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R. Uijlenhoet
,
J.-M. Cohard
, and
M. Gosset

Abstract

The potential of a near-infrared large-aperture boundary layer scintillometer as path-average rain gauge is investigated. The instrument was installed over a 2.4-km path in Benin as part of the African Monsoon Multidisciplinary Analysis (AMMA) Enhanced Observation Period during 2006 and 2007. Measurements of the one-minute-average received signal intensity were collected for 6 rainfall events during the dry season and 16 events during the rainy season. Using estimates of the signal base level just before the onset of the rainfall events, the optical extinction coefficient is estimated from the path-integrated attenuation for each minute. The corresponding path-average rain rates are computed using a power-law relation between the optical extinction coefficient and rain rate obtained from measurements of raindrop size distributions with an optical spectropluviometer and a scaling-law formalism for describing raindrop size distribution variations. Comparisons of five-minute rainfall estimates with measurements from two nearby rain gauges show that the temporal dynamics are generally captured well by the scintillometer. However, the instrument has a tendency to underestimate rain rates and event total rain amounts with respect to the gauges. It is shown that this underestimation can be explained partly by systematic differences between the actual and the employed mean power-law relation between rain rate and specific attenuation, partly by unresolved spatial and temporal rainfall variations along the scintillometer path. Occasionally, the signal may even be lost completely. It is demonstrated that if these effects are properly accounted for by employing appropriate relations between rain rate and specific attenuation and by adapting the pathlength to the local rainfall climatology, scintillometer-based rainfall estimates can be within 20% of those estimated using rain gauges. These results demonstrate the potential of large-aperture scintillometers to estimate path-average rain rates at hydrologically relevant scales.

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M. Alcoba
,
M. Gosset
,
M. Kacou
,
F. Cazenave
, and
E. Fontaine

Abstract

A simple scheme that is based on the shape and intensity of the radar bright band is used to infer the density of hydrometeors just above the freezing level in Sahelian mesoscale convective systems (MCS). Four MCS jointly observed by a ground-based X-band radar and by an instrumented aircraft as part of the Megha-Tropiques algorithm-validation campaign during August 2010 in Niamey, Niger, are analyzed. The instrumented aircraft (with a 94-GHz radar and various optical probes on board) provided mass–diameter laws for the particles sampled during the flights. The mass–diameter laws derived from the ground-radar vertical profile of reflectivity (VPR) for each flight are compared with those derived from the airborne measurements. The density laws derived by both methods are consistent and encourage further use of the simple VPR scheme to quantify hydrometeor density laws and their variability for various analyses (microphysical processes and icy-hydrometeor scattering and radiative properties).

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E-P. Zahiri
,
M. Gosset
,
J-P. Lafore
, and
V. Gouget

Abstract

A full radar simulator, which works with the 3D output fields from a numerical mesoscale model, has been developed. This simulator uses a T-matrix code to calculate synthetic radar measurements, accounts for both backscattering and propagation effects, and includes polarimetric variables. The tool is modular to allow several options in the derivation of the synthetic radar variables. A measurement uncertainty can be taken into account on both the simulated reflectivities and the differential phase shift. A scheme can also be switched on to allow for the gate-to-gate variability of the rain drops size distribution or, also, their oblateness. This work was done in the framework of the installation in West Africa of a polarimetric X-band radar for the observation of tropical rain. Accordingly, the first objective pursued with this simulation setup is a detailed analysis of X-band polarimetric rain retrieval algorithms. Two retrieval schemes, a simple RK DP formula and a profiler that uses both reflectivity and ϕ DP, are tested. For that purpose the simulator is run on a model case study of an African squall line, then the two schemes are used to retrieve the rain rates from the synthetic radar variables and compare them to the original. The scores of the schemes are discussed and compared. The authors analyze the sensitivity of the results to the measurement uncertainty and also to several aspects of drop size distribution and drop shape variability.

