CEOP-AEGIS Periodic Report #1

CEOP-AEGIS (GA n° 212921) Periodic Report no. 1

PROJECT PERIODIC REPORT

Grant Agreement number: 212921

Project acronym: CEOP-AEGIS

Project title: Coordinated Asia-European long-term Observing system of Qinghai – Tibet
Plateau hydro-meteorological processes and the Asian-monsoon systEm with Ground satellite
Image data and numerical Simulations

Funding Scheme: CP-SICA

Date of latest version of Annex I against which the assessment will be made: 25/08/2009

Periodic report: 1st x 2nd ! 3rd ! 4th !
Period covered: from 1/5/2008 to 31/10/2009

Name, title and organisation of the scientific representative of the project's coordinator1:

Prof.dr. Massimo Menenti Faculty of Aerospace Engineering, TU Delft, Delft, The Netherlands

Tel: +31 15 2784244

Fax: +31 15 278348

E-mail: M.Menenti@tudelft.nl

Project website2 address: http://www.ceop-aegis.org/

1
Usually the contact person of the coordinator as specified in Art. 8.1. of the grant agreement
2
The home page of the website should contain the generic European flag and the FP7 logo which are available in electronic
format at the Europa website (logo of the European flag: http://europa.eu/abc/symbols/emblem/index_en.htm ; logo of the 7th
FP: http://ec.europa.eu/research/fp7/index_en.cfm?pg=logos). The area of activity of the project should also be mentioned.

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Declaration by the scientific representative of the project coordinator1

1
I, as scientific representative of the coordinator of this project and in line with the obligations as stated in
Article II.2.3 of the Grant Agreement declare that:

! The attached periodic report represents an accurate description of the work carried out in this project for
this reporting period;

! The project (tick as appropriate):

x has fully achieved its objectives and technical goals for the period;

! has achieved most of its objectives and technical goals for the period with relatively minor
3
deviations ;

! has failed to achieve critical objectives and/or is not at all on schedule . 4

! The public website is up to date, if applicable.

! To my best knowledge, the financial statements which are being submitted as part of this report are in line
with the actual work carried out and are consistent with the report on the resources used for the project
(section 6) and if applicable with the certificate on financial statement.

! All beneficiaries, in particular non-profit public bodies, secondary and higher education establishments,
research organisations and SMEs, have declared to have verified their legal status. Any changes have
been reported under section 5 (Project Management) in accordance with Article II.3.f of the Grant
Agreement.

Name of scientific representative of the Coordinator1: .Prof. Dr. Massimo Menenti.

Date: ....21..../ ...12......./ 2009......

Signature of scientific representative of the Coordinator1:

3
If either of these boxes is ticked, the report should reflect these and any remedial actions taken.
4
If either of these boxes is ticked, the report should reflect these and any remedial actions taken.

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Project Title

Coordinated Asia-European long-term Observing system of Qinghai – Tibet
Plateau hydro-meteorological processes and the Asian-monsoon systEm with
Ground satellite Image data and numerical Simulations
CEOP AEGIS

Thematic Priority: ENV.2007.4.1.4.2. Improving observing systems for water resource management

Start Date of the Project: 1 – May – 2008 Duration: 48 months

Report Title
1st Periodic Report
May 1st 2008 – October 31st 2009

Massimo Menenti1, Li Jia2 and Jerome Colin3
1 Faculty of Aerospace Engineering, TU Delft, Delft, The Netherlands,
2 Alterra, Wageningen University and Research Centre, Wageningen, The Netherlands
3 Image Sciences, Computing Sciences and Remote Sensing Laboratory, University of Strasbourg, Illkirch,
France

Date: December 21st 2009
Version: 1.0

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Coordinator contact details

Prof.dr. Massimo Menenti

E-mail: M.Menenti@tudelft.nl
Web site: www.lr.tudelft.nl/olrs
Telephone: +31 15 2784244 Fax: +31 15 278348

Deputy coordinator details:
Dr. Li Jia
E-mail: li.jia@wur.nl
Web site: http://www.alterra.wur.nl/UK/
Telephone: +31 317 481610 Fax: +31 317 419000

Contractors involved

BENEFICIARY BENEFICIARY NAME BENEFICIARY COUNTRY DATE DATE EXIT
NUMBER SHORT NAME ENTER PROJECT
PROJECT
1 CO Université de Strasbour LSIIT UDS France 1 48
2 CR International Institute for Geo- ITC The 1 48
information science and Earth Netherlands
Observation
3 CR ARIES Space ARIES Italy 1 48
4 CR University of Bayreuth UBT Germany 1 48
5 CR Alterra - Wageningen University ALTERRA The 1 48
and Research Centre Netherlands
6 CR University of Valencia UVEG Spain 1 48
7 CR Institute for Tibetan Plateau ITP China 1 48
Research – Lhasa, Tibet
8 CR China Meteorological CAMS China 1 48
Administration – Beijing
9 CR Beijing Normal University– BNU China 1 48
Beijing
11CR University of Tsukuba – UNITSUK Japan 1 48
12 CR WaterWatch WAWATCH The 1 48
Netherlands
13 CR Cold and Arid Regions CAREERI China 1 48
Environmental and Engineering
Research Institute – Lanzhou,
Gansu
14 CR University of Ferrara UNIFE Italy 1 48
15 CR Institute of Geographical IGSNRR China 1 48
Sciences and Natural Resources
Research CAS – Beijing
16 CR Institute for Remote Sensing IRSA China 1 48
Applications CAS – Beijing
17 CR Future Water FUWATER The 1 48
Netherlands
18 CR Delft University of Technology TUD The 12 48
Netherlands
19 CR National Institute of Technology NIT India 12 48

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CO = Coordinator CR = Contractor

1. Publishable summary
CEOP AEGIS 1st Periodic Report: May 1st 2008 – October 31st 2009
Summary

http://www.ceop-aegis.org/

Objectives
The goal of this project is to:
1. Construct out of existing ground measurements and current / future satellites an observing
system to determine and monitor the water yield of the Plateau, i.e. how much water is finally going
into the seven major rivers of SE Asia; this requires estimating snowfall, rainfall, evapotranspiration
and changes in soil moisture;
2. Monitor the evolution of snow, vegetation cover, surface wetness and surface fluxes and
analyze the linkage with convective activity, (extreme) precipitation events and the Asian Monsoon;
this aims at using monitoring of snow, vegetation and surface fluxes as a precursor of intense
precipitation towards improving forecasts of (extreme) precipitations in SE Asia.

Work Performed
The project started with a kick-off meeting held in Beijing on May 1st – 5th 2008 attended by 65
participants. In preparation of the meeting all partners were requested to define more precisely their
contribution and roles. This material provided a good basis for a productive meeting. A project mailing
list system was established to handle internal communication, given the complexity of the consortium.

The 1st Annual Progress Meeting was held in Milano, Italy on June 29th through July 3rd, including a
joint workshop with the CEOP High Elevation Initiative (HE) and an internal businness meeting
dedicated to a review of progress and to the preparation of the 1st Periodic Report. The meeting was
attended by 30 participants. In preparation of the meeting all partners were requested to prepare an
overview presentation for each Work Package.

The material prepared for the meetings is available on the project web site. To date there are 112
registered Team Members.

During the 1st six months period work focused on three main objectives:
1. Define the work plan and detailed contributions of partners;
2. Perform local experiments and collect first data for validation of algorithms and models;
3. Review and improvements of algorithms and models.
Ad.1. In order to identify more precisely roles and responsibilities all partners were requested to
elaborate further the work plan now included in the Description of Work. This includes now a more
precise description of (sub)-tasks and of elements of contractual deliverables with individual
responsibilities clearly identified.
Ad.2. Field experiments were carried out during the reporting period as described under “Main
Results” below
Ad.3 Work towards improvement of retrieval algorithms, process models and land-atmospheric models
advanced in several directions. This included collection and preparation of data sets acquired by space-
and airborne platforms to test algorithms and models, numerical experiments to document the
performance of algorithms and process models and improvement of algorithms and models in those
cases where the causes of poor performances was known already. More details are provided under

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“Main Results” below.

During the 2nd six-months period work focused on five main objectives:
1. Finalize and implement Grant Agreement, including accession of partners;
3. Review and improvements of algorithms and models.
4. Design, development and use of atmospheric and water balance models;
5. First analyses of time series of drought and flood indicators
Ad.1. The Grant Agreement was completed and signed on December 4th 2008. Accession forms were
signed by all partners except Partner NIH. As explained below, the National Institute of Technology,
Rourkela, will replace NIH and carry out all planned tasks.
Ad.2. Field experiments were carried out during the reporting period and data analysis started as
described under “Main Results” below. Work concentrated on the analysis of ground measurements on
land – atmosphere interactions collected at the permanent observatories on the Plateau.
Ad.3 Work towards improvement of retrieval algorithms, process models and land-atmospheric models
advanced towards the implementation of specific improvements emerged in the previous period. This
included development of new procedures to deal with complex terrain in radiative transfer models and
retrieval algorithms, new algorithms for the retrieval of land surface temperature and radiative fluxes at
the surface and preparation of data sets on precipitation measurements with rain radars.
Ad.4 Work advanced both on the assessment of connections between land surface conditions with
convective activity and precipitation events and on the design of the regional water balance model to
integrate all observations for the entire Plateau.
Ad. 5 Work was also initiated on the analysis of time series of satellite data towards the early detection
of anomalies in land surface conditions and early warning on droughts and floods. Because of the need
for extended data records, this element of the project relies on existing data sets, besides the ones
generated by the project. During this 6-months period work concentrated on development of
procedures for the detection of anomalies, based on a moving window analysis and comparison with
the climatology of the land surface variables under consideration. Different indicators were evaluated.

