Global validation of FY-3A total ozone unit (TOU) total ozone columns using ground-based Brewer and Dobson measurements

Analysis of the accuracy and variability of total ozone columns (TOC) has been conducted by many studies, while the TOC observations derived from the total ozone unit (TOU) on board the Chinese FengYun-3A (FY-3A) satellite platform are notably less well documented. Therefore, in this present study, we mainly focus on the global-scale validation of TOU-derived total ozone column data by comparing them with spatially and temporally co-located ground-based measurements from the well-established Brewer and Dobson spectrophotometer for the period July 2009 through December 2011. The results show that TOU-derived total ozone column data yields high accuracy, with the root mean square error less than 5% in comparison with ground-based measurements. Meanwhile, TOU underestimates Brewer measurements by 1.1% in the Northern Hemisphere and overestimates Dobson total ozone 0.3% globally. In addition, TOU-derived total ozone shows no significant dependence on latitude in comparison with either Brewer or Dobson total ozone measurements. Nevertheless, a significant dependence of TOU-derived total ozone is observed on the solar zenith angle (SZA) in comparison with both Brewer and Dobson, demonstrating that TOU underestimates at large SZA and overestimates at small SZA. Finally, the dependence of satellite – ground-based relative difference for total ozone values shows fair agreement when total ozone values are in the range 250–450 Dobson units (DU). Overall, the Chinese FY-3A/TOU performs well on total ozone retrieval with high accuracy, and the total ozone data derived from the TOU can be used as a reliable data source for ozone monitoring and other atmospheric applications.     

Assessment of MetOp-A Advanced Very High Resolution Radiometer (AVHRR) short-wave infrared channel measurements using Infrared Atmospheric Sounding Interferometer (IASI) observations and line-by-line radiative transfer model simulations

MetOp-A satellite-based hyper-spectral Infrared Atmospheric Sounding Interferometer (IASI) observations are used to evaluate the accuracy of the broadband short-wave infrared (SWIR) atmospheric window channel (channel 3B) centred at 3.74 μm of the Advanced Very High Resolution Radiometer (AVHRR) carried on the same platform. To complement the partial spectral coverage of IASI, line-by-line radiative transfer model (LBLRTM)-simulated IASI spectra are used. The comparisons result in significant negative AVHRR minus IASI bias in radiance (～–0.04 mW m^–2 sr^–1 cm^–1) with scene temperature dependency in which the absolute value of the bias linearly increases with increasing temperature. It is demonstrated that the negative bias and the scene temperature dependency of the bias are the results of significant absorption in the portion of AVHRR spectral band not seen by IASI, leading to the conclusion that MetOp-A AVHRR channel 3B is not purely an ‘atmospheric window’ channel.     

Remote sensing ‘ground-based automatic UV / visible spectrometer’ for the study of atmospheric trace gases

An advance remote sensing instrument, the ‘ground-based automatic UV / visible spectrometer’, has been developed indigenously at Pune (18° 31′ N, 73° 55′ E) to cover the spectra (462–498 nm) of zenith sky scattered light. A spectrometry technique is used to find out the vertical column density (VCD) of many atmospheric trace gases, such as NO₂, O₃, H₂O and O₄. The VCDs of these gases are extracted from observed spectra by comparing the magnitude of the differential optical depth (DOD) of each species in the 462–498 nm spectral range. Slant column densities (SCDs) of each species are found to increase with solar zenith angle (SZA), due to the approaching higher path length of sunlight. The VCDs of O₃ and NO₂ derived by the UV / visible spectrometer are compared with the ozone monitoring instrument (OMI) Aura satellite and ground-based Brewer spectrometer data. The compared VCD values are found to be close to satellite and ground-based measurements.     

