Sorry, you need to enable JavaScript to visit this website.

# FAQ's

Q. Where can I find LIS data?
Tags:

A. The Land Information System (LIS) is an open source flexible land-surface modeling and data assimilation software framework developed here at NASA Goddard within the Hydrological Sciences LaboratoryGLDASNLDASNCA-LDAS, and FLDAS are specific uses of the LIS software, and these LDAS projects have produced land-surface forcing data and model output going back many decades and continuing to near real-time. Links to download LDAS datasets are located on the right side of this FAQ. There is no "LIS data" - unless, of course, you use LIS yourself to generate your own!

Q. What FLDAS domains are available?
Tags:

A. There are FLDAS domains available for:

• Eastern Africa
• Daily, monthly, monthly anomaly, and monthly climatology at 0.1-deg.
• Daily and monthly at 0.25-deg.
• Southern Africa
• Daily, monthly, monthly anomaly, and monthly climatology at 0.1-deg.
• Daily and monthly at 0.25-deg.
• Western Africa
• Daily, monthly, monthly anomaly, and monthly climatology at 0.1-deg.
• Daily and monthly at 0.25-deg.
• Global
• Monthly, monthly anomaly, and monthly climatology at 0.1-deg.
Q. Are hourly fields available from NCA-LDAS?
Tags:

A. No, because the model output from LIS was only saved as a daily average. The objective of NCA-LDAS is to provide an integrated terrestrial water analysis system. Daily-averaged output meets this objective. Future versions of the NCA-LDAS may include sub-daily output fields if there is sufficient demand/interest.

Q. Where is the latest real-time NLDAS forcing and model data?
Tags:

A. The near real-time NLDAS Phase 2 (NLDAS-2) forcing and model output data is currently running operationally at NOAA/NCEP/EMC. Automated scripts and programs gather and process the data needed to generate the NLDAS-2 forcing datasets. These scripts/programs run once per day, and update one day's worth (typically 12Z to 12Z) of forcing. This forcing data is then used to drive the various land-surface models to produce the model output. Scripts archive the data at the NASA GES DISC.

The NLDAS-2 forcing currently is available around ~3-4 days behind the current date. Long-time users of NLDAS products will note that this is a slightly longer delay than the 2-3 day data latency that was typical from NLDAS Phase 1. The primary reason for this is that the NARR model data used in the generation of NLDAS-2 forcing is currently in a quasi-operational mode and not available as early as the model data used in the generation of NLDAS-1 forcing. Also, GDS data may be behind by another couple days, as the updated index file is generated.

New for 2019: NLDAS-2.5 is expected to be running operationally at NOAA by the end of the year.  NLDAS-2.5 will have the same LSMs and grid as NLDAS-2, with the only change being different forcing datasets used every day to fill the ~4-day latency gap to make NLDAS truly real-time. See the NULDAS white paper for details (especially Figure 1) on the forcing datasets that will be used.

Q. What is the latency for GLDAS data?
Tags:

A. Currently, GLDAS data at the NASA GES DISC is updated at about a month delay. The updates are made usually in the middle of each month.

Tags:

A. Yes, it is now possible to subset the LDAS datasets by region and/or by variable using the GES DISC's Mirador search tool. For additional help, please see these news articles from the GES DISC about the on-the-fly subset service for the GLDAS and NLDAS datasets.

More recently, the NASA GES DISC has enabled subsetting by region and/or variable by clicking on the "Subset / Get Data" link available under each collection.  Click on each LDAS collection under "Get Data" to see this link.

You can also subset by region and/or variable through Giovanni. Users can select a bounding box region or subset using shapefiles, including counties, U.S. states, and watersheds.

Q. Are monthly averages available from NCA-LDAS?
Tags:

A. Not at this time. However, monthly averages can be easily created from the daily-averaged files using the GES DISC Giovanni service. Future versions of the NCA-LDAS may include monthly-averaged output fields if there is sufficient demand/interest.

Q. Are monthly NLDAS datasets available?
Tags:

A. Yes, monthly NLDAS datasets for NLDAS-1 forcing, NLDAS-2 forcing, NLDAS-2 Mosaic, NLDAS-2 Noah, and NLDAS-2 VIC are now available from the GES DISC. Please see the updated NLDAS-1 README and NLDAS-2 README files for details about the creation and content of these datasets. The latest month of data will typically be available around 10-15 days after the beginning of the following month. Monthly climatology datasets are also available.

