A Geometry-Based Approach to Identifying Cloud Shadows in the VIIRS Cloud Mask Algorithm for NPOESS

Transcription

1 1388 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26 A Geometry-Base Approach to Ientifying Clou Shaows in the VIIRS Clou Mask Algorithm for NPOESS KEITH D. HUTCHISON Center for Space Research, The University of Texas at Austin, Austin, Texas ROBERT L. MAHONEY Algorithms Moeling an Simulations, NPOESS System Engineering, Northrop Grumman Space Technology, Reono Beach, California ERIC F. VERMOTE University of Marylan at College Park, College Park, Marylan THOMAS J. KOPP The Aerospace Corporation, El Seguno, California JOHN M. JACKSON, ALAIN SEI, AND BARBARA D. IISAGER Algorithms Moeling an Simulations, NPOESS System Engineering, Northrop Grumman Space Technology, Reono Beach, California (Manuscript receive 15 July 2008, in final form 7 January 2009) ABSTRACT A geometry-base approach is presente to ientify clou shaows using an automate clou classification algorithm evelope for the National Polar-orbiting Operational Environmental Satellite System (NPOESS) program. These new proceures exploit both the clou confience an clou phase intermeiate proucts generate by the Visible/Infrare Imager/Raiometer Suite (VIIRS) clou mask (VCM) algorithm. The proceures have been teste an foun to accurately etect clou shaows in global atasets collecte by NASA s Moerate Resolution Imaging Spectroraiometer (MODIS) sensor an are applie over both lan an ocean backgroun conitions. These new proceures represent a marke eparture from those use in the heritage MODIS clou mask algorithm, which utilizes spectral signatures in an attempt to ientify clou shaows. However, they more closely follow those evelope to ientify clou shaows in the MODIS Surface Reflectance (MOD09) ata prouct. Significant ifferences were necessary in the implementation of the MOD09 proceures to meet NPOESS latency requirements in the VCM algorithm. In this paper, the geometry-base approach use to preict clou shaows is presente, ifferences are highlighte between the heritage MOD09 algorithm an new VIIRS clou shaow algorithm, an results are shown for both these algorithms plus clou shaows generate by the spectral-base approach. The comparisons show that the geometry-base proceures prouce clou shaows far superior to those preicte with the spectral proceures. In aition, the new VCM proceures preict clou shaows that agree well with those foun in the MOD09 prouct while significantly reucing the execution time as require to meet the operational time constraints of the NPOESS system. Corresponing author aress: Keith D. Hutchison, Center for Space Research, The University of Texas at Austin, TX keithh@csr.utexas.eu DOI: /2009JTECHA Ó 2009 American Meteorological Society

2 JULY 2009 H U T C H I S O N E T A L Introuction The National Aeronautics an Space Aministration s (NASA) Moerate Resolution Imaging Spectroraiometer (MODIS) is a heritage sensor of the Visible/ Infrare Imager/Raiometer Suite (VIIRS) sensor, which was first launche on boar the NASA-sponsore National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) mission. MODIS collects ata in 36 spectral bans (Salomonson et al. 1989) an these ata are use to generate a variety of ata proucts (Savtchenko et al. 2004). VIIRS will collect ata in 22 bans that will be use to create 23 ata proucts (Hutchison an Cracknell 2006). A key prouct create with both MODIS an VIIRS sensors is the clou mask, which is generate using sophisticate logic that inclues a series of clou etection tests. Although the MODIS clou mask (MCM) algorithm has evolve since the launch of MODIS on the Terra spacecraft in December 1999 (Ackerman et al. 1997, 2002), the VIIRS clou mask (VCM) algorithm was base upon an early version of the MCM algorithm (Ree 2002). The VCM algorithm has been recently upate to more fully exploit the unique esign features of the VIIRS sensor (Hutchison et al. 2005, 2008b; Hutchison an Jackson 2003). In the NPOESS program, the Active Fire mask an VCM algorithms form the beginning of the processing chain for all VIIRS ata proucts, except for VIIRS imagery, which is a stan-alone prouct. The VIIRS prouct chain inclues seven clou