11. MODEL ASSIMILATED AND FORECAST DATA SETS

11.1 Near-Term Objectives

One of the principal functions of the regional mesoscale models, as was noted in Section 2 is to produce the model assimilated and forecast output products for GCIP research, especially for energy and water budget studies. The production of such data sets was initiated as a GCIP major thrust area in 1995.

The near-term objectives for this thrust area are:

The activities relevant to the third objective above were described in Section 2.

11.2 Regional Mesoscale Model Output

The list of model output fields needed by GCIP researchers was given in Table 3, Volume I of the GCIP Implementation Plan (IGPO,1993). From the beginning of GCIP, it has been the intent to acquire model output from several different models of varying resolution, physics and data assimilation systems. The large volume of data produced by the current generation of atmospheric models has forced a number of compromises in order to achieve a tractable data handling solution for model output data. The data volume is further enlarged by the GCIP need to enhance the traditional model output to include additional fields needed by researchers to perform meaningful studies of the water and energy cycles. The near-term GCIP needs for model output data will be met by concentrating on three regional mesoscale models: The model output is divided into three types: Each model output type is described in the following sections.

A summary of the model output tasks is given in Task 11.2.1 for the Eta model, Task 11.2.2 for the RFE model, and Task 11.2.3 for the MAPS model.

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ENHANCED OBSERVATIONS AND DATA PRODUCTS TASK SUMMARY

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TASK TITLE -- 11.2.1 Eta Model Output

OBJECTIVE -- To provide the model output products from the operational Eta model to the GCIP Data Management System.

PRODUCT DESCRIPTION -- A series of analyzed and forecast products are produced each day by the Eta model running in an operational mode at the NOAA/NCEP. During operational production , NCEP significantly expands the number and type of fields produced with emphasis on those needed by GCIP investigators to compute atmospheric and ground surface energy budgets following the guidelines of the GCIP Implementation Plan , Vol I, Section 5 (IGPO, 1993).

PROJECTED IMPROVEMENTS -- A description of the planned improvements to the Eta model is given in Section 2 of Part I. Some GCIP specific improvements expected during the next two to three years are:

GCIP DATA SOURCE MODULE -- Model Output (Contact:R. Jenne, NCAR)

SCHEDULE -- Operational product sent by NOAA/NCEP each month to the GCIP Model Output Data Source Module.

GCIP USER AVAILABILITY --Three months after the end of the Eta product month.

RESOURCE SUPPORT -- Development support from NOAA GEWEX Program through the NWS CORE Project for GCIP. The operational product is a contribution from the NOAA/NCEP.

TASK LEADER -- K. Mitchell, NOAA/NCEP

GCIP PRA COORDINATION -- Coupled Modeling and Data Assimilation

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ENHANCED OBSERVATIONS AND DATA PRODUCTS TASK SUMMARY

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TASK TITLE -- 11.2.2 RFE Model Output

OBJECTIVE -- To provide the model output products from the operational RFE model to the GCIP Data Management System

PRODUCT DESCRIPTION -- A series of analyzed and forecast products are produced each day by the RFE model operated by the AES/CMC in Canada. The focus of the output from the RFE model during the second year of the EOP will be on the MOLTS and the MORDS.

PROJECTED IMPROVEMENTS -- A description of the planned improvements to the RFE model was given in Section 2 of Part I. Some specific improvements expected during the next two to three years are:

GCIP DATA SOURCE MODULE -- Model Output (Contact: R. Jenne)

SCHEDULE -- Operational product sent by the AES/CMC each month to the GCIP Model Output Data Source Module.

GCIP USER AVAILABILITY -- Three months after the end of the RFE product month.

RESOURCE SUPPORT -- Development support from the Canadian GEWEX Program. The operational product is a contribution from the AES/CMC

TASK LEADER -- H. Ritchie, AES/RPN

GCIP PRA COORDINATION -- Coupled Modeling and Data Assimilation

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ENHANCED OBSERVATIONS AND DATA PRODUCTS TASK SUMMARY

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TASK TITLE -- 11.2.3 MAPS Model Output

OBJECTIVE -- To provide the model output products from the experimental MAPS model to the GCIP Data Management System

PRODUCT DESCRIPTION -- A series of analyzed and forecast products from the MAPS 3- hr cycle are produced each day for the MAPS model running in an experimental mode at the NOAA/FSL. During the second year of the EOP, the focus of the output from MAPS will be on the MOLTS and the MORDS concentrating on the LSA-SW.

PROJECTED IMPROVEMENTS -- A description of the planned improvements to the MAPS model was given in Section 2 of Part I. Some specific improvements expected during the next two to three years are: 1) Addition and improvement of soil/vegetation model for improved flux forecasts;
2) Explicit microphysics, with forecasts of cloud water, rain water, snow and ice mixing ratios;
3) Addition of new data types, including radar reflectivity and radial winds, satellite radiances, Global Positioning System (GPS), and aircraft high-resolution ascent/descent data;
4) Use of surface fields from NMC's LDAS, or implement MAPS-based LDAS, if necessary.
5) Increased horizontal and vertical resolution. GCIP DATA SOURCE MODULE -- Model Output (Contact: R. Jenne)

SCHEDULE -- Experimental products sent by the NOAA/FSL each month to the GCIP Model Output Data Source Module.

GCIP USER AVAILABILITY -- Three months after the end of the MAPS product month.

RESOURCE SUPPORT -- Development support from the NOAA GEWEX Program.