During the 3rd six-months period work focused on the same five main objectives as in the 2nd six-
months period:
1. Finalize documents for the amendments of the Grant Agreement, including accession of new
partners;
3. Improvements of algorithms and models.
4. Development and use of atmospheric and water balance models;
5. First analyses of time series of drought and flood indicators.
Ad.1.The access of two new partners, i.e. NIT and TUD required a significant amount of time and
work. Progress of the project was monitored through a series of Skype conferences, the 1st Annual
Progress Meeting and additional working meetings in 2009: Beijing August and October, Lanzhou in
August and Roorkee in September.
Ad.2. Field work intensified during this period. In addition to the normal operation of the
observatories, new instruments were installed to improve observations of radiative and turbulent heat
fluxes and to characterize the size distribution of rain droplets, necessary to improve accuracy of
retrievals by rain radars (see Main Results below).
Ad.3 Work towards improvement of retrieval algorithms was focused on atmospheric correction of
satellite measurements in the VNIR-SWIR, TIR and microwave regions. This included dealing with
retrieval of Land Surface Variables using data acquired by the new satellites HJ-1B (China) and IRS
(India). The new algorithms developed in the previous period were applied to generate time series of
Snow Covered Area and Snow Water Equivalent. The development of a new data processing system
for Surface Energy Balance analyses based on the combination of satellite measurements with PBL

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fields generated by the GRAPES NWF model was completed.
Ad.4 Significant advances have been achieved towards analysis of land – atmosphere interactions with
atmospheric models and towards regional modeling of the Plateau water balance. A full forecast run
was performed for the entire year 2008 with the system GRAPES. A study of the sensitivity Monsoon
Convective Systems (MCS) to land surface conditions was carried out with the model WRF at the
University of Tsukuba and the prototype water balance model of the Qinghai –Tibet Plateau was
implemented at a 5 km x 5 km spatial resolution and applied to obtain daily rainfall excess and river
flow over the entire domain
Ad.5 Several results became available on different indicators relevant to drought and flood early
warning. Work focused on two parallel streams: improving algorithms and analyzing available time
series of satellite data. A new version of the HANTS algorithm was released and a new model to
compute daily EvapoTranspiration (ET) was developed and applied. Time series of satellite data on
Land Surface Temperature (LST), photosynthetic activity (EVI, fAPAR) and soil wetness were
analyzed to document inter-annual variability, detect anomalies and evaluate them as precursor
indicators for drought and flood early warning.

Main Results
Field experiments During the 1st Reporting Period the existing system of Plateau observatories was
improved by adding several instruments: gauges to measure total precipitation above 6000 m, two
Long Path Scintillometers, three disidrometers to measure the size distribution of water droplets, four
sets of radiometers to measure the four components of the radiative balance and one suntracker to
measure direct irradiance.
Several Co-Investigators participated in a major RS experiment covering an entire watershed on the
northern rime of the Plateau: the WATER project provided invaluable detailed data to improve and
validate several algorithms to be used within CEOP-AEGIS. Collection of soil moisture and
temperature measurements at the Maqu site for the validation of algorithms to retrieve soil moisture
continued. An expedition to the the Yamdruk-tso lake basin and Qiangyong Glacier was carried out.
The Naimona'Nyi ice core was processed in cold room.
The first eddy-covariance measurements of turbulent flux densities became available after quality
characterization and gap filling. The analysis of the data collected at the NamCo observatory revealed
a significantly higher number of free convection events in the monsoon period. The results have been
published in JGR. An approach to upscale flux measurements to the grid scale of meso-scale models
and remote sensing data was developed.

Work towards improvement of retrieval algorithms, process models and land-atmospheric models
advanced in several directions:
- Collection and preparation of several data sets comprising multi-spectral, multi-angular
radiometric data;
- Evaluation of land – atmosphere models
- Review and preparation of codes of radiative transfer models of the soil-vegetation system
- Improvement and generalization of multi-scale model of land surface energy balance;
- Estimation and mapping of land – atmosphere heat and water exchanges with ASTER multi-
spectral radiometric data for the areas surrounding the ITP observatories on the Plateau;
- Preparation of microwave radiometer data (AMSR-E) for the evaluation of soil moisture
retrieval algorithms;
- Improvement of model to characterize the diurnal cycle of Land Surface Temperature using
Feng Yun infrared data and use of the CLM to relate the diurnal LST cycle to soil moisture
- Improvements in the meso-scale land-atmospheric model GRAPES of CMA; preliminary case
studies performed and hypotheses identified;
- Preparation of data sets for the evaluation of candidate water balance models; evaluation of
snow-melt-runoff models using MODIS and AMSR-E satellite data;

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- Preparation of MODIS time series (LAI/fAPAR, Vis, and LST) for entire China;
- Improvements in the algorithms to detect and predict anomalies in vegetation development;
- Case studies on drought events combining ground and satellite data;

2nd period
- Analysis of sample data set HeiHe basin with simultaneous multi-angular, multi-spectral and
lidar observations of vegetation canopies
- Topography correction inserted in the RT modeling system for the VNIR, SWIR and TIR
spectral ranges.
- Development of a simple model to describe the thermal directional radiation in rugged terrain;
- A topographic correction algorithm for albedo retrieval in rugged terrain was developed.
- Development of a preliminary algorithm to calculate land surface temperature from AMSR-E
data;
- Developing the concept of a new radiative transfer model, capable of simulating the seasonal
changes of canopy structure;
- Development of new version of MSSEBS (vers. 2.0.2) SEB algorithm;
- Development of algorithm for regional estimation of net radiation flux;
- Determination the surface albedo, surface temperature, vegetation fractional cover, NDVI,
LAI and MSAVI over whole Tibetan Plateau;
- Implementation of a radiative transfer soil moisture retrieval method using ASCAT data
- Comparison of in situ data collected by Maqu soil moisture monitoring network with AMSR-E
VUA-NASA satellite soil moisture products;
- Collected the soil moisture and temperature data of 20 SMTMS, and replaced 4 temperature
and moisture probes;
- Processing the raw precipitation radar data in the Tibetan Plateau and provide the gridded
precipitation data for case studies;
- Final revision of paper on the nighttime monsoon precipitation over the TP was submitted to
JMSJ and accepted in March
- Simulation of daily snow cover using daily and eight-day MODIS snow cover products and
meteorological observation;
- Analysis of glacier and lake changes using observed data and RS data in the Nam Co Basin;.

3rd period
Development of algorithms and retrieval of canopy structure from airborne LIDAR;
- Development of algorithm for atmospheric corrections of AMSR-E (microwave);
- Generalized procedure for atmospheric correction based on an ensemble of MODTRAN
simulations;
- Automation of procedures to generate LST from MODIS data;
- Implementation and first tests on generic algorithm for retrieval of LAI and fCover;
- Development of new algorithm to retrieve LST from HJ-1B (China) and IRS (India) data;
- Development of new Angular & Spectral Kernel based BRDF model for the normalization of
data acquired with different angular and spectral configurations;
- First test of SEB algorithm combining satellite data for land surface observations and PBL
fields generated with high resolution atmospheric model (GRAPES);
- Evaluation against turbulent heat flux measurements of SEB estimates based on ASTER data;
- Mosaic of rain-rates observed with rain radars over the Plateau have been generated and
delivered to other investigators for calibration of algorithms based on satellite data;
- Improved algorithm for retrieval of snow covered area from MODIS
has been developed and evaluated against observations at higher spatial resolution ( TM);

Design, development and use of atmospheric and water balance models.

