CARPE DIEM Kick-off Meeting, 28-29 January, 2002 EURAINSAT European Satellite Rainfall Analysis and...

CARPE DIEM Kick-off Meeting, 28-29 January, 2002

EURAINSAT European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale

V. LevizzaniV. LevizzaniConsiglio Nazionale delle RicercheConsiglio Nazionale delle RicercheIstituto di Scienze dell’Atmosfera e del ClimaIstituto di Scienze dell’Atmosfera e del ClimaBolognaBologna

and all EURAINSAT Scientistsand all EURAINSAT Scientists


Increasing demand for local and global products for:

Products for developing countries (e.g. Africa)

Monitoring of remote areas

Applications to short range forecasting and nowcasting

Agriculture (crop control, irrigation,…)

Assimilation into NWP models (eg. latent heat nudging, physical initialization,…)

Weather modification

…

Climate and Global ChangeLarge underestimation of the role of precipitation processes


In particular, for meteorology:

Instantaneous rapid update estimates for hydrology:Disaster management (eg. Flash flood);Use in coupled LAM + hydrological models that include runoff.

Identification of orographic enhancement and monitoring of extreme events.

Correct determination of precipitation not only in case of deep convection, but also for frontal and stratiform rainfall in general.


What is EURAINSAT?A shared-cost project (contract EVG1-2000-00030) co-funded by the Research DG of the European Commission within the RTD activities of a generic nature of the Environment and Sustainable Development sub-programme (5th Framework Programme).Funded over a 3-year period starting January 1st, 2001.

What is the main purpose?Develop new satellite rainfall estimation methods at the geostationary scale for an operationaluse in short and very short range weather monitoring and forecasting.

Who are the key target users?The project is very much application-oriented and natural users are to be found among:National and regional met services,Basin authorities,International agencies (WMO, FAO, …),National and international space agencies,National agencies for civil and environmental protection,Institutions for the protection against hydrogeological risks,Air traffic control centers,Research institutions,Industry, agriculture, …


The Consortium:ITALYV. Levizzani, A. Buzzi, F. TampieriCNR – Istituto di Scienze dell’Atmosfera e dell’Oceano, BolognaA. MugnaiCNR – Istituto di Fisica dell’Atmosfera, Roma

F. MeneguzzoLaboratorio per la Meteorologia e le Modellistica Ambientale (LAMMA), Firenze

F. S. MarzanoUniv. dell’Aquila, Dip. di Ingegneria Elettrica, Monteluco di Roio

F. ProdiUniv. di Ferrara, Dip. di Fisica, Ferrara

ISRAELD. Rosenfeld, A. KhainHebrew University of Jerusalem, Institute of Earth Sciences, Jerusalem

GERMANYM. KästnerGerman Aerospace Centre (DLR), Oberpfaffenhofen

UNITED KINGDOMC. KiddUniv. of Birmingham, School of Geography and Environmental Sci., Edgbaston, Birmingham

EURAINSAT - European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale


EXTERNAL STEERING AND COOPERATION:

European Centre for Medium-Range Weather Forecasts, Reading, UK, P. Bauer

European Organisation for the Exploitation of Meteorological Satellites, Darmstadt, Germany, J. Schmetz

European Space Agency, Nordwijk, The Netherlands, J. P. V. Poiares Baptista

NASA, Goddard Space Flight Center, Greenbelt, Maryland, E. A. Smith

Naval Research Laboratory, Monterey, California, J. F. Turk

NOAA-NESDIS, Office of Research and Applications, Silver Springs, Maryland, J. F. W. Purdom

Raytheon ITSS, Distributed Active Archive Center, NASA-GSFC, Greenbelt, Maryland, G. A. Vicente

World Meteorological Organization, Geneva, Switzerland, D. E. Hinsman

EURAINSAT - European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale


Research activities:Research activities:Precipitating system structurePrecipitating system structureQuantitative rainfall estimationsQuantitative rainfall estimations

Operational MeteorologyOperational MeteorologyAssimilation into NWP Local Area ModelsAssimilation into NWP Local Area Models


To combined estimatesthat are more

•Microphysically correct,

•Linked to operational requirements,

•To be assimilated into NWP models

From simple VIS-IRMWestimates

Through:

•Multispectral cloud microphysical characterization

•Cloud modeling

•Rapid update cycles


METEOSAT Second Generation (MSG)


MSGMeteosat

1.4-km (hi-res visible)

4.8-km (others)

2.25-km (visible)

5-km (others)

On-Earth pixel resolution

15-minutes30-minutesUpdate cycle

1-km (hi-res visible)

3-km (others)

2.25-km (visible)

