GSWP-2 Output


Model output should be stored in the ALMA-compliant NetCDF format for direct file transfer to the GSWP-2 Inter-Comparison Center (ICC), or as an ALMA-compliant data set served on a DODS server. The ICC provides a web page for data submission with several options for data delivery.

A website has been set up at the ICC for delivery of output data (http://www.tkl.iis.u-tokyo.ac.jp:8080/gswp2/). The web side allows for data to be submitted through a web browser from local disk to the ICC (pushed), or posted on the modeler’s own FTP site or DODS server to be retrieved by the ICC (pulled). To facilitate this semi-automated data retrieval, a convention for file names should be followed. Daily output data from LSSs should be structured as:
MODEL_expNAME_VERSION_dYEARMONTH.nc
where MODEL: model name, NAME: experiment name identifier (such as B0 for baseline simulations; a list of names for sensitivity experiments is given on the sensitivity studies page), VERSION: version number of the run by 8 digits of the run (year, month, and date of completion of the integration), and the YEAR and MONTH of the contents. The letter d indicated daily data, h is used for 3-hourly data, and f for the fixed fields.

The 10-year data set will be divided into 120 monthly files containing all of the recommended variables in one file. For example, the file containing the baseline run by the gSiB model from IIS for October 1992 completed in mid-April 2003 would be named:
gSiBIIS_expB0_20030415_d199210.nc
The version number is crucial since many models will likely re run and submit their updated outputs.

There are several categories of data to be reported:

Fixed Fields

ALMA time-invariant model fields to be reported once for each model are listed in the table below. This information will aid in the calculation of soil wetness indices, and the comparison of soil wetness and temperatures among models or between models and observations. Some of these fields may be redundant with the supplied input soil parameter data, but there are so many different approaches to soil modeling that it will be clearer if each LSS simply reports the three-dimensional grid of global soil properties used.

Name

Description

Units

SoilDepth

Depth of each soil layer in the column (3D)

M

M_fieldcap*

Field capacity (3D)

M

M_wilt*

Wilting point (3D)

M

M_sat*

Saturated water content (porosity × layer depth) (3D)

M
* Note: change to soil moisture variable names to distinguish them from input data sets


Daily fields

A full compliment of ALMA output variables are requested from each model on a daily interval. Fluxes will be reported as means for the day. Surface state variables are daily means, and subsurface state variables are instantaneous unless noted otherwise. The reporting time is 0000UTC, with the averaging period as the 24 hours preceding the reporting time. For example, the daily flux data for 0000UTC 10 November 1993 will represent the mean for 9 November 1993 (UTC). Table 9 gives the ALMA list of output variables to be reported on the daily interval. The sign convention shown is traditional meteorological convention. ALMA also allows for the mathematical sign convention. ALMA standard output variables for the GSWP-2 baseline simulation are listed in the table below (see http://www.lmd.jussieu.fr/ALMA/ for a detailed discussion of these variables).

Variable

Description

Units

Sign (+)

O.1) General energy balance components

Swnet

Net shortwave radiation

W m-2

Down

Lwnet

Net longwave radiation

W m-2

Down

Qle

Latent heat flux

W m-2

Up

Qh

Sensible heat flux

W m-2

Up

Qg

Ground heat flux

W m-2

Down

Qf

Energy of fusion

W m-2

Sol.<Liq.

Qv

Energy of sublimation

W m-2

Sol.<Vap.

Qa

Heat transferred to snowpack by rainfall

W m-2

Down

DelSurfHeat

Change in surface heat storage

J m-2

Incr.Heat

DelColdCont

Change in snow cold content

J m-2

Decr.Heat

O.2) General water balance components

Snowf

Snowfall rate

kg m-2 s-1

Down

Rainf

Rainfall rate

kg m-2 s-1

Down

Evap

Total evapotranspiration (all terms)

kg m-2 s-1

Up

Qs

Surface runoff

kg m-2 s-1

Out

Qsb

Subsurface runoff

kg m-2 s-1

Out

Qsm

Snowmelt

kg m-2 s-1

Sol.<Liq.

Qfz

Refreezing of water in the snowpack

kg m-2 s-1

Liq.<Sol.

Qst

Water flowing out of snowpack

kg m-2 s-1

Out

DelSoilMoist

Change in column soil moisture

kg m-2

Increase

DelSWE

Change in snow water equivalent

kg m-2

Increase

DelSurfStor

Change in surface liquid water storage

kg m-2

Increase

DelIntercept

Change in canopy interception storage

kg m-2

Increase

O.3) Surface state variables

SnowT

Snow surface temperature

K

Pos.Def.

