TRMM-PR Observations Research Articles

A specific stratospheric precursory signal of overshooting convective systems over the southern slope of the Tibetan Plateau

Using the TRMM PR observations, ERA5 reanalysis and Outgoing Longwave Radiation (OLR) datasets, a specific stratospheric precursory signal to the occurrence of overshooting convective systems (OCSs) over the southern slope of the Tibetan Plateau (SSTP) is investigated. We compared two types of OCS events: OCSs associated with stratospheric intrusions and other OCSs. The results indicate that there is a notable decline in the tropopause height starting two days before to on the day of the OCS onset for OCSs associated with stratospheric intrusions, but the tropopause height for other OCSs increases with the occurrence of OCS. It is found that the descending of the tropopause height is accompanied by downward intrusion of stratospheric high potential vorticity (PV) air into the troposphere for the OCSs associated with stratospheric intrusions. The increase in PV near the tropopause can cause an increase in temperature and relative vorticity near the tropopause. The OCSs associated with stratospheric intrusions are closely related to strong synoptic variability. As the stratospheric intrusion deepens on the day of the OCS onset, increased relative vorticity near the tropopause, stronger upward motion in the troposphere associated with divergence and convergence, more specific humidity in the troposphere, and weakened static stability in the middle troposphere are found within the OCS region, which are conducive to the development of deep convection that penetrates into the stratospheric intrusion. Compared with OCSs associated with stratospheric intrusions, other OCS events are characterized by stronger high cloud cover (HCC) and negative Outgoing Longwave Radiation (OLR) anomaly, as well as higher upward movement in the troposphere. This is conducive to other OCSs occurring in a more barotropic convective environment characteristic of the Asian monsoon, the vertical development height of weakened static stability and upward motion are higher, promoting the development of convective activity to higher altitudes and penetrating into the tropopause, thereby causing the uplift of the tropopause.

A Real-Time Radar QPE Error Correction for Convective Precipitation Using Long-Term TRMM-PR and GPM-DPR Observations

A Real-Time Radar QPE Error Correction for Convective Precipitation Using Long-Term TRMM-PR and GPM-DPR Observations

Intercomparison between IMD ground radar and TRMM PR observations using alignment methodology and artificial neural network

An inter-comparison of ground radar reflectivity with space-borne TRMM’s Precipitation Radar using alignment methodology has been presented. For this purpose, reflectivity data from Dual Polarization Ground Radar (GR) maintained by the India Meteorological Department (IMD) at the IMD Delhi site is utilized. IMD Delhi has collected radar data during Continental Tropical Convergence Zone (CTCZ) programme from 2011 to 2013. The present study utilizes monsoon data collected during 4 months, namely, June, July, August, and September (JJAS) from the year 2013. The GR observables are first converted from polar coordinates to Cartesian coordinates and then spatially aligned with TRMM PR data at a near-real-time to a common volume. It was found that in all the overpass cases, IMD’s GR reflectivity has a positive bias when compared with TRMM PR. A methodology is proposed to ‘correct’ the GR reflectivity data by considering TRMM PR data as ‘truth’ using a neural network-based approach. A supervised learning algorithm based on the back-propagation neural network is used for this purpose. Ground radar reflectivity is fed as input to the network, while the TRMM PR reflectivity is the target. The trained network is then tested for its performance against data which is not used as part of the training process. The present methodology demonstrates the match up of uncalibrated ground radar measured reflectivity and a well-calibrated space-borne radar.

