Comparative Analysis of GMI and DPR Precipitation Measurements over Global Oceans During Summer Season

Abstract

This study provides a comprehensive comparison between Global Precipitation Measurement (GPM) Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) measurements through analysis of collocated precipitation at the 19 GHz footprint scale for pixels during hemispheric summer seasons (JJA for Northern Hemisphere and DJF for Southern Hemisphere). Precipitation pixels exceeding 0.2 mm/h are categorized into convective, stratiform, and mixed types based on DPR classifications. While showing generally good agreement in spatial patterns, the GMI and DPR exhibit systematic differences in precipitation intensity measurements. The GMI underestimates convective precipitation intensity by 13.8% but overestimates stratiform precipitation by 12.1% compared to DPR. Mixed precipitation shows the highest occurrence frequency (47.6%) with notable differences between instruments. While measurement differences for convective precipitation have significantly improved from previous Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) estimates (62% to 13.8%), the overall difference has increased (from 2.6% to 12.6%), primarily due to non-convective precipitation. Latitudinal analysis reveals distinct precipitation regimes: tropical regions (below ~30°) produce intense convective precipitation that contributes about 40% of total precipitation despite lower frequency, while mid-latitudes (beyond 30°) shift toward stratiform-dominated regimes where stratiform precipitation accounts for 60–90% of the total. Additionally, geographical variation in GMI-DPR differences shows a see-saw pattern across latitude bands, with opposite signs between tropical and mid-latitude regions for convective and stratiform precipitation types. A fundamental transition in precipitation characteristics occurs between 30° and 40°, reflecting changes in precipitation mechanisms across Earth’s climate zones. Analysis shows that tropical precipitation systems generate approximately three times more precipitation per unit area than mid-latitude regions.

1. Introduction

The latent heat released during precipitation formation constitutes a primary energy source driving weather and climate systems in the atmosphere (e.g., [1,2,3,4,5]). Accurate measurement of precipitation at surface is very important as latent heat is generally estimated from these measurements. Consequently, precipitation has become recognized as a critical resource for agriculture, irrigation, and water management [4,6]. Despite its importance, precipitation remains one of the most challenging meteorological parameters to measure accurately and consistently.

Satellite remote sensing techniques have emerged as a promising approach for deriving global precipitation estimates [7,8,9,10]. Among various satellite observation methods, microwave observations have proven particularly effective for precipitation measurements. Microwave radiation strongly interacts with hydrometeors inside clouds through processes of absorption, emission, scattering, and transmission [7,11,12], whereas infrared radiation primarily interacts with cloud tops and surfaces (e.g., [13]). The Precipitation Measurement Missions (PMM) of NASA evolved from the Special Sensor Microwave/Imager (SSM/I) through the Tropical Rainfall Measuring Mission (TRMM) to the current Global Precipitation Measurement (GPM) mission [14,15,16,17,18]. A major advancement in the TRMM was the introduction of active microwave technology through Precipitation Radar (PR), which directly measures precipitation by transmitting radar pulses and analyzing backscattered signals from hydrometeors [16]. Building upon the TRMM’s success, the GPM Core Observatory features an advanced Dual-frequency Precipitation Radar (DPR) and the GPM Microwave Imager (GMI) [18,19]. These instruments employ fundamentally different measurement principles—passive radiometric observation versus active radar detection—which can lead to systematic differences in precipitation estimates across various precipitation regimes. These satellites function as flying rain gauges, calibrating other constellation satellites and enabling consistent global precipitation measurements.

Understanding precipitation patterns over oceans is critical for global water cycle and energy balance calculations. The GMI and DPR provide independent yet complementary measurements of precipitation properties. As the GMI serves as the calibration reference for the GPM constellation satellites and plays a crucial role in global precipitation estimation, a thorough understanding of its retrieval characteristics is essential for accurate precipitation monitoring.

While many studies have validated satellite-based precipitation measurements [20,21,22,23,24,25], these validations are particularly challenging over ocean regions where in situ observations are limited. As Kidd and Levizzani (2011) [9] noted, active microwave techniques provide perhaps the most direct method of space-based precipitation estimation. Both the TRMM and GPM instruments provide unique opportunities for precipitation measurement and characteristic comparisons, as they observe the same precipitation systems simultaneously from the same platform. Liu et al. (2020) [26] leveraged this advantage by using combined DPR and GMI observations to investigate global overshooting convection features. Related to this, previous studies have identified systematic differences across various precipitation regimes and geographical regions primarily using TRMM TMI and PR measurements [25,27].

