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NASA NTRS1998

Cloud Distribution Statistics from LITE

The Lidar In-Space Technology Experiment (LITE) mission has demonstrated the utility of spaceborne lidar in observing multilayer clouds and has provided a dataset showing the distribution of tropospheric clouds and aerosols. These unambiguous observations of the vertical distribution of clouds will allow improved verification of current cloud climatologies and GCM cloud parameterizations. Although there is now great interest in cloud profiling radar, operating in the mm-wave region, for the spacebased observation of cloud heights the results of the LITE mission have shown that satellite lidars can also make significant contributions in this area.

Winker, David M.↗

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 NTRS1998

A Catchment-Based Land Surface Model for GCMs and the Framework for its Evaluation

A new GCM-scale land surface modeling strategy that explicitly accounts for subgrid soil moisture variability and its effects on evaporation and runoff is now being explored. In a break from traditional modeling strategies, the continental surface is disaggregated into a mosaic of hydrological catchments, with boundaries that are not dictated by a regular grid but by topography. Within each catchment, the variability of soil moisture is deduced from TOP-MODEL equations with a special treatment of the unsaturated zone. This paper gives an overview of this new approach and presents the general framework for its off-line evaluation over North-America.

Ducharen, A.↗

NASA NTRS1999

Soil Surface Runoff Scheme for Improving Land-Hydrology and Surface Fluxes in Simple SiB (SSiB)

Evapotranspiration on land is hard to measure and difficult to simulate. On the scale of a GCM grid, there is large subgrid-scale variability of orography, soil moisture, and vegetation. Our hope is to be able to tune the biophysical constants of vegetation and soil parameters to get the most realistic space-averaged diurnal cycle of evaporation and its climatology. Field experiments such as First ISLSCP Field Experiment (FIFE), Boreal Ecosystem-Atmosphere Study (BOREAS), and LBA help a great deal in improving our evapotranspiration schemes. However, these improvements have to be matched with, and coupled to, consistent improvement in land-hydrology; otherwise, the runoff problems will intrinsically reflect on the soil moisture and evapotranspiration errors. Indeed, a realistic runoff simulation also ensures a reasonable evapotranspiration simulation provided the precipitation forcing is reliable. We have been working on all of the above problems to improve the simulated hydrologic cycle. Through our participation in the evaluation and intercomparison of land-models under the behest of Global Soil Wetness Project (GSWP), we identified a few problems with Simple SiB (SSIB; Xue et al., 1991) hydrology in regions of significant snowmelt. Sud and Mocko (1999) show that inclusion of a separate snowpack model, with its own energy budget and fluxes with the atmosphere aloft and soil beneath, helps to ameliorate some of the deficiencies of delayed snowmelt and excessive spring season runoff. Thus, much more realistic timing of melt water generation was simulated with the new snowpack model in the subsequent GSWP re-evaluations using 2 years of ISLSCP Initiative I forcing data for 1987 and 1988. However, we noted an overcorrection of the low meltwater infiltration of SSiB. While the improvement in snowmelt timing was found everywhere, the snowmelt infiltration has became excessive in some regions, e.g., Lena river basin. This leads to much reduced runoff in many basins as compared to observations. We believe this is a consequence of neglect of the influence of subgrid-scale variations in orography that affects the production of surface runoff.

Sud, Y. C.↗

NASA NTRS1997

Atmospheric Angular Momentum Fluctuations During 1979-1988 Simulated by Global Circulation Models

