Reviewing water vapour observations using microwave radiometry for meteorological applications

Transcription

1 Reviewing water vapour observations using microwave radiometry for meteorological applications Susanne Crewell Institut für Geophysik und Meteorologie Universität zu Köln

2 Content water vapor information needed for meteorological informations methods and instruments microwave radiometry - retrieval accuracy algorithm types gas absorption model influence of different frequencies - vertical profiles MICCY examples outlook HATPRO

3 Meteorological Applications Initial conditions for numerical weather prediction (NWP) models 3D-fields spatial gradients of water vapor (convergence) for initiation of convection, water vapor fluxes small scale variability 10 km investigation of water and energy cycle, long-term trends for analysing climate change high accuracy

4 e - Water vapor: units ρ v - absolute humidity [kg m -3 ] T d - water vapor partial pressure [hpa] R v = R/M v =462 J kg -1 K -1 gas constant e s =f(t) saturation pressure e = ρ R dew point [K] cooling to dew points leads to condensation v v T Atmospheric Boundary Layer (ABL) Integrated water vapor IWV Vosges = ρ dz 0 v Black forest q - m - specific humidity [kg/kg] ratio of water vapor mass to total mass of air mixing ratio [kg/kg] ratio of water vapor mass to mass of dry air m > q, m q f - relative humidity [%] e = 100 e T f - wet bulb temperature [K] s f

5 Water vapor observations: Radio sondings e = ρ R v v T

6 Water vapor profiles dew point temperature Kuemmersbruck 12Z 07 Oct N, E, 418 NN IWV = 17.5 kg m -2 absolute humidity [kgm -3 ]

7 Radiosonde accuracy Westwater et al., 2005 Typically an accuracy of 5 % in relative humidity is specified problems in low humidity conditions and at strong gradients

8 Method Microwave radiometry GPS Thermal Infrared Sun photometer Reflected sunlight Platform ground-based ground-based spaceborne GOES, MSG HIRS, GOES AIRS, IASI ground-based spaceborne MODIS, MER-IS, POLDER Methods and Instruments spaceborne SSM/I, TMI, AMSU, AMSR Parameter IWV profile z=0.5-2 km IWV profile z=2-3 km IWV IWV profile profile IWV IVW Principle water vapour emission at GHz rotational line pressure broadening of rotational line as for ground-based delay of GPS signal caused by water vapour differential emission at 11 and 12 µm (split window) channels along 6.7 µm line high resolution spectroscopy extinction of direct sunlight at 0.95 µm absorption band difference of reflectances at 0.95 µm and at closeby window wavelengths Strengths and Weaknesses high temporal resolution time series in all weather conditions except precipitation dense surface networks are too costly polar orbiting satellite; at least daily coverage for all weather conditions, over ocean surfaces only with coarse resolution of about 50x50 km 2 inexpensive surface networks for all weather conditions, real time products have less accuracy good spatial and temporal in cloudfree situations only limited accuracy high vertical resolution and accuracy sun tracking only possible during daylight and cloud-free conditions high spatial (1x1 km) resolution only in cloud-free situations or above clouds Lidar ground-based profile Raman backscatter of water best during night z < 100 m vapour; differential absorption non operational at two channels Crewell, S., Hydrological applications of remote sensing: Atmospheric states and fluxes: Water vapor and clouds (passive/active techniques), Encyclopedia of Hydrological Sciences, Edited by M G Anderson John Wiley & Sons, Ltd., October 2005

9 Water vapor Differential Absorption Lidar (DIAL) Courtesy of Andreas Behrendt, UHohenheim

10 Comparison of different methods 45 Only microwave radiometers and GPS can give continuous observations IWV kgm Vapic campaign 2004, courtesy of Oliver Bock

11 Microwave Radiometry T cos = 2.7 K Emission of - atmospheric gases - hydrometeors τ = 0 α ( s) ds s τ τ optical depth α absorption coefficient [km -1 ] B(T) blackbody radiation [W m -2 Hz -1 sr -1 ] I radiance at frequency ν mean radiating temperature T MR I ν = B ( T ν cos )exp( τ ) + Bν ( T( s)) α( s) exp( α( s') ds') ds, 0 s 0 Conversion into brightness temperatures T B via Planck-function T b = Tb cos exp( τ ) + Tmr (1 exp( τ ))

12 Microwave Radiometry Radiative Transfer (RT) for standard atmosphere temperature profiles water vapor profiles liquid water path LWP=250 gm -2 ν /GHz

