Evaluating anemometer drift: A statistical approach to correct biases in wind speed measurement

Recent studies on observed wind variability have revealed a decline (termed “stilling”) of near-surface wind speed during the last 30–50 years over many mid-latitude terrestrial regions, particularly in the Northern Hemisphere. The well-known impact of cup anemometer drift (i.e., wear on the bearings) on the observed weakening of wind speed has been mentioned as a potential contributor to the declining trend. However, to date, no research has quantified its contribution to stilling based on measurements, which is most likely due to lack of quantification of the ageing effect. In this study, a 3-year field experiment (2014–2016) with 10-minute paired wind speed measurements from one new and one malfunctioned (i.e., old bearings) SEAC SV5 cup anemometer which has been used by the Spanish Meteorological Agency in automatic weather stations since mid-1980s, was developed for assessing for the first time the role of anemometer drift on wind speed measurement. The results showed a statistical significant impact of anemometer drift on wind speed measurements, with the old anemometer measuring lower wind speeds than the new one. Biases show a marked temporal pattern and clear dependency on wind speed, with both weak and strong winds causing significant biases. This pioneering quantification of biases has allowed us to define two regression models that correct up to 37% of the artificial bias in wind speed due to measurement with an old anemometer

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

Surface water numerical modelling for the Gloucester subregion. Product 2.6.1 for the Gloucester subregion from the Northern Sydney Basin Bioregional Assessment

No abstract available

Surface winds - (i) Land surface winds and atmospheric evaporative demand

International audienc

Where does all the water go? Partitioning water transmission losses in a data-sparse, multi-channel and low-gradient dryland river system using modelling and remote sensing

Drylands cover approximately one-third of the Earth's surface, are home to nearly 40% of the Earth's population and are characterised by limited water resources and ephemeral river systems with an extremely variable flow regime and high transmission losses. These losses include actual evaporation, infiltration to the soil and groundwater and residual (terminal) water remaining after flood events. These critical components of the water balance of dryland river systems remain largely unknown due to the scarcity of observational data and the difficulty in accurately accounting for the flow distribution in such large multi-channel floodplain systems. While hydrodynamic models can test hypotheses concerning the water balance of infrequent flood events, the scarcity of flow measurement data inhibits model calibration, constrains model accuracy and therefore utility. This paper provides a novel approach to this problem by combining modelling, remotely-sensed data, and limited field measurements, to investigate the partitioning of flood transmissions losses based on seven flood events between February 2006 and April 2012 along a 180. km reach of the Diamantina River in the Lake Eyre Basin, Australia. Transmission losses were found to be high, on average 46% of total inflow within 180. km reach segment or 7. GL/km (range: 4-10. GL/km). However, in 180. km reach, transmission losses vary non-linearly with flood discharge, with smaller flows resulting in higher losses (up to 68%), which diminish in higher flows (down to 24%) and in general there is a minor increase in losses with distance downstream. Partitioning these total losses into the major components shows that actual evaporation was the most significant component (21.6% of total inflow), followed by infiltration (13.2%) and terminal water storage (11.2%). Lateral inflow can be up to 200% of upstream inflow (mean. =. 86%) and is therefore a critical parameter in the water balance and transmission loss calculations. This study shows that it is possible to constrain the water balance using hydrodynamic models in dryland river systems using remote sensing and simple field measurements to address the otherwise scarce availability of data. The results of this study also enable a better understanding of the water resources available for ecosystems in these unique multi-channel and large floodplain rivers. The combined modelling/remote sensing approach of this study can be applied elsewhere in the world to better understand the water balances and water transmission losses, important drivers of ecohydrological processes in dryland environments. © 2015 Elsevier B.V

The impact of forest regeneration on streamflow in 12 meso-scale humid tropical catchments

Although regenerating forests make up an increasingly large portion of humid tropical landscapes, little is known of their water use and effects on streamflow (Q). Since the 1950s the island of Puerto Rico has experienced widespread abandonment of pastures and agricultural lands, followed by forest regeneration. This paper examines the possible impacts of these secondary forests on several Q characteristics for 12 mesoscale catchments (23-346 km2; mean precipitation 1720-3422 mm yr-1) with long (33-51 yr) and simultaneous records for Q, precipitation (P), potential evaporation (PET), and land cover. A simple spatially-lumped, conceptual rainfall-runoff model that uses daily P and PET time series as inputs (HBV-light) was used to simulate Q for each catchment. Annual time series of observed and simulated values of four Q characteristics were calculated. A least-squares trend was fitted through annual time series of the residual difference between observed and simulated time series of each Q characteristic. From this the total cumulative change (Â) was calculated, representing the change in each Q characteristic after controlling for climate variability and water storage carry-over effects between years. Negative values of  were found for most catchments and Q characteristics, suggesting enhanced actual evaporation overall following forest regeneration. However, correlations between changes in urban or forest area and values of  were insignificant (P ≥ 0.389) for all Q characteristics. This suggests there is no convincing evidence that changes in the chosen Q characteristics in these Puerto Rican catchments can be ascribed to changes in urban or forest area. The present results are in line with previous studies of meso-and macro-scale (sub-)tropical catchments, which generally found no significant change in Q that can be attributed to changes in forest cover. Possible explanations for the lack of a clear signal may include errors in the land cover, climate, Q, and/or catchment boundary data; changes in forest area occurring mainly in the less rainy lowlands; and heterogeneity in catchment response. Different results were obtained for different catchments, and using a smaller subset of catchments could have led to very different conclusions. This highlights the importance of including multiple catchments in land-cover impact analysis at the mesoscale. © 2013 Author(s)

Global evaluation of four AVHRR-NDVI data sets: Intercomparison and assessment against Landsat imagery

Advanced Very High Resolution Radiometer (AVHRR) data with their long-term (1981-current) global coverage at frequent intervals provide unique opportunities to explore vegetation dynamics related to climate variability, climate change, and land-use driven changes of land cover. Several AVHRR-derived Normalized Difference Vegetation Index (NDVI) data sets exist, each based on the AVHRR Global Area Coverage archive but differing in their processing to correct for sensor and atmospheric effects. This paper presents a global comparative analysis for the land surface involving four AVHRR-derived NDVI data sets: (1) Pathfinder AVHRR Land (PAL); (2) Global Inventory Modeling and Mapping Studies (GIMMS); (3) Land Long Term Data Record (LTDR) version 3 (V3); and (4) Fourier-Adjustment, Solar zenith angle corrected, Interpolated Reconstructed (FASIR). Our aims are two-fold: (1) to assess the level of agreement of the medians, trends, and variances, as well as the correlation between the four AVHRR-NDVI data sets from 1982 to 1999; and (2) to independently assess the performance of each AVHRR-NDVI data set, and that of Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI, using 11,764 Landsat samples of 20×20k

Using multiple lines of evidence to evaluate the hydrological response to deforestation of large catchments in the dry tropics of Queensland, Australia

We used daily rainfall and streamflow time series from two large catchments in the seasonal tropics of Queensland, Australia to investigate the hydrological impacts of woodland clearing. The Comet catchment (16,440k

Global patterns in base flow index and recession based on streamflow observations from 3394 catchments

Numerous previous studies have constructed models to estimate base flow characteristics from climatic and physiographic characteristics of catchments and applied these to ungauged regions. However, these studies generally used streamflow observations from a relatively small number of catchments (<200) located in small, homogeneous study areas, which may have led to less reliable models with limited applicability elsewhere. Here, we use streamflow observations from a highly heterogeneous set of 3394 catchments (<10,000 k