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.
FAQ's
Filter By System:
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.
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.
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.
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.