Geophysical validation of NSCAT winds using atmospheric data and analyses

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1 JOURNAL OF GEOPHYSCAL RESEARCH, VOL. 104, NO. C5, PAGES 11,405-11,424, MAY 15, 1999 Geophyscal valdaton of NSCAT wnds usng atmospherc data and analyses R. Atlas, 1 S.C. Bloom, 2 R. N. Hoffman, 3 E. Brn, 2 J. Ardzzone, 2 J. Terry, 2 D. Bungato, 2 and J. C. Jusem 2 Abstract. A detaled geophyscal evaluaton of the ntal NASA scatterometer (NSCAT) wnd data sets was performed n order to determne the error characterstcs of these data and ther applcablty to ocean surface analyss and numercal predcton. The frst component of ths evaluaton conssted of collocatons of NSCAT data to shp and buoy wnd reports, specal sensor mcrowave mager wnd observatons, and Natonal Centers for Envronmental Predcton and Goddard Earth Observng System (GEOS) model wnd analyses. Ths was followed by data assmlaton experments to determne the mpact of NSCAT data on analyss and forecastng. The collocaton comparsonshowed the NSCAT wnd velocty data to be of hgher accuracy than operatonal ERS 2 wnd data. The mpact experments showed that NSCAT has the ablty to correct major errors n analyses over the oceans and also to mprove numercal weather predcton. NSCAT data typcally show the precse locatons of both synoptc-scale and smaller-scale cyclones and fronts over the oceans. Ths often results n sgnfcant mprovements to analyses. Forecast experments usng the GEOS model show approxmately a 1-day extenson of useful forecast skll n the southern hemsphere, n good agreement wth the results of Observng System Smulaton Experments conducted pror to launch. 1. ntroducton usng scatterometer wnd vectors. Although the NSCAT msson was cut short after 9 months, suffcent data were collected Ocean surface wnds are the most mportant factor couplng the ocean and atmosphere. Surface wnds control the fluxes of momentum, heat, and mosture at the atmosphere-ocean nterface. They are key to the scentfc understandng of clmate and to operatonal forecastng at the long range (1 month to 1 year). Surface wnd data are also needed for nowcastng condtons at sea, for wave forecastng, for provdng boundary condtons for ocean general crculaton models, and for refnng the analyses of ocean surface wnd whch are part of the ntal condtons for numercal weather predcton (NWP). The ocean s vast; shps and buoys are few and rregularly located. Satellte mcrowave remote sensng of the ocean surface now provdes a complete and accurate depcton of the surface wnd over the ocean. The focus of ths paper s the valdaton of the wnd vectors observed by the NASA scatto establsh the hgh qualty of the NSCAT wnds and to demonstrate the utlty of these data for a varety of purposes. NSCAT s one of a seres of spaceborne scatterometers begnnng wth the Skylab msson and Seasat A n the 1970s [Grantham et al., 1977] and contnung n the 1990s wth the European Remote Sensng mssons, ERS 1 and ERS 2 [Francs et al., 1991]. Future NASA mssons nclude QUKSCAT (QSCAT) and Sea Wnds. Another set of actve mcrowave nstruments, altmeters, observes only wnd speed and only along the subsatellte track. Spaceborne passve mcrowave nstruments also observe the ocean surface wnd speed. Snce 1987, the specal sensor mcrowave mager (SSM/) nstruments [Hollnger et al., 1987] aboard the DMSP seres of satelltes have reported the ocean surface wnd speed wth great regularty, coverage, and accuracy. terometer (NSCAT) [Nader et al., 1991]. NSCAT was an actve The calbraton and valdaton actvtes for NSCAT data mcrowave radar, operatng at a frequency near 14 GHz and measurng the backscatter of the ocean surface. Ocean wnd were orgnally conceved as requred precursors to scentfc and operatonal use. NSCAT data were used operatonally by the Natonal vectors are retreved from multple observatons of backscatter Weather Servce's Marne Predcton Center from observed at varyng ncdence and azmuth angles [Brown, md-aprl 1997 through the demse of the Advanced Earth 1983]. The retreved wnds are ambguous; typcally, two wnds Observng System (ADEOS) 1 satellte at the end of June of nearly equal speed, but of nearly opposte drecton are most However, NSCAT data were never used operatonally consstent wth the backscatter observatons [Prce, 1976; Stof- for NWP purposes. Other scentfc uses of the NSCAT data felen and Anderson, 1997a]. Thus specal care s requred n are reported elsewhere n ths ssue; however, for many uses a longer record s requred. The calbraton and valdaton actv- Data Assmlaton Offce, NASA Goddard Space Flght Center, tes reported n ths specal secton and ths paper clearly Greenbelt, Maryland. demonstrate the hgh qualty of the NSCAT data and pont to 2General Scences Corporaton, Greenbelt, Maryland. very promsng scentfc and operatonal returns from future 3Atmospherc and Envronmental Research, nc., Cambrdge, Mas- Ku band scatterometer mssons. sachusetts. Copyrght 1999 by the Amercan Geophyscal Unon. Paper number 98JC /99/98JC ,405 Two prncpal valdaton approaches are used n ths study. Frst, collocaton statstcs are used to compare the NSCAT wnds to surface wnds from other sources, ncludng wnd observatons and meteorologcal analyses. The observatons

2 11,406 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS nclude those of shps and buoys and ERS 2. The analyses are those of the Natonal Centers for Envronmental Predcton terometer measurements are made of the same Earth locaton, and wnds are obtaned by optmally fttng these data. t should be noted that there are several prelmnary NSCAT data products avalable. These dffer n resoluton (25 or 50 (NCEP) and the Goddard Earth Observng System (GEOS). Second, lmted data mpact experments are used to evaluate the relatve effects of NSCAT, SSM/, and ERS 2 wnds km), geophyscal model functon (NSCAT 0 or NSCAT 1), and usng both the NCEP and GEOS data assmlaton systems ambguty selecton procedure (autonomous or nudged medan (DAS). A number of prevous studes have examned the mpact of scatterometer data n DAS. For example, Duffy and Atlas [ 1986], Stoffelen and Cats [ 1991 ], and Lenzen et al. [ 1993] examned the mpact of Seasat scatterometer data on the smulaton of the QE storm, and Hoffman [1993] studed the mpact of the ERS 1 scatterometer data on the European Centre for Medum-Range Weather Forecasts (ECMWF) flter). All NSCAT data used n ths study are 50-km resoluton data based on the NSCAT 0 model functon. Although our general concluson s that these NSCAT data are hgh qualty, we antcpate even better future reprocessed NSCAT data products due to refned model functons and mproved ambguty selecton methods. For example, NSCAT 1 data products have become avalable snce we began our study. DAS. Although experments of ths type are not generally used Four dfferent NSCAT wnd data sets are examned n ths for geophyscal valdaton, the comparson of the mpact of NSCAT data wth that predcted by Observng System Smulaton Experments (OSSEs) that were conducted pror to launch provdes a very useful measure of the degree to whch the expected performance of NSCAT has been acheved. The results of these experments are evaluated objectvely usng study. These are denoted: NSCAT S, NSCAT B, NSCAT N and NSCAT A for "speed only," "baselne,""nudged," and "ambguous." n bref, NSCAT S gnores NSCAT drectonal nformaton and uses only the wnd speed nformaton. NSCAT B resolves the ambguty usng a medan flter autonomously,.e., wth no a pror nformaton to seed or ntalze conventonal measures of analyss and forecast accuracy and the medan flter. NSCAT N s smlar to NSCAT B but uses subjectvely by comparng analyses and forecast felds. Specfc effects of the NSCAT data wll be llustrated by examnng specfc cases. The key measures examned n our valdaton are as follows: (1) the drecton and speed dfferences between NSCAT and other data types; (2) the number and patterns of NSCAT data rejected by the GEOS model's objectve qualty control (QC); (3) the synoptc plausblty of the NSCAT wnd patterns based on space-tme coherence, dynamc feasblty, and agreement wth meteorologcal experence and other nformaton; and (4) The effect of the NSCAT data on analyses and forecasts. n operatonal NCEP analyses to seed the medan flter. NSCAT A selects the ambguty closest n drecton to a prespecfed background feld. For comparson, European Space Agency (ESA) operatonal ERS 2 wnd vectors are also examned. For a fuller explanaton we defne some characterstcs of the NSCAT measurement process. The ndvdual backscatter observatons assocated wth the dfferent antennas and polarzatons are organzed by a grd orented along the satellte track. The grd boxes are termed wnd vector cells (WVCs). Nomnally there are 4 to 16 backscatter observatons n a 25- or 50-km WVC. The coordnates along and perpendcular to the partcular, the followng questons are addressed: Are analyses satellte track are called row and cell, respectvely. Each cell s and forecasts mproved on average? Do sgnfcant negatve effects occur? What s the magntude of the NSCAT mpact relatve to ERS 2 and SSM/? assocated wth nearly constant ncdence angle for each antenna, wth the values beng equal for the fore and aft antennas. Wnd ambgutes are retreved for each WVC contanng Secton 2 presents a bref descrpton of the scatterometer suffcent qualty-controlled backscatter observatons. The redata products that are evaluated n ths paper. Secton 3 shows treved wnds maxmze a lkelhood functon locally. The lkerepresentatvexamples of some of the NSCAT wnd products. lhood functon, n turn, depends on the geophyscal model Ths s followed n secton 4 wth the collocaton statstcs for functon to compare a canddate wnd to the backscatter ob- NSCAT relatve to n stu wnds, other satellte wnds, and atmospherc model analyses. Secton 5 presents the results of servatons [Ch and L, 1988; Offler, 1994]. Because of the nonlnearty of the model functon, several the data mpact experments that were conducted as a compo- wnd vectors consstent wth the backscatter observatons are nent of the geophyscal valdaton. Concludng remarks are gven n secton 6. usually found [Prce, 1976]. These multple wnd vectors are called alases n the early lterature and are now generally referred to as ambgutes. Wth two measurements, Seasat A 2. Scatterometer Data Products scatterometer system (SASS) typcally retreved four ambgutes. Wth addtonal measurements, NSCAT and ERS often Scatterometers are actve radars measurng the backscatter (normalzed radar cross secton (NRCS) or (r ø) from the Earth's surface. At moderate ncdence angles ( ø ) the major mechansm for ths scatterng s Bragg scatterng from centmeter-scale waves, whch are, n most condtons, n equretreve just two ambgutes approxmately 180 ø out of phase. The ambgutes are ordered by lkelhood. The frst ambguty s the ambguty wth the hghest lkelhood; t s most consstent wth the backscatter data. The second ambguty s usually of nearly equal speed and consstency, but of nearly opposte lbrum wth the local wnd. To date, emprcal relatonshps drecton. are superor to theory for the quanttatve descrpton of ths scatterng process. These emprcal relatonshps, called model functons, relate the backscatter to the geophyscal parameters and are derved from collocated observatons [Jones et al., 1977]. n current model functons the backscatter depends very nonlnearly on wnd speed and drecton. Although the scatterometer wnds are usually provded as neutral wnds at some reference heght, the measurement s physcally most closely connected wth surface stress [Brown, 1986]. Several scat- Snce the wnd retreval s performed for each WVC ndvdually, a wnd feld of frst ambgutes wll generally be very rregular and unphyscal. Spatal flterng can be used to produce a horzontally consstent wnd feld and resolve the drectonal ambguty. A varety of algorthms usng a varety of a pror nformaton have been appled to ths problem [Hoffman, 1984; Schroeder et al., 1985; Wentz, 1991; Th paut et al., 1993; Long, 1993; Stoffelen and Anderson, 1997b]. Pror to launch, smulaton studes establshed that NSCAT B, a me-