Despite the availability of GPM data since its launch in 2014, comprehensive analyses comparing instantaneous precipitation measurements from GMI rainfall retrievals and collocated DPR measurements across global oceanic regions remain limited. Over global oceans, where relatively low and homogeneous surface emissivity enables robust passive microwave rain retrieval [10,17], this study aims to conduct such a comparison. Using five years of observations during summer months (June–August) for each hemisphere, we investigate rainfall characteristics of latitudinal regimes from tropical to mid-latitude environments. This analysis utilizes DPR’s precipitation type classification capabilities to examine the measurement attributes of both instruments across convective and stratiform precipitation regions and various geographical settings through detailed analysis of frequency and amount distributions.

This systematic comparison helps address important questions regarding satellite-based precipitation measurement uncertainties that directly impact global water cycle studies, climate model validation, and extreme weather monitoring. Identifying the complementary strengths and systematic biases of active and passive microwave instruments across different precipitation regimes is essential for improving retrieval algorithms and developing more accurate merged precipitation products. Furthermore, the geographical patterns of instrument differences revealed in this study provide valuable context for interpreting satellite-based precipitation climatologies, especially in data-sparse oceanic regions where in situ validation remains challenging. By quantifying measurement uncertainties across latitudinal bands and precipitation types, these findings will contribute to more reliable precipitation monitoring for both operational forecasting and long-term climate research.

The remainder of this paper is organized as follows: Section 2 describes the data and methodology used in this study, including the characteristics of the GMI and DPR instruments and the collocation approach. Section 3 presents the results of this comparative analysis, examining both global spatial patterns and regional variations in rainfall intensity and accumulated precipitation across different latitudes. Finally, Section 4 discusses the implications of these findings for satellite-based precipitation monitoring and summarizes the conclusions.

2. Data and Methods

2.1. GMI and DPR Rain Products

The GPM Core Observatory operates at an altitude of 407 km in a non-sun-synchronous orbit, covering the tropics, subtropics, and mid-latitudes (65° S–65° N). This orbital configuration enables sampling at different local times, providing observations unbiased by the diurnal cycle for various precipitation types [4]. Due to its orbital characteristics, GPM sampling frequency increases with latitude, resulting in more frequent observations in mid-latitude regions compared to tropical areas. The GMI measures naturally upwelling radiation across 13 different frequency channels with a swath width of 885 km [18]. DPR operates at Ku-band (13.6 GHz) and Ka-band (35.5 GHz) with swath widths of 245 km and 125 km, respectively. These radar instruments measure reflectivity with minimum detection thresholds of approximately 18 dBZ for KuPR and 12 dBZ for KaPR [19].

This study utilizes GPM precipitation products from version 9 (1B.GPM.GMI, 2A.GPM.GMI and 2A.GPM.DPR) from the GMI and DPR over oceanic regions, employing the Ku-only algorithm retrievals for DPR data. GMI rainfall retrievals are derived from the GMI PROFiling (GPROF) algorithm, which employs a Bayesian approach using a priori databases [17] and quantifies rain rates from 0.2 to 60.0 mm/h at an effective resolution of ~15 km [18]. The DPR rainfall products are retrieved with a spatial resolution of ~5 km and can quantify rain rates between ~0.2 and 110.00 mm/h [4,18,19,28]. Additionally, the DPR algorithm classifies precipitation into convective, stratiform, and other types based on the horizontal and vertical structure characteristics of the precipitation systems [19]. We use this classification information from collocated DPR pixels to determine rain types for each GMI rain pixel.

2.2. GMI and DPR Collocation

This study analyzes oceanic precipitation measurements during summer seasons: June–August 2020–2024 for the Northern Hemisphere (NH) and December–February 2020–2024 for the Southern Hemisphere (SH). The analysis focuses on ocean regions with low surface emissivity to minimize surface effects on passive microwave measurements. The collocation procedure involves collecting DPR pixels and identifying their associated rain rate and type products within each GMI pixel footprint. It matches DPR pixels with a given GMI pixel footprint, weighting DPR rain rates using the 19 GHz antenna gain function (e.g., [24,27]). By doing so, the horizontal scales (~15 km) between these two observations are better aligned for rigorous comparison. Pixels are archived when either instrument’s rain rate exceeds 0.2 mm/h.

