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The Global Precipitation Climatology Project (GPCP) monthly precipitation exhibits a significant negative trend during 1979–2004 over southern tropical Africa from the Congo River Basin to the east coast. This trend appears as a more than 20% drop beginning in 1992 in the 6-year and 9-year averages of the areal mean GPCP satellite-gauge precipitation, whose magnitude is largely determined by the gauge analyses. This paper's analysis of satellite precipitation estimates, gauge precipitation analyses, and gauge coverage information suggests that the negative precipitation trend is only true in part of southern tropical Africa but the magnitude is much smaller than that calculated from the GPCP. In the eastern portion of the region, the precipitation drop in the GPCP is confirmed by the satellite-only estimates but the decrease of more than 16% is amplified by a change in gauge coverage. In the western portion of the region, basically the southern Congo River Basin, all gauge dependent products show a negative precipitation trend, which is much larger in the GPCP merged satellite-gauged data set, but not supported by the satellite-only precipitation estimates. In this study we conclude that for the Congo River Basin, where both the mean precipitation and its spatial gradient are high, the spurious negative trend detected in the GPCP precipitation is caused by a significant change in local gauge coverage and the methodology used by the GPCP to merge satellite and gauge data during the analysis period. Copyright © 2009 Royal Meteorological Society

The Advanced Very High Resolution Radiometer (AVHRR) outgoing longwave radiation (OLR) product, which NOAA has been operationally generating since 1979, is a very long data record that has been used in many applications, yet past studies have shown its limitations and several algorithm-related deficiencies. Ellingson et al. have developed the multispectral algorithm that largely improved the accuracy of the narrowband-estimated OLR as well as eliminated the problems in AVHRR. NOAA has been generating High Resolution Infrared Radiation Sounder (HIRS) OLR operationally since September 1998. In recognition of the need for a continuous and long OLR data record that would be consistent with the earth radiation budget broadband measurements in the National Polar-orbiting Operational Environmental Satellite System (NPOESS) era, and to provide a climate data record for global change studies, a vigorous reprocessing of the HIRS radiance for OLR derivation is necessary. This paper describes the development of the new HIRS OLR climate dataset. The HIRS level 1b data from the entire Television and Infrared Observation Satellite N-series (TIROS-N) satellites have been assembled. A new radiance calibration procedure was applied to obtain more accurate and consistent HIRS radiance measurements. The regression coefficients of the HIRS OLR algorithm for all satellites were rederived from calculations using an improved radiative transfer model. Intersatellite calibrations were performed to remove possible discontinuity in the HIRS OLR product from different satellites. A set of global monthly diurnal models was constructed consistent with the HIRS OLR retrievals to reduce the temporal sampling errors and to alleviate an orbital-drift-induced artificial trend. These steps significantly improved the accuracy, continuity, and uniformity of the HIRS monthly mean OLR time series. As a result, the HIRS OLR shows a comparable stability as in the Earth Radiation Budget Satellite (ERBS) nonscanner OLR measurements. HIRS OLR has superb agreement with the broadband observations from Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth’s Radiant Energy System (CERES) in the ENSO-monitoring regions. It shows compatible ENSO-monitoring capability with the AVHRR OLR. Globally, HIRS OLR agrees with CERES with an accuracy to within 2 W m−2 and a precision of about 4 W m−2. The correlation coefficient between HIRS and CERES global monthly mean is 0.997. Regionally, HIRS OLR agrees with CERES to within 3 W m−2 with precisions better than 3 W m−2 in most places. HIRS OLR could be used for constructing climatology for applications that plan to use NPOESS ERBS and previously used AVHRR OLR observations. The HIRS monthly mean OLR data have high accuracy and precision with respect to the broadband observations of ERBE and CERES. It can be used as an independent validation data source. The uniformity and continuity of HIRS OLR time series suggest that it could be used as a reliable transfer reference for the discontinuous broadband measurements from ERBE, CERES, and ERBS.

The Coordinated Enhanced Observing Period (CEOP) is an international project that was first proposed by the Global Energy and Water Cycle Experiment (GEWEX) in 1997 and was formally launched in 2001. Since that time it has been adopted by the World Climate Research Programme (WCRP), which views it as an essential part of its strategy for developing global datasets to evaluate global climate models, and by the Integrated Global Observing Strategy Partnership (IGOS-P), which views it as the first element of its global water cycle theme. The United States has been an active partner in all phases of CEOP. In particular, the United States has taken the lead in contributing data from a number of reference sites, providing data processing, and archiving capabilities and related research activities through the GEWEX Americas Prediction Project (GAPP). Other U.S. programs and agencies are providing components including model and data assimilation output, satellite data, and other services. The U.S. scienc...

