The Tropical Rainfall Measuring Mission (TRMM) satellite measurements from the precipitation radar and TRMM microwave imager have been combined to yield a comprehensive 3-yr database of precipitation features (PFs) throughout the global Tropics (±36° latitude). The PFs retrieved using this algorithm (which number nearly six million Tropicswide) have been sorted by size and intensity ranging from small shallow features greater than 75 km2 in area to large mesoscale convective systems (MCSs) according to their radar and ice scattering characteristics. This study presents a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective–stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space. The observations are sorted regionally to examine the stark differences in the diurnal cycle of rainfall and convective intensity over land and ocean areas. Over the oceans, the diurnal cycle of rainfall has small amplitude, with the maximum contribution to rainfall coming from MCSs in the early morning. This increased contribution is due to an increased number of MCSs in the nighttime hours, not increasing MCS areas or conditional rain rates, in agreement with previous works. Rainfall from sub-MCS features over the ocean has little appreciable diurnal cycle of rainfall or convective intensity. Land areas have a much larger rainfall cycle than over the ocean, with a marked minimum in the midmorning hours and a maximum in the afternoon, slowly decreasing through midnight. Non-MCS features have a significant peak in afternoon instantaneous conditional rain rates (the mean rain rate in raining pixels), and convective intensities, which differs from previous studies using rain rates derived from hourly rain gauges. This is attributed to enhancement by afternoon heating. MCSs over land have a convective intensity peak in the late afternoon, however all land regions have MCS rainfall peaks that occur in the late evening through midnight due to their longer life cycle. The diurnal cycle of overland MCS rainfall and convective intensity varies significantly among land regions, attributed to MCS sensitivity to the varying environmental conditions in which they occur.
Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), TRMM Microwave Imager (TMI), and Visible and Infrared Scanner (VIRS) observations within the Precipitation Feature (PF) database have been analyzed to examine regional variability in rain area and maximum horizontal extent of rainfall features, and role of storm morphology on rainfall production (and thus modes where vertically integrated heating occurs). Particular attention is focused on the sampling geometry of the PR and the resulting impact on PF statistics across the global Tropics. It was found that 9% of rain features extend to the edge of the PR swath, with edge features contributing 42% of total rainfall. However, the area (maximum dimension) distribution of PR features is similar to the wider-swath TMI up until a truncation point of nearly 30 000 km2 (250 km), so a large portion of the feature size spectrum may be examined using the PR as with past ground-based studies. This study finds distinct differences in land and ocean storm morphology characteristics, which lead to important differences in rainfall modes regionally. A larger fraction of rainfall comes from more horizontally and vertically developed PFs over land than ocean due to the lack of shallow precipitation in both relative and absolute frequency of occurrence, with a trimodal distribution of rainfall contribution versus feature height observed over the ocean. Mesoscale convective systems (MCSs) are found to be responsible for up to 90% of rainfall in selected land regions. Tropicswide, MCSs are responsible for more than 50% of rainfall in almost all regions with average annual rainfall exceeding 3 mm day−1. Characteristic variability in the contribution of rainfall by feature type is shown over land and ocean, which suggests new approaches for improved convective parameterizations.
1 October 2008 in Journal of Applied Meteorology and Climatology
An event-based method of analyzing the measurements from multiple satellite sensors is presented by using observations of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR), Microwave Imager (TMI), Visible and Infrared Scanner (VIRS), and Lightning Imaging System (LIS). First, the observations from PR, VIRS, TMI, and LIS are temporally and spatially collocated. Then the cloud and precipitation features are defined by grouping contiguous pixels using various criteria, including surface rain, cold infrared, or microwave brightness temperature. The characteristics of measurements from different sensors inside these features are summarized. Then, climatological descriptions of many properties of the identified features are generated. This analysis method condenses the original information of pixel-level measurements into the properties of events, which can greatly increase the efficiency of searching and sorting the observed historical events. Using the TRMM cloud and precipitation feature database, the regional variations of rainfall contribution by features with different size, intensity, and PR reflectivity vertical structure are shown. Above the freezing level, land storms tend to have larger 20-dBZ area and reach higher altitude than is the case for oceanic storms, especially those land storms over central Africa. Horizontal size and the maximum reflectivity of oceanic storms decrease with altitude. For land storms, these intensity measures increase with altitude between 2 km and the freezing level and decrease more slowly with altitude above the freezing level than for ocean storms.
