FN Archimer Export Format
PT J
TI Model derived uncertainties in deep ocean temperature trends between 1990-2010
BT 
AF Garry, F. K.
   McDonagh, E. L.
   Blaker, A. T.
   Roberts, C. D.
   Desbruyères, Damien
   Frajka-Williams, E.
   King, B. A.
AS 1:1,2;2:3;3:3;4:4;5:3;6:1,3;7:3;
FF 1:;2:;3:;4:;5:;6:;7:;
C1 Ocean and Earth Science, University of Southampton; National Oceanography Centre; Southampton, UK
   College of Life and Environmental Sciences; University of Exeter, Streatham Campus; Exeter ,UK
   National Oceanography Centre; Southampton, UK
   Met Office Hadley Centre; FitzRoy Road Exeter, UK
C2 NOC, UK
   UNIV EXETER, UK
   NOC, UK
   MET OFF, UK
IF 3.559
TC 12
UR https://archimer.ifremer.fr/doc/00479/59021/61642.pdf
   https://archimer.ifremer.fr/doc/00479/59021/61643.gz
LA English
DT Article
DE ;deep oceans;temperature trends;ocean heat content;decadal variability;ocean modeling;observational uncertainties
AB We construct a novel framework to investigate the uncertainties and biases associated with estimates of deep ocean temperature change from hydrographic sections, and demonstrate this framework in an eddy‐permitting ocean model. Biases in estimates from observations arise due to sparse spatial coverage (few sections in a basin), low frequency of occupations (typically 5‐10 years apart), mismatches between the time period of interest and span of occupations, and from seasonal biases relating to the practicalities of sampling during certain times of year. Between the years 1990 and 2010, the modeled global abyssal ocean biases are small, although regionally some biases (expressed as a heat flux into the 4000 ‐ 6000 m layer) can be up to 0.05 W m−2. In this model, biases in the heat flux into the deep 2000 ‐ 4000 m layer, due to either temporal or spatial sampling uncertainties, are typically much larger and can be over 0.1 W m−2 across an ocean. Overall, 82% of the warming trend deeper than 2000 m is captured by hydrographic section‐style sampling in the model. At 2000 m, only half the model global warming trend is obtained from observational‐style sampling, with large biases in the Atlantic, Southern and Indian Oceans. Biases due to different sources of uncertainty can have opposing signs and differ in relative importance both regionally and with depth, revealing the importance of reducing temporal and spatial uncertainties in future deep ocean observing design. Plain Language Summary In recent decades, deep (below 2000 m) ocean temperature trends have been measured when scientific research vessels repeat the same lines across an ocean basin. Repeats typically happen once or twice a decade and there are only a few repeated lines across each basin. The sparsity of data in both space and time will result in errors in the multidecadal temperature trends calculated from this data. Here, we use a state‐of‐the‐art ocean model to show how trends calculated from observational‐style sampling compare to trends calculated using all model data. For the period 1990‐2010, we estimate the error that may exist in observed deep ocean trend estimates. Overall, around 80% of the below 2000 m warming trend was captured by observational‐style sampling in the model, so deep ocean warming in recent decades may have been underestimated. However, our results are based on only one model simulation. The largest sources of sampling error are found in the Atlantic, Southern and Indian Oceans. For each basin, we reveal whether limited sampling in time or space contributes most error to the temperature trend estimate, and therefore in which regions temperature trend estimates would benefit from additional deep ocean sampling. 
PY 2019
PD FEB
SO Journal Of Geophysical Research-oceans
SN 2169-9275
PU American Geophysical Union (AGU)
VL 124
IS 2
UT 000461856400020
BP 1155
EP 1169
DI 10.1029/2018JC014225
ID 59021
ER

EF