Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains

Root Mean Square Errors (RMSE) in the soil moisture anomaly time series obtained from the Advanced Scatterometer (ASCAT) and the Advanced Microwave Scanning Radiometer (AMSR-E; using the Land Parameter Retrieval Model) are estimated over a continental scale domain centered on North America, using two methods: triple colocation (RMSETC ) and error propagation through the soil moisture retrieval models (RMSEEP ). In the absence of an established consensus for the climatology of soil moisture over large domains, presenting a RMSE in soil moisture units requires that it be specified relative to a selected reference data set. To avoid the complications that arise from the use of a reference, the RMSE is presented as a fraction of the time series standard deviation (fRMSE). For both sensors, the fRMSETC and fRMSEEP show similar spatial patterns of relatively highlow errors, and the mean fRMSE for each land cover class is consistent with expectations. Triple colocation is also shown to be surprisingly robust to representativity differences between the soil moisture data sets used, and it is believed to accurately estimate the fRMSE in the remotely sensed soil moisture anomaly time series. Comparing the ASCAT and AMSR-E fRMSETC shows that both data sets have very similar accuracy across a range of land cover classes, although the AMSR-E accuracy is more directly related to vegetation cover. In general, both data sets have good skill up to moderate vegetation conditions

GLEAM v3 : satellite-based land evaporation and root-zone soil moisture

The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C-and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land-atmosphere feedbacks

Towards estimating land evaporation at field scales using GLEAM

The evaporation of water from land into the atmosphere is a key component of the hydrological cycle. Accurate estimates of this flux are essential for proper water management and irrigation scheduling. However, continuous and qualitative information on land evaporation is currently not available at the required spatio-temporal scales for agricultural applications and regional-scale water management. Here, we apply the Global Land Evaporation Amsterdam Model (GLEAM) at 100 m spatial resolution and daily time steps to provide estimates of land evaporation over The Netherlands, Flanders, and western Germany for the period 2013-2017. By making extensive use of microwave-based geophysical observations, we are able to provide data under all weather conditions. The soil moisture estimates from GLEAM at high resolution compare well with in situ measurements of surface soil moisture, resulting in a median temporal correlation coefficient of 0.76 across 29 sites. Estimates of terrestrial evaporation are also evaluated using in situ eddy-covariance measurements from five sites, and compared to estimates from the coarse-scale GLEAM v3.2b, land evaporation from the Satellite Application Facility on Land Surface Analysis (LSA-SAF), and reference grass evaporation based on Makkink's equation. All datasets compare similarly with in situ measurements and differences in the temporal statistics are small, with correlation coefficients against in situ data ranging from 0.65 to 0.95, depending on the site. Evaporation estimates from GLEAM-HR are typically bounded by the high values of the Makkink evaporation and the low values from LSA-SAF. While GLEAM-HR and LSA-SAF show the highest spatial detail, their geographical patterns diverge strongly due to differences in model assumptions, model parameterizations, and forcing data. The separate consideration of rainfall interception loss by tall vegetation in GLEAM-HR is a key cause of this divergence: while LSA-SAF reports maximum annual evaporation volumes in the Green Heart of The Netherlands, an area dominated by shrubs and grasses, GLEAM-HR shows its maximum in the national parks of the Veluwe and Heuvelrug, both densely-forested regions where rainfall interception loss is a dominant process. The pioneering dataset presented here is unique in that it provides observational-based estimates at high resolution under all weather conditions, and represents a viable alternative to traditional visible and infrared models to retrieve evaporation at field scales

Adaptation of transferrin protein and glycan synthesis

We report the patterns of variability in transferrin structure in pregnancy, iron deficiency anemia, women using oral contraceptives, nonanaemic rheumatoid arthritis, iron deficient rheumatoid arthritis and anemia of the chronic diseases. Changes in microheterogeneity were assessed by crossed immuno isoelectric focusing of serum transferrin. Intra-individual variation in the control group was minimal. Equally, inter-individual variation in controls and groups with established stable disease was very limited. In pregnancy an increase in transferrin concentration was accompanied by redirection of glycan synthesis to the highly sialylated and highly branched glycans, an effect also shown in women using oral contraceptives. Iron deficiency anemia was accompanied by increased protein core synthesis without the large shifts in the microheterogeneity pattern as seen in pregnancy at similar transferrin concentration. In contrast to this, rheumatoid arthritis was accompanied by decreased protein synthesis while the microheterogeneity pattern shifted significantly towards the highly branched glycans. Interpreted in the respective pathophysiological contexts results show that: (1) N-linked glycosylation of transferrin is a strictly controlled process, both in the physiological states and in disease. (2) Microheterogeneity is determined independently from transferrin protein synthetic rate. (3) Provisionally observed changes in the glycosylation can modulate the biological activity of the glycoprotein and as a result redirect internal iron fluxes. This proposition can be applied to altered iron metabolism in both pregnancy, oral contraceptives and rheumatoid arthritis. Changes are not operative in iron deficiency because qualitatively iron metabolism is not altered in this state

Evaluating global trends (1988-2010) in harmonized multi-satellite surface soil moisture