Changes in major global dynamical phenomena in the Earth's atmosphere are manifested in the time series of atmospheric angular momentum (AAM), as determined directly from meteorological observations and indirectly from geodetic observations of small fluctuations in the rotation of the solid Earth which are proportional to length of day. AAM fluctuations are intimately linked with energetic processes throughout the whole atmosphere and also with the stresses at the Earth's surface produced largely by turbulent momentum transport in the oceanic and continental boundary layers and by the action of normal pressure forces on orographic features. A stringent test of any numerical global circulation model (GCM) is therefore provided by a quantitative assessment of its ability to represent AAM fluctuations on all relevant timescales, ranging from months to several years. From monthly data provided by the Atmospheric Model Intercomparison Project (AMIP) of the World Climate Research Programme, we have investigated seasonal and interannual fluctuations and the decadal mean in the axial component of AAM in 23 AMIP GCMs over the period 1979-1988. The decadal means are generally well simulated, with the model median value (1.58 x 10(exp 26) kg sq m/s) being only 3.5% larger than the observed mean and with 10 of the models being within 5% of the observed. The seasonal cycle is well reproduced, with the median amplitude of the models seasonal standard deviations being only 2.4% larger than observed. Half the seasonal amplitudes lie within 15% of the observed, and the median correlation found between the observed and model seasonal cycles is 0.95. The dominant seasonal error is an underestimation of AAM during northern hemisphere winter associated with errors in the position of subtropical jets. Less robust are the modeled interannual variations, although the median correlation of 0.61 between model simulations and observed AAM is statistically significant. The two El Nino-Southem Oscillation events that occurred during the AMIP decade 1979-1988 have the expected positive AAM anomalies, although the AAM signature of the 1982-1983 event tends to be underestimated and that of the 1986-1987 event overestimated.

Hide, R.↗

NASA NTRS1999

Parallelization of the Physical-Space Statistical Analysis System (PSAS)

Atmospheric data assimilation is a method of combining observations with model forecasts to produce a more accurate description of the atmosphere than the observations or forecast alone can provide. Data assimilation plays an increasingly important role in the study of climate and atmospheric chemistry. The NASA Data Assimilation Office (DAO) has developed the Goddard Earth Observing System Data Assimilation System (GEOS DAS) to create assimilated datasets. The core computational components of the GEOS DAS include the GEOS General Circulation Model (GCM) and the Physical-space Statistical Analysis System (PSAS). The need for timely validation of scientific enhancements to the data assimilation system poses computational demands that are best met by distributed parallel software. PSAS is implemented in Fortran 90 using object-based design principles. The analysis portions of the code solve two equations. The first of these is the "innovation" equation, which is solved on the unstructured observation grid using a preconditioned conjugate gradient (CG) method. The "analysis" equation is a transformation from the observation grid back to a structured grid, and is solved by a direct matrix-vector multiplication. Use of a factored-operator formulation reduces the computational complexity of both the CG solver and the matrix-vector multiplication, rendering the matrix-vector multiplications as a successive product of operators on a vector. Sparsity is introduced to these operators by partitioning the observations using an icosahedral decomposition scheme. PSAS builds a large (approx. 128MB) run-time database of parameters used in the calculation of these operators. Implementing a message passing parallel computing paradigm into an existing yet developing computational system as complex as PSAS is nontrivial. One of the technical challenges is balancing the requirements for computational reproducibility with the need for high performance. The problem of computational reproducibility is well known in the parallel computing community. It is a requirement that the parallel code perform calculations in a fashion that will yield identical results on different configurations of processing elements on the same platform. In some cases this problem can be solved by sacrificing performance. Meeting this requirement and still achieving high performance is very difficult. Topics to be discussed include: current PSAS design and parallelization strategy; reproducibility issues; load balance vs. database memory demands, possible solutions to these problems.

Larson, J. W.↗

NASA NTRS1999

I/O Parallelization for the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

The National Aeronautics and Space Administration (NASA) Data Assimilation Office (DAO) at the Goddard Space Flight Center (GSFC) has developed the GEOS DAS, a data assimilation system that provides production support for NASA missions and will support NASA's Earth Observing System (EOS) in the coming years. The DAO's support of the EOS project along with the requirement of producing long-term reanalysis datasets with an unvarying system levy a large I/O burden on the future system. The DAO has been involved in prototyping parallel implementations of the GEOS DAS for a number of years and is now converting the production version from shared-memory parallelism to distributed-memory parallelism using the portable Message-Passing Interface (MPI). If the MPI-based GEOS DAS is to meet these production requirements, we must make I/O from the parallel system efficient. We have designed a scheme that allows efficient I/O processing while retaining portability, reducing the need for post-processing, and producing data formats that are required by our users, both internal and external. The first phase of the GEOS DAS Parallel I/O System (GPIOS) will expand upon the common method of gathering global data to a Single PE for output. Instead of using a PE also tasked with primary computation, a number of PEs will be dedicated to I/O and its related tasks. This allows the data transformations and formatting required prior to output to take place asynchronously with respect to the GEOS DAS assimilation cycle, improving performance and generating output data sets in a format convenient for our users. I/O PEs can be added as needed to handle larger data volumes or to meet user file specifications. We will show I/O performance results from a prototype MPI GCM integrated with GPIOS. Phase two of GPIOS development will examine ways of integrating new software technologies to further improve performance and build scalability into the system. The maturing of MPI-IO implementations and other supporting libraries such as parallel HDF should provide performance gains while retaining portability.