The two monthly precipitation products of the Global Precipitation Climatology Project (GPCP) and the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) are compared on a 23-yr period, January 1979–December 2001. For the long-term mean, major precipitation patterns are clearly demonstrated by both products, but there are differences in the pattern magnitudes. In the tropical ocean the CMAP is higher than the GPCP, but this is reversed in the high-latitude ocean. The GPCP–CMAP spatial correlation is generally higher over land than over the ocean. The correlation between the global mean oceanic GPCP and CMAP is significantly low. It is very likely because the input data of the two products have much less in common over the ocean; in particular, the use of atoll data by the CMAP is disputable. The decreasing trend in the CMAP oceanic precipitation is found to be an artifact of input data change and atoll sampling error. In general, overocean precipitation represented by the GPCP is more reasonable; over land the two products are close, but different merging algorithms between the GPCP and the CMAP can sometimes produce substantial discrepancy in sensitive areas such as equatorial West Africa. EOF analysis shows that the GPCP and the CMAP are similar in 6 out of the first 10 modes, and the first 2 leading modes (ENSO patterns) of the GPCP are nearly identical to their counterparts of the CMAP. Input data changes [e.g., January 1986 for Geostationary Operational Environmental Satellite (GOES) precipitation index (GPI), July 1987 for Special Sensor Microwave Imager (SSM/I), May 1994 for Microwave Sounding Unit (MSU), and January 1996 for atolls] have implications in the behavior of the two datasets. Several abrupt changes identified in the statistics of the two datasets including the changes in overocean precipitation, spatial correlation time series, and some of the EOF principal components, can be related to one or more input data changes.

Traditionally, earth radiation budget studies use polar orbiting satellites to estimate the global distribution of outgoing longwave radiation (OLR). However, the two-pass per day per satellite orbit significantly limits the accuracy of the daily mean OLR due to diurnal variations. Geosynchronous satellites, on the other hand, have high temporal resolution but have less spatial coverage. To increase the accuracy of daily mean of the High Resolution Infrared Radiation Sounder (HIRS) OLR, one could blend the OLR from polar orbiters with the diurnal information provided by the geosynchronous satellite observations. We demonstrate a scheme to generate a hybrid OLR product by integrating the HIRS observations on board of the US National Oceanic and Atmospheric Administration polar satellites and the Geostationary Operational Environment Satellite Imager observations. This kind of product can be utilized to avoid the day/night bias that may appear when broadband longwave is derived from spectral subtraction of a SW signal from an unfiltered total channel with errors in calibration of the short wave part of the spectrum. The paper investigated the errors in the HIRS daily mean OLR at averaging domains of various temporal and spatial scales.

The operational climate monitoring and diagnostic community will continue to favor in using outgoing longwave radiation (OLR) estimates that have long and continuous time series such as those estimated from the High Resolution Infrared Sounder (HIRS). OLR from HIRS data could be generated since these data exist since 1979 and will continue during NPOESS era with Cross-Track Infrared Sounder (CrIS) and HIRS/4 on NPOESS and METOP satellites, respectively. OLR estimated from Earth Radiation Budget Suite (ERBS)/Clouds and the Earth’s Radiant Energy System (CERES) can be used to calibrate the HIRS technique that will be used to generate continuous time series of OLR. This will ensure to have a consistent climate data involving different data sources. OLR generated from CrIS on the afternoon orbit could provide a backup in the event of ERBS’s failure. There will be three evenly spaced sounders (two CrIS and one HIRS/4) that could be used to retrieve OLR allowing therefore a better definition of the diurnal variability of OLR. This paper will present results from GOES sounder data to estimate OLR using an approach similar to that used for HIRS. The instantaneous OLR estimates are compared with collocated OLR products from the CERES instruments onboard TRMM and Terra spacecraft to establish the instantaneous accuracy of the multi-spectral estimation techniques for homogeneous scenes. The hourly GOES sounder OLR estimates are used to study the diurnal cycle of OLR. The time-averaged data are used to estimate the accuracy of the ERBE/CERES and HIRS diurnal cycle models as applied to daily- and monthly-averaged products at different spatial resolutions. The study suggests that the technique can be implemented for NPOESS using the CrIS and HIRS/4 for both augmenting the temporal sampling of OLR estimates and reducing the risk of OLR EDR generation.

The precipitation efficiencies for mesoscale convective systems (MCS) over the central United States are calculated. During July–September 2000 and June–September 2001, 24 MCS for which sufficient data were available occurred over or near Missouri. Precipitable water fields from the hourly Rapid Update Cycle (RUC) and radar-derived precipitation grids are used to calculate the precipitation efficiency. Geostationary Operational Environmental Satellite soundings and RUC winds are used to assess the pre-MCS environment. Statistical analysis reveals that precipitation efficiency has a relatively strong positive correlation with the relative humidity in the layer between the surface and the lifting condensation level; significant negative correlations are found between the precipitation efficiency and both the convective inhibition and the environmental wind shear. The latter, inverse relationship between shear and precipitation efficiency supports the findings of previous investigators.

