GOES成像儀資料簡介

達成鄒曉蕾,

（1 佛羅里達州立大學地球海洋大氣科學系，美國；2 南京信息工程大學資料同化研究與應(yīng)用中心，南京 210044）

GOES成像儀資料簡介

達成1鄒曉蕾1,2

（1 佛羅里達州立大學地球海洋大氣科學系，美國；2 南京信息工程大學資料同化研究與應(yīng)用中心，南京 210044）

“衛(wèi)星資料應(yīng)用” 專題系列

對地同步（geosynchronous）衛(wèi)星以地球自轉(zhuǎn)角速度圍繞地軸轉(zhuǎn)動。如果衛(wèi)星星下點（sub-satellite point）保持在地球表面同一位置，這樣的對地同步衛(wèi)星又被稱為對地靜止（geostationary）衛(wèi)星。在圓環(huán)軌道的假設(shè)下，根據(jù)對地靜止衛(wèi)星運行的向心力和萬有引力大小相等，可算出對地靜止衛(wèi)星與地心距離約為42164km。與一天提供兩次全球資料的極軌衛(wèi)星不同，靜止衛(wèi)星在其觀測范圍內(nèi)可提供時間連續(xù)的高水平分辨率資料，可用來追蹤快變天氣變量，如云、水汽和風。因此，越來越多的國家都相繼發(fā)射覆蓋自己領(lǐng)土的對地靜止衛(wèi)星。表1列出了目前在軌運行的對地靜止氣象衛(wèi)星太空位置、名稱、發(fā)射時間、衛(wèi)星狀態(tài)及所屬機構(gòu)。

可見光紅外成像儀是搭載于對地靜止衛(wèi)星上的一類重要儀器。這類儀器包括美國GOES系列（圖1）上的成像儀（Imager），中國FY-2系列的可見光紅外自旋掃描輻射儀（S-VISSR）及歐洲Meteosat系列的自旋增強可見光紅外成像儀（SEVIRI）。下面以美國的GOES成像儀為例，討論靜止衛(wèi)星資料的一些主要特點。GOES成像儀擁有1個可見光通道和4個紅外通道。表2列舉了GOES成像儀各通道中心波長、星下點水平分辨率及各通道的主要應(yīng)用目的。在晴空條件下，考慮熱放射項、忽略散射項，成像儀測得的輻射量主要由兩部分構(gòu)成。一部分為由地表發(fā)射、穿透大氣到達成像儀的輻射。另一部分為各層大氣發(fā)射、穿透上層大氣到達成像儀的輻射。GOES成像儀紅外通道2的中心頻率約為3.9μm，靠近二氧化碳4.3μm強轉(zhuǎn)動振動帶[1]，屬于短紅外通道。除了上述兩項，

通道2還包含有反射的太陽輻射的貢獻，這是GOES成像儀通道2不同于其他紅外通道的特點。GOES成像儀通道3（6.5或6.7μm）靠近水汽在6.3μm的轉(zhuǎn)動振動帶[1]，主要吸收氣體為水汽。該通道亮溫水平分布圖常用來觀察對流層中高層水汽的水平輸送。除了中心波長的細微移動，GOES-12后的通道3的波長范圍（5.8～7.3μm）大于GOES-11通道3的波長范圍（6.5～7.00μm)[2]。由于GOES-12通道3的星下點水平分辨率（4km）高于GOES-11的通道3（8km），擴大波長范圍有助于抑制由于水平分辨率提升而增加的噪音，提高信噪比[3]。GOES成像儀通道4（10.7μm）屬于窗區(qū)通道，大氣中吸收氣體對該波長的輻射吸收強度較小。因此在晴空條件下，該通道測得的輻射量主要來自透過大氣層的地表輻射。又因為位于10.7μm的干陸地裸土的地表發(fā)射率接近1，因此地表皮溫可用來估計地表發(fā)出的輻射量 （skin temperature）[4]。GOES成像儀通道5（12.0μm）被稱為臟窗（dirty window）。與10.7μm通道相比，該通道對大氣中的水汽更敏感。這是由于位于12.0μm的水汽的折射指數(shù)虛部大于水汽位于10.7μm的折射指數(shù)虛部，而折射指數(shù)虛部與吸收系數(shù)成正比。因此，在濕空氣條件下，12.0μm通道測得的亮溫將低于10.7μm的觀測亮溫。12.0μm通道也常被用于冰云檢測。大致原理為，位于12.0μm的冰的折射指數(shù)虛部大于位于12.0μm的水的折射指數(shù)虛部，因此，通道5在有冰云條件下的觀測亮溫比在水云條件下的觀測亮溫小[5]。從GOES-12開始，12.0μm通道被13.3μm通道替換。13.3μm位于CO2吸收帶邊緣[6]。添加的通道6結(jié)合其他已有的通道可以精確地反演云頂氣壓、有效云量及云頂溫度[3]。