proucts (clou optical thickness an effective particle size; clou-top pressure, height, an temperature; clou-base height; an clou cover/layers), three ocean surface proucts (sea surface temperature, ocean color, an net heat flux), five lan surface proucts (lan surface temperature, normalize ifference vegetation inex, enhance vegetation inex, albeo, an surface type), three snow ice proucts (a subpixel snow mask, ice surface temperature, an ice age), an three atmospheric aerosol proucts (optical thickness, particle size parameter, an suspene matter), all of which use the VCM as input (Hutchison an Cracknell 2006). The MCM an VCM algorithms output a pixel-level clou confience consisting of four possible classes, that is, confiently clear, probably clear, probably clouy, an confiently clouy conitions. In aition, these algorithms generate a clou phase analysis. Using proceures evelope by Pavolonis an Heiinger (2004), the VCM clou phase inclues seven possible classes: water, mixe phase, cirrus, opaque ice, overlap (water an ice clous in a single pixel), partly clouy, an clou free (Hutchison et al. 2005). The MCM an VCM algorithms also use flags to ientify pixels that contain heavy aerosols an clou shaows. New proceures recently implemente in the VCM have been emonstrate to accurately ifferentiate between clous an heavy aerosols in global MODIS atasets (Hutchison et al. 2008b). Unetecte clou shaows can severely impact many of the VIIRS proucts, which are also referre to as environmental ata recors (EDRs), incluing the aerosol, lan, an snow ice EDRs. For example, the MODIS aerosol algorithms, use to create the MOD04 prouct, nominally examines four hunre 500-m pixels to retrieve the aerosol optical thickness (AOT) at a spatial resolution of 10 km over lan an inclues sophisticate schemes, for example, the ark pixel correction (Remer et al. 2006), to reuce the possible effects of clou shaows, which have been shown to prouce with MODIS ata much lower than expecte AOT values compare to groun-base observations (Hutchison et al. 2008a). On the other han, the VIIRS intermeiate AOT prouct is generate for each cloufree, nominal 800-m pixel an the prouct can be severely egrae if shaows are not accurately ientifie because the path raiance will be much lower than assume by the retrieval algorithm. Furthermore, the nee to accurately etect clou shaows is important to the generation of a variety of lan proucts create from a variety of remote sensing platforms incluing the Avance Very High Resolution Raiometer (AVHRR), Lansat, an MODIS (Huete et al. 2002; Liang et al. 2002; Simpson an Stitt 1998). Therefore, it is critically important that clou shaows be accurately ientifie in the automate clou-screening algorithms such as the VCM. During the initial testing of the VCM algorithm, it was foun that the heritage, spectral-base clou shaow approach selom etecte shaows that were evient in MODIS imagery, since no unique spectral characteristics exist that escribe clou shaows over complex global, clou-free surfaces. Similarly, the approach often preicte false shaows, that is, shaows not associate with any clous, as shown in section 2a. As a result, a new approach to ientifying clou shaows was sought an the geometry-base approach, use to create the MODIS Surface Reflectance (MOD09) prouct, was chosen as the primary caniate. However, preliminary testing with the MOD09 algorithm raise concerns about the lengthy processing time require to ientify shaows with this approach. As a result, the MOD09 clou shaow algorithm was significantly moifie for use in the VCM, as iscusse in section 2b, to meet the stringent latency requirements of the operational NPOESS system. In section 3, shaows for water an ice clous are presente for a number of algorithms, incluing