TASK LEADER -- S. Benjamin; NOAA/FSL

GCIP WORKING GROUP COORDINATION -- Coupled Modeling and Data Assimilation

11.3 Model Location Time Series

Results from the GCIP Integrated Systems Test (GIST) and ESOP-95 indicate that the vertical and surface time series at selected points is a very useful type of output for a number of applications. Indeed, some energy and water budget computations are making use of this type of model output data. GCIP labels this type of model output as Model Location Time Series (MOLTS) which is produced as an enhanced output containing a complete set of the surface" type of state and flux data needed by GCIP in addition to the basic atmospheric data which operational centers produce for normal monitoring use and other applications.

The output variables for the MOLTS are listed in Table 11-1. The variables listed under 2) Surface Variables and 3) Atmospheric Variables are considered a"fundamental" list. The MOLTS list from a specific model may add other variables depending on choice of physics package or other non-GCIP user requirements. Some examples for the surface variables could include turbulent kinetic energy and other diabatic heating and moistening rates, such as those due to vertical and horizontal diffusion. Some examples of the non- profile variables could include canopy water content, boundary layer depth, convective storm stability indices, precipitation type (frozen?), etc.

An assessment of the MOLTS requirements for GCIP, MAGS and other investigators indicates that a maximum number of 300 locations will satisfy these requirements during the period 1997 to 1999. The specific number could be less than this maximum number depending on resources available to the data producers and the changes in requirements for GCIP during the Enhanced Seasonal Observing Periods and outside of these periods. GCIP will provide inputs to the requirements as part of its annual update of the GCIP Major Activities Plan. The distribution of 300 MOLTS locations is shown in Figure 11-1. 

Table 11-1.   Output Variables for the Model Location Time Series (MOLTS)
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1)  Identifiers


2)  Surface Variables

3)  Atmospheric variables at each model vertical level

[MOLTS]

Figure 11-1 Proposed geographical Distributions of 300 MOLTS locations.

11.4 Model Output Reduced Data Set

An analysis of the different GCIP requirements for the gridded two- and three- dimensional fields indicates that most of the requirements can be met by a selected set of two-dimensional gridded fields. [NOTE: Some of the requirements for three-dimensional fields can be met with the MOLTS , e.g. by placing the locations around the boundaries of a river basin to do budget studies.] Some of the other 3-D field requirements can be met by a vertical integration through the atmosphere, e.g. vertically integrated atmospheric moisture divergence needed to calculated water budgets. GCIP will make use of this concentration of requirements to further the tractability of the model output data handling problem. A Model Output Reduced Data Set (MORDS) will continue to be produced as two-dimensional fields with the expectation that the MORDS can meet most of the GCIP requirements at a significantly reduced data volume over that needed to provide the information as three- dimensional fields. GCIP is proposing a total of 60 output variables for MORDS separated into the following four components: The specific model output variables in each of the four components are listed in Table 11-2. Output from the regional mesoscale models on the AWIPS 212 Lambert Conformal Map base at a 40 km resolution constitutes about 30 Kilobytes per field for each output step. The 55 fields from the list of variables shown in Table 11-2 will produce about 1.5 Mb for a single forecast or analysis valid time. The MORDS output of analysis, assimilation, and forecast fields for both 0000 UT and 1200 UT cycles comes to a daily total of about 40 Mb per day from each of the regional mesoscale models or about 1.2 Gb per month. This is significantly less than the data volume generated from each of the regional models output in three- dimensional fields. 

Table 11-2.  Output Variables for the Model Output Reduced Data Set
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A.  Near-Surface Fields


B.  Lowest level  Atmospheric Fields

C.  Upper Atmospheric Fields

D.   Meta Data Fixed Fields (as one-time companion file to MORDS)

11.5 Gridded Three-Dimensional Fields

The descriptions given in Section 11.3 on MOLTS and Section 11.4 on MORDS are aimed primarily at reducing the need to handle the full three-dimensional output fields from each of the regional models. This should make the model output more readily accessible for the GCIP investigators. It is also, in part, needed due to the limitations in the data handling capacity for the full model output by the Model Output Data Source Module in the GCIP Data Management and Service System. These limitations means it will be possible to collect the three-dimensional fields at this location for the Eta model only. GCIP encourages the producers of the three-dimensional fields for the other two regional models to store them locally to the extent possible.

The description given above on how GCIP plans to meet the model output data requirements within the data handling limitations experienced is applicable for the near-term requirements. It is expected that these requirements will evolve as the land physics packages of these models demonstrate their utility. GCIP will reevaluate this area on an annual basis as part of preparing updates to the GCIP Major Activities Plan.

11.6 Hydrological Model Output

The NOAA/OH is collecting and archiving operational model output from the National Weather Service River Forecast System (NWSRFS) in the Mississippi River basin. The NWSRFS is a system which integrates a variety of hydrological models into a comprehensive river forecast system. It includes models of runoff-generating processes and runoff and streamflow routing. The NWSRFS data being archived by NOAA/OH include values every six hours of all of the available elements of the daily water budget: precipitation, runoff (surface runoff and baseflow), evaporation and soil moisture storage for individual soil moisture accounting (SMA) areas and the downstream routed streamflows.

A description of the River Forecast Center (RFC) hydrological model and details of the hydrological model outputs were provided in Table 1 and in Appendix B of the GCIP Major Activities Plan for 1995, 1996 and Outlook for 1997 (IGPO, 1994c).

It is foreseen that these operational hydrological model outputs could be useful in several types of GCIP research studies especially in the computation of water budgets. However, this type of model output has not been archived in the past and there is no experience or infrastructure to make such data readily available to research users. To remedy this situation, the NOAA/OH is developing a pilot data set of Hydrology Model output to provide to potential users of these new types of data for research as part of the NOAA Core Project for GCIP.