Evaluation of surface shortwave and longwave downwelling radiations over the global tropical oceans

Abstract

In the present study, daily downwelling shortwave (Q S ) and longwave radiation (Q L ) data from one satellite and two hybrid products have been evaluated using Global Tropical Moored Buoy Array during 2001-2009 in the tropical oceans. Daily satellite data are used from the Clouds and Earth's Radiant Energy System (CERES) program. Data are obtained using Moderate Resolution Imaging Spectroradiometer (MODIS) (CM) aboard the Terra and Aqua satellites. Coordinated Ocean Research Experiments (CORE-II) and Tropical Flux data (TropFlux) are the other two hybrid products used in this study.The analysis shows that majority of Q S observations as well as derived products lie in 200-300 Wm −2 range in all the three tropical oceans. Both Q S and Q L in all products overestimated the majority of the observations. Yet, they underestimated the lower (0-100 Wm −2 ) values in Q S and higher (300-440 Wm −2 ) values in Q L . Majority of the Q L observations lie within 390-420 Wm −2 range, and CM slightly overestimated this observed distribution in the Pacific and the Atlantic Oceans. But, majority of the observations in the Indian Ocean lie within 420-450 Wm −2 range. This implies that the tropical Indian Ocean receives 30 Wm −2 more energy as compared to the tropical Pacific and the Atlantic in the form of downwelling longwave radiation. Daily observed Q S shows dominant seasonal cycle over the central, the eastern Pacific and the eastern Atlantic. On the other hand, the western Pacific, the central Atlantic and the Indian Oceans show intraseasonal variations. All products show this variation with high root-mean-square error (RMSE) values (Q S and Q L ) over the Indian Ocean than in the Pacific and the Atlantic Oceans. Downwelling radiation from CORE-II shows highest RMSE (for both Q S and Q L ) with least correlation coefficient (CC), and TropFlux has lowest RMSE and highest CC among all products in all three tropical oceans. CM has intermediate values of standard deviation, CC and RMSE. These results are not seasonally dependent, since the seasonal statistics are consistent with seasonal changes. Assuming that the SST is only driven by the downwelling shortwave and longwave fluxes, the errors associated with monthly SST can be as large as 0.2-0.3 (0.1-0.2) °C associated with errors in Q S (Q L ). Both Q S and Q L in CORE-II have lower spatial variability as compared to other datasets. Q L in the tropical oceans shows seasonal spatial variability determined by intertropical convergence zone positions. This variability does not change significantly over the Pacific and the Atlantic Oceans. The summer and winter monsoon patterns in the Indian Ocean guide the Q L variability. Opposite to Q S , higher Q L values have lower variability.Thus, this study aims at finding better radiation dataset to use in the numerical models and deduce that satellite data could be an alternative to existing reanalysis products.

Evaluation of the J-OFURO3 Sea Surface Net Radiation and Inconsistency Correction

“…The units for all radiative components are Wm −2 , the time format is GMT, and the downward direction is positive in this study. The R si , R li , and SST measurements were collected from 55 global moored buoy sites in 5 measuring networks (Table 1) and have been commonly used in previous studies [19,20]. Figure 1 shows the distribution of these buoy sites, which were mainly located within the sea areas between 50 • S and 50 • N. After strict quality control and a manual inspection, only the measurements with the highest quality were kept [21].…”

A sea-level monopole in the equatorial Indian Ocean

“…However, in other regions, when SLA increased, D20 shallowed. This could be due to the differences in shortwave radiation received and changes in the upper-ocean dynamics over the EIO 25,71,72 . In another way, irrespective of changing SLA over the central EIO, D20 shows no variability ( Fig.…”

“…As SLA is a function of thermosteric height, it defines the thermal expansion of the deep ocean and upper layers of the ocean due to varying heat and density. The EIO receives high solar radiation throughout the year, and the shift in the thermal equator, twice a year, cause changes in the wind patterns (south/north) over the Inter-Tropical Convergence Zone (ITCZ) 25 . These changes cause anomalous SST over this region at different temporal scales.…”

“…npj Climate and Atmospheric Science (2020)25 Published in partnership with CECCR at King Abdulaziz University1234567890():,;…”

Effects of Cropland Expansion on the Regional Land Surface Radiative Energy Balance and Heat Fluxes in Northern China

“…Net shortwave radiation (Rns) was calculated based on the radiation data and the albedo data; the formula [39] is:…”