The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

A method to derive two-layer cloud properties from concurrent visible, near-infrared, and infrared observations is described. It is a modification of a single-layer scheme and is applied to Spinning Enhanced Visible Infrared Imager (SEVIRI) observations and validated against coincident A-Train data, principally to evaluate the accuracy and characterize cloud top pressure (CTP) estimates. CTP values obtained from the single-layer scheme applied to multilayer clouds are significant overestimates of the upper layer value. The effect is usually larger than that on coincident IR-only retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS), and this characteristic can be traced to the use of visible wavelength observations. However, the solution cost from the optimal estimation method is found to be especially high in multilayer situations and is a strong indicator of CTP accuracy. Tighter thresholds on the solution cost select, with increasing stringency, scenes with single-layer or opaque upper layer cloud. High-cost (presumed multilayer) pixels are reprocessed with the scheme adapted to simulate a two-layer cloud and with only infrared measurements. The upper cloud is represented by the parameters of the original formulation; the additional lower cloud layer is gray and has a proxy height given by the surface temperature. Despite the simplicity of the cloud-atmosphere modeling under the upper layer, results obtained from the two-layer scheme are promising. Upper layer CTPs are of comparable accuracy to the single-layer cases, lower-layer CTPs show some useful accuracy, and upper layer optical depths correlate well with radar observations.

The development of an assimilation system for radiance data from the Atmospheric InfraRed Sounder (AIRS) is described, in particular the identification Of Cloud contamination. bias correction and the characterization of errors in the measured radiances and radiative-transfer model. The results of assimilation experiments are presented. These show that a conservative use of AIRS radiance data (in a system already extensively observed with other satellite data) results in a small, but consistent. improvement in the quality of analyses and forecasts. Larger impacts of AIRS are found in hypothetical experiments that test the use of radiances from only a single sounding instrument. In these, the use of AIRS is found to outperform the use of data either from a single Advanced Microwave Sounding Unit-A (AMSU-A) or front a single High-resolution InfraRed Sounder (HIRS). In this hypothetical context the relative forecast performance of each sensor is found to correlate with the size and vertical scale of increments caused by the assimilation of the radiances.

A method for detecting cloud contamination in radiances measured by high-spectral-resolution infrared sounders is presented. It seeks to identify clear channels within a measured spectrum, rather than the locations of completely clear spectra. Applied to simulated cloudy spectra, the scheme is able to detect clear channels with residual cloud contamination better than (i.e. less than) 0.2 K in many channels, and is thus considered sufficiently stringent for numerical weather-prediction applications. The scheme has been applied to spectra measured by the Advanced InfraRed Sounder and, whilst a quantitative validation is more difficult with real data (without true clear radiances), it is found to perform well compared with coincident imagery.

In this paper a consistent set of single-scattering properties is presented for radiative transfer calculations and remote sensing of cirrus cloud. The single-scattering properties consist of the extinction coefficient, single-scattering albedo and phase function. A randomly oriented randomized hexagonal ice aggregate is assumed to derive the extinction coefficient and single-scattering albedo. The phase function is an extension of the Henyey–Greenstein model called the “analytic” phase function, which is generated from the asymmetry parameter at non-absorbing and absorbing wavelengths. The satellite-based dual-view along track scanning radiometer (ATSR-2) instrument is utilized to test the single-scattering properties for consistency at scattering angles between about 60° and 170°, using a method of Optimal Estimation. Optimal Estimation is applied to a set of cloud parameters and radiance measurements, which are made simultaneously at the wavelengths of 0.87, 1.6, 3.7, 11.0 and 12.0μm, over cases of cirrus cloud located in the tropics and mid-latitudes. If the single-scattering properties and assumed model parameters were a perfect representation of the radiative properties of cirrus then the measurement residuals (i.e., differences between measurements and simulated measurements) would be identically equal to zero at each of the wavelengths for all scattering angles. It is found that the randomized ice aggregate combined with the analytic phase function minimizes the measurement residuals to generally well within ±1% (reflectance) and ±1K (brightness temperature) at 0.87, 11.0 and 12.0μm and to within ±3% and ±3K at 1.6 and 3.7μm, respectively. This compares to measurement residuals of about 8% and 10K if the single-scattering properties are based on the randomly oriented hexagonal ice column. It is recommended that single-scattering properties based on the randomized ice aggregate combined with the analytic phase function (or a very similar phase function) should be applied to remote sensing and radiative transfer studies of cirrus cloud.