[1] Global trends in a new multi-satellite surface soil moisture dataset were analyzed for the period 1988–2010. 27% of the area covered by the dataset showed significant trends (p = 0.05). Of these, 73% were negative and 27% positive. Subtle drying trends were found in the Southern US, central South America, central Eurasia, northern Africa and the Middle East, Mongolia and northeast China, northern Siberia, and Western Australia. The strongest wetting trends were found in southern Africa and the subarctic region. Intra-annual analysis revealed that most trends are not uniform among seasons. The most prominent trend patterns in remotely sensed surface soil moisture were also found in GLDAS-Noah and ERA Interim modeled surface soil moisture and GPCP precipitation, lending confidence to the obtained results. The relationship with trends in GIMMS-NDVI appeared more complex. In areas of mutual disagreement more research is needed to identify potential deficiencies in models and/or remotely sensed products

Photographic Work Exhibited in 'Parrworld: the Collection of Martin Parr', Haus der Kunst, Munich, Germany, (7 May – 17 August 2008), curated by Thomas Weski, then touring to Breda Design Museum, The Netherlands (26 September 2008 - 6 January 2009); Jeu de Paume, Paris (30 June - 27 September 2009) and The Baltic, Gateshead, UK (16 October 2009 - 17 January 2010)

Photographic work from the series 'Rays a Laugh' was exhibited in 'Parrworld: the Collection of Martin Parr', Haus der Kunst, Munich, Germany, (7 May – 17 August 2008), curated by Thomas Weski, then touring to Breda Design Museum, The Netherlands (26 September 2008 - 6 January 2009); Jeu de Paume, Paris (30 June 2009 - 27 September 2009) and The Baltic, Gateshead, UK (16 October 2009 - 17 January 2010) This touring show analysed photography as a contemporary medium and included photographic works by Parr, works from his own collection including Jill Constantine, Paul Graham, Chris Killip, Graham Smith, Mark Neville, David Goldblatt, William Eggleston, Frank Breuer, Gary Winogrand and Bernd and Hilla Becher and other collections. These included postcards and personally collected objects with a fascination for the peculiar and the curious. The assortment of commercial design and memorabilia documented key historical and political moments, for example, original posters and leaflets from the 1984 UK miners strike, a collection of commemorative china from Margaret Thatcher’s term as Prime Minister, examples of prayer mats featuring the New York Twin Towers, a range of Saddam Hussein watches and a collection of Barack Obama ephemera. There was a fully illustrated two volume hard back catalogue of the exhibition printed by Aperture

The Millennium Drought in southeast Australia (2001-2009): Natural and human causes and implications for water resources, ecosystems, economy, and society

The "Millennium Drought" (2001-2009) can be described as the worst drought on record for southeast Australia. Adaptation to future severe droughts requires insight into the drivers of the drought and its impacts. These were analyzed using climate, water

Changing Climate and Overgrazing Are Decimating Mongolian Steppes

Satellite observations identify the Mongolian steppes as a hotspot of global biomass reduction, the extent of which is comparable with tropical rainforest deforestation. To conserve or restore these grasslands, the relative contributions of climate and human activities to degradation need to be understood. Here we use a recently developed 21-year (1988-2008) record of satellite based vegetation optical depth (VOD, a proxy for vegetation water content and aboveground biomass), to show that nearly all steppe grasslands in Mongolia experienced significant decreases in VOD. Approximately 60% of the VOD declines can be directly explained by variations in rainfall and surface temperature. After removing these climate induced influences, a significant decreasing trend still persists in the VOD residuals across regions of Mongolia. Correlations in spatial patterns and temporal trends suggest that a marked increase in goat density with associated grazing pressures and wild fires are the most likely non-climatic factors behind grassland degradation.Funding for this research was through a University of New South Wales International Postgraduate Award and CSIRO Water for a Healthy Country Flagship Program scholarship. The data used in Figure 3b were supported through the Research Institute for Humanity and Nature (project number D-04). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Understanding Sentinel-1 Backscatter Response to Sugarcane Yield Variability and Waterlogging

Sentinel-1 observes the whole globe every 12 days (6 days when both satellites were operational) and provides a wealth of data relevant to agriculture. Sugarcane cultivators could potentially benefit from these data by using them to assist operational and management practices. However, first, thorough understanding is needed of Sentinel-1 backscatter and its behavior over sugarcane canopies. In this study, we aimed to improve understanding of how Sentinel-1 backscatter responds to sugarcane yield variability and waterlogging. In order to do so we focused on an irrigated sugarcane plantation in Xinavane, Mozambique. In the analysis presented, we assessed different polarizations, their ratio, and benchmarked them against optical indices and passive microwave observations in different seasons. With the help of a large sugarcane yield dataset, we analyzed how backscatter relates to sucrose yield variability in different seasons. We found VV backscatter related to the stalk development, the most important reservoir for sucrose accumulation. In addition, in a season with reported waterlogging, optical and radar observations showed a delay in sugarcane crop development. Further analysis showed the presence of water underneath the canopy caused an increase in all polarizations and the cross ratio (CR). The results imply that Sentinel-1 backscatter contains information on both waterlogging under the canopy as well as sucrose development in the stalk. By isolating and quantifying the impact of waterlogging on backscatter, it will be possible to further quantify sucrose development with backscatter observations and identify waterlogging simultaneously.Peer reviewe