Q. WGRIB gives a different variable name. Am I reading the GRIB file correctly?
Tags:

A. When you are not using the GLDAS GRIB table (gribtab), the names of the variables do not appear correctly. For example with GLDAS data, the rainfall rate is called 4LFTX and a WGRIB message "using NCEP-opn" appears. One way to ensure is to use KPDS values as guidance using "wgrib -v". The KPDS value for rainfall rate is 132. The PDS values are specified in Table 2 of the GLDAS-1 README file. Depending on the version of WGRIB and the operating system, the use of the GRIB table can be established through setting the environment and/or having a copy of gribtab in the working directory where WGRIB is issued. Please refer to "Reading the Data" section of the readme file for setting the environment. The GRIB tables are available from the GES DISC documentation website.

Q. Is LDAS data provided in UTC time or local time? Does it account for daylight saving time?
Tags:

A. All LDAS data is provided in Coordinated Universal Time (UTC). There is no accounting for daylight saving time. For assistance converting between UTC and a particular location by date, please visit the Time Zone Converter.

Q. Are real-time updates available from NCA-LDAS?
Tags:

A. Not at this time. It is projected that new versions of the NCA-LDAS datasets will be released every year or two. These updated versions will include the next full calendar year(s) of data. The latest version 2.0 of the NCA-LDAS dataset goes to 31 Dec 2016. The new versions will also include new/updated satellite Environmental Data Records (EDRs) and other associated data assimilation and forcing improvements.

Q. Are daily NLDAS datasets available?
Tags:

A. Daily NLDAS datasets are not currently available, and there are no immediate plans to make them available. The NLDAS group has received many requests for these datasets; however, some users have requested 00Z-00Z averages, some requested 12Z-12Z averages, and some requested 00LST-00LST averages. If you need daily averages, please download the hourly NLDAS datasets and create your own daily datasets.

Q. Does "soilm1" correspond to the top or bottom soil layer?
Tags:

A. The order of soil layers in the GLDAS datasets goes from bottom to top. For example, the first record for soil moisture in NOAH is the lowest 100-200 cm, followed by the 3rd layer 40-100cm, the 2nd layer 10-40cm, then the top 0-10cm layer. This order applies to the soil temperature as well. One way to confirm is to check the values: soil moisture amounts increase as layer depths increase.

Q. Where can I find the GRIB tables (gribtabs) for LDAS DATA?
Tags:

A. GRIB tables for GLDAS-1, NLDAS-1, and NLDAS-2 data as stored on the NASA Hydrology DISC can be found on the GES DISC documentation website.

Q. How can I obtain total soil moisture amount [kg m-2] from the NCA-LDAS data?
Tags:

A. The NCA-LDAS dataset currently provide soil moisture values in units of [m^3 m-3] for volumetric soil moisture. To convert to units of [kg m-2] for the total soil moisture amount in each layer, all you do is multiply the [m^3 m-3] value by the thickness of the layer in [mm]. The assumption is made that the density of the water in the soil is 1000 [kg m-3].

NCA-LDAS SM volumetric  ---->   [converting to]   ---->   NCA-LDAS SM amount

thickness of
1000 kg      1 m        layer in mm       kg
volumetric soil moisture  X  -------  X  -------  X  -----------   =   --
m^3       1000 mm          1            m^2



As an example, for the 0-10cm layer, just multiply by 100mm to convert the data from volumetric soil moisture to get units of [kg m-2]. For the 10-40cm layer, multiply by 300mm, and so on for the other soil moisture layers. The volumetric soil moisture values range between wilting point and porosity (e.g., ~0.01 to ~0.5). If we divide the volumetric soil moisture [m^3 m-3] by porosity [m^3 m-3], we will get the soil moisture fraction which ranges from 0 to 1.

Q. What is the difference between NLDAS Phase 1 (NLDAS-1) and NLDAS Phase 2 (NLDAS-2)?
Tags:

A. This is the most popular NLDAS question. Hopefully, below you can find an appropriately short yet fully detailed answer!

For further information, please refer to the NLDAS-1 ForcingNLDAS-1 ModelNLDAS-2 Forcing, and NLDAS-2 Model pages.

The most significant difference is the time frames of the datasets:

• NLDAS-1 is available from mid-1996 to the end of December 2007.
• NLDAS-2 is available from January 1979 to near real-time.

