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William B. Rossow
and
John J. Bates

Abstract

The current heterogeneity of the existing global collection of measuring assets, satellite and surface based, is a major obstacle to creating a truly integrated, globally uniform information system. Many surveys of Earth science needs over the last 40+ years mention research-to-operations (R2O) actions that are needed to develop such a system but focus mainly on making and collecting measurements with little discussion of the processing system and the integrated team of talented scientists needed to turn raw observations into usable information or the archival system needed to make reliable information readily and widely accessible. We discuss an example of addressing the problems in producing globally uniform information from such observations: the creation in 1982–83 of the data collection, processing, and archival system for the International Satellite Cloud Climatology Project (ISCCP). ISCCP was originally built in a research environment for climate studies, but has now transitioned to a fully operational environment to extend the length of the data record for climate research. Transforming multiple satellite observations into a uniform, global set of physical information about clouds that is readily accessible was and is challenging for several reasons. In this short commentary, we reflect on the experiences and lessons learned in building the ISCCP observation–processing–archival system to address these challenges and discuss the ISCCP R2O process to serve as a pathfinder for building a global observing and information system.

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Lei Shi
,
John J. Bates
, and
Changyong Cao

Abstract

Measurements from the simultaneous nadir overpass (SNO) observations of the High Resolution Infrared Radiation Sounder (HIRS) are examined. The SNOs are the measurements taken at the orbital intersections of each pair of satellites viewing the same Earth target within a few seconds at high latitudes. The dataset includes satellites from NOAA-6 through NOAA-17 from 1981 to 2004. The authors found that for many channels, intersatellite biases vary significantly with respect to scene radiances. For a number of these channels, the change of the intersatellite bias within a channel can be larger than 1 mW (m2 sr cm−1)−1, which is approximately 1 K in brightness temperature, across the channel scene radiance ranges. Many of the channels with large variations of intersatellite biases are the tropospheric sounding channels centered along the sharp slope of the transmission line. These channels are particularly sensitive to the difference in spectral response functions from satellite to satellite. This radiance-dependency feature of the biases is an important factor to consider when performing intersatellite calibrations.

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Lei Shi
,
Ge Peng
, and
John J. Bates

Abstract

High-latitude ocean surface air temperature and humidity derived from intersatellite-calibrated High-Resolution Infrared Radiation Sounder (HIRS) measurements are examined. A neural network approach is used to develop retrieval algorithms. HIRS simultaneous nadir overpass observations from high latitudes are used to intercalibrate observations from different satellites. Investigation shows that if HIRS observations were not intercalibrated, then it could lead to intersatellite biases of 1°C in the air temperature and 1–2 g kg−1 in the specific humidity for high-latitude ocean surface retrievals. Using a full year of measurements from a high-latitude moored buoy site as ground truth, the instantaneous (matched within a half-hour) root-mean-square (RMS) errors of HIRS retrievals are 1.50°C for air temperature and 0.86 g kg−1 for specific humidity. Compared to a large set of operational moored and drifting buoys in both northern and southern oceans greater than 50° latitude, the retrieval instantaneous RMS errors are within 2.6°C for air temperature and 1.4 g kg−1 for specific humidity. Compared to 5 yr of International Maritime Meteorological Archive in situ data, the HIRS specific humidity retrievals show less than 0.5 g kg−1 of differences over the majority of northern high-latitude open oceans.

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Clara Deser
,
Susan Wahl
, and
John J. Bates

Abstract

Satellite observations of visible cloudiness and sea surface temperature (SST) are used to test the hypothesis that the configuration of cool low-level winds blowing across a sharp SST front in the equatorial eastern Pacific gives rise to stratiform clouds on the warm (downstream) side of the front. The results show that there is a maximum in low clouds over the equatorial front during the cold season of 1988 when the front and cross-isotherm winds were strong. The low-cloud maximum was reduced in the warm El Niño year of 1987, consistent with the weakening of the front. Instability waves along the equatorial front were pronounced during the summer and autumn of 1988. The results show a strong association between visible cloud and the SST waves, with enhanced (reduced) cloudiness in the warm troughs (cold crests) of the waves.

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Xianmian Wu
,
John J. Bates
, and
Sirijodha Singh khalsa

Abstract

Measurements of brightness temperature from the water vapor band channels of the National Oceanic and Atmospheric Administration polar satellites from 1981 through 1988 are analyzed. Only clear and cloud-cleared measurements from the operational sounding product are used to produce averages for bins of 2.5° latitude by 2.5° longitude and 5 days. The standard deviations of random errors for these bins are estimated. A unique feature of this dataset is its ability to identify the dry regions in the middle and upper troposphere with unprecedented detail. Results agree with the known climatology in the tropics.

