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The standard approach for assimilating satellite radiance observations is to interpolate all vertical levels of the background state and analysis increment to the same horizontal location for input to the radiative transfer model. This can add significant error for observations with large zenith angle. The impact of accounting for the true slanted satellite-viewing geometry was tested by modifying the horizontal interpolation routines in Environment and Climate Change Canada’s Global Deterministic Weather Prediction System. Consequently, model variables are interpolated to a different horizontal position at each model level, for either just the innovation or both the innovation and increment calculation. When this slant-path operator is used for simulation of radiances, reductions in innovation standard deviation, up to 4.5%, for upper-tropospheric and stratospheric temperature and humidity channels of ATMS, AMSU-A, MHS, and CrIS instruments have similar magnitudes as reported in previous studies. In data assimilation experiments, statistically significant reductions in innovation standard deviation (up to 0.3%) for global GPSRO observations are obtained, due to an improved background state. Verification of short- and medium-range forecasts against ERA5, and our own analyses over the region poleward of 60°S show statistically significant reductions of error standard deviation by 2%–3% for wind and temperature in the upper troposphere and lower stratosphere. These positive impacts are mostly due to performing slant-path interpolation on the background state, while also using slant path on the analysis increment has little additional impact. This is expected since the analysis increment in this global configuration has lower spatial resolution, with grid spacing comparable with the maximum horizontal position error from not using the slant-path operator.

A new ensemble-based land surface data assimilation (DA) system is coupled with the atmospheric four-dimensional ensemble-variational data assimilation (4D-EnVar) system with the goal of improving the analyses within Environment and Climate Change Canada’s Global Deterministic Prediction System. Since 2001, the sequential assimilation of surface variables is used to generate the initial conditions to launch the Global Environmental Multiscale (GEM) coupled forecast model. The work presented here is to replace the sequential DA with an independent surface DA system, the Canadian Land Data Assimilation System (CaLDAS) assimilating screen-level observations, and to compare assimilation experiments with CaLDAS run in uncoupled and weakly coupled modes. In the uncoupled mode, CaLDAS is used to initialize the forecast without interacting with the 4D-EnVar system. In the coupled mode, the analyses generated from CaLDAS and 4D-EnVar are used to initialize the forecast model. The analyses and forecasts from uncoupled and coupled runs are evaluated against surface and radiosonde observations over different subdomains to conclude the impact of coupling CaLDAS with 4D-EnVar. Results indicate a statistically significant reduction in bias and standard deviation at the surface for screen-level temperature and dewpoint temperature on the order of 0.1 K, and in the lower troposphere between 1000 and 500 hPa on the order of 0.1 dam for geopotential height and 0.1 K for air temperature and dewpoint depression in the coupled DA runs. The positive impact persists up to 5 days over some subdomains. It is concluded that the coupled DA approach generally performs better than the uncoupled version.

Continuous observation of polar regions from space remains an important unsolved technical challenge of great interest for the international meteorological community. This capacity would allow achieving global continuous coverage once combined with the geostationary (GEO) satellite network. From a practical point of view, continuous coverage of polar regions with a small number of spacecraft can be obtained from a constellation of satellites either in highly elliptical orbits (HEO) or in medium Earth orbits (MEO). The study compares HEO and MEO satellite constellations for their capacity to provide continuous imaging of polar regions as function of the viewing zenith angle (VZA) and evaluates the corresponding latitude limits that ensure sufficient overlap with GEO imagery. Earlier studies assumed the latitude boundary of 60° and the VZA range 70°–85° depending on the space mission focus: meteorological purposes or communications. From the detailed analysis of meteorological retrieval requirements, this study suggests that the overlap of the GEO and polar observing systems (HEO or MEO) should occur down to the latitude band 45°–50° with a maximum VZA ranging between 60° and 64°. This coverage requirement can be met with two sets of three-satellite HEO constellations (one for each polar area) or a six-satellite MEO constellation. The 12-h Molniya and 14-, 15-, and 16-h HEO systems have been analyzed and determined to meet these revised requirements. The study demonstrates that the six-satellite 24-h MEO system can provide a suitable solution, which is also beneficial from the point of view of ionizing radiation and image acquisition geometry. Among the HEO systems, the 16-h HEO has some advantages relative to other HEO systems from the point of view of spatial coverage and space radiation.

AIM-North is a proposed satellite mission that would provide observations of unprecedented frequency and density for monitoring northern greenhouse gases (GHGs), air quality (AQ) and vegeta...

The study reports results of analysis related to minimization of the total ionizing dose (TID) for the Multiple Apogee Highly Elliptical Orbit with periods 14 h, 15 h and 16 h introduced earlier for continuous observation of the Earth’s polar regions. The modeling of space environment has been conducted with use of the European Space Agency’s SPENVIS tool based on the AE8/AP8 radiation models. Originally, the set of orbital parameters has been derived through the optimization process that included among other factors criteria for the apogee height limit and minimization of the radiation dose caused by trapped protons. By relaxing the apogee altitude limit, this study found the total ionizing dose TID can be significantly reduced for 15-h and 16-h orbits, while the originally proposed 14-h orbit is already at the minimum of radiation dose. For 15-h and 16-h orbits this converts into reduction of the thickness of aluminum shielding by factor 1.24–1.28 or an equivalent increase in the mission lifetime by up to 8.1 years. For example, an increase in apogee altitude to 49,620 km for 16-h orbit (eccentricity e = 0.74) in comparison to the originally proposed 16-h orbit (altitude equal to 43,500 km, e = 0.55) reduces the TID so that the shielding thickness decreases to 3.53 mm, instead of 4.35 mm of aluminum slab for the same 15-year duration of mission. Decrease of the TID is achieved due to significant reduction of ionizing radiation from the trapped electrons through the better placing of the orbit trajectory in the slot area, but at the expense of slight increase of ionizing radiation from the trapped protons and increase in apogee altitude to 46,640 km and 49,620 km for 15-h and 16-h orbit, correspondingly.