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F. Cazenave
,
M. Gosset
,
M. Kacou
,
M. Alcoba
,
E. Fontaine
,
C. Duroure
, and
B. Dolan

Abstract

The particle identification scheme developed by Dolan and Rutledge for X-band polarimetric radar is tested for the first time in Africa and compared with in situ measurements. The data were acquired during the Megha-Tropiques mission algorithm-validation campaign that occurred in Niger in 2010. The radar classification is compared with the in situ observations gathered by an instrumented aircraft for the 13 August 2010 squall-line case. An original approach has been developed for the radar–in situ comparison: it consists of simulating synthetic radar variables from the microphysical-probe information and comparing the two datasets in a common “radar space.” The consistency between the two types of observation is good considering the differences in sampling illustrated in the paper. The time evolution of the hydrometeor types and their relative proportion in the convective and stratiform regions are analyzed. The farther away from the convection one looks, the more aggregation dominates, riming diminishes, and hydrometeors are less dense. Particle identification based on the polarimetric radar will be applied to a 5-yr African dataset in the future.

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T. Vischel
,
G. Quantin
,
T. Lebel
,
J. Viarre
,
M. Gosset
,
F. Cazenave
, and
G. Panthou

Abstract

High-resolution rain fields are a prerequisite to many hydrometeorological studies. For some applications, the required resolution may be as fine as 1 km in space and 5 min in time. At these scales, rainfall is strongly intermittent, variable in space, and correlated in time because of the propagation of the rainy systems. This paper compares two interpolation approaches to generate high-resolution rain fields from rain gauge measurements: (i) a classic interpolation technique that consists in interpolating independently the rain intensities at each time step (Eulerian kriging) and (ii) a simple dynamic interpolation technique that incorporates the propagation of the rainy systems (Lagrangian kriging). For this latter approach, three propagation models are tested. The different interpolation techniques are evaluated over three climatically contrasted areas in West Africa where a multiyear 5-min rainfall dataset has been collected during the African Monsoon Multidisciplinary Analyses (AMMA) campaigns. The dynamic interpolation technique is shown to perform better than the classic approach for a majority of the rainy events. The performances of the three propagation models differ from one another, depending on the evaluation criteria used. One of them provides a satisfactory time of arrival of rainfall but slightly smooths the rain intensities. The two others reproduce well the rain intensities, but the time of arrival of the rain is sometimes delayed. The choice of an appropriate propagation algorithm will thus depend on the operational objectives underlying the rain field generation.

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Clement Guilloteau
,
Marielle Gosset
,
Cecile Vignolles
,
Matias Alcoba
,
Yves M. Tourre
, and
Jean-Pierre Lacaux

Abstract

Spatiotemporal rainfall variability is a key parameter controlling the dynamics of mosquitoes/vector-borne diseases such as malaria, Rift Valley fever (RVF), or dengue. Impacts from rainfall heterogeneity at small scales (i.e., 1–10 km) on the risk of epidemics (i.e., host bite rate or number of bites per host and per night) must be thoroughly evaluated. A model with hydrological and entomological components for risk prediction of the RVF zoonosis is proposed. The model predicts the production of two mosquito species within a 45 km × 45 km area in the Ferlo region, Senegal. The three necessary steps include 1) best rainfall estimation on a small scale, 2) adequate forcing of a simple hydrological model leading to pond dynamics (ponds are the primary larvae breeding grounds), and 3) best estimate of mosquito life cycles obtained from the coupled entomological model. The sensitivity of the model to the spatiotemporal heterogeneity of rainfall is first tested using high-resolution rain fields from a weather radar. The need for high-resolution rain data is thus demonstrated. Several high-resolution satellite rainfall products are evaluated in the region of interest using a dense rain gauge network. Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis 3B42, version 6 (TMPA-3B42V6), and 3B42 in real time (TMPA-3B42RT); Global Satellite Mapping of Precipitation (GSMaP) in near–real time (GSMaP-NRT) and Moving Vector with Kalman version (GSMaP-MVK); African Rainfall Estimation Algorithm, version 2.0 (RFE 2.0); Climate Prediction Center (CPC) morphing technique (CMORPH); and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN) are tested and finally corrected using a probability matching method. The corrected products are then used as forcing to the coupled model over the 2003–10 period. The predicted number and size of ponds and their dynamics are greatly improved compared to the model forced only by a single gauge. A more realistic spatiotemporal distribution of the host bite rate of the RVF vectors is thus expected.

