scholarly journals Long-Term Trends of Sea Surface Wind in the Northern South China Sea under the Background of Climate Change

2021 ◽  
Vol 9 (7) ◽  
pp. 752
Author(s):  
Bo Hong ◽  
Jie Zhang

The long-term trends of sea surface wind are of great importance to our understanding of the effects of climate change on the marine environment. In the northern South China Sea (SCS), the long-term changes in coastal sea surface wind are not well-understood. Based on the latest reanalysis (ERA5) data from 1979 to 2019, our analysis showed a decreasing trend in the annual mean wind speed in the coastal area and an increasing trend in the open sea. There was a significant weakening trend in the easterly wind component in the coastal and continental shelf areas, whereas there was an increasing trend in the northerly wind component in the open sea. The Mann–Kendall mutation analysis suggested that there were significant changes in the wind speed and frequency of strong wind. Significant correlations were found between the variation of the wind field and El Niño–Southern Oscillation by wave coherence analysis. The strengthening of the wind stress curl was an important factor for the enhancement of coastal upwelling along the coast of the northern SCS. The wind field plays an important role in modulating the climatic change of significant wave height.

Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.


2012 ◽  
Vol 50 (7) ◽  
pp. 2901-2909 ◽  
Author(s):  
Alexis A. Mouche ◽  
Fabrice Collard ◽  
Bertrand Chapron ◽  
Knut-Frode Dagestad ◽  
Gilles Guitton ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document