Retrieval of land and sea surface temperature using NOAA-11 AVHRR· data in north-eastern Brazil

The split-window method is investigated and a simple airborne atmospheric correction model for thermal data is proposed. Analysis shows that the atmospheric transmittance has a quadratic behaviour with the water vapour content in the first few kilometres of a wet atmosphere. The effect of the emissivity is evaluated for the retrieval of surface temperature using data from NOAA-11 AVHRR channels 4 and 5 for two extreme atmospheres. The results indicate that a spectral emissivity variation (Δε) in channels 4 and 5 of ±0.01 is not as important for a wet atmosphere as for a dry atmosphere. The split-window algorithm developed in this work has its parameters dependent on the atmospheric state and the values of these parameters are determined by using radiosonde profiles. Data from eighty-five radiosondes have been used to determine and check the local seasonal equatorial split-window parameters. The results of surface temperature retrieval show that the local seasonal equatorial and daily split-window parameters (given by daily radiosonde profiles) for NOAA-11 AVHRR data exhibit good agreement between their surface temperature results and the results of in situ measurements for two days. Comparisons with in situ measurements show that the maximum difference from retrieving a vegetated surface temperature using AVHRR data is less than 1.0°C in a wet atmosphere. Although the seasonal parameters have demonstrated a good performance when applied for two particular days, it does not indicate that they can be used successfully for other times when the atmospheric state differs from the average seasonal profile determined in this work. Evidence of this fact is shown through the variation of water vapour amount in the eighty-five radiosonde atmospheric profiles that have been analysed. This variation presents a wide range in water vapour from 2.8g cm^-2, to 4.92g cm^-2, which can significantly modify the retrieval of surface temperature using remote infrared sensors. Discussion of this problem is given in this paper.     

Observations of volcanic ash clouds in the 10-12 μm window using AVHRR/2 data

Abstract

Volcanic aerosols are always present in the atmosphere, but because of the nature of volcanic activity their abundance varies greatly with time. The problem of detecting and monitoring volcanic ash clouds using radiance measurements from the AVHRR/2 (Advanced Very High Resolution Radiometer) instrument is discussed and some results are presented for the Galunggung eruptions of July 1982. It is shown that during the first few hours of an explosive eruption AVHRR/2 thermal channel measurements can be used to detect and discriminate volcanic clouds. Once the eruption cloud has spread and thinned out however, the problem of detection is difficult because of the similarity between dispersed volcanic cloud and semi-transparent cirrus. In these cases, if the volcanic cloud consists of liquid H₂SO₄ droplets, then it is possible to discriminate them from water/ice clouds because of the reverse absorption effect in channel-4 and channel-5. Some evidence is presented showing this effect. It is proposed that the temperature difference image be used operationally to warn of the presence of volcanic clouds.     

An example of the use of synthetic 3.9 μm GOES-12 imagery for two-moment microphysical evaluation

In preparation for the launch of the next generation of geostationary satellites, considerable effort has been placed on developing new products and algorithms for operational purposes. In addition to satellite-based products and algorithms, satellite imagery can be used to evaluate numerical weather prediction models. Important first steps have already been undertaken to produce synthetic satellite imagery from numerical model output. By comparing synthetic imagery with observed imagery, model performance can be evaluated with a relatively new metric.

In this paper, synthetic Geostationary Operational Environmental Satellite (GOES)-12 imagery was used to improve the two-moment prediction of pristine ice in the RAMS (Regional Atmospheric Modeling System) mesoscale model. A thunderstorm event that occurred on 27 June 2005 over the central plains of the USA was chosen for study. Synthetic GOES-12 3.9 μm imagery of RAMS output was compared with observed GOES-12 3.9 μm imagery. A discrepancy between brightness temperatures of two anvils of thunderstorms led to an improvement in the prediction of pristine ice number concentrations. After the model was re-run, subsequent synthetic GOES-12 3.9 μm imagery of one anvil exhibited an improvement compared with observed imagery. Brightness temperatures of the second anvil became too warm, an issue that may be related to model-specified cloud condensation nuclei (CCN) concentrations. This example highlights the potential importance of using synthetic imagery to evaluate numerical weather prediction models.     

