Incorporation of Passive Microwave Brightness Temperatures in the ECMWF Soil Moisture Analysis
نویسنده
چکیده
For more than a decade, the European Centre for Medium-Range Weather Forecasts (ECMWF) has used in-situ observations of 2 m temperature and 2 m relative humidity to operationally constrain the temporal evolution of model soil moisture. These observations are not available everywhere and they are indirectly linked to the state of the surface, so under various circumstances, such as weak radiative forcing or strong advection, they cannot be used as a proxy for soil moisture reinitialization in numerical weather prediction. Recently, the ECMWF soil moisture analysis has been updated to be able to account for the information provided by microwave brightness temperatures from the Soil Moisture and Ocean Salinity (SMOS) mission of the European Space Agency (ESA). This is the first time that ECMWF uses direct information of the soil emission from passive microwave data to globally adjust the estimation of soil moisture by a land-surface model. This paper presents a novel version of the ECMWF Extended Kalman Filter soil moisture analysis to account for remotely sensed passive microwave data. It also discusses the advantages of assimilating direct satellite radiances compared to current soil moisture products, with a view to an operational implementation. A simple assimilation case study at global scale highlights the potential benefits and obstacles of using this new type of information in a global coupled land-atmospheric model.
منابع مشابه
Sensitivity of L-band Brightness Temperatures to Soil Roughness Parameterization. the Smosrex Case Study
The Soil Moisture and Ocean Salinity (SMOS) satellite mission of the European Space Agency (ESA), scheduled for launch in summer 2009, responds to the growing need for an accurate estimate of the root-zone soil water content. SMOS will operate at L-band frequencies, where the microwave signal is more sensitive to the soil water content. The European Centre for Medium-Range Weather Forecasts (EC...
متن کاملThe Ecmwf Surface Analysis: Use of Active and Passive Microwave Data for Soil Moisture Analysis
This paper presents the European Centre for Medium-Range Weather Forecasts (ECMWF) soil moisture (SM) analysis system and its recent developments which enables the assimilation of active and passive microwave data. The current operational SM analysis used in the Integrated Forecast System (IFS), is based on an Optimal Interpolation (OI) scheme using proxy observations (2 m air temperature and r...
متن کاملAssimilating remote sensing data in a surface flux–soil moisture model
A key state variable in land surface–atmosphere interactions is soil moisture, which affects surface energy fluxes, runoff and the radiation balance. Soil moisture modelling relies on parameter estimates that are inadequately measured at the necessarily fine model scales. Hence, model soil moisture estimates are imperfect and often drift away from reality through simulation time. Because of its...
متن کاملComparing ERA-40 based L-band brightness temperatures with Skylab observations: A calibration / validation study using the Community Microwave Emission Model
The community microwave emission model (CMEM) has been used to compute global L-band brightness temperatures at the top of the atmophere. The input data comprise surface fields from ECMWF’s 40-year Re-Analysis (ERA-40), vegetation data from the ECOCLIMAP data set, and the Food and Agriculture Organization (FAO) soil data base. Modelled brightness temperatures have been compared against (histori...
متن کاملScaling Properties of L-band Passive Microwave Soil Moisture: From SMOS to Paddock Scale
Remote sensing of soil moisture is a powerful and inexpensive way to map surface soil moisture for a range of applications, including weather prediction, water resources management and irrigation practices. Passive microwave sensors operating at L-band wavelength have shown the most potential for this task. However, this technology faces some major challenges, mostly related to correct interpre...
متن کاملذخیره 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 ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Remote Sensing
دوره 7 شماره
صفحات -
تاریخ انتشار 2015