Another major difference between the two phases of NLDAS is the sources of observations and reanalyses used to create the respective forcing datasets. NLDAS-1 uses the 40-km NCEP Eta model-based Data Assimilation System (EDAS) for the surface meteorology, while NLDAS-2 uses the 32-km NARR system. For downward shortwave radiation at the surface, NLDAS-1 uses GOES-based satellite retrievals, with EDAS data used when/where not available; NLDAS-2 uses GOES data to bias-correct the NARR shortwave radiation.

Both NLDAS-1 and NLDAS-2 use a 1/8th-degree CPC daily gauge analysis as the source of the precipitation forcing. This analysis is PRISM-adjusted and was produced by the CPC using a least squares distance weighting scheme. NLDAS-2 uses this analysis over the entire data record, while NLDAS-1 used this analysis from 2002 onward. For the period 2002 and before (in the NLDAS-1 data only), the other daily gauge analysis used was a daily 1/4th-degree CPC product, which was generated using a Cressman analysis and interpolated by the NLDAS team to 1/8th-degree using the budget bilinear method.

During the period when 4-km hourly Doppler radar Stage II precipitation estimates are available (mid-1996 to present) over CONUS, both NLDAS-1 and NLDAS-2 first use these hourly estimates to temporally disaggregate the daily gauge analysis into hourly precipitation. If the radar estimates are not available (such as due to maintenance or coverage issues), the additional hourly datasets used to calculate the weights differ between NLDAS-1 and NLDAS-2. In NLDAS-1, the EDAS precipitation data is used over CONUS, Canada, and Mexico. In NLDAS-2 over CONUS or Mexico, 8-km half-hourly CMORPH satellite-retrieved estimates (2002 to present) are used if Stage II is not available. If CMORPH is unavailable, such as before 2002, the 2 X 2.5 degree CPC Hourly Precipitation Dataset (HPD) is used. If the HPD is also unavailable, then the NARR precipitation data is used. Over Canada, only NARR precipitation is used due to poor gauge coverage, with a 1-degree blending applied at the U.S.-Canada border.

The hourly estimates from the radar, CMORPH, HPD, EDAS, or NARR are only used to calculate the weights for the temporal disaggregation; the daily sum of the hourly NLDAS precipitation will be equal to the daily gauge analysis from the CPC. In addition, over CONUS, the hourly precipitation from both the NLDAS-1 and NLDAS-2 precipitation should be nearly identical when/where the hourly radar estimates are available. Small differences between NLDAS-1 and NLDAS-2 may still be present, however, owing to the 1/4th-degree daily gauge analysis used in NLDAS-1 before 2002 or to the nature of the amount/quality of precipitation gauge observations and radar estimates used between retrospective or real-time data productions. Further details about the NLDAS-2 precipitation can be found in the Appendix C describing the NLDAS-2 forcing data.

Several significant attributes are identical between the NLDAS-1 and NLDAS-2 datasets. They are both run on the 1/8th-degree NLDAS grid and are available hourly. The vegetation, soils, and elevation datasets used are also identical. The same four land-surface models (Mosaic, Noah, SAC, and VIC) are also used in both phases, although the models underwent some upgrades and corrections between the two phases of NLDAS. For more on these model improvements, please see Section 2.3 of Xia et al. (2012, Part 1). The spin-up procedures between NLDAS-1 and NLDAS-2 do differ, owing the different time periods between them.

Q. What data are integrated/assimilated into GLDAS?
Tags:

A. Data are integrated within GLDAS as static parameter fields, as meteorological forcing, and through the process of data assimilation. Parameter fields include vegetation type and properties derived from AVHRR and MODIS, soil properties from the USDA, and elevation from GTOPO30 (see GLDAS vegetation page). Meteorological forcing datasets include downscaled NOAA Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP), Air Force Weather Agency solar radiation, and NOAA Global Data Assimilation System (GDAS) air temperature, surface pressure, wind speed, land specific humidity (see GLDAS forcing page).

Currently, the only data that GLDAS integrates through data assimilation is MODIS snow cover in the 0.25 degree Noah simulation. We have developed an technique for assimilating GRACE terrestrial water storage data, but that has not been used in GLDAS. We do assimilate GRACE data into a separate stand-alone simulation of the Catchment land surface model which is then used to diagnose drought. For more information, see the NDMC website.

