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Author(s): Jing Wang [sup.1] [sup.2] [sup.3] [sup.4] , Liang Feng [sup.3] [sup.4] , Paul I. Palmer [sup.3] [sup.4] , Yi Liu [sup.1] [sup.2] , Shuangxi Fang [sup.5] [sup.6] , Hartmut [...], Limiting the rise in global mean temperatures relies on reducing carbon dioxide (CO.sub.2) emissions and on the removal of CO.sub.2 by land carbon sinks. China is currently the single largest emitter of CO.sub.2, responsible for approximately 27 per cent (2.67 petagrams of carbon per year) of global fossil fuel emissions in 2017.sup.1. Understanding of Chinese land biosphere fluxes has been hampered by sparse data coverage.sup.2-4, which has resulted in a wide range of a posteriori estimates of flux. Here we present recently available data on the atmospheric mole fraction of CO.sub.2, measured from six sites across China during 2009 to 2016. Using these data, we estimate a mean Chinese land biosphere sink of -1.11 [plus or minus] 0.38 petagrams of carbon per year during 2010 to 2016, equivalent to about 45 per cent of our estimate of annual Chinese anthropogenic emissions over that period. Our estimate reflects a previously underestimated land carbon sink over southwest China (Yunnan, Guizhou and Guangxi provinces) throughout the year, and over northeast China (especially Heilongjiang and Jilin provinces) during summer months. These provinces have established a pattern of rapid afforestation of progressively larger regions.sup.5,6, with provincial forest areas increasing by between 0.04 million and 0.44 million hectares per year over the past 10 to 15 years. These large-scale changes reflect the expansion of fast-growing plantation forests that contribute to timber exports and the domestic production of paper.sup.7. Space-borne observations of vegetation greenness show a large increase with time over this study period, supporting the timing and increase in the land carbon sink over these afforestation regions. Newly available atmospheric carbon dioxide measurements from six sites across China during 2009 to 2016 indicate a larger land carbon sink than previously thought, reflecting increased afforestation.

The International Satellite Cloud Climatology Project (ISCCP) dataset and the Extended Pathfinder Atmospheres (PATMOS-x) dataset are the two longest satellite records of cloudiness (6,7). The datasets consist of cloud retrievals [...], Clouds substantially affect Earth's energy budget by reflecting solar radiation back to space and by restricting emission of thermal radiation to space (1). They are perhaps the largest uncertainty in our understanding of climate change, owing to disagreement among climate models and observational datasets over what cloud changes have occurred during recent decades and will occur in response to global warming (2,3). This is because observational systems originally designed for monitoring weather have lacked sufficient stability to detect cloud changes reliably over decades unless they have been corrected to remove artefacts (4,5). Here we show that several independent, empirically corrected satellite records exhibit large-scale patterns of cloud change between the 1980s and the 2000s that are similar to those produced by model simulations of climate with recent historical external radiative forcing. Observed and simulated cloud change patterns are consistent with poleward retreat of mid-latitude storm tracks, expansion of subtropical dry zones, and increasing height of the highest cloud tops at all latitudes. The primary drivers of these cloud changes appear to be increasing greenhouse gas concentrations and a recovery from volcanic radiative cooling. These results indicate that the cloud changes most consistently predicted by global climate models are currently occurring in nature.

The assimilation of cloud- and precipitation-affected observations into weather forecasting systems requires very fast calculations of radiative transfer in the presence of multiple scattering. At the European Centre for Medium-Range Weather Forecasts (ECMWF), performance limitations mean that only a single cloudy calculation (including any precipitation) can be made, and the simulated radiance is a weighted combination of cloudy- and clear-sky radiances. Originally, the weight given to the cloudy part was the maximum cloud fraction in the atmospheric profile. However, this weighting was excessive, and because of nonlinear radiative transfer (the 'beamfilling effect') there were biases in areas of cloud and precipitation. A new approach instead uses the profile average cloud fraction, and decreases RMS errors by 40% in areas of rain or heavy clouds when 'truth' comes from multiple independent column simulations. There is improvement all the way from low (e.g., 19 GHz) to high (e.g., 183 GHz) microwave frequencies. There is also improvement when truth comes from microwave imager observations. One minor problem is that biases increase slightly in mid- and upper-tropospheric sounding channels in light-cloud situations, which shows that future improvements will require the cloud fraction to vary according to the optical properties at different frequencies. DOI: 10.1175/2009JAMC2170.1

The assimilation of cloud- and rain-affected radiances in numerical weather prediction systems requires fast and accurate radiative transfer models. One of the largest sources of modeling errors originates from the assumptions regarding the vertical and horizontal subgrid-scale variability of model clouds and precipitation. In this work, cloud overlap assumptions are examined in the context of microwave radiative transfer and used to develop an accurate reference model. A fast cloud overlap algorithm is presented that allows for the accurate simulation of microwave radiances with a small number of radiative transfer calculations. In particular, the errors for a typical two-column approach currently used operationally are found to be relatively large for many cases of cloudy fields containing precipitation, even those with an overall cloud fraction of unity; these errors are largely eliminated by using the new approach presented here, at the cost of a slight increase in computation time. Radiative transfer cloud overlap errors are also evident in simulations when compared to actual satellite observations, in that the biases are somewhat reduced when applying a more accurate treatment of cloud overlap.

Radiative transfer models for scattering atmospheres that are accurate yet computationally efficient are required for many applications, such as data assimilation in numerical weather prediction. The successive-order-of-interaction (SOI) model is shown to satisfy these demands under a wide range of conditions. In particular, the model has an accuracy typically much better than 1 K for most microwave and submillimeter cases in precipitating atmospheres. Its speed is found to be comparable to or faster than the commonly used though less accurate Eddington model. An adjoint has been written for the model, and so Jacobian sensitivities can be quickly calculated. In addition to a conventional error assessment, the correlation between errors in different microwave channels is also characterized. These factors combine to make the SOI model an appealing candidate for many demanding applications, including data assimilation and optimal estimation, from microwave to thermal infrared wavelengths.

Author(s): Jing Wang [sup.1] [sup.2] [sup.3] [sup.4] , Liang Feng [sup.3] [sup.4] , Paul I. Palmer [sup.3] [sup.4] , Yi Liu [sup.1] [sup.2] , Shuangxi Fang [sup.5] [sup.6] , Hartmut [...], An amendment to this paper has been published and can be accessed via a link at the top of the paper.

We present the theory and application of a novel calibration system for millimeter and microwave polarimeters. The technique is a simple extension of the conventional wire-grid approach, but employs a thin dielectric sheet rather than a grid. The primary advantage of this approach is to obtain a calibration signal that is only slightly polarized, which can be beneficial for certain applications such as astronomical radiometers that measure very low levels of polarization, or systems with a small dynamic range. We compare this approach with other calibration techniques and discuss its successful use in the calibration of the polarization observations of large angular regions experiment, designed to measure polarization in cosmic microwave background radiation. Index Terms--Calibration, microwave receivers, polarization, radiometry.