Lucchesi, R.↗

NASA NTRS1998

Modeling of the Magnetosphere-Ionosphere-Atmosphere System

This grant covered the transition period between the ISTP/GGS main mission MAMI work (NAGW5-1097) to the extended mission of GGS/SolaxMax. During this period we concentrated on the following subjects: (1) Ionospheric modeling and in particular the coupling of the ionosphere and the magnetosphere require knowledge of the ionospheric conductances. We have an algorithm to derive these conductances from POLAR UVI or POLAR VIS images. The image analysis requires carefully calibrated measurements, separation of auroral brightness from scattered solar EUV and emissions caused by photoelectrons, and modeling of the auroral conditions, Under this grant we evaluated the various sources of uncertainty that contribute to the conductance calculation by comparing different model approaches and we conducted sensitivity studies. A joint modeling effort between our ionospheric models and a global MHD magnetospheric model with S. Slinker and J. Fedder lead to improved parameterizations for the MHD model. The predictions of that new model were validated using data from ground based instruments, POLAR UVI images, and DMSP satellites. These findings were presented at the GEM meeting in Snowmass, and at the Huntsville modeling workshop in Guntersville. A manuscript for publication is in preparation. A study to evaluate the thermospheric effects of large substorms and storms was con- ducted with the TIE-GCM model. Of particular interest are compositional changes of the thermosphere in the southern hemisphere. Southern hemisphere effects are stronger than those on the northern hemisphere because of the larger offset of the magnetic dipole from the rotational axis. These results were presented at the Huntsville modeling workshop in Guntersville.

Source record↗

NASA NTRS1997

Atmospheric Angular Momentum Fluctuations During 1979-1988 Simulated by Global Circulation Models

Changes in major global dynamical phenomena in the Earth's atmosphere are manifested in the time series of atmospheric angular momentum (AAM), as determined directly from meteorological observations and indirectly from geodetic observations of small fluctuations in the rotation of the solid Earth which are proportional to length of day. AAM fluctuations are intimately linked with energetic processes throughout the whole atmosphere and also with the stresses at the Earth's surface produced largely by turbulent momentum transport in the oceanic and continental boundary layers and by the action of normal pressure forces on orographic features. A stringent test of any numerical global circulation model (GCM) is therefore provided by a quantitative assessment of its ability to represent AAM fluctuations on all relevant timescales, ranging from months to several years. From monthly data provided by the Atmospheric Model Intercomparison Project (AMIP) of the World Climate Research Programme, we have investigated seasonal and interannual fluctuations and the decadal mean in the axial component of AAM in 23 AMIP GCMs over the period 1979-1 988. The decadal means are generally well simulated, with the model median value (1.58 x 10(exp 26) kg sq m/s) being only 3.5% larger than the observed mean and with 10 of the models being within 5% of the observed. The seasonal cycle is well reproduced, with the median amplitude of the models' seasonal standard deviations being only 2.4% larger than observed. Half the seasonal amplitudes lie within 15% of the observed, and the median correlation found between the observed and model seasonal cycles is 0.95. The dominant seasonal error is an under- estimation of AAM during northern hemisphere winter associated with errors in the position of subtropical jets. Less robust are the modeled interannual variations, although the median correlation of 0.61 between model simulations and observed AAM is statistically significant. The two El Nino-Southern Oscillation events that occurred during the AMIP decade 1979-1988 have the expected positive AAM anomalies, although the AAM signature of the 1982-1983 event tends to be underestimated and that of the 1986-1987 event overestimated.

