The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlie…The seasonal ice-free period in the Hudson Bay Complex (HBC) has grown longer in recent decades in response to warming, both from progressively earlier sea-ice retreat in summer and later sea-ice advance in fall. Such changes disrupt the HBC ecosystem and ice-based human activities. In this study, we compare 102 simulations from 37 models participating in phase 6 of the Coupled Model Intercomparison Project to the satellite passive microwave record and atmospheric reanalyses. We show that, throughout the HBC, models simulate an ice-free period that averages 30 d longer than in satellite observations. This occurs because seasonal sea-ice advance is unrealistically late and seasonal sea-ice retreat is unrealistically early. We find that much of the ice-season bias can be linked to a warm bias in the atmosphere that is associated with a southerly wind bias, especially in summer. Many models also exhibit an easterly wind bias during winter and spring, which reduces sea-ice convergence on the east side of Hudson Bay and impacts the spatial patterns of summer sea-ice retreat. These results suggest that, for many models, more realistic simulation of atmospheric circulation would improve their simulation of HBC sea ice.more
The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility-European Space Agency-Cli…The European Organisation for the Exploitation of Meteorological Satellites-Ocean and Sea Ice Satellite Application Facility-European Space Agency-Climate Change Initiative (EUMETSAT-OSISAF-ESA-CCI) Level-4 sea-ice concentration (SIC) climate data records (CDRs), named SICCI-25km, SICCI-50km and OSI-450, provide gridded SIC error estimates in addition to SIC. These error estimates, called total error henceforth, comprise a random, uncorrelated error contribution from retrieval and sensor noise, aka the algorithm standard error, and a locally-to-regionally correlated contribution from gridding and averaging Level-2 SIC into the Level-4 SIC CDRs, aka the representativity error. However, these CDRs do not yet provide an error covariance matrix. Therefore, correlation scales of these error contributions and the total error in particular are unknown. In addition, larger-scale SIC errors due to, e.g., unaccounted weather influence or mismatch between the actual ice type and the algorithm setup are neither well represented by the total error, nor are their correlation scales known for these CDRs. In this study, I attempt to contribute to filling this knowledge gap by deriving spatial correlation length scales for the total error and the large-scale SIC error for high-concentration pack ice. For every grid cell with > 90% SIC, I derive circular one-point correlation maps of 1000 km radius by computing the cross-correlation between the central 31-day time series of the errors and all other 31-day error time series within that circular area (disc) with 1000 km radius. I approximate the observed decrease in the correlation away from the disc's center with an exponential function that best fits this decrease and thereby obtain the correlation length scale L sought. With this approach, I derive L separately for the total error and the large-scale SIC error for every high-concentration grid cell, and map, present and discuss these for the Arctic and the Southern Ocean for the year 2010 for the above-mentioned products. I find correlation length scales are substantially smaller for the total error, mostly below ∼200 km, than the SIC error, ∼200 km to ∼700 km, in both hemispheres. I observe considerable spatiotemporal variability of the SIC error correlation length scales in both hemispheres and provide first directions to explain these. For SICCI-50km, I present the first evidence of the method's robustness for other years and time series of L for 2003-2010.more
The limited number of in situ stations of surface soil moisture (SM) in Africa creates a shortage in the validation of SM satellite products. Therefor…The limited number of in situ stations of surface soil moisture (SM) in Africa creates a shortage in the validation of SM satellite products. Therefore, this study investigates the performance of Soil Moisture Active Passive (SMAP), Soil Moisture and Ocean Salinity (SMOS), and the H113 product from the Advanced Scatterometer (ASCAT) on the regional scale over Africa through these goals: (1) validate of satellite SM products against in situ stations and SM data from the ERA-Interim atmospheric reanalysis product, (2) study the spatiotemporal variability of satellite SM products on the regional scale, and (3) evaluate the regional scale error patterns and investigate regions where the assimilation of satellites SM data may add improvement to ERA-Interim. Standard statistical metrics, hovmöller diagrams, and the Triple Collocation (TC) model were used to achieve these goals. Land cover data, Normalized Difference Vegetation Index, and precipitation data were used to interpret results. The validation results based on statistical metrics and TC indicate that over the desert and shrub, passive products showed better performance than ASCAT, while over moderate vegetation areas (grassland), SMAP had the best among SM products. Over high densely vegetated regions, ASCAT showed a high comparatively performance than passive products. The potential regions for assimilation of satellite data sets were selected to be over savannas and grassland regions for ASCAT, and over shrub and grassland regions for SMAP. In particular, SMAP and ASCAT SM data sets are considered more stable than SMOS for data assimilation and capturing the spatial distribution of SM on the regional scale over Africa.more
