ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2018-01-01
    Description: As integration of solar power into the national electric grid rapidly increases, it becomes imperative to improve forecasting of this highly variable renewable resource. Thus, a team of researchers from the public, private, and academic sectors partnered to develop and assess a new solar power forecasting system, Sun4Cast. The partnership focused on improving decision-making for utilities and independent system operators, ultimately resulting in improved grid stability and cost savings for consumers. The project followed a value chain approach to determine key research and technology needs to reach desired results. Sun4Cast integrates various forecasting technologies across a spectrum of temporal and spatial scales to predict surface solar irradiance. Anchoring the system is WRF-Solar, a version of the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model optimized for solar irradiance prediction. Forecasts from multiple NWP models are blended via the Dynamic Integrated Forecast (DICast) System, which forms the basis of the system beyond about 6 h. For short-range (0–6 h) forecasts, Sun4Cast leverages several observation-based nowcasting technologies. These technologies are blended via the Nowcasting Expert System Integrator (NESI). The NESI and DICast systems are subsequently blended to produce short- to midterm irradiance forecasts for solar array locations. The irradiance forecasts are translated into power with uncertainties quantified using an analog ensemble approach and are provided to the industry partners for real-time decision-making. The Sun4Cast system ran operationally throughout 2015 and results were assessed. This paper analyzes the collaborative design process, discusses the project results, and provides recommendations for best-practice solar forecasting.
    Print ISSN: 0003-0007
    Electronic ISSN: 1520-0477
    Topics: Geography , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2018-12-17
    Description: The northeast monsoon (NEM) brings the bulk of annual rainfall to southeastern peninsular India, Sri Lanka, and the neighboring Southeast Asian countries. This October–December monsoon is referred to as the winter monsoon in this region. In contrast, the southwest summer monsoon brings bountiful rainfall to the Indo-Gangetic Plain. The winter monsoon region is objectively demarcated from analysis of the timing of peak monthly rainfall. Because of the region’s complex terrain, in situ precipitation datasets are assessed using high-spatiotemporal-resolution Tropical Rainfall Measuring Mission (TRMM) rainfall estimates, prior to their use in monsoon evolution, variability, and trend analyses. The Global Precipitation Climatology Center’s in situ analysis showed the least bias from TRMM. El Niño–Southern Oscillation’s (ENSO) impact on NEM rainfall is shown to be significant, leading to stronger NEM rainfall over southeastern peninsular India and Sri Lanka but diminished rainfall over Thailand, Vietnam, and the Philippines. The impact varies subseasonally, being weak in October and strong in November. The positive anomalies over peninsular India are generated by anomalous anticyclonic flow centered over the Bay of Bengal, which is forced by an El Niño–related reduction in deep convection over the Maritime Continent. The historical twentieth-century climate simulations informing the Intergovernmental Panel on Climate Change’s Fifth Assessment (IPCC-AR5) show varied deficiencies in the NEM rainfall distribution and a markedly weaker (and often unrealistic) ENSO–NEM rainfall relationship.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 3
    Publication Date: 2018-12-28
    Description: Time series of surface meteorology and air–sea fluxes from the northern Bay of Bengal are analyzed, quantifying annual and seasonal means, variability, and the potential for surface fluxes to contribute significantly to variability in surface temperature and salinity. Strong signals were associated with solar insolation and its modulation by cloud cover, and, in the 5- to 50-day range, with intraseasonal oscillations (ISOs). The northeast (NE) monsoon (DJF) was typically cloud free, with strong latent heat loss and several moderate wind events, and had the only seasonal mean ocean heat loss. The spring intermonsoon (MAM) was cloud free and had light winds and the strongest ocean heating. Strong ISOs and Tropical Cyclone Komen were seen in the southwest (SW) monsoon (JJA), when 65% of the 2.2-m total rain fell, and oceanic mean heating was small. The fall intermonsoon (SON) initially had moderate convective systems and mean ocean heating, with a transition to drier winds and mean ocean heat loss in the last month. Observed surface freshwater flux applied to a layer of the observed thickness produced drops in salinity with timing and magnitude similar to the initial drops in salinity in the summer monsoon, but did not reproduce the salinity variability of the fall intermonsoon. Observed surface heat flux has the potential to cause the temperature trends of the different seasons, but uncertainty in how shortwave radiation is absorbed in the upper ocean limits quantifying the role of surface forcing in the evolution of mixed layer temperature.
    Print ISSN: 0894-8755
    Electronic ISSN: 1520-0442
    Topics: Geography , Geosciences , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...