3 1390 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26 the geometry-base clou shaow approach use in the latest version of the VCM an MOD09 algorithms along with those foun with the spectral-base clou shaow algorithms use in the oler version of the VCM an the current Collection 5 MCM algorithms. Conclusions are rawn in section Theoretical basis for clou shaow ientification The MCM algorithm theoretical basis ocuments (ATBDs) state that the Detection of clou shaows is a problem that has not been aresse aequately in the literature (Ackerman et al. 1997, 2002, 2006). These ocuments further state that clear-sky scenes that are potentially affecte by shaows can be theoretically compute given the viewing geometry, solar azimuth an zenith angles, clou ege istributions, an clou altitue. They go on to say that this approach requires too much CPU to run operationally, an all the information (e.g., clou altitue) is not available to the clou mask algorithm. Therefore the MCM algorithm employs spectral tests base upon solar reflectances collecte by MODIS to ientify clou shaows (Ackerman et al. 1997, 2002, 2006). a. Spectral-base clou shaow etection The MCM algorithm checks for shaows whenever the clou mask inicates a clear fiel of view. Using MODIS Airborne Simulator ata, it was originally believe that clou shaows were present when the following conitions escribe by Eqs. (1) an (2) were satisfie [Ackerman et al. (1997): the reflectance in a particular spectral ban is inicate by a subscript, e.g., reflectance in the 0.94-mm MODIS ban is given by R (0.94) ]: R (0.94), 0.12 an (1) R (0.87) /R (0.66) (2) Subsequently, the reflectance in the 1.2-mm ban was ae to the spectral-base clou shaow logic, as shown in Eq. (3) (Ackerman et al. 2002), an it remains in use in the MCM Collection 5 algorithm use to generate the MOD35 prouct (Ackerman et al. 2006). In the earliest of these upates, the threshol in Eq. (1) was also lowere to 0.07: R (1.2) is, 0.2. (3) The VCM spectral approach eparte slightly from the MODIS 2002 version of the spectral-base shaow algorithm, ue in part to the absence of a 0.94-mm ban on the VIIRS sensor. In the VCM spectral-base algorithm, clou shaows are base on the reflectances in the 1.24-, 1.61-, , an mm bans an a shaow is preicte if the following conitions are satisfie: an or R (0.865) /R (0.672). 0.3 (4) R (1.61), 0.07 (5) R (1.24), (6) Figure 1 shows results prouce by these spectral-base clou shaow tests applie to a MODIS Terra granule collecte over the western Unite States at 1835 UTC 30 October (The granule ID is MOD ) A false-color image, constructe by assigning the mm ban to re, the mm ban to the green, an the 0.55-mm ban to the blue, of the entire granule is shown in Fig. 1a while the region of interest is enlarge in Fig. 1b. Large shaows are apparent near clous locate at points A, B, an C. Figures 1c an 1 show shaows preicte with the spectral tests as iscusse in Eqs. (1) (6) using the original VCM (Ree 2002) an MCM Collection 5 algorithms. Notice first that results base upon the spectral tests fail to ientify shaows in regions where they are clearly visible (points A C) in the imagery shown in Fig. 1b. Secon, note that the spectral tests preict shaows will occur in regions not associate with clous, for example, points D an F in Fig. 1c. Shaows are also visible at point E in Fig. 1c but are not etecte by these spectral tests. It is emphasize that clou shaows preicte by the spectral tests with this case stuy represent the best prouce in 40 1 MODIS granules analyze uring the course of these investigations. In most cases, the spectral-base tests faile to etect correctly any clou shaows. b. Geometry-base clou shaow etection The logic use to generate clou shaows with the geometry-base approach was evelope by E. Vermote in support of NASA scientists responsible for the MODIS Surface Reflectance prouct. This is the first escription of that approach to appear in the literature. A escription of the geometry-base clou shaow logic is shown in Fig. 2. Differences between the MOD09 an VCM implementations of this clou shaow logic are highlighte (bolface an white text). As note earlier, these ifferences were necessary to reuce VCM latency, since the irect implementation of the MOD09

4 JULY 2009 HUTCHISON ET AL FIG. 1. (a) A color composite of MODIS granule MOD A (b) As in (a), but with the region of interest enlarge. (c) The results from the VCM shaow spectral test, an () the results from the spectral test in the Collection 5 MODIS Clou Mask (MOD35) prouct. Clous are golen in the VCM an yellow in the MCM, while shaows are turquoise in both analyses.