AERONET-based surface reflectance validation network (ASRVN) data evaluation: Case study for railroad valley calibration site

The AERONET-based Surface Reflectance Validation Network (ASRVN) is an operational processing system developed for validation of satellite derived surface reflectance products at regional and global scales. The ASRVN receives 50 × 50 km² subsets of MODIS data centered at AERONET sites along with AERONET aerosol and water vapor data, and performs an atmospheric correction. The ASRVN produces surface bidirectional reflectance factor (BRF), albedo, parameters of the Ross-Thick Li-Sparse (RTLS) BRF model, as well as Hemispherical-Directional Reflectance Factor (HDRF), which is required for comparison with the ground-based measurements. This paper presents a comparison of ASRVN HDRF with the ground-based HDRF measurements collected during 2001-2008 over a bright calibration Railroad Valley, Nevada site as part of the MODIS land validation program. The ground measurements were conducted by the Remote Sensing Group (RSG) at the University of Arizona using an ASD spectrometer. The study reveals a good agreement between ASRVN and RSG HDRF for both MODIS Terra and Aqua with rmse ~ 0.01-0.025 in the 500 m MODIS land bands B1-B7. Obtained rmse is below uncertainties due to the spatial and seasonal variability of the bright calibration 1 km² area. While two MODIS instruments have a similar rmse in the visible bands, MODIS Aqua has a better agreement (lower rmse) with the ground data than MODIS Terra at wavelengths 0.87-2.1 μm. An independent overall good agreement of two MODIS instruments with the ground data indicates that the relative calibration of MODIS Terra and Aqua at medium-to-bright reflectance levels for the stated time period is significantly better than uncertainties of the ASRVN and ground data.     

Intercomparison of satellite and ground-based measurements of ozone,NO2, HF,and HCl near Saint Petersburg,Russia

Regular intercomparison of different observing systems is a part of their testing and validation protocol, which gives the estimates of real measurement errors. The main objective of our study is the comparison of satellite and ground-based measurements of atmospheric composition near Saint Petersburg, Russia. Since early 2009, high-resolution Fourier Transform Infrared (FTIR) solar absorption spectra have been recorded at Peterhof station (59.82° N, 29.88° E), located in the suburbs of Saint Petersburg. We derived column amounts of O₃, HCl, HF, and NO₂ from these spectra using the retrieval codes SFIT2 and PROFFIT. We compared the data retrieved from Bruker 125 HR FTIR measurements with coincident satellite observations of the Microwave Limb Sounding (MLS), Ozone Monitoring Instrument (OMI), Fourier Transform Spectrometer from Atmospheric Chemistry Experiment (ACE-FTS), Global Ozone Monitoring Experiment (GOME and GOME-2), and Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) instruments. The relative differences in ozone columns of FTIR from OMI-TOMS amount within (+3.4 ± 2.9)%, from GOME-2 are (+2.2 ± 3.0)%. The comparison of FTIR and MLS measurements of stratospheric ozone columns gives no mean and 5% of the RMS differences. Measurements of NO₂ columns agree with the mean difference of +9% and the RMS differences within 14–16% for FTIR vs. GOME-2, SCIAMACHY, and OMI. FTIR vs. GOME comparison gives (+6 ± 31)%. HCl columns comparison for FTIR vs. MLS shows ?4.5% in the mean and 12% in the RMS differences. FTIR vs. ACE-FTS comparison (nine cases) gives ?8% and 10% for the mean and the RMS relative differences, respectively. Comparison of HF columns shows (?12 ± 6)% and (?12 ± 11)% for FTIR vs. ACE data v.2.2 and v.3.0, respectively. These figures show that the Peterhof ground-based FTIR measuring system can be used to support the validation of satellite data in the monitoring of stratospheric gases.     

SCIAMACHY/Envisat,OMI/Aura,and ground-based total ozone measurements over Kyiv-Goloseyev station

Validation of satellite ozone measurements is important for data improvement due to instrumental long-term drifts and retrieval algorithm limitations. For satellite data quality estimation, we compare the total ozone content (TOC) derived from the satellite Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY)/Envisat and Ozone Monitoring Instrument (OMI)/Aura spectrometer overpass data and the ground-based measurements made with the Dobson spectrophotometer 040 at the GAW station No. 498 Kyiv-Goloseyev. The station was opened for Dobson ozone measurements in 2010. The results for Direct Sun, Zenith Blue, and Zenith Cloud observations are presented separately, in order to assess the influence of weather conditions (clear or cloudy sky) on the difference between satellite and ground-based measurements. Results from the SCIAMACHY–Dobson and OMI–Dobson difference analyses show small relative overestimation of TOC for satellite data. The ground-based Dobson 040 data are of high quality for Direct Sun and Zenith Blue from AD ((305.5 and 325.0 nm) and (317.5 and 339.9 nm)) pair measurements. Seasonal variations of the difference are seen with maximal satellite–Dobson data discrepancy near the winter solstice. Satellite TOC values are systematically higher than Dobson ones at solar zenith angles larger than 70°. This difference could be explained by seasonal non-uniformity in the satellite data.     