3 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,407 a) RMS DRECTON DFFERENCES' SCAT V SHPS SEPTEMBER - NOVEMBER 1996 (b) RMS DRECTON DFFERENCES' SCAT VS BUOYS SEPTEMBER- NOVEMBER 1996 ' H NSCAT-B NSCAT-N T -- ',,--- NSCAT-A w,,,,= - '-. c ---'-:' :'---"-._ = n' -''.. ''? --' ' """ "' ' '" 4o... %. T -, = = NSCAT-B / 1-- NSCAT-N '_"_._. _';",!e--ees^ "' % o = --...,% r --%, -... X l -, ß x o SPEED BN (rn/sec) ß --! 0,, SPEED BN (m/sec) C) RMS DRECTON DFFERENCES' SCAT VS GEOS-1 SEPTEMBER- NOVEMBER 1996 loo t.! H NSCAT-B. 1"- lb NSC^T-N [, -'- NSCAT-A ". % G-- )ESA "'-,, '. X : X. ERS2-A "" o) 60!, ' t w "--, '-,, %! "' '. Z.. T_":, -17.'"' 0 o o lo o SPEED BN (rn/sec) (d) RMS DRECTON DFFERENCES' SCAT VS NCEP SEPTEMBER - NOVEMBER 1996 H NSC^T-B ll---ra NSCAT-N!......; T SPEED BN {m ec) Plate 1. Rms drecton dfference collocaton statstcs. Speed bns are defned by the scatterometer data (see text for defntons of the varous scatterometer types). (a) Comparson wth shps, (b) comparson wth buoys, (c) comparson wth Goddard Earth Observng System (GEOS) 1, and (d) comparson wth Natonal Centers for Envronmental Predcton (NCEP). s *'20 dan flter operatng autonomously,.e., wth no a pror nformaton, would provde excellent ambguty selecton [Schultz, 1990; Shaffer et al., 1991]. The medan flter must be ntalzed or seeded wth some ntal choce of ambgutes. n autonomous mode the seed s the frst ambguty. n practce, NSCAT B has not performed as well as expected. For NSCAT N the seed s the ambguty closest to a background obtaned from the NCEP operatonal DAS. No further reference to the background s made; at the end of the process the chosen wnds are consstent wth backscatter observatons n the WVC and hor- zontally consstent wth neghborng WVCs, but are not necessarly close to the background. Dfferences between NSCAT B and NSCAT N results show that the medan flter has mul- tple solutons. Thus flterng does not resolve all ambguty n the sense that two dfferent wnd felds are plausble. NSCAT A selects the wnd vector ambguty closest to the background. By contrast, NSCAT S uses only the wnd speed assocated wth the prmary ambguty, takng a wnd drecton from the background. Both of these approaches tend to overemphasze the background. As a result, assmlaton of these data tends to renforce the background wnd drecton. The ERS 2 scatterometer wnd data used for comparson dffer from the NSCAT data n several respects. Frst, the ERS scatterometers operate at C band n contrast to the Ku band used by NSCAT. The lower-frequency C band has the strongest Bragg scatterng occurrng from 5-cm ocean waves as opposed to 2-cm waves for the Ku band. Consequently, the model functons are very dfferent. Second, the antenna and polarzaton patterns dffer [Francs et al., 1991]. Thrd, the resoluton of the ERS data s 25 km, but only a sngle 500-km swath s covered and no scatterometer wnds are avalable when the synthetc aperature radar (SAR) s operatng. Fourth, the ERS data used here suffer from beng a near-realtme operatonal product. t should be noted that ERS data of hgher qualty are now avalable, and these data should yeld somewhat better results than n the comparsons presented here [Stoffelen, 1998; Qulfen et al., 1998]. 3. NSCAT Wnd Patterns Fgures 1-3 present a few representatve examples of NSCAT ocean surface wnd patterns as llustratons of some of

4 11,408 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS a) RMSPEED DFFERENCES- SCAT VS SHPS SEPTEMBER- NOVEMBER 1996 s '... --O ESA... NSCAT-B F-- El NSCAT-N t SPEED BN (m/sec) (C) RMSPEED DFFERENCES' SCAT VS GEOS-1 ' SEPTEMBER - NOVEMBER "'..--'""" (b) RMSPEED DFFERENCES'SCAT VS BUOYS SEPTEMBER- NOVEMBER 1996!! r [! 5-1o H NSCAT-B E3 NSCAT-N... / t SPEED BN (rn/sec) (d) RMSPEED DFFERENCES'SCAT VS NCEP SEPTEMBER - NOVEMBER ! n [H NSCAT-B - -- El NSCAT- N SPEED BN (m/sec) H NSOAT-B B--- E3 NSCAT-N!! SPEED BN (rn/sec) e) RMSPEED DFFERENCES- SCAT VS SSM/ $ SEPTEMBER- NOVEMBER 1996 t T t-! '! 5.-lO SPEED BN (rn/sec) )--.o ESA H NSCAT-B --E NSCAT-N Plate 2. Rms speed dfference collocaton statstcs, wth speed bns defned as n Plate 1. (a) Comparson wth shps, (b) comparson wth buoys, (c) comparson wth GEOS 1, (d) comparson wth NCEP, and (e) comparson wth specal sensor mcrowave mage (SSM/) speeds.

