应用气象学报
應用氣象學報
응용기상학보
QUARTERLY JOURNAL OF APPLIED METEOROLOGY
2014年
1期
42-51
,共10页
高玲%张里阳%李俊%陈林%孙凌%李晓静
高玲%張裏暘%李俊%陳林%孫凌%李曉靜
고령%장리양%리준%진림%손릉%리효정
AVHRR%地表反射率%气溶胶光学厚度%MODIS%AERONET
AVHRR%地錶反射率%氣溶膠光學厚度%MODIS%AERONET
AVHRR%지표반사솔%기용효광학후도%MODIS%AERONET
AVHRR%surface albedo%aerosol optical depth%MODIS%AERONET
开发 AVHRR 可见光通道反演陆地气溶胶光学厚度(AOD)的算法对于研究长时间序列 AOD 的变化有重要意义。AVHRR 由于缺少2.1μm 通道而不能采用 MODIS 的暗背景算法,该文利用背景合成算法进行陆地 AOD反演。背景合成算法是指假设一段时间内地表反射率变化不大且会出现相对清洁大气,采用最小值合成即可得到地表反射率,再通过辐射传输模式6S 制作的查算表查算得到 AOD 的反演结果。将此算法应用到2009年AVHRR 中国部分陆地区域(15°~45°N,75°~135°E)得到 AOD 的时空分布,将反演结果与同期 Aqua/MODIS 的MOD04 AOD 产品进行对比分析表明,华北和华东地区的反演效果较好,西北地区结果较差。以长江三角洲地区为例可知,AVHRR AOD 产品与 MODIS AOD 产品以及 AERONET 观测的 AOD 相比相关系数基本在0.6以上,从时间变化规律来看,AVHRR AOD 和 MODIS AOD 产品年变化趋势具有很好的一致性。该文为建立长时间序列 AVHRR AOD 数据集提供了一个较为可行的方法。
開髮 AVHRR 可見光通道反縯陸地氣溶膠光學厚度(AOD)的算法對于研究長時間序列 AOD 的變化有重要意義。AVHRR 由于缺少2.1μm 通道而不能採用 MODIS 的暗揹景算法,該文利用揹景閤成算法進行陸地 AOD反縯。揹景閤成算法是指假設一段時間內地錶反射率變化不大且會齣現相對清潔大氣,採用最小值閤成即可得到地錶反射率,再通過輻射傳輸模式6S 製作的查算錶查算得到 AOD 的反縯結果。將此算法應用到2009年AVHRR 中國部分陸地區域(15°~45°N,75°~135°E)得到 AOD 的時空分佈,將反縯結果與同期 Aqua/MODIS 的MOD04 AOD 產品進行對比分析錶明,華北和華東地區的反縯效果較好,西北地區結果較差。以長江三角洲地區為例可知,AVHRR AOD 產品與 MODIS AOD 產品以及 AERONET 觀測的 AOD 相比相關繫數基本在0.6以上,從時間變化規律來看,AVHRR AOD 和 MODIS AOD 產品年變化趨勢具有很好的一緻性。該文為建立長時間序列 AVHRR AOD 數據集提供瞭一箇較為可行的方法。
개발 AVHRR 가견광통도반연륙지기용효광학후도(AOD)적산법대우연구장시간서렬 AOD 적변화유중요의의。AVHRR 유우결소2.1μm 통도이불능채용 MODIS 적암배경산법,해문이용배경합성산법진행륙지 AOD반연。배경합성산법시지가설일단시간내지표반사솔변화불대차회출현상대청길대기,채용최소치합성즉가득도지표반사솔,재통과복사전수모식6S 제작적사산표사산득도 AOD 적반연결과。장차산법응용도2009년AVHRR 중국부분륙지구역(15°~45°N,75°~135°E)득도 AOD 적시공분포,장반연결과여동기 Aqua/MODIS 적MOD04 AOD 산품진행대비분석표명,화북화화동지구적반연효과교호,서북지구결과교차。이장강삼각주지구위례가지,AVHRR AOD 산품여 MODIS AOD 산품이급 AERONET 관측적 AOD 상비상관계수기본재0.6이상,종시간변화규률래간,AVHRR AOD 화 MODIS AOD 산품년변화추세구유흔호적일치성。해문위건립장시간서렬 AVHRR AOD 수거집제공료일개교위가행적방법。
The moderate-resolution imaging spectroradiometer (MODIS)onboard NASA EOS Terra and Aqua satellites,advanced very high resolution radiometer (AVHRR)onboard NOAA series provide important aerosol measurements.MODIS provides atmosphere aerosol optical depth (AOD)product since 2000,and AVHRR also provides AOD product since 1981 but only over ocean.Developing AOD retrieval algorithm which can also obtain AOD from AVHRR over land is very important for establishing a long term AOD da-ta record for climate studies.As 2.1 μm band is absent,an algorithm which is different from MODIS is in-troduced to retrieve AOD over land from AVHRR.With this method,the surface target is assumed to re-main radiometrically invariant over a certain time period and some of observations are made under clear-sky background aerosol conditions.When background aerosol conditions are given,surface reflectance can be estimated by extracting the second minimum reflectance during the previous 22 days and the future 22 days.The second darkest reflectance is chosen to reduce cloud shadow contamination.After surface reflec-tance is selected,AOD is retrieved from a look up table (LUT)generated with the second simulation of the satellite signal in the solar spectrum (6S)radiative transfer model.The AOD over part of China (15°—45°N,75°—135°E)from AVHRR in 2009 is obtained based on this algorithm.The distribution pattern of AOD from this work is consistent with that of MYDO04 from MODIS in North China and East China,but has some difference in Northwest China.The daily regional mean AOD from AVHRR in the Yangtze Delta (28°—36°N,112°—122°E)agrees well with MODIS AOD with all correlation coefficients larger than 0.5 for four seasons,even up to 0.8 in winter.The correlation coefficients are 0.70 in Beijing,0.63 in Xiang-he and 0.61 in Taihu when AOD from AERONET are used to validate the AVHRR AOD retrievals.To compare temporally varying AERONET data with spatially varying AVHRR,the time match window is limited within 30 minutes and the spatial distance is limited within 0.10.The monthly variation of AOD from AVHRR in the Yangtze River Delta is consistent with that from MODIS,but the former is larger. Error sources about this retrieving algorithm are also discussed,including different satellite zenith angles in the selected period,surface reflectance,aerosol types,background AOD,calibration and sensor noise and so on.According to these results,this algorithm has the potential for deriving long-term AOD climate data record over land from AVHRR although some uncertainties still exist.Quality control and error char-acterization will be further investigated in the future.