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Gary A. Wick
,
John J. Bates
, and
Donna J. Scott

Abstract

The latest Geostationary Operational Environmental Satellites (GOES) have facilitated significant improvements in the ability to measure sea surface temperature (SST) from geostationary satellites. Nonetheless, difficulties associated with sensor calibration and oceanic near-surface temperature gradients affect the accuracy of the measurements and the estimation and interpretion of the diurnal cycle of the bulk SST. Overall, measurements of SST from the GOES imagers on the GOES-8–10 satellites are shown to have very small bias (<0.02 K) and rms differences of between 0.6 and 0.9 K relative to buoy observations. Separate consideration of individual measurement times, however, demonstrates systematic bias variations of over 0.6 K with measurement hour. These bias variations significantly affect both the amplitude and shape of estimates of the diurnal SST cycle. Modeled estimates of the temperature difference across the oceanic cool skin and diurnal thermocline show that bias variations up to 0.3 K can result from variability in the near-surface layer. Oceanic near-surface layer and known “satellite midnight” calibration effects, however, explain only a portion of the observed bias variations, suggesting other possible calibration concerns. Methods of explicitly incorporating skin layer and diurnal thermocline effects in satellite bulk SST measurements were explored in an effort to further improve the measurement accuracy. While the approaches contain more complete physics, they do not yet significantly improve the accuracy of bulk SST measurements due to remaining uncertainties in the temperature difference across the near-surface layer.

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Wesley Berg
,
John J. Bates
, and
Darren L. Jackson

Abstract

Satellite microwave and infrared instruments sensitive to upper-tropospheric water vapor (UTWV) are compared using both simulated and observed cloud-cleared brightness temperatures (Tb’s). To filter out cloudy scenes, a cloud detection algorithm is developed for the Special Sensor Microwave/Temperature-2 (SSM/T2 or T2) data using the 92- and 150-GHz window channels. An analysis of the effect of clouds on the T2 183-GHz channels shows sensitivity primarily to high clouds containing ice, resulting in significantly better sampling of UTWV Tb’s over the convective zones and regions of persistent cloudiness. This is in contrast to the infrared sensors, which are extremely sensitive to any cloud contamination in the satellite field of view. A comparison of simulated UTWV Tb’s from T2, the High-resolution Infrared Sounder (HIRS), and the Visible Infrared Spin Scan Radiometer (VISSR) indicates a higher overall sensitivity to changes in UTWV in the T2 channel. HIRS and VISSR, however, are more sensitive to moisture at higher levels. Cloud-cleared Tb’s from T2 and HIRS were found to be highly correlated in the tropical dry zones and in regions of strong seasonal variability but less correlated at higher latitudes. The advantages of the microwave T2 sensor for monitoring UTWV are demonstrated by its greater sensitivity to changes in upper-tropospheric moisture and superior coverage over cloudy regions.

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John J. Bates
,
X. Wu
, and
D. L. Jackson

Abstract

A method for the intercalibration of the high-resolution infrared sounder (HIRS) upper-tropospheric water vapor band brightness temperature data is developed and applied to data from 1981 to 1993. Analysis of the adjusted anomaly time series show the location and strength of both the large-scale ascending and descending circulations in the Tropics as well as water vapor anomalies. Comparison of these HIRS data with outgoing longwave radiation and sea surface temperature anomalies reveals that both convection and increased upper-tropospheric moisture occur over anomalously warm water in the deep Tropics. The development and movement of deep convection and increased upper-tropospheric moisture can clearly he traced during the El Niño/Southern Oscillation warm events. These HIRS data are particularly useful in monitoring upper-tropospheric water vapor variability between the Tropics and subtropics.

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Kenneth R. Knapp
,
John J. Bates
, and
Bruce Barkstrom
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Thomas M. Smith
,
Phillip A. Arkin
,
John J. Bates
, and
George J. Huffman

Abstract

Systematic biases in satellite-based precipitation estimates can be the dominant component of their uncertainty. These biases may not be reduced by averaging, which makes their evaluation particularly important. Described here are several methods of evaluating the biases and their characteristics. Methods are developed and tested using monthly average precipitation estimates from several satellites. Direct estimates of bias are obtained from analysis of satellite–gauge estimates, and they indicate the general bias patterns and magnitudes over land. Direct estimates cannot be computed over the oceans, so indirect-bias estimates based on ensembles of satellite and gauge estimates are also developed. These indirect estimates are consistent with direct estimates in locations where they can be compared, while giving near-global coverage. For both bias estimates computed here, the bias uncertainty is higher than nonsystematic error estimates, caused by random or sampling errors and which have been previously reported by others for satellite estimates.

Because of their greater spatial coverage, indirect-bias estimates are preferable for bias adjustment of satellite-based precipitation. The adjustment methods developed reduce the bias associated with each satellite while estimating the remaining bias uncertainty for the satellite. By adjusting all satellites to a consistent base, the bias adjustments also minimize artificial climate-scale variations in analyses that could be caused by the addition or removal of satellite products as their availability changes.

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