表1 在軌對地靜止氣象衛(wèi)星太空位置、名稱、發(fā)射時間、衛(wèi)星狀態(tài)及所屬機構(gòu) Table 1 The longitude, name, launch date, operational status and operation agencies of current geostationary meteorological satellite

圖1 美國GOES系列衛(wèi)星 （a）GOES 1-3，（b）GOES 4-7，（c）GOES 8-12，（d）GOES 13-15（圖片來自http://www.goes-r.gov.） Fig. 1 Images of (a) GOES 1-3, (b) GOES 4-7, (c) GOES 8-12 and (d) GOES 13-15

GOES成像儀的垂直分辨率由各個通道的權(quán)重函數(shù)反映出來。圖2是根據(jù)美國標準大氣利用通用輻射傳輸模式[7]計算得到的GOES-11/12的權(quán)重函數(shù)的垂直分布圖。權(quán)重函數(shù)最大值所在高度的大氣對該通道的觀測輻射量貢獻最大。由圖2可知，通道2，4，6的觀測輻射量主要來自地表輻射。通道3的觀測輻射主要來自500～300hPa之間大氣的貢獻。此外，圖2還包含3個值得注意的特征。第一，GOES-11成像儀通道3（6.7μm）的權(quán)重函數(shù)峰值所在氣壓面略高于GOES-12成像儀通道3（6.5μm）權(quán)重函數(shù)峰值所在氣壓面。這是由GOES-11成像儀通道3的波長范圍小

于GOES-12成像儀通道3造成的[3]。相比于GOES-11，GOES-12成像儀通道3測得的輻射來自更下層的大氣，因此在晴空條件下的觀測亮溫將高于GOES-11通道3的觀測亮溫。第二，GOES成像儀通道4權(quán)重函數(shù)值在300hPa以上與通道5的權(quán)重函數(shù)接近，在300hPa以下大于通道5的權(quán)重函數(shù)值。這是因為通道5的水汽吸收系數(shù)大于通道4的吸收系數(shù)，在300hPa以下的任意等壓面，通道5的大氣光學厚度受水汽影響大于通道4，所以大氣對通道5波長的吸收大于通道4。因此，通道5對低層水汽比通道4更敏感。第三，GOES-12成像儀通道6位于20hPa以下的權(quán)重函數(shù)寬度大于GOES-11成像儀通道5。這反映了13.3μm通道測得的輻射量中，來自大氣的貢獻比 GOES-11成像儀通道5的大。這是由于13.3μm通道靠近CO2吸收帶，大氣中的CO2對該波長輻射產(chǎn)生影響。CO2在大氣中可認為是垂直均勻混合的，而水汽主要集中在對流層中低層大氣，因此對高層大氣，在同一氣壓面上，通道6的光學厚度將大于通道5的光學厚度，繼而大氣對通道6波長的吸收大于通道5 。

表2 GOES成像儀通道波長，水平分辨率，所在衛(wèi)星及通道用途 Table 2 The central wavelength, horizontal resolution, satellites, and the general usage of GOES imager channels

圖2 通過通用輻射傳輸模式計算的基于美國標準大氣的GOES-11（GOES-12）的3.9μm（紅），6.7（6.5）μm（藍），10.7μm（綠），12.0 （13.3）μm（黑）通道的權(quán)重函數(shù) Fig.2 Weighting functions of GOES-11 (top panel) and GOES-12 (bottom panel) 3.9μm (red), 6.7μm (blue), 10.7μm (green), 12.0μm (13.3μm) channels calculated by using CRTM with the U.S. standard atmosphere as the input

GOES成像儀的水平分辨率由各通道探頭的瞬時幾何視場（Instantaneous Geometry Field Of View，IGFOV）決定。對于GOES-12成像儀來說，中心波長為0.65μm通道的瞬時幾何視場為28μrad，中心波長在3.9，6.5，10.7μm的通道的瞬時幾何視場為112μrad，中心波長在13.3μm的通道的瞬時幾何視場為224μrad。這些瞬時幾何場轉(zhuǎn)換成對應(yīng)的星下點水平分辨率（即視場直徑）分別為1，4和8km。視場面積隨掃描角增大而增大，所以水平分辨率隨著掃描角的增大而降低。換句話說，掃描角大的單個視場測得的輻射量來自地表較大的面積。

用來描述任意視場面積與星下點視場面積的比例的一個常用參數(shù)是一維像素扭曲指數(shù)（K，pixel distortion index）[8]。一維像素扭曲指數(shù)（K）的計算公式如下：