The infrared spectral signature of volcanic ash determined from high-spectral resolution satellite measurements

High-spectral resolution infrared spectra of the earth's atmosphere and surface are routinely available from satellite sensors, such as the Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI). We exploit the spectral content of AIRS data to demonstrate that airborne volcanic ash has a unique signature in the infrared (8-12 μm) that can be used to infer particle size, infrared opacity and composition. The spectral signature is interpreted with the aid of a radiative transfer model utilizing the optical properties of andesite, rhyolite and quartz. Based on the infrared spectral signature, a new volcanic ash detection algorithm is proposed that can discriminate volcanic ash from other airborne substances and we show that the algorithm depends on particle size, optical depth and composition. The new algorithm has an improved sensitivity to optically thin ash clouds, and hence can detect them for longer (~ 4 days) and at greater distances from the source(~ 5000 km).     

An assessment of the black ocean pixel assumption for MODIS SWIR bands

Recent studies show that an atmospheric correction algorithm using shortwave infrared (SWIR) bands improves satellite-derived ocean color products in turbid coastal waters. In this paper, the black pixel assumption (i.e., zero water-leaving radiance contribution) over the ocean for the Moderate Resolution Imaging Spectroradiometer (MODIS) SWIR bands at 1240, 1640, and 2130 nm is assessed for various coastal ocean regions. The black pixel assumption is found to be generally valid with the MODIS SWIR bands at 1640 and 2130 nm even for extremely turbid waters. For the MODIS 1240 nm band, however, ocean radiance contribution is generally negligible in mildly turbid waters such as regions along the U.S. east coast, while some slight radiance contributions are observed in extremely turbid waters, e.g., some regions along the China east coast, the estuary of the La Plata River. Particularly, in the Hangzhou Bay, the ocean radiance contribution at the SWIR band 1240 nm results in an overcorrection of atmospheric and surface effects, leading to errors of MODIS-derived normalized water-leaving radiance at the blue reaching ~ 0.5 mW cm^− 2 μm^− 1 sr^− 1. In addition, we found that, for non-extremely turbid waters, i.e., the ocean contribution at the near-infrared (NIR) band < ~ 1.0 mW cm^− 2 μm^− 1 sr^− 1, there exists a good relationship in the regional normalized water-leaving radiances between the red and the NIR bands. Thus, for non-extremely turbid waters, such a red-NIR radiance relationship derived regionally can possibly be used for making corrections for the regional NIR ocean contributions without using the SWIR bands, e.g., for atmospheric correction of ocean color products derived from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS).     

Temporal and spatial variabilities of total ozone column over Portugal

This paper focuses on the spatial-temporal structure of total ozone column (TOC) over Portugal. This relevant region of southwestern Europe has not been evaluated yet in detail due to the lack of continuous and well-covered ground-based TOC measurements. The data used in this study are derived from the NASA's Total Ozone Mapping Spectrometer (TOMS) for the period 1978-2005. The TOC spatial behavior shows no significant longitudinal variability (smaller than 3%). In contrast, the variation in latitude changes between 3.5% and 6% depending on the calendar month. The TOC in the northern Portugal is, on average, higher than that recorded in the South. The temporal variability was analyzed for three scales: long-term, seasonal and short-term. The long-term TOC changes are analyzed between 1978 and 1999 by means of linear least squares fits. The results show an annual TOC trend of (−2.65 ± 0.70)%/decade which is statistically significant at the 95% confidence level. This TOC decrease is smaller than the trends obtained in other midlatitudes regions which could be partially explained by the compensation due to the observed increase in the tropospheric ozone over the Iberian Peninsula. A trend analysis performed for each individual month shows a statistically significant TOC decline between March and October, with a maximum linear trend value of (−7.30 ± 1.45)%/decade in May. The amplitude of the seasonal TOC cycle over Portugal shows a slight dependence in latitude, varying from 28.6 DU (37.5° N) to 33.6 DU (41.5° N). Finally, the short-term variability showed a notable seasonal behavior, with maximum day-to-day TOC changes in winter (~ 6%) and minimum in summer (~ 3%). In addition, the persistence (characterized by the autocorrelation coefficients) strongly decreases after a few days (except in summer months).     

