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Norman C. Grody

Abstract

The microwave sounding unit (MSU) aboard the NOAA polar orbiting satellites contains four channels in the oxygen band, at 50.30, 53.74, 54.96 and 57.95 GHz, which receive thermal radiation originating primarily from four regions ranging from the surface to the lower stratosphere. This study focuses on the measurements obtained for a convective storm over the central United States beginning 12 April 1979.

Temperature and precipitation effects are examined by comparing the MSU measurements with “clear column” brightness temperatures computed from radiosonde data. Decreases of up to 12 K from clear column values in the 53.74 GHz brightness temperature field identify precipitation regions. Measurements in the nonprecipitating areas correspond to temperatures near the 700 mb level where the channel has its maximum response. The 54.96 GHz upper tropospheric sounding channel (peaking near 300 mb) displays up to a 2 K decrease at the storm center, compared to neighboring measurements. This decrease around the storm center agrees with clear column values and is attributed to temperature changes due to evaporative cooling around the 1 50 mb tropopause level. For the 57.95 GHz stratosphere sounding channel (peaking near 90 mb) the measurements also compare well with the radiosonde data, although the measurements mainly reflect large-scale temperature variations rather than any local storm features.

In addition to providing atmospheric data, the MSU detects surface temperature and emissivity variations in the most transparent channel at 50.30 GHz. By combining the “window” channel with the 53.74 6Hz channel, temperature effects are minimized and surface emissivity is derived in nonprecipitating areas. The emissivity measurements are useful for displaying the wet ground in the clearer areas behind the advancing storm system.

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Fuzhong Weng and Norman C. Grody

Abstract

Based on the radiative transfer theory, the microwave radiance emanating from ice clouds at arbitrary viewing angles is expressed as an analytic function of the cloud ice water path (IWP), the particle effective diameter (D e), and the particle bulk density (ρ i). Thus, for a given particle density, the earth-viewing measurements at two frequencies (e.g., 340 and 89 GHz) can provide an estimate of D e and IWP for submillimeter-size particles. This physical retrieval is tested using data from the Millimeter-wave Imaging Radiometer (MIR). A comparison among MIR, radar, and infrared sensor measurements shows that the MIR frequencies are affected primarily by thick ice clouds such as cirrus anvil and convection. Over highly convective areas, the measurements from 89 to 220 GHz are nearly identical since the scattering by large ice particles aloft approaches the geometric optics limit, which is independent of wavelength. Under these conditions, only the lower MIR frequencies (89 and 150 GHz) are used to retrieve D e and IWP. In general, the MIR-derived D e displays a reasonable spatial distribution comparable to the radar and infrared measurements. However, the magnitude of the IWP remains highly uncertain because of insufficient information on the ice particle bulk density.

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Norman C. Grody and Paul P. Pellegrino

Abstract

Several frontal systems over Europe in August 1975 and January and February 1976 are examined using scanning microwave spectrometer (SCAMS) data. Comparisons are made with thermal fields constructed from radiosonde temperatures. Because of the cloud penetrating property of microwave radiation, together with the high stability and sensitivity of the SCAMS instrument, many of the problems encountered with infrared remote sensing instruments are absent in the SCAMS measurements. Synoptic-scale features displayed by the SCAMS retrievals are comparable with radiosonde temperature analysts under both clear and cloudy conditions. Results from the synoptic-scale studies, confirm the theoretical expectations of standard error, which are 2.2, 2.3, 2.9 and 3.6 K at the 700, 500, 300 and 100 mb levels, respectively. These SCAMS results were obtained using “theoretical” temperature retrieval coefficients, which are based on the simulated SCAMS response to a historical sample of independent temperature statistics and as such are unbiased toward any particular meteorological situation. The independence of SCAMS results is substantiated by the small differences found at pressures greater than 300 mb using “derived” temperature retrieval coefficients based on SCAMS measured response to a set of dependent radiosonde temperatures. At pressures less than 300 mb the lack of better weighting functions necessitates the use of improved statistical information in the theoretical coefficients.

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Ralph R. Ferraro, Fuzhong Weng, Norman C. Grody, and Alan Basist

The Special Sensor Microwave/Imager (SSM/I), first placed into operation in July 1987, has been making measurements of earth-emitted radiation for over eight years. These data are used to estimate both atmospheric and surface hydrological parameters and to generate a time series of global monthly mean products averaged to a 1° lat × 1° long grid. Specifically, this includes monthly estimates of rainfall and its frequency, cloud liquid water and cloud frequency, water vapor, snow cover frequency, and sea ice frequency. This study uses seasonal mean values to demonstrate the spatial and temporal distributions of these hydrological variables. Examples of interannual variability such as the 1993 flooding in the Mississippi Valley and the 1992–93 snow cover changes over the United States are used to demonstrate the utility of these data for regional applications.

