Downward longwave radiation categories in Nigeria

2018 ◽  
Vol 83 ◽  
pp. 122-134 ◽  
Author(s):  
Nsikan I. Obot ◽  
Michael A.C. Chendo ◽  
Elijah O. Oyeyemi
2017 ◽  
Author(s):  
Chunlüe Zhou ◽  
Yanyi He ◽  
Kaicun Wang

Abstract. Reanalyses have been widely used because they add value to the routine observations by generating physically/dynamically consistent and spatiotemporally complete atmospheric fields. Existing studies have extensively discussed their temporal suitability in global change study. This study moves forward on their suitability for regional climate change study where land–atmosphere interactions play a more important role. Here, surface air temperature (Ta) from 12 current reanalysis products were investigated, focusing on spatial patterns of Ta trends, using homogenized Ta from 1979 to 2010 at ~ 2200 meteorological stations in China. Results show that ~ 80 % of the Ta mean differences between reanalyses and in-situ observations are attributed to station and model-grid elevation differences, denoting good skill in Ta climatology and rebutting the previously reported Ta biases. However, the Ta trend biases in reanalyses display spatial divergence (standard deviation = 0.15–0.30 °C/decade at 1° × 1° grids). The simulated Ta trend biases correlate well with those of precipitation frequency, surface incident solar radiation (Rs), and atmospheric downward longwave radiation (Ld) among the reanalyses (r = −0.83, 0.80 and 0.77, p 


2016 ◽  
Author(s):  
Kwang-Yul Kim ◽  
Benjamin D. Hamlington ◽  
Hanna Na ◽  
Jinju Kim

Abstract. Sea ice melting is proposed as a primary reason for the Artic amplification, although physical mechanism of the Arctic amplification and its connection with sea ice melting is still in debate. In the present study, monthly ERA-interim reanalysis data are analyzed via cyclostationary empirical orthogonal function analysis to understand the seasonal mechanism of sea ice melting in the Arctic Ocean and the Arctic amplification. While sea ice melting is widespread over much of the perimeter of the Arctic Ocean in summer, sea ice remains to be thin in winter only in the Barents-Kara Seas. Excessive turbulent heat flux through the sea surface exposed to air due to sea ice melting warms the atmospheric column. Warmer air increases the downward longwave radiation and subsequently surface air temperature, which facilitates sea surface remains to be ice free. A 1 % reduction in sea ice concentration in winter leads to ~ 0.76 W m−2 increase in upward heat flux, ~ 0.07 K increase in 850 hPa air temperature, ~ 0.97 W m−2 increase in downward longwave radiation, and ~ 0.26 K increase in surface air temperature. This positive feedback mechanism is not clearly observed in the Laptev, East Siberian, Chukchi, and Beaufort Seas, since sea ice refreezes in late fall (November) before excessive turbulent heat flux is available for warming the atmospheric column in winter. A detailed seasonal heat budget is presented in order to understand specific differences between the Barents-Kara Seas and Laptev, East Siberian, Chukchi, and Beaufort Seas.


2021 ◽  
pp. 1-54
Author(s):  
Joseph P. Clark ◽  
Vivek Shenoy ◽  
Steven B. Feldstein ◽  
Sukyoung Lee ◽  
Michael Goss

AbstractThe wintertime (December – February) 1990 - 2016 Arctic surface air temperature (SAT) trend is examined using self-organizing maps (SOMs). The high dimensional SAT dataset is reduced into nine representative SOM patterns, with each pattern exhibiting a decorrelation time scale about 10 days and having about 85% of its variance coming from intraseasonal timescales. The trend in the frequency of occurrence of each SOM pattern is used to estimate the interdecadal Arctic winter warming trend associated with the SOM patterns. It is found that trends in the SOM patterns explain about one-half of the SAT trend in the Barents and Kara Seas, one-third of the SAT trend around Baffin Bay and two-thirds of the SAT trend in the Chukchi Sea. A composite calculation of each term in the thermodynamic energy equation for each SOM pattern shows that the SAT anomalies grow primarily through the advection of the climatological temperature by the anomalous wind. This implies that a substantial fraction of Arctic amplification is due to horizontal temperature advection that is driven by changes in the atmospheric circulation. An analysis of the surface energy budget indicates that the skin temperature anomalies as well as the trend, although very similar to that of the SAT, are produced primarily by downward longwave radiation.


2019 ◽  
Vol 138 (3-4) ◽  
pp. 1375-1394
Author(s):  
A. H. Maghrabi ◽  
M. M. Almutayri ◽  
A. F. Aldosary ◽  
B. I. Allehyani ◽  
A. A. Aldakhil ◽  
...  

2020 ◽  
Author(s):  
Yu Wei ◽  
Xiaotong Zhang ◽  
Li Wenhong ◽  
Ning Hou ◽  
Weiyu Zhang ◽  
...  

2019 ◽  
Vol 19 (20) ◽  
pp. 13227-13241 ◽  
Author(s):  
Stephan Nyeki ◽  
Stefan Wacker ◽  
Christine Aebi ◽  
Julian Gröbner ◽  
Giovanni Martucci ◽  
...  

Abstract. The trends of meteorological parameters and surface downward shortwave radiation (DSR) and downward longwave radiation (DLR) were analysed at four stations (between 370 and 3580 m a.s.l.) in Switzerland for the 1996–2015 period. Ground temperature, specific humidity, and atmospheric integrated water vapour (IWV) trends were positive during all-sky and cloud-free conditions. All-sky DSR and DLR trends were in the ranges of 0.6–4.3 W m−2 decade−1 and 0.9–4.3 W m−2 decade−1, respectively, while corresponding cloud-free trends were −2.9–3.3 W m−2 decade−1 and 2.9–5.4 W m−2 decade−1. Most trends were significant at the 90 % and 95 % confidence levels. The cloud radiative effect (CRE) was determined using radiative-transfer calculations for cloud-free DSR and an empirical scheme for cloud-free DLR. The CRE decreased in magnitude by 0.9–3.1 W m−2 decade−1 (only one trend significant at 90 % confidence level), which implies a change in macrophysical and/or microphysical cloud properties. Between 10 % and 70 % of the increase in DLR is explained by factors other than ground temperature and IWV. A more detailed, long-term quantification of cloud changes is crucial and will be possible in the future, as cloud cameras have been measuring reliably at two of the four stations since 2013.


Sign in / Sign up

Export Citation Format

Share Document