5 1392 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26 FIG. 2. Architecture for the geometry-base clou shaow logic with ifferences between the VCM an MOD09 implementations highlighte in bolface an white text. algorithm increase the VCM processing time by about an orer of magnitue when using the spectral-base clou shaow approach. The VCM implementation of the geometric-base approach, as shown in Fig. 2, reuce the processing time by a factor of 5 compare to the MOD09 implementation; however, it still ouble the time of the VCM algorithm when using the spectral-base approach. Key ifferences between the two implementations of the geometry-base clou shaow algorithms are also summarize in Table 1. The first step in the geometry-base shaow logic is to assess the ata for analysis by the algorithm. The shaow logic is execute uner aytime conitions efine by the solar zenith angle (SZA), but there remain some internal inconsistencies in the efinitions of ay in the VCM an other VIIRS clou algorithms. These inconsistencies arise because some proucts can be retrieve at higher SZA values than others. The clou shaow logic is execute if the SZA is less than or equal to 758. This conition is sufficient for all of the ownstream VIIRS algorithms that may be negatively impacte by unetecte shaows. However, the VCM clou etection logic efines nighttime by a SZA greater than 858. Thus, some aytime pixels, as classifie by the VCM, are eliminate from the clou shaow logic ue to these ifferences in these efinitions. Next, as shown in Fig. 2, the process of compiling statistics for a pixel winow, which is the basic analysis region use in the geometry-base clou shaow algorithm, is begun, as shown in the top part

6 JULY 2009 H U T C H I S O N E T A L TABLE 1. Comparisons between implementations of the VCM an MOD09 geometry-base shaow logic. Feature Ientification of caniate pixel regions that might contain shaows Estimation of clou bounaries Ientification of shaows in each region Projection of the clou shaow Implementation in the MOD09 prouct application Ientification of regions that contain clous (in a the MOD09 binary clou mask) Use of 11-mm brightness temperatures correcte for water vapor above clou top Use of a sliing winow (i.e., a pixel may be analyze 19 times) Use of up to 32 iterations for each pixel using a step size of 0.5 km to cover the estimate clou bounaries Implementation in the VCM algorithm Ientification of regions that contain at least one confiently clear pixel Use of clou phase an 11-mm brightness temperatures Use of a hopping winow (i.e., a pixel is analyze once) Use of up to four iterations for each pixel using a variable step size epening on estimate clou bounaries of Fig. 2. In the MOD09 prouct, this winow slies one row or one column at a time; however, in the VCM implementation, the winow hops by groups of pixels; that is, no single pixel is examine more than once. Use of a hopping winow significantly reuce the latency in the geometry-base clou shaow approach: A etermination is mae whether there are any confiently clear pixels within each winow in the VCM approach. A flag is set to ientify winows with at least one confiently clear pixel (ALOCCP). Clear-sky, mean surface temperatures are compute from the grie National Centers for Environmental Preiction (NCEP) 2-m air temperature fiels. The geometry-base clou shaow proceures next examine each pixel to ientify caniates that might cast a shaow. In preparation for estimating clou bounaries, that is, the clou-top an clou-base heights, the MOD09 approach collects 11- an 6.7-mm brightness temperatures for each clouy pixel. The clou-top temperatures are then base on the 11-mm brightness temperature that has been correcte for water vapor attenuation above the clou top using the 6.7-mm brightness temperature. Next, clou-top temperatures are converte to clou-top heights through comparisons against the mean 2-m NCEP surface air temperature, assuming a stanar lapse rate, as shown in the box title Basic Clou Bounary Logic in MOD09, Fig. 2. Clou-top an -base offsets are then applie to this estimate clou-top height, to prouce