Q. What tools are available to help with the GRIB data?
Tags:

A. Two extremely useful tools for processing the LDAS data in GRIB-1 format are WGRIB and grib2ctl.pl. More documentation about GRIB data can be found at NCEP. Climate Data Operators (CDO) are also useful to manipulate and analyze GRIB data. Another useful tool is NCL, which handles GRIB-1/GRIB-2 trivially. NCL has all the GRIB lookup tables built-in. Further, it has two command line utilities: "ncl_filedump", which creates a printed overview of the file contents, and "ncl_convert2nc", which converts GRIB-1/GRIB-2 to netCDF adhering to the Climate and Forecast netCDF convention.

Q. What are the known issues with the NCA-LDAS datasets?
Tags:

A. The NCA-LDAS LSMs were forced with the NLDAS-2 Forcing dataset, and are thus subject to the same issues as the NLDAS-2 forcing.

Q. What is the difference between NLDAS datasets at NASA and at NOAA/EMC?
Tags:

A. NLDAS datasets are available at both the NASA GES DISC (for both retrospective and real-time) and from NOAA (currently real-time only). Datasets from either NASA or from NOAA/EMC can be used, and the fields in the datasets are identical, except where noted below. The file name conventions are also different between NASA and NOAA, as well as the directory structures. Within each year, NASA uses the ordinal date while NOAA/EMC uses YYYYMMDD. The real-time data from NOAA is GRIB-2.  All NLDAS datasets are the NASA GES DISC are GRIB-1. The GRIB tables and a few PDS GRIB values also differ between the NLDAS datasets at NASA and at NOAA. GRIB tables and documentation for NLDAS data as stored at the NASA GES DISC are found on their documentation website.

For NLDAS-2 Mosaic, the NOAA retrospective data provides the vegetation cover as a fraction (from 0 to 1) while the real-time data from NOAA is provided as a percentage (from 0 to 100). All NLDAS-2 Mosaic vegetation cover data provided at the NASA GES DISC is in units of fraction.

For NLDAS-2 Noah, NOAA provides the albedo and the moisture availability variables in units of fraction, while the NASA GES DISC provides these variables in units of percentage. NOAA/EMC provides the net shortwave, net longwave, and ground heat flux with signs reversed from the traditional ALMA direction for general energy balance components. For these variables at the NASA GES DISC, the signs are reversed from the NOAA data, and these three variables have the sign correct in the traditional direction. Finally, the units of the snow water-equivalent in the NOAA data are in meters, while in the NASA GES DISC data, the units are in [kg m-2] (or millimeters).

For NLDAS-1 Forcing, some PDS variable ID numbers were changed for the datasets at the NASA GES DISC to prevent confusion, as the data at NOAA/EMC uses identical PDS ID values for several variables.

Q. What are the known issues with the GLDAS-1 datasets?
Tags:

A. There are several known issues with the GLDAS-1 datasets. These issues will be resolved in GLDAS-2.1, which will replace GLDAS-1:

• GLDAS-1 all models Forcing fields: highly uncertain during 1995-1997.
• GLDAS-1 all models SWdownsfc: Unrealistic patterns over China, Southern Europe, and Canada appear from time-to-time from 2001 onwards, especially prominent during June-December 2002.
• GLDAS-1 0.25-degree Noah Rainfsfc: Granularity of adjacent grid cell maxima and minima appears from time-to-time for 2001 onwards when the disaggregated CPC's CMAP precipitation fields are used. It is an artifact of the disaggregation method.
• The issues with the forcing will then affect the soil moisture, runoff, fluxes, etc. in the model output in the regions listed.

Please also check the FAQ page at the Hydrology GES DISC.

Q. How can I convert LDAS GRIB data into ASCII?
Tags:

A. The WGRIB tool can easily convert the LDAS GRIB data into ASCII. Here's a sample command, which will dump the first record in the GRIB file named "FILENAME" into an ASCII text file named "output.txt":

   wgrib -d 1 FILENAME | wgrib -text -i FILENAME -o output.txt


Please see the WGRIB documentation for additional options and assistance. LDAS datasets can also be obtained in ASCII via the GDS at the GES DISC, as well as by using the time series "data rods" feature.

