The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

Anvil cirrus clouds form in the upper troposphere from the outflow of ice crystals from deep convective cumulonimbus clouds. By reflecting incoming solar radiation as well as absorbing terrestrial thermal radiation, and re-emitting it at significantly lower temperatures, they play an important role for the Earth’s radiation budget. Nevertheless the processes that govern their life cycle are not well understood and, hence, they remain one of the largest uncertainties in atmospheric remote sensing and climate and weather modelling. In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus clouds. Together with a tool for identifying convective activity and a new cirrus tracking algorithm, CiPS is used to analyse the life cycle of 132 anvil cirrus clouds observed over southern Europe and northern Africa in July 2015. Although the anvil cirrus clouds grow optically thick during the convective phase, they become thinner at a rapid pace as convection ceases. Two hours after the last observed convective activity, 92±7 % of the anvil cirrus area has IOT_CiPS < 1 and IWP_CiPS < 30 g m−2 on average, with highest probability density around 0.1–0.2 and 1.5–3 g m−2 respectively. During the same time period, the cloud top height is observed to decrease. Since this is observed for both long-lived and short-lived anvil cirrus, it is deduced that in this life phase the amount of ice in the anvil is mainly controlled by sedimentation. This is in line with a corresponding decrease in the estimated effective radius. While the convective strength has no evident effect on the IOT and IWP, stronger vertical updraught is clearly correlated with higher cloud top height and larger effective radius. Larger ice crystals are, however, observed to be removed effectively within 2-3 h after convection has ceased, suggesting that the convective strength has no impact on the ice crystal sizes in ageing anvils. In this life stage, upper tropospheric relative humidity, as derived from ERA5 reanalysis data, is shown to have a larger impact on the anvil cirrus life cycle, where higher relative humidity govern larger and especially more long-lived anvil cirrus clouds

The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

Anvil cirrus clouds form in the upper troposphere from the outflow of ice crystals from deep convective cumulonimbus clouds. By reflecting incoming solar radiation as well as absorbing terrestrial thermal radiation, and re-emitting it at significantly lower temperatures, they play an important role for the Earth’s radiation budget. Nevertheless the processes that govern their life cycle are not well understood and, hence, they remain one of the largest uncertainties in atmospheric remote sensing and climate and weather modelling. In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus clouds. Together with a tool for identifying convective activity and a new cirrus tracking algorithm, CiPS is used to analyse the life cycle of 132 anvil cirrus clouds observed over southern Europe and northern Africa in July 2015. Although the anvil cirrus clouds grow optically thick during the convective phase, they become thinner at a rapid pace as convection ceases. Two hours after the last observed convective activity, 92±7 % of the anvil cirrus area has IOT_CiPS < 1 and IWP_CiPS < 30 g m−2 on average, with highest probability density around 0.1–0.2 and 1.5–3 g m−2 respectively. During the same time period, the cloud top height is observed to decrease. Since this is observed for both long-lived and short-lived anvil cirrus, it is deduced that in this life phase the amount of ice in the anvil is mainly controlled by sedimentation. This is in line with a corresponding decrease in the estimated effective radius. While the convective strength has no evident effect on the IOT and IWP, stronger vertical updraught is clearly correlated with higher cloud top height and larger effective radius. Larger ice crystals are, however, observed to be removed effectively within 2-3 h after convection has ceased, suggesting that the convective strength has no impact on the ice crystal sizes in ageing anvils. In this life stage, upper tropospheric relative humidity, as derived from ERA5 reanalysis data, is shown to have a larger impact on the anvil cirrus life cycle, where higher relative humidity govern larger and especially more long-lived anvil cirrus clouds

Spectral sizing of a coarse-spectral-resolution satellite sensor for XCO2

Verifying anthropogenic carbon dioxide (CO$_{2}$) emissions globally is essential to inform about the progress of institutional efforts to mitigate anthropogenic climate forcing. To monitor localized emission sources, spectroscopic satellite sensors have been proposed that operate on the CO$_{2}$ absorption bands in the shortwave-infrared (SWIR) spectral range with ground resolution as fine as a few tens of meters to about a hundred meters. When designing such sensors, fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, such sensors are envisioned to fly in fleets of satellites, requiring low-cost and simple design, e.g., by restricting the spectrometer to a single spectral band. Here, we use measurements of the Greenhouse Gases Observing Satellite (GOSAT) to evaluate the spectral resolution and spectral band selection of a prospective satellite sensor with fine ground resolution. To this end, we degrade GOSAT SWIR spectra of the CO$_{2}$ bands at 1.6 (SWIR-1) and 2.0 μm (SWIR-2) to coarse spectral resolution, without a further addition of noise, and we evaluate single-band retrievals of the column-averaged dry-air mole fractions of CO$_{2}$ (XCO$_{2}$) by comparison to ground truth provided by the Total Carbon Column Observing Network (TCCON) and by comparison to global “native” GOSAT retrievals with native spectral resolution and spectral band selection. Coarsening spectral resolution from GOSAT’s native resolving power of > 20000 to the range of 700 to a few thousand makes the scatter of differences between the SWIR-1 and SWIR-2 retrievals and TCCON increase moderately. For resolving powers of 1200 (SWIR-1) and 1600 (SWIR-2), the scatter increases from 2.4 (native) to 3.0 ppm for SWIR-1 and 3.3 ppm for SWIR-2. Coarser spectral resolution yields only marginally worse performance than the native GOSAT configuration in terms of station-to-station variability and geophysical parameter correlations for the GOSAT–TCCON differences. Comparing the SWIR-1 and SWIR-2 configurations to native GOSAT retrievals on the global scale, however, reveals that the coarseresolution SWIR-1 and SWIR-2 configurations suffer from some spurious correlations with geophysical parameters that characterize the light-scattering properties of the scene such as particle amount, size, height and surface albedo. Overall, the SWIR-1 and SWIR-2 configurations with resolving powers of 1200 and 1600 show promising performance for future sensor design in terms of random error sources while residual errors induced by light scattering along the light path need to be investigated further. Due to the stronger CO$_{2}$ absorption bands in SWIR-2 than in SWIR-1, the former has the advantage that measurement noise propagates less into the retrieved XCO$_{2}$ and that some retrieval information on particle scattering properties is accessible