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P. R. A. Brown
,
A. J. Illingworth
,
A. J. Heymsfield
,
G. M. McFarquhar
,
K. A. Browning
, and
M. Gosset

Abstract

The purpose of this paper is to assess the potential of a spaceborne 94-GHz radar for providing useful measurements of the vertical distribution and water content of ice clouds on a global scale.

Calculations of longwave (LW) fluxes for a number of model ice clouds are performed. These are used to determine the minimum cloud optical depth that will cause changes in the outgoing longwave radiation or flux divergence within a cloud layer greatear than 10 W m−2, and in surface downward LW flux greater than 5 W m−2, compared to the clear-sky value. These optical depth values are used as the definition of a “radiatively significant” cloud. Different “thresholds of radiative significance” are calculated for each of the three radiation parameters and also for tropical and midlatitude cirrus clouds. Extensive observational datasets of ice crystal size spectra from midlatitude and tropical cirrus are then used to assess the capability of a radar to meet these measurement requirements. A radar with a threshold of −30 dBZ should detect 99% (92%) of “radiatively significant” clouds in the midlatitudes (Tropics). This detection efficiency may be reduced significantly for tropical clouds at very low temperatures (−80°C).

The LW flux calculations are also used to establish the required accuracy within which the optical depth should be known in order to estimate LW fluxes or flux divergence to within specified limits of accuracy. Accuracy requirements are also expressed in terms of ice water content (IWC) because of the need to validate cloud parameterization schemes in general circulation models (GCMs). Estimates of IWC derived using radar alone and also using additional information to define the mean crystal size are considered. With crystal size information available, the IWC for samples with a horizontal scale of 1–2 km may be obtained with a bias of less than 8%. For IWC larger than 0.01 g m−3, the random error is in the range +50% to −35%, whereas for a value of 0.001 g m−3 the random error increases to between +80% and −45%. This level of accuracy also represents the best that may be achieved for estimates of the cloud optical depth and meets the requirements derived from LW flux calculations. In the absence of independent particle size information, the random error is within the range +85% to −55% for IWC greater than 0.01 g m−3. For the same IWC range, the estimated bias is few than ±15%. This accuracy is sufficient to provide useful constraints on GCM cloud parameteriation schemes.

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E. Drigeard
,
E. Fontaine
,
W. Wobrock
,
A. Schwarzenböck
,
C. Duroure
,
E. R. Williams
,
B. Russell
,
A. Protat
,
J. Delanoë
,
F. Cazenave
, and
M. Gosset

Abstract

This study addresses clouds with significant ice water content (IWC) in the stratiform regions downwind of the convective cores of African squall lines in the framework of the French–Indian satellite Megha-Tropiques project, observed in August 2010 next to Niamey (13.5°N, 2°E) in the southwestern part of Niger. The objectives included comparing the IWC–Z reflectivity relationship for precipitation radars in deep stratiform anvils, collocating reflectivity observed from ground radar with the calculated reflectivity from in situ microphysics for all aircraft locations inside the radar range, and interpreting the role of large ice crystals in the reflectivity of centimeter radars through analysis of their microphysical characteristics as ice crystals larger than 5 mm frequently occurred. It was found that, in the range of 20–30 dBZ, IWC and C-band reflectivity are not really correlated. Cloud regions with high IWC caused by important crystal number concentrations can lead to the same reflectivity factor as cloud regions with low IWC formed by a few millimeter-sized ice crystals.

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