ALBERT

Description: The satellite-derived HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data) and ECMWF (European Centre for Medium-Range Weather Forecasts) ERA-Interim reanalysis data sets have been validated against in situ precipitation measurements from ship rain gauges and optical disdrometers over the open ocean by applying a statistical analysis for binary estimates. For this purpose collocated pairs of data were merged within a certain temporal and spatial threshold into single events, according to the satellites' overpass, the observation and the ERA-Interim times. HOAPS detects the frequency of precipitation well, while ERA-Interim strongly overestimates it, especially in the tropics and subtropics. Although precipitation rates are difficult to compare because along-track point measurements are collocated with areal estimates and the number of available data are limited, we find that HOAPS underestimates precipitation rates, while ERA-Interim's Atlantic-wide average precipitation rate is close to measurements. However, when regionally averaged over latitudinal belts, deviations between the observed mean precipitation rates and ERA-Interim exist. The most obvious ERA-Interim feature is an overestimation of precipitation in the area of the intertropical convergence zone and the southern subtropics over the Atlantic Ocean. For a limited number of snow measurements by optical disdrometers, it can be concluded that both HOAPS and ERA-Interim are suitable for detecting the occurrence of solid precipitation.

Description: The present increase in average Arctic (60°-90°N) surface temperature is almost three times as high as the corresponding global average increase. An accelerated temperature rise was also observed at the beginning of the 20th century (1910-1940, ECW) and is referred to as "Arctic Amplication". It was followed by a sharp temperature decrease (1940-1970) with following warming. Its trend has only recently been exceeded by the current Arctic warming. The underlying mechanisms which produce such multidecadal climate variability are presently under debate. It is suggested that the ECW was driven by natural coupling mechanisms within the climate system. In this context it might have be linked to changing westerlies in the North Atlantic, anomalies of the Atlantic meridional overturning circulation as well as changes in sea surface temperatures of the tropical Pacic (NAO, MOC and NINO3, respectively). Since the Arctic climate system seems to play a crucial role with respect to global warming, further analysis is required in order to understand its origin. For the purposes of this study, three control simulations (1500 yrs. of integrations each) were analysed which dffer in complexity in sense of coupling between atmosphere and ocean components. These are a fully coupled atmospheric-seaice-ocean GCM (ECHAM5/MPI-OM), an atmospheric GCM coupled with a thermodynamical mixed-layer ocean model including a thermodynamical seaice model (ECHAM5/MLO) and an atmospheric GCM forced by prescribed lower boundary conditions (ECHAM5/xed-SST). The annual means of anomalies of Arctic surface temperature (SAT) and sea ice extent (ICE) were analysized with respect to the different runs and their links to the major possible climate variability drives such as NAO-, MOC- and NINO3-variability. The objective was to assess the impact of coupling between ocean and atmosphere concerning driving mechanisms of (multi-) decadal variability, using statistical tools like correlation, coherence and wavelet-analysis. The results show that the coupled model produces several multidecadal variabilities which might be particularly concentrated in the Barents Sea region. In this context, a low-frequency oscillation of SAT- and ICE-anomalies might represent an eigenmode of variability in the Arctic climate system. Arctic climate variability is further driven by MOC-uctuations which leads Arctic SAT-changes by four years. Furthermore, NINO3- and SAT-anomalies seem to be linked via atmospheric teleconnections with a time lag of several months. Additionally, SAT- and NAO-changes are suggested to be linked on decadal variability scale. Multidecadal Oscillations can hardly be resolved when excluding large-scale ocean dynamics, corresponding to the ECHAM5/MLO - controll run. Nevertheless, Arctic SAT- and NINO3-uctuations cohere signicantly, possibly producing hyper-modes which inuence the Arctic climate via teleconnections. Additionally, NAO- and SAT-changes seem to be related with a time lag of a few months, whereas NAO-anomalies impact Arctic SAT-changes on an intraseasonal timescale. An entire exclusion of interaction between ocean and atmosphere (ECHAM5/xed-SST, respectively) prohibits any kind of (multi-) decadal variability which emphasizes the significance of coupling. This can also be seen in the simulation results of the landmass regions. Corresponding variabilities remain low and do not depend on the model run's complexity.

Description: Latent heat fluxes (LHF) play an essential role in the global energy budget and are thus important for understanding the climate system. Satellite-based remote sensing permits a large-scale determination of LHF, which, amongst others, are based on near-surface specific humidity qa. However, the qa random retrieval error (Etot) remains unknown. Here, a novel approach is presented to quantify the error contributions to pixel-level qa of the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite (HOAPS, version 3.2) dataset. The methodology makes use of multiple triple collocation (MTC) analysis between 1995-2008 over the global ice-free oceans. Apart from satellite records, these datasets include selected ship records extracted from the Seewetteramt Hamburg (SWA) archive and the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), serving as the in-situ ground reference. The MTC approach permits the derivation of Etot as the sum of model uncertainty EM and sensor noise EN, while random uncertainties due to in-situ measurement errors (Eins) and collocation (EC) are isolated concurrently. Results show an Etot average of 1.1 ± 0.3 g kg-1, whereas the mean EC (Eins) is in the order of 0.5 ± 0.1 g kg-1 (0.5 ± 0.3 g kg-1). Regional analyses indicate a maximum of Etot exceeding 1.5 g kg-1 within humidity regimes of 12-17 g kg-1, associated with the single-parameter, multilinear qa retrieval applied in HOAPS. Multi-dimensional bias analysis reveals that global maxima are located off the Arabian Peninsula.