Description: Author Posting. © American Meteorological Society, 2007. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 20 (2007): 5376–5390, doi:10.1175/2007JCLI1714.1.

Description: Global estimates of oceanic evaporation (Evp) from 1958 to 2005 have been recently developed by the Objectively Analyzed Air–Sea Fluxes (OAFlux) project at the Woods Hole Oceanographic Institution (WHOI). The nearly 50-yr time series shows that the decadal change of the global oceanic evaporation (Evp) is marked by a distinct transition from a downward trend to an upward trend around 1977–78. Since the transition, the global oceanic Evp has been up about 11 cm yr−1 (10%), from a low at 103 cm yr−1 in 1977 to a peak at 114 cm yr−1 in 2003. The increase in Evp was most dramatic during the 1990s. The uncertainty of the estimates is about ±2.74 cm yr−1. By utilizing the newly developed datasets of Evp and related air–sea variables, the study investigated the cause of the decadal change in oceanic Evp. The decadal differences between the 1990s and the 1970s indicates that the increase of Evp in the 1990s occurred over a global scale and had spatially coherent structures. Larger Evp is most pronounced in two key regions—one is the paths of the global western boundary currents and their extensions, and the other is the tropical Indo-Pacific warm water pools. It is also found that Evp was enlarged primarily during the hemispheric wintertime (defined as the mean of December–February for the northern oceans and June–August for the southern oceans). Despite the dominant upward tendency over the global basins, a slight reduction in Evp appeared in such regions as the subtropical centers of the Evp maxima as well as the eastern equatorial Pacific and Atlantic cold tongues. An empirical orthogonal function (EOF) analysis was performed for the yearly winter-mean time series of Evp and the related air–sea variables [i.e., wind speed (U) and air–sea humidity differences (dq)]. The analysis suggested a dominant role of the wind forcing in the decadal change of both Evp and dq. It is hypothesized that wind impacts Evp in two ways. The first way is direct: the greater wind speed induces more evaporation by carrying water vapor away from the evaporating surface to allow the air–sea humidity gradients to be reestablished at a faster pace. The second way is indirect: the enhanced surface wind strengthens the wind-driven subtropical gyre, which in turn drives a greater heat transport by the western boundary currents, warms up SST along the paths of the currents and extensions, and causes more evaporation by enlarging the air–sea humidity gradients. The EOF analysis performed for the time series of the global annual-mean Evp fields showed that the first three EOF modes account for nearly 50% of the total variance. The mode 1 variability represents the upward trend in Evp after 1978 and is attributable to the increased U, and the mode 2 variability explains much of the downward trend in Evp before 1978 and is correlated to the global dq variability. The EOF mode 3 of Evp captures the interannual variability of Evp on time scales of the El Niño–Southern Oscillation, with the center of action over the eastern equatorial Pacific.

Description: The author acknowledges the supporting grants from the NOAA Office of Climate Observations (OCO) and Climate Change Data and Detection (CCDD) and from the NASA Ocean Vector Wind Science Team.

Description: Author Posting. © American Meteorological Society, 2007. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 20 (2007): 3190-3209, doi:10.1175/JCLI4163.1.

Description: This study investigated the accuracy and physical representation of air–sea surface heat flux estimates for the Indian Ocean on annual, seasonal, and interannual time scales. Six heat flux products were analyzed, including the newly developed latent and sensible heat fluxes from the Objectively Analyzed Air–Sea Heat Fluxes (OAFlux) project and net shortwave and longwave radiation results from the International Satellite Cloud Climatology Project (ISCCP), the heat flux analysis from the Southampton Oceanography Centre (SOC), the National Centers for Environmental Prediction reanalysis 1 (NCEP1) and reanalysis-2 (NCEP2) datasets, and the European Centre for Medium-Range Weather Forecasts operational (ECMWF-OP) and 40-yr Re-Analysis (ERA-40) products. This paper presents the analysis of the six products in depicting the mean, the seasonal cycle, and the interannual variability of the net heat flux into the ocean. Two time series of in situ flux measurements, one taken from a 1-yr Arabian Sea Experiment field program and the other from a 1-month Joint Air–Sea Monsoon Interaction Experiment (JASMINE) field program in the Bay of Bengal were used to evaluate the statistical properties of the flux products over the measurement periods. The consistency between the six products on seasonal and interannual time scales was investigated using a standard deviation analysis and a physically based correlation analysis. The study has three findings. First of all, large differences exist in the mean value of the six heat flux products. Part of the differences may be attributable to the bias in the numerical weather prediction (NWP) models that underestimates the net heat flux into the Indian Ocean. Along the JASMINE ship tracks, the four NWP modeled mean fluxes all have a sign opposite to the observations, with NCEP1 being underestimated by 53 W m−2 (the least biased) and ECMWF-OP by 108 W m−2 (the most biased). At the Arabian Sea buoy site, the NWP mean fluxes also have an underestimation bias, with the smallest bias of 26 W m−2 (ERA-40) and the largest bias of 69 W m−2 (NCEP1). On the other hand, the OAFlux+ISCCP has the best comparison at both measurement sites. Second, the bias effect changes with the time scale. Despite the fact that the mean is biased significantly, there is no major bias in the seasonal cycle of all the products except for ECMWF-OP. The latter does not have a fixed mean due to the frequent updates of the model platform. Finally, among the four products (OAFlux+ISCCP, ERA-40, NCEP1, and NCEP2) that can be used for studying interannual variability, OAFlux+ISCCP and ERA-40 Qnet have good consistency as judged from both statistical and physical measures. NCEP1 shows broad agreement with the two products, with varying details. By comparison, NCEP2 is the least representative of the Qnet variabilities over the basin scale.

