the performance of the 6-hour (lag-1) RDAS. Statistical results obtained over one month during a winter season indicate that the RDAS represents considerable improvement over the regular assimilation. Plans for implementation of the RDAS capability in our new finite-volume data assimilation system will also be presented at the time of the conference.

Zhu, Yanqiu

Precipitation Recycling and the Vertical Distribution of Local and Remote Sources of Water for Precipitation

Precipitation recycling is defined as the amount of water that evaporates from a region that precipitates within the same region. This is also interpreted as the local source of water for precipitation. In this study, the local and remote sources of water for precipitation have been diagnosed through the use of passive constituent tracers that represent regional evaporative sources along with their transport and precipitation. We will discuss the differences between this method and the simpler bulk diagnostic approach to precipitation recycling. A summer seasonal simulation has been analyzed for the regional sources of the United States Great Plains precipitation. While the tropical Atlantic Ocean (including the Gulf of Mexico) and the local continental sources of precipitation are most dominant, the vertically integrated column of water contains substantial water content originating from the Northern Pacific Ocean, which is not precipitated. The vertical profiles of regional water sources indicate that local Great Plains source of water dominates the lower troposphere, predominantly in the PBL. However, the Pacific Ocean source is dominant over a large portion of the middle to upper troposphere. The influence of the tropical Atlantic Ocean is reasonably uniform throughout the column. While the results are not unexpected given the formulation of the model's convective parameterization, the analysis provides a quantitative assessment of the impact of local evaporation on the occurrence of convective precipitation in the GCM. Further, these results suggest that local source of water is not well mixed throughout the vertical column.

Bosilovich, Michael G.

The Influence of Planetary Wave Transport on Arctic Ozone as Observed by POAM III

Three recent Arctic winters have been unusually warm or cold compared to the 1979-2001 mean, resulting in either a warm, disturbed vortex or a cold, quiet vortex. Interannual differences n ozone transport in the lower stratospheric Arctic vortex are investigated using data from the Polar Ozone and Aerosol Measurement (POAM) III satellite instrument obtained between May 1998 and April 2001. Time series of probability distribution functions (PDFs) of the FOAM data are used to identify seasonal and interannual variations in the transport processes controlling polar ozone. A major warming occurred in December, 1998, that caused the middle stratospheric vortex to be displaced from the pole for nearly a month and dissipate. Ozone transport is inferred from the PDFs and supported by potential vorticity (PV) analyses. The vortex reformed in January, 1999, filled with high O3 air from lower latitudes, which then cooled and descended. As a result, by the end of winter 1999, ozone at 500K in the vortex was 0.5-1.0 ppm higher than in the cold winter of 2000. The winter of 2000-1 had frequent wave disturbances, beginning with a fairly large event in November. However, at the end of this wave activity, the high PV core of the vortex was still intact, and by February, 03 in the vortex looked the same as in 2000. This study demonstrates that interannual variability in the 03-PV relationship can be caused by transport, independent of 03 loss by polar stratospheric clouds (PSCs). Ozone in the vortex in a very disturbed winter does not necessarily represent'pre-PSC' O3 levels in other years.

Strahan, Susan