其中

公式（2）中，λ為任意視場的經(jīng)度（緯度），λsub為星下點的經(jīng)度（緯度）。公式（1）中的a為衛(wèi)星與距離地心之間的距離，h為衛(wèi)星軌道距離地面的距離。對于GOES-12來說，h約等于35790km。α0為GOES成像儀可覆蓋的最大地球表面理論范圍，為81.3°。圖3為像素扭曲指數(shù)隨經(jīng)度（緯度）差絕對值α變化圖。在經(jīng)度（緯度）差絕對值α0等于60.38°時，像素扭曲指數(shù)K等于3。這意味著在一維扭曲的假設(shè)下，此時視場面積是星下點視場面積的3倍。由于一維像素扭曲指數(shù)假設(shè)視場只經(jīng)歷經(jīng)向扭曲或緯向扭曲，其只對衛(wèi)星所在經(jīng)圈及赤道緯圈的視場面積與星下點視場面積的比率有較精確的估計。地球表面其他經(jīng)緯度的視場同時經(jīng)歷緯度扭曲及經(jīng)度扭曲，所以真實的視場面積與星下點面積的比率大于一維像素扭曲指數(shù)得到的結(jié)果。

任意地球表面目標點視場軌跡可由目標點的緯度、經(jīng)度，衛(wèi)星天頂角、衛(wèi)星方位角、衛(wèi)星距離地球目標點的距離、成像儀探頭的瞬時幾何視場值，及地球為橢球體的假設(shè)計算得出（計算公式見附錄）。圖4展示了2008年5月22日18:15 UTC與18:21 UTC之間GOES-12成像儀對星下點所在經(jīng)圈（75?W）、赤道圈及其他經(jīng)緯度的觀測視場軌跡。由圖可見，星下點的視場類似正方形。衛(wèi)星所在經(jīng)圈的視場隨緯度變化經(jīng)歷南北向的扭曲，因此視場為長方形，緯向邊長小于經(jīng)向邊長。赤道圈的視場呈緯向邊長大于經(jīng)向邊長的長方形。其他經(jīng)緯度的視場由于同時經(jīng)歷經(jīng)向扭曲和緯向扭曲，視場類似于平行四邊形。圖4還有兩點值得強調(diào)的地方：第一，GOES成像儀的星下點視場為正方形，這是由于GOES成像儀的方形探頭造成的[2]；第二，GOES成像儀的觀測視場南北方向重疊小，東西方向重疊大。這意味著通過重采樣可以得到高于標定瞬時幾何視場的分辨率。Menzel等[9]指出通過重采樣可以得到的通道4的星下點分辨率為2.3km×4km。高緯度的視場由于像素扭曲率過大，這些地區(qū)的觀測輻射觀測值及其反演產(chǎn)品不再可信，因此不屬于有效觀測區(qū)域（即像素扭曲指數(shù)小于3時的觀測范圍）。例如K?pken[10]進行的水汽通道晴空輻亮度同化試驗剔除了掃描角較大的觀測點。圖5展示了目前全球主要對地靜止衛(wèi)星上成像儀的最大理論觀測范圍及像素扭曲指數(shù)小于3時的觀測范圍。由圖5可見，對地靜止衛(wèi)

星上成像儀對全球赤道和±50?緯度的區(qū)域有很好的資料覆蓋。

圖3 經(jīng)度（緯度）差絕對值α與像素扭曲率的關(guān)系 Fig. 3 Variation of the pixel distortion index K with respect to the absolute value of latitude (longitude) difference α

圖4 2008年5月22日18:15—18:21 UTC間GOES-12成像儀位于星下點（a）、衛(wèi)星所在經(jīng)圈（b）、赤道圈（c）及其他（d）經(jīng)緯度的視場軌跡（同一掃描線上相鄰的兩個視場由灰色塊與紅框表示，另一跟掃描線上相鄰的兩個視場由藍色塊及藍框表示，GOES-12位于75°W） Fig. 4 The IGFOVs of the GOES-12 imager channel 4 near (a) sub-satellite point, (b) the longitude same as the subsatellite point, (c) the equator, and (d) other locations during 1815 UTC - 1821UTC on May 22, 2008. GOES-12 is located as 75°W. The footprints of two adjacent IGFOVs are indicated in gray shaded and red lines, respectively, along the odd-numbered scan lines, and the two adjacent IGFOVs are indicated in light blue shaded and dark blue lines along even-numbered scan lines

圖5 現(xiàn)有主要對地靜止衛(wèi)星紅外成像儀最大理論覆蓋范圍（虛線）及像素扭曲指數(shù)≤3的覆蓋范圍（實線） Fig. 5 The theoretical maximum coverage (dashed), and areas with pixel distortion index being less than three (solid) of eight major geostationary satellites currently in operation: Meosat-7, -9 and -10, FY-2D and -2E, Himawari-7, FOES-13 and -15