The high resolution infrared spectrometer AIRS was launched on the NASA AQUA platform in May 2002. This paper documents briefly some of the characteristics, potential and initial experience with AIRS data in the ECMWF forecasting system. Section 1 outlines the instrument characteristics and the hoped for potential for improvements to NWP skill to be gained from high resolution measurements. Section 2 outlines the scheme adopted for detecting the presence of cloud in the data and section 3 describes the observed error characteristics of the AIRS data, especially the biases present and possible strategies for handling these. Section 4 presents results of assimilation of AIRS radiances and finally section 5 outlines areas of immediate and future research aimed at optimising the use of these exciting new data. 1. THE AIRS INSTRUMENT AIRS is an infrared spectrometer with nominal spectral resolution of around 1 cm on board the AQUA spacecraft along with an AMSU-A instrument. Measurements are made from around 3.7 to 15.5 microns with a gap in the longwave side of the 6 micron water vapour band. The ground IFOV is approximately 12x7 Km with 9 soundings per AMSU-A IFOV. This makes it comparable to the HIRS instrument apart from the spectral resolution and therefore number of channels; 19 for HIRS and 2378 for AIRS. The Metop high resolution sounder IASI will have ~8000 channels at 3-4 times the spectral resolution (~0.3 cm) but is otherwise comparable. HIRS, AIRS and IASI all have channel NeDT values from around 0.2 to 0.4 K. The rationale for flying the AIRS/IASI instruments is to obtain higher vertical resolution soundings than that obtainable from the HIRS and AMSU like radiometers. Most of this increase in resolution arises from the increased spectral sampling rather than from the somewhat narrower weighting functions obtained as a result of better spectral resolution. This is illustrated in figure 1 which shows at the top, the temperature jacobians for the AIRS (left) and HIRS (right) instruments. The jacobians for AIRS are seen to be comparable, but much more numerous (despite only 324 being shown, see section 4) than HIRS. The lower two plots in figure 1 show the averaging kernels expected from the two instruments. These are the response (in a 1Dvar retrieval) of the estimated vertical temperature for a give delta function error in the retrieval a priori profile. For the HIRS, it is clearly seen that perturbations are spread widely across the troposphere and that perhaps 2-3 separate pieces of information on the tropospheric temperature are available. The plot for AIRS shows much narrower kernels indicating significantly better resolution. Note that this simulation is somewhat optimistic in that it assumes a cloud-free scene but also pessimistic in that only the 324 channel subset of the data is used here. The hope for AIRS/IASI in NWP is that this improved vertical resolution can be successfully utilised in NWP models. Figure 1. Temperature Jacobians and averaging kernels for AIRS and HIRS

Well‐calibrated IR and visible image data sets, from satellite sensors designed to provide urgently needed information for the debate on climate change and global warming, are now available from the European Space Agency (ESA). These data sets also have application to a wide range of land use and other Earth studies.The data have been collected by Along Track Scanning Radiometer (ATSR) instruments on ERS 1 and 2 since the early 1990s. ESA will launch a further ATSR, the Advanced ATSR (AATSR),on its Envisat mission next year. It is expected that the data can also be applied in other fields and, through its synergistic use with information from other sensors, can improve calibration and reduce uncertainties in interpretation of that information.

Singh, in a recent paper, attempts to describe the effect of sea surface emissivity variations on sea surface temperature (SST) retrieval from satellite borne infrared instruments (specifically the Along Track Scanning Radiometer (ATSR)). It is based, for the most part, on an incorrect premise, draws conclusions about SST retrieval accuracy which are not supported by the necessary evaluation of atmospheric and retrieval algorithm effects, and contains erroneous calculations. The shortcomings of the paper are discussed.