Q. What are the known issues with the NLDAS datasets?
Tags:

A. There are a number of known issues with the NLDAS datasets:

• NLDAS-2 Forcing "A" APCPsfc and CONVfracsfc: Two days with zero precipitation over CONUS/Mexico (13Z 19 Feb 2018 to 12Z 21 Feb 2018); these days had heavy rain over the central U.S., which has resulted in drier-than-actual soil moisture in the region starting from 19 February 2018. (view1) (view2) (detail). UPDATE - 14 June 2018: NLDAS-2 Forcing "A" hourly files for these 48 times, and the February 2018 Forcing "A" monthly-average file were updated at the NASA GES DISC. No changes to the NLDAS-2 LSMs at this time. (detail).
• NLDAS-2 Forcing "A" APCPsfc: Dry spots of precipitation, resulting in very dry soil moistures in localized areas; start times range from mid-2010 to early 2015, and end on the analysis on 6 Apr 2016 (view1) (view2) (detail)
• NLDAS-2 Forcing "A" and Forcing "B" APCPsfc: Unrealistically high precipitation in Canada south of 46 North from mid-March 2012 to late-July 2014, with occasional recurrence to present (view1) (view2) (detail)
• NLDAS-2 Forcing "A" and Forcing "B" APCPsfc: Unrealistically low precipitation in Canada south of 50 North during 2002 (view) (detail)
• NLDAS-2 Forcing "A" APCPsfc: Unrealistically high precipitation in small localized regions in Texas and the Southeast U.S. for July and Aug 2008 (view) (detail)
• NLDAS-2 Forcing "A" APCPsfc: A band with lower values of the precipitation on the annual scale on the Canada side of the U.S.-Canada border for most years (view) (detail)
• NLDAS-2 Forcing "A" TMP2m: Warm bias in the 2-meter surface air temperature (small bias before 2008, becoming a more moderate bias at times from 2008 to present), especially in the SE U.S. during summer (detail)
• The issues with the forcing will then affect the soil moisture, runoff, fluxes, etc. in the model output in the regions listed.
Q. Are time series of LDAS datasets available?
Tags:

A. A set of variables from the NLDAS and GLDAS projects are now available as time series. These "data rods" datasets allow the access of the data in a long time series at a single point - without having to download the entire files. Access to the time series data is very quick, and is available as a plot or in ASCII format. A prototype to get the data in netCDF format is also available for testing. Please see the Data Rods News Article for additional information.

Q. Does the precipitation variable include snowfall?
Tags:

A. Yes. The precipitation fields in the NLDAS-1 Forcing files and in the NLDAS-2 Forcing "A" and "B" files represent the total precipitation, including both rain and snow. The land-surface models each have their own individual method to determine how this total precipitation reaches the land-surface (as rain, snow, or some combination). Typically, the near-surface air temperature from the forcing at the same time interval as the precipitation is used to determine rain or snowfall. The NLDAS-2 model output files contain rainfall and snowfall fields as a result of their individual methods.

Q. What services provide or programs use LDAS datasets?
Tags:

A. NASA LDAS datasets are available in the following ways:

Q. Can you explain the components of the evaporation in the NLDAS-2 model output?
Tags:

A. There are four evaporation components of the total latent heat flux in the NLDAS-2 model datasets.

They are as follows (with PDS ID number, variable names, full description, and units):

   199:EVBSsfc:Direct evaporation from bare soil [W/m^2]
200:EVCWsfc:Canopy water evaporation [W/m^2]
198:SBSNOsfc:Sublimation (evaporation from snow) [W/m^2]
210:TRANSsfc:Transpiration [W/m^2]



These variables correspond to the following evaporation components of the ALMA standard:

   NLDAS names     ALMA names     ALMA description/units
-----------     ----------     ----------------------
EVBSsfc         ESoil          Evaporation from bare soil [kg/m2s]
EVCWsfc         ECanop         Evaporation from canopy interception [kg/m2s]
SBSNOsfc        SubSnow        Total sublimation from the ground snow pack [kg/m2s]
TRANSsfc        TVeg           Transpiration from canopy [kg/m2s]



Additionally, the total latent heat flux is:

   121:LHTFLsfc:Latent heat flux [W/m^2]



For NLDAS-2 Mosaic, these components are defined as positive in the downward direction, which is the opposite direction as the traditional ALMA standard for these variables. However, the latent heat flux for NLDAS-2 Mosaic is defined as positive in the upward direction, which means that the latent heat flux is roughly equal to the negative of the sum of these four components for NLDAS-2 Mosaic:

