Wind power forecasting and integration to power grids

This is a summary of the presentation in the special session: "Digital Signal Processing for Green Power Systems and Delivery". In recent years, wind power penetration level in power systems has increased significantly. Grid integration has become one of the major issues for wind power growth due to the intermittent characteristics of wind power. The uncertainty of power generation from wind farms may result in power system stability and security problems. Accurate wind power forecasting could reduce the uncertainty to generation scheduling to certain extent, hence increase the wind power penetration level in the system. © 2010 IEEE.published_or_final_versionThe 1st International Conference on Green Circuits and Systems (ICGCS 2010), Shanghai, China, 21-23 June 2010. In Proceedings of ICGCS, 2010, p. 555-56

A study of the feasibility of using sea and wind information from the ERS-1 satellite. Part 1: Wind scatterometer data

The use of scatterometer and altimeter data in wind and wave assimilation, and the benefits this offers for quality assurance and validation of ERS-1 data were examined. Real time use of ERS-1 data was simulated through assimilation of Seasat scatterometer data. The potential for quality assurance and validation is demonstrated by documenting a series of substantial problems with the scatterometer data, which are known but took years to establish, or are new. A data impact study, and an analysis of the performance of ambiguity removal algorithms on real and simulated data were conducted. The impact of the data on analyses and forecasts is large in the Southern Hemisphere, generally small in the Northern Hemisphere, and occasionally large in the Tropics. Tests with simulated data give more optimistic results than tests with real data. Errors in ambiguity removal results occur in clusters. The probabilities which can be calculated for the ambiguous wind directions on ERS-1 contain more information than is given by a simple ranking of the directions

Future developments in surge forecast: probabilistic forecast and future surge statistic

This research investigated how the surge forecast can be improved, moving from a single-deterministic to a probabilistic forecast. Moreover a future storm surge scenario is estimated using new meteorological data: sea level (SL) forecast for the city of Venice and future changes of storm surge regime due to climate changes are of paramount importance for the management and maintenance of this historical city and for operating the movable barriers that are presently being built for its protection. An Ensemble Prediction System (EPS) for operational forecasting of storm surge in the northern Adriatic Sea is presented. EPS is meant to complement the existing SL forecast system by providing a probabilistic forecast and information on uncertainty of SL prediction. Ten relatively high storm surge events in the period 2009-2010 are simulated producing for each of them an ensemble of 50 simulations, using the meteorological data input of the European Centre for Medium-Range Weather Forecasts (ECMWF) as input to a shallow water hydrodynamic model “Hydrostatic Padua Surface Elevation Model” (HYPSE), which computes sea level and barotropic currents in the Adriatic Sea . It is shown that EPS slightly increases the accuracy of SL prediction with respect to the deterministic forecast (DF) and it is more reliable than it. It is shown that the SL peaks correspond to maxima of uncertainty ( as described by the spread of the EPS members) and the values of these maxima increase linearly with the forecast range. Uncertainty on sea level is caused by the uncertainty of the forcing meteorological fields and the quasi linear dynamics of the storm surges plays a minor role on its evolution except it produces a modulation of the uncertainty after the SL peak with period corresponding to that of the main Adriatic seiche. Finally, the error of the EPS mean is correlated with the EPS spread. The second part of the research focus on the future storm surge scenario, that is estimated using new high resolution data recently produced by EC-Earth, an Earth System Model based on the operational seasonal forecast system of ECMWF. The study considers an ensemble of six 5-year long simulations of the rcp45 scenario (Hazeleger et al. 2006) and compares the 2094-2098 to the 2004-2008 period. EC-Earth sea level pressure and surface wind fields are used as input to HYPSE. The results show that high resolution of wind fields are essential for producing realistic values of storm surge statistic. However, results confirm previous studies in that they show little sensitivity of storm surge levels to climate change

The WWRP Polar Prediction Project (PPP)

Mission statement: “Promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hours to seasonal”. Increased economic, transportation and research activities in polar regions are leading to more demands for sustained and improved availability of predictive weather and climate information to support decision-making. However, partly as a result of a strong emphasis of previous international efforts on lower and middle latitudes, many gaps in weather, sub-seasonal and seasonal forecasting in polar regions hamper reliable decision making in the Arctic, Antarctic and possibly the middle latitudes as well. In order to advance polar prediction capabilities, the WWRP Polar Prediction Project (PPP) has been established as one of three THORPEX (THe Observing System Research and Predictability EXperiment) legacy activities. The aim of PPP, a ten year endeavour (2013-2022), is to promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on hourly to seasonal time scales. In order to achieve its goals, PPP will enhance international and interdisciplinary collaboration through the development of strong linkages with related initiatives; strengthen linkages between academia, research institutions and operational forecasting centres; promote interactions and communication between research and stakeholders; and foster education and outreach. Flagship research activities of PPP include sea ice prediction, polar-lower latitude linkages and the Year of Polar Prediction (YOPP) - an intensive observational, coupled modelling, service-oriented research and educational effort in the period mid-2017 to mid-2019