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2nd period
- The first numerical experiments with the GRAPES land – atmosphere modeling and data assimilation
system were performed and evaluated:
- Sensitivity experiments of different soil initial conditions on the development of convections
by using 2-km resolution of GRAPES_Meso
- Detection of Meso-scale Convective System (MCS) on the TP was done for the passed six
years using METEOSAT-IR data
- Preparing GIS files for hydrological modeling, including boundary, DEM. Slope, aspect,
stream network.
-Model selection and algorithm comparison report for Plateau water balance monitoring tool was
completed

3rd period.
- The system GRAPES of CMA has been applied to generate forecasts for the entire year 2008;
- A study on the sensitivity of MCS to land surface heating has started using the WRF numerical
model at the Univ. Tsukuba;
- Gridded climate data have been used to compute the water balance of the Headwaters of the
Yellow River Basin and to compute potential ET;
- The prototype of the Qinghai – Tibet Plateau distributed water balance model has been
implemented and applied to compute for the year 2000 daily water balance for each 5 km x 5 km grid
and water routing; model riverflow at seven selected sections is being compared with observations;
-Model parameterization of glaciers mass balance is being applied to the Zhadang glacier; in- depth
case – study including the use of satellite data is in progress;

Analyses of time series of drought and flood indicators
2nd period
-Available satellite data were retrieved, time series were constructed and first analyses were
performed:
-Algorithm development on drought monitoring by time series analysis of anomalies in several land
surface parameters;
-Using time series of VTCI AVI, VCI and TCI as indicators for the estimation of the drought
impacts;
-Analysis of time series meteorological data (air temperature and precipitation, wind speed, air
humidity, solar radiation, etc)
-Development of soft computing techniques based on ANN and Fuzzy logic model for real time flood
forecasting

3rd period
- A new version of the HANTS algorithm for time series analysis of satellite data has been
released;
- A multi-annual MODIS data set covering the Plateau and surrounding regions has been created
after improved cloud screening and used to compute at-surface net radiation in addition to LST, EVI
and fAPAR;
- Analysis of a 25 years climatology of AVHRR LST and NDVI has been completed;
- Time series of SPI and VTCI have been generated and used as an indicator for drought
forecasting;
- A new ET model has been applied to evaluate potential yield loss in the winter 2008;
- A first evaluation of AMSR-E time series as an indicator of soil wetness and to detect
(positive) anomalies has been completed for the Plateau and Northern India;

Expected Final Results

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Data base containing ground observations, satellite data and higher level products, hydrologic
and atmospheric model fields for the period 2008 – 2010 over the Qinghai – Tibet Plateau.
System to generate daily streamflow in the upper catchment of all major river in SE Asia
gridded to 5 km x 5 km.
Potential Impact and Use of Results
Implementation and demonstration of an observing system of water balance and water flow on
and around the Qinghai – Tibet Plateau will provide to all countries information on water
resources and the role of the Plateau in determining weather and climate in the region.

2. Project objectives for the period
The goal of this project is to:
1. Construct out of existing ground measurements and current / future satellites an observing system to
determine and monitor the water yield of the Plateau, i.e. how much water is finally going into the seven major
rivers of SE Asia; this requires estimating snowfall, rainfall, evapotranspiration and changes in soil moisture;
2. Monitor the evolution of snow, vegetation cover, surface wetness and surface fluxes and analyze the
linkage with convective activity, (extreme) precipitation events and the Asian Monsoon; this aims at using
monitoring of snow, vegetation and surface fluxes as a precursor of intense precipitation towards improving
forecasts of (extreme) precipitations in SE Asia.

During the first year of the project, emphasis in all WP-s will be on review tools, experimental protocols,
algorithms and models. On this basis, the elements of the investigations next step will be identified in detail: the
first detailed description of new retrieval algorithms will be available, data analysis protocols will be agreed,
modelling experiments will be designed and the organization of data base will be consolidated.

During the second year of the project, work will be focused on the Algorithms Theoretical Basis Documents and
potential progresses towards community model to determine land-atmosphere energy and water fluxes with
multi-spectral satellite images. First analysis of datasets with candidate algorithms and models will be presented,
with preliminary results on time series analysis of Plateau water balance, droughts and floods indicators.

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3. Work progress and achievements during the period
Please provide a concise overview of the progress of the work in line with the structure of Annex I of the Grant Agreement.

For each work package -- except project management, which will be reported in section 3.5--please provide the
following information:

• A summary of progress towards objectives and details for each task;

• Highlight clearly significant results;

• If applicable, explain the reasons for deviations from Annex I and their impact on other tasks as well as on
available resources and planning;

• If applicable, explain the reasons for failing to achieve critical objectives and/or not being on schedule and explain
the impact on other tasks as well as on available resources and planning (the explanations should be coherent with
the declaration by the project coordinator) ;

• a statement on the use of resources, in particular highlighting and explaining deviations between actual and
planned person-months per work package and per beneficiary in Annex 1 (Description of Work)

• If applicable, propose corrective actions.

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3.1 Work progress in WP 1 and achievements during the period
" A summary of progress towards objectives and details for each task
Task 1.1
The in-situ data has been collected in the observation network of the GAME/Tibet and CAMP/Tibet and
the Mt. Everest station(QOMS), the Nam Co station(NAMOR) and the Linzhi Station(SETS) of the
TORP(Tibetan Observation and Research Platform) and Namco site of Tip( formally KEMA Station of TiP).
Four components radiation system were set up at the sites of D110, MS3608, Namco area, and Lhasa branch
of ITP (formally Yakou of Namco). Field trip to the Yamdruk-tso lake basin and Qiangyong Glacier was
performed. Precipitation, lake water and river water samples has been collected at 3 stations in this basin for
isotope analysis in the laboratory in Beijing. Glacier shallow ice cores were drilled at 6100m of the glacier to
rebuild the annual precipitation data in high elevation region. Daily atmospheric vapor samples were collected
at Lhasa and are still on going. Fig.1 to Fig.4 are the sites layout and the stations of this WP.

(a) (b)
Fig.1.1 The geographic map and the sites layout during the GAME/Tibet and the CAMP/Tibet.
(a) GAME/Tibet; (b) CAMP/Tibet.

Fig.1.2 The instruments in Mt.Everest station, Namco station and Linzhi station of ITP/CAS

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Fig.1.3. Sites of the four components radiation system over the Tibetan Plateau.

The seasonal and inter-annual time scale of the exchange of surface heat flux, momentum flux, water
vapour flux, surface and soil moisture over the different land surfaces of the Tibetan Plateau, and the structure
characteristics of the Surface Layer (SL) and Atmospheric Boundary Layer (ABL) were analyzed in the last one
and half year. The aerodynamic and thermodynamic variables were determined over the different land surfaces
of the Tibetan Plateau. The characteristics of precipitation and atmospheric water vapour transport over and
surrounding the Tibetan Plateau area were analyzed.
Task 1.2:
A technical report was prepared for the documentation of the flux calculation procedure in order to provide
all users of flux data the necessary information. Furthermore, within an UBT field trip to the Tibetan Plateau
(June-August 2009) a workshop was held from June 29th to July 1st for participants of ITP and CAREERI about
the usage of the UBT software packages for EC data post processing, footprint and QA/QC techniques. This
ensures a uniform data processing for all ground truth EC stations related to CEOP AEGIS, which is the task of
ITP and CAREERI according to the data policy rules.
Task 1.3:
In order to apply detailed footprint analysis for the EC stations, all necessary site information to prepare the
required land use maps were collected for Bj, Namco and Qomolangma site during the UBT field trip in summer
2009. Detailed footprint analysis already exists for Namco in late 2005 and from Oct 2005 up to Sept 2006, but

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has to be refined with actual flux data. Missing site information for Linzhi station will be gathered during a post
workshop excursion in July 2010 right after the CEOP workshop in Lhasa and the calculation of the footprint
analysis starts as soon as the flux data is available.

Task 1.4:
The gap filling will be processed following a procedure developed by Ruppert et al., but an extension to the
latent heat flux has to be made, for which data from Tibetan Plateau are necessary. The procedure starts as soon
as the flux data is available.

Task 1.5:
In order to find an adequate path for LAS measurements at Qomolangma site possible solutions were
investigated during the UBT field survey in summer 2009. The LAS system was set up in Mt.Everest
(Mt.Qomolangma) station in November, 2009 (Fig.4).Afterwards a preliminary footprint report was elaborated
examining the possible paths and hinting at the optimal solution. The results were documented within a special
report, the selected path and its respective footprint is shown in Fig.5.

Fig.4 The LAS system in Mt.Qomolangma(Mt.Everest ) Station

Fig.5: Selected path (solid red line) for the LAS measurements at Qomolangma site with source contributions for a
footprint “climatology” of the expected wind distribution, unstable stratification, zm = 20m.

A set of LAS was installed and aligned in Naqu BJ station (31°22'7.18"N, E91°53'55.36"E) in July, 2009, Naqu
area of Tibet. The underlying surface of observation site is alpine meadow. The effective height and path length
is 8.63 m and 1560m, respectively. Combined with the measurements of Eddy Covariance system (EC) and
Automatic Weather Station (AWS), the performance of LAS under Tibetan plateau environment has been
checked.

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Fig.6 The LAS system in Naqu BJ station

Task 1.6:
A first error analysis of flux data was given in a technical report. This will be updated as soon as the flux data is
available.