As part of the Global Precipitation Climatology Project (GPCP), analyses of pentad precipitation have been constructed on a 2.5° latitude–longitude grid over the globe for a 23-yr period from 1979 to 2001 by adjusting the pentad Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) against the monthly GPCP-merged analyses. This adjustment is essential because the precipitation magnitude in the pentad CMAP is not consistent with that in the monthly CMAP or monthly GPCP datasets primarily due to the differences in the input data sources and merging algorithms, causing problems in applications where joint use of the pentad and monthly datasets is necessary. First, pentad CMAP-merged analyses are created by merging several kinds of individual data sources including gauge-based analyses of pentad precipitation, and estimates inferred from satellite observations. The pentad CMAP dataset is then adjusted by the monthly GPCP-merged analyses so that the adjusted pentad analyses match the monthly GPCP in magnitude while the high-frequency components in the pentad CMAP are retained. The adjusted analyses, called the GPCP-merged analyses of pentad precipitation, are compared to several gauge-based datasets. The results show that the pentad GPCP analyses reproduced spatial distribution patterns of total precipitation and temporal variations of submonthly scales with relatively high quality especially over land. Simple applications of the 23-yr dataset demonstrate that it is useful in monitoring and diagnosing intraseasonal variability. The Pentad GPCP has been accepted by the GPCP as one of its official products and is being updated on a quasi-real-time basis.

In order to eventually use the capability of the Geostationary Operational Environmental Satellite (GOES) Sounder to capture the diurnal signal of outgoing longwave radiation (OLR), it is necessary to establish its instantaneous accuracy. Error characteristics of OLR derived from the GOES Sounder are analyzed using Clouds and Earth's Radiant Energy System (CERES) observations. The comparisons are based on over 28 000 data collected in July 1998 and April 2000 over the continental United States. The July data correspond to observations from GOES-8 and -9 and the CERES instrument on board the Tropical Rainfall Measurement Mission (TRMM) satellite. The April data correspond to GOES-8 and -10, and two CERES instruments on board the Terra satellite. The comparisons are for instantaneous, homogeneous scenes of 1° × 1° boxes. Comparisons of GOES Sounder with collocated TRMM and Terra CERES OLR show instantaneous rms agreement to within about 7 W m−2 for day and/or night homogeneous scenes. The GOES tech...

A multispectral approach is used to optimize the identification of raining clouds located at a given altitude estimated from the cloud-top temperature. The approach combines information from five channels on the National Oceanic and Atmospheric Administration Geostationary Operational Environmental Satellite (GOES): visible (0.65 μm), near infrared (3.9 μm), water vapor (6.7 μm), and window channels (11 and 12 μm). The screening of nonraining clouds includes the use of spatial gradient of cloud-top temperature for cirrus clouds (this screening is applied at all times) and the effective radius of cloud-top particles derived from the measurements at 3.9 μm during daytime. During nighttime, only clouds colder than 230 K are considered for the screening; during daytime, all clouds having a visible reflectance greater than 0.40 are considered for the screening, and a threshold of 15 μm in droplet effective radius is used as a low boundary of raining clouds. A GOES rain rate for each indicated raining ...

Two large–scale precipitation datasets, one produced by the Global Precipitation Climatology Project (GPCP) and the other by the Climate Prediction Center of the National Weather Service, and called Climate Prediction Center Merged Analysis of Precipitation (CMAP), were compared. Both datasets blend satellite and gauge estimates of precipitation. And while the latter has its heritage in the GPCP, different analysis procedures and some additional types of input data used by CMAP yielded different values. This study used the error characteristics of the data to assess the significance of the observed differences. Despite good spatial and temporal correlations between the two fields some of the observed differences were significant at the 95% level. These were traced to the use of some different input data such as the use by CMAP of atoll gauges in the tropical Pacific and gauges uncorrected for wetting evaporation and aerodynamic effects. The former impacts the tropical ocean rain amounts and the l...

The Global Precipitation Climatology Project (GPCP) satellite estimates have approximately twice the magnitude of estimates produced from the rain gauges used by the GPCP in central equatorial Africa. Different possible explanations are identified and investigated. The first is that there may not be enough GPCP rain gauges in the area to provide accurate estimates of rainfall for comparisons with satellite estimates. A comparison of the time-averaged GPCP rain gauge estimate with a long-term (over 40 yr) climatology indicates that the GPCP gauge estimates are similar to long-term rainfall averages, suggesting that the GPCP rain gauge analysis is not underestimating rainfall. Two other possible explanations related to the physical properties of the air masses in this region are studied. Evidence from the literature and from estimates of the effective radii of cloud droplets suggests that there may be an abundance of aerosols in central Africa, resulting in an abundance of cloud condensation nuclei, small drops, and inefficient rain processes. The second explanation is that convective clouds forming under dry conditions generally have cloud bases considerably higher than those of clouds forming in moist environments. This leads to an increase in the evaporation rate of the falling rain, resulting in less precipitation reaching the ground. Analysis of the moisture distributions from both the National Centers for Environmental Prediction numerical weather prediction model reanalysis data and the National Aeronautics and Space Administration Water Vapor Project global moisture dataset reveals that the lower troposphere in this region of Africa is relatively dry, which suggests that cloud bases are high.