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Claude N. Williams, Alan Basist, Thomas C. Peterson, and Norman Grody

The current network of internationally exchanged in situ station data is not distributed evenly nor densely around the globe. Consequently, the in situ data contain insufficient information to identify fine spatial structure and variations over many areas of the world. Therefore, satellite observations need to be blended with in situ data to obtain higher resolution over the global land surface. Toward this end, the authors calibrated and independently verified an algorithm that derives land surface temperatures from the Special Sensor Microwave/Imager (SSM/I). This study explains the technique used to refine a set of equations that identify various surface types and to make corresponding dynamic emissivity adjustments. This allowed estimation of the shelter height temperatures from the seven channel measurements flown on the SSM/I instrument. Data from first-order in situ stations over the eastern half of the United States were used for calibration and intersatellite adjustment. The results show that the observational difference between the in situ point measurements and the SSM/I-derived areal values is about 2°C with statistical characteristics largely independent of surface type. High-resolution monthly mean anomalies generated from the U.S. cooperative network served as independent verification over the same study area. This verification work determined that the standard deviation of the monthly mean anomalies is 0.76°C at each 1° × 1° grid box. This level of accuracy is adequate to blend the SSM/I-derived temperature anomaly data with in situ data for monitoring global temperature anomalies in finer detail.

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Roy W. Spencer, John R. Christy, and Norman C. Grody

Abstract

A method for measuring global atmospheric temperature anomalies to a high level of precision from satellites is demonstrated. Global data from the Microwave Sounding Units (MSUs), flying on NOAA satellites since late 1978, have been analysed to determine the extent to which these data can reveal atmospheric temperature anomalies on bidaily and longer time scales for regional and larger space scales. The global sampling provided by the MSUs is an important asset, with most of the earth sampled bidaily from each of (typically) two instruments flying concurrently on separate satellites at different solar times. The primary source of tropospheric thermal information is from the MSU 53.74 GHz channel. This channel is primarily sensitive to thermal emission from molecular oxygen in the middle troposphere, with relatively little sensitivity to water vapor, the earth's surface, and cloud (especially cirrus) variations. The long-term stability of the oxygen mixing ratio in the atmosphere makes it an ideal tracer for climate monitoring purposes. Lower stratospheric temperature anomalies are derived from the MSU 57.95 GHz channel.

Comparisons between monthly MSU temperature anomalies and corresponding thermometer-measured anomalies for the United States reveal a high (0.9) correlation, but hemispheric anomalies show much lower correlations. This results from some combination of poor thermometer sampling of remote regions and weak coupling of surface and deep-tropospheric temperature anomalies in tropical areas.

Analysis of data from two of the MSUs (on NOAA-6 and NOAA-7), whose operational periods overlapped by two years, reveals that hemispheric temperature anomalies measured by the separate instruments are very similar (to about 0.01°C) on monthly time scales. Their combined time series of unfiltered two-day hemispheric averages show standard deviations of their mean of 0.15°–0.20°C and standard deviations of their average difference of 0.02°–0.03°C, indicating a signal-to-noise ratio of 40 for the Southern Hemisphere and 45 for the Northern Hemisphere. The intercomparison period also reveals no evidence of calibration drift between satellites at the 0.01°C level. This was substantiated by two 15-month comparisons of NOAA-6 with rawinsonde data from 45 stations in the eastern United States, which revealed 0.013°C net difference over five years. Monthly averaged comparisons between individual rawinsonde and NOAA-6 data from 1980 through 1982 reveal a monthly standard deviation of their difference of 0.04°C. The statistical and geophysical portions of this noise are found to be about equal in magnitude, 0.03°C. The single-satellite noise due to imperfect sampling for ten-day, 2.5° gridpoint temperatures was calculated by measuring the standard deviation of the difference between two satellites with ranges from 0.2°C in the tropics to 0.4°C in middle latitudes.

The period of analysis (1979–84) reveals that Northern and Southern hemispheric tropospheric temperature anomalies (from the six-year mean) am positively correlated on multiseasonal time scales but negatively correlated on shorter time scales. The 1983 ENSO dominates the record, with early 1983 zonally averaged tropical temperatures up to 0.6°C warmer than the average of the remaining years. These natural variations are much larger than that expected of greenhouse enhancements, and so it is likely that a considerably longer period of satellite record must accumulate for any longer-term trends to be revealed.