a clou with a typical thickness of about 3 km. It is recognize that the simplistic approach to estimating clou-top temperatures of optically thin (ice) clous can lea to large errors in clou-top heights with the MOD09 approach. Thus, a ifferent approach is taken in the VCM implementation, using information from the clou phase analysis, as iscusse below. In aition, in orer for a clouy pixel to be a caniate to cast a shaow, there must exist at least one clear pixel (ALOCCP) in the neighborhoo winow where the geometry suggests a shaow coul occur. (Note that shaows may be cast up to 60 km from a pixel resiing in a winow. However, if no clear pixels exist in the neighborhoo winow, pixels are not processe for two reasons: shaows are not allowe to be cast upon lower-level clous an latency is greatly reuce by not processing shaows in regions of overcast clou conitions, although this oes occasionally cause some egraation in the shaow prouct.) In aition, shaows cannot be projecte from pixels classifie as both confiently clouy an containing heavy aerosols (Hutchison et al. 2008b); that is, aerosols are not assume to cast shaows. If at least one clear pixel exists in this winow where a shaow coul exist, the following steps are followe: Ice clou bounaries are estimate using an accurate clou phase analysis (Hutchison et al. 2005, 2008b) base on the algorithm escribe by Pavolonis an Heiinger (2004, 2005). The VCM approach follows ifferent processing paths to preict the clou-top height of ice clous, as shown by the white text in Fig. 2, epening on whether these clous are classifie as opaque, thin, or overlap. Thick cirrus clous, that is, opaque cirrus an overlap cirrus, cast shaows larger than those foun near thin cirrus. The clou-top temperatures of these thicker clous are base upon the 11-mm brightness temperatures, which are then converte to clou-top heights per the MOD09 approach. Thin cirrus clous project smaller shaows than thicker clous base upon tunable clou-top an -base heights parameters specific to thin cirrus. Clou bounaries for water clous follow the logic use in the MOD09 approach, as shown in Fig. 2. The

7 1394 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26 clou-top temperatures for these clous are again base on the 11-mm brightness temperatures; however, no correction is mae for water vapor attenuation above the clou top since VIIRS has no 6.7-mm brightness temperature. Clou-top temperatures are converte into clou-top heights using the MOD09 approach. The maximum allowable clou-top heights of all clous are varie linearly with latitue from a mean tropopause height of 16 km in tropical regions to 8 km in polar regions. No attempt is mae to preict cloubase heights more accurately, using the VIIRS cloubase height algorithm, since the retrieval of this an other VIIRS clou properties occurs after the completion of the clou shaows are projecte by the VCM, as shown in Fig. 1 of Wong et al. (2007). Estimates of clou bounaries in both approaches are then converte into geometric shaows using an algorithm that iterates over clou bounaries to compute the line of sight clou shaow geometry: In the MOD09 approach, each step of the iteration is constraine to a 0.5-km interval, which means 32 iterations per pixel may be require for a 16-km-thick clou to cast the shaow correctly onto the earth s surface. In the VCM implementation, a maximum of four iterations is use to reuce latency. Thus, the iteration height interval is varie in the VCM implementation to cover the entire clou bounary. While this aspect of the VCM implementation greatly reuces latency, it may prouce gaps in shaows at large solar zenith angles. The MOD09 implementation oes ensure that no gaps exist in the projection of the shaow onto the clou-free pixels at high solar zenith angles. However, the quality of any shaow may be egrae at these high values of SZA since clou-base heights are not known precisely, which means that contiguous shaows will be preicte while, in reality, shaowfree regions will occur between the clou an its true shaow location. Both implementations follow the same logic for the