The Global Precipitation Climatology Project (GPCP) has released monthly mean estimates of precipitation that comprise gauge observations and satellite-derived precipitation estimates. Estimates of standard random error for each month at each grid location are also provided in this data release. One of the primary intended uses of this dataset is the validation of climatic-scale precipitation fields that are produced by numerical models. Nearly coincident with this dataset development, the National Centers for Environmental Prediction and the National Center for Atmospheric Research have joined in a cooperative effort to reanalyze meteorological fields from the present back to the 1940s using a fixed state-of-the-art data assimilation system and large input database. In this paper, monthly accumulations of reanalysis precipitation are compared with the GPCP combined rain gauge–satellite dataset over the period 1988–95. A unique feature of this comparison is the use of standard error estimates tha...

The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5° × 2.5° latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.

Four precipitation estimates were intercompared from their spatial and temporal variability point of view. Two of the products are observational based and the other two are model based assimilation products. An EOF analysis technique was applied to decompose the data into various temporal and spatial modes. All four show similar spatial structure on annual and interannual time scales over continental regions, but differences exist over oceanic regions and observational based products show larger amplitudes. The first three EOF modes together explain 49.4% of the variance.

Three algorithm intercomparison experiments have recently been conducted as part of the Global Precipitation Climatology Project with the goal of (a) assessing the skill of current satellite rainfall algorithms, (b) understanding the differences between them, and (c) moving toward improved algorithms. The results of these experiments are summarized and intercompared in this paper. It was found that the skill of satellite rainfall algorithms depends on the regime being analyzed, with algorithms producing very good results in the tropical western Pacific and over Japan and its surrounding waters during summer, but relatively poor rainfall estimates over western Europe during late winter. Monthly rainfall was estimated most accurately by algorithms using geostationary infrared data, but algorithms using polar data [Advanced Very High Resolution Radiometer and Special Sensor Microwave/Imager (SSM/1)l were also able to produce good monthly rainfall estimates when data from two satellites wore availabl...

Eight years of cloudiness data from the International Satellite Cloud Climatology Project (ISCCP) were analyzed to study the diurnal variation and its annual variation. An empirical orthogonal function (EOF) analysis technique was used to analyze the ISCCP C-2 monthly hourly data. Results show that most of the diurnal variation is explained by the first two dominant EOF modes, which explain the diurnal cycle of clouds. On the basis of this analysis, two modes of diurnal cycle of clouds are defined. Mode 1 as defined by the first EOF indicates that cloudiness maximum occurs at 0500 or 1500 local solar time (LST); Mode 2 as defined by the second EOF indicates that cloudiness maximum occurs at 1000 or 2000 LST. In a broad sense, Mode 1 explains the diurnal cycle of low-level cloudiness, and Mode 2 explains the diurnal variation of high-level cloudiness. Mode 1 explains 58.5% of the normalized variance, and Mode 2 explains 25% of the normalized variance. Both modes of the diurnal cycle show annual variation. The Mode 1 annual variation is large along the western boundary currents over the oceanic regions and moist convective regions over the continents. Interestingly, this annual variation of the diurnal cycle of cloudiness bears some relationship with the annual variation of the surface temperature. This relationship is such that the cloudiness is maximum in the early morning when the annual surface temperature is at its minimum and in the afternoon when the annual surface temperature is at its maximum.

Comparisons have been made between estimates of the outgoing longwave radiation (OLR) at the top of the atmosphere derived from narrowband Advanced Very High Resolution Radiometer (AVHRR) and broadband Earth Radiation Budget Experiment (ERBE) scanning instruments. Four months of measurements are considered: April, July, and October 1985 and January 1986. Instantaneous comparisons (i.e., collocated in space and time) are considered. In the former, regional, zonal, and global analyses are performed using collocated and coincident OLR estimates on a 2.5° latitude-longitude scale. In general, the two datasets are found to be in reasonably good agreement, with the mean state and fundamental variability in time and space captured by the two sets of measurements. However, systematic biases are observed between the two datasets, particularly over the subtropical oceans, the daytime deserts, and over snow-covered surfaces at the high latitudes. The monthly global bias between the two datasets (ERBE minus ...

Seven January (1984 to 1990) months of three hourly monthly mean total cloud amount data were subjected to Empirical Orthogonal Function (EOF) analysis to study large scale features of the diurnal variation. The first two EOF modes explain two different types of diurnal variation. While the first EOF mode shows the diurnal variation contrast between land and ocean, the second EOF pattern shows diurnal variation over deep convective cloudy regions. In the second mode, maximum cloudiness occurs at around 2000 LST both over continental and oceanic regions, where deep convective cloudiness occurs. The first two EOF modes explain 78.4% of the total normalized variance. The time coefficients of these two EOF modes indicate that the diurnal variation of cloudiness undergoes non sinusoidal variation.

Simultaneous observations by the Earth Radiation Budget Experiment (ERBE) scanning radiometer and the High-Resolution Infrared Sounder (HIRS) on board the NOAA-9 spacecraft have been used to validate a multispectral technique for estimating the outgoing longwave radiation (OLR) from the earth-atmosphere system. Results from approximately 100 000 collocated observations show that the HIRS technique provides instantaneous OLR estimates that agree with the ERBE observations just as well as different ERBE scanners agree with each other--about 5 W m(exp -2) rms. Although there are differences between the HIRS and ERBE estimates that depend upon the scene type and time of day, the HIRS technique explained more than 99% of the variance of the ERBE observations for both day and night observations. The results suggest that the HIRS OLR technique is a suitable replacement for the Advanced Very High Resolution Radiometer technique now used by the National Oceanic and Atmospheric Administration for operational estimates of the OLR.