Slant satellite-viewing geometry is investigated for the simulation and assimilation of radiances in Environment Canada’s weather forecast system. The standard approach is to extract from a short-term forecast (trial field) a one-dimensional vertical profile, located at the ground footprint of the observation location, to compute the model equivalent of the observation. Since in general, the lines of sight are not vertical, the observation operator can be improved by interpolating the trial field to the slant path. The interpolation relies on the estimation of horizontal gradients of atmospheric variables, extracted at each altitude layer, and representative of a neighborhood of approximately 100 km. Using these slant profiles of the trial fields yields significant improvements in the simulation and assimilation of radiance observations. The impact of this modification in assimilation and forecasts is evaluated over two periods of two months. Both short-term and long-term effects are found, obtained not only from the more accurate interpolation of the trial fields, but also from a revision of the observation error suggested by the lower observation minus trial field difference statistics. The error standard deviation of the geopotential height shows, in the upper troposphere and lower stratosphere, in 12–48-h forecasts, up to 10% reduction in the zonal value at higher latitudes, and 1%–2% reduction in the global value. Given these improved statistics, a revision of the radiance error statistics was explored. Applying these revised statistics suggests that the impact of a slant operator extends into longer range.

A posteriori consistency diagnostics have been used in recent years to estimate correlated observation error. These diagnostics provide an estimate of what the observation error covariances should be and could, in turn, be introduced in the assimilation to improve the statistical consistency between the error statistics used in the assimilation and those obtained from observation departures with respect to the background and the analysis. To estimate the observation error covariances, it is often assumed that the background error statistics are optimal, an assumption that is open to criticism. The consequence is that if the background error covariances are in error, then the estimated observation error statistics will adjust accordingly to fit the innovation error covariances. In this paper, the RTTOV radiative transfer model is used as the observation operator. Using controlled experiments, the background error is considered fixed, and it is shown that the iterative procedure to estimate the observation error may require more than one iteration. It is also shown that the underlying matrix equation being solved can be factorized, and the exact solution can be obtained. If the true background error covariances are used in the assimilation, the estimated observation error covariances are then obtained by subtracting the background error covariances from those of the innovations. This can be applied to the full set of assimilated observations. Using the Environment Canada assimilation system, the results for several types of observations indicate that the background error estimation would deserve additional attention.

A fully coupled atmosphere–ocean–ice model has been used to produce global weather forecasts at Environment and Climate Change Canada (ECCC) since November 2017. Currently, the system relies on four uncoupled data assimilation (DA) components for initializing the fully coupled global atmosphere–ocean–ice forecast model: atmosphere, ocean, sea ice and sea surface temperature (SST). The goal of the present study is to implement a weakly coupled data assimilation (WCDA) between the atmosphere and ocean components and evaluate its performance against uncoupled DA. The WCDA system uses coupled atmosphere–ocean–ice short-term forecasts as background states for the atmospheric and the ocean DA components that independently compute atmospheric and ocean analyses. This system leads to better agreement between the coupled atmosphere–ocean analyses and the coupled atmosphere–ocean–ice forecasts than between the uncoupled analyses and the coupled forecasts. The use of WCDA improves the atmospheric forecast score near the surface, but a slight increase in the atmospheric temperature bias is observed. A small positive impact from using the short-term SST forecast on the satellite radiance observation-minus-forecast statistics is noted. Ocean temperature and salinity forecasts are also improved near the surface. The next steps toward stronger DA coupling are highlighted.

A fully coupled atmosphere-ocean-ice model has been used to produce global weather forecasts at Environment and Climate Change Canada (ECCC) since November 2017. Currently, the system relies on four uncoupled data assimilation (DA) components for initializing the fully coupled global atmosphere-ocean-ice forecast model: atmosphere, ocean, sea ice and sea surface temperature (SST). The goal of the present study is to implement a weakly coupled data assimilation (WCDA) between the atmosphere and the ocean components and evaluate its performance against uncoupled DA. The WCDA system uses coupled atmosphere-ocean-ice short-term forecasts as background states for the atmospheric and the ocean DA components that independently compute atmospheric and ocean analyses. This system leads to better agreement between the coupled atmosphere-ocean analyses and the coupled atmosphere-ocean-ice forecasts than between the uncoupled analyses and the coupled forecasts. The use of WCDA improves the atmospheric forecast score near the surface, but a slight increase in the atmospheric temperature bias is observed. A small positive impact from using the short-term SST forecast on the satellite radiance Observation-minus-Forecast statistics is noted. Ocean temperature and salinity forecasts are also improved near the surface. Next steps toward stronger DA coupling are highlighted.

An established radiative transfer model (RTM) is adapted for simulating all-sky infrared radiance spectra from the Canadian Global Environmental Multiscale (GEM) model in order to validate its forecasts at the radiance level against Atmospheric InfraRed Sounder (AIRS) observations. Synthetic spectra are generated for two months from short-term (3-9 hr) GEM forecasts. The RTM uses a monthly climatological land surface emissivity/reflectivity atlas. An updated ice particle optical property library was introduced for cloudy radiance calculations. Forward model brightness temperature (BT) biases are assessed to be of the order of ∼1 K for both clear-sky and overcast conditions. To quantify GEM forecast meteorological variables biases, spectral sensitivity kernels are generated and used to attribute radiance biases to surface and atmospheric temperatures, atmospheric humidity and clouds biases. The kernel method, supplemented with retrieved profiles based on AIRS observations in collocation with a microwave sounder, achieves good closure in explaining clear-sky radiance biases, which are attributed mostly to surface temperature and upper-tropospheric water vapor biases. Cloudy-sky radiance biases are dominated by cloud-induced radiance biases. Prominent GEM biases are identified as: 1) too low surface temperature over land, causing about -5 K bias in the atmospheric window region; 2) too high upper tropospheric water vapor, inducing about -3 K bias in the water vapor absorption band; 3) too few high clouds in the convective regions, generating about +10 K bias in window band and about +6 K bias in the water vapor band. This article is protected by copyright. All rights reserved.

This study highlights recent progress at the Canadian Meteorological Centre in the assimilation of Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) radiance observations that are sensitive to land surfaces. The assimilation is carried out using the Canadian global ensemble–variational system. That system benefits from flow-dependent background-error statistics that include covariances between surface skin temperature and atmospheric variables. Up to 142 channels from both AIRS and IASI are assimilated. A detailed database of spectral surface emissivity is used. Forecasts are evaluated against ERA-Interim analyses, own-cycle analyses, and radiosonde observations. A conservative approach is taken, with restrictive conditions on topography and surface emissivity. From 2-month assimilation experiments, a significant positive impact is obtained in the Northern Hemisphere extratropics beyond day 2 from the surface to the upper troposphere. The impact is mixed in other regions, depending on level or forecast lead time. Causes for these mixed results are examined in view of future experiments and eventual operational implementation.