Comparison of total ozone column observations from space-borne Ozone Monitoring Instrument with ground-based Dobson Ozone Spectrophotometer measurements at an urban location in Indo-Gangetic Basin

This article presents a comparison analysis of OMIT (Ozone Monitoring Instrument retrieved overpass total ozone column (TOC)), and DOST (Dobson Ozone Spectrophotometer observed TOC) over Delhi during a period from October 2004 to June 2011. Megacity Delhi, located in Indo-Gangetic Basin, is an important site for comparison of ground-based and satellite retrieved TOCs due to significant anthropogenic emissions of ozone precursors, large shift in seasons, and large-scale crop residue burning in the region. DOST and OMIT data show an overall bias of 3.07% and significant correlation with coefficient of determination R² = 0.73. Large seasonal fluctuations in the biases and correlations have been observed ranging from 2.46% (winter) to 3.82% (spring), and R² = 0.84 (winter) to R² = 0.09 (summer), respectively. The large biases are attributed to changes in temperature, cloud cover, pollutants emissions from urban area, and crop-residue burning events. We also find notable variations in correlations between the datasets due to the varying burden of absorbing aerosols from open field crop-residue burning. The R² has changed from 0.67 (for aerosol optical depth, AOD 1.5–3.5) to 0.77 (for AOD 0–0.99). The dependence of the bias on solar zenith angle, cloud fraction, and satellite distance is also discussed. A simple linear regression analysis is applied to check the linkage between DOST and OMIT. The influence of atmospheric air temperature and relative humidity on OMIT at different pressure levels between 1000 and 20 hPa has been discussed.     

Estimation of high-spatial resolution clear-sky longwave downward and net radiation over land surfaces from MODIS data

Surface downwelling longwave radiation (LWDN) and surface net longwave radiation (LWNT) are two components in the surface radiation budget. In this study, we developed new linear and nonlinear models using a hybrid method to derive instantaneous clear-sky LWDN over land from the Moderate Resolution Imaging Spectroradiometer (MODIS) TOA radiance at 1 km spatial resolution. The hybrid method is based on extensive radiative transfer simulation (physical) and statistical analysis (statistical). Linear and nonlinear models were derived at 5 sensor view zenith angles (0°, 15°, 30°, 45°, and 60°) to estimated LWDN using channels 27-29 and 31-34. Separate models were developed for daytime and nighttime observations. Surface pressure effect was considered by incorporating elevation in the models. The linear LWDN models account for more than 92% of variations of the simulated data sets, with standard errors less than 16.27 W/m² for all sensor view zenith angles. The nonlinear LWDN models explain more than 93% of variations, with standard errors less than 15.20 W/m². The linear and nonlinear LWDN models were applied to both Terra and Aqua TOA radiance and validated using ground data from six SURFRAD sites. The nonlinear models outperform the linear models at five sites. The averaged root mean squared errors (RMSE) of the nonlinear models are 17.60 W/m² (Terra) and 16.17 W/m² (Aqua), with averaged RMSE ~ 2.5 W/m² smaller than that of the linear models. LWNT was estimated using the nonlinear LWDN models and the artificial neural network (ANN) model method that predicts surface upwelling longwave radiation. LWNT was also validated using the same six SURFRAD sites. The averaged RMSEs are 17.72 (Terra) and 16.88 (Aqua) W/m²; the averaged biases are − 2.08 (Terra) and 1.99 (Aqua) W/m². The LWNT RMSEs are less than 20 W/m² for both Terra and Aqua observations at all sites.     

First results of ground-based Fourier Transform Infrared measurements of the H2O total column in the atmosphere over West Siberia