In 1988, the algorithm for retrieving temperature soundings from radiances measured by NOAA's polar-orbiting satellites was changed from a statistical to a “physical” retrieval system. Because of this change, the National Meteorological Center (NMC) wanted to update the satellite temperature error statistics used in the NMC analyses. The authors, therefore, updated the estimates of observational error variances, horizontal covariances, and vertical correlations for layer mean temperatures retrieved from NOAA-10 satellite radiance data. The temperature error statistics have also been used to estimate analogous error statistics for isobaric height. The computations used radiosonde data as a substitute for true temperatures. Each “matchup” in the dataset consisted of a satellite retrieval close in space and time to a radiosonde sounding. The matchups were stratified into clear, partly cloudy, and cloudy cases, depending on the amount of cloud contamination in the satellite radiance data. In each of ...

The impact of NOAA satellite sounding data on PRC's weather prediction model has been investigated using both 1979 FGGE and December 1987 datasets. Two experiments, NOSAT and SAT were conducted. Seven areas deemed to have adequate conventional data for definition of “truth,” were chosen to compute the verification statistics. The impact of satellite data was then assessed by changes in S1 skill score and root mean square errors for 24 and 48 h forecasts of sea level pressures and 500 mb height. A positive impact on rms errors of up to 11.5% was observed over land for SLP and 8% over ocean for 500 mb height for forecast period of 48 h. Some areas, however, show little or no improvement.

The International Precipitation Working Group (IPWG) was established in 2001 as a scientific-technical group co-sponsored by the Coordination Group for Meteorological Satellites (CGMS) and the World Meteoro- logical Organization (WMO). It is established to foster the development of better measurements, and improvement of their utilization, the improve- ment of scientific understanding, and the development of international partnerships. The IPWG has a worldwide partnership among operational bodies and research institutions, and aims towards a wider and improved use of satellite-derived rainfall products by operational organizations.

[1] The Global Precipitation Climatology Project (GPCP) has produced a combined satellite and in situ global precipitation estimate, beginning 1979. The annual average GPCP estimates are here analyzed over 1979–2004 to evaluate the large-scale variability over the period. Data inhomogeneities are evaluated and found to not be responsible for the major variations, including systematic changes over the period. Most variations are associated with El Nino/Southern Oscillation (ENSO) episodes. There are also tropical trend-like changes over the period, correlated with interdecadal warming of the tropical SSTs and uncorrelated with ENSO. Trends have spatial variations with both positive and negative values, with a global-average near zero.

The impact of NOAA satellite sounding data on the numerical analysis and forecast system of the People's Republic of China has been investigated. Four experiments were conducted. They are: (1) NOSAT; which uses conventional data only and provides benchmark statistics for the performance of the forecast model, (2) SAT; which includes satellite and conventional data (3) ALLSAT; which uses satellite data only, except for conventional surface data required to define the 1000 mb height reference level, and (4) DATGUESS; which uses the ALLSAT analysis as the first guess to which conventional dat are then added. Seven areas deemed to have adequate conventional data for definition of truth. The impact of satellite data was then assessed by computing systematic errors, changes in S1 skill score and root mean square errors for 24 and 48 h forecasts of Sea Level Pressure (SLP) and 500 mb height. Overall, the Chinese model is found to underforecast the strength of features in the mean SLP fields, i.e., pressures are too low near high pressure systems and too high near low pressure systems. The same type of pattern is also seen in the mean 500 mb height forecast. In general, satellite data have been shown to reduce systematic error near where the data have been introduced in the vicinity of low pressure systems. A positive impact on root-mean-square errors of up 10 11.5% was observed over land for SLP and 8% over ocean for 500 mb height for forecast period of 48 h. However, only a meager increase of 5.5% in S1 skill score was observed at SLP for 48 h forecast over oceans.

Hurricane Mitch may prove to be one of the most devastating tropical cyclones to affect the western hemisphere. Heavy rains over Central America from October 28, 1998, to November 1, 1998, caused widespread flooding and mud slides in Nicaragua and Honduras resulting in thousands of deaths and missing persons. News reports indicated entire towns being swept away, destruction of national economies and infrastructure, and widespread disease in the aftermath of the storm, which some estimates suggested dropped as much as 1300 mm of rain. However, in view of the widespread damage it is difficult to determine the actual amounts and distribution of rainfall. More accurate means of determining the rainfall associated with Mitch are vital for diagnosing and understanding the evolution of this disaster and for developing new mitigation strategies for future tropical cyclones. Satellite data may prove to be a reliable resource for accurate rainfall analysis and have yielded apparently reliable figures for Hurricane Mitch.