5 ß ß ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,409 the dfferent scatterometer data products and of the synoptc "reasonableness" of the NSCAT data. n each case the ambguous NSCAT wnd drectons are presented along wth the baselne (NSCAT B) and nudged (NSCAT N) unque wnd vectors. The unque wnd vectors are depcted n standard meteorologcal format as wnd barbs, wth each barb representng 5 m s -. Fgure 1 shows a typcal example of a synoptc-scale cyclone n the North Atlantc. The ambguous wnds from the overlappng swath show the locaton of ths relatvely large cyclone very clearly. Ether of the ambguty removal approaches worked very well n ths case. The NSCAT B and NSCAT N wnd felds are dentcal n ther depcton of ths ntense storm, although the NSCAT N wnds are better to the north of the cyclone center. Whle agreement between the two ambguty 38b 35b 32b 38N 35N 32N 38N 63N N1 32B 158E Fgure 2. Same as Fgure 1, but for a subsynoptc-scale cy- clone n the North Pacfc N 57N Fgure 1. NASA scatterometer (NSCAT) wnd patterns assocated wth a synoptc-scale cyclone n the North Atlantc showng (top) NSCAT ambguous wnd drectons (NSCAT A) and unque wnds determned (mddle) wthout the use of a pror nformaton (baselne NSCAT or NSCAT B) and (bottom) wth the use of a pror nformaton for nudged NSCAT (NSCAT N) data. The wnd barbs dsplayed n Fgure 1 (mddle and bottom) are n standard meteorologcal format, wth each barb representng 5 m s -. removal methods s not uncommon, sgnfcant dfferences often occur for mportant features n the ocean surface wnd feld. Ths s llustrated n Fgures 2 and 3. Fgure 2 shows an example of an ntense subsynoptc-scale cyclone, contaned wthn a sngle swath, over the North Pacfc. The ambguous NSCAT wnds are more complcated than n the precedng case owng to the scale of the cyclone and the presence of ntense fronts. Nevertheless, the ambguous wnds dsplay a strong sgnature of ths cyclone n the northeast quadrant of the plot. The NSCAT B wnd feld msrepresents ths feature by choosng the ambgutes that are 180 ø n error to the north and west of the cyclone center. n contrast, the NSCAT N wnds portray ths cyclone very accurately. As a fnal llustraton, Fgure 3 shows an example of a strong warm front n NSCAT data. All three of the maps show the presence of a wnd shft over the Labrador Sea very clearly. n the ambguous wnds the two-vector (180 ø ) ambgutes are suffcento locate the presence of the front (ndcated by the dashed lnes n Fgure 3). The NSCAT B wnds are correct n the depcton of the wnd drecton over most of the area to the south of the front, but they are 180 ø n error to the north of the

6 11,410 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS Table la. Collocaton Statstcs: Scatterometer Data for Baselne NSCAT B System Speed, m s - Drecton, deg Tme Perod n Collocaton Data Number of Collocatons rms Bas rms Bas Percent Correct 1996 Shps 11, Sept. 15 to Nov. 19 Buoys Sept. 15 to Nov. 19 GEeS analyss 1,417, Oct. NCEP analyss 1,091, Nov SSM/ F10 1,246, Oct. GEOS s Goddard Earth Observng System; NCEP s Natonal Centers for Envronmental Predcton; SSM/ s specal sensor mcrowave mager. Table lb. Collocaton Statstcs: Scatterometer Data for Nudged NSCAT N Product Speed, m s- Drecton, deg Tme Perod n Collocaton Data Number of Collocatons rms Bas rms Bas Percent Correct 1996 Shps Buoys 11, Sept. 15 to Nov. 19 Sept. 15 to Nov. 19 GEeS Analyss 1,409, Oct. NCEP Analyss 1,088, Nov SSM/ F10 1,240, Oct. Table lc. NSCAT: Closest Ambguty Speed, m s- Drecton, deg Tme Perod n Collocaton Data Number of Collocatons rms Bas rms Bas 1996 Shps 12, Sept. 15 to Nov. 19 Buoys Sept. 15 to Nov. 19 GEeS analyss 1,441, Oct. NCEP analyss 1,111, Nov Table ld. ESA ERS 2: Closest Ambguty Speed, m s- Drecton, deg Tme Perod n Collocaton Data Number of Collocatons rms Bas rms Bas 1996 Shps Sept Buoys Sept GEeS analyss 1,037, Sept Table le. ESA ERS 2 Speed, m s- Drecton, deg Tme Perod n Collocaton Data Number of Collocatons rms Bas rms Bas 1996 Shps Sept Buoys Sept GEeS analyss 1,119, Sept SSM/ F10 1,331, Sept

7 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,411 Table 2a. Collocaton Statstcs: Percent Correct for NSCAT B, September 15 to November 19, 1996 NSCAT Speed Bns, rn s - Collocaton Data All Bns Shps Buoys Fgure 3. Same as Fgure 1, but for a warm front n the Labrador Sea. The locaton of the warm front s depcted as a dashed lne. front. The NSCAT N wnds do not make ths error and show the wnd feld assocated wth the warm front correctly. 4. Collocaton Statstcs Collocaton statstcs were computed n order to defne the dfferences between NSCAT data and other sources of wnd gree of representatveness, observatons were only used for collocaton f they occurred wthn 90 mn and 100 km of a NSCAT observaton. Of the shp and buoy observatons that met ths wndowng requrement, the closest observaton to the NSCAT report that passed the qualty requrements was used for collocaton. The qualty control proceeded n a number of steps. Frst, the shp or buoy observaton was compared to an analyzed feld from the GEeS DAS, and those falng a gross error check (see secton 5.3) were rejected. Next, a varatonal analyss (descrbed byatlas et al. [1996]) was performed on the remanng data, usng the GEeS analyss as a background feld. The varatonal analyss used here fnds a grdded wnd feld that mnmzes a functonal contanng a number of terms penalzng departures from the background, conventonal data, and NSCAT data, as well as contanng smoothness and dynamcal constrants. Then, the qualty check was performed agan, ths tme comparng the observatons aganst the varatonal analyss and usng a tghter acceptance crteron. All of the shp and buoy data were adjusted to 10 m for these collocatons. Collocatons wth SSM/ wnd speeds were performed n the areas where the data swaths overlapped. The SSM/ data on a 25-km grd were blnearly nterpolated to the NSCAT locatons. The NCEP and GEeS 1 analyzed felds were blnearly nterpolated from 2 x 2.5 ø grds to the NSCAT locatons. Tables la-le summarze the collocaton statstcs for NSCAT and ERS 2 data n relaton to each of the comparson data sets. The collocatons presented encompass all wnd speeds. Tables la-lc show results for NSCAT data havng dfferent ambguty removal strateges, whle Tables ld and le show collocatons for ERS 2 wnds wth smlar data sets. n order to obtan a "best" estmate of the agreement of NSCAT or ERS to a partcular valdaton data type, the ambguty (from ether NSCAT or ERS) that s closesto the valdaton data drecton was chosen and labeled "closest ambguty." These data (whose statstcs are shown n Tables lc and ld) gve the upper bound of the performance of the measurng system and model functon for each nstrument. Note that for all the bas statstcs presented here the collocated data are subtracted from the scatterometer data; thus a negatve bas would mply a scatterometer value consstently smaller than nformaton, as well as to evaluate the effectveness of the that from a collocated data source. geophyscal model functon and ambguty removal algorthms. For ths purpose, NSCAT data were collocated wth shp and The collocaton results for the baselne NSCAT B system shown n Table la reveal that NSCAT data have a small speed buoy observatons of surface wnd velocty and SSM/ wnd speed observatons. NSCAT data were also collocated wth GEOS and NCEP grdded analyses of surface wnd velocty Table 2b. Collocaton Statstcs: Percent Correct for that had been generated n real tme and dd not nclude NSCAT observatons. Fnally, ESA operatonal ERS 2 wnd vectors were collocated to many of the same data sets, and the NSCAT N, September 15 to November 19, 1996 NSCAT Speed Bns, rn s - results obtaned were compared wth those for NSCAT. Collocaton Data All Bns Two screenng crtera were used n selectng a shp or buoy observaton for collocaton wth a NSCAT observaton: wn- Shps Buoys downg and qualty. n order to mantan an approprate de-