For each pair, we calculate convective fractions (convF) and stratiform fractions (stratF) using the 19 GHz antenna gain function [24,25] and classify precipitation as convective (convF > 50%), stratiform (stratF > 50%), or mixed (remainder). Both GMI and DPR rain rates and precipitation types are analyzed at this 15 km horizontal resolution.

The study analyzes precipitation characteristics at a 5° × 5° latitude/longitude grid scale. To account for the non-uniform sampling distribution of the GPM’s orbit, we standardized the observation counts across different latitudes by scaling up the number of observations in less frequently sampled regions to match the most frequently observed latitude band. This normalization ensures that latitudinal precipitation comparisons are not biased by differences in sampling frequency. Within these 5° × 5° grid boxes, ocean fractions are calculated for mixed ocean/land grids to adjust accumulated precipitation amounts for consistent comparison. For performance evaluation, correlation coefficients, root mean square errors (RMSEs), biases, and analyses of probability density functions (PDFs) and cumulative distribution functions (CDFs) are calculated to compare GMI retrievals against DPR measurements. Statistical significance of GMI-DPR differences was evaluated using two-sample t-tests. Even for convective precipitation (the least frequent type) with sample sizes ranging from 28 to over 72,000 observations per grid cell, differences are highly significant (p < 0.001) in the majority of grid cells.

3. Results and Discussion

3.1. Global Distribution

We analyzed rainfall events within 5° × 5° grids to calculate the fractional occurrence of precipitation types (Figure 1). This analysis reveals distinct regional characteristics in the global spatial distribution of convective, stratiform, and mixed precipitation categories. In low-latitude regions (between approximately ±30° latitude), convective fractions are typically in the range of 15–25%, while stratiform fractions generally range from 30% to 50%. Mixed-type precipitation is highly prevalent, typically exceeding ~40%. Within these tropical and subtropical regions, the subtropical high pressure (STHP) systems’ core and surrounding regions in both hemispheres exhibit a distinctive precipitation pattern, showing relatively higher convective fractions (~20–25%) with minimal stratiform precipitation (<15%) but substantial mixed-type precipitation (~60–85%). This suggests that precipitation is likely to form as isolated or unorganized convective systems in these thermodynamically stable and subsidence-dominated environments. These isolated and unorganized systems rarely develop large stratiform areas, unlike organized Mesoscale Convective Systems (MCSs) that typically produce extensive trailing stratiform regions (e.g., [29,30]). Beyond ±40° latitude in both hemispheres, convective fractions drop sharply below 10%, stratiform fractions increase up to ~75%, and mixed-type fractions typically vary between 20 and 40%, with an average around 30%. It should be noted that the relatively coarse horizontal resolution (~15 km) used in this analysis may influence precipitation type classifications. Isolated convective systems, particularly those smaller than the pixel scale, may be classified as mixed rather than convective precipitation, contributing to the high global mixed precipitation fraction (47.6%) and potentially explaining the lower convective fractions compared to studies using finer spatial resolution (e.g., [30,31]). These distributions reveal a clear shift from convective/mixed dominance in lower latitudes to stratiform dominance in regions beyond 40° latitude (e.g., [30,32]). Interestingly, the most pronounced gradient in this transition typically occurs between 30 and 40° latitude even during summer months, when one might expect this transition zone to shift poleward due to increased solar heating. These latitudinal patterns demonstrate how latitude fundamentally influences precipitation regimes across the global oceans.

To analyze annual accumulated precipitation, GMI precipitation intensities (mm/h) were accumulated within 5° × 5° grids over five summer seasons and then divided by five to derive annual values. As previously explained, sampling frequency variations with latitude have been adjusted, ensuring uniform sampling coverage across all grid cells. Therefore, when applying a consistent time interval factor to these normalized samples, these accumulation values effectively represent the spatial distribution of annual accumulated precipitation during the study period. Figure 2 displays these annual accumulated precipitation values of GMI along with their differences from DPR observations (GMI minus DPR) for each hemisphere by precipitation type, providing a representation of the annual precipitation distribution. The GMI measurements effectively capture major precipitation features across all precipitation types, including high accumulated rainfall zones associated with the Inter-Tropical Convergence Zone (ITCZ) and Southern Pacific Convergence Zone (SPCZ) and enhanced precipitation bands along continental eastern seaboards (west of STHP systems). The measurements also clearly depict dry regions in and extending from STHP systems in both hemispheres. These observations are consistent with documented global precipitation patterns (e.g., [33,34,35]). The relatively small differences between GMI and DPR values (typically within 5–8% of the total precipitation amounts) indicate good agreement between the two observational systems in both spatial patterns and quantitative assessments. This consistency supports previous cross-validation studies (e.g., [18,36]).