Mean seasonal cycle and evolution of the sea surface temperature from satellite and in situ data in the English Channel for the period 1986–2006

A night-time series of sea surface temperature (SST) of the advanced very high-resolution radiometer (AVHRR) sensors provided by the AVHRR/Pathfinder was analysed over the period 1986–2006 in the English Channel. The studied area is characterized by a strong influence of the bathymetry on the mixing of the water column, mostly through the action of the tide and waves, leading to regional patterns in the SST fields. Another specific aspect of the area is the relatively large number of in situ measurements available from coastal stations. The remotely sensed SST data with fine spatial resolution and high-frequency measurements made at coastal stations have been analysed using a common model. The long-term evolution of SST has been defined in this study through a linear trend while the seasonal evolution has been described through two harmonic functions. The daily satellite SST fields have been estimated over the period 1986–2006 by applying the kriging method to the anomalies calculated from the model. These interpolated temperatures were compared with in situ data, including many coastal stations unreachable at the sensor resolution. To use those coastal stations for comparison and to complement the satellite-derived data set, we defined transfer functions established from fine analysis of the in situ gradients along cross shore transects. The study showed the existence of a long-term warming and that this trend was not homogeneous in the area studied. The central part of the English Channel and the Western part of Brittany show an increase in temperature of about 0.6°C and the Northern part of the Irish and Baltic Sea, included in the studied area, show a maximum increase in the temperature of 1.6°C over the period 1986–2006.     

The effect of orbit drift on the calibration of the 3.7 µm channel of the AVHRR onboard NOAA-14 and its impact on night-time sea surface temperature retrievals

The orbit drift of National Oceanic & Atmospheric Administration (NOAA)-14 towards the terminator has caused the deterioration of the radiometric calibration of the Advanced Very High Resolution Radiometer (AVHRR) 3.7?µm channel at night. This deterioration is a result of solar contamination of the radiometric calibration system when the sun strikes the instrument from the spacecraft horizon. The long-term trend and seasonal variation of the contamination are analysed in this study based on trending data from 1995 to 2000. The calibration bias is evaluated and its effect on the sea surface temperature retrievals is quantified. The solar contamination in late 2000 affected as much as 25% of an orbit of data, compared to an average of 7% in 1995. The NOAA/NESDIS operational calibration algorithm partially corrects for the bias but residual effects can still contribute bias on the order of 0.5?K in scene brightness temperature.     

Preliminary measurements of leaf spectral reflectance in the 8-14 μm region

Previous broad band measurements of the spectral reflectance of leaves indicate variations in spectral emissivity that, although small, might be detected with current airborne thermal infrared imaging systems. Preliminary high spectral resolution measurements of the spectral reflectance of leaves of four different species reported here show a different spectral response for each species. These data suggest that species discrimination using remote sensing data in the thermal infrared may be feasible, and raise the possibility that other factors that might affect leaf surface composition and spectral response, such as metal stress, might also be detected     

Comparison of AMSR‐E and TMI sea surface temperature with Argo near‐surface temperature over the Indian Ocean

Sea surface temperature (SST) measurements from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) are compared with near‐surface temperature (foundation SST) in situ measurements obtained from Argo floats over the Indian Ocean. Spatial variation was compared for 2002–2006 and 11 floats were used for temporal variation collocated observations. The results show that TMI and AMSR‐E SST measurements are slightly overestimated during the pre‐ and post‐monsoon seasons and underestimated during the monsoon season. Statistical analysis shows that the SST from the AMSR‐E is better correlated with the Argo foundation SST compared to the TMI. The standard deviation (SD) and root mean square error (RMSE) for AMSR‐E SST are 0.58°C and 0.35°C, respectively, over the Equatorial Indian Ocean (EIO). The corresponding values for the TMI are 0.66°C and 0.47°C. Over the Arabian Sea the SD values are slightly higher compared to the EIO values, whereas RMSE values are less for both TMI and AMSR‐E SST. These retrieval accuracies are above the expected retrieval accuracy. The seasonal average spatial distribution of AMSR‐E SST shows a better match with the Argo foundation SST compared to TMI SST distributions. The robustness of the good spatial match during the monsoon season may be attributed to strong winds.     