The first results of the water vapour total column (WVTC) Fourier Transform Infrared (FTIR) measurements carried out over West Siberia (near Tomsk) in the framework of the combined experiment (22 May 2012) are presented. Direct solar radiation spectra with high spectral resolution were recorded by ground-based FTIR spectrometer Bruker IFS-125M. New spectral intervals (the advantage of this spectral band is that observations could be performed without cooling the interferometer’s detector) were tested and then used to retrieve the H₂O total columns in the atmosphere by SFIT2 v3.92. Ground-based measurements of the WVTC and aerosol optical thickness in the atmosphere were carried out by means of the automated sun photometers (SP series). Sun photometer and FTIR observations were performed under clear-sky conditions. During this study, we compared data obtained from ground-based remote sensing systems to the results of infrared atmospheric sounding interferometer (IASI) MetOP-A satellite measurements and airborne measurements with the use of the Tu-134 aircraft laboratory. Comparison shows that FTIR observations could give reasonable agreements with sun photometer data within 1%. This value is less than the combined error (1.2%) of both techniques. The average values of total H₂O obtained for three measurement systems were as follows: 1.50 and 1.49 g cm^–2 for the Fourier spectrometer and sun photometer, respectively, and 1.84 g cm^–2 for IASI.     

卫星遥感大气CO2的技术与方法进展综述

综合分析了国际上卫星遥感观测大气二氧化碳（CO²）含量的主要技术与方法,讨论了现有星载大气CO²探测器（传感器）的主要理论基础、反演方法,归纳了仪器的主要性能指标、观测方式和观测目标,分析了影响CO²遥感精度的主要因素。具体研究下列3类星载CO2探测器：① 技术相对成熟的、观测要素既包含CO²也包含其他微量气体的综合性星载被动探测仪器,例如大气红外垂直探测仪(AIRS)、大气制图扫描成像吸收光谱仪(SCIAMACHY)、超高光谱红外大气探测干涉仪(IASI);② 针对大气中CO²混合比或者对流层下层CO²含量进行专门观测的星载被动探测器：极轨碳观测卫星(Orbiting Carbon Observatory,OCO)和温室气体观测卫星(Greenhouse gas Observing Satellite,GOSAT)搭载的被动红外探测器;③ ASCENDS和A\|SCOPE等国际卫星计划正在研制中的星载主动激光雷达探测器。 进一步介绍了我国在高光谱仪器研制方面具备的研究基础。最后初步分析了星载CO²探测结果的验证、资料同化方法和未来的发展趋势。     

Atmospheric integrated water vapour measured by IR and MW techniques at the Peterhof site (Saint Petersburg,Russia)

Regular comparison of different systems for monitoring atmospheric integrated water vapour (IWV) is part of their testing and validation protocol. We compared coincident measurements of IWV over Saint Petersburg (Russia) from ground-based Fourier-transform spectrometer Bruker IFS 125 HR (FTIR) and microwave radiometer RPG-HATPRO (MW) at the Peterhof site between March 2013 and June 2015. This study is a contribution towards global efforts to make such inter-comparisons at various ground-based sites. Since FTIR measures solar radiance, the vast majority of coincident pairs correspond to the spring and summer seasons. The numbers of measurements in the dry season (from October to April) and in the wet season (from May to September) are almost identical, comprising 616 and 638 pairs, respectively. MW and FTIR data sets demonstrate a high level of agreement: the mean relative difference between MW and FTIR data is less than 3% (0.3 mm), with standard deviation from the means of about 4% (0.4 mm). Notwithstanding the short distance between both instruments (150 m), they can monitor different air masses: MW is a zenith-viewing instrument whereas FTIR follows the sun. We analysed the FTIR observation fields under different solar zenith and azimuth angles, taking into account the location of the Peterhof site between the Gulf of Finland and rural suburbs of Saint Petersburg. Although in general MW measurements slightly overestimated IWV in comparison with the FTIR data, we detected several episodes when FTIR gave higher values than MW. These episodes relate to the FTIR observations directed at the coastal region with more humid air than that above the measurement site. We may conclude at this stage of our investigations that the spatial inhomogeneity of humidity fields in the atmosphere causes the most significant differences between the two data sets. Detailed analysis of variation in spatial IWV, e.g. using a MW radiometer in angular scanning mode, is an issue for future research.     

