Tropical Rainfall Measuring Mission Radar Research Articles

Toward Improving Ice Water Content and Snow-Rate Retrievals from Radars. Part II: Results from Three Wavelength Radar–Collocated In Situ Measurements and CloudSat–GPM–TRMM Radar Data

AbstractTwo methods for deriving relationships between the equivalent radar reflectivity factor Ze and the snowfall rate S at three radar wavelengths are described. The first method uses collocations of in situ aircraft (microphysical observations) and overflying aircraft (radar observations) from two field programs to develop Ze–S relationships. In the second method, measurements of Ze at the top of the melting layer (ML), from radars on the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), and CloudSat satellites, are related to the retrieved rainfall rate R at the base of the ML, assuming that the mass flux through the ML is constant. Retrievals of R are likely to be more reliable than S because far fewer assumptions are involved in the retrieval and because supporting ground-based validation data are available. The Ze–S relationships developed here for the collocations and the mass-flux technique are compared with those derived from level 2 retrievals from the standard satellite products and with a number of relationships developed and reported by others. It is shown that there are substantial differences among them. The relationships developed here promise improvements in snowfall-rate retrievals from satellite-based radar measurements.

Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Ocean

AbstractUsing Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model-simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)–one-dimensional variational (1DVAR) approach.The optimization is based on comparing simulated to observed radar reflectivity profiles and the corresponding passive microwave observations at the frequencies of the TRMM Microwave Imager (TMI) instrument. To minimize the discrepancies between the actual and the synthetic observations, the simulated cloud and precipitation profiles are optimized by adjusting the contents of the hydrometeors. To reduce the dimension of the hydrometeor content profiles in the optimization, multivariate relations among hydrometeor species are used.After applying the optimization method to modify the simulated clouds, the optimized cloud-radiation database has a joint distribution of reflectivity and associated brightness temperatures that is considerably closer to that observed by TRMM PR and TMI, especially at 85 GHz. This implies that the EOF–1DVAR approach can generate profiles with realistic distributions of frozen hydrometeors, such as snow and graupel. This approach may be similarly adapted to operate with the variety and capabilities of the passive microwave radiometers that compose the Global Precipitation Measurement (GPM) constellation. Furthermore, it can be extended to other oceanic regions and seasons.

Where the Least Rainfall Occurs in the Sahara Desert, the TRMM Radar Reveals a Different Pattern of Rainfall Each Season

Abstract Some previous studies were unable to detect seasonal organization to the rainfall in the Sahara Desert, while others reported seasonal patterns only in the less-arid periphery of the Sahara. In contrast, the precipitation radar on the Tropical Rainfall Measuring Mission (TRMM) satellite detects four rainy seasons in the part of the Sahara where the TRMM radar saw the least rainfall during a 15-yr period (1998–2012). According to the TRMM radar, approximately 20°–27°N, 22°–32°E is the portion of the Sahara that has the lowest average annual rain accumulation (1–5 mm yr−1). Winter (January and February) has light rain throughout this region but more rain to the north over the Mediterranean Sea. Spring (April and May) has heavier rain and has lightning observed by the TRMM Lightning Imaging Sensor (LIS). Summer rain and lightning (July and August) occur primarily south of 23°N. At a maximum over the Red Sea, autumn rain and lightning (October and November) can be heavy in the northeastern portion of the study area, but these storms are unreliable: that is, the TRMM radar detects such storms in only 6 of the 15 years. These four rainy seasons are each separated by a comparatively drier month in the monthly rainfall climatology. The few rain gauges in this arid region broadly agree with the TRMM radar on the seasonal organization of rainfall. This seasonality is reason to reevaluate the idea that Saharan rainfall is highly irregular and unpredictable.