AbstractTemperature sounding of the troposphere using satellite‐borne infrared radiometers is complicated by the effects of clouds on the measured radiances. If accurate products are to be obtained these effects must first be detected and, if possible, corrections must be made for them in the retrieval procedures. This is normally done by converting the measured radiances to the ‘clear‐column’ values which would be observed from the same atmospheric profile in the absence of cloud—a process known as ‘cloud‐clearing’.In this paper a review of cloud‐clearing methods is presented. Then a new approach to cloud‐clearing, based on the principles of optimal estimation, is developed and applied to data from HIRS (the High‐resolution Infrared Radiation Sounder) on the TIROS‐N/NOAA satellite series.Preliminary estimates of clear‐column radiances and their expected errors are obtained at each HIRS spot by one of a number of methods, depending on the cloud characteristics. the properties of horizontal consistency expected in the clear‐column radiance field are then employed to improve the initial estimates using a sequential estimation procedure. This scheme is intended for implementation in the Local Area Sounding System of the Meteorological Office, which provides satellite soundings of high horizontal resolution for use in operational weather forecasting. Details of the new scheme, and of the old scheme which it replaces, are given. the improvements in clear‐column radiances are demonstrated by comparing the products of the old and new schemes with clear‐column radiances derived from coincident data of AVHRR (the Advanced Very High Resolution Radiometer).

The metabolic response of a 190-kg polar bear was tested at four different walking speeds within a respiration chamber mounted on a treadmill. Regressions of deep body temperature and oxygen consumption as a function of walking speed were determined. Equilibrium deep body temperature increased exponentially with speed of locomotion and indicated a relative inability to dissipate metabolic heat at high walking speeds. Metabolic rate, as measured by weight-specific oxygen consumption, was also best fit by a curvilinear equation and was twice that predicted by a general equation for quadruped locomotion. The apparent inefficiency of locomotion in polar bears suggests a compromise between thermoregulation, hunting strategies, and economy of transport.

Body temperatures and oxygen consumption of three sub-adult polar bears (Ursus maritimus) during treadmill exercise are presented. Comparisons are also made with results from prior studies of polar bear locomotion. The increase in body temperature and the metabolic cost were unexpectedly high, particularly in young animals. An equation describing the cost of locomotion versus body mass shows a negative, and apparently linear relationship. A significant correlation between body temperature and oxygen consumption may permit the use of body temperature telemetry to estimate activity metabolism of free-ranging polar bears.

The results of serveral studies imply that estrogen can act upon the central nervous system via a protein synthetic step. Our objective was to determine if the intrahypothalamic (preoptic area, POA) injection of cycloheximide (CHX), an inhibitor of protein synthesis, at 17.00 h on diestrus II of the 4-day cycle altered lordotic behavior and (or) ovulation in the intact rat (sexual receptivity to males normally begins on the evening of proestrus as herein defined; ovulation occurs on estrus of the cycle). CHX-treated females were tested for lordotic behavior at 23.00 h on proestrus, then killed at 17.00 h on the following day. None of the CHX-POA rats were receptive to the males and 90% of these rats did not ovulate. Thus, CHX significantly suppressed sex behavior and ovulation in the cyclic rat.

The results of serveral studies imply that estrogen can act upon the central nervous system via a protein synthetic step. Our objective was to determine if the intrahypothalamic (preoptic area, POA) injection of cycloheximide (CHX), an inhibitor of protein synthesis, at 17.00 h on diestrus II of the 4-day cycle altered lordotic behavior and (or) ovulation in the intact rat (sexual receptivity to males normally begins on the evening of proestrus as herein defined; ovulation occurs on estrus of the cycle). CHX-treated females were tested for lordotic behavior at 23.00 h on proestrus, then killed at 17.00 h on the following day. None of the CHX-POA rats were receptive to the males and 90% of these rats did not ovulate. Thus, CHX significantly suppressed sex behavior and ovulation in the cyclic rat.

Evidence is emerging that global supplies of rock phosphate used for production of phosphorus (P) fertilizers are declining. The term peak phosphorus has been applied to the situation that phosphorus, the first non-renewable, non-substitutable life-supporting element, will become scarce in the foreseeable future. As a result, management of phosphorus on the land and the prevention of nutrient pollution in aquatic ecosystems are aligned by the common goal of keeping phosphorus on the land for crops. The objective of the study was to investigate the confluence of intensive management of phosphorus in agriculture with the goals of securing food productivity and water pollution prevention as symbolized by Lake Winnipeg, visibly the most eutrophic Great Lake in the world. The method was an action research approach designed to disseminate and gather information on existing and future challenges related to P management and social process of change. Based upon review of science, analysis of the basin and dialogue with 40 stakeholders, action recommendations for best management practices, P recycling and stewardship were formulated. The results demonstrate the urgency and importance of establishing an integrated watershed management approach including all aspects of Lake Winnipeg-related water security, phosphorus recycling, traditional knowledge and governance.