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Alan N. Basist, Chester F. Ropelewski, and Norman C. Grody

Abstract

The Microwave Sounding Units (MSU) aboard the NOAA series of polar-orbiting satellites (TIROS-N to NOAA-12) have provided stable and precise measurements of vertically integrated atmospheric temperature since December 1978. Comparisons are made between the MSU channel measurements and temperatures derived from the global data assimilation system (GDAS) at the National Meteorological Center (NMC) for the period 1979–1990. The largest correlations occur at high to midlatitudes, where the troposphere exhibits large monthly anomaly fields, and where radiosondes provide ample coverage for the GDAS. Intermonthly differences from each dataset had global correlations above 0.97. However, poor correlations with MSU were noted over areas of high terrain and tropical landmasses. These poorer correlations can be attributed to temporal changes and data limitations in the GDAS analysis. Comparisons between the GDAS and MSU temperature anomaly fields indicate that frequent model changes mask the climate signal in the GDAS analysis. Nonetheless, the study suggests that both GDAS- and MSU-derived temperature anomalies detect similar spatial and temporal variability over regions where the GDAS is data rich and the signal is large, that is, the El Niño-Southern Oscillations. This study suggests that the NMC reanalysis, using a fixed assimilation model, will produce a stable dataset of tropospheric temperatures. Therefore, the 35 years of reanalyzed NMC model data can he used in conjunction with satellite data to improve the suite of tools used in climate monitoring.

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Alan Basist, Norman C. Grody, Thomas C. Peterson, and Claude N. Williams

Abstract

The worldwide network of in situ land surface temperatures archived in near-real time at the National Climatic Data Center (NCDC) has limited applications, since many areas are poorly represented or provide no observations. Satellite measurements offer a possible way to fill in the data voids and obtain a complete map of surface temperature over the entire globe. A method has been developed to calculate near-surface temperature using measurements from the Special Sensor Microwave/Imager (SSM/I). To accomplish this, the authors identify numerous surface types and make dynamic adjustments for variations in emissivity. Training datasets were used to define the relationship between the seven SSM/I channels and the near-surface temperature. For instance, liquid water on the surface reduces emissivity; therefore, the authors developed an adjustment to correct for this reduction. Other surface types (e.g., snow, ice, and deserts) as well as precipitation are identified, and numerous adjustments and/or filters were developed for these features. The article presents the results obtained from training datasets, as well as an independent case study, containing extreme conditions for deriving temperature from the SSM/I. The U.S. networks of first-order and cooperative stations, quality controlled by NCDC, serve as validation data. The correlation between satellite-derived and in situ temperatures during the independent case (“Blizzard of 1996”) was greater than 0.95, and the standard error was 2°C. The authors also present SSM/I-derived snow cover and wetness maps from this 2-week period of the blizzard. A prototype for blending the satellite and in situ measurements into a single land surface temperature product is also presented.

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Thomas C. Peterson, Alan N. Basist, Claude N. Williams, and Norman C. Grody

A near-global surface temperature dataset was produced by blending several sources of information. For the oceans, these include in situ and infrared satellite-derived sea surface temperatures that were already processed into a monthly product. Land data analysis uses two sources of data. The first is high quality monthly in situ reports from the Global Historical Climatologic Network with more than 1000 stations from around the world. The second source of information is the recently developed passive microwave satellite-derived land surface temperature derivation methodology described in Williams et al. These data are blended on a 1° × 1° grid that excludes only ice- and snow-covered regions lacking in situ observations. Available starting in January 1992 and updated 10 days after the end of the calendar month, this product is useful for monitoring regional climate anomalies and provides insights into climate variations.

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Fuzhong Weng, Norman C. Grody, Ralph Ferraro, Alan Basist, and David Forsyth

Abstract

A Special Sensor Microwave/Imager (SSM/I) algorithm is developed to measure both cloud liquid water path (LWP) and cloud frequency (CF) over the oceans. For climate analysis, the LWP and CF parameters are computed on pentad and monthly timescales. Comparisons are made between cloud frequencies obtained from microwave and visible/infrared measurements. It is shown that the SSM/I CF correlates with International Satellite Cloud Climatology Program low- and middle-level cloudiness. Interannual variations of monthly LWP are found to be strongly correlated with El Niño and La Niña events. In general, positive LWP anomalies are associated with positive SST anomalies. However, positive LWP anomalies may also occur in regions of negative SST anomalies. This is probably due to an increase in warm top rain clouds, produced from low-level convergence. When pentads of outgoing longwave radiation data are compared to the LWP, they both show the detailed structure for atmospheric intraseasonal oscillations at 30–60-day periods. However, there are some interesting differences. Finally, as an important application, the monthly LWP is compared with simulations from a general circulation model. While the simulation captures the locations of observed maxima and minima, there is a large discrepancy between the model and measurement for the Northern Hemisphere in summer.

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