13 Clear sky example: 9 April 2006, Benin GHz GHz

14 Retrieval Algorithms in general retrieval is an ill-posed problem statistical methods regression, (simulated) measurements neuronales net representative data set is required "truth" is hardly ever available; especially hydrometeor profiles Truth physical methods - inclusion of physical measurement into retrieval scheme (radiative transfer) - stabilisation by using a priori profiles Löhnert, U. und S. Crewell, Accuracy of Cloud Liquid Water Path From Ground-based Microwave Radiometry. Part I : Dependency on Cloud Model Statistics, Radio Science, 2003 Crewell, S. und U. Löhnert, Accuracy of Cloud Liquid Water Path From Ground-based Microwave Radiometry. Part II : Part II: Sensor Accuracy and Synergy, Radio Science, 2003

15 Training Statistical Algorithms Radiosonde data set Cloud model (- 95 % threshold) Atmosphericprofile: p(z), T(z), rh(z), LWC(z) Test Integration MWMOD MWMOD Integration LWP, IWV TB(ν) TB(ν) LWP, IWV IWV N + + = a Statistical b model i TB ( ν i ) ci TB ( ν i ) mult. Regression, ANN N 2 Algorithm Comparison

16 Complex atmospheric state: Cloud Classification no rain reaches the ground

17 Integrated Profiling Technique (IPT) Microwave brightness temperatures (TB) Radar profile Lidar cloud base a priori LWC profile (climatology) a priori T & q profiles (closest radiosonde) Bayesian Retrieval physical consitentcy of observations and retrieval optimum profiles of temperature (T) humidity (q) liquid water content (LWC) Löhnert, U., S. Crewell, C. Simmer, 2004: An integrated approach towards retrieving physically consistent profiles of temperature, humidity, and cloud liquid water,j. Appl. Meteorol., 43(9),

18 Retrieval Accuracy Which parameters determine humidity accuracy? ill-posed retrieval problem - depends on choice of frequencies - inclusion of additional measurements (Ir, ceilo,...) uncertainty in observed brightness temperatures - sensitivity T B r - stability T B s - absolute accuracy T b a - bandpass characteristics (mean frequency) - contamination through RFI or dew/rain on radome T B time truth assumptions in retrieval process - representativity of data set / a priori information - choice of cloud model used for LWC-profile generation - uncertainty of gas absorption model - statistical model (ANN, multiple regression, order)

19 Influence of frequency combination MICCY Frequencies GHz GHz 90 GHz Starting with a channel at 23 GHz the channel giving the strongest decrease in RMS is searched for

20 Influence of radiometer noise No possibility to characterize bias errors in retrieval effects of radiometer bias and gas absorption errors is difficult to distinguish Addition of random noise to simulated brightness temperatures too much noise reduces information content too little noise can amplify bias errors IWV RMS [kg m -2 ] 2,0 1,8 1,6 1,4 1,2 1,0 0,8 0,6 0,4 0,2 0, Offset 23 GHz [K] Offset 28 GHz [K] Difference in mean IWV [kg m -2 ] added noise / K

21 Comparing different algorithms extremly difficult case: strong inversion thick cloud (~600 g m -2 ) 19 T B + T,p, z BASE + radar Z (IPT) Höhe [km] Radiosonde 1 h later Temperatur [ C] Abs. Feuchte [g m -2 ] LWC [g m -2 ] IPT NN REG (quadratic T B ) REG(linear T B )

22 Ill-determined problem 23.8 GHz 31.4 GHz

23 IWV accuraccy: Additional information Inclusion of additional observations by meteorological observations at the ground (T gr, p gr, q gr ) lidar ceilometer for cloud base height (z clb ) infrared radiometer for cloud base temperature (T clb ) Input variables Regression IWV RMS [kg m -2 ] NN IWV RMS [kg m -2 ] 3 TB TB + T gr 0.84 (6.6 %) 0.71 (4.0 %) 3 TB + p gr 0.86 (4.5 %) 0.72 (2.7 %) 3 TB + q gr 0.79 (12.3 %) 0.68 (9.2 %) 3 TB + z clb 0.88 (2.3 %) 0.70 (5.4 %) 3 TB + T clb 0.84 (6.6 %) 0.66 (10.8 %) 3 TB + z clb,t clb 0.83 (7.8 %) 0.66 (10.8 %) 3 TB + T gr, p gr, q gr 0.75 (16.6 %) 0.66 (10.8 %) 3 TB+ T gr, p gr, q gr, z clb,t clb 0.73 (18.8 %) 0.62 (16.2 %)