Contribution of Tropical Cyclones to Global Very Deep Convection

Abstract Based on the 12-yr (1998–2009) Tropical Rainfall Measuring Mission (TRMM) precipitation feature (PF) database, both radar and infrared (IR) observations from TRMM are used to quantify the contribution of tropical cyclones (TCs) to very deep convection (VDC) in the tropics and to compare TRMM-derived properties of VDC in TCs and non-TCs. Using a radar-based definition, it is found that the contribution of TCs to total VDC in the tropics is not much higher than the contribution of TCs to total PFs. However, the area-based contribution of TCs to overshooting convection defined by IR is 13.3%, which is much higher than the 3.2% contribution of TCs to total PFs. This helps explain the contradictory results between previous radar-based and IR-based studies and indicates that TCs only contribute disproportionately large amount of overshooting convection containing mainly small ice particles that are barely detected by the TRMM radar. VDC in non-TCs over land has the highest maximum 30- and 40-dBZ height and the strongest ice-scattering signature derived from microwave 85- and 37-GHz observations, while VDC in TCs has the coldest minimum IR brightness temperature and largest overshooting distance and area. This suggests that convection is much more intense in non-TCs over land but is much deeper or colder in TCs. It is found that VDC in TCs usually has smaller environmental shear but larger total precipitable water and convective available potential energy than those in non-TCs. These findings offer evidence that TCs may contribute disproportionately to troposphere-to-stratosphere heat and moisture exchange.

Comparing meteorological spaceborne and ground-based radars: optimal satellite overpass distance from a ground-based radar site

Spaceborne and ground-based radars (GRs) provide a complementary view of the complex precipitation field. As there are significant differences between the two instruments, it is possible to use the peculiarities of one sensor to check the consistency of the results of the other. For instance, the radar measurement is affected by changes in the spatial resolution, which ‘worsens’ with the square of the range. Unfortunately, the GR has to measure rain from small to large distances. In contrast, changes in size of the Tropical Rainfall Measuring Mission (TRMM) radar sampling volume are almost negligible, since its measurements originate from similar distances of 400–420 km. However, the TRMM precipitation radar (TPR) vertical resolution becomes poorer when the angle of incidence increases (i.e. when the distance of the TPR samples from the nadir increases). This article shows that part of this problem, which affects the reference radar (namely the TPR), can be transferred to the radar under investigation (namely the GR), depending on the satellite overpass distance from the GR site. Given the present swath of the TPR (∼240 km), the worst cases occur when the satellite passes close or at the maximum range of the GR. A small influence is found when the satellite passes at approximately half of the GR range. These results, which have been derived for the first-ever spaceborne radar (the TRMM radar), can be easily adapted to future missions (e.g. the global precipitation measuring dual-wavelength radar).

Using TRMM spaceborne radar as a reference for compensating ground-based radar range degradation: Methodology verification based on rain gauges in Israel

[1] While intense scientific efforts have focused on radar precipitation estimation in temperate climatic regimes, relatively few studies have examined dry climatic regions. This paper examines rain depth estimation for a 19 day rainfall period in Israel, where the gauge spatial distribution is particularly nonhomogeneous. This fact exacerbates the main drawback of rain gauge observations, which is undersampling. Meteorological ground-based radar (GR) can supplement the desired information on precipitation distribution. However, especially in a complex orographic region, radar scientists are faced with beam broadening with distance, nonhomogeneous beam filling, and partial-beam occultation, together with changes in the vertical reflectivity profile. This paper presents an improvement of GR precipitation estimates thanks to a range adjustment based on spaceborne meteorological radar. In the past, the Tropical Rainfall Measuring Mission (TRMM) satellite radar was used for checking the GR mean field bias around the world. To our knowledge, however, it is the first time that GR-derived cumulative rainfall amounts show a better agreement with gauges, thanks to the mean field bias and range-dependent compensation derived using the well-calibrated Ku band TRMM radar as a reference. The average bias improves from +1.0 dB to −0.3 dB; more interesting and difficult to obtain is a reduction of the dispersion of the error. Using TRMM-based range compensation, the scatter decreases from 2.21 dB to 1.93 dB. We conclude that it is well worth trying to compensate for the GR range degradation.

