Retrieval of volcanic ash particle size, mass and optical depth from a ground-based thermal infrared camera

Volcanoes can emit fine-sized ash particles (1–10 μm radii) into the atmosphere and if they reach the upper troposphere or lower stratosphere, these particles can have deleterious effects on the atmosphere and climate. If they remain within the lowest few kilometers of the atmosphere, the particles can lead to health effects in humans and animals and also affect vegetation. It is therefore of some interest to be able to measure the particle size distribution, mass and other optical properties of fine ash once suspended in the atmosphere. A new imaging camera working in the infrared region between 7–14 μm has been developed to detect and quantify volcanic ash. The camera uses passive infrared radiation measured in up to five spectral channels to discriminate ash from other atmospheric absorbers (e.g. water molecules) and a microphysical ash model is used to invert the measurements into three retrievable quantities: the particle size distribution, the infrared optical depth and the total mass of fine particles. In this study we describe the salient characteristics of the thermal infrared imaging camera and present the first retrievals from field studies at an erupting volcano. An automated ash alarm algorithm has been devised and tested and a quantitative ash retrieval scheme developed to infer particle sizes, infrared optical depths and mass in a developing ash column. The results suggest that the camera is a useful quantitative tool for monitoring volcanic particulates in the size range 1–10 μm and because it can operate during the night, it may be a very useful complement to other instruments (e.g. ultra-violet spectrometers) that only operate during daylight.     

Remote Sensing Monitoring of Volcanic Ash Clouds Based on PCA Method

Volcanic ash clouds threaten the aviation safety and cause global environmental effects. It is possible to effectively monitor the volcanic ash cloud with the aid of thermal infrared remote sensing technology. Principal component analysis (PCA) is able to remove the inter-band correlation and eliminate the data redundancy of remote sensing data. Taking the Eyjafjallajokull volcanic ash clouds formed on 15 and 19 April 2010 as an example, in this paper, the PCA method is used to monitor the volcanic ash cloud based on MODIS bands selection; the USGS standard spectral database and the volcanic absorbing aerosol index (AAI) are applied as contrasts to the monitoring result. The results indicate that: the PCA method is much simpler; its spectral matching rates reach 74.65 and 76.35%, respectively; and the PCA method has higher consistency with volcanic AAI distribution.     

利用独立分量分析进行火山灰云遥感检测

火山灰云不但引起全球气候和环境系统的重大变化,而且还会威胁航空安全。热红外遥感技术为检测火山灰云提供了新手段,但是遥感数据自身的冗余和波段相关性大大降低了火山灰云的检测精度。独立分量分析(Independent Component Analysis,ICA)能够实现遥感数据的去相关和消除冗余,在火山灰云检测中具有一定的潜力。通过探索火山灰云的物理、化学性质,文中以2010年4月19日冰岛艾雅法拉(Eyjafjallajokull)火山灰云MODIS图像为数据源,在对MODIS数据进行主成分分析处理的基础上,利用ICA进行火山灰云检测。结果表明:ICA能够较好地从MODIS图像中获取火山灰云信息,所得结果与美国地质调查局标准光谱数据库和火山灰云SO2浓度分布具有较好的一致性,取得了较好的检测效果。     

Impact on volcanic ash detection caused by the loss of the 12.0 μm “Split Window” band on GOES Imagers

Geostationary Operational Environmental Satellite (GOES) Imager and Sounder data were evaluated to determine the potential effects of volcanic ash detection without the use of a 12 μm infrared (IR) band, on GOES-M (12) through Q (a period of at least 10 years). Principal component analysis (PCA) images with and without 12 μm IR data were compared subjectively for six weak to moderate eruptions using pattern recognition techniques, and objectively by determining a false detection rate parameter. GOES Sounder data were also evaluated in a few instances to assess any potential contributions from the new 13.3 μm Imager band.Results indicated that, during periods of daylight, there was little apparent difference in the quality of IR detection without the 12 μm IR, likely due to a maximum in solar reflectance of silicate ash in a shortwave IR (SWIR) band centered near 3.9 μm. At night when SWIR reflectance diminished, the ash detection capability appeared to be significantly worse, evidenced by increased ambiguity between volcanic ash and meteorological clouds or surface features. The possible effects of this degradation on aviation operations are discussed. The new 13.3 μm IR band on GOES has the capability to help distinguish ash from cirrus clouds, but not from low level clouds consisting of water droplets.Multi-spectral data from higher resolution polar orbiting satellites may also be used to supplement analyses from lower resolution GOES for long-lived ash cloud events. The Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments appear to be the best options in accomplishing this, with additional satellite missions becoming available later in the decade. In summary, it will still be possible to observe and track significant volcanic ash clouds in the GOES-M through Q era (2003–2012) without the benefit of 12 μm IR data, but with some degradation that will be most significant at night.     