The estimation of atmospheric corrections to one-channel (11 μ m) data from the AVHRR; simulation using AVHRR/ 2

It has been established that the sea-surface brightness temperatures Tb₄ in the 11 μ m channel and T_b4in the 12 μ m channel of the Advanced Very High Resolution Radiometer (AVHRR/ 2) are linearly related to a good degree of accuracy, i.e. T_b5= α+ β T_b4 Using AVHRR/ 2 data for various dates and from different parts of the world's oceans, the parameters a and 0 have been determined. The above relation may then be used for simulating T_b5 for those cases for which only Tb4 is available (e.g. for the AVHRR on TIROS-N, NOAA-6, NOAA-8, etc.). The brightness temperature TM and pseudo-brightness temperature T_b5 then enable one to use the split-window technique for estimating atmospherically-corrected sea-surface temperatures (SSTs) from the 11μ m channel data alone. Such an atmospheric correction technique should be a possibility because the 11μ m channel of the AVHRR on the various satellites in question are almost identical

This technique has been used with two split-window algorithms for correcting the data from the 11μ m channel of the AVHRR instrument on the TIROS-N satellite obtained off south-western Portugal. One of the algorithms gives ‘ skin’ temperatures and the other algorithm gives bulk temperatures. The resulting SSTs for twelve dates from 15 June 1979 to 14 June 1980 have been compared with sea-surface (skin) temperatures which were obtained with airborne radiometer data obtained on the same dates.     

Simultaneous non‐linear retrieval of atmospheric profiles and surface skin temperature from MODIS infrared radiances in Taiwan Strait

A non‐linear iterative physical algorithm that simultaneously retrieves atmospheric temperature, water vapour distribution and surface skin temperature from Moderate Resolution Imaging Spectroradiometer (MODIS) longwave infrared radiances is presented. The retrieval algorithm uses clear‐sky radiances measured by MODIS in Taiwan Strait for both day and night, and shows that it is capable of retrieving medium‐scale atmospheric temperature and water vapour. Sea surface temperature is retrieved with an accuracy similar to that achieved by MOD07 products. Evaluation of retrieval total precipitable water vapour (TPW) is performed by comparisons with retrievals from MOD07 products and data from a ground‐based sunphotometer. These show that MODIS retrieval of TPW, in general, agrees with other sounder retrievals of TPW. The total totals index (TTI) distribution retrieved from MODIS data is similar to that from MOD07 products.     

The decorrelation time of microwave radar echoes from the sea surface†

The case is considered of a CW microwave radar looking at the sea surface at moderate angles of incidence. This is treated using the ‘facet’ concept, in which the sea surface is considered as being covered by spatially uncorrelated facets, each a small number of Bragg wavelengths across and being transported by the particle velocities in the longer sea waves. The facets are considered to have an unknown decorrelation time. In two cases simplifications allow approximate numerical values for the coherent decorrelation time of the radar return to be calculated. These are compared with measured bandwidths and decorrelation times reported in the literature. These agree adequately with the theory and indicate that the facet decorrelation time is long. However, some properly thought-out measurements of coherent decorrelation time are badly needed.     