Ground, Proximal, and Satellite Remote Sensing of Soil Moisture

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security

Status of the Global Observing System for Climate

Status of the Global Observing System for Climat

The sporadic nature of meridional heat transport in the atmosphere

The present study analyses meridional atmospheric heat transport, due to transient eddies, in the European Centre for Medium-Range Weather Forecasts ERA-Interim reanalysis data. Probability density functions of the transport highlight the dominant role played by extreme events. In both hemispheres, events in the top 5 percentiles typically account for over half of the net poleward transport. As a result of this sensitivity to extremes, a large fraction of the heat transport by transient eddies, at a given location and season, is realised through randomly spaced bursts (a few per season), rather than through a continuum of events. Abstract Fast growing atmospheric modes are associated with a large heat transport, suggesting a link between these bursts and growing baroclinic systems (defined here as motions in the 2.5–6 day band). However, wavelet power spectra of the transport extremes suggest that they are driven by very precise phase and coherence relationships, between meridional velocity and moist static energy anomalies, acting over a broad range of frequencies (2-32 days). Motions with periods beyond 6 days play a key role in this framework. Moreover, these longer periods are found to be mainly driven by planetary-scale motions. Notwithstanding this, the heat transport bursts can be matched to specific synoptic-scale patterns. The bursts are therefore interpreted as the signatures of travelling synoptic systems superimposed on larger scale motions. The dominant role of extreme events can be reproduced in highly idealised simulations. Both a statistical model, where atmospheric motions are assumed to be linear superpositions of sinusoidal curves, and a two-layer model, representing heat transport as a quantised process effected by point vorticity anomalies, are successful in simulating the transport bursts. The fact that two very different idealised models both reproduce the transport's sporadic nature suggests that this must be an intrinsic property of waves in the atmosphere.Open Acces

Sea surface wind estimation by multi-frequency SAR imagery

Living Planet Symposium, 23-27 May 2022, Bonn, GermanyOcean surface wind vector is of paramount importance in a broad range of applications including wave forecasting, weather forecasting, and storm surge [R1-R5]. The primary remote sensing instruments for wind field retrieval from space is the microwave scatterometer. Although the latter calls for a spatial sampling adequate for several climatological and meso-scale applications, severe limitations to the use of scatterometer products arise when dealing with regional-scale applications. In contrast, the Synthetic Aperture Radar (SAR) achieves a finer spatial resolution and therefore has the potential to provide wind field information with much more spatial details. This can be important in several applications, such as in semi enclosed seas, in straits, along marginal ice zones, and in coastal regions, where scatterometer measurements are contaminated by backscatter from land and ice and the wind vector fields are often recognized to be highly variable. In such regions, wind field estimates retrieved from SAR images would be very desirable. In this study, the main outcomes related to the Italian Space Agency (ASI) funded project APPLICAVEMARS, whose goal is estimating the ocean surface wind vector using L-, C- and X-band SAR imagery, are presented. The wind processor developed to estimate sea surface wind field from L-band SAOCOM, C-band Sentinel-1A/B and X-band CSK/CSG SAR imagery is described through some thought showcases where: a) the scatterometer-based Geophysical Model Function is forced using both external (SCAT/ECMWF) and SAR-based wind directions, the latter evaluated by the developed methodologies based on the 2D Continuous Wavelet Transform [6] and Convolutional Neural Network [7] at high spatial resolution (1 km); b) the wind field is estimated over collocated L-, C- and X-band SAR imagery to study both the aspects related to the GMFs and those dependent on the capacity of the different SAR frequencies to reveal the wind spatial structures. [R1] Chelton D. B., M. G. Schlax, M. H. Freilich, R. F. Milliff, 2004: Satellite measurements reveal persistent small-scale features in ocean winds. Science, 303, 978- 983, doi:10.1126/science.1091901. [R2] Lagerloef, G., R. Lukas, F. Bonjean, J. Gunn, G. Mitchum, M. Bourassa, and T. Busalacchi, 2003: El Niño tropical Pacific Ocean surface current and temperature evolution in 2002 and outlook for early 2003. Geophys. Res. Lett., 30, 1514, doi:10.1029/2003GL017096. [R3] Gierach, M. M. M. A. Bourassa, P. Cunningham, J. J. O'Brien, and P. D. Reasor, 2007: Vorticity-based detection of tropical cyclogenesis. J. Appl. Meteor. Climatol., 46, 1214-1229, doi:10.1175/JAM2522.1. [R4] Isaksen, L., A. Stoffelen, 2000: ERS-Scatterometer wind data impact on ECMWF's tropical cyclone forecasts. IEEE Trans. Geosci. Rem. Sens., 38, 1885-1892. [R5] Morey, S. L., S. R. Baig, M. A. Bourassa, D. S. Dukhovskoy, and J. J. O'Brien, 2006: Remote forcing contribution to storm-induced sea level rise during Hurricane Dennis, Geophys. Res. Lett., 33, L19603, doi:10.1029/2006GL027021. [6] Zecchetto, S., Wind Direction Extraction from SAR in Coastal Areas, Remote Sensing,10(2), 261, 2018 (doi:10.3390/rs10020261) [7] Zanchetta, A. and S. Zecchetto, Wind direction retrieval from Sentinel-1 SAR images using ResNet, Remote Sensing of Environment, 253, 2021 (https://doi.org/10.1016/j.rse.2020.112178)Peer reviewe