如果要將靜止衛(wèi)星成像儀的紅外通道資料用于資料同化，首先需要知道成像儀的測量精度，這一參數(shù)可由等效噪音溫差表示（Noise Equivalent delta Temperature，NEdT）。等效噪音溫差是觀測亮溫及中心波長的函數(shù)。表3[11-13]列出了GOES-12—GOES-15成像儀通道2，4，6在300K和通道3在230K時的等效噪音溫差。

關(guān)于GOES成像儀還有一些補充信息。GOES成像儀的掃描方式類似于跨軌掃描輻射計。成像儀的掃描鏡旋轉(zhuǎn)操作由兩個發(fā)動機控制?？刂茤|西向的發(fā)動機首先帶動掃描鏡完成一條由西向東的掃描線?？刂颇媳毕虻陌l(fā)動機向北旋轉(zhuǎn)掃描鏡?？刂茤|西向的發(fā)動機再次帶動掃描鏡完成一條由東向西的掃描線，如此完成目標區(qū)域的掃描[2]。成像儀的紅外探頭掃描速率為5460/s。GOES成像儀有4種業(yè)務(wù)成像方式①：（1）常規(guī)業(yè)務(wù)（Routine Operations）；（2）全盤掃描業(yè)務(wù)（Full Disk Operations）；（3）快速掃描業(yè)務(wù)（Rapid Scan Operations, RSO）；（4）超快速掃描業(yè)務(wù)（Super Rapid Scan Operations, SRSO）。表4及表5

分別列舉了GOES東西星常規(guī)業(yè)務(wù)包含的框架名稱、地理范圍、掃描用時及掃描起始時刻①②③。對于GOES東星來說，全盤掃描業(yè)務(wù)④包含每小時1次的全盤掃描及1次簡略全盤掃描?？焖賿呙铇I(yè)務(wù)⑤在30分鐘里進行4次美國大陸掃描，1次北半球掃描及1次南美部分掃描。超快掃描業(yè)務(wù)則在30分鐘內(nèi)對面積為1000km2的指定區(qū)域進行10次耗時1分鐘的掃描。剩余的時間則用于北半球掃描及美國大陸掃描。

與微波探測儀相比，紅外成像儀探測通道的波長較短。因此，紅外輻射在云中衰減更快。對于光學厚度大的云，成像儀測得的輻射主要來自于云頂輻射。圖6、7展示了云對觀測亮溫的影響。其中A處于晴空區(qū)，B處于云區(qū)。B由于云的影響，通道2，3，4，6的亮溫均低于A。圖7b為各通道的觀測亮溫減模擬的晴空亮溫?？梢园l(fā)現(xiàn)，晴空（有云）條件下，兩者差值很?。ê艽螅?。第二，通道3的差值的絕對值小于通道2，4，6。這是因為通道2，4，6都是地面通道，而通道3觀測的為300～500hPa的亮溫。云所在高度離影響通道3觀測的大氣層高度更近，因此溫差小。

表3 GOES-12, -13和-15成像儀通道2，4，6在300K，通道3在230K時的等效噪音溫差（單位：K） Table 3 The NEdT of imager channels 2, 4 and 6 at 300 K and channel 3 at 230 K of GOES-12, -13 and -15 (unit: K)

表4 GOES東星常規(guī)業(yè)務(wù)包含的框架名稱、掃描范圍、掃描用時及掃描起始時間Table 4 The frame name, coverage, scan duration and scan starting time for GOES East routine operations

表5 GOES西星常規(guī)業(yè)務(wù)包含的框架名稱、掃描范圍、掃描用時及掃描起始時間 Table 5 Same as Table 4 except for GOES West

圖 6 2008年5月22日17:47—17:50 UTC GOES-12成像儀通道4的觀測亮溫（K）（A點位于 32.16°N，88.72°W；B點 位于32.02°N，84.06°W） Fig. 6 Spatial distribution of brightness temperature observations of GOES-12 imager channel 4 during 1747-1750 UTC on May 22, 2008. A is located as 32.16°N, 88.72°W, and B is located at 32.02°N, 84.06°W

圖 7 圖6中A，B點通道2（藍），3（綠），4（黃），6（紅）的觀測亮溫（a）及觀測亮溫減模擬的晴空亮溫（b） Fig.7 (a) Brightness temperature observations and (b) O-B differences of imager channels 2, 3, 4 and 6 at points A (solid bars) and B (dashed bars) shown in Fig.7