   LHTFLsfc ~= -(EVBSsfc + EVCWsfc + SBSNOsfc + TRANSsfc)



As an additional complication, the sign of the SBSNOsfc variable in NLDAS-2 Mosaic switched directions on and after 9 March 2008. Before this date, NLDAS-2 Mosaic SBSNOsfc was defined as positive in the downward direction, but after this date, SBSNOsfc is defined as positive in the upward direction. Thus, on and after 9 March 2008, the evaporation balance equation for NLDAS-2 Mosaic becomes:

   LHTFLsfc ~= -(EVBSsfc + EVCWsfc - SBSNOsfc + TRANSsfc)



For NLDAS-2 Noah and NLDAS-2 VIC, these components and the latent heat flux are all defined as positive in the upward direction. The latent heat flux is roughly equal to the sum of the four evaporation components:

   LHTFLsfc ~= EVBSsfc + EVCWsfc + SBSNOsfc + TRANSsfc



There is another energy term that describes snow phase-change heat flux:

   229:SNOHFsfc:Snow phase-change heat flux [W/m^2]



The SNOHFsfc can be thought of as roughly identical to the sum of the Qsm and Qfz terms (albeit, in different units) from the ALMA standard.

When comparing these four evaporation components and the SNOHFsfc variable between NLDAS-2 Mosaic and Noah/VIC, please reverse the sign in the NLDAS-2 Mosaic data. The exception to this is for SBSNOsfc, but only on or after 9 March 2008.

Additionally, another term for the total evapotranspiration (in mass units) can be found here:

   057:EVPsfc:Total evapotranspiration [kg/m^2]



The EVPsfc variable is in mass units and the LHTFLsfc variable is in energy units, but both represent the total upwards water flux. A unit conversion between the two variables (assuming a constant latent heat of vaporization value) shows that the values of these variables should be roughly equal.

Q. Are LDAS data available in other than GRIB format?
Tags:

A. Yes, GLDAS-2.0, GLDAS-2.1, FLDAS, and NCA-LDAS datasets are natively in netCDF-4 format.  GLDAS-1, NLDAS-1, and NLDAS-2 are natively in GRIB-1 format.  However, the NASA GES DISC has enabled on-the-fly conversion from GRIB-1 to netCDF-4 by clicking on the "Subset / Get Data" link available under each collection.  Click on each LDAS collection under "Get Data" to see this link.

Q. What is the average surface skin temperature in the NLDAS-2 model output?
Tags:

A. NLDAS-2 Mosaic, Noah, and VIC provide the hourly instantaneous surface skin temperature (aka, the temperature at exactly 00 minutes of every hour - not the average temperature over the entire hour). The "average" here refers to the average over the entire grid box for all vegetation, bare soil, and snow skin temperatures. For more on the definition of the AVSFTsfc variable, see the "AvgSurfT" description at the ALMA standard pages.

Q. In which direction are the fluxes defined in the LDAS data?
Tags:

A. The majority of the fluxes in all of the LDAS datasets are defined as positive in the "traditional" direction. For some more details on this, please see the ALMA (Assistance for Land-surface Modeling Activities) webpages, such as on the sign conventioninput, and output.

There are some exceptions to this convention, where the sign of the fluxes in the output were inadvertently reversed. Thus, for these variables within the individual datasets listed below, please reverse the sign to make them conform to the positive "traditional" direction:

   In NLDAS-2 Mosaic:
EVBSsfc, EVCWsfc, SBSNOsfc [*], SNOHFsfc, TRANSsfc

[*] - SBSNOsfc should only be reversed before 9 March 2008.
SBSNOsfc data on and after 9 March 2008 does not need to be reversed.


The positive direction of all variables in GLDAS and NLDAS are summarized in this table.

Q. Why is the canopy conductance undefined/wrong in NLDAS-2 Mosaic output?
Tags:

A. On 9 March 2008, the NLDAS-2 Mosaic data was transferred from the retrospective stream (starting back from Jan 1979) to the real-time simulations. Unfortunately, the canopy conductance is not properly defined in the real-time NLDAS-2 production. There are no plans to correct this in the NLDAS-2 Mosaic hourly or monthly output data from after this date.