4.5-km (others)

Sampling distance

9.38-9.44

12.4-14.4

Pseudo-sounding

3.48-4.36

8.30-9.10

9.80-11.80

11.0-13.0

11.5Infrared windows

5.35-7.15

6.85-7.85

6.4Water vapor

spectrum

0.75 m broadband

0.56-0.71

0.74-0.88

1.50-1.78

0.5-0.9 mVisible spectrum

MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI)


Using MODIS prior to the MSG Launch

Wavelength (m)

Tra

nsm

ittan

ce

AMSR-E SSM/I AMSU-A,B

CloudSat


Key target areasKey target areasand experimentsand experiments


IOP 2 18-21 Sept. 1999

Frontal system and heavy rain over the Lago Maggiore region (NW Italy and Switzerland)

IOP 5 2-5 Oct. 1999

Frontal passage and cyclogenesis

over Northern Italy

IOP 8 20-22 Oct. 1999

Persistent lifting of stable air during a frontal passage over the Alps

IOP 15 5-10 Nov. 1999

Cold frontal passage over the Alps


UK andNorthern Europe

Light and/or Sustained rain

30 Oct. 2000UK and Europesustained rain fromseveral subsequent storms

28 June 2001Insignificant rain over the UK. Interesting case to test the sensitivity of rain algorithms to very light rain.


Climatological areasEurope

and Africa


Areas for cloud microphysics


StrategiesStrategies

1.1. Use of new active and passive sensors:Use of new active and passive sensors:MW instrumentsMW instrumentsVIS/IR/NIR channels VIS/IR/NIR channels Precipitation radarsPrecipitation radars

2.2. Development of hybrid IR/MW rainfall algorithms in rapid updateDevelopment of hybrid IR/MW rainfall algorithms in rapid update

3.3. Assimilation of rainfall fields in NWP modelsAssimilation of rainfall fields in NWP models


TRMM VIRS image of fires, smoke and clouds over Kalimantan, Indonesia, from 1 March 1998, 02:50 UTC. The color is composed of: red for visible reflectance, green for 3.7 m reflectance (approximating re), and blue for the inverse of 10.8 m brightness temperature. The northwest coast of the island is denoted by the yellow line. The small orange areas on the upper right (east) corner are hot spots indicating the fires. The smoke, streaming from the hot spots south-westward, is indicated by the fuzzy purple color of the background. The smoke-free background is blue. This color scheme shows clouds with small droplets (re<10 m) as white, becoming yellow at the supercooled temperatures. Clouds with larger droplets (re>15 m) are colored pink, and cold ice clouds appear red. The black hatching marks the areas in which the TRMM radar detected precipitation.

Vertical cross section along the line AB in the above figure, where the left end is point A and the right end correspond to point B. The gray area is the clouds, as measured by their top temperature. The colors represent the precipitation reflectivity, in dBZ, as measured by the TRMM radar. The white line is the brightness temperature of the TRMM Microwave Imager 85 GHz vertical polarization, plotted at the altitude of that temperature.

Rosenfeld, D., 1999: TRMM observed first direct evidence of smoke from forest fires inhibiting rainfall. Geophys. Res. Lett., 26 (20), 3105-3108.

Impact of smoke particleson cloud microstructure and precipitation…


Stratiform

Convective

Normalized LIS event vs maximum reflectivity

Maximum Reflectivity & Lightning Events

Dietrich et al., 2001


Elements of a Global Precipitation Analysis

Rapidly updated IR-based observations

Infrequent microwave-based rainfall

estimates

Global or regional-scale model forecast

Orographic adjustment, cloud growth/decay

adjustment

microphysical information

space-time information

dynamical information


An Information Transfer Perspective

Denotes equally-spaced geostationary-based IR observation

Denotes non-routine, non-equally spaced microwave-based observation

In essence, the procedure is an information-transfer. How much and for how longis microphysical information from past microwave overpasses maintained? Whatare the best techniques to forward-propagate past information (microwave observations, multispectral IR observations)?

t0

t-1t-2 t+1 etc.

Shaded box represents the previous-time “window” prior to t0


24-hour accumulations from merged microwave sensors (F-11,13,14,15; TRMM)

24-hour accumulations from geostationary-based technique 2000/04/27 1200 UTC


21 June 2001. Daily rainfall totals (mm) from a combined microwave-infrared rainfall estimation technique. Infrared cloud top brightness temperatures are calibrated using passive microwave estimates updated on a daily basis. Data fusion and artificial neural networks are also being evaluated.Chris Kidd, Univ. of Birmingham, UK.