Hide, R.↗

NASA NTRS1999

The Variability and Predictability of Precipitation over Southeast Asian

The large scale atmospheric moisture budget, including precipitation, moisture flux convergence, and evaporation is described over southeast Asian. ne results are from the Goddard Earth Observing System (GEOS-1) data assimilation system for the period March 1981 - February 1995. On average, in the late spring and early summer season, precipitation is largely balanced by the atmospheric moisture flux convergence over southeast Asian; evaporation is also an important contributor. The seasonal variability of precipitation is best related to variations in the moisture flux convergence. On the monthly time scales, both the precipitable water and precipitation anomalies are most closely related to moisture flux convergence anomalies and less closely related to evaporation anomalies. The impact of the low-level jet (LLJ) on the strong low-level moisture flux convergence will be discussed. An ensemble of GEOS-2 atmospheric General Circulation Model (GCM) seasonal forecasts and long-term simulation are analyzed to assess the controlling influences of boundary forcing and memory of initial conditions. We also assess the variability and potential predictability from these experiments.

Chang, Yehui↗

NASA NTRS1999

The Impact of Surface Boundary Forcing on Simulation of the 1998 Summer Drought Over the US Midwest Using Factor Separation Technique

The factor separation (FS) technique has been utilized to evaluate quantitatively the impact of surface boundary forcings on simulation of the 1988 summer drought over the Midwestern part of the U.S. The four surface boundary forcings used are: (1)Sea Surface Temperature (SST), (2) soil moisture, (3) snow cover, and (4) sea ice. The Goddard Earth Observing System(GEOS) General Circulation Model (GCM) is used to simulate the 1988 U.S. drought. A series of sixteen simulations are performed with climatological and real 1988 surface boundary conditions. The major single and mutual synergistic factors/impacts are analyzed. The results show that SST and soil moisture are the major single pro-drought factors. The couple synergistic effect of SST and soil moisture is the major anti-drought factor. The triple synergistic impact of SST, soil moisture, and snow cover is the strongest pro-drought impact and is, therefore, the main contributor to the generation of the drought. The impact of the snow cover and sea ice anomalies for June 1988 on the drought is significant only when combined with the SST and soil moisture anomalies.

Stein, Uri↗

NASA NTRS1999

Relating Paleoclimate Data and Past Temperature Gradients: Some Suggestive Rules

Understanding tropical sensitivity is perhaps the major concern confronting researchers, for both past and future climate change issues. Tropical data has been beset by contradictions, and many techniques applicable to the extratropics are either unavailable or fraught with uncertainty when applied at low latitudes. Paleoclimate data, if interpreted within the context of the latitudinal temperature gradient data they imply, can be used to estimate what happened to tropical temperatures in the past, and provide a first guess for what might happen in the future. The approach is made possible by the modeling result that atmospheric dynamical changes, and the climate impacts they produce, respond primarily to temperature gradient changes. Here we review some "rules" obtained from GCM (General Circulation Model) experiments with different sea surface temperature gradients and different forcing, that can be used to relate paleoclimate reconstructions to the likely temperature gradient changes they suggest.

Rind, David↗

NASA NTRS1998

A Simple Model of Cirrus Horizontal Inhomogeneity and Cloud Fraction

A simple model of horizontal inhomogeneity and cloud fraction in cirrus clouds has been formulated on the basis that all internal horizontal inhomogeneity in the ice mixing ratio is due to variations in the cloud depth, which are assumed to be Gaussian. The use of such a model was justified by the observed relationship between the normalized variability of the ice water mixing ratio (and extinction) and the normalized variability of cloud depth. Using radar cloud depth data as input, the model reproduced well the in-cloud ice water mixing ratio histograms obtained from horizontal runs during the FIRE2 cirrus campaign. For totally overcast cases the histograms were almost Gaussian, but changed as cloud fraction decreased to exponential distributions which peaked at the lowest nonzero ice value for cloud fractions below 90%. Cloud fractions predicted by the model were always within 28% of the observed value. The predicted average ice water mixing ratios were within 34% of the observed values. This model could be used in a GCM to produce the ice mixing ratio probability distribution function and to estimate cloud fraction. It only requires basic meteorological parameters, the depth of the saturated layer and the standard deviation of cloud depth as input.