More detailed examination reveals systematic differences between the two measurements across various precipitation types. For convective precipitation (Figure 2a,b), the GMI exhibits a characteristic behavior similar to what was documented by Seo et al. (2015) [25] in their comparison between the TRMM Microwave Imager (TMI) and Precipitation Radar (PR), where passive microwave sensors tend to overestimate precipitation at lower rain rates (<~1 mm/h) and underestimate at higher rain rates compared to radar measurements. In particular, the underestimation of the GMI at higher rain rates is primarily due to the scattering effects from large ice particles, the saturation effect in the TB-rain rate relationship at high intensities (e.g., [7,37]), the confusion between the surface and atmospheric signals [17], and limitations in the Bayesian approach used in retrieval algorithms [24]. This pattern is clearly reflected in the spatial distribution of GMI-DPR differences. Across most tropical and subtropical oceanic regions with intense convection, the GMI shows negative differences, indicating underestimation of high-intensity rainfall. Conversely, higher latitude regions (beyond approximately ±40°) show positive differences, reflecting the GMI’s tendency to overestimate lower rainfall intensities that are common in these areas. These positive differences also appear in Maritime Southeast Asia and Caribbean/Central American coastal regions despite these regions typically experiencing higher rainfall intensities. In these coastal and island regions, the proximity of landmasses is likely to influence the microwave signatures detected by the GMI. This influence leads to increased brightness temperatures in emission channels, which probably results in overestimation of precipitation, even in areas with substantial rainfall.

In contrast to convective precipitation, stratiform precipitation (Figure 2c,d) exhibits remarkably uniform positive differences (GMI > DPR) across almost all oceanic regions, without the latitude-dependent variation seen in convective precipitation. This widespread overestimation trend aligns with previous findings regarding passive microwave sensors’ tendency to overestimate stratiform precipitation (e.g., [24,25]). The overestimation is particularly pronounced in the tropical Pacific warm pool and the Bay of Bengal. Mixed precipitation exhibits similar difference patterns to stratiform precipitation (Figure 2e,f). In the overall analysis of all precipitation types, the GMI generally shows positive differences across most regions, indicating that the overestimation in stratiform and mixed precipitation outweighs the underestimation in convective precipitation (Figure 2g,h).

Figure 3 shows the relative contributions of precipitation types to annual accumulated precipitation for each measurement as shown in Figure 2. While spatial distributions generally align with occurrence fraction patterns (Figure 1), certain regions show distinct characteristics. In monsoon-influenced areas, along continental eastern seaboards, in the Gulf of Mexico, and in regions west of the Pacific STHP system, convective precipitation delivers approximately 40% of total precipitation despite less occurrence (typically ~20%) compared to other types (Figure 3a). This significant contribution reflects the high intensity of convective events in most of these regions except for areas near STHP. These regions share favorable environmental conditions: abundant moisture and warm ocean surfaces, particularly in areas away from STHP centers (e.g., [38]). The convective contribution progressively decreases poleward, accounting for less than 20% of total precipitation in most regions beyond 30° latitude in both hemispheres. The GMI-DPR differences show that the GMI generally underestimates convective contributions in tropical and subtropical regions (up to approximately 40°), while slight overestimation appears in limited areas of latitudes beyond 40° (Figure 3b).

In most of tropical and subtropical regions (below 40° N), stratiform precipitation accounts for approximately 50–70% of rainfall. Meanwhile, lower stratiform contribution (20–30%) is found mainly in the periphery of subtropical high pressure systems of the NH and in both the center and periphery of subtropical high pressure systems of the SH (Figure 3c). These findings are consistent with PR-based studies. Ref. [30] found that while stratiform precipitation covers 73% of the rain-affected areas in the tropics, it contributes only 40% of the total precipitation volume according to TRMM PR data. The spatial patterns in both studies show similarities in the central and eastern Pacific (50–60% stratiform fraction) but differ significantly in oceanic regions near continents. This GMI-DPR analysis shows higher stratiform fractions (50–70%) over the Maritime Continent region, and oceanic areas near Africa and South America compared to Schumacher and Houze’s results (20–40%). This discrepancy likely stems from differences in instrumentation (DPR vs. TRMM PR) and spatial resolution (~15 km vs. ~5 km), affecting precipitation classification particularly in these regions with complex precipitation systems.