Task 1.7:
For tasks 1.6 and 1.7 a footprint scheme is currently developed by UBT and will soon be published in a peer
reviewed journal. A foundation for this scheme was elaborated within a Master thesis, for a description see
section results. Furthermore, a experiment was performed nearby the Namco Station (Fig.7). The investigations
cover EC, energy balance and soil moisture measurements for a period from June 26th to August 8th and was set
up directly at the shoreline of a small lake, pre-located to the Namco lake. This measurements will be used to
validate the footprint related upscaling scheme and serve for parameterization of fluxes above lake surface and
Kobresia mats. A documentation of the experiment is now available.

Fig.7. Turbulence measurements at Namco lake

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• Highlight clearly significant results

1. Underlying surface roughness lengths under the quality control of observation were determined

Eddy covariance flux data collected from ITP/CAS three research stations (Qomolangma station, Namco
station and Southeast Tibet station-Linzhi station) on the Tibetan Plateau are used to analyze the variation of
momentum transfer coefficient (CD), heat transfer coefficient (CH), aerodynamic roughness length (z0m), thermal
roughness length (z0h) and excess resistance to heat transfer (kB-1). All the data was checked under the
quality control firstly. The monthly average surface roughness, bulk transfer coefficient and excess resistance to
heat transfer at all three sites are obtained. Momentum transfer coefficient (CD) is quite changeable during the
day but relatively stable and lower in the night. The parameter kB-1 exhibits clear diurnal variations with lower
values in the night and higher values in the daytime, especially in the afternoon. Negative values of kB-1 are often
observed in the night for relatively smooth surfaces on the Tibetan Plateau.

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(a)

(b)

Fig. 8 Frequency distribution of ln(z0m) at Nam Co station in September(a) and October(b)

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(a) (b)

(c)

Fig. 9 The diurnal variations of observed excess resistance to heat transfer (kB-1)at Qomolangma station(a), Namco station(b)
and Southeast Tibet station(c) in March

2 Variation characteristics of radiation of the wetland surface in the Northern Tibetan Plateau
Based on the observed data at Automatic Weather Site(AWS) of MS3478 in the typical wetland of northern
Tibetan Plateau from March 2007 to February 2008. The seasonal mean diurnal, seasonal and annual variation
features of the radiation budget components were analyzed in this paper. The results indicated that in spring
diurnal variations of both global solar radiation and the reflective radiation were larger than in other seasons, and
their annual variations were double-peak-shaped, but the phases were different. The distributions of both the
diurnal variation and the annual variation of the earth surface long-wave radiation were unsymmetrical. Annual
variation of the earth effective radiation was of bimodal pattern. One peak corresponded to March and April,
when frozen soil melted, while the other to October, when froze soil froze. Net radiation mainly concentrated in
May, June and July, accounting for 40.14% of the total, indicating that in late spring and early summer the
region's surface had obtained the largest net energy, which played a decisive role for the formation of terrestrial
heat and the heating of the atmosphere.

3. Analysis onpotential evapo-transpiration and dry-wet condition in the seasonal frozen soil region of
northern Tibetan Plateau
This study was based on the observed data at Automatic Weather Site(AWS) of MS3478 in the seasonal
frozen soil region of northern Tibetan plateau from March 2007 to February 2008.The variation characteristics of
potential evapotranspiration (PE) was analyzed based on Penman-Monteith method recommended by FAO. The
contributions of dynamic, thermal and water factors to PE were discussed. Meanwhile, the wet-dry condition of
that region was further studied. The results indicated that daily PE was between 0.52mm and 6.46mm in the
whole year. In summer evaporation was the most intensive, and from May to September monthly PE was over
100mm. In November, there was a clear mutant. Annual potential evapotranspiration was 1037.83mm. In
summer, thermal evapotranspiration was much more significantly than dynamic evapotranspiration; in winter it
was on the contrary. In addition, drought and semi-drought climate lasted for a long time while semi-humid
climate short. The effect of water and dynamic factors on PE varied considerably with the season. Soil moisture
was not the main factor affected PE.

4.Up-scaling scheme was developed
The location of the footprint function varies in time due to changing wind direction and atmospheric stability.
Therefore the footprint of atmospheric measurements does not only affect data quality but also

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representativeness of the observed data for the grid level. A scheme to overcome this drawback is in
development and will work in principle as shown in figure 3.

Fig.10. Upscaling scheme for turbulent flux data from heterogeneous landscapes

5.Free convection events at Nam Co site of the Tibetan Plateau were found and analyzed
The spatial and temporal structure in the quality of eddy covariance (EC) measurements at Nam Co site is
analyzed, by using the comprehensive software package TK2 together with a footprint model, and the high
quality turbulent flux data have been obtained for the investigation of free convection events (FCEs). The
research of FCEs at Nam Co site indicates that the generation of FCEs not only can be detected in the morning
hours, when the diurnal circulation system changes its previously prevailed wind direction, but also can be
triggered by the quick variation of heating difference between different types of land use during the daytime
when clouds cover the underlying surface or move away. FCEs at Nam Co site are found to occur frequently,
which can lead to the effective convective release of near ground air masses into the atmosphere boundary layer
(ABL) and may strongly influence its local moisture and temperature profiles and its structure.

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Fig. 11. The distribution (a) and frequency statistics (b) of free convection events (FCEs) times at Nam Co site.

6. Diurnal variation of sensible heat flux were very clear
Careful data processing and quality control of LAS has been performed in Naqu BJ station. The comparison
of sensible heat flux measurement by LAS and EC are plotted in Fig12, which shows the similar variation
between LAS and EC measurement.

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Fig 12 Comparison of sensible heat flux measurement by LAS and EC (2009.08.01-2009.08.28)

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3.2 Work progress in WP2 and achievements during the period
WP2 aims to develop algorithms to retrieve surface parameters from a broad family of multi-spectral and/or
multi-angular radiometric data and produce a consistent data set over the region of Tibetan Plateau.

# Instrument and validation

A multispectral canopy imager (MCI) was developed for the field measurements of forestry canopy LAI. It
can capture image pairs in three different wavelength bands at arbitrary zenithal and horizontal directions.
The MCI image pairs can be used to discriminate the sky, leaves, cloud and woody components. As a result,
this instrument is capable of measuring the woody area index which is very important in field LAI
measurements. In the Heihe river field campaign which was taken in June 2008, MCI was used to get the
directional clumping index and woody-to-total area ratio. Finally, the LAI values were obtained in several
locations after consider the correcting of the clumping effects and woody components.

# Model development

A Whole Growth Stages (WGS) model was developed for simulating the directional reflectance of the row
planted canopy across the whole growth stages. Based on a series of simplifications and assumptions, we
gave out an analytical expression to describe the spatial regular fluctuation of LAVD of row planted wheat
canopy. We found that the LAVD of the vegetal row is approximately negative correlation to the distance
from the centre of the row. Then we put forward a suit of calculation scheme to estimate the directional gap
fraction which well considering the spatial regular fluctuation of LAVD within row-planted wheat canopy. In
our new model, only 4 input parameters are needed, including LAI, the ratio of row width to height, the ratio
of row space to height, row direction.

A new angular & spectral kernel model was developed to describe the BRDF characteristics for most of the
land covers. Compared with the semi-empirical kernel-driven model used by AMBRALS (Algorithm for
Model Bidirectional Reflectance Anisotropies of the Land Surface) which was employed in the MODIS
(Moderate Resolution Imaging Spectra Radiometer) albedo/BRDF product, the component spectra were
combined into the kernel functions instead of kernel coefficients. Then the kernels were expressed as function
of both the observed geometry and wavelength. As a result, the kernel coefficients are independent of
wavelength in this new model. That characteristic enables the broad band conversion to be a linear
combination of the new integral kernels which is much simple and efficient.

A model describing thermal directional radiation was established for the rugged terrain. By parameterization
of sky-view factor and terrain configuration factor, the emitted radiance was parameterized as a linear
composition of the contributions of radiance from vegetation and soil, taking into account the coupling
between vegetation-soil, vegetation-vegetation and soil-vegetation interactive processes.

# A generic inversion algorithm

In order to enable the application of the method to several satellite sensors, the observation model SLC (soil-
leaf-canopy) was extended for applications in the thermal domain, and the MODTRAN interrogation
technique was extended to this domain as well. In addition, look-up table (LUT) techniques were optimized
in order to allow for efficient image simulations under various conditions. This means that for angular
interpolations of the sun-target-sensor geometry only a limited size of the LUTs is required. Topographic
effects were included by considering slope and aspect angles to be obtained from a DEM (digital elevation

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model) of the area. Slope and aspect are used to estimate the fractions of solar and sky spectral irradiance in
the optical and thermal domains. A unified equation was derived to describe the TOA radiance as a function
of surface and atmospheric parameters in the optical and thermal domains with the incorporation of
topographic effects. The MODTRAN interrogation technique was extended into the thermal domain as well,
and several MODTRAN outputs were identified with physical quantities of four-stream radiative transfer
theory.