Integrated satellite observations of the 2001 eruption of Mt. Cleveland, Alaska

Satellite data were the primary source of information for the eruption of Mt. Cleveland, Alaska on 19 February, and 11 and 19 March 2001. Multiple data sets were used pre-, syn- and post-eruption to mitigate the hazard and determine an eruption chronology. The 19 February eruption was the largest of the three, resulting in a volcanic cloud that formed an arc over 1000 km long, moved to the NE across Alaska and was tracked using satellite data over more than a 50-h period. The volcanic cloud was “concurrently” detected on the GOES, AVHRR and MODIS data at various times and their respective signals compared. All three sensors detected a cloud that had a very similar shape and position but there were differences in their areal extent and internal structural detail. GOES data showed the largest volcanic cloud in terms of area, probably due to its oblique geometry. MODIS bands 31 and 32, which are comparable to GOES and AVHRR thermal infrared wavelengths, were the least effective single channels at detecting the volcanic cloud of those investigated (MODIS bands 28, 29, 31 and 32). MODIS bands 28 and 29 detected the largest volcanic clouds that could easily be distinguished from weather clouds. Of the split-window data, MODIS bands 29 minus band 32 detected the largest cloud, but the band 31 minus band 32 data showed the volcanic cloud with the most internal structural detail. The Puff tracking model accurately tracked the movement, and predicted the extent and shape of this complex cloud even into areas beyond satellite detection. Numerous thermal anomalies were also observed during the eruption on the twice-daily AVHRR data and the high spatial-resolution Landsat data. The high-resolution Radarsat data showed that the AVHRR thermal anomalies were due to lava and debris flow features and a newly formed fan along the west coast of the island. Field observations and images from a hand-held Forward Looking Infrared Radiometer (FLIR) showed that the flow features were ′a′a lava, debris flows and a warm debris fan along the west coast. Real-time satellite data were the primary tool used to monitor the eruption, track changes and to mitigate hazards. High-resolution data, even though coverage is infrequent, were critical in helping to identify volcanic processes and to compile an eruption chronology.     

Evaluation of the Physical and Chemical Properties of Eyjafjallajökull Volcanic Plume Using a Cloud-Resolving Model

The Eyjafjallajökull volcanic eruption, which occurred on April 14, 2010, caused many environmental, air traffic and health problems. An attempt has been made to demonstrate for the first time that certain improvements could be made in the quantitative prediction of the volcanic ash parameters, and in the accounting of the processes in the immediate vicinity of the volcano, using a cloud-resolving model. This type of explicit modeling by treatment of volcanic ash and sulfate chemistry parameterization, with input of a number parameters describing the volcanic source, is the way forward for understanding the complex processes in plumes and in the future plume dispersion modeling. Results imply that the most significant microphysical processes are those related to accretion of cloud water, cloud ice and rainwater by snow, and accretion of rain and snow by hail. The dominant chemical conversion rates that give a great contribution to the sulfate budget are nucleation and dynamic scavenging and oxidation processes. A three-dimensional numerical experiment has shown a very realistic simulation of volcanic ash and other chemical compounds evolution, with a sloping structure strongly influenced by the meteorological conditions. In-cloud oxidation by H₂O₂ is the dominant pathway for SO₂ oxidation and allows sulfate to be produced within the SO₂ source region. The averaged cloud water pH of about 5.8 and rainwater pH of 4.5 over simulation time show quantitatively how the oxidation may strongly influence the sulfate budget and acidity of volcanic cloud. Compared to observations, model results are close in many aspects. Information on the near field volcanic plume behavior is essential for early preparedness and evacuation. This approach demonstrates a potential improvement in quantitative predictions regarding the volcanic plume distribution at different altitudes. It could be a useful tool for modeling volcanic plumes for better emergency measures planning.     