A novel type of multiple-apogee highly elliptical orbits termed as MAP HEO with a period of rotation between 14 h and 15 h is introduced. These orbits are designed to achieve continuous geostationary (GEO)-like imaging of the polar regions in an optimum way. The combination of GEO and HEO satellites would then offer continuous monitoring of weather from space at any point of the globe. This capacity would represent a breakthrough for short- and long-term weather forecasting and narrowing uncertainties in the knowledge of the Earth’s climate through better sampling and more accurate characterization of the diurnal cycle. MAP HEO systems can be launched at critical inclination and are characterized by a local minimum of ionizing radiation. These features simplify the process of orbit maintenance, reduce radiation shielding requirements, and favor a longer lifetime of the mission. Unlike previously considered HEO systems implemented for communications, such as 12-h Molniya and 24-h Sirius radio systems, a MAP HEO constellation achieves a uniform geometrical sampling, which reduces view angle dependent biases. These observational conditions with complete coverage of the diurnal cycle, diverse range of solar illumination, and viewing observational conditions are beneficial for high-latitude meteorological and climate applications, such as the retrieval of Essential Climate Variables (ECV).

A major set of changes was made to the Environment Canada global deterministic prediction system during the fall of 2014, including the replacement of four-dimensional variational data assimilation (4DVar) by four-dimensional ensemble–variational data assimilation (4DEnVar). The new system provides improved forecast accuracy relative to the previous system, based on results from two sets of two-month data assimilation and forecast experiments. The improvements are largest at shorter lead times, but significant improvements are maintained in the 120-h forecasts for most regions and vertical levels. The improvements result from the combined impact of numerous changes, in addition to the use of 4DEnVar. These include an improved treatment of radiosonde and aircraft observations, an improved radiance bias correction procedure, the assimilation of ground-based GPS data, a doubling of the number of assimilated channels from hyperspectral infrared sounders, and an improved approach for initializing model forecasts. Because of the replacement of 4DVar with 4DEnVar, the new system is also more computationally efficient and easier to parallelize, facilitating a doubling of the analysis increment horizontal resolution. Replacement of a full-field digital filter with the 4D incremental analysis update approach, and the recycling of several key variables that are not directly analyzed significantly reduced the model spinup during both the data assimilation cycle and in medium-range forecasts.

There is a well-recognized spatiotemporal meteorological observation gap at latitudes higher than 55°, especially in the region 55°–70°. A possible solution to address this issue is a constellation of four satellites in a highly elliptical orbit (HEO), that is, two satellites for each polar region. An important satellite product to support weather prediction is atmospheric motion wind vectors (AMVs). This study uses observing system simulation experiments (OSSEs) to evaluate the benefit to forecasts resulting from the assimilation of HEO AMVs covering one or both polar regions. The OSSE employs the operational global data assimilation system of the Canadian Meteorological Center. HEO AMVs are assimilated north of 50°N and south of 50°S. From 2-month assimilation cycles, the study examines the following three issues: 1) the impact of AMV assimilation in the real system, and how this compares to the impact seen in the simulated system, 2) the added value of HEO AMVs in the Arctic on top of what is currently available, and 3) the relative impact of HEO AMVs in the Arctic and Antarctic in comparison with no AMVs. Although the simulated impact of currently available AMVs is somewhat higher than the real impact, a firm conclusion is that the added value of Arctic HEO AMVs is substantial, improving predictability at days 3–5 by a few hours in terms of 500-hPa geopotential height. The impact of HEO AMVs is relatively stronger in the Southern Hemisphere. Forecast validation of atmospheric profiles against the simulated “true” state and against analyses generated within the assimilation cycles yields very similar results beyond 48 h.

The Observing System Simulation Experiment (OSSE) capability developed at Environment Canada allows simulation of all observation types currently used operationally as well as future data types. Its infrastructure, based on the operational global data assimilation system used at the Canadian Meteorological Centre, was recently enhanced to conduct data assimilation experiments for two future satellite missions. This study presents a subcomponent of that system, focusing on the assimilation of infrared radiances from the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer (IASI) instruments. The goal is to realistically simulate the radiance observations and to reproduce statistical characteristics of these data seen in the real system, notably background and analysis departures. Care is taken to emulate the operational quality control procedures leading to the assimilation of clear radiances, which implies radiance simulation for all-sky conditions. It is found that the standard deviation of the Gaussian random perturbation applied to the simulated observations should be close to that of the radiometric noise level for sounding channels in the 13.0–14.5-μm region but that it should be significantly higher for water vapor channels in the 5.5–6.7-μm region. The study also allows evaluation of residual biases linked to cloud contamination. For atmospheric window channels, that bias can reach −0.4 K. It reduces rapidly with peak height of the channel response function. This suggests that improvements are needed in low-cloud detection. The realism of the OSSE is further demonstrated through the shown impact consistency of AIRS and IASI radiance assimilation in forecasts up to 5 days from the separate use of simulated and real observations.

A new system that resolves the stratosphere was implemented for operational medium-range weather forecasts at the Canadian Meteorological Centre. The model lid was raised from 10 to 0.1 hPa, parameterization schemes for nonorographic gravity wave tendencies and methane oxidation were introduced, and a new radiation scheme was implemented. Because of the higher lid height of 0.1 hPa, new measurements between 10 and 0.1 hPa were also added. This new high-top system resulted not only in dramatically improved forecasts of the stratosphere, but also in large improvements in medium-range tropospheric forecast skill. Pairs of assimilation experiments reveal that most of the stratospheric and tropospheric forecast improvement is obtained without the extra observations in the upper stratosphere. However, these observations further improve forecasts in the winter hemisphere but not in the summer hemisphere. Pairs of forecast experiments were run in which initial conditions were the same for each experiment but the forecast model differed. The large improvements in stratospheric forecast skill are found to be due to the higher lid height of the new model. The new radiation scheme helps to improve tropospheric forecasts. However, the degree of improvement seen in tropospheric forecast skill could not be entirely explained with these purely forecast experiments. It is hypothesized that the cycling of a better model and assimilation provide improved initial conditions, which result in improved forecasts.

