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NASA NTRS1994

A fixed-lag Kalman smoother for retrospective data assimilation

Analyses incorporating future data, as well as current and past data, are termed retrospective analyses. In this paper, the fixed-lag Kalman smoother (FLKS) is proposed as a means of providing retrospective analysis capability in data assimilation. The FLKS is a direct generalization of the Kalman filter. It incorporates all data observed up to and including some fixed amount of time past each analysis time. A computationally efficient form of the FLKS is derived. A simple scalar examination of the FLKS demonstrates that incorporating future data improves analyses the most in the presence of dynamical instabilities, for accurate models and for accurate observations. An implementation of the FLKS for two-dimensional linear shallow-water model corroborates the scalar analysis. The numerical experiments also demonstrate the ability of the FLKS to propagate information upstream as well as downstream, thus improving analysis quality substantially in data voids.

Cohn, Stephen E.↗
NASA NTRS1994

Suboptimal schemes for atmospheric data assimilation based on the Kalman filter

This work is directed toward approximating the evolution of forecast error covariances for data assimilation. The performance of different algorithms based on simplification of the standard Kalman filter (KF) is studied. These are suboptimal schemes (SOSs) when compared to the KF, which is optimal for linear problems with known statistics. The SOSs considered here are several versions of optimal interpolation (OI), a scheme for height error variance advection, and a simplified KF in which the full height error covariance is advected. To employ a methodology for exact comparison among these schemes, a linear environment is maintained, in which a beta-plane shallow-water model linearized about a constant zonal flow is chosen for the test-bed dynamics. The results show that constructing dynamically balanced forecast error covariances rather than using conventional geostrophically balanced ones is essential for successful performance of any SOS. A posteriori initialization of SOSs to compensate for model - data imbalance sometimes results in poor performance. Instead, properly constructed dynamically balanced forecast error covariances eliminate the need for initialization. When the SOSs studied here make use of dynamically balanced forecast error covariances, the difference among their performances progresses naturally from conventional OI to the KF. In fact, the results suggest that even modest enhancements of OI, such as including an approximate dynamical equation for height error variances while leaving height error correlation structure homogeneous, go a long way toward achieving the performance of the KF, provided that dynamically balanced cross-covariances are constructed and that model errors are accounted for properly. The results indicate that such enhancements are necessary if unconventional data are to have a positive impact.

Todling, Ricardo↗
NASA NTRS1995

Diabatic forcing and intialization with assimilation of cloud water and rainwater in a forecast model

In this study, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. Diabatic forcing, in conjunction with diabatic contributions in the initialization, is found to help the forecast retain the diabatic signal found in the liquid water or heating rate data, consequently reducing the spinup time associated with grid-scale precipitation processes. Both observational Special Sensor Microwave/Imager (SSM/I) and model-generated data are used. A physical retrieval method incorporating SSM/I radiance data is utilized to estimate the 3D distribution of precipitating storms. In the retrieval method the relationship between precipitation distributions and upwelling microwave radiances is parameterized, based upon cloud ensemble-radiative model simulations. Regression formulae relating vertically integrated liquid and ice-phase precipitation amounts to latent heating rates are also derived from the cloud ensemble simulations. Thus, retrieved SSM/I precipitation structures can be used in conjunction with the regression-formulas to infer the 3D distribution of latent heating rates. These heating rates are used directly in the forecast model to help initiate Tropical Storm Emily (21 September 1987). The 14-h forecast of Emily's development yields atmospheric precipitation water contents that compare favorably with coincident SSM/I estimates.

Raymond, William H.↗
NASA NTRS1997

Assimilation of Satellite Data in Regional Air Quality Models

In terms of important uncertainty in regional-scale air-pollution models, probably no other aspect ranks any higher than the current ability to specify clouds and soil moisture on the regional scale. Because clouds in models are highly parameterized, the ability of models to predict the correct spatial and radiative characteristics is highly suspect and subject to large error. The poor representation of cloud fields from point measurements at National Weather Services stations and the almost total absence of surface moisture availability observations has made assimilation of these variables difficult to impossible. Yet, the correct inclusion of clouds and surface moisture are of first-order importance in regional-scale photochemistry.

SPATIAL DISTRIBUTION↗
NASA NTRS1996

Two Reduced Resolution Filter Approaches to Data Assimilation

In this paper we evaluate the performance of two reduced resolution filter approaches to data assimilation. The main distinction between these approaches is in the manner they propagate error covariances. Both account for error covariances in a space with dimension m smaller than the model's state vector dimension n. In the first approach the m dimensional error covariance matrix is interpolated to the n-dimensional space and propagated with the n-dimensional dynamics. In the second approach the low-dimensional error covariance matrix is propagated by a dynamical operator generated in the m-dimensional space. Our experiments indicate that the first approach provides a more reliable simplified scheme for error covariance propagation than the second approach.