8 11,412 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS bas (especally when compared to SSM/). The speed rms dfferences for these collocatons are also small. The problems nherent n NSCAT B data are revealed n the rms drecton dfferences, whch are large n comparson wth each of the valdaton data sets. The "percent correct" column gves an ndcaton that the ambguty removal process s the prmary source of the relatvely poor drecton behavor. Here "percent correct" refers to the percentage of tmes the chosen ambguty s the one closest n drecton to the verfyng wnd vector. NSCAT B only chooses the correct ambguty 72-75% of the tme. The results for the nudged NSCAT N product are presented n Table lb. Whle the speed collocaton statstcs are largely unaffected, there s a dramatc decrease n the rms drecton dfferences, and the percentage correct s sgnfcantly hgher. Table lc shows how much the rms drecton dfferences could be further reduced f the ambguty removal scheme worked perfectly. The decrease n drectonal rms between Tables lb and l c gves a measure of what could be ganed from mprovements to the ambguty removal process. For the sake of comparson, results from ERS 2 are shown n Tables l d and l e. The ERS 2 results show consstently hgher rms speed dfferences, larger speed bases, and hgher rms drecton dfferences. The operatonal product, shown n Table l e, shows results comparable to NSCAT B and much worse than the NSCAT N results. Tables 2a and 2b present a breakdown of the ambguty removal percentage correct nto four wnd speed bns. The wnd speed bns are defned by the scatterometer wnd speed. Thus the bns have the same meanng whether NSCAT s compared wth buoys or NCEP analyses. Note that other studes mght bn the collocatons on some other bass. t shows a very strong wnd speed dependence for NSCAT B and NSCAT N. The trend s for mproved ambguty removal as wnd speed ncreases, wth the excepton of a slght decrease for the hghest wnd speeds. The superorty of the nudged wnd product n relaton to the baselne product can be seen by comparng NSCAT N to NSCAT B over all wnd speeds, wth NSCAT N showng excellent results for wnd speeds greater than 5 m s-1. A further analyss of the speed and drecton statstcs as a functon of NSCAT wnd speed s presented n Plates 1-3. Plates la-ld show the behavor of rms drecton dfference for ERS and NSCAT data sets aganst shps, buoys, GEeS 1, and NCEP, respectvely. The man feature n these plots s the nearly unform decrease n rms drecton dfferences wth ncreasng speed (wth the man outler beng NSCAT B at the hghest speeds). That ths trend s heavly nfluenced by the ambguty removal process s shown by the nearly flat nature of the NSCAT A (NSCAT nearest ambguty), ERS 2 A (ERS 2 nearest ambguty), and, to a lesser extent, NSCAT N (NSCAT nudged) lnes. There s no sgnfcant drectonal bas for any of the scatterometer data comparsons. Speed collocaton statstcs are shown n Plates 2 and 3. The overall smlarty between the NSCAT B and NSCAT N results s due to the fact that the dfferent NSCAT wnd ambgutes have nearly dentcal speeds. n general, the rms speed dfferences, shown n Plate 2, ncrease wth larger wnd speeds. Exceptons to the monotonc ncrease n rms speed dfferences occur n speed bns where the speed bas statstcs are decreasng rapdly: ERS aganst shps, NSCAT aganst shps, GEeS 1, and NCEP. The best rms agreement, for both ERS and NSCAT, occurred wth SSM/ wnd speeds. NSCAT agreement wth buoy data was nearly as good (there was an nadequate Table 3. Data Assmlaton Experments Experment Control SSM/ ERS 2 NSCAT NSCAT NSCAT NSCAT B N A S Data Used all conventonal data plus STS plus CTW control plus Wentz [1991] SSM/ Wnd Speeds control plus ESA ERS 2 wnd vectors control plus baselne NSCAT wnd vectors control plus nudged NSCAT wnd vectors control plus ambguous NSCAT wnd vectors control plus NSCAT wnd speeds Spn-up occurred from 0300 UTC on September 10 to 0300 to UTC on September 15, Assmlaton was from 0300 UTC on September 15 to 0300 UTC on November 12, The 5-day forecasts ncluded eght ndependent cases from the assmlaton perod. STS s satellte temperature soundngs; CTW s cloud-tracked wnds. sample of collocatons of ERS wth buoys for ths study). Where the ERS and NSCAT rms statstcs dffer the most, shps and GEeS 1, the ERS bas statstcs n Plate 3 have consstently greater magntude. The poorer rms agreement of the scatterometer data wth the two data assmlaton systems s lkely a consequence of the nadequaces of those systems n resolvng small but strong mesoscale features. The NSCAT bas collocaton statstcs shown n Plate 3 have a general smlarty: they ndcate a low bas for low wnd speeds, lttle bas for ntermedate wnd speeds, and a hgh bas for larger wnd speeds. Ths s probably an artfact of the underlyng model functon (NSCAT 0); a later verson of the NSCAT model functon (NSCAT 1) was desgned to address some of these problems (especally the bases at low wnd speeds). 5. Data mpact Experments The experments that we performed were amed at assessng the relatve utlty of NSCAT, SSM/, and ERS 2 wnds, the relatve contrbutons of NSCAT drectonal and speed nformaton, and the effectveness of the NSCAT ambguty removal algorthms. For the ntal experments a 2 ø x 2.5 ø resoluton verson of the GEeS 1 DAS s used. Ths system has been descrbed n detal by Schubert et al. [1993] and was used prevously n observng system experments to assess the mpact of ERS 1 wnds [Atlas et al., 1995]. The prmary reason for choosng ths system for the ntal experments s because t was prevously used n observng system smulaton experments (esses) for NSCAT [Atlas, 1997]. As such, a comparson of the current "real" data experments wth the earler "smulated" data experments provdes both an evaluaton of the esse methodology, as well as a measure of whether NSCAT s performng close to expectatons Expermental Desgn A control assmlaton was generated usng all avalable data (conventonal surface data, rawnsondes, arcraft observatons, satellte temperature soundngs, and cloud-drft wnds), wth the excepton of satellte surface wnds. Then assmlatons were generated that added ether SSM/ wnd speeds, NSCAT wnd speeds (NSCAT S), ERS 2 unque wnd vectors, NSCAT ambguous wnd vectors (NSCAT A), or NSCAT unque wnd vectors determned from the baselne ambguty removal method n whch no external nformaton s used (NSCAT B) or one n whch model felds have a weak nfluence (NSCAT N). The experments that were performed are summarzed n Table 3. For

9 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,413 SPEED BAS' SCAT VS SHPS SEPTEMBER - NOVEMBER 1996 (b) r 1 ' o, T SPEED BAS ß SCAT VS BUOYS SEPTEMBER - NOVEMBER r -!...- -, t O--O ESA H NSC^T - B 13.,-- D NSCAT-N SPEED BN (m/sec)! ,, SPEED BN (mlsec) (C) 2 1 's' o {, 13 uj a. -1 -,._ SPEED BAS' SCAT VS GEOS-1 SEPTEMBER- NOVEMBER 1996 T r,--e NSC^T-N 3-- O ESA... HNSCAT-B... SPEED BN (m/sec) (d) SPEED BAS' SCAT VS NCEP SEPTEMBER- NOVEMBER T q--- H NSCAT-B t-!-- E] NSCAT--N 5-1o SPEED BN (m/sec) SPEED BAS' SCAT VS SSM/ SEPTEMBER- NOVEMBER ! = =NSCAT-B -2 - t fl-- O-- NSCAT-N ESA -: SPEED BN (mlsec) Plate Same as Plate 2, but for speed bas collocaton statstcs.

