Ocean surface wind fields estimated from satellite active and passive microwave instruments

Bentamy, Abderrahim; Queffeulou, P.; Quilfen, Yves; Katsaros, Kristina B.

doi:10.1109/36.789643

Cited by 104 publications

(80 citation statements)

References 17 publications

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“…It is therefore not surprising to see a robust ocean evaporation trend as a result, particularly for the GSSTF product. The near-surface wind patterns of GSSTF (Wentz and Schabel 2000) and HOAPS (Bentamy et al 1999) are similar, even though both are derived from different retrieval approaches (described in section 2). The trend in Q a is much stronger for GSSTF.…”

Section: Diagnosis Of Evaporation Trendmentioning

confidence: 88%

“…The value of C E is adjusted according to stability and salinity (for GSSTF only) conditions. Furthermore, GSSTF uses SSM/I version 4 wind speed products (Meissner et al 2001); on the other hand, HOAPS uses the Goodberlet algorithm (Bentamy et al 1999) with SSM/I brightness temperature data. For Q a , GSSTF employs a secondorder EOF expansion to fit a humidity profile with (version 4) SSM/I precipitable water retrievals, while HOAPS2 uses an improved Schulz inverse model (Bentamy et al 2003) with SSM/I brightness temperatures.…”

Section: ϫ2mentioning

confidence: 99%

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Assessing a Satellite-Era Perspective of the Global Water Cycle

Schlosser

Houser

2007

Journal of Climate

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The capability of a global data compilation, largely satellite based, is assessed to depict the global atmospheric water cycle's mean state and variability. Monthly global precipitation estimates from the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) span from 1979 to 1999. Monthly global Special Sensor Microwave Imager (SSM/I)-based bulk aerodynamic ocean evaporation estimates span from June 1987 to December 1999. Global terrestrial evapotranspiration rates are estimated over a multidecade period (1975-99) using a global land model simulation forced by bias-corrected reanalysis data. Monthly total precipitable water (TPW) from the NASA Global Water Vapor Project (NVAP) spans from 1988 to 1999.The averaged annual global precipitation (P) and evaporation (E ) estimates are out of balance by 5% or 24 000 (metric) gigatons (Gton) of water, which exceeds the uncertainty of global mean annual precipitation (ϳϮ1%). For any given year, the annual flux imbalance can be on the order of 10% (48 000 Gton of water). However, observed global TPW interannual variations suggest a water flux imbalance on the order of 0.01% (48 Gton of water)-a finding consistent with a general circulation model (GCM) simulation. Variations in observationally based global P and E rates show weak monthly and interannual consistency, and depending on the choice of ocean evaporation data, the mean annual cycle of global E Ϫ P can be up to 5 times larger to that of TPW. The global ocean annual evaporation rates have as much as a ϳ1% yr Ϫ1 increase during the period analyzed , which is consistent in sign with most transient CO 2 GCM simulations, but at least an order of magnitude larger. The ocean evaporation trends are driven by trends in SSM/I-retrieved near-surface atmospheric humidity and wind speed, and the largest year-to-year changes are coincident with transitions in the SSM/I fleet.In light of (potential) global water cycle changes in GCM projections, the ability to consistently detect or verify these changes in nature rests upon one or more of the following: quantification of global evaporation uncertainty, at least a twofold improvement in consistency between the observationally based global precipitation and evaporation variations, a two order of magnitude rectification between annual variations of E Ϫ P and precipitable water as well as substantial improvements in the consistency of their seasonal cycles, a critical reevaluation of intersatellite calibration for the relevant geophysical quantities used for ocean evaporation estimates, and the continuation of a dedicated calibration in this regard for future satellite transitions.

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Section: Diagnosis Of Evaporation Trendmentioning

confidence: 88%

Section: ϫ2mentioning

confidence: 99%

Assessing a Satellite-Era Perspective of the Global Water Cycle

Schlosser

Houser

2007

Journal of Climate

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“…The differences are very similar to what Chelton and Freilich (2005) found by comparing ECMWF and QuikSCAT fields. A part of the disagreements can be explained by the differences between the equivalent neutral stability wind, which is observed by the scatterometer, and the actual wind, which is represented in the NWP (numerical weather prediction) analyses, and the fact that scatterometer retrievals typically overestimate buoy observations for relatively low wind speeds (< 4 m s −1 ) (Bentamy et al, 1999;Chelton and Freilich, 2005). It should also be noted that Chelton (2005) remarked that NWP models do not represent well the influence of SST on low-speed winds over warm waters that could lead to a model underestimation in these regions.…”