Todling, Ricardo↗
NASA NTRS1996

High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems

This is the final technical report for the project entitled: "High-Performance Computing and Four-Dimensional Data Assimilation: The Impact on Future and Current Problems", funded at NPAC by the DAO at NASA/GSFC. First, the motivation for the project is given in the introductory section, followed by the executive summary of major accomplishments and the list of project-related publications. Detailed analysis and description of research results is given in subsequent chapters and in the Appendix.

Makivic, Miloje S.↗
NASA NTRS1998

Surface Hydrology in Global River Basins in the Off-Line Land-Surface GEOS Assimilation (OLGA) System

Land surface hydrology for the Off-line Land-surface GEOS Analysis (OLGA) system and Goddard Earth Observing System (GEOS-1) Data Assimilation System (DAS) has been examined using a river routing model. The GEOS-1 DAS land-surface parameterization is very simple, using an energy balance prediction of surface temperature and prescribed soil water. OLGA uses near-surface atmospheric data from the GEOS-1 DAS to drive a more comprehensive parameterization of the land-surface physics. The two global systems are evaluated using a global river routing model. The river routing model uses climatologic surface runoff from each system to simulate the river discharge from global river basins, which can be compared to climatologic river discharge. Due to the soil hydrology, the OLGA system shows a general improvement in the simulation of river discharge compared to the GEOS-1 DAS. Snowmelt processes included in OLGA also have a positive effect on the annual cycle of river discharge and source runoff. Preliminary tests of a coupled land-atmosphere model indicate improvements to the hydrologic cycle compared to the uncoupled system. The river routing model has provided a useful tool in the evaluation of the GCM hydrologic cycle, and has helped quantify the influence of the more advanced land surface model.

Bosilovich, Michael G.↗
NASA NTRS1999

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water.

Lakshmi, Venkataraman↗
NASA NTRS1999

Regional Studies and Applications with a Variable Resolution Stretched Grid Data Assimilation System

The variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM, is used for regional analysis, forecast, and climate applications. The region of interest with enhanced horizontal resolution, mostly used in experiments, is a rectangle over the U.S. The SG-DAS is capable of reproducing regional mesoscale fields, patterns and diagnostics that are not produced by the medium uniform resolution run with the same amount of grid points as for the SG. The SG-DAS regional analyses and diagnostics are used for: validation of regional climate simulation experiments produced with the SG-GCM for the U.S. 1988 summer drought; and are planned to be used for atmospheric chemistry transport experiments. Also, a case study is conducted on a super-typhoon development in December 1997. The SG-DAS appears to be a viable candidate for a variety of regional studies and applications.

Fox-Rabinovitz, Michael↗
NASA NTRS1999

Data Assimilation in the Presence of Forecast Bias: The GEOS Moisture Analysis

We describe the application of the unbiased sequential analysis algorithm developed by Dee and da Silva (1998) to the GEOS DAS moisture analysis. The algorithm estimates the persistent component of model error using rawinsonde observations and adjusts the first-guess moisture field accordingly. Results of two seasonal data assimilation cycles show that moisture analysis bias is almost completely eliminated in all observed regions. The improved analyses cause a sizable reduction in the 6h-forecast bias and a marginal improvement in the error standard deviations.

Dee, Dick P.↗
NASA NTRS1996

Intercomparison, Visualization, and Analysis Testbed System for EOS Global Assimilated Datasets and Satellite Data

The Space Science and Engineering Center (SSEC) of the University of Wisconsin - Madison had two primary goals for NASA grant NAG5-2906. (1) Collaborate with scientists at NASA Goddard Space Flight Center (GSFC) to integrate SSEC's Vis5D software into NASA's Interactive Image Spread Sheet (IISS). Vis5D provides environmental modelers with interactive three-dimensional visualization of their model output. Integration of Vis5D with the IISS would give 3-D graphics capability to the iiss. (2) Make improvements in Vis5D as required by scientists at the NASA Data Assimilation Office (DAO). We were successful in both of these goals. Furthermore, the generic approach taken to achieving the first goal has enabled Vis5D to be integrated into many other software systems.

Source record↗
NASA NTRS1999

A Variable Resolution Stretched Grid Data Assimilation System for Regional Studies and Applications

The variable resolution stretched grid (SG) version of the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS) incorporating the GEOS SG-GCM, has been developed and tested. The area/region of interest used in experiments is a rectangle over the U.S. with -60 km horizontal resolution and 70 layers extending from the surface to 0.1 hPa. The forecast error statistics has been reassessed for finer regional resolution. The experiments are performed for winter and summer seasons. The SG-GCM and SG-DAS experiments show that a definite down-scaling takes place over the area of interest. The SG-DAS is capable of reproducing regional mesoscale patterns and diagnostics that are not produced by coarser uniform resolution runs. The SG-DAS fields and diagnostics are used for regional forecasting, new instrument impact studies, and for validation of regional climate simulation experiments.