24 Uncertainty of gas absorption model H. J. Liebe,1989 "MPM, An Atmospheric Millimeter Wave Propagation Model," Int. J. Infrared Millimeter Waves, vol, 10( 6,), pp , H. J. Liebe, G. A. Hufford, and M. G. Cotton,1993 Propagation Modeling of Moist Air and Suspended Water/Ice Particles at Frequencies below 1000, in AGARD Conference Proceedings 542, Atmospheric propagation effects through natural and man-made obscurants for visible through MM-wave radiation, 1993, pp. 3.1 to 3.10 (available from NASA Center for Aerospace Information, Linthicum Heights, MD,). P.W.Rosenkranz,1998 Water Vapor Microwave Continuum Absorption: A Comparison of Measurements and Models, Radio Sci., vol. 33(4), pp , Correction to Water Vapor Microwave Continuum Absorption: a Comparison of Measurements And Models, Radio Sci., vol. 34(4), p. 1025, P.W.Rosenkranz,2003 Private communication J. R. Pardo, J. Cernicharo, and E. Serabyn, 2001: Atmospheric transmission at microwaves (ATM): An improved model for mm/submm applications. IEEE Trans. on Antennas and Propagation

25 Comparison of Tb Clear-Sky Forward Models

26 Comparison of Brightness Temperatures Lindenberg 2005

27 Water vapor gas absorption model J. C. Liljegren, S.-A. Boukabara, K. Cady- Periera, and S. A. Clough, 2004: The Effect of the Half-Width of the 22-GHz Water Vapor Line on Retrievals of Temperature and Water Vapor Profiles with a Twelve-Channel Microwave Radiometer, TGARS

28 Microwave Radiometers Cabauw 2001 IRE MTP TROWARA WVRA MICCY HATPRO MARSS Drakkar Conrad

29 IWV accuracy: Frequency dependence linear regression TB / optical depth quadratic regression TB / optical depth

30 Brightness Temperature Intercomparison BBC2 8. Mai 2003 HUTPRO

31 Cloud variability Instrument WVRA DRAKKAR MICCY t / s 30 s 1 s 1 s Θ / LWP /gm

32 Water Vapor Profiles Improvement through surface value Temperature RMS /K Absolute Humidity RMS / gm -3 Crewell, S., H. Czekala, U. Löhnert, C. Simmer, Th. Rose, R. Zimmermann and R. Zimmermann, 2001: Microwave Radiometer for Cloud Carthography: A 22-channel ground-based microwave radiometer for atmospheric research. Radio Science, 36,

33 Accuracy of humidity profiles Development data set 10 year radiosonde Lindenberg, Germany slight improvement through inclusion of angular information (BL) max. 0.2 g m -3 improvement through noise reduction

34 Advantage over RS Interpolation IPT Application to 2 months during Baltex Bridge Campaign (BBC) and comparison to independent radiosoundings Remote sensing profit absorption model uncertainty courtesy Ulrich Löhnert

35 Profile Resolution Definition of vertical resolution through interlevel error covariance Liljegren et al., 2004

36 Lindenberg, August/September 2000 Example: Diurnal cycle Güldner and Leps, 2005

37 High Altititude Observations Schneefernerhaus, 2600 m MSL

38 Profile comparison Altitude Schneefernerhaus Temperature [K] absolute Humidity [g m -3 ] Radiosonde von München-Schleissheim K. Rasp

39 Comparison of humidity profiles N=87 SALF September N=33 SALF October N=54 SALF

40 Challenges and Outlook reference Radiative Transfer Model (RTM) - improve description of water vapor absorption - scattering by non-sperical ice and mixed phase particles at higher frequencies - 3-dimensional RT algorithm development for sensor synergy - combination with lidar and IR - determination of spatial gradients by combining different frequencies and observation angles networks of low cost instrumentation - addition/replacement of radio soundings - new methods for water vapor flux observations field experiments - COPS: Convective and Orographically-induced Precipitation Study -AMMA - long-term validation

41 Outlooks: COPS EUMETSAT special satellite operation modes and data European THORPEX Regional Campaign 2007 (ETReC07) General Observations Period (GOP) region, duration: 1 year in 2007 Transport and Chemistry in Convective Systems (TRACKS) region Region of COPS, accepted as WWRP RDP SFB 641 Tropospheric Ice Phase Mesoscale Alpine Programme (MAP) Forecast Demonstration Project (FDP) region Atmospheric Radiation Measurement (ARM) Program Mobile Facility (AMF)

42 ARM Mobile Facility (AMF) Atmospheric Radiation Measurement (ARM) Department of Energy (DOE) betreibt 2007 für 9 Monate AMF im COPS Gebiet PQP fügt abtastende Instrumentierung hinzu

43 Thanks for your help African Monsoon Multidisciplinary Analysis Djougou, Benin 2006