Frank J. Wentz

A well‐calibrated ocean algorithm for special sensor microwave / imager

I describe an algorithm for retrieving geophysical parameters over the ocean from special sensor microwave/imager (SSM/I) observations. This algorithm is based on a model for the brightness temperature T(sub B) of the ocean and intervening atmosphere. The retrieved parameters are the near-surface wind speed W, the columnar water vapor V, the columnar cloud liquid water L, and the line-of-sight wind W(sub LS). I restrict my analysis to ocean scenes free of rain, and when the algorithm detects rain, the retrievals are discarded. The model and algorithm are precisely calibrated using a very large in situ database containing 37,650 SSM/I overpasses of buoys and 35,108 overpasses of radiosonde sites. A detailed error analysis indicates that the T(sub B) model rms accuracy is between 0.5 and 1 K and that the rms retrieval accuracies for wind, vapor, and cloud are 0.9 m/s, 1.2 mm, and 0.025 mm, respectively. The error in specifying the cloud temperature will introduce an additional 10% error in the cloud water retrieval. The spatial resolution for these accuracies is 50 km. The systematic errors in the retrievals are smaller than the rms errors, being about 0.3 m/s, 0.6 mm, and 0.005 mm for W, V, and L, respectively. The one exception is the systematic error in wind speed of -1.0 m/s that occurs for observations within +/-20 deg of upwind. The inclusion of the line-of-sight wind W(sub LS) in the retrieval significantly reduces the error in wind speed due to wind direction variations. The wind error for upwind observations is reduced from -3.0 to -1.0 m/s. Finally, I find a small signal in the 19-GHz, horizontal polarization (h(sub pol) T(sub B) residual DeltaT(sub BH) that is related to the effective air pressure of the water vapor profile. This information may be of some use in specifying the vertical distribution of water vapor.

How Much More Rain Will Global Warming Bring

Climate models and satellite observations both indicate that the total amount of water in the atmosphere will increase at a rate of 7% per kelvin of surface warming. However, the climate models predict that global precipitation will increase at a much slower rate of 1 to 3% per kelvin. A recent analysis of satellite observations does not support this prediction of a muted response of precipitation to global warming. Rather, the observations suggest that precipitation and total atmospheric water have increased at about the same rate over the past two decades.

Observations of Coupling between Surface Wind Stress and Sea Surface Temperature in the Eastern Tropical Pacific

Satellite measurements of surface wind stress from the QuikSCAT scatterometer and sea surface temperature (SST) from the Tropical Rainfall Measuring Mission Microwave Imager are analyzed for the three-month period 21 July‐20 October 1999 to investigate ocean‐atmosphere coupling in the eastern tropical Pacific. Oceanic tropical instability waves (TIWs) with periods of 20‐40 days and wavelengths of 1000‐2000 km perturb the SST fronts that bracket both sides of the equatorial cold tongue, which is centered near 1 8S to the east of 1308W. These perturbations are characterized by cusp-shaped features that propagate systematically westward on both sides of the equator. The space‐time structures of these SST perturbations are reproduced with remarkable detail in the surface wind stress field. The wind stress divergence is shown to be linearly related to the downwind component of the SST gradient with a response on the south side of the cold tongue that is about twice that on the north side. The wind stress curl is linearly related to the crosswind component of the SST gradient with a response that is approximately half that of the wind stress divergence response to the downwind SST gradient. The perturbed SST and wind stress fields propagate synchronously westward with the TIWs. This close coupling between SST and wind stress supports the Wallace et al. hypothesis that surface winds vary in response to SST modification of atmospheric boundary layer stability.

The complex dielectric constant of pure and sea water from microwave satellite observations

We provide a new fit for the microwave complex dielectric constant of water in the salinity range between 0-40 ppt using two Debye relaxation wavelengths. For pure water, the fit is based on laboratory measurements in the temperature range between -20/spl deg/C and +40/spl deg/C including supercooled water and for frequencies up to 500 GHz. For sea water, our fit is valid for temperatures between -2/spl deg/C and +29/spl deg/C and for frequencies up to at least 90 GHz. At low frequencies, our new model is a modified version of the Klein-Swift model. We compare the results of the new fit with various other models and provide a validation using an extensive analysis of brightness temperatures from the Special Sensor Microwave Imager.

Measurement of oceanic wind vector using satellite microwave radiometers

The possibility of retrieving both wind speed and direction from microwave radiometer measurements of the ocean is studied using Special Sensor Microwave/Imager (SSM/I) measurements collocated with buoy reports from the National Data Buoy Center (NDBC). A physically based algorithm is used to retrieve the wind speed. The RMS difference between the SSM/I and buoy wind speed is 1.6 m/s for 3321 comparisons. It is found that the SSM/I minus buoy wind speed difference is correlated with wind direction. When this wind direction signal is removed, the RMS difference between the SSM/I and buoy winds reduces to 1.3 m/s. The wind direction signal is used to make global, low-resolution maps of the monthly mean oceanic vector. The wind direction sensing capability of a prospective two-look satellite radiometer is also processed. >