24-hour accumulations from geostationary-based technique2000/05/16 0300 UTC

Local flood event in southwest coast iscaptured

24-hour accumulations from merged microwave sensors(F-11,13,14,15; TRMM) 2000/05/16 0300 UTC

Limited overpasses over Italian coastSome possible false identification in Alps


Strengths/Weaknesses

To combined estimates that are:•Microphysically correct,•Linked to operational requirements,•To be assimilated into NWP models

Through:•Multispectral cloud microphysical characterization

•Cloud modeling•Mesoscale Forecasts

•Rapid update cycles•Space/Time information

From simple rainfall estimate using:•VISIR

•(GOES/MSG/MODIS)•Microwave

•(SSM/I, TRMM, AMSU, AMSR)

Orographic adjustment

Ancillary Data:

Strengths:• Convective-based rain systems

Typically heaviest rain locations Slower moving systems, e.g., tropical cyclones

• Accumulations on a daily scale or longer Adaptation to daily changes Correlations near 0.6 with land gauge data

• Well-suited for insertion into numerical models

Soil moisture analysis (land data assimilation)

Weaknesses:• Defining the rain/no-rain threshold

Areas of light (< 0.5 mm/hr) precipitationtend to be too widespread

• Fast moving mid-latitude systemsInsufficient observations of precipitationdevelopment from necessary spectral regions

• Movement over areas of complex topographyProper accounting for orographic precipitation and rain shadowing effects

24-hr AccumulationsCOAMPS Surface WindsTopography Adjusted


If Rsat > Rfor increase q over saturation

qnew(z) = qsatur(z) + c(t,z) (Rsat-Rfor)

if Rsat < Rfor decrease q

qnew(z) = qsatur(z) + d(t,z) (Rsat-Rfor) {q(z) – qref(z)}

where qref(z) is the reference humidity profile and c

and d are nudging coefficients.


First resultsFirst results


Calabria Flood8 Sept 20001030 UTC

MODIS ch020.86 m


Calabria Flood9 Sept 20000935 UTC

MODIS ch020.86 m


Features of the FSU Superensemble Forecast System:

Real-time assimilation of SSMI, TRMM 2A12, and blended microwave/IR rain rate algorithms and techniques via a physical initialization (ie, reverse initialization)

Forecast uses multi-analysis forecasts (12 different models) and statistics from a training phase to produce superensemble forecasts of precipitation

Day 2 and 3 forecasts show improved skill in precipitation forecast compared to operational models that do not employ physical initialization

This forecast technique is promising for the prediction and guidance of extreme rain events in flood prone areas

T.N.Krishnamurti, FSUJ.F.Turk, NRL


12 UTC September 8, 2000: Observed and 1,2,3-day forecasted average precipitation


Orographic Conditions: California frontal passage January 11, 2001 0000 UTC


6 October, 1998

METEOSAT-7 IR image SSM/I 85-GHz Brightness Temperature

24-h rainfall accumulation (mm) 20-GHz Path Attenuation at 0600 UTC

F. S. Marzano – Univ. of L’Aquila


Want to know about the future?

We will not only think in terms of:

Using single satellite platformsAdopting a synergy of satellites conceived for different uses

What’s boiling in the pot?


International Precipitation Working Group (IPWG)co-sponsored byCoordination Group for Meteorological Satellites (CGMS)andWorld Meteorological Organization (WMO)

Co-chairsArnold Gruber, NOAA-NESDISVincenzo Levizzani, ISAC-CNR

The IPWG is established to foster the:Development of better measurements, and improvement of their utilization;Improvement of scientific understanding;Development of international partnerships.


1st Meeting in Ft. Collins, COCSU, 20-22 June, 2001


International Precipitation Working Group (IPWG)

The objectives of the IPWG are:

to promote standard operational procedures and common software for deriving precipitation

measurements from satellites;to establish standards for validation and independent verification of precipitation measurements derived from satellite data; including:

•reference standards for the validation of precipitation for weather, hydrometeorological and climate applications;•standard analysis techniques that quantify the uncertainty of ground-based measurements over relevant time and space scales needed by satellite products;

to devise and implement regular procedures for the exchange of data on inter-comparisons

of operational precipitation measurements from satellites;to stimulate increased international scientific research and development in this field and to

establish routine means of exchanging scientific results and verification results;to make recommendations to national and international agencies regarding the utilization of

current and future satellite instruments on both polar and geostationary platforms; and to encourage regular education and training activities with the goal of improving global

utilization of remote sensing data for precipitation measurements.


http://www.isao.bo.cnr.it/~eurainsat

CARPE DIEM Kick-off Meeting, 28-29 January, 2002 EURAINSAT European Satellite Rainfall Analysis and...

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