Smith, Samantha A.↗

NASA NTRS1999

Modeled Impact of Cirrus Cloud Increases Along Aircraft Flight Paths

The potential impact of contrails and alterations in the lifetime of background cirrus due to subsonic airplane water and aerosol emissions has been investigated in a set of experiments using the GISS GCM connected to a q-flux ocean. Cirrus clouds at a height of 12-15km, with an optical thickness of 0.33, were input to the model "x" percentage of clear-sky occasions along subsonic aircraft flight paths, where x is varied from .05% to 6%. Two types of experiments were performed: one with the percentage cirrus cloud increase independent of flight density, as long as a certain minimum density was exceeded; the other with the percentage related to the density of fuel expenditure. The overall climate impact was similar with the two approaches, due to the feedbacks of the climate system. Fifty years were run for eight such experiments, with the following conclusions based on the stable results from years 30-50 for each. The experiments show that adding cirrus to the upper troposphere results in a stabilization of the atmosphere, which leads to some decrease in cloud cover at levels below the insertion altitude. Considering then the total effect on upper level cloud cover (above 5 km altitude), the equilibrium global mean temperature response shows that altering high level clouds by 1% changes the global mean temperature by 0.43C. The response is highly linear (linear correlation coefficient of 0.996) for high cloud cover changes between 0. 1% and 5%. The effect is amplified in the Northern Hemisphere, more so with greater cloud cover change. The temperature effect maximizes around 10 km (at greater than 40C warming with a 4.8% increase in upper level clouds), again more so with greater warming. The high cloud cover change shows the flight path influence most clearly with the smallest warming magnitudes; with greater warming, the model feedbacks introduce a strong tropical response. Similarly, the surface temperature response is dominated by the feedbacks, and shows little geographical relationship to the high cloud input. Considering whether these effects would be observable, changing upper level cloud cover by as little as 0.4% produces warming greater than 2 standard deviations in the Microwave Sounding Unit (MSU) channels 4, 2 and 2r, in flight path regions and in the subtropics. Despite the simplified nature of these experiments, the results emphasize the sensitivity of the modeled climate to high level cloud cover changes, and thus the potential ability of aircraft to influence climate by altering clouds in the upper troposphere.

Rind, David↗

NASA NTRS1998

Upper Limits of Predictability in Long-Range Climate/Hydrologic Forecasts

The accurate forecasting of el nino or la nina conditions in the tropical Pacific can potentially lead to valuable predictions of hydrological anomalies over land at seasonal to interannual timescales. Even with highly accurate earth system models, though, our ability to generate these continental forecasts will always be limited by the chaotic nature of the atmospheric circulation. The nature of this fundamental limitation is explored through the use of 16-member ensembles of multi-decade GCM simulations. In each simulation of the first ensemble, sea surface temperatures (SSTs) are given the same realistic interannual variations over a 45-year period, and land surface state is allowed to evolve with that of the atmosphere. Analysis of the results shows that the SSTs control the temporal organization of continental precipitation anomalies to a significant extent in the tropics and to a much smaller extent in midlatitudes. In each simulation of the second ensemble, we prescribe SSTs as before, but we also prescribe interannual variations in the low frequency component of evaporation efficiency over land. Thus, in the second ensemble, we effectively make the extreme assumption that surface boundary conditions across the globe are perfectly predictable, and we quantify the consistency with which the atmosphere (particularly precipitation) responds to these boundary conditions. The resulting "absolute upper limit" on the predictability of precipitation is found to be quite high in the tropics yet only moderate in many midlatitude regions.

Koster, R. D.↗

NASA NTRS1999

Aerosol Retrievals Using Channel 1 and 2 AVHRR Data

The effect of tropospheric aerosols on global climate via the direct and indirect radiative forcings is one of the largest remaining uncertainties in climate change studies. Current assessments of the direct aerosol radiative effect mainly focus on sulfate aerosols. It has become clear, however, that other aerosol types like soil dust and smoke from biomass burning are also likely to be important climate forcing factors. The magnitude and even the sign of the climate forcing caused by these aerosol types is still unknown. General circulation models (GCMs) can be used to estimate the climatic effect of the direct radiative forcing by tropospheric and stratospheric aerosols. Aerosol optical properties are already parameterized in the Goddard Institute for Space Studies GCM. Once the global distribution of aerosol properties (optical thickness, size distribution, and chemical composition) is available, the calculation of the direct aerosol forcing is rather straighfforward. However, estimates of the indirect aerosol effect require additional knowledge of the physics and chemistry of aerosol-cloud interactions which are still poorly understood. One of the main objectives of the Global Aerosol Climatology Project, established in 1998 as a joint initiative of NASA's Radiation Science Program and GEWEX, is to infer the global distribution of aerosols, their properties, and their seasonal and interannual variations for the full period of available satellite data. This will be accomplished primarily through a systematic application of multichannel aerosol retrieval algorithms to existing satellite data and advanced 3-dimensional aerosol chemistry/transport models. In this paper we outline the methodology of analyzing channel 1 and 2 AVHRR radiance data over the oceans and describe preliminary retrieval results.

