Clear-sky biases in satellite infrared estimates of upper tropospheric humidity and its trends

We use microwave retrievals of upper tropospheric humidity (UTH) to estimate the impact of clear-sky-only sampling by infrared instruments on the distribution, variability and trends in UTH. Our method isolates the impact of the clear-sky-only sampling, without convolving errors from other sources. On daily time scales IR-sampled UTH contains large data gaps in convectively active areas, with only about 20-30 % of the tropics (30 S­ 30 N) being sampled. This results in a dry bias of about -9 %RH in the area-weighted tropical daily UTH time series. On monthly scales, maximum clear-sky bias (CSB) is up to -30 %RH over convectively active areas. The magnitude of CSB shows significant correlations with UTH itself (-0.5) and also with the variability in UTH (-0.6). We also show that IR-sampled UTH time series have higher interannual variability and smaller trends compared to microwave sampling. We argue that a significant part of the smaller trend results from the contrasting influence of diurnal drift in the satellite measurements on the wet and dry regions of the tropics

Analysis of upper tropospheric humidity measurements by microwave sounders and radiosondes

This thesis describes results of several analyses of humidity measurements by microwave humidity sounders and radiosondes. The goal of this work is to pave the way for fully utilizing these measurements for climatological applications. High resolution radiosonde data are used to examine the variability of the clear-sky outgoing longwave radiation (OLR). The global variability of OLR is found to be 33 Wm-2, of which a large part can be attributed to temperature variations. The variability after filtering the temperature part is associated with the humidity variability in the horizontal and the vertical. The impact of the vertical structures on the OLR calculations is also investigated in detail. It is observed that smoothed profiles in relative humidity are sufficient to obtain the mean value of OLR, even though the variability cannot be exactly reproduced. AMSU-B Channel 18 brightness temperatures are sensitive to upper tropospheric humidity (UTH). A simple method is developed to transform the brightness temperatures to UTH. This method is validated with high quality radiosonde data. An initial attempt to make a UTH climatology and the usefulness of a robust estimator such as the median in climatological studies are discussed. Finally, a robust method was developed to compare the humidity measurements from satellite humidity sounders and radiosondes. The method is developed and tested using the high quality radiosonde data from the Lindenberg radiosonde station. A case study using different versions of the data shows that the method is sensitive to humidity differences in the different versions. The main result from the case study is that the corrected radiosonde data still have a slight dry bias in the upper troposphere. The method is then applied to assess the performance of different radiosonde sensors and stations. It isfound to be useful for monitoring the global radiosonde network, using the microwave satellite data as a benchmark

Statistical characterisation of water vapour variability in the troposphere

Tropospheric water vapour plays an important role in thermodynamic and radiative processes which have an immediate impact on the weather and climate system. However, the processes that determine the distribution of water vapour remain poorly understood. The complexity arises out of a range of source and sink processes from convective clouds on the kilometre scale to cloud systems associated with motions on scales of a thousand or more kilometres, as well as advection of water vapour as a passive tracer outside of clouds. While large-scale advection of water vapour is well represented in general circulation models, the simulation of small-scale moist processes that are of central importance to the representation of clouds are heavily dependent on parameterisations. However, observations as well as processes that determine the distribution of the water vapour field are insufficiently explored, leading to constrained parameterisations and therefore contributing significantly to the uncertainty of numerical weather and climate predictions. Hence, a more accurate description of the inhomogeneous water vapour field based on high-resolution observations is required. This thesis investigates a comprehensive data set of two-dimensional airborne water vapour observations in the free troposphere collected by a Differential Absorption Lidar (DIAL) in order to gain a height-resolved statistical characterisation of the inhomogeneous water vapour field. Structure functions, i.e., statistical moments up to the fifth order of absolute increments over a range of scales, are investigated and power-law behaviour or scale dependence is identified over horizontal distances from about 5~km to 100~km. The slope of the power-law fit, the so-called scaling exponent, is found to take different values, depending on whether or not the observations were taken in an air mass where convective clouds were present. These results are consistent with a non-convective regime that is dominated by large-scale advective processes, leading to monofractal scaling, but strong localised input of small-scale variability by convective circulations leading to intermittent fields. Further, the observed power-law statistics are used to evaluate the high-resolution numerical weather prediction model COSMO-DE of the German weather service with regard to the small-scale water vapour variability. The results of the scaling exponent analysis of cloud-free and partly cloudy scenes suggest, that the small-scale variance is modeled quite well in comparison with the lidar observations. By using the advantage of the model simulation where data is not limited to a specific flight path, the influence of sampling limitation is estimated and is found to be not significant. Further, the simulation provides humidity data in and beneath clouds which allows for an estimation of the uncertainty of data gaps in the lidar observations due to optically thick clouds. The error is identified to be in a range of only few percents. This thesis demonstrates that airborne DIAL observations are useful to build up a height-resolved statistical characterisation of tropospheric water vapour variability that allows to distinguish physical mechansims that are responsible for the water vapour distribution, to get new insights into stochastic parameterisations and further to use the structure function method as a suitable reality check of the numerical weather model COSMO-DE