Vertical profiling of tropical precipitation using passive microwave observations and its implications regarding the crash of Air France 447

In a recent study by Haddad and Park (2009), a method was proposed to use colocated simultaneous observations by the space‐borne Tropical Rainfall Measuring Mission (TRMM) precipitation radar and microwave imager to train the microwave radiometer to retrieve vertical profiles of precipitation in the absence of radar observations. This radar‐trained passive‐microwave approach was developed for midlatitude precipitation regimes, where it was found that the inhomogeneity of the rain within the radiometer field of view was the main impediment to the estimation of the vertical distribution of rain. The approach constrains the brightness temperature combinations used in the retrieval to lie in the orthogonal complement to the two main clear‐sky principal components in brightness temperature space. This note summarizes the results of applying this approach to observations over the Atlantic Intertropical Convergence Zone during May 2009 and deriving estimates of the uncertainty in passive‐microwave retrievals of the storm‐top height and of the first vertical principal component of the rain. The results are illustrated on a serendipitous granule of data taken while the TRMM radar was unfortunately not operational, about 20 min after the last transmission from the ill‐fated flight Air France 447.

Note on the weekly cycle of storm heights over the southeast United States

An earlier paper by Bell et al. (2008) showed satellite evidence that average summertime (1998–2005) rainfall over the noncoastal southeast U.S. varied with the day of the week in a statistically significant way, with the maximum occurring midweek (Tuesday–Thursday). An explanation was proposed in which the recurring midweek increase in air pollution over the area causes a shift in the drop size distribution in clouds to smaller sizes as the clouds develop. The smaller droplets could be carried to higher altitudes where their freezing releases additional latent heat, invigorating the storms. Evidence for this phenomenon was provided by storm height distributions obtained from the Tropical Rainfall Measuring Mission radar, but the statistical significance of the midweek increase in storm heights was unclear. An improved statistical analysis of the storm height distributions is provided here, indicating that the probability that storms climb above altitudes of 7–15 km is increased midweek relative to weekends (Saturday–Monday) for afternoon storms (1200–2400 LT). The morning storm heights, on the other hand, are found not to exhibit statistically significant shifts, which would be consistent with the above explanation. Morning storm statistics are also found to be much more sensitive than afternoon storm statistics to the exact area over which the averages are taken.

An Interpretation of TRMM Radar Observations of Shallow Convection with a Rain Cell Model

Observations of shallow, isolated convection from the Precipitation Radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) observatory were compared with simulations from a rain cell model to examine effects of sub-resolution scale convection on space-borne radar observations. A large sample of shallow isolated convection was obtained from PR data over the central Pacific Intertropical Convergence Zone. Storm top heights, ranged from 1000 to 3750 m, with a mode at 1500 m. A secondary classification was made to identify 3 classes with progressively smaller spatial scales: groups of rainy fields-of-view (FOVs), rainy FOVs with one neighboring rainy FOV, and solitary rainy FOVs. Smaller spatial scales were associated with shallower storms and lower radar reflectivity (dBZ) values. The solitary class was the focus of the modeling comparison. The first objective of the modeling exercise was to explore the possibility that information on the horizontal scale and rain rate intensity of sub-resolution shallow convection could be extracted from the PR observations by finding an optimal fit between simulated and observed dBZ distributions. The height and diameter of simulated rain cells were linked by assuming an average aspect ratio of one. Simulated and observed probability distributions of dBZ were compared for two modes of rain cell variability: a fixed aspect ratio with variable cell dBZ, and a fixed cell dBZ with variable aspect ratio. Both modes resulted in excellent comparisons with observed distributions. The second modeling objective was to compare rain rates from the simulated “ground truth” and simulated “retrieved” rain rates, and to determine the effective sampling area of the modeled FOV. In general, simulated retrieved rain rates had a positive bias, as expected from the non-linear Z-R relation. However, more complex patterns of potential negative biases were evident, depending on the size and intensity of modeled rain cells.

