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Mamoudou B. Ba and Arnold Gruber

Abstract

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 cloud group referenced by its cloud-top temperature is obtained by the product of probability of rain (P b) and mean rain rate (RRmean) and is adjusted by a moisture factor that is designed to modulate the evaporation effects on rain below cloud base for different moisture environments. The calibration of the algorithm for constants P b and RRmean is obtained using collocated instantaneous satellite and radar data and hourly gauge-adjusted radar products collected during 17 days in June and July 1998. A comparison of the combined visible and a temperature threshold of 230 K (e.g., previous infrared/visible algorithms) with the combined visible and a threshold of 15 μm demonstrates that the latter improves the detection of rain from warm clouds without lowering the skill of the algorithm. The quantitative validation shows that the algorithm performs well at daily and monthly scales. At monthly scales, a comparison with GOES Precipitation Index (GPI) shows that GOES Multispectral Rainfall Algorithm's performance against gauges is much better for September and October 1999.

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Mamoudou B. Ba and Sharon E. Nicholson

Abstract

The convective activity over the Rift Valley lakes of East Africa, as deduced from cloud tops colder than a predefined threshold, is examined. Relationships between satellite-derived convective indices and rainfall measurements are also examined. The diurnal cycle of convective activity over Lake Victoria and over the land is analyzed. The maximum convection is found to occur during the morning between 0500 and 0800 LST over Lake Victoria, and a second maximum occurs in the afternoon. In contrast, over surrounding land, the maximum occurs generally in late afternoon and during the evening. It is also found that a linear relationship exists between satellite-derived convective indices and rainfall measurements; the correlation between the two is strong enough that the indices can be used to estimate annual and areally averaged monthly rainfall. The cold cloud indices explain more than 50% of observed variances of rainfall for the months of May through October. However, the performance is inadequate in several instances during February and March. The results show that the satellite algorithm is robust enough to estimate spatial averages of monthly rainfall with satellite estimates accounting for between 75% and 95% of observed variances of rainfall. The results further show that there is an exceedingly high correlation between convective rainfall over Lake Victoria and in the surrounding catchment. This permitted the derivation of a relationship between rainfall over the lake and its catchment.

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Robert G. Ellingson and Mamoudou B. Ba

Abstract

A multispectral outgoing longwave radiation (OLR) estimation technique is applied to GOES Sounder data to study the diurnal cycle of OLR. OLR data collected from several regional areas over the continental United States and adjacent oceans during July 1998 are analyzed to determine diurnal variations for clear-sky and all-sky conditions. It is found that the desert regions exhibit a diurnal range that can reach up to about 70 W m−2 while the vegetated areas and ocean regions exhibit much lower diurnal range. The results for this one month show that the form of the monthly diurnal variation of the different regions can be approximated with a sine-like function, with the desert sites exhibiting a more nearly perfect sine curve. It is also found that the rms errors associated with sparse data such as those of polar orbiting satellites depend on sampling time and interval. The high temporal and spatial characteristics of OLR data from geostationary satellites offer a unique opportunity to obtain increased understanding of the diurnal cycles of atmospheric processes.

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Mamoudou B. Ba, Sharon E. Nicholson, and Robert Frouin

Abstract

The temporal and spatial variabilities of the surface radiation budget over the African continent are examined using Meteosat data acquired during 1983–88. Continental maps of land surface albedo, downward solar irradiance, and net radiation are presented for the midseasonal months of January, April, July, and October. Surface albedo is further compared with Special Sensor Microwave Imager polarization difference of brightness temperature at 19 GHz and with the normalized difference vegetation index to assess the results and to test proposed explanations for some of the unanticipated results. An example of the latter is the finding that albedo increases throughout most of the Southern Hemisphere and in the lower latitudes of the Northern Hemisphere during the wet season. Overall, the study demonstrates the complexity of the relationships among surface albedo, vegetation, and soils and underscores a strong interhemispheric contrast in radiation regimes.

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Mamoudou B. Ba, Robert Frouin, and Sharon E. Nicholson

