Understanding inter-satellite biases of microwave humidity sounders using global simultaneous nadir overpasses

Simultaneous nadir overpasses (SNOs) of polar-orbiting satellites are most frequent in polar areas but can occur at any latitude when the equatorial crossing times of the satellites become close owing to orbital drift. We use global SNOs of polar orbiting satellites to evaluate the intercalibration of microwave humidity sounders from the more frequent high-latitude SNOs. We have found based on sensitivity analyses that optimal distance and time thresholds for defining collocations are pixel centers less than 5 km apart and time differences less than 300 s. These stringent collocation criteria reduce the impact of highly variable surface or atmospheric conditions on the estimated biases. Uncertainties in the estimated biases are dominated by the combined radiometric noise of the instrument pair. The effects of frequency changes between different versions of the humidity sounders depend on the amount of water vapor in the atmosphere. There are significant scene radiance and thus latitude dependencies in the estimated biases and this has to taken into account while intercalibrating microwave humidity sounders. Therefore the results obtained using polar SNOs will not be representative for moist regions, necessitating the use of global collocations for reliable intercalibration.

Thermal aspects of satellite downscaling

The strong trend toward nanosatellites creates new challenges in terms of thermal balance control. The thermal balance of a satellite is determined by the heat dissipation in its subsystems and by the thermal connections between them. As satellites become smaller, heat dissipation in their subsystems tends to decrease and thermal connectivity scales down with dimension. However, these two terms do not necessarily scale in the same way, and so the thermal balance may alter and the temperature of subsystems may reach undesired levels. This paper focuses on low-Earth-orbit satellites. We constructed a generalized lumped thermal model that combines a generalized low-Earth-orbit satellite configuration with scaling trends in subsystem heat dissipation and thermal connectivity. Using satellite mass as a scaling parameter, we show that subsystems do not become thermally critical by scaling mass alone.

Generation and Evolution of Natal Pulses: Solitary Meanders in the Agulhas Current

Solitar y meanders of the Agulhas Current, so-called Natal pulses, may play an important role in the overall dynamics of this current system. Several hypotheses concer ning the triggering of these pulses are tested using sea sur face height and temperature data from satellites. The data show the for mation of pulses in the Natal Bight area at irregular inter vals ranging from 50 to 240 days. Moving downstream at speeds between 10 and 20 km day 2 1 they sometimes reach sizes of up to 300 km. They seem to play a role in the shedding of Agulhas rings that penetrate the South Atlantic. The inter mittent for mation of these solitar y meanders is argued to be most probably related to barotropic instability of the strongly baroclinic Agulhas Current in the Natal Bight. The vorticity structure of the obser ved basic flow is argued to be stable anywhere along its path. However , a proper perturbation of the jet in the Natal Bight area will allow barotropic instability , because the bottom slope there is considerably less steep than elsewhere along the South African east coast. Using satellite altimetr y these perturbations seem to be related to the inter mittent presence of offshore anticyclonic anomalies, both upstream and eastward of the Natal Bight.

Concepts for a geostationary-like polar missions

An evidence-led scientific case for development of a space-based polar remote sensing platform at geostationary-like (GEO-like) altitudes is developed through methods including a data user survey. Whilst a GEO platform provides a nearstatic perspective, multiple platforms are required to provide circumferential coverage. Systems for achieving GEO-like polar observation likewise require multiple platforms however the perspective is non-stationery. A key choice is between designs that provide complete polar view from a single platform at any given instant, and designs where this is obtained by compositing partial views from multiple sensors. Users foresee an increased challenge in extracting geophysical information from composite images and consider the use of non-composited images advantageous. Users also find the placement of apogee over the pole to be preferable to the alternative scenarios. Thus, a clear majority of data users find the “Taranis” orbit concept to be better than a critical inclination orbit, due to the improved perspective offered. The geophysical products that would benefit from a GEO-like polar platform are mainly estimated from radiances in the visible/near infrared and thermal parts of the electromagnetic spectrum, which is consistent with currently proven technologies from GEO. Based on the survey results, needs analysis, and current technology proven from GEO, scientific and observation requirements are developed along with two instrument concepts with eight and four channels, based on Flexible Combined Imager heritage. It is found that an operational system could, mostly likely, be deployed from an Ariane 5 ES to a 16-hour orbit, while a proof-of-concept system could be deployed from a Soyuz launch to the same orbit.