Opportunities and challenges for evaluating precipitation estimates during GPM mission

Data assimilation in conjunction with numerical weather prediction and a variety of hydrologic applications now depend on satellite observations of precipitation. However, providing values of precipitation is not sufficient unless they are accompanied by the associated uncertainty estimates. The main approach of quantifying satellite precipitation uncertainties generally requires establishment of reliable uncertainty estimates for the ground validation rainfall products. This paper discusses several of the relevant validation concepts evolving from the Tropical Rainfall Measuring Mission (TRMM) era to the Global Precipitation Measurement mission (GPM) era in the context of determining and reducing uncertainties of ground and space-based radar rainfall estimates. From comparisons of probability distribution functions of rain rates derived from TRMM precipitation radar and co-located ground based radar data - using the new NASA TRMM radar rainfall products (version 6) - this paper provides 1) a brief review of the importance of comparing pdfs of rain rate for statistical and physical verification of space-borne radar estimates of precipitation; 2) a brief review of how well the ground validation estimates compare to the TRMM radar retrieved estimates; and 3) discussion on opportunities and challenges to determine and reduce the uncertainties in space-based and ground-based radar estimates of rain rate distributions.

WHERE ARE THE MOST INTENSE THUNDERSTORMS ON EARTH?

The instruments on the Tropical Rainfall Measuring Mission (TRMM) satellite have been observing storms as well as rainfall since December 1997. This paper shows the results of a systematic search through seven full years of the TRMM database to find indicators of uncommonly intense storms. These include strong (> 40 dBZ) radar echoes extending to great heights, high lightning flash rates, and very low brightness temperatures at 37 and 85 GHz. These are used as proxy variables, indicating powerful convective updrafts. The main physical principles supporting this assertion involve the effects of such updrafts in producing and lofting large ice particles high into the storm, where TRMM's radar easily detects them near storm top. TRMM's passive microwave radiometer detects the large integrated ice water path as very low brightness temperatures, while high lightning flash rates are a physically related but instrumentally independent indicator. The geographical locations of these very intense convective storms ...

Radiative and Microphysical Characteristics of Deep Convective Systems in the Tropical Western Pacific

Abstract The radiative and microphysical characteristics of 17 precipitating systems observed by the Tropical Rainfall Measuring Mission (TRMM) satellite over Manus, Papua New Guinea, and Nauru Island are modeled. These cases represent both deep and midlevel convection. Reflectivity data from the TRMM precipitation radar and Geostationary Meteorological Satellite infrared radiometer measurements are used to parameterize the three-dimensional cloud microphysics of each precipitating cloud system. These parameterized cloud properties are used as input for a two-stream radiative transfer model. Comparisons with measurements of broadband radiative fluxes at the top of atmosphere and the surface show agreement to within 20%. In cases in which the convective available potential energy (CAPE) is large, deep convective clouds with extended anvil decks form, containing layers of ice crystals that are too small to be detected by the TRMM radar but have a large optical thickness. This results in maximum shortwave he...

Validation of TRMM Radar Rainfall Data over Major Climatic Regions in Africa

Abstract The Global Precipitation Climatology Center global-precipitation-analyses rain gauge data have been used to validate the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) data over the major climatic regions in Africa. The threshold-matched precipitation index and the TRMM-and-other-sources “best-estimate” data (3B43) have also been compared with rain gauge data and with the TRMM PR rainfall product. In the 36-month climatological assessment of the satellite products at a grid spacing of 1.0°, continental Africa has been categorized into five distinct climatic regions: arid, semiarid, savanna, tropical wet, and the South Atlantic Ocean. Zonal mean analysis shows that TRMM PR has a large overestimation in the tropical-rain-forest region of Africa in December–January–February and in March–April–May. The bias is minimized in June–July–August and September–October–November. Bias is generally high for all algorithms in the dry seasons when rainfall is minimal but is less pronounced i...