Recent reports on Arctic climate change sparked an interest in the development of a new observing system for this region, specifically a satellite system making use of a highly elliptical orbit (HEO), an idea supported by the World Meteorological Organization. This paper attempts to quantify the advantages of such a system relative to a traditional constellation of Lower Earth Orbit (LEO) polar satellites. A realistic two-satellite HEO system is compared with currently operating two-, four-, and seven-satellite LEO constellations in terms of spatio-temporal coverage and capability to provide sequences of single, dual, and triplet images at a required temporal resolution. This is important to properly monitor dynamic events, such as volcanic ash transport, frontal systems, smoke from wild fires, and cloud motion from which wind vectors are derived. A two-satellite HEO system is 5–10 times more efficient for monitoring dynamic events from image pairs above 70°N than a standard four-satellite morning-afterno...

A highly elliptical orbit (HEO) with a 16-h period is proposed for continuous meteorological imaging of polar regions from a two-satellite constellation. This orbit is characterized by three apogees (TAP) separated by 120°. The two satellites are 8 h apart, with repeatable ground track in the course of 2 days. Advantages are highlighted in comparison to the Molniya 12-h orbit described in detail in a previous study (Trishchenko and Garand). Orbital parameters (period, eccentricity, and inclination) are obtained as a result of an optimization process. The principles of orbit optimization are based on the following four key requirements: spatial resolution (apogee height), the altitude of crossing the trapped proton region at the equator (minimization of radiation doze caused by trapped protons), imaging time over the polar regions, and the stability of the orbit, which is mostly defined by the rotation of perigee. The interplay between these requirements points to a 16-h period with an eccentricity of 0.55 as the optimum solution. The practical range of orbit inclinations that could be maintained during the spacecraft lifetime can vary from a critical value of 63.435° to 70° (subject to the amount of propellant available for orbital maneuvers). In comparison to Molniya, this type of orbit reduces the radiation exposure to high-energy protons by factor of 103–104. On the other hand, the main advantage of 16 h versus longer orbital periods up to 24 h is better spatial resolution as a result of a lower apogee height. A two-satellite TAP constellation with an orbital inclination of 66° provides 100% temporal coverage above 60°N, >95% above 55°N, >85% above 50°N, and >75% above 45°N.

There has been a significant increase of interest in the building of a comprehensive Arctic observing system in recent years to properly and timely track the environmental and climate processes in this vast region. In this regard, a satellite observing system on highly elliptical orbit (HEO) with 12-h period (Molniya type) is of particular interest, because it enables continuous coverage of the entire Arctic region (58°–90°N) from a constellation of two satellites. Canada is currently proposing to operate such a constellation by 2017. Extending the pioneering study of S. Q. Kidder and T. H. Vonder Haar, this paper presents in-depth analysis of spatiotemporal sampling properties of the imagery from this system. This paper also discusses challenges and advantages of this orbit for various applications that require high temporal resolution and angular sampling.

The well-known CO2 slicing technique which provides retrievals of cloud parameters (effective height and amount) is adapted in light of model validation using multispectral infrared sounders. The technique is applied to both real Atmospheric Infrared Sounder (AIRS) radiances and to corresponding radiances simulated from global 6 h and 12 h forecasts for the 31 days of July 2008. The forecast model is the one used operationally at the Canadian Meteorological Centre. Radiances are simulated from the Radiative Transfer for the Television and Infrared Observation Satellite (TIROS) Operational Vertical Sounder (RTTOV) model. When compared to model output of cloud parameters, simulated retrievals help us understand systematic biases linked to the retrieval technique. Systematic errors of interest, attributed to forecast cloud parameters, are then more clearly assessed from real retrievals. This is the central idea of this paper. The proposed definition of model cloud top, based on cloud transmittance, correspon...

A variational estimation procedure for the simultaneous retrieval of cloud parameters and thermodynamic profiles from infrared radiances is proposed. The method is based on a cloud emissivity model which accounts for the frequency dependence of cloud absorption and scattering and possible mixed phase situations. An effective cloud top height and emissivity are assumed. Monte Carlo experiments performed in a 1D‐var assimilation context using simulated Atmospheric Infrared Radiance Sounder (AIRS) observations from 100 channels demonstrate the substantial added value, in theory, of cloudy radiance assimilation as opposed to clear‐channel assimilation. Improved temperature and humidity retrievals are obtained for a broad layer above the cloud as well as below cloud level under partial cloud cover conditions. The impact is most pronounced in broken to overcast situations involving mid‐level clouds. In these situations, the effective cloud top height and emissivity are retrieved with estimated rms erro...

Radiances measured by remote-sensing instruments are now the largest component of the atmospheric observation network. The assimilation of radiances from nadir sounders involves fast radiative transfer (RT) models which project profiles provided by forecast models onto the observation space for direct comparison with the measurements. One of the features typically characterizing fast RT models is the use of a fixed vertical coordinate. If the vertical coordinate of the RT model is not identical to that used by the forecast model, an interpolation of forecast profiles to the RT model coordinate is necessary. In variational data assimilation, the mapping of the Jacobians (derivatives of the RT model output with respect to its inputs) from the RT model coordinate to the forecast model coordinate is also required. This mapping of Jacobians is accomplished through the adjoint of the forecast profile interpolator. As shown, the nearest-neighbour log-linear interpolator commonly used operationally can lead to incorrect mapping of Jacobians and, consequently, to incorrect assimilation. This incorrect mapping occurs as a result of leaving out intermediate levels in the interpolation. This problem has been previously masked in part through the smoothing effect of forecast-error vertical correlations on the analysis increments. To solve this problem, two simple versions of an interpolator relying on piecewise log-linear weighted averaging over the layers are investigated. Both markedly improve Jacobian mappings in the assimilation of observations, with one being slightly favoured over the other. This interpolator is being incorporated into the RTTOV model used by several operational weather forecasting centres. Copyright © 2007 Crown in the right of Canada. Published by John Wiley & Sons, Ltd.