Abstract

Two satellite algorithms for rain estimation are used to study the interannual variability of West African rainfall during contrasting years of the period 1983–88. The first algorithm uses a frequency of occurrence index quantifying the number of times Meteosat thermal infrared radiance below 2.107 W m−2 sr−1 µm−1 (−40°C) occurs during the rainy season. The second algorithm uses the average Meteosat thermal infrared radiance over the period of interest. Appropriate calibrations are performed using these satellite parameters and ground-based rainfall observations. Separate calibration and equations are considered for each of three suggested subrainfall zones in West Africa: two Sahelian zones located just north of 9°N (one cast and one west of 5°W) and the region extending south from 9°N to the coast. Over 80% of the variance in the ground-based rainfall data is explained by both algorithms in regions located north of 9°N, but poor correlations between observed and estimated rainfall exist south of 9°N. The interannual variability of rainfall in the Sahel is well described by that of cold clouds and average radiances. The satellite estimates also reveal substantial longitudinal variability in the anomaly fields, indicating that some Sahelo–Soudanian areas may receive above average rainfall during a year cataloged as dry. The latitudinal displacement and the extent of the cloud band associated with the intertropical convergence zone (ITCZ), as derived from cold cloud indices, indicate a northward displacement of the ITCZ in some, but not all, wet years in the Sahel. No systematic anomalous southward displacement of the ITCZ is evident in dry years. Drought in the Sahel appears to be more closely linked to the latitudinal extent and the intensity of the convection within the ITCZ.

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Mamoudou B. Ba, Robert Frouin, Sharon E. Nicholson, and Gérard Dedieu

Abstract

Downward surface solar irradiance and albedo of the African continent are estimated from Meteosat B2 data at 30-km spatial resolution. The algorithm, based on Dedieu et al.’s approach, is verified against other satellite estimates and ground-based measurements. In the computations, the International Satellite Cloud Climatology Project’s (ISCCP) radiometric calibration is adjusted using the Libyan desert as a reference target of constant reflectance properties. Surface albedo is corrected for sun zenith angle effects, allowing for better detection of seasonal changes due to the vegetation cycle. The estimates obtained with Meteosat B2 data agree generally well with other satellite estimates, although biases of 20 W m−2 (downward surface solar irradiance) and 0.15 (surface albedo) are obtained in some cases. There is evidence, from comparisons with surface measurements, that the clear-sky downward surface solar irradiance is overestimated over semiarid regions of Africa because of uncertainties in aerosol characteristics. In the Sahel region, where spatial albedo gradients are high, it is advantageous to use 30-km Meteosat B2 products instead of the current, coarser 280-km-resolution ISCCP products.

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Mamoudou B. Ba, Robert G. Ellingson, and A. Gruber

Abstract

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 technique explained over 91% and 96% of the variance of CERES observations for both night and day, and for both land and ocean scenes for July 1998 and April 2000, respectively.

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Jeffrey R. McCollum, Arnold Gruber, and Mamoudou B. Ba

Abstract

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.

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Mamoudou Ba, Lingyan Xin, John Crockett, and Stephan B. Smith

Abstract

NCAR’s AutoNowCaster (ANC) was modified to run over a large domain that encompasses the air traffic management hubs of Chicago, Illinois; New York City, New York; and Atlanta, Georgia. ANC produces nowcasts of convective likelihood (CL), with higher values delineating areas where storms are likely to form and be sustained, and vice versa. This paper presents the results of verifying ANC’s 60-min nowcasts of CL over the study area using data collected from 11 June to 30 September 2012. To reduce the high sensitivity of statistical scores to small errors in location and timing, spatial and temporal relaxation techniques were explored. The results show that, at a spatial scale of roughly 50 km and with no temporal relaxation, a CL value of 0.6 is an optimum threshold for nowcasting the general areas both where new storms may initiate and where existing storms will be sustained. Moreover, at that same spatial scale and with temporal relaxation (45–90 min from the nowcast issuance time), a CL value of 0.7 is a good threshold for nowcasting convective initiation alone.

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Jeffrey R. McCollum, Witold F. Krajewski, Ralph R. Ferraro, and Mamoudou B. Ba

Abstract

A bias-adjusted radar rainfall product is created and used for evaluation of two satellite rainfall estimation algorithms. Three years of collocated rainfall estimates from radar, rain gauges, a microwave satellite algorithm, and a multispectral (visible through near-infrared) algorithm were collected over the continental United States from July 1998 through July 2001. The radar and gauge data are compared to determine the locations and times at which the rainfall occurrences estimated by these two sensors are in sufficient agreement for the data to be used for validation. This procedure serves as quality control for both sensors and determines the locations at which the radar has difficulty detecting rainfall and should not be used in a validation dataset. For the data remaining after quality control, the gauge data are used for multiplicative adjustment of the radar estimates to remove the radar bias with respect to the gauges. These bias-adjusted estimates are compared with the satellite rainfall estimates to observe the evolution of the satellite biases over the 3-yr period. The multispectral algorithm was under development throughout the 3-yr period, and improvement is evident. The microwave algorithm overestimates rainfall in the summer months, underestimates in the winter months, and has an east-to-west bias gradient, all of which are consistent with physical explanations and previous findings. The multispectral algorithm bias depends highly on diurnal sampling; there is much greater overestimation for the daytime overpasses. These results are applicable primarily to the eastern half of the United States, because few data in the western half remain after quality control.

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