Q. How can I convert [kg m-2] to [mm]?
Tags:

A. Many of the output fields for water amounts (e.g., precipitation, evapotranspiration, soil moisture, etc.) are given in units of [kg m-2]. Many users prefer units of [mm]. If the assumption is made that the density of the water in the soil is 1000 [kg m-3], then the value in [kg m-2] is identical to the value in [mm]:

   [kg m-2]  ---->  [converting to]  ---->  [mm]

kg       m^3        1000 mm
--   X  -----    X  -------  =  mm
m^2     1000 kg       1 m


The density of water does vary slightly with temperature. Users can use the 2-m air temperature or the soil temperatures (as appropriate) to calculate the density of water for each grid box and time period, if desired.

Q. What value was used for the soil heat capacity in the NLDAS-1/-2 Mosaic model?
Tags:

A. The value used for Mosaic in NLDAS-1 is 175,000 J m-2 K-1, while the value used for Mosaic in NLDAS-2 is 70,000 J m-2 K-1. The name of this variable in the Mosaic code is "CSOIL0". The reason for this difference is explained in detail in Section 5.3 within Robock et al. (2003).

Q. How can I convert [W m-2] to [mm day-1]?
Tags:

A. Many of the output fields for fluxes (e.g., transpiration, direct evaporation from bare soil, etc.) are given in units of [W m-2]. Many users prefer units of [mm day-1]. If assumptions are made to use the value of the latent heat of vaporization of water at 0 degrees Celsius [2.5x10^6 J kg-1] - and that the water density is 1000 [kg m-3], then the conversion from [W m-2] to [mm day-1] is given as:

[W m-2]   ---->   [converting to]   ---->   [mm day-1]

W          kg           J         m^3       1000 mm     86400 sec     mm
---  X  ----------  X  -----  X  -------  X  -------  X  ---------  =  ---
m^2     2.5x10^6 J     W sec     1000 kg       1 m          day        day


The latent heat of vaporization of water and the density of water both vary slightly with temperature. Users can use the appropriate temperature to calculate these values for each grid box and time period, if desired. Also, note that the latent heat of fusion should be used when converting sublimation.

Q. What geographic coordinate system was used to generate the NLDAS grid?
Tags:

A. No particular geographic coordinate system was consulted when the NLDAS grid was originally configured. The grid boxes are simply 1/8th-degree boxes with the center of the lower-left grid box at 25.0625 N and 124.9375 W. The details of the grid are available here and here.

Q. How can I obtain volumetric soil moisture [m^3 m-3] from the LDAS data?
Tags:

A. The LDAS datasets currently provide soil moisture values in units of [kg m-2] over the entire thickness of the layer indicated. To convert to units of average volumetric soil moisture [m^3 m-3] over the same thickness, all you need to do is divide the [kg m-2] value by the thickness of the layer in [mm]. The assumption is made that the density of the water in the soil is 1000 [kg m-3].

LDAS SM amount  ---->   [converting to]   ---->   LDAS SM volumetric

kg       m^3        1000 mm          1
--   X  -----    X  -------  X  -----------     = volumetric soil moisture
m^2     1000 kg        1 m      thickness of
layer in mm


As an example, for the 0-10cm layer, just divide by 100mm to convert the data from [kg m-2] to volumetric soil moisture. For the 10-40cm layer, divide by 300mm, and so on for the other soil moisture layers. The volumetric soil moisture values range between wilting point and porosity (e.g., ~0.01 to ~0.5). If we further divide the volumetric soil moisture [m^3 m-3] by porosity [m^3 m-3], we will get the soil moisture fraction which ranges from 0 to 1.

Q. Is there a shapefile available for the NLDAS grid?
Tags:

A. Yes, a shapefile (and associated files) for GIS can be found here.

You can also subset by shapefiles through Giovanni.

Users can select a bounding box region or subset using shapefiles, including countries, U.S. states, and watersheds.

Q. Why does Python/GDAL plot temperature in Celsius instead of Kelvin?
Tags:

A. All temperature fields in the LDAS datasets are in units of Kelvin. However, some users have reported that when GRIB-1 data is plotted in Python/GDAL, the values appear to be in units of Celsius. The GDAL GRB driver has an option to automatically convert units to "metric" for versions of GDAL >= 1.9.0. In Python, adding the line:

        "gdal.SetConfigOption('GRIB_NORMALIZE_UNITS', 'NO')"


at the beginning of the script will result in temperature units being read in and displayed correctly in Kelvin.