Quantifying the contribution of the Megha‐Tropiques mission to the estimation of daily accumulated rainfall in the Tropics

Satellite estimation of accumulated precipitation is an important facet of the study of the tropical water cycle. An advanced data merging approach using infrared geostationary imagery and microwave constellation based instantaneous rain rate estimates has been implemented in the framework of the Megha‐Tropiques and Global Precipitation Measurements missions. The Tropical Amount of Rainfall with Estimation of ERors (TAPEER) algorithm has been tailored to account for the loss of the MADRAS conical scanning radiometer by using the SAPHIR sounder rainfall detection capability, thanks to a novel two‐constellation implementation of the algorithm. A new bias correction module based on the TRMM PR observations is also presented. The performances of this new version of the product are reviewed with emphasis on West Africa. In particular, using data‐denial experiments, the contribution of SAPHIR data to the rainfall daily accumulation is quantified for various configurations of the microwave constellation and various algorithmic parameter selections. The results show that the daily accumulation statistics are well improved when SAPHIR is taken into the constellation. The improvements can be quantified using bulk statistics but are more evident following a frequency analysis. The pattern of the impact is a complex convolution of rainfall occurrence and of the Megha‐Tropiques mission original sampling. Over the 20°N–20°S belt, in zonal mean, the inclusion of SAPHIR data alters the daily accumulation substantially (more than 50% of the daily accumulation) more than 10% of the time and more than 20% when conditioned upon rainfall. Under both metrics, the improvement is majored in the 12°–17° latitude band where the Megha‐Tropiques mission sampling is at its maximum.

Three-dimensional fusion of spaceborne and ground radar reflectivity data using a neural network-based approach

The spaceborne precipitation radar onboard the Tropical Rainfall Measuring Mission satellite (TRMM PR) can provide good measurement of the vertical structure of reflectivity, while ground radar (GR) has a relatively high horizontal resolution and greater sensitivity. Fusion of TRMM PR and GR reflectivity data may maximize the advantages from both instruments. In this paper, TRMM PR and GR reflectivity data are fused using a neural network (NN)-based approach. The main steps included are: quality control of TRMM PR and GR reflectivity data; spatiotemporal matchup; GR calibration bias correction; conversion of TRMM PR data from Ku to S band; fusion of TRMM PR and GR reflectivity data with an NN method; interpolation of reflectivity data that are below PR’s sensitivity; blind areas compensation with a distance weighting-based merging approach; combination of three types of data: data with the NN method, data below PR’s sensitivity and data within compensated blind areas. During the NN fusion step, the TRMM PR data are taken as targets of the training NNs, and gridded GR data after horizontal downsampling at different heights are used as the input. The trained NNs are then used to obtain 3D high-resolution reflectivity from the original GR gridded data. After 3D fusion of the TRMM PR and GR reflectivity data, a more complete and finer-scale 3D radar reflectivity dataset incorporating characteristics from both the TRMM PR and GR observations can be obtained. The fused reflectivity data are evaluated based on a convective precipitation event through comparison with the high resolution TRMM PR and GR data with an interpolation algorithm.

Ground-based radar reflectivity mosaic of mei-yu precipitation systems over the Yangtze River–Huaihe River basins

The 3D radar reflectivity produced by a mosaic software system, with measurements from 29 operational weather radars in the Yangtze River–Huaihe River Basins (YRHRB) during the mei-yu season of 2007, is compared to coincident TRMM PR observations in order to evaluate the value of the ground-based radar reflectivity mosaic in characterizing the 3D structures of mei-yu precipitation. Results show reasonable agreement in the composite radar reflectivity between the two datasets, with a correlation coefficient of 0.8 and a mean bias of -1 dB. The radar mosaic data at constant altitudes are reasonably consistent with the TRMM PR observations in the height range of 2–5 km, revealing essentially the same spatial distribution of radar echo and nearly identical histograms of reflectivity. However, at altitudes above 5 km, the mosaic data overestimate reflectivity and have slower decreasing rates with height compared to the TRMM PR observations. The areas of convective and stratiform precipitation, based on the mosaic reflectivity distribution at 3-km altitude, are highly correlated with the corresponding regions in the TRMM products, with correlation coefficients of 0.92 and 0.97 and mean relative differences of -7.9% and -2.5%, respectively. Finally, the usefulness of the mosaic reflectivity at 3-km altitude at 6-min intervals is illustrated using a mesoscale convective system that occurred over the YRHRB.