Towards the estimation root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals

The upcoming deployment of satellite-based microwave sensors designed specifically to retrieve surface soil moisture represents an important milestone in efforts to develop hydrologic applications for remote sensing observations. However, typical measurement depths of microwave-based soil moisture retrievals are generally considered too shallow (top 2–5 cm of the soil column) for many important water cycle and agricultural applications. Recent work has demonstrated that thermal remote sensing estimates of surface radiometric temperature provide a complementary source of land surface information that can be used to define a robust proxy for root-zone (top 1 m of the soil column) soil moisture availability. In this analysis, we examine the potential benefits of simultaneously assimilating both microwave-based surface soil moisture retrievals and thermal infrared-based root-zone soil moisture estimates into a soil water balance model using a series of synthetic twin data assimilation experiments conducted at the USDA Optimizing Production Inputs for Economic and Environmental Enhancements (OPE³) site. Results from these experiments illustrate that, relative to a baseline case of assimilating only surface soil moisture retrievals, the assimilation of both root- and surface-zone soil moisture estimates reduces the root-mean-square difference between estimated and true root-zone soil moisture by 50% to 35% (assuming instantaneous root-zone soil moisture retrievals are obtained at an accuracy of between 0.020 and 0.030 m³ m⁻³). Most significantly, improvements in root-zone soil moisture accuracy are seen even for cases in which root-zone soil moisture retrievals are assumed to be relatively inaccurate (i.e. retrievals errors of up to 0.070 m³ m⁻³) or limited to only very sparse sampling (i.e. one instantaneous measurement every eight days). Preliminary real data results demonstrate a clear increase in the R² correlation coefficient with ground-based root-zone observations (from 0.51 to 0.73) upon assimilation of actual surface soil moisture and tower-based thermal infrared temperature observations made at the OPE³ study site.     

Surface area, porosity and water adsorption properties of fine volcanic ash particles

Our understanding on how ash particles in volcanic plumes react with coexisting gases and aerosols is still rudimentary, despite the importance of these reactions in influencing the chemistry and dynamics of a plume. In this study, six samples of fine ash (<100 m) from different volcanoes were measured for their specific surface area, a_s, porosity and water adsorption properties with the aim to provide insights into the capacity of silicate ash particles to react with gases, including water vapour. To do so, we performed high-resolution nitrogen and water vapour adsorption/desorption experiments at 77 K and 303 K, respectively. The nitrogen data indicated a_s values in the range 1.1–2.1 m²/g, except in one case where a a_s of 10 m²/g was measured. This high value is attributed to incorporation of hydrothermal phases, such as clay minerals, in the ash surface composition. The data also revealed that the ash samples are essentially non-porous, or have a porosity dominated by macropores with widths >500 Å. All the specimens had similar pore size distributions, with a small peak centered around 50 Å. These findings suggest that fine ash particles have relatively undifferentiated surface textures, irrespective of the chemical composition and eruption type. Adsorption isotherms for water vapour revealed that the capacity of the ash samples for water adsorption is systematically larger than predicted from the nitrogen adsorption a_s values. Enhanced reactivity of the ash surface towards water may result from (i) hydration of bulk ash constituents; (ii) hydration of surface compounds; and/or (iii) hydroxylation of the surface of the ash. The later mechanism may lead to irreversible retention of water. Based on these experiments, we predict that volcanic ash is covered by a complete monolayer of water under ambient atmospheric conditions. In addition, capillary condensation within ash pores should allow for deposition of condensed water on to ash particles before water reaches saturation in the plume. The total mass of water vapour retained by 1 g of fine ash at 0.95 relative water vapour pressure is calculated to be ~10^–2 g. Some volcanic implications of this study are discussed.Editorial responsibility: J. Gilbert     

Complex spatial feedbacks of tephra redistribution,ice melt and surface roughness modulate ablation on tephra covered glaciers