Variation of total column ozone along the monsoon trough region over north India

This study examined the total column ozone (TCO) variations over New Delhi (28.65° N, 77.217° E) and Varanasi (25.32° N, 83.03° E), which lie along the monsoon trough region, and over the tropical station Kodaikanal (10.23° N, 77.46° E), which lies outside the monsoon trough. Monthly, seasonal and annual TCO variations were determined using data from ground-based Dobson spectrophotometers during 2000–2008, Brewer spectrophotometers during 2000–2005 and the satellite-based Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) during 2002–2008. We found that Dobson, Brewer and SCIAMACHY TCO variations showed negative trends, indicating a decreasing tendency during the period studied at all three stations. Over Varanasi, the trend decreased further by about 3 DU year^?1. Quasi-Biennial Oscillation (QBO) influences were seen in the time series of TCO over New Delhi and Varanasi, and weaker QBO signals over Kodaikanal. Comparisons were made between ground-based Dobson and Brewer spectrophotometer and SCIAMACHY satellite monthly mean TCO values. The differences between SCIAMACHY and Dobson TCO were 0.4–4.2% for New Delhi and 2.3–6.2% for Varanasi. The differences between SCIAMACHY and Brewer TCO values were 2.0–6.4% for Kodaikanal. In the peak monsoon months (July and August), decreases in TCO values over New Delhi and Varanasi (the monsoon trough region) may be due to the deep convection present during the monsoon season. During the monsoon season, several intense cyclonic systems appear over the monsoon trough region and may cause lowering of the TCO. Kodaikanal shows opposite features, with high values being observed during the peak monsoon months. TCO values over New Delhi were found to be higher than those over Varanasi and Kodaikanal, and TCO values over Varanasi were higher than over Kodaikanal. It was concluded that TCO values increase with increasing latitude.     

Comparison and evaluation of Medium Resolution Imaging Spectrometer leaf area index products across a range of land use

Leaf area index (LAI) is a commonly required parameter when modelling land surface fluxes. Satellite based imagers, such as the 300 m full resolution (FR) Medium Spectral Resolution Imaging Spectrometer (MERIS), offer the potential for timely LAI mapping. The availability of multiple MERIS LAI algorithms prompts the need for an evaluation of their performance, especially over a range of land use conditions. Four current methods for deriving LAI from MERIS FR data were compared to estimates from in-situ measurements over a 3 km × 3 km region near Ottawa, Canada. The LAI of deciduous dominant forest stands and corn, soybean and pasture fields was measured in-situ using digital hemispherical photography and processed using the CANEYE software. MERIS LAI estimates were derived using the MERIS Top of Atmosphere (TOA) algorithm, MERIS Top of Canopy (TOC) algorithm, the Canada Centre for Remote Sensing (CCRS) Empirical algorithm and the University of Toronto (UofT) GLOBCARBON algorithm. Results show that TOA and TOC LAI estimates were nearly identical (R² > 0.98) with underestimation of LAI when it is larger than 4 and overestimation when smaller than 2 over the study region. The UofT and CCRS LAI estimates had root mean square errors over 1.4 units with large (∼ 25%) relative residuals over forests and consistent underestimates over corn fields. Both algorithms were correlated (R² > 0.8) possibly due to their use of the same spectral bands derived vegetation index for retrieving LAI. LAI time series from TOA, TOC and CCRS algorithms showed smooth growth trajectories however similar errors were found when the values were compared with the in-situ LAI. In summary, none of the MERIS LAI algorithms currently meet performance requirements from the Global Climate Observing System.     

Characterization of terrestrial water dynamics in the Congo Basin using GRACE and satellite radar altimetry

The Congo Basin is the world's third largest in size (~ 3.7 million km²), and second only to the Amazon River in discharge (~ 40,200 m³ s^− 1 annual average). However, the hydrological dynamics of seasonally flooded wetlands and floodplains remains poorly quantified. Here, we separate the Congo wetland into four 3° × 3° regions, and use remote sensing measurements (i.e., GRACE, satellite radar altimeter, GPCP, JERS-1, SRTM, and MODIS) to estimate the amounts of water filling and draining from the Congo wetland, and to determine the source of the water. We find that the amount of water annually filling and draining the Congo wetlands is 111 km³, which is about one-third the size of the water volumes found on the mainstem Amazon floodplain. Based on amplitude comparisons among the water volume changes and timing comparisons among their fluxes, we conclude that the local upland runoff is the main source of the Congo wetland water, not the fluvial process of river-floodplain water exchange as in the Amazon. Our hydraulic analysis using altimeter measurements also supports our conclusion by demonstrating that water surface elevations in the wetlands are consistently higher than the adjacent river water levels. Our research highlights differences in the hydrology and hydrodynamics between the Congo wetland and the mainstem Amazon floodplain.     