Agreement between monthly land rainfall estimates from TRMM-PR and gauge-based observations over South Asia

There is a demand for reliable rainfall data-set over the South Asia region covering both land and ocean for model validation/development and various applications. For satellite rainfall estimates (SREs), the algorithm development groups also need validation information on SRE. The Tropical Rainfall Measuring Mission (TRMM) project has produced recently improved version 7 (V7) rainfall data-sets. Version 6 (V6) and V7 of 3A25, the surface rainfall products derived from TRMM precipitation radar (PR), are compared with gauge-based observations at 0.5° latitude/longitude resolution for the period of 1998–2007 over the South Asian land region. Both 3A25V7 and 3A25V6 represent the mean rainfall distribution patterns reasonably well. However, 3A25 products overestimate rainfall over the Indonesian region compared to gauge-based data. For some parts of South Asia, SREs show considerable difference in the magnitude of coefficient of variation compared to gauge-based information. At seasonal scale, a contrasting feature in bias over India during the pre-monsoon and monsoon seasons is noticed from both the versions of 3A25 data-set. In general, 3A25 rainfall data-sets are able to capture the interannual variability of rainfall over South Asia. The frequency distribution of monthly rainfall rate reveals that 3A25 products marginally underestimate rainfall below 10 mm day−1 and overestimate higher rainfall rate compared to gauge-based data. Overall, 3A25V7 product is marginally better than its previous version (3A25V6) over the South Asian land region.

Climatology of Warm Rain and Associated Latent Heating Derived from TRMM PR Observations

Abstract The large-scale distribution of precipitation and latent heating (LH) profiles in the tropics, subtropics, and part of the midlatitudes was studied using a 9-yr dataset derived from Tropical Rainfall Measuring Mission precipitation radar observations, with emphasis on the contribution of warm rain. The distribution of warm rain showed features unique from those of rain in other categories and those of outgoing longwave radiation. Warm rain was weak over land but widely distributed over oceans, especially along the intertropical convergence zone (ITCZ) and the western part of the subtropical oceans. The observed amount of warm rain depended on the rainfall intensity rather than on the frequency of warm rain events. The amount of warm rain over ocean was positively correlated with sea surface temperature (SST); this dependency was found in the tropics, subtropics, and part of the midlatitudes, whereas dependency of SST on total rain was confined to the tropics. Both total rain and warm rain were concentrated in the ITCZ, which elongated along the local SST maximum. Small amounts of warm rain were found along subtropical convergence zones (the baiu frontal zone and subtropical portions of the South Pacific convergence zone and the South Atlantic convergence zone) with ample total rainfall. However, larger amounts of warm rain were observed at the lower-latitude sides of these zones in the upstream portions of low-level moisture flow toward the zones. Warm rain may cultivate the subtropical convergence zones by deepening the moist boundary layer and increasing moisture flux toward the zones. The statistical relationship between warm rain and low-level cloudiness showed that the warm rain amount was large when low-level cloudiness was 20%–30% and small when low-level cloudiness was greater than 40%. This indicates that intense warm rain is provided by convective clouds, not by stratiform clouds, in conditions of substantial cloudiness. Despite the small contribution to total rain, warm rain maintained positive LH values over most of the tropical and subtropical oceans. The LH by warm rain masked low-level cooling observed in stratiform rain and maintained positive LH in the lower atmosphere below the melting layer. Because warm rain was confined to oceans, a strong LH contrast was maintained along the coast; this contrast reached values of 1–2 K day−1 in certain places and may affect local and monsoonal circulation across continental coasts.