Description: This work is supported by the NOAA Office of Climate Observation and the Office of Climate Change and Data Detection under Grant NA17RJ1223.

Description: Author Posting. © American Geophysical Union, 2017. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 122 (2017): 6547–6564, doi:10.1002/2016JC012281.

Description: This study analyzed shipboard air-sea measurements acquired by the icebreaker Aurora Australis during its off-winter operation in December 2010 to May 2012. Mean conditions over 7 months (October–April) were compiled from a total of 22 ship tracks. The icebreaker traversed the water between Hobart, Tasmania, and the Antarctic continent, providing valuable in situ insight into two dynamically important, yet poorly sampled, regimes: the sub-Antarctic Southern Ocean and the Antarctic marginal ice zone (MIZ) in the Indian Ocean sector. The transition from the open water to the ice-covered surface creates sharp changes in albedo, surface roughness, and air temperature, leading to consequential effects on air-sea variables and fluxes. Major effort was made to estimate the air-sea fluxes in the MIZ using the bulk flux algorithms that are tuned specifically for the sea-ice effects, while computing the fluxes over the sub-Antarctic section using the COARE3.0 algorithm. The study evidenced strong sea-ice modulations on winds, with the southerly airflow showing deceleration (convergence) in the MIZ and acceleration (divergence) when moving away from the MIZ. Marked seasonal variations in heat exchanges between the atmosphere and the ice margin were noted. The monotonic increase in turbulent latent and sensible heat fluxes after summer turned the MIZ quickly into a heat loss regime, while at the same time the sub-Antarctic surface water continued to receive heat from the atmosphere. The drastic increase in turbulent heat loss in the MIZ contrasted sharply to the nonsignificant and seasonally invariant turbulent heat loss over the sub-Antarctic open water.

Description: NOAA Climate Observation Division Grant Number: NA09OAR4320129

Description: 2018-02-23

Description: Author Posting. © American Geophysical Union, 2011. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 116 (2011): C10025, doi:10.1029/2010JC006937.

Description: Ocean evaporation (E) and precipitation (P) are the fundamental components of the global water cycle. They are also the freshwater flux forcing (i.e., E-P) for the open ocean salinity. The apparent connection between ocean salinity and the global water cycle leads to the proposition of using the oceans as a rain gauge. However, the exact relationship between E-P and salinity is governed by complex upper ocean dynamics, which may complicate the inference of the water cycle from salinity observations. To gain a better understanding of the ocean rain gauge concept, here we address a fundamental issue as to how E-P and salinity are related on the seasonal timescales. A global map that outlines the dominant process for the mixed-layer salinity (MLS) in different regions is thus derived, using a lower-order MLS dynamics that allows key balance terms (i.e., E-P, the Ekman and geostrophic advection, vertical entrainment, and horizontal diffusion) to be computed from satellite-derived data sets and a salinity climatology. Major E-P control on seasonal MLS variability is found in two regions: the tropical convergence zones featuring heavy rainfall and the western North Pacific and Atlantic under the influence of high evaporation. Within this regime, E-P accounts for 40–70% MLS variance with peak correlations occurring at 2–4 month lead time. Outside of the tropics, the MLS variations are governed predominantly by the Ekman advection, and then vertical entrainment. The study suggests that the E-P regime could serve as a window of opportunity for testing the ocean rain gauge concept once satellite salinity observations are available.

Description: The study was supported by the NASA Remote Sensing Science for Carbon and Climate program under grant NNX07AF97G and by the NSF Physical Oceanography program under grant OCE‐0647949.