In recent years, electricity production from wind turbines and photovoltaic systems has grown significantly in Germany. To determine the multiple impa…In recent years, electricity production from wind turbines and photovoltaic systems has grown significantly in Germany. To determine the multiple impacts of rising variable renewable energies on an increasingly decentralized power supply, spatially and temporally resolved data on the power generation are necessary or, at least, very helpful. Because of extensive data protection regulations in Germany, especially for smaller operators of renewable power plants, such detailed data are not freely accessible. In order to fill this information gap, simulation models employing publicly available plant and weather data can be used. The numerical simulations are performed for the year 2016 and consider an ensemble of almost 1.64 million variable renewable power plants in Germany. The obtained time series achieve a high agreement with measured feed-in patterns over the investigated year. Such disaggregated power generation data are very advantageous to analyze the energy transition in Germany on a spatiotemporally resolved scale. In addition, this study also derives meaningful key figures for such an analysis and presents the generated results as detailed maps at county level. To the best of our knowledge, such highly resolved electricity data of variable renewables for the entire German region have never been shown before.more
Incoming solar radiation is the most important factor shaping climate system on Earth and the main element of the surface heat balance. The main aim o…Incoming solar radiation is the most important factor shaping climate system on Earth and the main element of the surface heat balance. The main aim of this study was to investigate the changes in the amount of global solar radiation reaching the Earth's surface in Poland during the 30-year period 1986–2015. Trends in changes and fluctuations in the size of global solar radiation over Poland were determined. The solar radiation was described based on satellite products originating from the Surface Incoming Shortwave Radiation product from the Surface Solar Radiation Data Set – Heliosat, Edition 2 (SARAH-2). The average annual sum of global solar radiation over Poland amounted to 3,902 MJ·m−2. The average annual radiation sums were the smallest in northern Poland and mountain basins, while they were the largest in southern Poland. The average annual radiation sum over Poland increased by 7.16 MJ·m−2·year−1 on average. The areas with the largest increase in the amount of solar radiation had the smallest average radiation sums during the multi-year period (Pomerania, Northern Poland), and those where the increase in radiation was moderate had the highest average radiation sums (Central and Southern Poland). This shows that the spatial differentiation of the amount of solar radiation over Poland was gradually decreasing during this period. A several-year cycle (of 12–13 years) of annual fluctuations in global solar radiation sums was observed using wavelet analysis. The cycle was visible between the early 1990s and 2005. It resulted from the medium-term cyclical component (an 11.3-year cycle which was the strongest until 2010) that occurred in summer. In the long term, the occurrence of cycles in the time series of solar radiation may result from cyclical or quasi-cyclical changes in aerosol concentration, but this requires a separate study and further in-depth research based on much longer data series.more
Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. Howe…Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. However, there are also local emission sources such as coal and diesel power plants, snowmobiles and ships, but their influence on the background concentrations of trace gases has not been thoroughly assessed. This study is based on data of tropospheric ozone (O-3) and nitrogen oxides (NOx) collected in three main Svalbard settlements in spring 2017. In addition to these ground-based observations and radiosonde and O-3 sonde soundings, ERAS reanalysis and BrO satellite data have been applied in order to distinguish the impact of local and synoptic-scale conditions on the NOx and O-3 chemistry. The measurement campaign was divided into several sub-periods based on the prevailing large-scale weather regimes. The local wind direction at the stations depended on the large-scale conditions but was modified due to complex topography. The NOx concentration showed weak correlation for the different stations and depended strongly on the wind direction and atmospheric stability. Conversely, the O-3 concentration was highly correlated among the different measurement sites and was controlled by the long-range atmospheric transport to Svalbard. Lagrangian backward trajectories have been used to examine the origin and path of the air masses during the campaign.more