remaining steps of casting shaows onto the clou-free earth. Each clouy pixel is projecte onto a clou-free pixel at the earth s surface. No correction is mae for terrain. If the clou shaow logic projects onto a cloufree pixel, the shaow fills all clou-free pixels in a neighborhoo aroun this location. This process is then repeate for each clouy pixel. [Note: It is emphasize that the box is use to maintain consistency with the heritage MOD09 clou shaow algorithm. A typical MODIS granule contains FIG. 3. (a) The new VCM geometry-base shaow flag, as escribe in Fig. 1. (b) Same as (a), but for the MODIS (MOD09) prouct where shaows appear slightly larger than in the VCM prouct pixels in the cross-track irection an 1375 pixels in the along-track irection. This box size prouces 102 analysis regions in the cross-track irection. While the pixel region is use to compute a mean surface air temperature an to etermine whether there are any caniate pixels for casting shaows within the omain of the mean surface air temperature, the actual geometry computation is base on iniviual pixels. The compute shaows are allowe to project beyon the bounaries of the region an may project into neighboring granules. In aition, the MOD09 algorithm creates its own binary clou mask; that is, it oes not use the MCM (MOD35) prouct while the VCM contains clou confience fiels similar to the MOD35 prouct. The implementation of the VCM shaow logic prouces shaows (by efault) from confiently clouy pixels only but the coe allows for other possibilities; for example, shaows coul be prouce from pixels classifie as probably clouy.] 3. Results Results are presente for two MODIS granules: one containing well-efine shaows for water clous the other containing shaows cast by ice clous. Figure 3 shows the results of the geometry-base clou shaows for the scene shown in Fig. 1, which contains water clous. Figure 3a shows the results from the VCM algorithm while Fig. 3b shows the ata containe in MODIS Collection 5 Surface Reflectance (MOD09) prouct. To help ifferentiate between the algorithms, MODIS clous are isplaye in yellow while clous generate by the VCM algorithm appear as orange. Shaows appear turquoise for both proucts. First, it is evient that both proucts ientify substantially more shaows than those foun in either of the spectral-base tests shown in Fig. 1. This is most evient

8 JULY 2009 HUTCHISON ET AL FIG. 4. (a) A true-color composite of MODIS granule Cirrus clous are seen in the re box, which are examine more closely in the other isplays. (b) VCM clous (orange) an shaows (turquoise) base on the original spectral tests for this area of interest. (c),() The shaows from the VCM an MOD09 geometry-base approaches, respectively, as escribe in Fig. 1. In this ice clou case, the VCM shaows are larger than those foun in the MOD09 prouct. by examining regions surrouning points A, B, an C in Fig. 1b. A close examination of the VCM reveals the layering of the four height intervals use to locate the shaow, especially at the small-scale clous above point C. The effects of this layering are less evient in the MOD09 prouct since the 0.5-km interpolation interval prouces a shaow with smoother eges. However, comparisons between the clou shaows observe above

9 1396 J O U R N A L O F A T M O S P H E R I C A N D O C E A N I C T E C H N O L O G Y VOLUME 26 point B in Fig. 1b show that the VCM shaow mask, along with the MOD09 prouct, completely ientifies all pixels seen in the imagery to contain shaows. In aition, the geometry-base algorithms o not place shaows in regions where clous o not exist. This reuction in erroneous or false clou shaows is most apparent in the areas surrouning points D an F in Fig. 1c. While the spectral tests ientifie many shaows in these regions, far fewer are seen in the results generate by the geometry-base algorithms. Further enlargements of the imagery containe in Fig. 1b (not shown) reveal the presence of some small-scale clous in these regions, in agreement with the VCM shaows ientifie by the geometry-base algorithm; however, the M5 Reflectance Test use in the VCM oes create some false clous