針對目前GOES成像儀通道較少的問題，美國下一代對地靜止衛(wèi)星GOES-R搭載的高級基線成像儀（Advanced Baseline Imager，ABI）則配有16個通道⑥，其中包含2個可見光通道，4個近紅外通道，10個紅外通道。紅外通道的星下點水平分辨率提高到2km。高級基線成像儀可以在1小時內(nèi)進行4次全盤掃描

或12次大陸掃描。高級基線成像儀增添了中尺度業(yè)務(wù)模式。它可以以30s一次的頻率對1000km×1000km的區(qū)域進行觀測。GOES-R衛(wèi)星計劃將于2015年發(fā)射⑦。中國計劃發(fā)射的風云4號（FY-4）靜止衛(wèi)星將搭載高級對地靜止輻射成像儀（Advanced Geostationary Radiation Imager，AGRI）和對地靜止干涉紅外探測儀（Geostationary Interferometric Infrared Sounder，GIIRS）。AGRI與ABI相似，將搭載包含可見光、近紅外、短波紅外、中波紅外及熱紅外的14個通道⑧。GIIRS是包含913個通道的對地靜止干涉紅外探測儀⑨。GIIRS類似于目前美國Aqua衛(wèi)星上的大氣紅外探測儀（AIRS）。現(xiàn)有的高光譜探測儀均放置在極軌衛(wèi)星上。FY-4將是首顆搭載高光譜成像儀的對地靜止衛(wèi)星。在氣象應(yīng)用中，同化AIRS的觀測資料可以顯著提高數(shù)值預報水平。氣候應(yīng)用中，AIRS觀測資料可用來反演CO2等溫室氣體含量。因此，GIIRS的觀測將對數(shù)值天氣預報及氣候研究發(fā)揮重要作用。

Serial of Applications of Satellite Observations

Geosynchronous satellites rotate around the Earth’s axis at the same angular velocity as the Earth does. If the sub-satellite point stays at the same location relative to the Earth surface, a geosynchronous satellite is called geostationary. The altitude of a geostationary satellite can thus be determined by a balance between the centripetal force and the gravitational force. Under the assumption of circular orbit, the altitude of the geostationary satellite is approximately 35787.6 kilometers above the Earth’s surface. Unlike a sun-synchronous polar-orbiting satellite that provides global observations twice daily, a geostationary satellite provides temporally continuous observations within a limited area centered at the subsatellite point. The horizontal resolution of geostationary satellite imager data is also high. The temporal and spatial continuity of the geostationary satellite data is extremely important for capturing rapid variations of atmospheric variables such as cloud, atmospheric water vapor and wind. Therefore, more and more geostationary meteorological satellites have been launched by different countries to cover their own territories. Table 1 lists all current operational meteorological geostationary satellites, along with their longitudes, names, launch dates, operational status and operation agencies.

The visible and infrared imager sensors onboard geostationary satellites include the Geostationary Operational Environmental Satellites (GOES) imager onboard United States GOES series (Figure 1), the Stretched Visible and Infrared Spin Scan Radiometer (S-VISSR) onboard Chinese Fengyun-2 (FY-2) series, and the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard European Meteosat series. In the following, we discuss some main characteristics of observations from GOES imager. GOES imager has one visible and four infrared channels. Table 2 provides the central wavelength, spatial resolution at the sub-satellite point, and the general usage of each channel. Under clearsky conditions, the scattering effect can be neglected and the thermal emission is the only source term. The infrared radiance received by the GOES imager mainly consists of the radiance emitted by the surface and transmitted throughout the entire atmosphere as well as the radiance that is emitted by a particular atmospheric layer and is transmitted throughout the atmosphere above that layer. For examples, the GOES channel 2 is a shortwave infrared channel with its central wavelength located at 3.9 micrometers (μm). This wavelength is close to the 4.3μm strong CO2rotation-vibration band[1]. The reflected solar radiance also contributes to the measured radiance of this channel, which is a unique characteristic that is different from other three GOES infrared channels. GOES imager channel 3 (central wavelength of 6.5μm or 6.7μm) is close to the 6.3μm vibration-rotation band[1]. The major absorber of this channel is water vapor, thus