Section: Sea Salt Source Functionmentioning

confidence: 99%

Modelling of primary aerosols in the chemical transport model MOCAGE: development and evaluation of aerosol physical parameterizations

et al. 2015

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Abstract. This paper deals with recent improvements to the global chemical transport model of Météo-France MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) that consists of updates to different aerosol parameterizations. MOCAGE only contains primary aerosol species: desert dust, sea salt, black carbon, organic carbon, and also volcanic ash in the case of large volcanic eruptions. We introduced important changes to the aerosol parameterization concerning emissions, wet deposition and sedimentation. For the emissions, size distribution and wind calculations are modified for desert dust aerosols, and a surface sea temperature dependant source function is introduced for sea salt aerosols. Wet deposition is modified toward a more physically realistic representation by introducing re-evaporation of falling rain and snowfall scavenging and by changing the in-cloud scavenging scheme along with calculations of precipitation cloud cover and rain properties. The sedimentation scheme update includes changes regarding the stability and viscosity calculations. Independent data from satellites (MODIS, SEVIRI), the ground (AERONET, EMEP), and a model inter-comparison project (AeroCom) are compared with MOCAGE simulations and show that the introduced changes brought a significant improvement on aerosol representation, properties and global distribution. Emitted quantities of desert dust and sea salt, as well their lifetimes, moved closer towards values of AeroCom estimates and the multimodel average. When comparing the model simulations with MODIS aerosol optical depth (AOD) observations over the oceans, the updated model configuration shows a decrease in the modified normalized mean bias (MNMB; from 0.42 to 0.10) and a better correlation (from 0.06 to 0.32) in terms of the geographical distribution and the temporal variability. The updates corrected a strong positive MNMB in the sea salt representation at high latitudes (from 0.65 to 0.16), and a negative MNMB in the desert dust representation in the African dust outflow region (from − 1.01 to −0.22). The updates in sedimentation produced a modest difference; the MNMB with MODIS data from 0.10 in the updated configuration went to 0.11 in the updated configuration only without the sedimentation updates. Yet, the updates in the emissions and the wet deposition made a stronger impact on the results; the MNMB was 0.27 and 0.21 in updated configurations only without emission, and only without wet deposition updates, respectively. Also, the lifetime, the extent, and the strength of the episodic aerosol events are better reproduced in the updated configuration. The wet deposition processes and the differences between the various configurations that were tested greatly influence the representation of the episodic events. However, wet deposition is not a continuous process; it has a local and episodic signature and its representation depends strongly on the precipitation regime in the model.

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“…prisingly, tropical SST biases in CAM5.5 are well correlated with the precipitation biases, namely over the tropical western Pacific and western Indian oceans. Surface stress from the atmosphere is another important component to the coupled system and the surface stress biases, computed relative to the European Remote Sensing Satellite Scatterometer (ERS; Bentamy et al, 1999) observations, can be seen in Fig 9. Similar to the SST biases, we see that the positive surface stress bias in the Southern Ocean increases by 20 % in CAM5.4 and CAM5.5 when compared to CAM5.3. We note that this increase in surface stress for CESM-CAM5.4 and CESM-CAM5.5 is very similar to that found in atmosphere-only simulations.…”

Section: Mean State Climatementioning

confidence: 99%

The path to CAM6: coupled simulations with CAM5.4 and CAM5.5

et al. 2018

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Abstract. This paper documents coupled simulations of two developmental versions of the Community Atmosphere Model (CAM) towards CAM6. The configuration called CAM5.4 introduces new microphysics, aerosol, and ice nucleation changes, among others to CAM. The CAM5.5 configuration represents a more radical departure, as it uses an assumed probability density function (PDF)-based unified cloud parameterization to replace the turbulence, shallow convection, and warm cloud macrophysics in CAM. This assumed PDF method has been widely used in the last decade in atmosphere-only climate simulations but has never been documented in coupled mode. Here, we compare the simulated coupled climates of CAM5.4 and CAM5.5 and compare them to the control coupled simulation produced by CAM5.3. We find that CAM5.5 has lower cloud forcing biases when compared to the control simulations. Improvements are also seen in the simulated amplitude of the Niño-3.4 index, an improved representation of the diurnal cycle of precipitation, subtropical surface wind stresses, and double Intertropical Convergence Zone biases. Degradations are seen in Amazon precipitation as well as slightly colder sea surface temperatures and thinner Arctic sea ice. Simulation of the 20th century results in a credible simulation that ends slightly colder than the control coupled simulation. The authors find this is due to aerosol indirect effects that are slightly stronger in the new version of the model and propose a solution to ameliorate this. Overall, in these early coupled simulations, CAM5.5 produces a credible climate that is appropriate for science applications and is ready for integration into the National Center for Atmospheric Research's (NCAR's) next-generation climate model.

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Ocean surface wind fields estimated from satellite active and passive microwave instruments

Cited by 104 publications

References 17 publications

Assessing a Satellite-Era Perspective of the Global Water Cycle

Assessing a Satellite-Era Perspective of the Global Water Cycle

Modelling of primary aerosols in the chemical transport model MOCAGE: development and evaluation of aerosol physical parameterizations

The path to CAM6: coupled simulations with CAM5.4 and CAM5.5

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