# Topography and scale effect correction for albedo products

One coarse scale pixel includes many tilted micro-areas, which have different slopes and aspects. Its
directional reflectance is affected by these micro-areas and their shadows. An equivalent smooth surface
directional reflectance was introduced for a virtual surface of the coarse scale pixel, which was assumed to be
smooth so that there were no micro-area topography effects. A scale effect correction factor was defined to
correct the topography and scale effect. This factor is only dependent on DEM and the geometry of sun and
sensor. The topography and scale effect correction algorithm includes three steps: (1) Setting up a database for
pixel-average slope and aspect angle for each pixel of 500m grid and 5km grid, and scale effect correction
factor for each 5km pixel; (2) Correcting the pixel level topography effect for 500m directional reflectance,
using slope and aspect angles; (3) Correcting the pixel level, as well as subpixel level, topography effect for
5km directional reflectance, using slope, aspect angles and the scale effect correction factor.

# A priori knowledge based LAI inversion

The a priori knowledge of LAI was obtained by three ways: (1) Getting the relationship between a
multidirectional averaged NDVI and LAI by simulation using a BRDF model (eg. SAILH model); (2)
Developing the empirical crop growth model by the regression of a LOGISTIC equation and the field
measured LAI data sets; (3) Developing a priori LAI trend from several years’ MODIS LAI product. All of
this a priori information was used in the inversion of radiative transfer models to get the temporal continuous
and robust LAI. Both of the MODIS and MISR data were used in the inversion to improve LAI product.

# Angular effect correction of fractional vegetation cover

Under the assumption of that a remote sensing pixel is mixed by vegetation and background, a simple
directional fractional vegetation cover (FVC) model was developed based on Beer-Lambert law. The
variables in this model can be got by using the MODIS images in 16 days and high resolution HJ-1 images
The Scaled Trust-Region Solver for Constrained Nonlinear Equations (STRSCNE) algorithm was used to
retrieve the variables. A vegetation growth model was introduced to constrain the relative worse quality of HJ
data in a temporal scale. The different spectral responds of MODIS and HJ were also compared with
spectrums of typical surface class. Uncertainty was assessed by error propagation theory and field
experiments.

# LST inversion using polar satellite data

A review of existing algorithms to retrieve land surface emissivities (LSE) and land surface temperatures
(LST) has been carried out. This review has allowed the selection of the needed algorithms to retrieve LSE
and LST, which includes the preliminary determination of several parameters such as NDVI (Normalized
Difference Vegetation Index), FVC (Fraction of Vegetation Cover), total atmospheric water vapour content,
as well as carrying out cloud tests, image atmospheric and geometric correction. In the absence of the MODIS
– CEOP-AEGIS dataset, these algorithms are being implemented on the data acquired by the Global Change
Unit at the University of Valencia (Spain), in order to obtain a near-real estimation of LSE and LST. The
completion of this process is expected during the next reporting period. In a second step, this processing chain
will be adapted to the Tibet area in order to process the MODIS – CEOP-AEGIS dataset.

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The algorithm of daytime 150m LST product was proposed by using the HJ-1 dataset over the Tibet Plateau.
A view angle dependent single channel LST algorithm has been developed for correcting atmospheric and
emissivity effects for all land cover types.

• Highlight clearly significant results (3 pages)

# Multispectral canopy imager (MCI) and its use in woody-to-total area ratio determination

The MCI, which mainly comprises a near-infrared band camera, two visible band cameras, filters and a pan
tilt, was developed to measure clumping index, woody-to-total area ratio and geometrical parameters of
isolated trees (figure 1). Two typical sampling plots (Plots 1 and 5) which were covered by Picea crassifolia
were selected for the estimation of woody-to-total area ratio and its directional change in Heihe river basin,
China. The clumping index and woody-to-total area ratio values of the forest canopy were got at eight zenith
angles (from 0 to 70° in increments of 10°) using MCI images based on gap size distribution theory (figure
2,3).

Figure 1. Illustration of the multispectral canopy imager (MCI).

Erreur ! Des objets ne peuvent pas être créés à partir des codes de champs de mise en forme.Erreur ! Des objets ne
peuvent pas être créés à partir des codes de champs de mise en forme.
Figure2. Clumping indices at Plot 1 (a) and Plot 5 (b).

Erreur ! Des objets ne peuvent pas être créés à partir des codes de champs de mise en forme.Erreur ! Des objets ne
peuvent pas être créés à partir des codes de champs de mise en forme.
Figure3. The woody-to-total area ratio of Plot 1 (a) and Plot 5 (b).

The detailed description of the equipment and the method can be found in the following paper:

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Jie Zou, Guangjian Yan, Lin Zhu and Wuming Zhang, Woody-to-total area ratio determination with a
multispectral canopy imager (MCI), Tree Physiology, 2009; doi: 10.1093/treephys/tpp042.

# Unified modelling of TOA radiance for the generic inversion algorithm

A unified equation was derived to describe the TOA radiance as a function of surface and atmospheric
parameters in the optical and thermal domains with the incorporation of topographic effects. This equation
reads:

where and are the viewing factors associated with illumination from the sun and the sky, respectively.
They are given by

,

where and are terrain slope and aspect, respectively.

The four terms in square brackets are the ones associated with:

• Atmospheric path radiance in both domains
• Adjacency effects in both domains
• Sky irradiance contributions in both domains for the target
• Direct solar bi-directional and thermal direct target contributions

Note, that emissivities are represented here by their associate reflectance equivalents and
(hemispherical and directional emissivity).

# Time series LAI mapping over Heihe river basin

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The developed variational assimilation method was implemented and some results on LAI values for the
whole year of 2008 over Heihe River Basin are presented in Figure 4. It shows the regional LAI mapping
results from the time series MODIS reflectance data acquired over this area in 2008 with the spatial
resolution of 500m. As seen, temporal variation of the LAI values in this region is reasonable. And the spatial
variability is consistent with the vegetation cover map in this area.

Figure 4 LAI inversion results in the middle of Heihe River area.

# Emissivity measurements and data preparation

Several papers have been published regarding different topics of LST from polar satellites such as:

(1) José A. Sobrino, Cristian Mattar, Pablo Pardo, Juan C. Jiménez-Muñoz, Simon J. Hook, Alice Baldridge,
and Rafael Ibañez. 2009. Soil emissivity and reflectance spectra measurements. Applied Optics, Vol. 48, Issue
19, pp. 3664-3670.

This work present a laboratory procedure to characterize the emissivity spectra about several soil samples
collected in diverse suite of test sites in Europe, North Africa, and South America from 2002 to 2008. Here,
we presented a cross calibration with in-situ measurements and further application to thermal remote sensing.
This work presents a methodology to characterise the emissivity values of a given soil sample, additionally,
the soil emissivity values analyzed here were presented for all polar satellites which have thermal sensors.

(2) C. Mattar, J.A. Sobrino, Y.Julien, J.C. Jiménez-Muñoz, G. Soriá, J. Cuenca, M. Romaguera, V. Hidalgo,
B. Franch, R. Oltra. 2009. Database of atmospheric profiles over Europe for correction of Landsat thermal
data. Proceedings of the 33rd International Symposium on Remote Sensing of Environment. (in press)

This work presents a new vertical profile data base for correct thermal remote sensing images. In this case we
focused our work to provide useful information to correct Landsat thermal images. However, the data base
could be used for other remote sensing sensors.

# Spectra normalization of HJ and MODIS data
Difference of spectral responds of HJ and MODIS sensors should be considered in FVC retrieval, though
MODIS and HJ sensors have overlapped region in spectral respond functions (figure 5). Many reflectance
spectrums of leaves and soils were selected from spectrum library of ENVI software. The mean values were

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computed for the two sensors (table 1). Scattering plot of 4 bands in figure 6 didn’t exhibit much difference
for HJ and MODIS.

Figure 5. Relative spectral respond function of MODIS and HJ-1 bands used in FVC retrieval

Table 1. Mean reflectance of typical land covers with HJ and MODIS relative spectral response
Reflectance of typical leaves and soils
conifer deciduous Grass and soil
arbre
Blue HJ-1 0.0704562 0.07849 0.08478 0.077605
MODIS 0.0621984 0.065187 0.071822 0.064877
Green HJ-1 0.100901 0.132595 0.135229 0.139566
MODIS 0.114949 0.149223 0.14475 0.12815
Red HJ-1 0.075 0.119595 0.129705 0.204328
MODIS 0.071389 0.110964 0.12425 0.195855
Near- HJ-1 0.51273 0.683053 0.517343 0.281649
infrared MODIS 0.525689 0.692068 0.534383 0.300353

Scattering plot of reflectances

Blue
Green
Red
NIR

Figure 6. Reflectances of HJ-1 and MODIS signal corresponding to typical land cover types

# Development of a quantitative remote sensing products inversion system

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A quantitative remote sensing products inversion system is being developed for the parameters products
generation. It is composed of 5 sub-systems, including database, data pre-processing, products inversion,
validation, and visualization.
(1) Database subsystem takes charge of the data management and data flow of the whole system. All the
other sub-systems will be connected together by database without physical connection between the 4
sub-systems;
(2) Data pre-processing subsystem will process all the incoming remotely sensed data into standard data
products. The pre-processing procedures include cross radiometric calibration, geometric correction,
projection transferring, gridding, and cloud screening;
(3) Products inversion subsystem is a products “pool” which is composed of 22 geo and bio parameters and
system users will make their own product producing workflow. The subsystem will be producing
products through the workflow instantaneously or routinely;
(4) Validation subsystem will validate the inversion products based on the predefined methods routinely or
by users’ convenience;
(5) Visualization subsystem is a visual interface which provides users with data management, image display
environment, image and graphic processing, terrain analysis, statistics analysis, and annotating.

