ALBERT

Beschreibung: Shortwave Infrared (SWIR) imaging spectroscopy enables accurate remote mapping of cloud thermodynamic phase at high spatial resolution. We describe a measurement strategy to exploit signatures of liquid and ice absorption in cloud top apparent reflectance spectra from 1.4-1.8  μ m. This signal is generally insensitive to confounding factors such as solar angles, view angles, and surface albedo. We first evaluate the approach in simulation, and then apply it to airborne data acquired in the Calwater-2 / ACAPEX campaign of Winter 2015. Here, NASA's “Classic” Airborne Visible Infrared Imaging Spectrometer (AVIRIS-C) remotely observed diverse cloud formations while the US Department of Energy ARM Aerial Facility (AAF) G-1 aircraft measured cloud integral and microphysical properties in situ . The coincident measurements demonstrate good separation of the thermodynamic phases for relatively homogeneous clouds.

Beschreibung: The bi-spectral method retrieves cloud optical thickness ( τ ) and cloud droplet effective radius ( r e ) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and r e . In the literature, the retrievals of τ and r e are often assumed to be independent and considered separately when investigating the impact of sub-pixel cloud reflectance variations on the bi-spectral method. As a result, the impact on τ is contributed only by the sub-pixel variation of VIS/NIR band reflectance and the impact on r e only by the sub-pixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and r e retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and r e retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the r e retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in r e retrievals, leading to a potential contribution of positive bias to the r e retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from MODIS. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from sub-pixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and r e retrievals between two instruments.

Beschreibung: [1]  We propose and demonstrate a new approach for the simulation of woody ecosystem stand dynamics, demography and disturbance-mediated heterogeneity suitable for continental to global applications and designed for coupling to the terrestrial ecosystem component of any earth system model. The approach is encoded in a model called Populations-Order-Physiology (POP). We demonstrate the behaviour and performance of POP coupled to the Community Atmosphere Biosphere Land Exchange model (CABLE) applied along the Northern Australian Tropical Transect, featuring gradients in rainfall and fire disturbance. The model is able to simultaneously reproduce observation-based estimates of key functional and structural variables along the transect, namely gross primary production, tree foliage projective cover, basal area and maximum tree height. Prospects for the use of POP to address current vegetation dynamic deficiencies in earth system modeling are discussed.

Beschreibung: The regional haze over the southeast (SE) Atlantic Ocean induced by biomass burning in southern Africa can be problematic for passive imager-based retrievals of the underlying quasi-permanent marine boundary layer (MBL) clouds and for estimates of top-of-atmosphere (TOA) aerosol direct radiative effect (DRE). Here, an algorithm is introduced to simultaneously retrieve above-cloud aerosol optical thickness (AOT) and the cloud optical thickness (COT) and effective particle radius (CER) of the underlying MBL clouds while also providing pixel-level estimates of retrieval uncertainty. This approach utilizes reflectance measurements at six MODIS channels from the visible to the shortwave infrared. Retrievals are run under two aerosol model assumptions on eight years (2006–2013) of June-October Aqua MODIS data over the SE Atlantic, from which a regional cloud and above-cloud aerosol climatology is produced. The cloud retrieval methodology is shown to yield COT and CER consistent with those from the MODIS operational cloud product (MOD06) when forcing AOT to zero, while the full COT-CER-AOT retrievals that account for the above-cloud aerosol attenuation increase regional monthly mean COT and CER by up to 9% and 2%, respectively. Retrieved AOT is roughly 3 to 5 times larger than the collocated 532nm CALIOP retrievals, though closer agreement is observed with the CALIOP 1064nm retrievals, a result consistent with previous case study analyses. Regional cloudy sky above-cloud aerosol DRE calculations are also performed that illustrate the importance of the aerosol model assumption and underlying cloud retrievals.

Beschreibung: The P ersonal ER ythemal EX posure (PEREX) model for seafarers working on decks of vessels has been developed to be used for retrospective estimates of personal occupational erythemal exposure in dependence of work-profile, time period and sea route. Extremely high UV index values up to 22 and daily erythemal exposure up to 89 SED (Standard Erythemal Dose) have been derived from ship-based measurements in tropical oceans. Worldwide climatological maps of daily solar erythemal exposure derived from 10-year (2004 – 2013) hourly grid-point radiative transfer model calculations for both cloudless sky and cloudy sky serve as the data base of PEREX. The PEREX data base is compared with ship-based measurements taken along 4 routes of merchant vessels, continuous UV radiation measurements taken on the Research Vessel METEOR on its mainly tropical and subtropical routes for two years, daily cloudless-sky erythemal exposure derived from 10-minute LibRadtran radiative transfer model calculations, and two years of satellite-based erythemal exposure data of the Ozone Monitoring Instrument on the Aura satellite along the ship routes. Systematic differences between PEREX model data, ship-based data and satellite-based daily erythemal exposure for all-sky conditions are only 1 to 3%, while short-term variations of cloudiness results in standard deviations of differences around 30%. Measured ratios between cloudless-sky erythemal radiation at vertical to horizontal incidence decrease with decreasing solar zenith angle, while clouds flatten their diurnal course.