Tropical lake surface temperatures from locally received NOAA-11 AVHRR d— comparison with in situ measurements

The estimation of tropical lake surface temperature from locally received NOAA AVHRR data was investigated. The applicability of published sea surface temperature algorithms in estimating the tropical lake surface temperature of Lake Malawi was confirmed; the most accurate algorithm being that of McClain et al( 1985) with a root mean square deviation of 0-45 K. Other published algorithms tested required localised bias correction. Newly derived algorithms showed the advantage of the triple window approach, with a correlation coefficient of 0-92 between the estimated and measured temperatures.     

The continuous measurement of the temperature of the upper layer of the sea—a practical approach

A new instrument for the continuous direct measurement of temperature in the upper layer of the sea (within the first millimetre) is described. The technique makes use of a miniature thermistor in a surface-floating hydrophobic support. A wide range of possible applications in fields such as oceanography and climatology exist, and the method also provides a promising alternative to the conventional ‘bottle and reversing thermometers’ or ‘bucket’ methods currently used to provide in situ data for comparison with remote-sensing measurements.     

On the Formalization of the Modal μ-Calculus in the Calculus of Inductive Constructions

We present a natural deduction proof system for the propositional modal μ-calculus and its formalization in the calculus of inductive constructions. We address several problematic issues, such as the use of higher-order abstract syntax in inductive sets in the presence of recursive constructors, and the formalization of modal (sequent-style) rules and of context sensitive grammars. The formalization can be used in the system Coq, providing an experimental computer-aided proof environment for the interactive development of error-free proofs in the modal μ-calculus. The techniques we adopt can be readily ported to other languages and proof systems featuring similar problematic issues.     

A study of the seasonal dynamics of grassland growth rates in Inner Mongolia based on AVHRR data and a light‐use efficiency model

Growth rate data for different pastures could provide important reference data for developing rotation grazing plans, for hay production, and for forage replenishment. Based on AVHRR NDVI data and a light‐use efficiency (LUE) model, we estimated absorbed photosynthetically active radiation and LUE (ε) by integrating air and soil temperature, precipitation and total solar radiation time series data from 1986 to 1999, and calculated the absolute growth rate (AGR) and cumulative absolute growth rate (CAGR) of aboveground biomass in each growing season in China's Inner Mongolia region. AGR and CAGR estimated by the LUE model were validated using monthly growth data obtained for the vegetation in desert steppe, typical steppe, and meadow steppe ecosystems from 1986 to 1995. The LUE model provided sufficiently good simulation accuracy that its use should permit improved livestock feed management in the study area. From 1986 to 1999, average CAGR of steppe vegetation during the growing season increased quickly in June and July, reached a maximum in July and August, and declined in September. In 1999, AGR reflected the pattern of seasonal vegetation dynamics during the growing season.     

Time synchronization of the data of a training sample and the data of recognized objects in classification problems in the course of interpretation of space images of the Earth’s surface

The classification problem is considered under the conditions when there is temporal non-coordination in the data of a training sample and the data of the recognized object. A modification of the conventional classification scheme is proposed that presumes that an additional stage is involved, whose goal is to temporally match the data of the training sample to the current observation moment. The feature vectors are recalculated at the current observation moment by calculating their conditional expectations connecting the realizations of feature vectors at the time instants taking place in the training sample with their values for the current observation moment. By the example of processing and analyzing space images, it is demonstrated that the use in the course of classification of the proposed procedure of synchronizing the data of the training sample and the recognized object can substantially improve the reliability of classification results.     

Review Article. The sea surface thermal boundary layer and its relevance to the measurement of sea surface temperature by airborne and spaceborne radiometers†

This review examines the importance of the thermal boundary layer of the ocean to the measurement of sea surface temperature (SST) by satcllitc-bornc infrared (IR) radiometers. Attention is focused on the difference between the temperature of the top 01mm which is observed by radiometers, and the temperature found at depths between a few centimetres and one metre, which is that recorded as bulk SST by ship measurement techniques. The question addressed is whether corrections for this effect are necessary in the light of the accuracy of IR radiometers, and the demands made by the application of SST data.