the distributions of channel 3 brightness temperatures are usually utilized to observe the horizontal transport of water vapors in the middle and high troposphere. Besides the minor shift of central wavelength, the bandwidth of channel 3 onboard GOES-12, -13 and -15 (5.8μm–7.3μm) is wider than that of channel 3 onboard GOES-11 (6.5μm–7.0μm)[2]. Considering the higher spatial resolution (4 km) of GOES-12 channel 3 than that of GOES-11 channel 3 (8 km), enlarging the wavelength bandwidth suppresses the increased noise due to improved spatial resolution, thus improving signal-to-noise ratio[3]. Channel 4 is a window channel whose central wavelength is located at 10.7μm. The gas molecules in the atmosphere have weak absorption on the radiance at this wavelength. In addition, the emissivity of the dry ground is close to one, therefore the radiance emitted by the surface can be approximated by skin temperature[4]. The central wavelength of of channel 5 is 12.0 μm and is called a dirty window channel. Due to a stronger continuum absorption from water vapor, channel 5 is more sensitive to water vapor than channel 4. The observed brightness temperature of channel 5 will be lower than that of channel 4 when the air is moist. Channel 5 can be utilized to detect ice clouds as well. The imagery part of the refraction index at 12.0 μm is larger than that at 10.7 μm. The presence of ice clouds also leads to a lower brightness temperature of channel 5 than channel 4[5]. Since the launch of GOES-12, the 12.0 μm channel 5 is replaced with a 13.3 μm channel 6. Channel 6 is located in the wing of the CO2band[6]. With channel 6 measurements, the cloud top pressure, effective cloud amount, and cloud top temperature can be accurately retrieved[3].

The vertical resolution of GOES imager is reflected by the weighting function of each channel. Figure 2 shows the weighting function of GOES-11/12 imager channels calculated by the Community Radiative Transfer Model (CRTM)[7]with the U.S. standard atmosphere profile as the input. The largest contribution of observed radiance comes from the layer at which the weighting weight is the largest. It can be concluded from Fig. 2 that the observed radiance mainly comes from the surface emission for GOES imager channel 2, 4, 6 while the major contribution to channel 3 radiance comes from the layer between 500 and 300 hPa. Three additional features are worth mentioning based on Fig. 3. Firstly, the level where the weighting peak resides for GOES-11 imager channel 3 (6.7 μm) is slightly higher than that for GOES-12 imager channel 3 (6.5 μm). This results from a narrower bandwidth of GOES-11 channel 3 than that of GOES-12 channel 3[3]. Compared to GOES-11, the observed radiance of channel 3 by GOES-12 comes from the lower troposphere. Therefore, the brightness temperatures of channel 3 observed by GOES-12 imager are anticipated to be higher than those by GOES-11. Secondly, the weighting functions of channels 4 and 5 have similar vertical distributions above 300 hPa, but are different below 300 hPa. The weighting function of channel 4 is smaller than the weighting function of channel 5 below 300 hPa. This is because the absorption coefficient by water vapor of channel 5 is larger than that of channel 4. For any arbitrary level below 300 hPa, the optical depth of channel 5 is larger than that of channel 4 due to a stronger water vapor absorption. In other words, channel 5 is more sensitive to the water vapor in the lower troposphere than channel 4. Thirdly, channel 6 of GOES-12 imager has larger weighting functions than those of channel 5 of GOES-11 below 20hPa. This reflects that the contribution from the atmosphere is larger in the observed 13.3 μm radiance than GOES-11 channel 5. The mixing ratio of CO2is nearly constant throughout the atmosphere while water vapor mainly resides at the middle and lower troposphere. At high levels, the optical depth of channel 6 is larger than the optical depth of Channel 5, resulting a stronger absorption at the wavelength of channel 6 than at that of channel 5.

The horizontal resolution of GOES imager is determined by the instantaneous geometry field of view (IGFOV) of each channel. For GOES-12 imager, the IGFOV is 28 μrad for channel 1, 112 μrad for channels 2, 3 and 4, and 224 μrad for channel 6. The corresponding sub-satellite point resolution of these IGFOV is 1 km, 4 km, and 8 km, respectively. The area covered by IGFOV increases as the scan angle increases, so the horizontal resolution decreases as the scan angle increases. In other words, the observed radiation for a single IGFOV comes from a large area if the scan angle is larger.

The ratio of the area covered by an arbitrary field of view to the area covered by the field of view at sub-satellite point is defined as the pixel distortion indices (K)[8]. The equation for calculating the pixel distortion indices can be written as

where

In equation (1) and (2), λ is the longitude or the latitude of an arbitrary observation, λsubis the longitude of the sub-satellite point, ais the distance between the satellite and the earth center, and h is the altitude of satellite orbit above the earth surface. For GOES-12, h is approximately 35790 km. α0(=81.3°) is the maximum value of α and indicates the furthest location in longitude and latitude from the sub-satellite point of a GOES imager coverage. Figure 3 illustrates the relationship between the pixel distortion index K and the absolute value of the longitude (or latitude) difference α. When the absolute value of longitude (or latitude) difference, α, is equal to 60.38°, the pixel distortion index equals three. This means that under the assumption of the onedimensional distortion, the area covered by a IGFOV is three times as large as the IGFOV area at the sub-satellite point. It is reminded that the pixel distortion index in equation (1) assume that the area covered by an IGFOV experiences either a zonal distortion or a meridional distortion, it is accurate only for the pixel distortion at the equator, or at the longitude where satellite resides. Pixels located at other regions experience distortions in both the zonal and meridional directions. Therefore, the ratio of the actual area covered by a single IGFOV to that at the sub-satellite point will be larger than the pixel distortion index in (1).