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Summary of progress towards objectives, per task:

Task 3.1 (ALTERRA, ITC, BNU, CAREERI, TUD): local validation of algorithms with ground eddy
covariance measurements at footprint scale and cross-comparison of approaches to turbulent flux partitioning.

The remote sensing based algorithm for flux calculation to be evaluated in this task can be applied at local
scale (S-SEBI, SEBS) or at a larger (meso) scale (SEBS, MSSEBS). They all follow the approach proposed
by Menenti and Choudhury (1993) stating that for a given net radiation value, and for homogeneous
atmospheric conditions, the surface temperature is related to the ratio between actual and potential
evaporation. Both methods require physical properties of the surface extracted from remote sensing to
characterize the surface radiative balance (albedo, surface temperature, emissivity) and vegetation structure
(fractional cover, Leaf Area Index). Also they differ in the way to define wet and dry boundaries in terms of
normalized surface to air temperature gradient, they all require some basic meteorological information.
Therefore the contribution of UDS in this task consisted in:
i. identify remote sensing products available to conduct SEB calculation for areas and periods of time
where reliable ground measurement data were available;
ii. gather and post-process meteorological data to be used as forcing conditions in the SEB schemes

The remote sensing products used to conduct the algorithm comparisons are Modis images acquired by Terra.
The reasons are: i. the adequate spatial and temporal resolution of the sensor; ii. the panel of adequate
products; iii. ad hoc products from WP2 are not available at this stage of the project. The products and dates
are summarized in the tables bellow. The candidate dates were selected on the basis of global cloudiness on
the Plateau.

April 2003 15th and 25th
May 2003 28th
October 2003 17th and 23rd
November 2003 8th and 11th

Product Variable Spatial resolution Temporal resolution
MOD11A1 LST/Emissivity 1km Daily
MCD43B3 Albedo 1km 16 days
MOD13A2 Vegetation index NDVI 1km 16 days
MOD15A2 LAI 1km 8 days

The characterization of the state of the Planetary Boundary Layer is based on the output from the Meso-scale
Numerical Weather Prediction Model GRAPES developed by the Chinese Academy of Meteorological
Sciences, partner in this project. The following variables were extracted from GRAPES simulations covering
the entire Plateau at a resolution of 30 km and 30’ time step:
Variables extracted at the height of the Atmospheric Boundary Layer:
• ABL height
• Air temperature
• Specific humidity
• Wind speed
• Air pressure
Variables needed at 2 meters:
• Specific humidity

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• Air pressure

UDS prepared two set of inputs centered on the validation site called BJ, with either 400x400 km or 100x100
km extent. The processing consisted in:
• extraction of MODIS products, re-projection and spatial re-sampling of albedo, LST with
corresponding acquisition time layer, NDVI, LAI
• extraction of GRAPES outputs from GrADS raw files, geo-processing of layer variables to the same
resolution and coverage as MODIS products
• creation of time-composite PBL layers to associate adequate GRAPES field to MODIS LST
following MODIS LST acquisition time
• extraction of SRTM Digital Elevation Data for the selected scene to calculate PBL elevation

This dataset was used to perform S-SEBI, SEBS and MSSEBS calculations, tests and comparisons (see next
section).

Task 3.2 (UDS, ALTERRA, ITC, ITP, BNU): generalize SEB calculation at a high spatial resolution and on a
regional extent. On such an extent, local towers cannot be used to define boundary conditions. The MSSEBS
(Colin, 2006) approach enables to link ground variables at a high spatial resolution (typically 30 meters) with
Atmospheric Boundary Layer (ABL) state at a proper resolution related to the typical ABL length scale.

Generalize SEB calculation on the entire Plateau lead to several conceptual and technical challenges:
• the combination of high resolution remote sensing products with medium (meso) resolution NWPM
outputs in a single calculation scheme, combining physical variables whose meaning is closely
related to their inherent scale, as to be taken into account in the algorithm implementation
• the use of high (1km) resolution remote sensing products over the Plateau lead to significant amount
of data (e.g. 1,400 x 1,700 km grid means 2.4E6 calculation nodes, for n variables and j time steps
with n > 25 and j >> 100).
• the use of NWPM with different spatial and temporal resolution, geo projection, supposes to have a
powerful pre-processing procedure to mix various data sources in a single model input set of layers
• the probable occurrence of data unavailability (clouds…), data inconsistency (NaN, error code)
supposes to have a flexible enough implementation to manage with various situations with a
minimum of manual work
These considerations lead to the prototyping and current development of a new SEB framework, with the
following characteristics:
• core algorithms are separated from I/O procedures; external I/O procedures can be extended without
any modification of the algorithms to allow the use of new data sources
• efficient object oriented python coding based on Numpy and SciPy math libraries for fast processing
of numerical arrays; multi-core computation capability; fully open source based and cross-plateform
• XML based configuration, with HTML/PhP user interface (under development)
• powerful geo-processing library GDAL embedded
• self-diagnosis capability for fast analysis of mass of log files
At this stage of the project, this code is under development, with evaluation of a beta version. The first stable
version will be described in details in the Algorithm Theoretical Basis Document to be delivered on
milestone M2. The resulting products will be made available to WP8 partners, and as a new product in the
database of the project to be registered to GEOSS.

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Figure 1: SEB framework chart

Task 3.3 (UDS, ALTERRA, ITC, ITP) : The same MSSEBS approach is used with low resolution satellite
images (Feng Yun-2) and NWP model outputs over the entire plateau. These low resolution fluxes maps can
be validated from spatially integrated maps obtained in Task 3.2.
(nothing at this stage of the project)

Significant results

The aim of the calculations performed with the 2003 dataset is to perform a cross-comparison of algorithms
and a validation with ground measurements.
The candidate algorithm of UDS is the Multi-Scale Surface Energy Balance System (Colin, 2006). This is a
single source SEBI based scheme designed to process radiative balance, PBL stability and external
resistances at appropriate scales as regards the physical meaning of key variables (e.g. roughness length for
momentum and heat, stability functions in the atmospheric boundary layer…), to produce evaporative
fraction maps. The soil heat flux is computed following vegetation fraction data, and the total diurnal
evaporation is computed with a locally fitted model of net available energy for turbulent flux. The sensible
heat flux is calculated as the residual of the energy balance.

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Figure 2: example of results for Nov 11th 2003: (top left) PBL forcing from GRAPES, values are allocated following the
acquisition time of the LST; (top right) MODIS products; (bottom left) Sensible heat flux map from MSSEBS; (top
right) Latent heat flux map from MSSEBS.

For the 1x1 km pixel where the Bijie site is located is, for Nov. 11th 2003 at 11:06, the latent heat flux calculated
with MSSEBS is 7.6 W.m-2 , and the sensible heat flux is 143.1 W.m-2, while ground values of latent heat flux
measured at respectively 10:30 and 11:30 range from -14.3 W.m-2 to -55.5 W.m-2, and the corresponding sensible
heat flux ranges from 91.4 W.m-2 to 200.0 W.m-2.
Since the latent heat flux from MSSEBS is of the order of magnitude of the model uncertainty (Colin 2006), the
evaporation can be considered as almost negligible. Moreover, as the ground measurement values used here are
sensor values, a comparison with a 1 km resolution pixel would require further analysis of the spatial meaning of
the measures.

This first experiment gives important information for the preparation of the next phase of the project:
• whatever the date of the year, even a limited scene is affected by clouds. The SEB framework has to be
able to deal with missing values in mathematical processing, and gap filling technics to be implemented
in WP2 will probably be critical to provide a continuous flow of inputs for the time series processing
phase to come

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• also these experiments are based of GRAPES simulations, GRAPES usually provide analysis data, ie. at
a fixed 6 hour time step. This is of consequence as regard the acquisition time of LST products. An
additional step may be required to derive LST at a GRAPES time step from the remote sensing products.

This first experiment has several significant limitations:
• no data were available to conduct a dual-source calculation
• validation data were only available for one point, and local meteorological conditions only allowed to
use one of the selected dates
• ground measurement data used for validation didn’t passed through detailed quality and footprint
analysis

Therefore a new validation experiment was initiated with a selection of 3 different sites located in very different
parts of the Plateau, using 4 sets of 10 days of data in January, April, July and October 2008. This set of
validation data was made available late September 2009 by WP1 partners. MODIS products were collected, and
GRAPES simulations still have to be performed at the time of writing this report. Therefore it is asked that the
target delivery time of deliverable de 3.1 “Review of selected existing algorithms and models on local, regional
and Plateau scales data sets” is set to December 20th to allow for the completition of this analysis.