Tephra fallout from the 2011 Grímsvötn eruption onto Svínafellsjökull, Iceland, created an ice‐ash landscape of a type that is rarely studied but is nevertheless common in glacio‐volcanic regions. We used terrestrial laser scanning (TLS) to measure ice surface topography and absorption at high spatial resolution, confirming ablation rates either reduce or increase under thick (insulating) and thin (reduced albedo) ash deposits, respectively. Fourier transform analysis of the TLS data identified that a three‐fold increase in aerodynamic roughness was attributable to an increase in larger (> 0·2 m) surface features. Moreover, TLS measurements revealed the importance of ash redistribution by meltwater in generating differential melting which modifies roughness and ash patchiness, such that the net effect of these spatial ash–ice feedbacks was to reduce ablation rates by up to 59%. The modulating effects of these previously undocumented feedbacks on ablation rates are, therefore, significant and must be correctly parameterized if ash‐covered glacier mass balances are to be predicted correctly. Copyright © 2012 John Wiley & Sons, Ltd.     

Isotopic geochemistry of acid thermal waters and volcanic gases from Zaō volcano in Japan

The chemical composition and D/H, and ratios have been determined for the acid hot waters and volcanic gases discharging from Zaō volcano in Japan. The thermal springs in Zaō volcano issue acid sulfate-chloride type waters (Zaō) and acid sulfate type waters (Kamoshika). Gases emitted at Kamoshika fumaroles are rich in CO₂, SO₂ and N₂, exclusive of H₂O. Chloride concentrations and oxygen isotope data indicate that the Zaō thermal waters issue a fluid mixture from an acid thermal reservoir and meteoric waters from shallow aquifers. The waters in the Zaō volcanic system have slight isotopic shifts from the respective local meteoric values. The isotopic evidence indicates that most of the water in the system is meteoric in origin. Sulfates in Zaō acid sulfate-chloride waters with δ³⁴S values of around +15‰, are enriched in ³⁴S compared to Zaō H₂S, while the acid sulfate waters at Kamoshika contain supergene light sulfate (δ³⁴S = + 4‰) derived from volcanic sulfur dioxide from the volcanic exhalations. The sulfur species in Zaō acid waters are lighter in δ³⁴S than those of other volcanic areas, reflecting the difference in total pressure.     

Volcanic ash cloud detection from MODIS image based on CPIWS method

Volcanic ash cloud detection has been a difficult problem in moderate-resolution imaging spectroradiometer (MODIS) multispectral remote sensing application. Principal component analysis (PCA) and independent component analysis (ICA) are effective feature extraction methods based on second-order and higher order statistical analysis, and the support vector machine (SVM) can realize the nonlinear classification in low-dimensional space. Based on the characteristics of MODIS multispectral remote sensing image, via presenting a new volcanic ash cloud detection method, named combined PCA-ICA-weighted and SVM (CPIWS), the current study tested the real volcanic ash cloud detection cases, i.e., Sangeang Api volcanic ash cloud of 30 May 2014. Our experiments suggest that the overall accuracy and Kappa coefficient of the proposed CPIWS method reach 87.20 and 0.7958%, respectively, under certain conditions with the suitable weighted values; this has certain feasibility and practical significance.     

利用ENVISAT/AATSR资料反演黄土高原陇东地区地表温度

由于ENVISAT/AATSR资料不同角度热辐射亮度值之间存在较高的相关性从而导致较大误差的产生,本文尝试避开这种误差源,只选取天底观测数据对黄土高原陇东地区整层大气水汽含量及地表温度进行反演.与MODIS整层大气水汽含量产品对比验证表明,本文结果与MODIS产品有一定差异,但是可以直接用于大气透过率的估算.结合野外观测数据对地表温度反演结果的检验表明,最大绝对误差为4.0 ℃,平均相对误差为5.0％,因此,该算法在黄土高原陇东地区应用比较成功.     