The footprint of any arbitrary IGFOV can be calculated given the latitude and longitude of a target IGFOV, satellite zenith angle, satellite azimuth angle, the distance between satellite and the targeted IGFOV under the assumption that the Earth’s surface is an ellipsoid. Figure 4 illustrates the footprint covered by the IGFOV near the sub-satellite point (Fig. 4a), the 75?W longitude (Fig. 4b), the equator (Fig. 4c), and other locations (Fig. 4d) of GOES-12 imager from 1815 UTC to 1821 UTC on May 22, 2008. The IGFOVs at the sub-satellite point are squares, which is expected because GOES imagers use square detectors[2]. Pixels near the longitude of the sub-satellite point experience a meridional distortion and are of rectangular shape. The meridional length is longer than the zonal length for the IGFOVs near the longitude of the sub-satellite point. The IGFOVs near the equator are rectangles with their zonal lengths being larger than their meridional lengths. The IGFOVs at other locations experience both zonal and meridional distortions and thus have parallelogram shapes. A significant overlapping between two adjacent pixels is noticed in the zonal direction, which is greater than in the meridional direction. Through a resampling process, higher resolution observations can be achieved from overlapping GOES imager radiances. Menzel et al.[9]pointed out the sub-point resolution of channel 4 after resampling can be as high as 2.3 km × 4 km. Since the pixels at high latitudes have larger pixel distortion, the observed radiances and their retrieval products are not as reliable as in low latitudes. In the data assimilation experiment conducted by K?pken[10], observations with large scan angles are removed. Figure 5 shows the theoretical maximum coverage and area with pixel distortion index being less than three of several operational geostationary satellites. It can be seen that the global region within 50? is fully covered by the geostationary satellites.

The measurement precision of infrared imagers, which is a required input for data assimilation of GOES imager infrared radiance, is quantified by the Noise Equivalent differential Temperature (NEdT). NEdT is a function of observed brightness temperature and central wavelength. Table 3[11-13]lists the NEdT of imager channels 2, 4 and 6 at 300 K and channel 3 at 230 K from GOES-12, -13 and -15.

The scan operation of GOES Imager is similar to a cross-track sensor. Two motors control the rotation operation of the scan mirror. The motor controlling westeast operation fi rstly fi nishes one scan line from west to east. Then the motor controlling north-south operation rotates the scan mirror towards the south. An east to west scan is then performed by the west-east operation motor. The scan speed for each detector of infrared channel is 5460 observations per second. There are four operation modes for GOES imager①: (1) routine operation, (2) full disk operation, (3) rapid scan operation (RSO), and (4) super rapid scan operations (SRSO). Tables 4 and 5 list the name of the frame, observation coverage, scan duration and scan starting time of GOES-11 (e.g., GOES East) and GOES-12 (e.g., GOES West)①②③. For GOES East, the full disk operations④includes one full-disk scan and one abbreviated full-disk scan in each hour. The RSO⑤performs four U.S. continental scans, one Northern-

Hemisphere scan, and Southern-Hemisphere partial-frame scan in each 30 minutes. The SRSO is able to perform a total of 26 1-minute scans, covering an area of 1000 km2in 30 minutes.

Compared with satellite microwave sensors, the channel wavelengths of the infrared imager channels are shorter. This leads to stronger infrared absorption in clouds. For clouds with large optical depth, the radiance observed by the imager mainly comes from the cloud top. Figures 6 and 7 illustrate the influence of clouds in observed brightness temperatures. Point A is under a clear-sky condition while point B is located within clouds. In the presence of cloud, the brightness temperature of channels 2, 3, 4 and 6 (point B) is lower than that in a clear-sky condition (point A). Figure 6b shows the differences between the observed brightness temperature (O), and simulated brightness temperature under clearsky conditions (B), i.e., O?B. Under clear-sky (cloudy) conditions, the absolute value of O?B is small (large). Furthermore, the absolute value of (O?B) of channel 3, |O?B|, is smaller than those of channels 2, 4 and 6. This is because channels 2, 4 and 6 are window channels while channel 3 is an atmospheric sounding channel between 300 hPa and 500 hPa. The level where clouds exist is closer to the observed layer of channel 3, resulting a smaller absolute value of O?B of channel 3 than those of other channels.