Fox-Rabinovitz, Michael S.↗
NASA NTRS2000

Troposphere-Stratosphere Connections in Recent Northern Winters in NASA GEOS Assimilated Datasets

The northern winter stratosphere displays a wide range of interannual variability, much of which is believed to result from the response to the damping of upward-propagating waves. However, there is considerable (growing) evidence that the stratospheric state can also impact the tropospheric circulation. This issue will be examined using datasets generated in the Data Assimilation Office (DAO) at NASA's Goddard Space Flight Center. Just as the tropospheric circulation in each of these years was dominated by differing synoptic-scale structures, the stratospheric polar vortex also displayed different evolutions. The two extremes are the winter 1998/1999, when the stratosphere underwent a series of warming events (including two major warmings), and the winter 1999/2000, which was dominated by a persistent, cold polar vortex, often distorted by a dominant blocking pattern in the troposphere. This study will examine several operational and research-level versions of the DAO's systems. The 70-level-TRMM-system with a resolution of 2-by-2.5 degrees and the 48-level, 1-by-l-degree resolution ''Terra'' system were operational in 1998/1999 and 1999/2000, respectively. Research versions of the system used a 48-level, 2-by-2.5-degree configuration, which facilitates studies of the impact of vertical resolution. The study includes checks against independent datasets and error analyses, as well as the main issue of troposphere-stratosphere interactions.

Pawson, Steven↗
NASA NTRS2001

Assimilation of MGS Data Into a Coupled GCM-Mesoscale Model of the Martian Atmosphere

The project sought to develop a coupled GCM-mesoscale model and to assimilate Mars Global Surveyor (MGS) data into the coupled model. To achieve the project goals, four specific research activities were proposed. These activities are reiterated for completeness and the progress in each of the activities is noted in future sections of this report.

Rafkin, Scot C. R.↗
NASA NTRS2001

CLAES Product Improvement by use of GSFC Data Assimilation System

Recent development in chemistry transport models (CTM) and in data assimilation systems (DAS) indicate impressive predictive capability for the movement of airparcels and the chemistry that goes on within these. This project was aimed at exploring the use of this capability to achieve improved retrieval of geophysical parameters from remote sensing data. The specific goal was to improve retrieval of the CLAES CH4 data obtained during the active north high latitude dynamics event of 18 to 25 February 1992. The model capabilities would be used: (1) rather than climatology to improve on the first guess and the a-priori fields, and (2) to provide horizontal gradients to include in the retrieval forward model. The retrieval would be implemented with the first forward DAS prediction. The results would feed back to the DAS and a second DAS prediction for first guess, a-priori and gradients would feed to the retrieval. The process would repeat to convergence and then proceed to the next day.

Kumer, J. B.↗
NASA NTRS2002

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.↗
NASA NTRS2002

Assimilation of TES Water Vapor Observations

The Thermal Emission Spectrometer (TES) on the Mars Global Surveyor has made extensive observations of the Martian atmospheric water vapor column since the beginning of its mapping mission in early 1999. The results show broad agreement with the earlier Viking Mars Atmospheric Water Detector (MAWD) results (though column amounts in southern summer are higher, perhaps due to dust obscuration during the Viking mission). General circulation model (GCM) simulations of the annual Martian water cycle also show broad agreement with the TES observations. Details of the simulations depend on cloud and boundary layer parameterizations and on the adsorbing properties of the regolith. In order to make quantitative assessments of this agreement and to obtain observational values for the required physical parameters, a tracer transport data assimilation model has been developed. Model winds are derived from both tracer measurements and retrieved atmospheric temperature structures, providing a useful check of the underlying dynamical core of the GCM. By allowing detailed intercomparison between spacecraft and ground-based observations of Martian water vapor, the model should also contribute significantly to our understanding of the diurnal water cycle.

Houben, Howard↗
NASA NTRS2000

CLAES Product Improvement by Use of the GSFC Data Assimilation System (DAS)

This report presents the Cryogenic Limb Array Etalon Spectrometer (CLAES) product improvement by use of the GSFC Data Assimilation System (DAS). The first task is to plug line of sight gradients derived from the CTM for 2/20/92 into the forward model of our retrieval software (RSW) in order to assess the impact on the retrieved quantities. The reporting period covers 12 May 2000 - 21 December 2000.

Kumer, J. B.↗