Growth of volcanic ash aggregates in the presence of liquid water and ice: an experimental approach

Key processes influencing the aggregation of volcanic ash and hydrometeors are examined with an experimental method employing vibratory pan aggregation. Mechanisms of aggregation in the presence of hail and ice pellets, liquid water (≤30?wt%), and mixed water phases are investigated at temperatures of 18 and ?20?°C. The experimentally generated aggregates, examined in hand sample, impregnated thin sections, SEM imagery, and X-ray microtomography, closely match natural examples from phreatomagmatic phases of the 27?ka Oruanui and 2010 Eyjafjallaj?kull eruptions. Laser diffraction particle size analysis of parent ash and aggregates is also used to calculate the first experimentally derived aggregation coefficients that account for changing liquid water contents and subzero temperatures. These indicate that dry conditions (<5–10?wt% liquid) promote strongly size selective collection of sub-63?μm particles into aggregates (given by aggregation coefficients >1). In contrast, liquid-saturated conditions (>15–20?wt% liquid) promote less size selective processes. Crystalline ice was also capable of preferentially selecting volcanic ash <31?μm under liquid-free conditions in a two-stage process of electrostatic attraction followed by ice sintering. However, this did not accumulate more than a monolayer of ash at the ice surface. These quantitative relationships may be used to predict the timescales and characteristics of aggregation, such as aggregate size spectra, densities, and constituent particle size characteristics, when the initial size distribution and water content of a volcanic cloud are known. The presence of an irregularly shaped, millimeter-scale vacuole at the center of natural aggregates was also replicated during interaction of ash and melting ice pellets, followed by sublimation. Fine-grained rims were formed by adding moist aggregates to a dry mixture of sub-31?μm ash, which adhered by electrostatic forces and sparse liquid bridges. From this, we infer that the fine-grained outer layers of natural aggregates reflect recycled exposure of moist aggregates to regions of volcanic clouds that are relatively dry and dominated by <31?μm ash.     

Eastern Pacific spreading rate fluctuation and its relation to Pacific area volcanic episodes

Sea-floor spreading rates from four locations along the Nazca-Pacific plate boundary and one along the Juan de Fuca-Pacific plate boundary show variations over the past 2.4 m.y., with decreasing rates prior to the Jaramillo to Olduvai time interval (0.92–1.73 m.y. ago) and increasing rates since then. Other Pacific area volcanic phenomena in mid-plate and convergent-boundary settings also show minima about 1.3–1.5 m.y. ago and a maximum at present and another maximum about 5 m.y. ago: extrusion rates along the Hawaiian Ridge; volcanic episodes associated with calc-alkalic provinces of western Oregon and Central America; temporal variations in the SiO₂ content of Aleutian ash layers; and the number of deep-sea ash layers. These phenomena may fluctuate in response to changing spreading rates. During times of more rapid spreading increased shear and melting along lithospheric boundaries may occasion increased volcanic activity, whereas during times of less rapid spreading volcanic activity may be less intense.     

An automated algorithm for river ice monitoring over the Susquehanna River using the MODIS data

Reliable and prompt information on river ice condition and extent is needed to make accurate hydrological forecasts to predict ice jams breakups and issue timely flood warnings. This study presents a technique to detect and monitor river ice using observations from the MODIS instrument onboard the Terra satellite. The technique incorporates a threshold‐based decision tree image classification algorithm to process MODIS data and to determine the extent of ice. To differentiate between ice‐covered and ice‐free pixels within the riverbed, the algorithm combines observations in the visible and near‐infrared spectral bands. The developed technique presents the core of the MODIS‐based river ice mapping system, which has been developed to support National Oceanic and Atmospheric Administration NWS's operations. The system has been tested over the Susquehanna River in northeastern USA, where ice jam events leading to spring floods are a frequent occurrence. The automated algorithm generates three products: daily ice maps, weekly composite ice maps and running cloud‐free composite ice maps. The performance of the system was evaluated over nine winter seasons. The analysis of the derived products has revealed their good agreement with the aerial photography and with in situ observations‐based ice charts. The probability of ice detection determined from the comparison of the product with the high‐resolution Landsat imagery was equal to 91%. A consistent inverse relationship was found between the river discharge and the ice extent. The correlation between the discharge and the ice extent as determined from the weekly composite product reached 0.75. The developed CREST River Ice Observation System has been implemented at National Oceanic and Atmospheric Administration–Cooperative Remote Sensing Science and Technology Center as an operational Web tool allowing end users and forecasters to assess ice conditions on the river. Copyright © 2012 John Wiley & Sons, Ltd.     