10 11,414 ATLAS ET AL.' GEOPHYSCAL VALDATON OF NSCAT WNDS 45OO QC REJECTON STATSTCS 4OOO ] --.CAr-e --- NSOOT-N ld 0 (. 25OO to 20OO... ½D ,.. t- :'" ;:4!t, ß ß, ' 21 EP 26{Ep ( CT - ' 6OCT 1100T )GT 210CT Plate 4. Numbers of rejected NSCAT B (black), NSCAT N (red), and NSCAT A wnds (blue) durng the frst 2 months of data assmlaton wth the GEOS 1 DAS. Date each experment an assmlaton for nearly 2 months was performed and then eght ndependent numercal forecasts were generated (from ntal states obtaned at approxmate 5-day ntervals wthn the 2-month assmlaton perod). All of the forecasts were verfed aganst GEOS 1 analyses (wthout any satellte surface wnd data) that had prevously been generated for a stratospherc experment n real tme Descrpton of the GEOS 1 Data Assmlaton System delta-eddngton approxmaton [Joseph et al., 1976; Kng and Harshvardhan, 1986]. The penetratve convecton orgnatng n the boundary layer s parameterzed usng the relaxed Arakawa-Schubert (RAS) scheme [Moorth and Suarez, 1992], whch s a smple and effcent mplementaton of the Arakawa and Schubert [1974] scheme. The planetary boundary layer (PBL) s explctly resolved n a two- to four-layeregon. Wnd, temperature, and humdty profles n an "extended" surface layer (whch can be up to 150 m thck) and the turbulent fluxes of heat, mosture, and momentum at the surface are obtaned from Monn-Obukhov smlarty theory by selectng smlarty functons The man components of the data assmlaton system are the GEOS 1 model and a three-dmensonal, multvarate optmal nterpolaton (O) scheme. These components, as well as that approach the convectve lmt for unstable profles and that the qualty control of data are summarzed below. agree wth observatons for very stable profles. Surface roughness The GEOS 1 model. The GEOS 1 model employs a lengths are taken as a functon of surface stress over water. Turpotental enstrophy and energy-conservng horzontal dfferencng scheme on a C grd developed by Sadourney [1975] and bulent fluxes above the extended surfaced layer are computed further descrbed by Burrdge and Haster [1977]. An explct usng the second-order closure model of Helfand and Labraga leapfrog scheme s used for tme dfferencng, applyng an [1988]. n ths scheme the turbulent knetc energy s a prognostc Assdn [1972] tme flter to damp out the computatonal mode. varable, and the remanng second-order moments are dagnosed An eghth-order Shapro flter s appled to the wnd, potental from t and the atmospherc soundng. temperature, and specfc humdty to avod nonlnear compu- The standard resoluton of GEOS 1 s 2 ø lattude by 2.5 ø tatonal nstablty. The model's vertcal fnte-dfferencng longtude wth 20 o- levels. The sgma levels are dstrbuted to scheme s that of Arakawa and Suarez [1983]. The nfrared and provde enhanced resoluton n the planetary boundary layer solar radaton parameterzatons follow closely those de- and at upper levels. The sea surface temperature s updated scrbed by Harshvardhan et al. [1987]. Cloud albedo and trans- accordng to the observed monthly mean values provded by mssvty for the model layers are obtaned from specfed sn- the Clmate Analyss Center at NCEP and the Center for gle-scatterng albedo and cloud optcal thckness usng the Ocean, Land and Atmosphere (COLA).

11 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11, The data assmlaton process. The O analyss s carred out at a horzontal resoluton of 2 ø lattude by 2.5 ø longtude at 12 upper ar pressure levels (from 50 to 1000 hpa) and at sea level. The analyss ncrements are computed every 6 hours usng observatons from a _+3-hour data wndow centered on the analyss tmes (0000, 0600, 1200, and 1800 UTC). (n more recent experments wth the GEOS 2 DAS, scatterometer data are treated asynoptcally.) The nnovaton vector (observaton mnus background forecast) used as nput to the O s computed usng a sngle forecast vald at the analyss tme. enhanced n the followng four ways: 1. The physcs of the GEOS PBL scheme s used consstently. Frst, we create a frst-guessurface wnd feld consstent wth the GEOS DAS planetary boundary layer parameterzaton (GEOS PBL) at the level of the observatonal data. The dfferences between ths frst-guessurface wnd feld and surface wnd observatons ("observaton ncrements") are used n the surface analyss, whch generates analyss ncrements of sea level pressure and surface wnd that are added to the frst-guess values of these felds. 2. The sea level pressure/surface wnd analyss s multvarate. Thus the scatterometer data nfluence the sea level pressure analyss as well as the surface wnd analyss. Modfcatons to the sea level pressure feld nfluence the way n whch the GEOS system assmlates satellte thckness observatons. On the bass of the hydrostatc relatonshp, the frst-guess hpa heght feld s adjusted n accordance wth the sea level pressure analyss. The adjusted heght s then used to convert satellte thckness observatons nto heght observatons (whch are the nput to the GEOS DAS upper ar analyss). 3. Observaton ncrements of 1000-hPa heghts are calculated wherever satellte surface wnd observatons are used by the surface analyss. These ncrements are hydrostatcally consstent wth the sea level pressure analyss ncrements and are used drectly as "pseudo-observatons" of 1000 hpa heght n the GEOS 1 upper ar analyss. 4. The analyzed surface wnd feld s used to compute the wnd feld at the lowest model level consstent wth the GEOS For the global sea level pressure and near-surface wnd analyss over the oceans, data from surface land synoptc reports (sea level pressure only), shps, and buoys are used. The upper ar analyses of heght, wnd, and mosture ncorporate the data from rawnsondes, dropwndsondes, arcraft wnds, cloud-tracked wnds, and heghts from the TROS operatonal vertcal sounder (TOVS) soundngs produced by the Natonal Oceanc and Atmospherc Admnstraton (NOAA) Natonal Envronmental Satellte Data and nformaton Servce (NES- PBL. The analyss ncrements of ths feld are then nterpolated to all the model levels below 850 hpa, thereby extendng the DS). The satellte heghts are computed from satellte thck- vertcal nfluence of the scatterometer data. nesses usng a reference level that depends on the analyzed sea level pressure. t s for ths reason that the surface analyss s performed before the upper ar analyss. The O scheme used for the upper ar analyss s multvarate n geopotental heght and wnds and employs a damped cosne functon for the horzontal correlaton of model predcton The above procedure allows scatterometer data to make consstent modfcatons to the sea level pressure and hgherlevel wnd and mass felds. Harlan and O'Bren [1986], Levy and Brown [1986], and Hsu and Lu [1996] have all shown benefts of usng scatterometer data to mprove sea level pressure felds, whle Duffy and Atlas [1986] demonstrated the need to error. The heght-wnd cross-correlaton model n the upper ar extend the vertcal nfluence of scatterometer wnds n data analyss s geostrophc and scaled to zero at the equator. A assmlaton. separate multvarate (n surface wnd and sea level pressure) 5.3. analyss scheme s used for sea level analyses over the oceans. Qualty Control The sea level analyss employs an Ekman balance for the pressure-wnd cross-correlaton model. The mosture analyss for mxng rato employs only rawnsonde mosture data. The anal- The qualty control technque employed n the GEOS 1 DAS conssts of two major steps, a gross error check and a buddy check. The gross error check s defned as yss at each grd pont uses up to 75 nearby observatons from wthn a crcular data selecton cylnder of 1600 km radus. The assmlaton system does not nclude an ntalzaton where <_ A s the dfference + between an observaton and the scheme and reles on the dampng propertes of a Matsuno tme-dfferencng scheme to control ntal mbalances generated by the nserton of observatons. However, the ntal mbalances and spn-up have been greatly reduced over earler versons by the ntroducton of an ncremental analyss update nterpolated background frst-guess value; (r rø) 2 and (err) 2 are the observaton and forecast error varances, respectvely; and r s a subjectvely defned tolerance value that vares wth quantty, lattude, and heght. Those data that fal to satsfy the above relaton are marked as suspect. The buddy check n- (AU) procedure [Bloom et al., 1996]. n the AU procedure, volves performng a smplfed unvarate spatal nterpolaton standard O analyss ncrements are computed at the analyss tmes (0000, 0600, 1200, 1800 UTC). The ncrements are then nserted gradually nto the model by rerunnng the forecast and addng a fracton of the ncrement at each model tme step. Over the 6-hour perod centered at the analyss tme the full of the data that passed the gross check to the locatons of the suspect data. The dfference between the nterpolated value and the suspect value s then compared to the error statstcs n a manner smlar to the relaton used for the gross check, and a decson s then made ether to accept or to reject the obsereffect of the ncrement s realzed. The assmlaton thus effec- vaton. For NSCAT data, A s the magntude of the wnd vector tvely conssts of a contnuous model forecast wth addtonal heat, momentum, mosture, and mass source terms updated every 6 hours from observatons. dfference between the NSCAT wnd report and the frst-guess surface wnd feld nterpolated to the observaton locaton. The value of rr ø used for NSCAT s 2.8 m s- n these experments. Wthn GEOS the nfluence of satellte surface wnds s Ths s the same value as used for shp wnd data n GEOS 1. A global value of r = 2.0 s used n the surface wnd qualty control procedure. Typcal falure modes for the ambguty selecton are llustrated n Fgures 2 and 3 for the NSCAT B data. The objectve qualty control s very effectve n rejectng ambguty removal errors of ths magntude. However, the QC s somewhat conservatve, and t s not uncommon for some accurate NSCAT data to also be rejected. Ths s partcularly true for wnds assocated wth features too small to be resolved by GEOS model.