Tropical precipitation estimated by GPCP and TRMM PR observations

In this study, tropical monthly mean precipitation estimated by the latest Global Precipitation Climatology Project (GPCP) version 2 dataset and Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are compared in temporal and spatial scales in order to comprehend tropical rainfall climatologically. Reasons for the rainfall differences derived from both datasets are discussed. Results show that GPCP and TRMM PR datasets present similar distribution patterns over the Tropics but with some differences in amplitude and location. Generally, the average difference over the ocean of about 0.5 mm d−1 is larger than that of about 0.1 mm d−1 over land. Results also show that GPCP tends to underestimate the monthly precipitation over the land region with sparse rain gauges in contrast to regions with a higher density of rain gauge stations. A Probability Distribution Function (PDF) analysis indicates that the GPCP rain rate at its maximum PDF is generally consistent with the TRMM PR rain rate as the latter is less than 8 mm d−1. When the TRMM PR rain rate is greater than 8 mm d−1, the GPCP rain rate at its maximum PDF is less by at least 1 mm d−1compared to TRMM PR estimates. Results also show an absolute bias of less than 1 mm d−1 between the two datasets when the rain rate is less than 10 mm d−1. A large relative bias of the two datasets occurs at weak and heavy rain rates.

A case study on rainfall dynamics during El Niño/La Niña 1997/99 in Ecuador and surrounding areas as inferred from GOES-8 and TRMM-PR observations

A case study on rainfall dynamics during El Niño/La Niña 1997/99 in Ecuador and surrounding areas as inferred from GOES-8 and TRMM-PR observations

A Re-examination of Precipitation Activity in the Subtropics and the Mid-latitudes Based on Satellite-derived Data.

Large-scale precipitation activity in the subtropics and the mid-latitudes, in addition to seasonal variation, were studied using new climatological precipitation datasets: GPCP rain gauge-satellite combined data, and TRMM level-3 data derived from TRMM-PR observations. We found significant large-scale precipitation zones extending between the subtropics and the midlatitudes, referred to as SMPZs (Subtropical Mid-latitude Precipitation Zones) in this study. Most portions of the SMPZs existed over the oceans. Meridional variation of zonal averaged precipitation was quite different between land and the oceans. Mid-latitude peaks at @40 in zonal averaged precipitation were observed only over the oceans, because the SMPZs over the ocean formed the 40 peaks. The midlatitude peaks significantly intensified in the fall and winter when the SMPZs zonally extended in the mid-latitudes and kept precipitation as substantial as in summer. In summer, the SMPZs extended diagonally across the subtropics from the active tropical monsoon rainfall areas. Precipitation over the subtropical oceans thus increased in summer. Over land, mid-latitude peaks were not found. Precipitation intensified in summer, both in the subtropics and in the mid-latitudes. The mid-latitude portions of the SMPZs extended near the storm tracks defined by high baroclinic wave activity. However, many portions of the SMPZs shifted to the lower latitudes from the storm tracks in fall and winter. In summer, baroclinic wave activity was weak for the subtropical portions of the SMPZs, which were characterized by convergence and frontal zones with weak baroclinicity. Vertical structure of precipitation observed by PR suggested that deep (shallow) stratiform and convective precipitation largely contributed to the active rainfall along the SMPZs in summer (fall and winter). A possible relationship between the shallow precipitation and the displacement of the SMPZs from the storm tracks in fall and winter was discussed.

Relationships between Radar Properties at High Elevations and Surface Rain Rate: Potential Use for Spaceborne Rainfall Measurements

Abstract Ground-based radar data have been used to investigate the relationship between reflectivity at high elevations and surface rain rates. Such relations are useful for rainfall measurements by spaceborne radars at attenuating wavelength such as the 2.2-cm Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite. In addition to attenuation, these relations are complicated by partial beamfilling, hail, and windshear sorting of particles, among others that affect the corresponding ground-based radar reflectivity–surface rain-rate relationships. TRMM-PR observations were simulated based on radar data from Darwin, Australia. The three-dimensional simulated data were classified by rain type according to several radar properties at high altitudes that are not seriously affected by attenuation. These properties are physical parameters relevant to the variations in the desired relationships. The resulting relationships are robust and permit the classification of near-surface...