Beschreibung: MODIS retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a pre-computed look-up-table (LUT). When observations fall outside of the LUT, the retrieval is considered “ failed ” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on one year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86μm and 2.1μm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86μm and 3.7μm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade-wind cumulus regimes. The leading type of failure is the “ r e too large” failure accounting for 60%~85% of all failed retrievals. The rest is mostly due to the “ r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high sub-pixel inhomogeneity, are located at special sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Beschreibung: Using short-temporal baseline interferometric synthethic aperture radar (InSAR), we capture instantaneous images of a persistent field of infragravity waves propagating through sea ice near Barrow, Alaska, during January 2015. We estimate wave amplitudes to be between 1.2 – 1.8 mm. Curvature of wave fronts is consistent with refraction of waves entering shallow water from a source region north of Barrow. A shallow water wave model indicates the geometry of the wave fronts is relatively insensitive to the source location, but other evidence suggests the waves may have originated in the North Atlantic, making this perhaps the longest observed propagation path for waves through ice. We also note that steepening of the waves entering shallow water can increase the peak strain by an order of magnitude, suggesting that infragravity waves may play a role in determining the location of the landfast ice edge with respect to water depth.

Beschreibung: Abstract Ship‐tracks appear as long winding linear features in satellite images and are produced by aerosols from ship exhausts changing low cloud properties. They are one of the best examples of aerosol‐cloud interaction experiments. However, manually finding ship‐tracks from satellite data on a large‐scale is prohibitively costly while a large number of samples are required. Here we train a deep neural network to automate finding ship‐tracks. The neural network model generalizes well as it not only finds ship‐tracks labeled by human experts, but also detects those that are occasionally missed by humans. It finds more ship‐tracks than all previous studies combined and produces a map of ship‐track distributions off the California coast that matches well with known shipping traffic. Our technique will enable studying aerosol effects on low clouds using ship‐tracks on a large‐scale, which will potentially narrow the uncertainty of the aerosol‐cloud interactions.

Beschreibung: Abstract The degree of Hadley cell expansion under global warming will have a substantial impact on changing rainfall patterns. Most previous studies have quantified changes in total tropical width, focused on the Southern Hemisphere Hadley cell or considered each hemisphere's response to a multitude of anthropogenic forcings. It is shown here that under exclusive CO2 forcing, climate models predict twice as much Hadley cell expansion in the Southern Hemisphere relative to the Northern Hemisphere. This asymmetry is present in the annual‐mean expansion and all seasons except boreal autumn. It is robust across models and Hadley cell edge definitions. It is surprising since asymmetries in simulated Hadley cell expansion are typically attributed to stratospheric ozone depletion or aerosol emission. Its primary cause is smaller sensitivity of the Northern Hemisphere Hadley cell to static stability changes. The pattern of sea surface warming and the CO2 direct radiative effect also contribute to the asymmetry.

Beschreibung: [1]  Atmospheric phase delays are considered to be one of the main performance limitations for high-quality satellite radar techniques, especially when applied to ground deformation monitoring. Numerical weather prediction (NWP) models are widely seen as a promising tool for the mitigation of atmospheric delays as they can provide knowledge of the atmospheric conditions at the time of Synthetic Aperture Radar (SAR) data acquisition. However, a thorough statistical analysis of the performance of using NWP production in radar signal correction is missing to date. This study provides a quantitative analysis of the accuracy in using operational NWP products for signal delay correction in satellite radar geodetic remote sensing. The study focuses on the temperate, subarctic and Arctic climate regions due to a prevalence of relevant geophysical signals in these areas. In this study, the operational High Resolution Rapid Refresh over the Alaska region (HRRR-AK) model is used and evaluated. Five test sites were selected over Alaska (AK), USA, covering a wide range of climatic regimes that are commonly encountered in high latitude regions. The performance of the HRRR-AK NWP model for correcting absolute atmospheric range delays of radar signals is assessed by comparing to radiosonde observations. The average estimation accuracy for the one-way zenith total atmospheric delay from 24 hour simulations was calculated to be better than ~14 mm. This suggests that the HRRR-AK operational products are a good data source for spaceborne geodetic radar observations atmospheric delay correction, if the geophysical signal to be observed is larger than 20 mm.