The United States next generation geostationary satellite, GOES-R, will be equipped with the Advanced Baseline Imager (ABI) with 16 channels⑥. Among these 16 channels, two are visible channels, four are near-infrared channels, and 10 are infrared channels. The observation resolution at the sub-satellite point for infrared channel increases to 2 km. The ABI is able to perform four fulldisk scans or 12 continentals scans in one hour. The ABI has added an additional mesoscale mode. In this mode, the ABI can scan an area of 1000 km2every 30 seconds. GOES-R satellite is scheduled to be launched in 2015⑦. The next generation Chinese geostationary satellite FY-4 will be equipped with the Advanced Geostationary Radiation Imager (AGRI) and the Geostationary Interferometric Infrared Sounder (GIIRS). Similar to the ABI, the AGRI will have 14 channels that cover visible, near-infrared, shortwave infrared, midwave infrared and thermal infrared bands⑧. The GIIRS onboard FY-4 is an interferometric infrared sounder with 913 channels⑨. The GIIRS is similar to the Atmospheric Infrared Sounder (AIRS) onboard Aqua polar-orbiting satellite. Currently all hyperspectral sounders are onboard polar-orbiting satellites. FY-4 will be the first geostationary satellites with hyperspectral sounders onboard. Given the facts that assimilation of AIRS observations signif i cantly improves the forecast skill in numerical weather prediction (NWP) and AIRS retrieval products of greenhouse gases such as CO2provide insights into climate change, observations from GIIRS will play an important role in both NWP and climate studies.

注釋

① http://www.ospo.noaa.gov/Operations/GOES/schedules.html

② http://www.ospo.noaa.gov/Operations/GOES/west/imager-routine.html

③ http://www.class.ncdc.noaa.gov/release/data_available/goes/index.html

④ http://www.ospo.noaa.gov/Operations/GOES/east/fd.html

⑤ http://www.ospo.noaa.gov/Operations/GOES/east/rso.html

⑥ http://www.goer-r.gov/spacesegment/abi.html

⑦ http://www.nesdis.noaa.gov/flyout_schedules.html

⑧ http://www.wmo-sat.info/oscar/instruments/view/275

⑨ http://www.wmo-sat.info/oscar/instruments/view/214

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[3]Schmit T J, Elaine M P, Anthony J S, et al. Introducing the GOES-M imager. National Weather Digest 25, 2002(3/4): 28-37.

[4]Kidder S Q, Haar T H V. Satellite Meteorology: An Introduction. Vol. 466. San Diego: Academic Press, 1995: 466.

[5]Strabala K I, Ackerman S A, Menzel W P. Cloud properties inferred from 8-12μm Data. J Appl Meteor, 1994, 33: 212-229.

[6]Wu X, Schmit T, Galvin R, et al. Investigation of GOES imager 13.3μm channel cold bias. EUMETSAT Meteorological Satellite Conference, 2008: 1-12.

[7]Weng F. Advances in radiative transfer modeling in support of satellite data assimilation. J Atmos Sci, 2007, 64: 3799-3807.

[8]Capderou M. Satellites: Orbits and Missions. France: Springer-Verlag, 2005: 544.

[9]Menzel W P, James F W P. Introducing GOES-I: The fi rst of a new generation of geostationary operational environmental satellites. Bull Amer Meteor Soc, 1994, 75: 757-781.

[10]K?pken C, Kelly G, Thépaut J-N. Assimilation of Meteosat radiance data within the 4D-Var system at ECMWF: Assimilation experiments and forecast impact. Q J Roy Meteor Soc, 2004, 130: 2277-2292.

[11]Hillger W D, Timothy J S. NOAA Technical Report NESDIS 125: The GOES-13 Science Test: Imager and Sounder Radiance and Product Validations. United States National Environmental Satellite, Data, and Information Service, 2007.

[12]Hillger W D, Timothy J S. NOAA Technical Report NESDIS 131: The GOES-14 Science Test: Imager and Sounder Radiance and Product Validations. United States National Environmental Satellite, Data, and Information Service, 2010.

[13]Hillger W D, Timothy J S. NOAA Technical Report NESDIS 141: The GOES-15 Science Test: Imager and Sounder Radiance and Product Validations. United States National Environmental Satellite, Data, and Information Service, 2011.

An introduction to GOES Imager Data

Da Cheng1Zou Xiaolei1,2
(1 Department of Earth, Ocean and Atmospheric Science, Florida State University, USA 2 Center of Data Assimilation for Research and Application, Nanjing University of Information and Science & Technology, Nanjing 210044)

10.3969/j.issn.2095-1973.2014.04.008

2013年12月12日；

2014年7月18日

達成，Email: cd10k@my.fsu.edu

資助信息：科技部全球變化研究國家重大科學研究計劃（2010CB951600）