A Summary of Reflectivity Profiles from the First Year of TRMM Radar Data

Abstract A preliminary climatology of reflectivity profiles derived from the first spaceborne precipitation radar (PR), which is on board the Tropical Rainfall Measuring Mission (TRMM) satellite, is described using the data from January 1998 to February 1999. This study focuses on the behavior of the melting-layer (bright band) altitude in stratiform precipitation. This analysis will be useful for improving passive microwave radiometric estimations of rain rates because it provides information about otherwise unknown parameters in the estimation models (the depth of the rain column). The monthly means of the melting-layer altitude estimated over 10° × 10° latitude–longitude grid boxes show that high melting layers (>4.5 km) tend to appear during extreme events such as El Nino and the Asian summer monsoon, and lower melting layers are usually observed in the winter hemisphere, which suggests a close relationship between surface temperature and the melting-layer altitude. Detailed climatologies of the profi...

衛星搭載型レーダと地上設置型観測機により観測された降雨強度を比較する場合の誤差のシミュレーションによる評価

The Tropical Rainfall Measuring Mission (TRMM) is a United States-Japan joint project for rain measurement from space. The first spaceborne rain radar has been installed aboard the TRMM satellite. The performance of the TRMM radar should always be validated against reference data. Use of the rainfall rate measured by ground-based instruments such as rain radar, rain gauges, or a radio link is a possible way to validate the TRMM radar. We have analyzed errors in the comparison of rainfall rates measured with the TRMM radar and with the ground-based instruments by means of a computer simulation that uses actual ground-based rain radar data. Results show that if the rainfall rate measured by the TRMM is compared with that measured by the ground-based radar at a higher correlation, the time difference between the TRMM and the ground-based radar measurements should be less than 5 minutes. Results also show that if the rainfall rate measured by the TRMM is compared with that measured by rain gauges and a radio link within a typical error on the radar measurement, nine rain gauges with 1 minute integration time or 16 rain gauges with 10 minutes integration time will be required in a pixel of the TRMM, and propagation path longer than 7 km of a radio link will be required.

Estimating 13.8-GHz Path-Integrated Attenuation from 10.7-GHz Brightness Temperatures for the TRMM Combined PR–TMI Precipitation Algorithm

Abstract This study presents research in support of the design and implementation of a combined radar–radiometer algorithm to be used for precipitation retrieval during the Tropical Rainfall Measuring Mission (TRMM). The combined algorithm approach is expected to overcome various difficulties that arise with a radar-only approach, particularly related to estimates of path-integrated attenuation (PIA) along the TRMM radar beam. A technique is described for estimating PIA at the 13.8-GHz frequency of the TRMM precipitation radar (PR) from 10.7-GHz brightness temperature TB measurements obtained from the TRMM microwave imager. Because the PR measures at an attenuating frequency, an independent estimate of PIA is used to constrain the solution to the radar equation, which incorporates effects of attenuation propagation along a radar beam. Through the use of variational or probabilistic techniques, the independent PIA calculations provide a means to adjust for errors that accumulate in estimates of range-depen...

Optimal Estimation of Rain-Rate Profiles from Single-Frequency Radar Echoes

The significant ambiguities inherent in the determination of a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency are well documented. Indeed, one already knows that by appropriately varying the parameters of the frequency are well documented. Indeed, one already knows that by appropriately varying the parameters of the reflectively-rain rate (Z–R) and/or attenuation-rain rate (k–R) relationships one can produce several substantially different rain-rate profiles that would produce the same radar power profile. Imposing the additional constraint that the path-averaged rain rate be a given fixed number does reduce the ambiguities but falls far short of eliminating them. While formulas to generate all mutually ambiguous rain-rate profiles from a given profile of received radar reflectivities have already been derived, there remains to be produced a quantitative measure to assess how likely each of these profiles is, what the appropriate “average” profile should be, and what the “variance” of these multiple solutions is. To do this, one needs to spell out the stochastic constraints that can allow us to make sense of the words “averaged” and “variance” in a mathematically rigorous way. Such a quantitative approach would be particularly well suited for such systems as the planned precipitation radar of the Tropical Rainfall Measuring Mission (TRMM). Indeed, one would then be able to use the radar reflectivities measured by the TRMM radar to estimate the rain-rate profile that would most likely have produced the measurements, as well as the uncertainty in the estimated rain rates as a function of range. Such an optimal approach is described in this paper.