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth’s volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.     

Tephrochronology of the Kamchatka–Kurile and Aleutian arcs: evidence for volcanic episodicity

Volcanic ash layers in North Pacific deep-sea sediment provide a record of episodic explosive volcanism in the Kamchatka–Kurile and Aleutian arcs over the past five million years. We counted 450 ash layers, determined layer thickness and cumulative ash thickness to quantify the flux of ash with time. We use this record to investigate the eruptive history of these arcs, test the reliability of the marine ash record, and inquire into the regional episodicity of North Pacific explosive volcanic history. Episodes of explosive volcanism occurred at approximately 0.2–0.5, 0.7–0.9, 1.5–1.7, and 2.5–2.65 Ma in the Kamchatka arc and 0.15–0.4, 1.7–1.8, 2.55–2.65, and at 3.0–3.1 Ma in the eastern Aleutian arc. These generally coeval eruptive episodes suggest that the pulses in explosive volcanism in the North Pacific enumerated here and recognized by others are regionally episodic over a wide portion of the Pacific rim and not just a response to local volcanogenic processes.     

Volcanic particle aggregation in explosive eruption columns. Part II: Numerical experiments

The goal of this paper is to determine the parameters that control the aggregation efficiency and the growth rate of volcanic particles within the eruption column. Numerical experiments are performed with the plume model ATHAM (Active Tracer High resolution Atmospheric Model). In this study we employ the parameterizations described in a companion paper (this issue). The presence of hydrometeors promotes the aggregation of ash particles, which strongly increases their fall velocities and thus their environmental impact. The tephra mass is about two orders of magnitude greater than that of hydrometeors during typical Plinian eruptions without interaction of external water. Ice is highly dominant in comparison to liquid water (> 99% by mass). This is caused by the fast column rise (> 100 m s^− 1 on average) to very cold altitudes. Most particles occur in the form of frozen aggregates with low ice content.The collection efficiency is governed by the availability of hydrometeors acting as adhesives at the particles’ surface in our study, and wet ash particles have a higher sticking capacity than icy ones. Therefore, aggregation is fastest during the eruption within the column when limited regions of liquid water exist and when particle concentrations are very high (of the order of 10⁵ cm^− 3). Increased humidity in the background atmosphere generally leads to enhanced ice formation, but shows only a weak influence on the aggregation process. First sensitivity studies showed, however, a significant increase of the liquid water fraction when considering salinity effects. The availability of water or ice at the particles' surfaces is also governed by the surface properties, the porosity and permeability of ash, which are not well established to date. Particle growth is significantly enhanced for greater differences in the sizes and fall velocities among particles, as gravitational capture becomes more efficient. Our experiments indicate a major influence of the erupted particle size distribution. First sensitivity studies show that electrostatic forces result in a significant enhancement of aggregated particles.The present exploratory study provides new insights into the sensitivity of the ash aggregation process to a number of key parameters. Our results indicate the need of further constraining particle composition, size, porosity, permeability, and surface properties at low temperatures by in situ observations in the laboratory and in the field. In addition further research on electrostatic aggregation would be desirable.     

HJ-1B/IRS热红外数据反演太湖水温的方法比较

太湖是我国典型的富营养化湖泊,水温是影响太湖藻类生长的重要环境因子之一,我国环境减灾卫星HJ-1B搭载的红外多光谱相机IRS对太湖水温动态遥感监测具有较大的性能优势.利用6景过境太湖的IRS热红外遥感影像,分别采用单通道普适性算法、辐射传输模型法和单窗算法反演太湖水温,并与实测水温和同期的TERRA/MODIS温度产品进行对比.结果表明,普适性单通道算法反演水温偏高,而辐射传输模型法和单窗算法则偏低;3种算法反演水温的均方根误差在1.001 K以内,单窗算法反演精度最高,其次是辐射传输模型法,再次为普适性单通道算法,而同期MODIS温度产品的均方根误差为1.507 K.3种算法从IRS热红外数据反演的水温直方图均呈正峰态、尖峰状态分布,反演结果能真实地反映太湖水温的空间分布特征.本研究对只有单个热红外通道的卫星传感器开展内陆水体水温遥感监测具有一定的参考意义.