VegT

Vegetation canopy temperature

K

Pos.Def.

BaresoilT

Bare soil surface temperature

K

Pos.Def.

AvgSurfT

Area-weighted average surface temperature

K

Pos.Def.

RadT

Effective surface radiative temperature

K

Pos.Def.

Albedo

Surface albedo

-

Pos.Def.

SWE

Snow water equivalent on ground (3-D)

kg m-2

Pos.Def.

SWEVeg

Snow water equivalent in canopy interception

kg m-2

Pos.Def.

SurfStor

Surface water storage

kg m-2

Pos.Def.

O.4) Subsurface state variables

SoilMoist

Average layer soil moisture (3-D)

kg m-2

Pos.Def.

SoilTemp

Average layer soil temperature (3-D)

K

Pos.Def.

SoilWet

Total column soil wetness (wilting point = 0, saturation = 1)

-

> wilting point

O.5) Evaporation components

PotEvap

Potential evapotranspiration

kg m-2 s-1

Up

Ecanop

Evaporation of canopy interception

kg m-2 s-1

Up

Tveg

Vegetation transpiration

kg m-2 s-1

Up

Esoil

Bare soil evaporation

kg m-2 s-1

Up

Ewater

Open water evaporation

kg m-2 s-1

Up

RootMoist

Root zone soil moisture

kg m-2

Pos.Def.

CanopInt

Total canopy water storage

kg m-2

Pos.Def.

EvapSnow

Evaporation of liquid water from snowpack

kg m-2 s-1

Up

SubSnow

Snow sublimation

kg m-2 s-1

Up

SubSurf

Sublimation of ice from soil and canopy interception

kg m-2 s-1

Up

Acond

Aerodynamic conductance

m s-1

Pos.Def.

CCond

Canopy (stomatal) conductance

m s-1

Pos.Def.

O.6) Other hydrologic variables

WaterTableD

Depth to water table

m

Pos.Def.

O.7) Cold season processes

SnowFrac

Snow cover fraction

-

Pos.Def.

SAlbedo

Snow albedo

-

Pos.Def.

SnowDepth

Depth of snow layers (3-D)

m

Pos.Def.

O.8) Variables to be compared with remotely sensed data

RadTmax

Maximum daily radiative surface temperature

K

Pos.Def.

RadTmin

Minimum daily radiative surface temperature

K

Pos.Def.


Global 3-hourly Fields

For the final year of the integrations (1995), a subset of the required ALMA output variables will be reported globally at the 3-hourly forcing interval. This is requested for two main reasons. First, this 1-year data set will provide a global picture of the simulation of the diurnal cycle across all seasons for all models. Second, this set of output data will provide sufficient archives for the remote sensing evaluations, as 3-hourly data give a closer rendition of the instantaneous picture that satellite platforms provide. Reporting of data only once a day spatially limits the regions of satellite validation, due to the sun-synchronous orbits of most polar-orbiting platforms.  All state variables will be reported as instantaneous values and fluxes will be reported as the average rate over the preceding interval (3 hours). Variables to be reported during this intensive model output period (IMOP) are indicated in the table below.

O1

O2

O3

O5

Swnet

Snowf

SnowT

PotEvap

Lwnet

Rainf

VegT

Ecanop

Qle

Evap

BaresoilT

Tveg

Qh

Qs

AvgSurfT

Esoil

Qg

Qsb

RadT

RootMoist

Qf

Qsm

Acond

Qv

Qfz

CCond

Qa

Qst

DelSurfHeat

DelSoilMoist

DelColdCont

DelSWE

DelSurfStor

DelIntercept


Local 3-hourly Fields

It will be impractical to request many global 3-hourly fields, and it is certainly not within current storage and data transmission capabilities to do so for the entire 10-year period. However, it may be tractable to request 3-hourly data over specific grid boxes for more extended periods, corresponding to locations where comparable measurements have been collected that can be used for validation. In particular, locations of field campaigns or long-term monitoring sites, such as the ARM-CART site, FluxNET sites, or Valdai. Details of these point integrations will be decided later in the project.

Ancillary Information

In addition to the model data, we request that each modeling group submit a description of the model used. A questionaire has been prepared to simplify this reporting.