that then project erroneous shaows. The M5 test has been correcte to reuce these false etections. A cursory view might lea one to think that shaows, shown in Figs. 3a an 3b appear to surroun some clous. However, this is not the case. The irect rays of sunlight are arriving into this scene in a irection from the bottom right towar the upper left of the scene. The shaows from the clous lie along this irection. In some instances, see, for example, point B in Fig. 1b, shaows appear on both sies of the clous. The shaows to the lower right of the clous are projecte from another set of clous an are sprea using the filling logic. Thus, in some instances, these shaows may exten up to the ege of another clou system, making it appear that the shaows are being projecte in all irections aroun a clou. Clou shaows are also shown for the geometrybase logic for the ice clous shown in the MODIS scene containe in Fig. 4, which covers the southwest Unite States an northern Mexico. These ata were collecte by MODIS Terra at 1750 UTC 1 February 2002 (granule ID MOD ). The Baja Peninsula is surroune by the blue water of the Pacific Ocean an is clearly seen through nearly overcast cirrus in the lowerleft corner of the scene, which extens across the bottom half of Fig. 4. An extensive area of snow extens from the northern Great Plains (upper-right corner) towar the Rocky Mountains in the mile of the scene. The Great Salt Lake is also seen towar the upper-left corner in Fig. 4. Figure 4b contains clou shaow results from the VCM clou mask algorithm using the spectral tests. (In this case, the actual VCM clou mask is not shown separately since the spectral tests etecte so few shaows.) Figures 4c an 4 again show the VCM an MOD09 geometry-base clou shaows. In this case, the VCM projects a slightly larger shaow than is foun in the MOD09 prouct. Upon closer examination of the MOD09 prouct, it is seen that unmaske shaows in the imagery are evient aroun points A an B in Fig. 4, while these eges of unetecte shaows are not observe in the VCM results shown in Fig. 4c. It appears that using the clou phase analyses in the VCM to specify the clou-top height of cirrus clous can provie a more accurate clou shaow when the clous are not completely opaque. The smaller shaows cast by the MOD09 approach probably occur because the actual clou-top temperature is coler than the 11-mm brightness temperature, so the clou-top height is place too low in the atmosphere. 4. Conclusions A geometry-base approach has been presente to ientify clou shaows with the Visible/Infrare Imager/ Raiometer Suite (VIIRS) clou mask (VCM) algorithm for the NPOESS program. The proceures closely follow those evelope to ientify clou shaows in the MODIS Surface Reflectance (MOD09) ata prouct. However, significant ifferences were necessary in the VCM implementation of the MOD09 proceures to reuce latency in the VCM algorithm an to compensate for the absence of some MODIS bans not available in the VIIRS sensor. The new VCM clou shaow proceures exploit both the clou confience an clou phase intermeiate proucts to better classify clou tops associate with optically thin cirrus clous. The analysis of water clous follows more closely the MOD09 proceures. In general, the results from the VCM an MOD09 shaow algorithms are in goo agreement. NPOESS latency requirements force some moifications to the MOD09 shaow logic to be implemente in the VCM algorithm. First, the VCM approach uses a hopping pixel region as the basic analysis area for the shaow logic while the MOD09 employs a sliing winow. In aition, once clou bounaries have been etermine, the VCM uses a maximum of four iterations of varying clou thickness to buil the shaow while the MOD09 approach uses a constant 0.5-km clou thickness with up to 32 iterations to construct the shaow. Results show that the geometry-base approaches use to preict clou shaows are far superior to those proceures that preict shaows with the spectral tests that continue to be use in the MODIS Collection 5 Clou Mask (MOD35) algorithm. In aition, proceures use in the new VCM geometry-base implementation significantly reuce the execution time of the MOD09 approach, when compare to running the VCM spectral-base tests. The analyses of about 40 MODIS runs showe the core time on an International Business Machine (IBM) computer, running the