Preliminary applications of a land surface temperature retrieval method to IASI and AIRS data

Land surface temperature (LST) is one of the key state variables for many applications. This article aims to apply our previously developed LST retrieval method to infrared atmospheric sounding interferometer (IASI) and atmospheric infrared sounder (AIRS) data. On the basis of the opposite characteristics of the atmospheric spectral absorption and surface spectral emissivity, a ‘downwelling radiance residual index’ (DRRI) has been recalled and improved to obtain LST and emissivity. To construct an efficient DRRI, an automatic channel selection procedure has been proposed, and 11 groups of channels have been selected within the range 800–1000 cm^?1. The DRRI has been tested with IASI and AIRS data. For the IASI data, the radiosonde data have been used to correct for atmospheric effects and to retrieve LST, while the atmospheric profiles retrieved from AIRS data have been used to perform the atmospheric corrections and subsequently to estimate LST from AIRS data. The differences between IASI- and Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LSTs are no more than 2 K, while the differences between AIRS- and MODIS-derived LSTs are less than 5 K. Even though an exceptionally problematic value occurred (–12.89 K), the overall differences between AIRS-estimated LST and the AIRS L2 LST product are no more than 5 K. Although the IASI-derived LST is more accurate than the AIRS-derived one, the convenient retrieval of AIRS atmospheric profile made this method more applicable. Limitations and uncertainties in retrieving LST using the DRRI method are also discussed.     

Cross-scalar satellite phenology from ground, Landsat, and MODIS data

Phenological records constructed from global mapping satellite platforms (e.g. AVHRR and MODIS) hold the potential to be valuable tools for monitoring vegetation response to global climate change. However, most satellite phenology products are not validated, and field checking coarse scale (≥ 500 m) data with confidence is a difficult endeavor. In this research, we compare phenology from Landsat (field scale, 30 m) to MODIS (500 m), and compare datasets derived from each instrument. Landsat and MODIS yield similar estimates of the start of greenness (r² = 0.60), although we find that a high degree of spatial phenological variability within coarser-scale MODIS pixels may be the cause of the remaining uncertainty. In addition, spatial variability is smoothed in MODIS, a potential source of error when comparing in situ or climate data to satellite phenology. We show that our method for deriving phenology from satellite data generates spatially coherent interannual phenology departures in MODIS data. We test these estimates from 2000 to 2005 against long-term records from Harvard Forest (Massachusetts) and Hubbard Brook (New Hampshire) Experimental Forests. MODIS successfully predicts 86% of the variance at Harvard forest and 70% of the variance at Hubbard Brook; the more extreme topography of the later is inferred to be a significant source of error. In both analyses, the satellite estimate is significantly dampened from the ground-based observations, suggesting systematic error (slopes of 0.56 and 0.63, respectively). The satellite data effectively estimates interannual phenology at two relatively simple deciduous forest sites and is internally consistent, even with changing spatial scale. We propose that continued analyses of interannual phenology will be an effective tool for monitoring native forest responses to global-scale climate variability.     

Satellite and surface-based remote sensing of Saharan dust aerosols

The spatial and temporal characteristics of dust aerosols and their properties are assessed from satellite and ground-based sensors. The spatial distribution of total column aerosol optical depth at 550 nm (AOD) from the Moderate Resolution Imaging SpectroRadiometer (MODIS) coupled with top of atmosphere Clouds and the Earth's Radiant Energy System (CERES) shortwave fluxes are examined from the Terra satellite over the Atlantic Ocean. These data are then compared with AOD from two Aerosol Robotic Network (AERONET) ground-based sun photometer measurement sites for nearly six years (2000-2005). These two sites include Capo Verde (CV) (16°N, 24°W) near the Saharan dust source region and La Paguera (LP) (18°N, 67°W) that is downwind of the dust source regions. The AOD is two to three times higher during spring and summer months over CV when compared to LP and the surrounding regions. For a unit AOD value, the instantaneous TOA shortwave direct radiative effect (DRE) defined as the change in shortwave flux between clear and aerosol skies for CV and LP are − 53 and − 68 Wm^− 2 respectively. DRE for LP is likely more negative due to fall out of larger particles during transport from CV to LP. However, separating the CERES-derived DRE by MODIS aerosol effective radii was difficult. Satellite and ground-based dust aerosol data sets continue to be useful to understand dust processes related to the surface and the atmosphere.