A Reanalysis of the MSU Channel 2 Tropospheric Temperature Record

Abstract Over the period from 1979 to 2001, tropospheric trends derived from a widely cited analysis of the Microwave Sounding Unit (MSU) temperature record show little or no warming, while surface temperature trends based on in situ observations show a pronounced warming of ∼0.2 K decade−1. This discrepancy between trends at the surface and in the upper atmosphere has been a source of significant debate. Model predictions of amplification of warming with height in the troposphere are clearly inconsistent with the available observations, leading some researchers to question the adequacy of their representation of the water vapor greenhouse feedback. A reanalysis of the MSU channel 2 dataset, with the objective of providing a second independent source of these data, is described in this paper. Results presented herein show a global trend of 0.097 ± 0.020 K decade−1, generally agreeing with the work of Prabhakara et al. but in disagreement with the MSU analysis of Christy and Spencer, which shows significan...

Identification of human-induced changes in atmospheric moisture content

Data from the satellite-based Special Sensor Microwave Imager (SSM/I) show that the total atmospheric moisture content over oceans has increased by 0.41 kg/m2 per decade since 1988. Results from current climate models indicate that water vapor increases of this magnitude cannot be explained by climate noise alone. In a formal detection and attribution analysis using the pooled results from 22 different climate models, the simulated “fingerprint” pattern of anthropogenically caused changes in water vapor is identifiable with high statistical confidence in the SSM/I data. Experiments in which forcing factors are varied individually suggest that this fingerprint “match” is primarily due to human-caused increases in greenhouse gases and not to solar forcing or recovery from the eruption of Mount Pinatubo. Our findings provide preliminary evidence of an emerging anthropogenic signal in the moisture content of earths atmosphere.

A model function for the ocean-normalized radar cross section at 14 GHz derived from NSCAT observations

A model for the ocean surface normalized radar cross section σo is derived from 3 months of NASA scatterometer (NSCAT) observations (September 15 to December 18, 1996). The model expresses σo as a function of wind speed, relative wind direction, incidence angle, and polarization. The dependence of σo on wind speed is based on collocated special sensor microwave/imager (SSM/I) satellite wind retrievals and European Centre for Medium-Range Weather Forecasts (ECMWF) model winds. We find that at low winds (<5 ms−1), the SSM/I winds are more reliable than ECWMF, probably owing to small location errors in the ECMWF wind features. The primary wind direction dependence of σo (i.e., the second harmonic) is found from histograms of the σo difference between the forward and aft antennas. The σo versus wind speed relationship is adjusted for cross-swath incidence angle differences and is then incorporated into the NSCAT 1 model used to process the 10-month (September 15, 1996, to June 29, 1997) NSCAT data set. The resulting NSCAT 1 wind vectors are compared to ECMWF wind fields and buoys. The mean and standard deviation of the NSCAT minus ECMWF (buoy) wind speed difference are 0.05 and 1.78 ms−1 (−0.29 and 1.26 ms−1), respectively. The wind direction mean and standard deviation differences are 0.8° and 18.5° (7.9° and 15.7°), respectively. The difference between the NSCAT and the ECMWF (buoy) direction exceeds 90° only 1.1% (1.2%) of the time. We have no explanation for why the buoy wind directions are biased 8° relative to both NSCAT and ECMWF.

Cloud Liquid Water Path from Satellite-Based Passive Microwave Observations: A New Climatology over the Global Oceans

Abstract This work describes a new climatology of cloud liquid water path (LWP), termed the University of Wisconsin (UWisc) climatology, derived from 18 yr of satellite-based passive microwave observations over the global oceans. The climatology is based on a modern retrieval methodology applied consistently to the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer (AMSR) for Earth Observing System (EOS) (AMSR-E) microwave sensors on eight different satellite platforms, beginning in 1988 and continuing through 2005. It goes beyond previously published climatologies by explicitly solving for the diurnal cycle of cloud liquid water by providing statistical error estimates, and includes a detailed discussion of possible systematic errors. A novel methodology for constructing the climatology is used in which a mean monthly diurnal cycle as well as monthly means of the liquid water path are derived simul...

High-Resolution Satellite Measurements of the Atmospheric Boundary Layer Response to SST Variations along the Agulhas Return Current

Abstract The marine atmospheric boundary layer (MABL) response to sea surface temperature (SST) perturbations with wavelengths shorter than 30° longitude by 10° latitude along the Agulhas Return Current (ARC) is described from the first year of SST and cloud liquid water (CLW) measurements from the Advanced Microwave Scanning Radiometer (AMSR) on the Earth Observing System (EOS) Aqua satellite and surface wind stress measurements from the QuikSCAT scatterometer. AMSR measurements of SST at a resolution of 58 km considerably improves upon a previous analysis that used the Reynolds SST analyses, which underestimate the short-scale SST gradient magnitude over the ARC region by more than a factor of 5. The AMSR SST data thus provide the first quantitatively accurate depiction of the SST-induced MABL response along the ARC. Warm (cold) SST perturbations produce positive (negative) wind stress magnitude perturbations, leading to short-scale perturbations in the wind stress curl and divergence fields that are li...