We studied the effect of clouds on the Earth's radiation budget at the top of the atmosphere. Both the northern hemisphere summer and winter are considered in terms of cloud-radiative forcing, which describes the total effect of clouds on the Earth's radiation budget components. The cloud forcing is obtained by using statistically generated models correlating simultaneous observations of cloud properties and radiation budget parameters obtained from observations from Nimbus 7 satellite observations. The models estimate the broadband albedo and longwave flux throughout the range of variation, including periods of extensive to near-total cloud cover where more simplistic representations fail. As such, the models are used to estimate period-averaged clear-sky radiation budget components. Knowledge of the cloudy-sky and clear-sky radiation budget components permits the computation of cloud-radiative forcing. We show that the net effect of clouds is to cool the Earth. On the average, for an Earth observed to be 52.1% cloud covered, the net cloud forcing is −26.8 Wm−2. This net cooling is obtained from a longwave warming of 24.1 Wm−2 and a shortwave cooling of −50.9 Wm−2. Over much of the Earth there is a general compensation between the warming and cooling effects of clouds. However, over the middle- and high-latitude oceans the albedo effect of clouds is dominant. This is particularly true in each summer hemisphere, where the effects of persistent cloudiness, low oceanic albedos, and high solar insolation combine to drive the net cloud forcing strongly negative. The net effect of cloud forcing cools the Earth, primarily due to the effect of clouds in the summer hemisphere oceans.

Clear-sky planetary albedos are derived from NOAA-9 AVHRR data during 1986 over the U.S. Great Plains with several distinct surface types (shrubland, grassland, deciduous and coniferous forests). The cloud-free observations are selected using a combination of absolute threshold and spatial coherence cloud-screening procedures. The broadband albedo is approximated from the narrow-band visible and near-infrared albedos. Bi-directional reflectivity models are applied to account for the effect of Sun-target-sensor geometry. The corrected albedos are converted to daily means using a directional model to account for the dependence upon sun angle. The results indicate a significant reduction in variability of the observed albedos. The efficiency of the model application is demonstrated on two examples: 1) using time series of cloud-free observations over one target and 2) using one daily image of mapped data in July, 1986.

Observations made with the current and proposed narrowband shortwave channels aboard the NOAA series of satellites were simulated for a number of different surfaces (ocean, vegetative land, desert, cloud and snow) using the ATRAD radiation model to study the relative merit of each channel and, in various combinations to predict the broadband albedo. Solar zenith angles were varied over the range from 0 to 60 degrees. The results indicated that for all of the surfaces considered there would be no significant difference in predicting the broadband albedo with either the current (0.58–0.68 μn) or proposed (0.58–0.68 μm) channel 1 of the AVHRR. The proposed narrower channel 2(0.84–0.87 μm), however, would be a better predictor than the current wider channel 2(0.725–1.0 μm). Channel 1 is better than channel 2 for surfaces of low or moderate reflectivity, while over snow, the error in using channel 2 would be less than half of that for channel 1. Combining channels 1 and 2 would reduce the error by abo...

The wavenumber-frequency spectra of satellite-observed brightness have been examined for the period 1 February 1967 through 29 February 1968 for the latitude belt 20N to 20S. It was found that the quasi-stationary modes and low wavenumbers contain most of the power. The propagating wave activity was located primarily in the 5–15N latitude zone. Perturbations with periods of 12.5 days and wavenumber 5 and about 6 days and wavenumber 9 were prominent. These are consistent with Rossby waves and easterly waves. Since the propagating brightness spectra are due to propagating clouds, the results indicate a traveling heat source as being important in the generation and maintenance of those waves. There was no indication in the brightness spectra of periods and wavelengths consistent with Kelvin waves. However, a tropospheric heat source is not ruled out for those waves.

The wavenumber–frequency spectra of the 200 mb wind field from 28.7°N to 28.7°S were examined for the 128–day period from mid-May to mid-September of 1970 and 1971. Evidence was presented that supported the existence of Rossby and mixed Rossby–gravity waves. Westward–propagating waves, with periods of about 10 days and wavenumber 10, centered at about 24°N were also observed. These waves appear to he associated with the tropical upper troughs. There were indications of equatorward transfers of energy from the mid-latitudes at periods of 9–10 and about 5 days.

Experiments with the numerical models of the Israel Meteorological Service show that the impact of satellite soundings can be substantial but depends on how the soundings are used by the models. The quasi-optimum use of satellite data in defining a first guess for the hemispheric analyses results in average reductions of error of up to 20% for 48-h predictions of sea level pressure and 10% for 500 mb height. The greatest average impact occurs at low levels in the atmosphere over the ocean near where the satellite data are introduced. Impact for individual cases tends to be large and concentrated near important synoptic features such as lows, but small elsewhere.