A brief preview is made of the accuracy of the best presently available sensor for space observations of SST, the AVHRR, the associated atmospheric corrections and other sources of error. Current knowledge of the thermal boundary layer of the ocean is then presented in a thorough review of the scientific literature. The evidence of field observations suggests that the surface skin can be typically 0.1-0.5 degK cooler than the water a few centimetres deeper. Theoretical models of the effect are available and there is some understanding of the dependence of spatial and temporal variability of the skin effect on other environmental parameters, but there is a need for more systematic observation before prediction of the effect can confidently be achieved.

The existing and potential applications of SST in oceanography and meteorology are summarized, with emphasis on the required accuracy, in certain areas 0 2 degK being desirable. Following a survey of the likely capabilities of the next generation of spaceborne IR radiometers (notably the ATSR) it is concluded that while the inaccuracies of present systems tend to be greater than the skin effect, if future systems meet their specification then the skin temperature deviation will become a significant factor in the calibration procedure. In the light of this, the review concludes with some remarks regarding the value of further studies of the thermal skin effect.     

Tracking the calibration stability and consistency of the 3.7, 11.0 and 12.0 μm channels of the NOAA-KLM AVHRR with MODIS

The NOAA-KLM satellites (NOAA-15 to 18) are the current polar-orbiting operational environmental satellites (POES) that carry the Advanced Very High Resolution Radiometer (AVHRR). This study examines the calibration stability and consistency of all three infrared channels (3.7, 11.0 and 12.0 μm) of AVHRR onboard NOAA-15 to 18. The short-term stability is examined from variations of the scan-by-scan gain response, while the long-term stability and calibration consistency are examined by tracking the trends of gain response and measured scene brightness temperatures. The relative differences of observed scene brightness temperatures among NOAA-15 to 18 AVHRR are determined using MODIS as a transfer radiometer based on observations from simultaneous nadir overpasses (SNO). Results show that variations of the scan-to-scan gain responses are within 0.10% under normal operational conditions, while long-term gain changes over six years from 2001 to 2006 vary from 2 to 4% depending on channel. Long-term trending results show that total six-year drifts in observed brightness temperature from NOAA-15 to 18 AVHRR are less than 0.5 K for a given scene temperature in the 250 to 270 K range for the 3.7, 11.0 and 12.0 μm channels, respectively. The calibration consistency is examined for a scene temperature range of 220 to 290 K. The temperature biases among NOAA-16 to 18 AVHRR are within ±0.5 K for the 11.0 and 12.0 μm channels. For NOAA-15 AVHRR, biases of –2.0 K at 11.0 μm and –1.5 K at 12.0 μm are found in comparison with others at the low end of the temperature range. For the 3.7 μm channel, relative biases up to a few degrees among NOAA-15 to 18 could be found at low brightness temperatures.     

On the use of observers in finite-time optimal regulator problems†

When a compatible dynamical observer is employod to construct the estimates of the inaccessible states of the system, an increase in the value of the performance index of a finite-time optimal regulator is in general encountered. An expression for this increase in the value is derived. The conditions for zero increase in the cost are discussed.     

A simple equation for determining sea surface emissivity in the 3–15 µm region

The high level of accuracy demanded for the sea surface temperature retrieval from infrared data requires an accurate determination of directional sea surface emissivity (SSE). Previous models have permitted calculating SSEs using a physical characterization of sea surface roughness and emission. However, these result in complex equations, and make an operational application difficult. This paper presents a simple SSE algorithm based on a parametrization of one of these models, which was selected as a reference since it reproduces SSE experimental data to a reasonable level of accuracy. The parametrization provides the SSE variation with observation angle and wind speed from a given nadir SSE value, using only one channel-dependent coefficient. This coefficient and the nadir SSE value are given for the IR bands of several current satellite sensors: ENVISAT‐AATSR, EOSTerra/Aqua‐MODIS, NOAA17‐AVHRR and MSG‐SEVIRI. The average standard error of the SSE estimate using the proposed equation is±0.0009.