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Summary of progress

Task 4.1: Review and inter-comparison of available algorithms and products (microwave backscattering
coefficient, microwave emissivity and land surface temperature diurnal cycle) (ITC, CAREERI, BNU,
IGSNRR)
This task is completed and report is written

Task 4.2: Collection of consistent continuous in-situ soil moisture measurements at regional scale of
selected sites on the Tibetan plateau measurements which will include soil moisture (including soil
temperature, vegetation parameter, soil texture and land surface roughness) at two sites (Maqu-grassland,
and Naqu tentatively) (CAREERI, ITC)
Task 4.2 has been completed and Deliverable 4.1 has been distributed.
CARRERI and ITC have installed in May-July 2008 an extensive soil moisture and soil temperature
monitoring network in the water source region of the Yellow River to the South of Maqu city, on the border
between Gansu and Sichuan province, in China (33°30’-34°15’N, 101°38’-102°45’E). The network consists
of 20 stations monitoring the soil moisture and temperature at different depths (from 5 to 80 cm deep) every
15 minutes. The network covers an area of approximately 40 km*80 km, where the elevation ranges between
3430 m and 3750 m a.s.l (north-eastern edge of the Tibetan Plateau). To ensure complete data continuity, the
data are downloaded twice per year by CAREERI: at the beginning of the monsoon season (in May) and at
the end (in October).
A specific calibration of the probes has been carried out for the soil type of Maqu area, increasing the
accuracy of the soil moisture measurements from 6% to 2%.
The quality of the data downloaded from Maqu monitoring network has been checked by evaluating their
consistency in time and space and by comparing their trends with meteorological data and with soil moisture
satellite products. A clear consistency and a good agreement have been found.
The calibrated data collected at all the stations and at all available depths are reported in an Excel file and a
detailed technical report has been attached to the data. Both of them have been delivered to the project teams.

Task 4.3: Development of a satellite sensor independent system for the soil moisture combined retrieval
algorithms (ITC, CAREERI, BNU)
This task is in progress. A retrieval model is developed for ASCAT data which will be combined with passive
microwave data in the course of the project.

Task 4.4: Estimation of soil moisture from Geostationary Satellite (GS) data (optical remotely sensed
data) (IGSNRR)
In order to develop method of estimate soil moisture based on geostationary satellite data using the diurnal
variation of LST derived and global radiation (shortwave). Following investigations were conducted during this
time:
1. Construction of land surface diurnal temperature cycle model and the ellipse relationship between
LST and solar shortwave radiance.
In geostationary satellite observation system, there are adequate images to describe land surface temperature
variation under clear sky condition. In generally, land surface temperature diurnal variation can be expressed as a
harmonic term in daytime and an exponential term during the nighttime. This two-part semi-empirical diurnal
temperature cycle (DTC) model has used by Göttsche and Olesen (2001), Schädlich et al. (2001) and Jiang et al.
(2006). In our work, we chose the model applied in Jiang (2006).

2. Land surface temperature simulation with land surface model (i.e. Common Land Model )

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In order to validate some assumption and analyze the method mentioned above, simulation data is an easy and
fast way. In our simulation, Common Land Model was selected to simulate land surface temperature under
different environment conditions in clear air condition. During the simulation, soil type and land cover type were
usually set to be constant. Then we modeled the land surface temperature variation under different percent
vegetation cover varying from 0%- 100% with a step of 10% and soil volumetric water content varying from
0%-50% with a step of 5%.
Several parameters were extracted from the land surface temperature daily cycle like maximum temperature,
minimum temperature, daily temperature amplitude, temperature morning raising rate and so on. Correlation
analysis was conducted here to analyze the relationship of there parameters with soil water content and percent
vegetation cover. The results showed that land surface temperature is a complex variable. It is influenced not
only by soil water content, but also is greatly influenced by surface land cover type and percent vegetation cover.
As an interface between land and air, Land surface has strong energy and material exchange processes. In order
to understand the degree of soil water content’s influence on land surface temperature, the other factors should
be eliminated firstly.

3. Organization and implement field experiment in Lang fang experimental base.
Beside land surface model simulation, we also organized a field experiment in Lang fang experimental base in
He bei province, China. In order to measure the atmosphere and soil data, such as air temperature, wind velocity,
soil volumetric water content, we purchased an Automatic Weather Station and Time Domain Relectometers
(TDR). Meanwhile, land surface temperature was measured by infrared thermometer. Down-welling globe
radiation and net radiation were also recorded using Solar Radiometer.
The experiment was implemented from 17th Oct. to 5th Nov. 2008 for 20 days. Three sites were executed
simultaneously with three soil types (sand, watered local soil and non-watered local soil).

4. In-situ measurement data analysis
From the experiment, many data was collected. Fig. 3.4.1 shows the observed records of soil surface
temperature, wind speed and air temperature at 2 Meter height of 5 days.

Fig.3.4.1 Sample of observed data during the experiment

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From the observed data, we analyzed the soil temperature raising rate related to the Net Surface Shortwave
Radiation (NSSR) during the morning time, and the temperature falling rate related to NSSR or Net Surface
Radiation (NSR) during the afternoon time.

5. Abnormal surface nocturnal cooling effect analysis
From the in-situ measurements and satellite data of MSG SEVIRI, we found that there exists an abnormal rising
of the change of the soil temperature in the nocturnal cooling process. Nocturnal surface intense cooling may
result in the inversion of the atmospheric temperature and water vapor. In order to study the abnormal
phenomenon, we analyze and simulate the changes of surface temperature under different atmospheric
conditions

Task 4.5: A data product of the plateau using different sensors simultaneously (AMSR-E, ASCAT,
SMOS) (BNU, ITC)
Up to October 2009, we had collected all of the satellite observation data and ancillary data used for retrieval,
including AMSR-E Level 2A, Level 3 brightness temperature data, SRTM 90m DEM data, MODIS IGBP
land cover map, and surface freeze/thaw status data, etc.
Available ground surface emission models were evaluated and compared in detail, on this basis, a forward
simulation system was established. It uses Qp model to calculate the emission of rough soil surface, and !-"
model to consider the vegetation effects. Through simulation analysis, the crucial inversion methods were
determined. A multi-channel temperature estimation algorithm using AMSR-E was selected to obtain the
surface temperature. The new developed microwave vegetation Indices (MVIs) was used to eliminate the
vegetation effects. And a soil moisture index developed from Qp model was put forward to minimize the
effects of surface roughness. When the above methods were used in the soil moisture retrieval, some good
results were achieved, and further results are still in progress.

Task 4.6: Validation results and documentation of uncertainties (CAREERI, BNU)
There is no progress made so far and is in accordance with project plan.

Significant results

Collection of consistent continuous in-situ soil moisture measurements at regional scale
One of the objectives of the CEOP-AEGIS project is to develop a soil moisture retrieval algorithm based on the
simultaneous use of active and passive microwave satellite data. The developed algorithm is sensor
configuration independent and is able to incorporate data of present and future satellite data, such as AMSR-E,
ASCAT and SMOS. The long term and large scale products obtained applying the developed algorithm over the
Tibetan Plateau, will be extremely important to understand the links between Monsoon system, precipitation
patterns and soil moisture.

For this reason, extensive soil moisture monitoring networks are required to obtain ground information which
can be compared to the retrieved soil moisture products, in order to evaluate their consistency.
To tackle this validation problem, CARRERI and ITC have installed in July 2008 an extensive soil moisture and
soil temperature monitoring network in the water source region of the Yellow River to the South of Maqu city
(Gansu province, China). The network consists of 20 stations monitoring the soil moisture and temperature at
different depths (from 5 to 80 cm deep) every 15 minutes. The network covers an area of approximately 40
km*80 km.
The area selected for the installation of an extensive soil moisture monitoring network is located to the South of
Maqu city, on the border between Gansu and Sichuan province, in China. The network is at the north-eastern
edge of the Tibetan Plateau (33°30 -34°15’N, 101°38’-102°45’E) and at the first major meander of the Yellow
River, where it meets the Black river. It covers the large valley of the river and the surrounding hills (Figure

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3.4.2), characterised by a uniform land cover of short grassland used for grazing by sheep and yaks. In this area
the elevation ranges between 3430 m and 3750 m a.s.l.

The installation of the soil moisture and soil temperature monitoring stations started in May 2008 with the
stations CST_01-05 and was concluded at the end of June 2008 with all the other stations. Therefore since July
2008 the complete network is operative.
The network covers an area of approximately 80 km*40 km and the locations have been selected in order to
monitor the area extensively at different altitudes and for different soil characteristics.