The interchannel observation error correlation (IOEC) associated with radiance observations is currently assumed to be zero in meteorological data assimilation systems. This assumption may lead to suboptimal analyses. Here, the IOEC is inferred for the Atmospheric Infrared Radiance Sounder (AIRS) hyperspectral radiance observations using a subset of 123 channels covering the spectral range of 4.1–15.3 μm. Observed minus calculated radiances are computed for a 1-week period using a 6-h forecast as atmospheric background state. A well-established technique is used to separate the observation and background error components for each individual channel and each channel pair. The large number of collocations combined with the 40-km horizontal spacing between AIRS fields of view allows robust results to be obtained. The resulting background errors are in good agreement with those inferred from the background error matrix used operationally in data assimilation at the Meteorological Service of Canada. The IOEC is in general high among the water vapor–sensing channels in the 6.2–7.2-μm region and among surface-sensitive channels. In contrast, it is negligible for channels within the main carbon dioxide absorption band (13.2–15.4 μm). The impact of incorporating the IOEC is evaluated from 1D variational retrievals at 381 clear-sky oceanic locations. Temperature increments differ on average by 0.25 K, and ln(q) increments by 0.10, where q is specific humidity. Without IOEC, the weight given to the observations appears to be too high; the assimilation attempts to fit the observations nearly perfectly. The IOEC better constrains the variational assimilation process, and the rate of convergence is systematically faster by a factor of 2.

In this study, Observing System Simulation Experiments (OSSEs) are conducted to analyze the impact of assimilating surface sensitive infrared radiance observations over land and sea ice. This type of assimilation has not yet been successfully implemented at operational weather centers. Infrared radiance from AIRS (Atmospheric Infrared Sounder) and IASI (Infrared Atmospheric Sounding Interferometer) is simulated from the Nature Run (NR) provided by European Centre for Medium-Range Weather Forecasts and assimilated in a 3D-Var. analysis system. A control simulation was generated excluding the new data source, but including all data assimilated operationally at the Canadian Meteorological Center. Experiments were conducted allowing surface sensitive channels to be assimilated over all surfaces or excluding Polar Regions. Resulting forecasts were intercompared and validated against NR fields. Results indicate significant positive impacts in the tropics and Southern Hemisphere extratropics and more modest impacts in the Northern Hemisphere extratropics. Some limitations of the OSSE approach are identified, linked to the different forecast systems used for the NR and the assimilation and higher cloud contamination in Polar Regions. This analysis provides useful insight in preparation for the assimilation of real radiance observations.

This paper makes use of ensemble forecasts to infer the correlation between surface skin temperature Ts and air temperature Ta model errors. The impact of this correlation in data assimilation is then investigated. In the process of assimilating radiances that are sensitive to the surface skin temperature, the Ts–Ta error correlation becomes important because it allows statistically optimal corrections to the background temperature profile in the boundary layer. In converse, through this correlation, surface air temperature data can substantially influence the analysis of skin temperature. One difficulty is that the Ts–Ta correlation depends on the local static stability conditions that link the two variables. Therefore, a correlation estimate based on spatial or temporal averages is not appropriate. Ensembles of forecasts valid at the analysis time provide a novel means to infer the correlation dynamically at each model grid point. Geostationary Operational Environmental Satellite (GOES)-8 and -10 surface-sensitive imager radiances are assimilated with and without the inferred correlations in a 3D variational analysis system. The impact of the correlation on analyses is assessed using independent radiosonde data. The impact on 6-h forecasts is also evaluated using surface synoptic reports. The influence of the correlation extends from the surface to about 1.5 km. Temperature differences in the resulting analyses on the order of 0.3–0.6 K are typical in the boundary layer and may extend over broad regions. These difference patterns persist beyond 6 h into the forecasts.

Geostationary Operational Environmental Satellite (GOES)-East and -West window channel radiances are directly assimilated using a 1D variational technique, providing surface skin temperature (Ts) estimates over all surface types (land, water, or ice) from a unique system. This is an important advantage over commonly used regression methods, such as split window. The physical nature of the method allows any combination of channels to be used, and adaptation to new sensors is straightforward. A full month (May 2001) of GOES-8 and -10 data is processed every 6 h; Ts estimates are obtained using radiances from imager channels 4 (11 μm) and 5 (12 μm). Imager channel 2 (3.9 μm) can also be used at night. Surface emissivity maps were constructed from available information based on surface type. The diurnal cycle is studied; its range is on the order of 0.7 K over the ocean. Over land, the diurnal range reaches 30 K for mountainous regions, such as the Rockies or Andes. A full GOES disk image can be proc...

To improve cloud and precipitation forecasts in the Canadian numerical weather prediction system, three cloud schemes with various degrees of complexity are evaluated. Several winter cases are simulated and mesoscale forecasts are compared with satellite, radiosonde, and surface observations. In particular, the distribution of cloud-top pressure is studied in detail using Geostationary Operational Environmental Satellite-8 (GOES-8) data. The three-dimensional structure of temperature and moisture is compared with upper-air data and forecasts of surface precipitation are scored against synoptic observations. This study demonstrates that the operational Canadian cloud scheme has problems that can be partially addressed by the inclusion of more realistic cloud microphysics in the forecast system.

The direct assimilation of satellite radiances is now operational in a few forecast centres, providing global temperature (T) and moisture (Q) information. The critical parameters which influence the quality of the resulting analysis are mainly the selection of channels, the respective errors of the background field and radiance observations, and the quality of the radiative transfer model. These various aspects are studied from sensitivity experiments based on 1‐D variational assimilations using the ensemble of 19 infrared channels (HIRS) of the NOAA‐14 satellite. It is shown that significant improvements in the retrievals would be obtained if the radiance observation error (measurement plus radiative transfer), currently estimated to be about equal to that of the background (in radiance units), were decreased. This could in principle be achieved by improving the forward radiative transfer model (RTM). Two RTMs suitable for radiance assimilation are compared in terms of analyzed increments, Jaco...

An intercomparison of radiation codes used in retrieving upper tropospheric humidity (UTH) from observations in the v2 (6.3 microns) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the GEWEX Water Vapor Project (GVaP) to assess our ability to monitor the distribution and variations of upper tropospheric moisture from space-borne sensors. A total of 23 different codes, ranging from detailed line-by-line (LBL) models, to coarser resolution narrow-band (NB) models, to highly-parameterized single-band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature (T(sub b)). The majority of NB and SB models agreed to within +/- 1 K of the LBL models, although a few older models exhibited systematic T(sub b) biases in excess of 2 K. A discussion of the discrepancies between various models, their association with differences in model physics (e.g. continuum absorption), and their implications for UTH retrieval and radiance assimilation is presented.