The technique used by NOAA to estimate the outgoing longwave flux from 10 μm window radiance observations has been reexamined because the data that result from the application of the empirically determined regression equation are systematically lower than those obtained from regression models based on earlier radiative transfer calculations. A new set of radiation calculations was made from a set of 1600 atmospheric soundings and the resulting regression equation gives flux differences from the empirical model that are of the order of ±5 W m−2 over the range of 150 to 300 W m−2, as compared to the +10 W m−2 systematic differences from previous studies. The differences are attributed to the size and representativeness of the sample of soundings used in the radiation calculations. The results also show that although the explained variance of the regression is of the order of 95%, this type of estimation technique may make errors of ±20 W m−2 or larger for a given radiance observation. This will lea...

National Oceanic and Atmospheric Administration (NOAA) satellites have provided over eight years of observations from which estimates of the earth's total longwave emittance can be derived. Changes in satellite instrumentation, orbit, and algorithms used in obtaining these estimates are briefly summarized. The algorithms used by NOAA in obtaining a longwave radiation data set are provided.

The impact of satellite sounding data on the systematic errors of the numerical weather prediction model of the Israel Meteorological Service has been investigated. In general, satellite data have been shown to reduce systematic error, and in particular, the greatest impact is near where the data have been introduced in the vicinity of low pressure systems.

The daily variation of cloudiness, as measured by the Synchronous Meteorological Satellite (SMS-1), was studied for the GATE A/B area (outer hexagon). The amplitude of the diurnal variation was found to be more pronounced on convectively enhanced days than undisturbed days. A primary maximum in both upper and total cloudiness was observed at 1800 GMT (about 1630 local time) and a secondary maximum at 0900 GMT (0730 local time) was observed in the total cloudiness. The existence of a semidiurnal oscillation in cloudiness suggests the influence of the semidiurnal solar atmospheric tide on the cloudiness. The lack of a nighttime maximum in cloudiness implies no nighttime maximum in precipitation, in contrast to other observations of maritime precipitation.

The annual variation of the diurnal cycle of outgoing longwave radiation (OLR) is examined. Our results are based on the climatological amplitude and phase of the first diurnal harmonic for each month. The diurnal harmonic was extracted from a composite daily cycle from several polar orbiting satellites that flew in different years with ten different equator crossing times. We compute a “diurnal vector standard deviation” which is the square root of the sum of the variances of both components of the 12 climatological monthly diurnal vectors. This allows contributions from both phase and amplitude changes of the diurnal vector. A map of the diurnal vector standard deviation is presented. The values over land are an order of magnitude larger than over the ocean. The maxima are located over the seasonally migrating monsoons and over the midlatitude semi-arid zones. In midlatitudes the large standard deviation results from an increased daily cycle of insolation during summer and from clouds associate...

The global and monthly distribution of the diurnal variation of outgoing longwave radiation (OLR) has been calculated by compositing estimates of the planetary OLR obtained from polar orbiting satellites at different equator crossing times. These data include NOAA and NASA polar orbiting satellites for the year 1974 through 1983, giving a total of ten different local observations per day throughout the whole data period. A Fourier analysis was then applied to calculate the phase and amplitude of the diurnal cycle on a 2.5° latitude/longitude grid for each month of the year. Assumption was implicitly made that the first harmonic alone explains most of the diurnal variation. The results are represented on maps extending from 55° south to 55° north for four different seasons from which a large seasonal variability of the diurnal harmonic primarily experienced by the mid-latitude continents was clearly depicted. Over land areas the amplitude of the diurnal variation was large. In desert and semi-arid areas it seem to be clearly related to surface solar heating i.e. phases of maximum OLR generally occurring near noon during summer and afternoon during winter months. Over the oceans, the amplitude is generally small even in the convectively active regions, such as the ITCZ, and the diurnal cycle appears to be modulated primarily by clouds. Finally, a ‘harmonic dial’ was constructed to examine the most dramatic features of the diurnal variation representative of such areas as the ITCZ, deserts, tropical convective clouds regions and highly variable mid-latitude areas. Results of this study are consistent with other studies of the diurnal variability of clouds and radiation budget parameters.

A brief description of an earth radiation budget data set, as determined from NOAA operational spacecraft, is presented. The data are continuous from June 1974 through February 1978. Some samples of the mapped outputs are shown, and information on the availability of these data is provided.

Studies of diurnal variation in the planetary radiation budget parameters from space are possible only with observations from geosynchronous satellites. Such studies are necessary to establish possible bias in the radiation budget estimates derived currently from polar orbiting satellites. This paper outlines a preliminary approach to estimate the diurnal variation of the net radiation at the top of the atmosphere, using the Geostationary Operational Environmental Satellite (GOES) visible (0.55–0.75 μm) and IR window (10.5–12.5 μm) observations. Model development and analysis used GOES-E data for the summer of 1982. This paper is the first to report monthly averaged diurnal variations in the planetary radiation budget parameters for several months. The possible error in the daily mean net radiation when derived from one observation per day instead of hourly observations, was also estimated. Computational experiments were conducted with different calibration techniques to assess the possible bias error in the quantities derived due to calibration.

The observational error of satellite temperature retrievals and their horizontal error structure were calculated for April 1980 for TIROS N and NOAA 6 for clear and cloudy retrievals. The results suggest different horizontal error structures for clear and cloudy retrievals and perhaps stratification by atmospheric layer.

