Intercomparison of the JULES and CABLE land surface models through assimilation of remotely sensed soil moisture in southeast Australia

نویسندگان

  • Gift Dumedah
  • Jeffrey P. Walker
چکیده

Numerous land surface models exist for predicting water and energy fluxes in the terrestrial environment. These land surface models have different conceptualizations (i.e., process or physics based), together with structural differences in representing spatial variability, alternate empirical methods, mathematical formulations and computational approach. These inherent differences in modeling approach, and associated variations in outputs make it difficult to compare and contrast land surface models in a straight-forward manner. While model intercomparison studies have been undertaken in the past, leading to significant progress on the improvement of land surface models, additional framework towards identification of model weakness is needed. Given that land surface models are increasingly being integrated with satellite based estimates to improve their prediction skill, it is practical to undertake model intercomparison on the basis of soil moisture data assimilation. Consequently, this study compares two land surface models: the Joint UK Land Environment Simulator (JULES) and the Community Atmosphere Biosphere Land Exchange (CABLE) for soil moisture estimation and associated assessment of model uncertainty. A retrieved soil moisture data set from the Soil Moisture and Ocean Salinity (SMOS) mission was assimilated into both models, with their updated estimates validated against in-situ soil moisture in the Yanco area, Australia. The findings show that the updated estimates from both models generally provided a more accurate estimate of soil moisture than the open loop estimate based on calibration alone. Moreover, the JULES output was found to provide a slightly better estimate of soil moisture than the CABLE output at both near-surface and deeper soil layers. An assessment of the updated membership in decision space also showed that the JULES model had a relatively stable, less sensitive, and more highly convergent internal dynamics than the CABLE model. Crown Copyright 2014 Published by Elsevier Ltd. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Remotely Sensed Soil Moisture over Australia from AMSR-E

Soil moisture can significantly influence atmospheric evolution. However the soil moisture state predicted by land surface models, and subsequently used as the boundary condition in atmospheric models, is often unrealistic. New remote sensing technologies are able to observe surface soil moisture at the scales and coverage required by numerical weather prediction (NWP), and there is potential t...

متن کامل

Land Surface Model Data Assimilation for Atmospheric Prediction

Accurate latent and sensible heat flux prediction in response to land surface soil moisture at midlatitudes has been shown to be as important as sea surface temperature in making accurate precipitation prediction at mid-latitudes over land (Koster et al., 2000). Unfortunately, land surface models typically give a poor prediction of soil moisture and atmospheric feedback, with large differences ...

متن کامل

Soil moisture initialization for climate prediction: Assimilation of scanning multifrequency microwave radiometer soil moisture data into a land surface model

[1] Climate model prediction skill is currently limited in response to poor land surface soil moisture state initialization. However, initial soil moisture state prediction skill can potentially be enhanced by the assimilation of remotely sensed near-surface soil moisture data in off-line simulation. This study is one of the first to evaluate such potential using actual remote sensing data toge...

متن کامل

Recent Advances on Soil Moisture Data Assimilation

This study reviews recent progress on soil moisture data assimilation. Data assimilation is a process of merging observations with a system dynamic model to provide an improved estimate of the states of the environment. The application of data assimilation in hydrology is relatively new, however, rapid progress has been made in the last decade or so with the available remotely sensed soil moist...

متن کامل

A Novel Method for Quantifying Value in Spaceborne Soil Moisture Retrievals

A novel methodology is introduced for quantifying the added value of remotely sensed soil moisture products for global land surface modeling applications. The approach is based on the assimilation of soil moisture retrievals into a simple surface water balance model driven by satellite-based precipitation products. Filter increments (i.e., discrete additions or subtractions of water suggested b...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2014