During the installation, soil samples were collected in order to analyse bulk density, particle size distribution and
organic matter content. The samples for particle size and organic matter were collected at a depth between 5 and
15 cm. A laser scanner (Mastersizer S Ver. 2.18 by Malvern Instruments Ltd.) was employed to estimate the soil
particle size distribution and the standard method for the organic matter content. Soil sample rings (aluminium
cylinders of known volume) were collected at 5 cm depth and oven dried at 105°C to estimate the bulk density
(i.e. dry soil mass in a known volume). When the soil profile showed a variation at deeper layers, the sample
collection and the analyses were repeated for the second horizon as well.

Figure 3.4.2 Maqu area, Yellow River valley and location of the 20 soil moisture and soil temperature stations of the
network.

Each network station consists of one Em50 ECH2O datalogger (by Decagon), which is recording the data
collected by two to five EC-TM ECH2O probes (by Decagon) able to measure both soil moisture and soil
temperature.
EC-TM ECH2O probe consists of 3 flat pins 5.2 cm long. It is a capacitance sensor measuring the dielectric
permittivity of the soil surrounding the pins. The dielectric permittivity is then converted in volumetric soil
moisture according to a standard calibration equation. The soil temperature is measured using a thermistor
located on the same probe.

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Figure 3.4.3 Installation procedure

A specific calibration of the probes was needed for the soil type of Maqu area. Therefore soil samples were
collected and laboratory calibrations were carried out (see following paragraph).
For the installation, a deep hole in the soil was dug and the probes were installed on one of the hole walls, at
different depths and with the pins in horizontal direction. Then probes and datalogger (closed in a box) were
completely buried (see Figure 3.4.3).

EC-TM ECH2O probes estimate the volumetric water content of the soil by measuring the dielectric constant of
the soil. However the dielectric properties of the soils depend on soil texture and salinity. Decagon has
determined a generic calibration equation (applied by default by the datalogger), which is valid for all fine
textured mineral soils with an accuracy of approximately ± 3%. This accuracy can be increased to 1-2%,
performing a soil-specific calibration. For this reason about 5-6 kg of soil were collected in each location at a
depth of about 5-15 cm (as well as at deeper layers, in case the soil profile was different) in order to carry out a
laboratory specific calibration, following the instruction guide provided by Decagon.

Figure 3.4.4 Results of the soil specific calibration of ECH2O probes

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In conclusion, the calibration (Fig.3.4.4) has led to a decrease of the rmse between the volumetric soil moisture
measured by the rings and that measured by the probes from 0.06 to 0.02 m3/m3.

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Estimation of precipitation over the Plateau and surrounding zones with optical and microwave
observations

The objective of this WP was twofold: to provide multisensor and multiplatform observation of precipitation
over the Plateau, and to get a deeper understanding of cloud and precipitation processes ongoing over this area.
The temporal development of the activities identified as the first step the set-up of a reliable strategy to provide
quantitative precipitation measurement. This was achieved during the first reporting period of the project: the
weather radar data have been pre-processed to provide the project with a quality controlled 3D precipitation
dataset over the project target area.
On the other side, two studies were completed indicating that prevailing synoptic scale trough is one of a key
indicator to establish unique precipitation system over the Tibetan Plateau. Other activities are in their first
developing phase, and did not yet achieved significant results, as planned in the DoW document.
In the next pages a more detailed description of the activities is presented task by task.

Summary of progress.

Task 5.1: To observe the cloud and precipitation microphysics processes in Tibetan Plateau and
southwestern China by cloud Doppler radar, movable X and C band dual linear polarization radar. A
hydrometeors classification algorithm will be applied to retrieve the 3D microphysical cloud structure.
The radar observation has started in the sites operated by CAMS: the radar network and rain gauge information,
analyze the ground blockage for radar in Tibetan and Qinghai Province. The results show that the radars in
Tibetan are blockage by around mountain severely, the radar coverage is limited. The radar in Qinghai province
can be used to precipitation estimation with rain gauges. A fuzzy-logic based algorithm for hydrometeor phase
classification with polarimetric radar has been developed by CAMS. A small network of three X-band
disdrometers (PLUDIX) is planned by UNIFE (with the assistance of ITP-CAS) and the installation will be
completed in November 2009.

Task 5.2: To develop the QC and mosaic algorithms for operational Doppler radar network. The
disdrometric data will be used in radar QC and for radar calibration if disdrometers instruments are
available.
Research work on radar data quality and reflectivity remap and mosaic has been carried on by CAMS, and the
algorithm for 3 D mosaic. A the fuzzy logic based algorithm is used to detect the anomalous propagation and
ground clutter; four interpolation approaches are used to remap raw radar reflectivity fields onto a 3D Cartesian
grid with high resolution, and three approaches of combining multiple-radar reflectivity fields are used. The
algorithm has been used to process the radar data and provide 3D data to the other partners of WP5.
In particular, the raw precipitation data in Tibetan and the gridded precipitation data were provided by CAMS to
UNIFE for two case studies. for period of 18 June 2008-19 June 2008 and 18 July 2008-20 July 2008, with
spatial and temporal resolution (0.01°#0.01°#0.5km#5min)
Finally, CAMS processed radar data and provided 3D reflectivity data to WP5. Grid Reflectivity in Qinghai
from 18 July 2008 -21 July 2008 were product, the radar data in Tibetan from 18 June 2008 to19 June 2008, 18
July 2008 to 20 July 2008 were provide.
The data of three X-band disdrometers will made available by UNIFE for the period 1 November 2009 – 30
October 2010, to improve the quantitative radar rainfall products.

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Task 5.3: To analyze the meso-scale structures and processes of precipitation systems in Tibetan Plateau and
southwestern China by operational Doppler radar network in China and satellite (e.g. cloud products of MODIS).
The precipitation distributions with different algorithms will be compared in case studies.
UNIFE carried out an inventory of satellite precipitation estimation techniques, including both physical and
statistical approach and considering microwave (AMSR-E, SSM/I-SSMIS and AMSU), visible-infrared (MODIS,
AVHRR, Meteosat, FY-2C), and blended techniques. The characteristics of different techniques were analyzed
to select the more suitable ones for application over the Tibetan Plateau. The events proposed by CAMS were
selected as case study for the early application of selected techniques.
UNITSUK completed an analysis of the meso-scale structures and processes of precipitation systems and
identification of the indicators for the rainfall processes in Tibetan Plateau (TP) and southwestern China, and the
results will be summarized in the next section.

Task 5.4: To use the rain maps obtained by the ANN technique along two main lines: improve the performance
of floods and drought warning systems, and analyze long term (seasonal) rainfall pattern.
IGSNRR performed an inventory of Satellite Rainfall Estimation approaches and studied the theory of Artificial
Neural Network (ANN) and application in satellite rainfall estimation. The MATLAB software is considered for
ANN implementation. A first satellite dataset (June 2007 to September 2007) has collected and processed: FY-
2C satellite images (provided by the National Satellite Meteorological Center of China at 5Km spatial resolution
and hourly temporal resolution) and Gauge data (purchasing from the National Satellite Meteorological Center
of China) at hourly temporal resolution as well.
An ANN technique is implemented and tested with gauges data by IGSNRR, and the preliminary results will be
summarized in the next section.
UNIFE started to apply an ANN technique developed for MODIS data and focused on mid-latitude, to the case
studies over the Tibetan Plateau.

Task 5.5: To retrieve the precipitation with Doppler radar, satellite data and rain gauges in mountain region.
The retrieval of precipitation fields from radar and rain gauges has started (see task 5.2), while the satellite
approach is still in its preliminary phase (see also Tasks 5.3, 5.4 and 5.8).

Task 5.6: To obtain the distribution of Precipitable Water Vapor (PWV) in Tibetan Plateau and its
adjoining area by GPS receiver.
This task is not yet started by CAMS.

Task 5.7: To obtain the indicators of the rainfall process in Tibetan Plateau and southwestern China by analyzing
the change of PWV.
UNITSUK carried on a study on the relevance of water vapor transportation processes, using reanalysis data and
numerical weather prediction output. Results of this study will be summarized in the next section.

Task 5.8: To improve the current combined precipitation estimation technique with the radiometer
(TMI) and PR with the simulation database developed above and inclusion of the effects of topography over the
Plateau; Also here we will correct the satellite estimation of precipitation using the ground rain gauge data in the
algorithm, and validate the inversion scheme with ground observation.
For this task UNIFE planned to apply a rainfall retrieval scheme that works on conical scanner data (SSM/I-
SSMIS, AMSR-E, TMI). The algorithm is based on a cloud radiation database constructed as follows. A cloud
profile data set is assembled by means of cloud resolving model outputs (the Non-hydrostatic Modeling System
of the University of Wisconsin is used to this end), then a radiative transfer algorithm is applied to simulate the
radiances upwelling from the modeled cloud profiles. When a set of satellite radiances is measured from a given
sensor, the database is searched for the cloud profile whose simulated radiance better match the observed ones.
This algorithm is currently applied in different regions with encouraging results.

Significant results

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CEOP-AEGIS Periodic Report #1

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