Comments on “Changes in Global Surface Temperature from 1880 to 1977 Derived from Historical Records of Sea Surface Temperature”

1983 ◽  
Vol 111 (1) ◽  
pp. 240-240
Author(s):  
Makoto Hoshiai
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Historical Records ◽  
Global Surface Temperature ◽  
Global Surface

scholarly journals A new merge of global surface temperature datasets since the start of the 20th century

2019 ◽  
Vol 11 (4) ◽  
pp. 1629-1643 ◽  
Author(s):  
Xiang Yun ◽  
Boyin Huang ◽  
Jiayi Cheng ◽  
Wenhui Xu ◽  
Shaobo Qiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Global Climate Change ◽  
Global Climate ◽  
Sea Surface ◽  
Climate Change Research ◽  
Global Surface Temperature ◽  
Spatial Coverage ◽  
Global Surface

Abstract. Global surface temperature (ST) datasets are the foundation for global climate change research. Several global ST datasets have been developed by different groups in NOAA NCEI, NASA GISS, UK Met Office Hadley Centre & UEA CRU, and Berkeley Earth. In this study, a new global ST dataset named China Merged Surface Temperature (CMST) was presented. CMST is created by merging the China-Land Surface Air Temperature (C-LSAT1.3) with sea surface temperature (SST) data from the Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5). The merge of C-LSAT and ERSSTv5 shows a high spatial coverage extended to the high latitudes and is more consistent with a reference of multi-dataset averages in the polar regions. Comparisons indicated that CMST is consistent with other existing global ST datasets in interannual and decadal variations and long-term trends at global, hemispheric, and regional scales from 1900 to 2017. The CMST dataset can be used for global climate change assessment, monitoring, and detection. The CMST dataset presented here is publicly available at https://doi.org/10.1594/PANGAEA.901295 (Li, 2019a) and has been published on the Climate Explorer website of the Royal Netherlands Meteorological Institute (KNMI) at http://climexp.knmi.nl/select.cgi?id=someone@somewhere&field=cmst (last access: 11 August 2018; Li, 2019b, c).

scholarly journals A new merge of global surface temperature datasets since the start of the 20th Century

2019 ◽  
Author(s):  
Xiang Yun ◽  
Boyin Huang ◽  
Jiayi Cheng ◽  
Wenhui Xu ◽  
Shaobo Qiao ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Global Climate Change ◽  
Global Climate ◽  
Sea Surface ◽  
Climate Change Research ◽  
Global Surface Temperature ◽  
Spatial Coverage ◽  
Global Surface

Abstract. Global surface temperature (ST) datasets are the foundation for global climate change research. There are several global ST datasets developed by different groups in NOAA/NCEI，NASA/GISS and UKMO Hadley Centre & UEA/CRU. This study presents a new global ST dataset, the China Merged Surface Temperature (CMST) dataset. CMST is created by merging the China-Land Surface Air Temperature (C-LSAT1.3) with the sea surface temperature (SST) data from the Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5). The merge of C-LSAT and ERSSTv5 shows a high spatial coverage extended to the high latitudes and is more consistent with a reference of multi-datasets average in Polar Regions. Comparisons indicate that CMST is consistent with other existing global ST datasets in interannual-decadal variations and long-term trends at global, hemispheric, and regional scales from 1900 to 2017. Therefore CMST dataset can be used for global climate change assessment, monitoring, and detection. CMST dataset presented in this article is publicly available at: https://doi.pangaea.de/10.1594/PANGAEA.901295 (Yun et al., 2019) and has been published on the Climate Explorer website of the Royal Netherlands Meteorological Institute (KNMI) at: http://climexp.knmi.nl/select.cgi?id=someone@somewhere&field=cmst.

scholarly journals Global air temperature variability independent of sea-surface temperature influences

2012 ◽  
Vol 37 (1) ◽  
pp. 29-35
Author(s):  
Andrew C. Comrie ◽  
Gregory J. McCabe
Keyword(s):  
Time Series ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Air Temperature ◽  
Recent Literature ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Sea Surface ◽  
Sst Variability ◽  
Global Surface

Mean global surface air temperature (SAT) and sea surface temperature (SST) display substantial variability on timescales ranging from annual to multi-decadal. We review the key recent literature on connections between global SAT and SST variability. Although individual ocean influences on SAT have been recognized, the combined contributions of worldwide SST variability on the global SAT signal have not been clearly identified in observed data. We analyze these relations using principal components of detrended SST, and find that removing the underlying combined annual, decadal, and multi-decadal SST variability from the SAT time series reveals a nearly monotonic global warming trend in SAT since about 1900.

Holocene sea surface temperature variations recorded in corals from Kikai Island, Japan

2017 ◽  
Vol 51 (4) ◽  
pp. e9-e14 ◽  
Author(s):  
Hiroto Kajita ◽  
Atsuko Yamazaki ◽  
Takaaki Watanabe ◽  
Chung-Che Wu ◽  
Chuan-Chou Shen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Temperature Variations

PENENTUAN DAERAH POTENSIAL BUDIDAYA RUMPUT LAUT KAPPAPHYCUS ALVAREZII DI PROVINSI NUSA TENGGARA TIMUR

2019 ◽  
Vol 3 ◽  
pp. 929
Author(s):  
Marianus Filipe Logo ◽  
N M. R. R. Cahya Perbani ◽  
Bayu Priyono
Keyword(s):  
Dissolved Oxygen ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Kappaphycus Alvarezii ◽  
Sea Surface

Provinsi Nusa Tenggara Timur (NTT) merupakan penghasil rumput laut kappaphycus alvarezii kedua terbesar di Indonesia berdasarkan data Badan Pusat Statistik (2016). Oleh karena itu diperlukan zonasi daerah potensial budidaya rumput laut kappaphycus alvarezii untuk pengembangan lebih lanjut. Penelitian ini bertujuan untuk menentukan daerah yang potensial untuk budidaya rumput laut kappaphycus alvarezii di Provinsi NTT berdasarkan parameter sea surface temperature (SST), salinitas, kedalaman, arus, dissolved oxygen (DO), nitrat, fosfat, klorofil-a, dan muara sungai. Penentuan kesesuaian lokasi budidaya dilakukan dengan memberikan bobot dan skor bagi setiap parameter untuk budidaya rumput laut kappaphycus alvarezii menggunakan sistem informasi geografis melalui overlay peta tematik setiap parameter. Dari penelitian ini diperoleh bahwa kadar nitrat, arus, kedalaman, dan lokasi muara sungai menjadi parameter penentu utama. Jarak maksimum dari bibir pantai adalah sekitar 10 km. Potensial budidaya rumput laut kappaphycus alvarezii ditemukan di Pulau Flores bagian barat, kepulauan di Kabupaten Flores Timur dan Alor, selatan Pulau Sumba, Pulau Rote, dan Teluk Kupang.

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