A continuous assimilation of high-density global satellite observations is required in order to improve numerical weather prediction analyses used to start forecasts. Until now, it was assumed that efficiency requirements imposed the use of regression-based models of atmospheric transmittance (typically on fixed pressure layers with coefficients varying for each layer) and prohibited the use of physically based models. Here, it is demonstrated that an explicit calculation of infrared transmittances for each absorbing gas (H2O, CO2, O3, CH4, N2O, and O2) can be done efficiently, provided that a monochromatic approach is followed as in a regression model such as Radiative Transfer for TOVS (the TIROS Operational Vertical Sounder) (operational in most weather centers). The classical Goody random model is chosen as a physical formulation for spectral line absorption along with established water vapor and oxygen continua parameterizations. Line-by-line transmittance calculations for 189 atmospheric pr...

Both the issues of high-resolution satellite analysis and model evaluation for a region centered on the Arctic Circle (60°–75°N) are addressed. Model cloud fraction, cloud height, and outgoing radiation are compared to corresponding satellite observations using a model-to-satellite approach (calculated radiances from model state). The dataset consists of forecasts run at 15-km resolution up to 30 h and nearly coincident Advanced Very High Resolution Radiometer (AVHRR) imagery during the Beaufort and Arctic Storm Experiment over the Mackenzie Basin for a monthly period in the fall of 1994. A cloud detection algorithm is designed for day and night application using the 11-μ channel of AVHRR along with available information on atmospheric and ground temperatures. The satellite and model estimates of cloud fraction are also compared to observations at 20 ground stations. A significant result of the validation is that the model has a higher frequency of low cloud tops and a lower frequency of midlevel cloud tops than the observations. On a monthly basis, the model 11-μ outgoing brightness temperature (TB) is consequently higher than observed by about 4.4 K at all forecast times, which corresponds to a deficit of 760 m in mean cloud-top height and about 10 W m−2 in outgoing flux at the top of the atmosphere. Possible errors in the parameterization of ice or water cloud emissivity are evaluated but ruled out as the dominant cause for the warm TB bias in the model. Rather, the problem is attributed to low clouds being trapped in the boundary layer, whereas high clouds appear to be reasonably well modeled. The role of thin ice clouds is further evaluated by comparing distributions of observed and modeled 11-μ minus 12-μ TB differences, DIF45 (channel 4 minus channel 5). The relationship between the true height of the clouds and the effective height observed by satellite is modeled from forecast outputs as a function of DIF45. The quality of daily estimates is evaluated from time series at various locations. The time series shows that there was a marked drop in DIF45 during the month, which is attributed to a decrease in the occurrence of cirrus clouds. Finally, the diurnal cycle of TB and cloud fraction is found to be relatively large with average monthly 0600–1800 UTC TB differences of both signs of the order of 4–8 K in broad sectors and cloud fraction differences of 10%–30%. Where low clouds prevail, the cloud fraction tends to decrease at night and TB increases. Overall, model–observation differences are dominated by differences in the vertical distribution of clouds. A reduction of this effect implies a modification of the “preferred” model climatology in terms of its vertical distribution of humidity and cloud water.

A strong linearity exists between the 6.7-μm clear-sky outgoing brightness temperature (BT) and dewpoint depression (DPD) at upper-tropospheric levels. A similar relationship, using the logarithm of relative humidity instead of DPD, was developed by Soden and Bretherton. Here, however, the humidity at specific levels is derived as opposed to the humidity integrated over upper-tropospheric levels. Linear relationships are obtained between a 6-h model forecast of DPD and calculated BTs at different viewing angles. The data are further stratified in terms of 400-mb temperature as an indicator of airmass type. Applying these relationships using observed 6.7-μm BTs and a 6-h forecast of 400-mb temperature yields vertically correlated estimates of DPD between 200 and 500 mb, with DPD typically decreasing with height, and corresponding rms error estimates in the range 3–6 K. The retrieval technique is applied to GOES-8 and GOES-9 data, which cover about 40% of the globe. In cloudy regions, proxy humidit...

Satellite retrievals of environmental parameters for October 1993 were used to validate the Canadian Meteorological Center (CMC) analysis/forecast system and an improved version of the forecast model (including a prognostic equation for cloud water). In part 1 [Deblonde and Wagneur, this issure], SSM/I (special sensor microwave imager) retrievals using different algorithms were intercompared for each environmental parameter (column integrated water vapor (IWV), near-surface oceanic wind speed (SWS), liquid water path (LWP) and surface rain rate (SRR). Here a subset of the SSM/I retrieval algorithms that performed best and other observation data sets are used to evaluate the hydrological cycle of the analysis/forecast system on a monthly timescale. Over the global oceans the agreement between analyzed IWV, forecasted IWV, and SSM/I retrievals was quite good (R ∼0.96). However, where Humsat (GOES) retrieved water vapor profiles were assimilated, significant biases were observed in large areas (up to ∼15 kgm−2). Significant differences were found between analyzed SWS and SSM/I-retrieved SWS. In the tropics, zonally averaged analyzed SWS was underestimated by up to 1.4 ms−1 and in the southern hemisphere midlatitude differences of ∼1 ms−1 were found. Forecasted cloud fraction from the improved model was compared with that observed using the Humsat retrieval system. Over the open oceans, modeled cloud fraction was overestimated by 8%, suggesting that cloud formation was too active. By comparing SSM/I LWP retrievals with those forecasted it was possible to identify mispositioning of cloud systems that were associated with noted biases in the humidity analysis. It was also shown that the choice of function to obtain the liquid phase component of the modeled cloud water modified considerably the magnitude of the monthly mean LWP, particularly in the midlatitudes. The differences in patterns between precipitation short-range forecasts (accumulated over a month) obtained with the operational and improved forecast models were considerably smaller than the differences between each of these forecasted fields and SSM/I retrievals or long-term climatologies.