12 11,416 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS z z z z z z z z z z z z z z z

13 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,417 The rejecton rates for NSCAT data depend very strongly upon the method of ambguty removal. Plate 4 shows the numbers of NSCAT B, NSCAT N, and NSCAT A data rejected durng the frst 2 months of data assmlaton. Ths fgure reveals the much hgher rejecton rates for the NSCAT B data that result from the less accurate ambguty removal. Ths can also be seen from Fgure 4, whch shows typcal patterns of rejected wnds for each of these data sets. The clusterng of rejected data that s evdent n Fgure 4 results prmarly from sgnfcant errors n ambguty removal n these areas. ntude dfferences between the control and NSCAT N analyses exceedng 25 m s -. An mportant queston wth regard to the above mpacts s whether or not the dfferences between the control and NSCAT N experments represent mprovements to surface wnd analyses. Whle no absolute ground truth exsts, n every case of sgnfcant mpact n our experments, the NSCAT data provded clear unequvocal evdence (smlar to that n Fgure 9d) to support the modfcaton to the control analyss that occurred. There were, however, smaller negatve effects pr Analyss mpacts n ths subsecton the mpact of NSCAT data on GEOS 1 analyses s presented. For brevty, the dscusson here s lmted to NSCAT N wnds. The mpact of the other NSCAT data sets s smlar, but smaller for NSCAT S, and slghtly smaller for marly assocated wth treatng the NSCAT wnds as synoptc observatons (that s, treatng the NSCAT wnds as f they were all observed at the analyss tme). One way to further valdate the NSCAT wnds and the analyses usng these data s to perform forecast experments. These are descrbed n secton 5.5. NSCAT B and NSCAT A. n data assmlaton the mpact of any specfc type of data 5.5. Forecast mpacts typcally grows n tme (and space) from the frst nserton of The GEOS 1 model forecasts that are descrbed below were the data. Ths s due to the model ntegraton process where the mpact on each analyss affects the model's 6-hour forecast. Ths 6-hour forecast then becomes the background for the next analyss, thereby amplfyng the ntal mpact untl an asymptotc level approprate for the data type s reached. Ths same effect s observed for the NSCAT data mpact. Fgure 5 dsplays the locatons of the frst 6 hours of NSCAT performed as a component of the overall valdaton of NSCAT wnds. Eght ndependent 5-day forecasts were generated from the control assmlaton. These were followed by correspondng forecasts from the assmlatons whch added ether SSM/, ERS 2, NSCAT B, NSCAT N, NSCAT A, or NSCAT S ocean surface wnds to the control. All of the forecasts were verfed aganst GEOS 1 analyses (wthout any satellte surface wnd data that were assmlated nto GEOS 1 and the dfferences data) that had been generated prevously n real tme. (The between the control and NSCAT N surface wnd analyses that resulted from the frst nserton of ths data. From Fgure 5 t can be seen that all along the NSCAT swaths, modfcatons to the GEOS 1 surface wnd analyss occur. Although the ndvdual vector dfferences cannot be seen on ths global plot, t s clear that even the ntal analyss mpact s spatally coherent and covers large areas. The most sgnfcant dfferences occur over the southern hemsphere extratropcs. Fgure 6 shows the mpact on both the sea level pressure and surface wnd analyses for a porton of ths regon. Here a sgnfcant mpact of 11 results of the evaluaton of 2 to 5-day forecast skll presented n ths secton were found to be nearly ndependent of the analyss chosen for verfcaton. Very smlar results were obtaned when the forecasts were verfed aganst ECMWF analyses or drectly aganst shp, buoy, NSCAT, or cloud-track wnd data.) The objectve measures of forecast accuracy that were appled to a wde range of prognostc varables from each of these experments nclude anomaly correlaton, rms error, and S1 skll score. For brevty, only the sea level pressure anomaly correlatons for the averages over all eght forecasts are prehpa n pressure and up to 17 m s - n wnd vector magntude sented for the northern and southern hemsphere extratropcs. can be seen. The mpact on wnds above the surface s shown (An anomaly correlaton of 1.0 represents a perfect forecast, as a vertcal cross secton through ths regon n Fgure 7. On the frst nserton of NSCAT data, GEOS 1 wnds from the surface through 750 hpa are modfed; 6 hours later, the mpact whle 0.60 s generally consdered to be the lmt of useful forecast skll.) A subjectv evaluaton of each of the forecasts was also performed. One example to llustrate the mpact of NSCAT N wnds on GEOS 1 sea level pressure forecasts s presented. Fgures summarze the forecast mpact results. n each of the fgures the control and NSCAT N forecast accu- on wnds extends through the entre model atmosphere. Fgure 8 shows that after 6 days of assmlaton the mpact of NSCAT has grown substantally. n partcular, modfcatons to GEOS 1 surface wnd analyses are evdent over the global oceans, not just the swaths, and the magntude of the mpact s races are ncluded for reference. Fgure 10 shows the average larger. Fgures 9a-9c llustrate the large mpact that occurred anomaly correlatons for the NSCAT B, NSCAT N, NSCAT A, over the North Pacfc. mpacts of ths magntude, whle com- and control forecasts. Comparng the accuraces of each of mon n the southern hemsphere, occur only nfrequently n the these forecasts evaluates both the overall mpact of NSCAT northern hemsphere. They are typcally assocated wth the data and the relatve mpact of the three drectonal ambguty correcton of a poston error for an mportant meteorologcal approaches. From Fgure 10 t can be seen that n the northern feature such as a cyclone or antcyclone. n addton, NSCAT hemsphere extratropcs there s, on average, vrtually no dfsometmes observes a feature that s not present n the control ference between any of the forecasts. However, a very sgnfassmlaton or ndcates that a feature n the control analyss s cant postve mpact of NSCAT data s evdent n the southern spurous. n the case shown n Fgure 9 the assmlaton of hemsphere. The assmlaton of each of the NSCAT data sets NSCAT data resulted n a sgnfcant change n the poston of results n a large ncrease n anomaly correlaton relatve to the the cyclone n the North Pacfc and a decrease n ts central control from days 2-5 of the forecast. n addton, the 5-day pressure. Fgure 9d shows the NSCAT N data that was respon- forecast wth any of the NSCAT data sets s more accurate sble for ths change. t ndcates very clearly that the cyclone at than the 4-day control forecast wthout NSCAT data. These 160øE n the control analyss should be located farther east. results help to valdate the NSCAT data and ndcate that the The analyss mpacts n the southern hemsphere at the same mpact of NSCAT data on ocean surface wnd analyses s tme are even larger, wth maxmum surface wnd vector mag- overwhelmngly postve.

14 11,418 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 46S Fgure 6. Sea level pressure and surface wnd dfferences between the NSCAT N and control analyses n the eastern South Pacfc on 0600 UTC on September 15, The dfferences between the NSCAT B, NSCAT N, and NSCAT A results are smaller than mght be expected from the collocaton statstcs presented n secton 4 or the synopt comparsons presented n secton 3. Ths s probably due to the effectveness of the objectve qualty control n elmnatng large ambguty removal errors and to the coarse horzontal resoluton of the GEOS 1 DAS. Overall, the NSCAT N forecast results are slghtly superor to those of NSCAT B and NSCAT A. Fgure 11 provdes a comparson of the relatve mpact of SSM/ and NSCAT wnd speeds, as well as the relatve mportance of NSCAT speed and drectonal nformaton. As n Fgure 10, there s, on average, no mpact of any of the satellte surface wnd data sets on the sea level pressure forecasts for the northern hemsphere extratropcs. n the southern hemsphere extratropcs the use of ether the SSM/ or NSCAT S wnds results n a sgnfcant mprovement n forecast accuracy. For both data sets the mpact s about half that of the NSCAT N mpact through most of the forecast perod. Ths ndcates that the NSCAT wnd speeds are of comparable utlty to those of SSM/ and that both the NSCAT drectons and speeds are addng very useful nformaton for data assmlaton. Fgure 12 compares the mpact of the ESA operatonal ERS 2 ocean surface wnds wth those of SSM/ and NSCAT. Once agan, there s no mpact dscernable n the northern hem- 10C ] ] 251] 30½ 35½ 40t] 451] 50t], { /1 -, L. % 1 140W 128W 116W 104W 92W 80W Longtude Fgure 7. Vertcal cros sectonshowng (top) wnd dfferences between the NSCAT N and control analyses along lattude 62øS, resultng from the frst nserton of NSCAT N data at 0600 UTC on September 15, 1996 and (bottom) 6 hours later after model ntegraton and subsequent analyss.