A cautionary note on the use of Gaussian statistics in satellite-based UTH climatologies

This letter presents a cautionary note on the assumption of Gaussian behavior for upper tropospheric humidity (UTH) derived from satellite data in climatological studies, which can introduce a wet bias in the climatology. An example study using European Centre for Medium-Range Weather Forecasts reanalysis data shows that this wet bias can reach up to 6 %RH, which is significant for climatological applications. A simple Monte Carlo approach demonstrates that these differences and their link to the variability of brightness temperatures are due to a log-normal distribution of the UTH. This problem can be solved by using robust estimators such as the median instead of the arithmetic mean.Validerad; 2006; 20070427 (pafi)</p

The Southern Ocean Observing System (SOOS)

[in “State of the Climate in 2014” : Special Supplement to the Bulletin of the American Meteorological Society Vol. 96, No. 7, July 2015

Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change

This Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) has been jointly coordinated by Working Groups I (WGI) and II (WGII) of the Intergovernmental Panel on Climate Change (IPCC). The report focuses on the relationship between climate change and extreme weather and climate events, the impacts of such events, and the strategies to manage the associated risks. The IPCC was jointly established in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Programme (UNEP), in particular to assess in a comprehensive, objective, and transparent manner all the relevant scientific, technical, and socioeconomic information to contribute in understanding the scientific basis of risk of human-induced climate change, the potential impacts, and the adaptation and mitigation options. Beginning in 1990, the IPCC has produced a series of Assessment Reports, Special Reports, Technical Papers, methodologies, and other key documents which have since become the standard references for policymakers and scientists.This Special Report, in particular, contributes to frame the challenge of dealing with extreme weather and climate events as an issue in decisionmaking under uncertainty, analyzing response in the context of risk management. The report consists of nine chapters, covering risk management; observed and projected changes in extreme weather and climate events; exposure and vulnerability to as well as losses resulting from such events; adaptation options from the local to the international scale; the role of sustainable development in modulating risks; and insights from specific case studies

Greenland ice sheet [in "State of the Climate in 2014"]

peer reviewe

Climate change 2013: the physical science basis

This report argues that it is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century. This is an an unedited version of the Intergovernmental Panel on Climate Change\u27s Working Group I contribution to the Fifth Assessment Report following the release of its Summary for Policymakers on 27 September 2013.&nbsp; The full Report is posted in the version distributed to governments on 7 June 2013 and accepted by Working Group I and the Panel on 27 September 2013. It includes the Technical Summary, 14 chapters and an Atlas of Global and Regional Climate Projections. Following copy-editing, layout, final checks for errors and adjustments for changes in the Summary for Policymakers, the full Report will be published online in January 2014 and in book form by Cambridge University Press a few months later