The PCW (Polar Communications and Weather) mission is a dual satellite mission with each satellite in a highly eccentric orbit with apogee ~42,000 km and a period (to be decided) in the 12–24 hour range to deliver continuous communications and meteorological data over the Arctic and environs. Such as satellite duo can give 24×7 coverage over the Arctic. The operational meteorological instrument is a 21-channel spectral imager similar to the Advanced Baseline Imager (ABI). The PHEOS-WCA (weather, climate and air quality) mission is intended as an atmospheric science complement to the operational PCW mission. The target PHEOS-WCA instrument package considered optimal to meet the full suite of science team objectives consists of FTS and UVS imaging sounders with viewing range of ~4.5° or a Field of Regard (FoR) ~ 3400×3400 km 2 from near apogee. The goal for the spatial resolution at apogee of each imaging sounder is 10×10 km 2 or better and the goal for the image repeat time is targeted at ~2 hours or better. The FTS has 4 bands that span the MIR and NIR with a spectral resolution of 0.25 cm −1 . They should provide vertical tropospheric profiles of temperature and water vapour in addition to partial columns of many other gases of interest for air quality. The two NIR bands target columns of CO 2 , CH 4 and aerosol optical depth (OD). The UVS is an imaging spectrometer that covers the spectral range of 280–650 nm with 0.9 nm resolution and targets the tropospheric column densities of O 3 and NO 2 and several other Air Quality (AQ) gases as well the Aerosol Index (AI).

This study explores the feasibility of performing an objective analysis of instantaneous rain rate combining satellite estimates (and eventually other types of observations) with those from a numerical prediction model using the method of statistical interpolation. Results demonstrate that the quality of the short-term precipitation forecasts serving as background field has reached a level that makes such an objective analysis possible. The two main requirements to obtain an accurate analysis from available information are a realistic estimate of background field and observation errors and knowledge of the horizontal correlation of these errors with distance. The importance of specifying the errors for joint model-observation situations is emphasized; it is especially important in situations where model and observations are in conflict. These aspects of the problem are studied using collocated 6-h forecast with satellite estimates derived from visible and infrared imagery, and ground-truth rainfa...

Total precipitable water (TPW) retrieved from Special Sensor Microwave/lmager (SSM/I) brightness temperatures and specific humidity retrieved from Geostationary Operational Environmental Satellite (GOES) radiances are assimilated using a one-dimensional (ID) variational analysis technique. The study is divided into two parts. First, collocations with radiosondes are performed to arm the quality of the satellite water vapor retrievals. Collocations are also performed with 6-h forecast Acids. Second, SSM/I TPW and GOES specific humidity are assimilated using a ID variational analysis technique that minimizes the error variance of the analyzed field. A global collocation study over the oceans for SSM/I TPW retrievals and 6-h forecasts of TPW shows that the rmse (with respect to radiosondes) are, respectively, 4.7 and 5.0 kg m−2. A separate collocation study over both the oceans and land for GOES retrieved TPW and 6-h forecasts of TPW yields rmse of 4.6 and 4.4 kg m−2, respectively, in the midlatitudes and 6.8 and 5.9 kg m−2 in the Tropics. The reduction of the 6-h forecast rmse when assimilating SSM/I TPW is 1 kg m−2, which is a reduction of 20% in the rmse. When GOES retrievals of specific humidity are assimilated, the elective reduction is 0.6 kg m−2. It is shown that in the upper levels of the troposphere (above 600 mb), the error reduction of specific humidity is largely due to the GOES retrievals, whereas in the lower troposphere (850 and 700 mb), the reduction is mostly due to the SSM/I TPW. This emphasizes the complementarity of the information contained at different wavelengths and the advantage of using multisensor retrievals in data analysis.

Using Global Precipitation Climatology Project data gathered during June, July, and August 1989 over Japan, rainfall estimates are examined from both geostationary satellite imagery using a multifeature classification approach, and from short-term weather prediction model fields. Additionally, the utility of combining model forecast information within such a classifier to improve the final estimate is investigated. During both months satellite estimates are superior to model forecasts in detecting heavy rain events associated with extremely cold cloud tops, and in identifying cloud-free regions. Model estimates are superior to satellite retrievals in terms of dynamic range and regional bias. Addition of visible data to an infrared-only scheme improved monthly rainfall estimates during June, and hourly estimates during both months. In June it is shown that a combined satellite-model method clearly yields improved retrievals of rainfall relative to those obtained by using either satellite data or m...

Model simulated cloud properties such as cloud fraction, cloud top height, and infrared (IR) radiance are compared to those from GOES-7 satellite observations over a monthly period from an ensemble of thirty-one forecasts launched each day of October 1993. The aim is to evaluate both the above mentioned parameters and the cloud optical properties (emissivity, optical depth) in a global model that carries cloud water (ice and water phases combined) as a prognostic variable. The results show that the model simulates well the cloud fraction, cloud top height, and IR radiance in the middle and high latitude regions, especially in the Northern Hemisphere. Most obvious deficiencies are found in the tropics and subtropics over the ocean: underestimation of cloud fraction and cloud top height in the inter-tropical convergence zone, and overestimation of low clouds in the subtropics. The causes of these deficiencies are discussed. The cloud emissivity parameterization is tested and its sensitivity to effective cloud fraction and outgoing radiance is assessed from comparisons with cases that assume an emissivity of unity. The resulting global infrared budget is realistic with a net loss at the top of the atmosphere of 243 W/m 2 and 55 W/m 2 at the surface. Although error compensation between cloud height and fraction occurs in some areas to yield good IR radiances, the outgoing radiation is excellent in regions where clouds are best, thus validating the chosen emissivity parameterization. After some adjustment of the parameterized visible cloud optical depth, the global shortwave budget is also reasonable compared to available climatology with a net surface flux of 157 W/m 2 and a planetary albedo of 30%. The sensitivity to various parameters affecting the radiation budget is examined. DOI: 10.1034/j.1600-0870.1997.t01-1-00006.x

The TICFIRE mission concept developed with the support of the Canadian Space Agency aims: 1) to improve measurements of water-vapour concentration in the low limit, where cold regions are most sensitive and 2) to determine the contribution of Thin Ice Clouds (TIC) to the energy balance and the role of their microphysical properties on atmospheric cooling. TICFIRE is a process-oriented mission on a micro-satellite platform dedicated to observe key parameters of TIC forming in the cold regions of the Poles and globally, in the upper troposphere. It locates cloud top profiles at the limb and measures at nadir the corresponding upwelling radiance of the atmosphere directly in the thermal window and in the Far Infrared (FIR) spectrum over cold geographical regions, precisely where most of the atmospheric thermal cooling takes place. Due to technological limitations, the FIR spectrum (17 to 50 μm) is not regularly monitored by conventional sensors despite its major importance. This deficiency in key data also impacts operational weather forecasting. TICFIRE will provide on a global scale a needed contribution in calibrated radiance assimilation near the IR maximum emission to improve weather forecast. TICFIRE is therefore a science-driven mission with a strong operational component. The TICFIRE payload consists of two instruments; the main one being a Nadir-looking multiband radiometer based on uncooled microbolometer technology and covering a large spectral range from 7.9 μm to 50 μm. The secondary one is an imager that performs Limb measurements and provides cloud vertical structure information. This paper presents the key payload requirements, the conceptual design, and the estimated performance of the TICFIRE payload. Current technology developments in support to the mission are also presented.