Proceedings of the 4th International Conference on Transport, Atmosphere and Climate

The "4th International Conference on Transport, Atmosphere and Climate (TAC-4)" held in Bad Kohlgrub (Germany), 2015, was organised with the objective of updating our knowledge on the impacts of transport on the composition of the atmosphere and on climate, three years after the TAC-3 conference in Prien am Chiemsee (Germany). The TAC-4 conference covered all aspects of the impact of the different modes of transport (aviation, road transport, shipping etc.) on atmospheric chemistry, microphysics, radiation and climate, in particular

The Added Value of Large-Eddy and Storm-Resolving Models for Simulating Clouds and Precipitation

More than one hundred days were simulated over very large domains with fine (0.156 km to 2.5 km) grid spacing for realistic conditions to test the hypothesis that storm (kilometer) and large-eddy (hectometer) resolving simulations would provide an improved representation of clouds and precipitation in atmospheric simulations. At scales that resolve convective storms (storm-resolving for short), the vertical velocity variance becomes resolved and a better physical basis is achieved for representing clouds and precipitation. Similarly to past studies we found an improved representation of precipitation at kilometer scales, as compared to models with parameterized convection. The main precipitation features (location, diurnal cycle and spatial propagation) are well captured already at kilometer scales, and refining resolution to hectometer scales does not substantially change the simulations in these respects. It does, however, lead to a reduction in the precipitation on the time-scales considered – most notably over the ocean in the tropics. Changes in the distribution of precipitation, with less frequent extremes are also found in simulations incorporating hectometer scales. Hectometer scales appear to be more important for the representation of clouds, and make it possible to capture many important aspects of the cloud field, from the vertical distribution of cloud cover, to the distribution of cloud sizes, and to the diel (daily) cycle. Qualitative improvements, particularly in the ability to differentiate cumulus from stratiform clouds, are seen when one reduces the grid spacing from kilometer to hectometer scales. At the hectometer scale new challenges arise, but the similarity of observed and simulated scales, and the more direct connection between the circulation and the unconstrained degrees of freedom make these challenges less daunting. This quality, combined with already improved simulation as compared to more parameterized models, underpins our conviction that the use and further development of storm-resolving models offers exciting opportunities for advancing understanding of climate and climate change

The life cycle of anvil cirrus clouds from a combination of passive and active satellite remote sensing

In this thesis the temporal evolution of the anvil cirrus properties throughout their life cycle is investigated, as is their relationship with the meteorological conditions. For a comprehensive retrieval of the anvil cirrus properties, a new algorithm for the remote sensing of cirrus clouds called CiPS (Cirrus Properties from SEVIRI) is developed. Utilising a set of artificial neural networks, CiPS combines the large spatial coverage and high temporal resolution of the imaging radiometer SEVIRI aboard the geostationary satellites Meteosat Second Generation, with the high vertical resolution and sensitivity to thin cirrus clouds of the lidar CALIOP aboard the polar orbiting satellite CALIPSO. In comparison to CALIOP, CiPS detects 71 % and 95 % of all cirrus clouds with an ice optical thickness (IOT) of 0.1 and 1.0 respectively. Furthermore, CiPS retrieves the corresponding cloud top height, IOT, ice water path (IWP) and, by parameterisation, effective ice crystal radius. This way, macrophysical, microphysical and optical properties can be combined to interpret the temporal evolution of the anvil cirrus cloud

Global Land Water Mask

&lt;p&gt;This is a global land water mask dataset stored in a GeoTIFF file. Water surface types are stored as value 0, whereas land surface types are stored as value 100.&lt;/p&gt;&lt;p&gt;The land water mask has been generated using the Global Self-consistent Hierarchical High-resolution Geography (GSHHG, Version 2.3.7) dataset. To construct the land water mask the &lt;i&gt;intermediate &lt;/i&gt;(&lt;i&gt;i&lt;/i&gt;) resolution has been used and the following shoreline categories have been considered and used for the land/water classification :&lt;/p&gt;&lt;ul&gt;&lt;li&gt;L1: boundary between land and ocean, except Antarctica (continents) -&gt; land&lt;/li&gt;&lt;li&gt;L2: boundary between lake and land (lakes) -&gt; water&lt;/li&gt;&lt;li&gt;L3: boundary between island-in-lake and lake (islands in lakes) -&gt; land&lt;/li&gt;&lt;li&gt;L6: boundary between Antarctica grounding-line and ocean (Antarctica) -&gt; land&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;Hence ponds on islands (L4) are ignored and consequently classified as land and Antarctic sea ice (L5) is classified as water. Furthermore, the shapefiles for rivers have not been used, meaning that rivers are not resolved in this dataset and thus classified as land.&lt;/p&gt;&lt;p&gt;The land water mask dataset has been stored in a GeoTIFF file with global coverage (-90 to 90 degrees North and -180 to 180 degrees East) and a geographic coordinate system referenced to the WGS84 datum (proj4 string: '+proj=longlat +datum=WGS84 +no_defs +type=crs'). The GeoTIFF image has the shape 6750 x 13500 pixels meaning that the dataset has a resolution of 0.0267 degrees or approx. 3 km (at the equator).&lt;/p&gt