Selecting algorithms for Earth observation of climate within the European Space Agency Climate Change initiative: introduction to a special issue

This special issue is focused on the assessment of algorithms for the observation of Earth’s climate from environ- mental satellites. Climate data records derived by remote sensing are increasingly a key source of insight into the workings of and changes in Earth’s climate system. Producers of data sets must devote considerable effort and expertise to maximise the true climate signals in their products and minimise effects of data processing choices and changing sensors. A key choice is the selection of algorithm(s) for classification and/or retrieval of the climate variable. Within the European Space Agency Climate Change Initiative, science teams undertook systematic assessment of algorithms for a range of essential climate variables. The papers in the special issue report some of these exercises (for ocean colour, aerosol, ozone, greenhouse gases, clouds, soil moisture, sea surface temper- ature and glaciers). The contributions show that assessment exercises must be designed with care, considering issues such as the relative importance of different aspects of data quality (accuracy, precision, stability, sensitivity, coverage, etc.), the availability and degree of independence of validation data and the limitations of validation in characterising some important aspects of data (such as long-term stability or spatial coherence). As well as re- quiring a significant investment of expertise and effort, systematic comparisons are found to be highly valuable. They reveal the relative strengths and weaknesses of different algorithmic approaches under different observa- tional contexts, and help ensure that scientific conclusions drawn from climate data records are not influenced by observational artifacts, but are robust.

The EarthCARE satellite: the next step forward in global measurements of clouds, aerosols, precipitation, and radiation

The collective representation within global models of aerosol, cloud, precipitation, and their radiative properties remains unsatisfactory. They constitute the largest source of uncertainty in predictions of climatic change and hamper the ability of numerical weather prediction models to forecast high-impact weather events. The joint European Space Agency (ESA)–Japan Aerospace Exploration Agency (JAXA) Earth Clouds, Aerosol and Radiation Explorer (EarthCARE) satellite mission, scheduled for launch in 2018, will help to resolve these weaknesses by providing global profiles of cloud, aerosol, precipitation, and associated radiative properties inferred from a combination of measurements made by its collocated active and passive sensors. EarthCARE will improve our understanding of cloud and aerosol processes by extending the invaluable dataset acquired by the A-Train satellites CloudSat, Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and Aqua. Specifically, EarthCARE’s cloud profiling radar, with 7 dB more sensitivity than CloudSat, will detect more thin clouds and its Doppler capability will provide novel information on convection, precipitating ice particle, and raindrop fall speeds. EarthCARE’s 355-nm high-spectral-resolution lidar will measure directly and accurately cloud and aerosol extinction and optical depth. Combining this with backscatter and polarization information should lead to an unprecedented ability to identify aerosol type. The multispectral imager will provide a context for, and the ability to construct, the cloud and aerosol distribution in 3D domains around the narrow 2D retrieved cross section. The consistency of the retrievals will be assessed to within a target of ±10 W m–2 on the (10 km)2 scale by comparing the multiview broadband radiometer observations to the top-of-atmosphere fluxes estimated by 3D radiative transfer models acting on retrieved 3D domains.

Constraining the aerosol influence on cloud fraction

Aerosol-cloud interactions have the potential to modify many different cloud properties. There is significant uncertainty in the strength of these aerosol-cloud interactions in analyses of observational data, partly due to the difficulty in separating aerosol effects on clouds from correlations generated by local meteorology. The relationship between aerosol and cloud fraction (CF) is particularly important to determine, due to the strong correlation of CF to other cloud properties and its large impact on radiation. It has also been one of the hardest to quantify from satellites due to the strong meteorological covariations involved. This work presents a new method to analyze the relationship between aerosol optical depth (AOD) and CF. By including information about the cloud droplet number concentration (CDNC), the impact of the meteorological covariations is significantly reduced. This method shows that much of the AOD-CF correlation is explained by relationships other than that mediated by CDNC. By accounting for these, the strength of the global mean AOD-CF relationship is reduced by around 80%. This suggests that the majority of the AOD-CF relationship is due to meteorological covariations, especially in the shallow cumulus regime. Requiring CDNC to mediate the AOD-CF relationship implies an effective anthropogenic radiative forcing from an aerosol influence on liquid CF of −0.48 W m−2 (−0.1 to −0.64 W m−2), although some uncertainty remains due to possible biases in the CDNC retrievals in broken cloud scenes.

Bayesian analysis of uncertainty in the GlobCover 2009 land cover product at climate model grid scale

Land cover data derived from satellites are commonly used to prescribe inputs to models of the land surface. Since such data inevitably contains errors, quantifying how uncertainties in the data affect a model’s output is important. To do so, a spatial distribution of possible land cover values is required to propagate through the model’s simulation. However, at large scales, such as those required for climate models, such spatial modelling can be difficult. Also, computer models often require land cover proportions at sites larger than the original map scale as inputs, and it is the uncertainty in these proportions that this article discusses. This paper describes a Monte Carlo sampling scheme that generates realisations of land cover proportions from the posterior distribution as implied by a Bayesian analysis that combines spatial information in the land cover map and its associated confusion matrix. The technique is computationally simple and has been applied previously to the Land Cover Map 2000 for the region of England and Wales. This article demonstrates the ability of the technique to scale up to large (global) satellite derived land cover maps and reports its application to the GlobCover 2009 data product. The results show that, in general, the GlobCover data possesses only small biases, with the largest belonging to non–vegetated surfaces. In vegetated surfaces, the most prominent area of uncertainty is Southern Africa, which represents a complex heterogeneous landscape. It is also clear from this study that greater resources need to be devoted to the construction of comprehensive confusion matrices.