A retrieval technique based on cloud classification is designed to derive humidity profiles from Meteosat visible (VIS), infrared window (IR), and water vapor (WV) channels, or equivalent sensors available on other satellites. Dewpoint depression (DPD) is the variable retrieved at six standard levels: 1000, 850, 700, 500, 400, and 300 mb. Collocation of soundings and Meteosal-2 imagery was obtained over Europe for March, June, and July 1988. Results are derived from over 2000 dependent and 1000 independent samples. It is found that a classification in seven (IR only) or nine (VIS-IR) classes contains the essential information on cloud type for the application sought. Measures were extracted from approximately 8-km pixel resolution images on 80-km × 80-km and 160-km × 160-km arm, little dependency on horizontal scale was found for the mean humidity profiles associated with each cloud class. The WV channel proved very useful in improving DPDs at higher levels while the VIS channel improved inferenc...

[1] It is shown that the deviation of air from an ideal gas has nonnegligible effects when assimilating GPS radio occultation (GPSRO) data in a Numerical Weather Prediction (NWP) system. Therefore an assimilation system that aims to be unbiased to within the threshold of detection should account for this effect. GPSRO data are vertically referenced in terms of mean sea level altitude. Many other data types are vertically referenced in pressure units. The assimilation system may use yet another vertical coordinate. The required transformations between vertical coordinate systems should not induce significant biases. In the context of NWP the threshold of detection for a systematic height bias is on the order of 1–2 m. This study demonstrates that this level of accuracy cannot be obtained unless the deviation of air from an ideal gas, known as compressibility factor, is properly taken into account. With the current volume of GPSRO data an inconsistency between pressure and altitude scales larger than the mentioned threshold can lead to the development of nonnegligible biases in NWP assimilation cycles. Consideration of the compressibility factor realigns the altitude- and pressure-based scales to better than 1 m in the entire troposphere. Impacts are appreciated not only from global averages but from zonal averages as well.

The usefulness of numerical weather prediction models in very short-range forecasting is limited by the spinup problem, resulting in an underestimation of both the divergent wind component and the precipitation. To alleviate the spinup problem, latent-heating profiles were directly assimilated into the Canadian regional finite-element (RFE) model. The estimates of latent heating were based on the precipitation rates inferred from GOES infrared and visible imagery. The latent heating was distributed in the vertical according to the stratiform condensation scheme of the model, but the heating rates were normalized to correspond to the satellite-inferred rain rates. The initial relative humidity field was enhanced to 95% between sigma-level 0.875 and the cloud top wherever the probability of precipitation, derived from satellite imagery, was larger than 40%. The results of a case study from the Canadian Atlantic Storms Program (CASP) indicated that the spinup time of the vertical motion, initially o...

The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: seven HIRS (High-resolution Infrared Sounder) and four AMSU (Advanced Microwave Sounding Unit) channels. Interest in this topic was evidenced by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances, but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle and more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences. Recommendations for future intercomparisons are suggested.

From a pattern recognition technique applied on GOES-7 full disks, humidity profiles defined at six standard levels (300 - 1000 mb) are retrieved on 1 degree(s) X 1 degree(s) areas in all weather/cloud conditions. Using one of two retrievals in each direction, about 3000 profiles are assimilated every six hours from 60 degree(s) N to 60 degree(s) S, 50 degree(s) E to 170 degree(s) W in the Canadian global forecast model. Slightly improved forecasts of geopotential are obtained over North America. Significant differences are noted locally in the forecast instantaneous and accumulated precipitation, especially in the tropics. Both analyses and forecasts of low level stratocumulus which are extensive west of continents are clearly improved. The system became operational in April 1993 and will soon be extended to Meteosat-3 now at 75 degree(s) W; the two geostationary satellites provide humidity profiles on 40% of the globe four times daily.

Sunshine data are received daily on a real time basis at the Quebec Forecast Office and are converted into terms of percent of possible sunshine. On the basis of a survey held in the Quebec Forecast Office, the percent of possible sunshine was associated with the plain language expressions used to describe sky cover. Using this relationship, it was possible to use these observed sunshine reports to objectively verify the worded forecasts of sky cover. Techniques are being developed to forecast the percent of possible sunshine to be used as guidance in our public forecasts.

Infrared heating rate calculations with the emissivity formulation are improved by developing simple methods to minimize the effects of the two main sources of error 1) the use of the strong-line approximation; 2) the neglect of temperature variations along the optical path. When compared to band-by-hand calculations, the resulting new scheme maintains a 5% accuracy on cooling rates, and errors generally less than 2 W m−2 on fluxes. The most recent band parameters of MeClatchey et al. (1973) are used in the band-by-band calculations, including measured data for the vibration-rotation bands. Another novel aspect of the new scheme is the treatment of “e-type” absorption, which is a very important effect in hot humid air near the ground. An implicit parameterization is developed which allows for “e-type” absorption in the pre-tabulated transmission functions, and so requires no computational overhead. This is based on the derivation of an approximate formula which expresses the optical depth due to ...

A scheme is presented for the automated classification of oceanic cloud patterns. The 20 cloud classes reflect the rich variety of morphologies that are detectable from space. A training set is defined by 2000 samples of size 128 × 128 km taken from GOES visible and infrared images over the western Atlantic in February 1984. Class discrimination is obtained from 13 features representing height, albedo, shape and multilayering characteristics of the cloud fields. Two features derived from the two-dimensional power spectrum of the visible images proved essential for the detection of directional patterns (cloud “streets or rolls) and open cells. Based on the assumption of multinormal distributions of the features, a simple classification algorithm is developed. The generation of artificial samples yields a theoretical separability of 97% while the actual separability obtained on the training set is 95%. From 1020 independent samples, the separate verification of three expert nephanalysts indicates s...