10 JULY 2009 H U T C H I S O N E T A L Avance Interactive Executive (AIX) operating system was about 22 s per granule. Replacing the spectral test with a irect implementation of the MOD09 algorithm increase this core time to about 200 s, while running the VCM with the VCM implementation require about 45 s. As a result, the VCM implementation provies a high quality shaow analysis within the operational time constraints of the NPOESS system. However, users shoul exercise caution with ata collecte at high solar zenith angles where shaows may not be contiguous. Acknowlegments. The views, opinions, an finings containe in this article are those of the authors an shoul be construe as an official position of Northrop Grumman, NOAA, the Aerospace Corporation, or the NPOESS program. REFERENCES Ackerman, S. A., an Coauthors, 1997: Discriminating clear-sky from clou with MODIS. NASA Algorithm Theoretical Basis Doc. MOD35, version 3.2, 125 pp., an Coauthors, 2002: Discriminating clear-sky from clou with MODIS. MODIS Algorithm Theoretical Basis Doc. MOD35, version 4.0, 115 pp. [Available online at mois.gsfc.nasa.gov/ata/atb/atb_mo06.pf.], an Coauthors, 2006: Discriminating clear-sky from clou with MODIS. NASA Algorithm Theoretical Basis Doc. MOD35, version 5.0, 129 pp. Huete,A.,K.Dian,T.Miura,E.P.Roriguez,X.Gao,an L. G. Ferreira, 2002: Overview of the raiometric an biophysical performance of the MODIS vegetation inices. Remote Sens. Environ., 83, Hutchison, K. D., an J. M. Jackson, 2003: Clou etection over esert regions using the 412 nanometer MODIS channel. Geophs. Res. Lett., 30, 2187, oi: /2003gl ,ana.p.cracknell,2006:visible Infrare Imager Raiometer Suite: A New Operational Clou Imager. CRC Press, 256 pp., J. K. Roskovensky, J. M. Jackson, A. K. Heiinger, T. J. Kopp, M. J. Pavolonis, an R. Frey, 2005: Automate clou etection an typing of ata collecte by the Visible Infrare Imager Raiometer Suite (VIIRS). Int. J. Remote Sens., 20, , S. Faraqui, an S. Smith, 2008a: Improving correlations between MODIS aerosol optical thickness an groun-base PM 2.5 observations through 3D spatial analyses. Atmos. Environ., 42, , B. Iisager, T. Kopp, an J. M. Jackson, 2008b: Discriminating between clous an aerosols in the VIIRS clou mask algorithms. J. Atmos. Oceanic Technol., 25, Liang, S., H. Fang, J. T. Morisette, M. Chen, C. J. Shuey, C. L. Walthall, an C. S. T. Daughtry, 2002: Atmospheric correction of Lansat ETM1 lan surface imagery. II. Valiation an applications. IEEE Trans. Geosci. Remote Sens., 40, Pavolonis, M. J., an A. K. Heiinger, 2004: Daytime clou overlap etection from AVHRR an VIIRS. J. Appl. Meteor., 43, , an, 2005: Daytime global clou typing from AVHRR an VIIRS: Algorithm escription, valiation, an comparisons. J. Appl. Meteor., 44, Ree, B., 2002: VIIRS clou mask (VCM) algorithm theoretical basis ocument. Raytheon Systems SBRS Doc. 2412, 44 pp. [Available online at Remer, L. A., D. Tanré, an Y. Kaufman, 2006: Algorithm for remote sensing of tropospheric aerosol from MODIS: Collection 5. MODIS Algorithm Theoretical Basis Doc., NASA Goar Space Flight Center, 87 pp. [Available online at Salomonson, V. V., W. L. Barnes, P. W. Maymon, H. E. Montgomery, an H. Ostrow, 1989: MODIS: Avance facility instrument for stuies of the earth as a system. IEEE Trans. Geosci. Remote Sens., 27, Savtchenko, A., D. Ouzounov, S. Ahma, J. Acker, G. Leptoukh, J. Koziana, an D. Nickless, 2004: Terra an Aqua MODIS proucts available from NASA GES DAAC. Av. Space Res., 34, Simpson, J. J., an J. R. Stitt, 1998: A proceure for the etection an removal of clou shaow from AVHRR ata over lan. IEEE Trans. Geosci. Remote Sens., 36, Wong, E., K. D. Hutchison, S. C. Ou, an K. N. Liou, 2007: Cirrus clou top temperatures retrieve from raiances in the National Polar-Orbiting Operational Environmental Satellite System Visible Infrare Imager Raiometer suite 8.55 an 12.0 mm banpasses. Appl. Opt., 46,