15 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,419 90N 60N 30N EO 30S N H., 0- ' H H o.,-,<,e.,. ','...,., : y s, 2 / ' H q - -- '[k H :,,,, ';;',;, XS - H - "--2 H. x H z 905 3DE 7DE 10E 15OE 17OW l 3OW 9OW SOW 1 OW 3DE Fgure 8. Dfferences between the GEOS 1 NSCAT N and control analyses of ocean (top) surface wnd and (bottom) sea level pressure at 0600 UTC on September 21, 1996.

16 (a) 42N 1o 1 --1oo8-- oo4-- 1oo4-- 1oo8-T-1 o! (b) t oo8--1 oo4--t oo4 -- rl oo o 16--t o o Fgure 9. llustraton of the mpact of NSCAT data on the analyss of a cyclone over a porton of the North Pacfc at 0600 UTC on September 21, 1996, showng (a) control and (b) NSCAT N sea level pressure and surface wnd analyses, (c) the dfferences between them, and (d) NSCAT wnds that were responsble for the mpact, wth the postons of the control (Lc) and NSCAT N (Ln) cyclone centersupermposed. Z 1.0 O LAT' 30N- 86N LONG' 0-355E O.80 O Control _ NSCAT-B... NSCAT-N NSCAT-A DAY 1.0 LAT' 86S - 30S LONG' 0-355E...'. / NSCAT-N NSCAT, [ Control DAY Fgure 10. Relatve mpact of NSCAT B, NSCAT N, and NSCAT A data on GEOS 1 model forecasts showng sea level pressure for (top) northern and (bottom) southern hemsphere extratropcs.

17 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,421 N O J.V }} O D X VA O NV NOœV }}O D X VA O N V = NO &V }}O D X VA O N V N O J.V }} O D X VA O N V

18 11,422 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 20S 30S 40S 50S 60S 20S 40S 50S 60S 20S 30S 40S 50S and the representaton of the sea level pressure rdge to the southwest of ths cyclone. The results presented n ths secton are partcularly sgnfcant for valdaton because an OSSE conducted pror to the launch of NSCAT [Atlas, 1997] predcted very smlar results. Ths OSSE had ndcated a very substantal mprovement n forecast skll wth the GEOS 1 model n the southern hem- sphere and a small mprovement n forecast skll n the northern hemsphere and that the mpact of NSCAT would be much larger than for ERS or SSM/. The most sgnfcant dscrepancy between the OSSE and real data mpact results appears to be the lack of any mpact, on average, n the northern hemsphere. The prmary reason for the lack of dscernable mpact n the northern hemsphere s the relatvely large amount of rawnsonde data over contnental areas and shp and buoy observatons over the North Atlantc and North Pacfc. The northern hemsphere analyses are thus of hgher qualty than those for the southern hemsphere, and there s usually less room for mprovement from spacebased data. Nevertheless, the OSSEs dd ndcate a modest mprovement n forecast skll for the northern hemsphere, and ths was not acheved n ths ntal experment wth the GEOS 1 DAS. Ths dscrepancy due, n part, to one of the smplfyng assumptons of the OSSE. n that experment, NSCAT data were smulated as beng synoptc,.e., at 6-hour ntervals, wth no tme dsplacement from the analyss tmes. Therefore n the OSSE there was no error assocated wth assmlatng the data at 6-hour ntervals. Ths suggests that takng account of the asynoptcty of the NSCAT wnds would mprove ts mpact n the northern hemsphere. ntal experments wth a verson of the GEOS 2 DAS, n whch NSCAT wnds are treated asynoptcally, have ndcated a substantal mprovement n mpact n the northern hemsphere. Ths, as well as the use of NSCAT wnds n other DAS, wll be the subject of a later paper. Fgure 13. The (top) 96-hour control and (mddle) NSCAT N sea level pressure forecasts for a porton of the southern hemsphere and (bottom) the verfyng analyss (generated wthout NSCAT data) at 0000 UTC on November 1, sphere. n the southern hemsphere the mpact of the ERS 2 wnd vectors s also very small, on average, and can be seen to be much less than the mpact of SSM/ or NSCAT. Ths result s very dependent upon the use of the operatonal ERS 2 product, and t s lkely that other ERS 2 wnd vector data sets mght yeld a larger mpact. Fgure 13 presents an example of the mpact of NSCAT wnds on numercal predcton. n the fgure the GEOS 1 96-hour control and NSCAT N sea level pressure forecasts from 0000 UTC on October 28, 1996, and the correspondng verfcaton are shown for a porton of the southern hem- 6. Summary and Concludng Remarks The NASA scatterometer was launched on board the Japanese ADEOS 1 satellte on August 16, Followng the launch, a detaled geophyscal evaluaton of the ntal NSCAT data sets was performed n order to determne the error characterstcs of these data and ther applcablty to ocean surface analyss and numercal weather predcton. Ths evaluaton conssted of collocatons of NSCAT data to a varety of atmospherc data sets and model analyses, synoptc evaluatons of NSCAT wnd patterns n whch dfferent methods of ambguty selecton were appled, and data assmlaton experments to determne the mpact of NSCAT wnds on analyss and forecastng. Results from ths evaluaton ndcate that the NSCAT data are extraordnarly useful. The collocaton comparson show the NSCAT wnds to be of hgher accuracy than the operasphere extratropcs. Comparson of the forecasts wth the ver- tonal ERS 2 wnd data. These comparsons together wth the fyng analyss shows a very sgnfcant mprovement to the synoptc evaluaton also demonstrate the need for usng a cyclonc crculaton over ths area. n partcular, the central pressure and structure of the ntense cyclone south of Afrca are mproved very substantally, and the cyclone's poston error s reduced by more than 500 km. Other mprovements pror nformaton n ambguty removal, when usng the NSCAT 0 model functon and show the desrablty of mprovng the model functon at both hgh and low wnd speeds. The results of our data assmlaton experments ndcate nclude the formaton of the weaker cyclone near 47øS, 5øW that the use of NSCAT data n the GEOS 1 data assmlaton