Mishchenko, Michael I.↗

NASA NTRS1999

Validation of Land-Surface Mosaic Heterogeneity in the GEOS DAS

The Mosaic Land-surface Model (LSM) has been included into the current GEOS Data Assimilation System (DAS). The LSM uses a more advanced representation of physical processes than previous versions of the GEOS DAS, including the representation of sub-grid heterogeneity of the land-surface through the Mosaic approach. As a first approximation, Mosaic assumes that all similar surface types within a grid-cell can be lumped together as a single'tile'. Within one GCM grid-cell, there might be 1 - 5 different tiles or surface types. All tiles are subjected to the grid-scale forcing (radiation, air temperature and specific humidity, and precipitation), and the sub-grid variability is a function of the tile characteristics. In this paper, we validate the LSM sub-grid scale variability (tiles) using a variety of surface observing stations from the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. One of the primary goals of SGP ARM is to study the variability of atmospheric radiation within a G,CM grid-cell. Enough surface data has been collected by ARM to extend this goal to sub-grid variability of the land-surface energy and water budgets. The time period of this study is the Summer of 1998 (June I - September 1). The ARM site data consists of surface meteorology, energy flux (eddy correlation and bowen ratio), soil water observations spread over an area similar to the size of a G-CM grid-cell. Various ARM stations are described as wheat and alfalfa crops, pasture and range land. The LSM tiles considered at the grid-space (2 x 2.5) nearest the ARM site include, grassland, deciduous forests, bare soil and dwarf trees. Surface energy and water balances for each tile type are compared with observations. Furthermore, we will discuss the land-surface sub-grid variability of both the ARM observations and the DAS.

Bosilovich, Michael G.↗

NASA NTRS1999

Current and Future Plans of the NASA Data Assimilation Office (DAO)

The mission of the Data Assimilation Office (DAO) is to advance the state of the art of data assimilation and produce research-quality assimilated data sets which make optimal use of space-based observations. Development efforts over the last few years have focused on delivering a production data assimilation system in support of NASA's Terra platform. That system, called the Goddard Earth Observing System - version 2 or GEOS-2, represents a major upgrade to the baseline GEOS-1 system employed in NASA's first reanalysis effort. GEOS-2 includes a physical-space three dimensional variational analysis algorithm (the Physical-space Statistical Analysis System or PSAS) and numerous improvements to the general circulation model. The latter include a Soil-Vegetation-Atmosphere Transfer (SVAT) land surface scheme, a level 2.5 moist turbulence scheme and new Short Wave (SW) and Long Wave (LW) radiation code. The system also includes an off-line ozone assimilation system, and the capability to assimilate scatterometer surface winds, and TIROS Operational Vertical Sounder (TOVS) and Special Sensor Microwave Imager (SSM/I) moisture data. GEOS-2 is currently run at 1 degree horizontal resolution and 48 levels extending to O.Olmb. Experimental versions of GEOS-2 are run with a global stretched grid allowing enhanced (e.g. 1/4 deg) regional resolution. Other capabilities being developed include, the assimilation of Tropical Rainfall Measuring Mission (TRMM) precipitation and Global Positioning System (GPS) data, an off-line land surface assimilation system, and a retrospective analysis scheme. The DAO is also engaged in a number of collaborative efforts to help accelerate the development of the next generation data assimilation system. These include, a joint modeling effort between the DAO and NCAR/CGDD to develop a new Global Circulation Model (GCM), and a Department of Energy Lawrence Livermore National Laboratory (DOE/LLNL) collaboration on model parallelization. Plans for the next reanalysis will be discussed in the context of current and near term system quality and computing capabilities, and the need for multiple reanalysis products.

Atlas, Robert↗