The planetary outgoing longwave radiation has been estimated since 1974 from two different series of NOAA operational polar spacecraft. The first series provided data from June 1974 through February 1978 and was designated “SR” for the scaning radiometers used at that time. This data set has been used in a variety of radiation budget and climate studies, such as that by Ohring and Gruber, 1983. The second satellite system is the currently operational TIROS-N series of satellites. Data from this series began in January 1979 and are continuing. In both systems, estimates of the outgoing longwave radiation are obtained from narrow spectral interval (10–12 μm) window radiances. A comparison is made of the estimates from the two different series of satellites in order to arrive at an assessment of their compatibility. This is important since the SR observations were taken at approximately 0900 and 2100 local times, while the TIROS-N data alternate between 0730-1930 and 0300-1500 local times. In addition, there is a period of overlap between the TIROS-N data and the broad band (5–50 μm) Nimbus 7 EArth radiation budget data. A comparison of those two data sets indiciate excellent agreement generally within about 1–2 Wm−2 on the monthly means on global and hemispherical scales. Comparisons of zonal averages indicate maximum differences as large as 9 Wm−2. Evidence is presented to suggest that observations taken at different local observing times may be biased by the diurnal variation of emitted flux, even on global scales.

A new technique for estimating outgoing longwave radiation from observations on the NOAA operational satellites has been developed from a regression analysis of radiation model calculations. The technique consists of a weighted sum of radiance in but four intervals sensed by the High-resolution InfraRed Sounder (HIRS). The analysis shows that model outgoing flux may be reproduced to within ±2 W · m−2 rms, which is about a factor of 4 smaller than the rms error of the method used by NOAA to estimate flux from the AVHRR. The small errors suggest that the new technique holds the promise of eliminating the large systematic errors possible with the current NOAA technique. Additionally, the new technique often the possibility of directly relating flux changes to changes in atmospheric parameters.

The scanning microwave spectrometer (SCAMS) aboard Nimbus-6 contains a 22.23 GHz water vapor channel and 31.65 GHz window channel for deriving integrated water vapor (precipitable water) and cloud liquid water through a column over the oceans. The SCAMS derived parameters are based on a nonlinear relationship between the two channel measurements, and is shown to be more accurate than a linear model, particularly for the large values of precipitable water found in the tropics. Comparisons are made between the SCAMS derived precipitable water and 163 radiosonde measurements collected from 19 island stations over the tropical Pacific for the period between 18 August and 4 September 1975. The SCAMS values of precipitable water are shown to display the same variability as the radiosonde data, with a 0.5 cm rms difference. Fields of both precipitable water and liquid water derived by the SCAMS were averaged for the 2-week period for the ocean area between 130°E–100°W and 35°N–35°S. The Intertropical Co...

A statistical evaluation of satellite soundings from TIROS-N and NOAA-6 is presented. Collocated satellite-radiosonde data were collected by season from July 1979 through May 1980 for clear and cloudy retrievals. In addition to RMS and mean error statistics, vertical correlations, ratio of satellite variance to radiosonde variance, and land minus sea differences for 30–60°N, 30–60°S and 30°N–30°S were examined. The results indicate that the mean and RMS differences are larger for cloudy retrieval paths than for clear retrieval paths. The largest RMS errors occur in the 1000–850 mb layer and in the tropopause region. Vertical correlations are highest between adjacent layers. The ratio of satellite variance to radiosonde variance is considerably higher than reported in Phillips et at. (1979), with clear retrievals exhibiting a higher ratio than cloudy retrievals. Land minus sea differences suggest that there is a continental influence in the coefficient data base used to generate cloudy retrievals.

An objective technique for adjusting wind data, such that the total mass divergence in a volume of the atmosphere is zero, is developed. The adjustment is obtained by applying a least-squares smoothing with a Lagrangian multiplier to constrain the total mass divergence to a specified amount. The computational details are derived and the method is applied to several examples. Both for theoretical wind profiles and for actual data, a very satisfactory adjustment is achieved without destroying the physical information contained in the data.

An attempt to estimate rainfall in convectively active regions using Kuo's parameterization scheme has been made. The precipitation in this model is given by P = lQ1/Δt, where P is the precipitation per unit time, l the fraction of a synoptic area covered by deep active convection, Q1 the mount of condensation heating according to moist adiabatic ascent, and Δt a time parameter related to the precipitating lifetime of the convective elements. Investigation of the above equation when P, l and Q1 were available indicated that an appropriate time parameter was 30 min and that the main contribution to the precipitation comes from the l parameter. A case is presented where l is obtained from satellite observations. The resulting precipitation estimate appears quite reasonable. The potential for estimating precipitation over the tropical means is pointed out.

Resultant winds over the Pacific are derived from an Advanced Technology Satellite (ATS 1) for the month of November 1969. Since the method uses clouds as tracers, these resultant winds are biased toward cloud-producing circulation features. These biases appear to be smallest in the Tropics and, consequently, the winds here can be very useful for studies of the average circulation at low latitudes. Some of the important features of this circulation over the equatorial Pacific are clearly revealed.