19 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS 11,423 system yelds very sgnfcant mprovements to atmospherc Asseln, R., Frequency flter for tme ntegratons, Mon. Weather Rev., 100, , analyses over the global oceans. The resultng mprovement to Atlas, R., Atmospherc observatons and experments to assess ther numercal weather forecasts s equvalent to about a 24-hour usefulness n data assmlaton, J. Meteorol. Soc. Jpn., 75(1B), 111- extenson n useful forecast skll n the southern hemsphere. 130, Ths mpact was found to be much larger than for SSM/ or Atlas, R., R. N. Hoffman, E. Brn, and P.M. Woceshyn, The mpact operatonal ERS 2 wnd data, n agreement wth earler obof ERS-1 scatterometer data on GEOS model forecasts, n nternatonal Symposum on Assmlaton of Observatons n Meteorology and servng system smulaton experments. n the more data-dense Oceanography, Publ. WMO TD-651, pp , World Meteorol. northern hemsphere, the mpact of all satellte surface wnd Organ., Geneva, data sets on GEOS 1 was neglgble, on average, but, on oc- Atlas, R., R. N. Hoffman, S.C. Bloom, J. C. Jusem, and J. Ardzzone, cason, sgnfcant mprovements to the analyss and predcton A multyear global surface wnd velocty dataset usng SSM/ wnd observatons, Bull. Am. Meteorol. Soc., 77(5), , of cyclones and fronts due to NSCAT wnd data were observed. Bloom, S.C., L. L. Takacs, A.M. da Slva, and D. Ledvna, Data Whle t s not possble to generalze the results of these assmlaton usng ncremental analyss updates, Mort. Weather Rev., experments to other data assmlaton systems, the results 124, , Brown, R. A., On a satellte scatterometer as an anemometer, J. Geopresented here suggest consderable potental for scatteromphys. Res., 88, , eter data to correct sgnfcant analyss errors when they occur. Brown, R. A., On satellte scatterometer capabltes n ar-sea nter- Addtonal data mpact experments wth the GEOS 2 and acton, J. Geophys. Res., 91, , NCEP data assmlaton systems are ether recently completed Burrdge, D. M., and J. Haseler, A model for medum range weather or underway and wll be descrbed n future papers. The GEOS forecastng-adabatc formulaton, Tech. Rep. 4, European Centre for Medum-Range Weather Forecasts, Readng, England, studes appear partcularly noteworthy, n that the control Ch, C.-Y., and F. K. L, A comparatve study of several wnd estmaresults are much mproved, yet the mpact of NSCAT data s ton algorthms for spaceborne scatterometers, EEE Trans. Geosc. ncreased. Ths s contrary to the usual result that mprove- Remote Sens., 26, , ments n data assmlaton systems result n smaller mpacts Duffy, D., and R. Atlas, The mpact of seasat-a scatterometer data on the numercal predcton of the QE storm, J. Geophys. Res., 91, from a partcular data source. At least one of the key aspects , here appears to be the asynoptc use of the NSCAT data. Ths Francs, R., et al., The ERS-1 spacecraft and ts payload, ESA Bull., 65, has been emphaszed by Person et al. [1986] and seems to be 27-48, Grantham, W. L., E. M. Bracalente, W. L. Jones, and J. W. Johnson, requred to get a regular postve mpact n the northern hem- The Seasat-A satellte scatterometer, EEE J. Oceanc Eng., OE-2, sphere. n addton to the above experments, further research , s beng performed to optmze the use of NSCAT wnd data n Harlan, J., Jr., and J. J. O'Bren, Assmlaton of scatterometer wnds combnaton wth other remotely sensed data, ncludng ERS 2 nto surface pressure felds usng a varatonal method, J. Geophys. Res., 91, , scatterometer wnds and SSM/ wnd speeds. Harshvardhan, H., R. Daves, D. A. Randall, and T. G. Corsett, A fast The utlty of NSCAT wnd data for operatonal use by radaton parameterzaton for atmospherc crculaton models, J. marne and hurrcane predcton centers should also be noted. Geophys. Res., 92, , Patterns n the ambguous wnd felds, readly seen by the Helfand, H. M., and J. C. Labraga, Desgn of a non-sngular level 2.5 human eye, allow the precse locaton of cyclone centers. Thus second-order closure model for the predcton of atmospherc turbulence, J. Atmos. Sc., 45, , the ambguous wnd felds are mmedately useful to opera- Hoffman, R. N., SASS wnd ambguty removal by drect mnmzaton, tonal predcton centers for the generaton of surface analyses,, Use of smoothness and dynamcal constrants, Mort. Weather Rev., short-term forecasts, and warnngs. 112, , n summary, the geophyscal valdaton for NSCAT wnd Hoffman, R. N., A prelmnary study of the mpact of the ERS 1 C-band scatterometer wnd data on the ECMWF global data assmdata demonstrates the excellent qualty and hgh degree of laton system, J. Geophys. Res., 98, 10,233-10,244, utlty of these data for both scentfc and operatonal uses. Hollnger, J., R. Lo, and G. Poe, Specal sensor mcrowave mager user's gude, techncal report, Nav. Res. Lab., Washngton, D.C., Sept. 14, Hsu, C. S., and W. T. Lu, Wnd and pressure felds near tropcal Acknowledgments. Ths paper s dedcated to the memory of Steven Peteherych, who served on the Satellte Surface Stress Workng Group, and, together wth Peter Woceshyn and the lead author, worked on defnng the meteorologcal requrements for NSCAT. The authors would lke to acknowledge J. J. O'Bren for hs leadershp of the Satellte Surface Stress Workng Group, T. Lu and M. Frelch for ther leadershp of the NSCAT Scence Team, and J. Graf for managng the NSCAT Project at JPL. We would lke to thank Frank Wentz of Remote Sensng Systems for provdng the SSM/ wnd speed observatons used n ths study. Dscussons wth many members of the NSCAT Project and NSCAT Scence Team contrbuted to ths work, but we would especally lke to acknowledge W. Person and W. Patzert. Ths research was supported by the NSCAT Project and by NASA Headquarters Offce of Earth Scence. References Arakawa, A., and W. H. Schubert, nteracton of cumulus cloud ensemble wth the large-scale envronment,, J. Atmos. Sc., 31, , Arakawa, A., and M. J. Suarez, Vertcal dfferencng of the prmtve equatons n sgma coordnates, Mon. Weather Rev., 111, 34-45, cyclone Olver derved from scatterometer observatons, J. Geophys. Res., 101, 17,021-17,028, Jones, W. L., L. C. Schroeder, and J. L. Mtchell, Arcraft measurements of the mcrowave scatterng sgnature of the ocean, EEE J. Oceanc Eng., OE-2, 52-61, Joseph, J. H., W. J. Wscombe, and J. E. Wenman, The delta- Eddngton approxmaton for radatve flux transfer, J. Atmos. Sc., 33, , Kng, M.D., and R. Harshvardhan, Comparatve accuracy of selected multple scatterng approxmatons, J. Atmos. Sc., 43, , Lenzen, A. J., D. R. Johnson, and R. Atlas, Analyss of the mpact of Seasat scatterometer data and horzontal resoluton on GLA model smulatons of the QE H storm, Mon. Weather Rev., 121, , Levy, G., and R. A. Brown, A smple, objectve analyss scheme for scatterometer data, J. Geophys. Res., 91, , Long, D. G., Wnd feld model-based estmaton of Seasat scatterometer wnds, J. Geophys. Res., 98, 14,651-14,668, Moorth, S., and M. J. Suarez, Relaxed Arakawa Schubert: A param- eterzaton of most convecton for general crculaton models, Mon. Weather Rev., 120, , Nader, F. M., M. H. Frelch, and D. G. Long, Spaceborne radar

20 11,424 ATLAS ET AL.: GEOPHYSCAL VALDATON OF NSCAT WNDS measurement of wnd velocty over the ocean--an overvew of the NSCAT scatterometer system, Proc. EEE, 79, , Offler, D., The calbraton of ERS-1 satellte scatterometer wnds, J. Atmos. Oceanc Technol., (4), , Person, W. J., Jr., W. B. Sylvester, and M. A. Donelan, Aspects of the determnaton of wnds by means of scatterometry and of the utlzaton of vector wnd data for meteorologcal forecasts, J. Geophys. Res., 91, , Prce, J. C., The nature of multple solutons for surface wnd speed over the oceans from scatterometer measurements, Remote Sens. Envron., 5, 47-54, Qulfen, Y., B. Chapron, T. Elfouhaly, K. Katsaros, and J. Tournadre, Observaton of tropcal cyclones by hgh-resoluton scatterometry, J. Geophys. Res., 103, , Sadourney, R., The dynamcs of fnte dfference models of the shallow water equatons, J. Atmos. Sc., 32, , Schroeder, L. C., W. L. Grantham, E. M. Bracalente, C. L. Brtt, K. S. Shanmugam, F. J. Wentz, D. P. Wyle, and B. B. Hnton, Removal of ambguous wnd drectons for a Ku-band wnd scatterometer usng three dfferent azmuth angles, EEE Trans. Geosc. Remote Sens., GE-23, , Schubert, S. D., R. B. Rood, and J. Pfaendtner, An assmlated dataset for earth scence applcatons, Bull. Am. Meteorol. Soc., 74(12), , Schultz, H., A crcular medan flter approach for resolvng drectonal ambgutes n wnd felds retreved from spaceborne scatterometer data, J. Geophys. Res., 95, , (Correcton, J. Geophys. Res., 95, 9783, 1990.) Shaffer, S. J., R. S. Dunbar, S. V. Hsao, and D. G. Long, A medanflter-based ambguty removal algorthm for NSCAT, EEE Trans. Geosc. Remote Sens., 29, , Stoffelen, A., Toward the true near-surface wnd speed: Error modelng and calbraton usng trple collocaton, J. Geophys. Res., 98, , Stoffelen, A., and D. Anderson, Scatterometer data nterpretaton: Measurement space and nverson, J. Atmos. Oceanc Technol., 14(6), , 1997a. Stoffelen, A., and D. Anderson, Ambguty removal and assmlaton of scatterometer data, Q. J. R. Meteorol. Soc., 123, , 1997b. Stoffelen, A., and G. J. Cats, The mpact of SEASAT-A scatterometer data on hgh resoluton analyses and forecasts: The development of the QE storm, Mon. Weather Rev., 119, , Thdpaut, J.-N., R. N. Hoffman, and P. Courter, nteractons of dynamcs and observatons n a four-dmensonal varatonal assmla- ton, Mon. Weather Rev., 121, , Wentz, F. J., A smplfed wnd vector algorthm for satellte scatterometers, J. Atmos. Oceanc Technol., 8, , R. Atlas, NASA Goddard Space Flght Center, Mal Code 910.4, Greenbelt, MD (atlas@dao.gsfc.nasa.gov) J. Ardzzone, S.C. Bloom, E. Brn, D. Burgato, J. C. Jusem, and J. Terry, General Scences Corporaton, NASA Goddard Space Flght Center, Greenbelt, MD R. N. Hoffman, Atmospherc and Envronmental Research nc., 840 Memoral Drve, Cambrdge, MA (Receved March 6, 1998; revsed June 22, 1998; accepted July 14, 1998.)

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