An algorithm has been developed to identify precipitation features (≥75 km2 in size) in two land and two ocean regions during August, September, and October 1998. It uses data from two instruments on the Tropical Rainfall Measuring Mission (TRMM) satellite: near-surface precipitation radar (PR) reflectivities, and TRMM Microwave Imager (TMI) 85.5-GHz polarization corrected temperatures (PCTs). These features were classified by size and intensity criteria to identify mesoscale convective systems (MCSs), precipitation with PCTs below 250 K, and other features without PCTs below 250 K. By using this technique, several hypotheses about the convective intensity and rainfall distributions of tropical precipitation systems can be evaluated. It was shown that features over land were much more intense than similar oceanic features as measured by their minimum PCTs, maximum heights of the 30-dBZ contour, and 6-km reflectivities. The diurnal cycle of precipitation features showed a strong afternoon maximum ... Abstract An algorithm has been developed to identify precipitation features (≥75 km2 in size) in two land and two ocean regions during August, September, and October 1998. It uses data from two instruments on the Tropical Rainfall Measuring Mission (TRMM) satellite: near-surface precipitation radar (PR) reflectivities, and TRMM Microwave Imager (TMI) 85.5-GHz polarization corrected temperatures (PCTs). These features were classified by size and intensity criteria to identify mesoscale convective systems (MCSs), precipitation with PCTs below 250 K, and other features without PCTs below 250 K. By using this technique, several hypotheses about the convective intensity and rainfall distributions of tropical precipitation systems can be evaluated. It was shown that features over land were much more intense than similar oceanic features as measured by their minimum PCTs, maximum heights of the 30-dBZ contour, and 6-km reflectivities. The diurnal cycle of precipitation features showed a strong afternoon maximum ...
1 March 2004 in Natural Hazards and Earth System Sciences
The linkages between the space-time variability of observed clouds, rainfall, large-circulation patterns and topography in northern India and the Himalayas were investigated using remote sensing data. The research purpose was to test the hypothesis that cloudiness patterns are dynamic tracers of rainstorms, and therefore their temporal and spatial evolution can be used as a proxy of the spatial and temporal organization of precipitation and precipitation processes in the Himalayan range during the monsoon. The results suggest that the space-time distribution of precipitation, the spatial variability of the diurnal cycle of convective activity, and the terrain (landform and altitudinal gradients) are intertwined at spatial scales ranging from the order of a few kms (1–5km) up to the continental-scale. Furthermore, this relationship is equally strong in the time domain with respect to the onset and intra-seasonal variability of the monsoon. Infrared and microwave imagery of cloud fields were analyzed to characterize the spatial and temporal evolution of mesoscale convective weather systems and short-lived convection in Northern India, the Himalayan range, and in the Tibetan Plateau during three monsoon seasons (1999, 2000 and 2001). The life cycle of convective systems suggests landform and orographic controls consistent with a convergence zone constrained to the valley of the Ganges and the Himalayan range, bounded in the west by the Aravalli range and the Garhwal mountains and in the East by the Khasi Hills and the Bay of Bengal, which we call the Northern India Convergence Zone (NICZ). The NICZ exhibits strong night-time activity along the south-facing slopes of the Himalayan range, which is characterized by the development of short-lived convection (1–3h) aligned with protruding ridges between 1:00 and 3:00 AM. The intra-annual and inter-annual variability of convective activity in the NICZ were assessed with respect to large-scale synoptic conditions, monsoon activity in the Bay of Bengal, and the modulating role of orography. Empirical orthogonal function (EOF) and canonical correlation (CC) analysis suggest that joint modes of variability of monsoon weather and topography, which we call orographic land-atmosphere interactions, modulate the space-time variability of cloudiness in the region. Finally, scaling analysis of cloudiness suggests three different scaling regimes of orographic land-atmosphere interactions: 1) a synoptic-scale regime (≥70-80km); 2) an orographic meso–β regime (30–70km) associated with the succession of wide valleys and bulky terrain features; and 3) an orographic meso–α regime (≤30km) associated with the complex succession of protruding south-facing ridges and narrow valleys that characterize the Himalayan foothills between altitudes of 3000 and 5000m elevations.