In mid-latitudes (beyond 40°), stratiform precipitation becomes increasingly dominant, comprising up to ~85% of total precipitation in the NH and ~80% in the SH. This pattern reflects the prevalence of synoptic-scale systems and diminished convective potential at higher latitudes. Pfahl et al.’s (2014) [39] findings support this result, showing that warm conveyor belts (WCBs) within extratropical cyclones contribute substantially to precipitation in these regions, producing primarily stratiform rainfall. The GMI-DPR comparison shows that the GMI overestimates stratiform contributions below 40° while underestimating them in higher latitudes, with particularly larger negative differences in SH high latitudes (Figure 3d). Mixed precipitation is dominant in small, localized regions primarily in the southwestern United States near California and along the Argentine coast (contributing up to 85% of total precipitation) while remaining minimal (below 10%) throughout most other global regions (Figure 3e). The GMI-DPR differences show predominantly positive biases across most regions, indicating the GMI’s tendency to overestimate mixed precipitation contributions (Figure 3f).

Mean precipitation intensities (Figure 4) exhibit consistent spatial patterns of annual accumulated precipitation across precipitation types as shown in Figure 2. For convective precipitation, both the GMI and DPR show high intensities (>4 mm/h) over Asian monsoon regions, the Gulf of Mexico, and storm tracks and east continental coasts in both hemispheres (Figure 4a). The GMI-DPR difference reveals negative values (generally between −0.6 to −1.2 mm/h) throughout most oceanic regions globally, indicating the GMI systematically underestimates convective intensities (Figure 4b). Stratiform precipitation patterns show similar spatial distributions between retrievals, but with the GMI displaying higher values across most regions in both hemispheres (Figure 4c,d). Similar to stratiform precipitation, mixed precipitation also exhibits uniformly higher GMI values relative to DPR (Figure 4e,f). Thus, the contrasting GMI-DPR differences between convective (negative) and stratiform (positive) precipitation intensity is likely to offset each other to some degree when all types are combined. When examining overall patterns, mean precipitation intensity for all global oceanic rain is in the range of 0.24 to 2.40 mm/h, with higher values (>2 mm/h) primarily observed in the western Pacific, tropical convergence zones, and mid-latitude storm tracks, while lower values are seen in subtropical regions and beyond 40° (Figure 4g). The spatial pattern of GMI-DPR differences for combined precipitation types closely mirrors that of stratiform precipitation (Figure 4h). This indicates that the positive differences from stratiform and mixed precipitation components outweigh the GMI’s underestimation of convective precipitation intensity, resulting in a net positive difference when all types are combined. While similar compensating effects between precipitation types were observed in earlier TRMM TMI and PR comparisons [24], measurement differences for convective precipitation have significantly improved in current GMI-DPR observations. As for statistical significance of GMI-DPR differences, statistically significant differences (p < 0.001) are observed across all grid cells even for convective precipitation (the least frequent type).

3.2. Latitudinal Variations

The relative number of oceanic precipitation occurrences for all precipitation types, adjusted for GPM sampling frequency and averaged over five summer seasons, is calculated at each latitude, showing a distinct peak at ~7.5° N with sharp gradients (solid lines in Figure 5a). The prominent peak is partly attributed to the extensive oceanic surface area in this equatorial region. Meanwhile, this maximum also coincides with the ITCZ location, where converging trade winds and warm sea surface temperatures foster rain band development [40]. Beyond this peak, the frequency of convective precipitation decreases gradually poleward. In particular, non-convective precipitation types (stratiform and mixed) show a pronounced increase beyond 40° S in the SH, though this pattern is absent in the NH due to differences in ocean coverage between the hemispheres.

When normalized by ocean area at each latitude (dotted lines in Figure 5a), representing the number of occurrences per unit ocean area (100 km × 100 km), the tropical maximum at ~7.5° N remains distinct but appears less dominant compared to high-latitude values, while the frequency increases significantly poleward of 40° in both hemispheres for non-convective precipitation types. Notably, these high-latitude precipitation frequencies approach the magnitude of those observed at the ITCZ, revealing a secondary region of substantial precipitation driven by mid-latitude baroclinic systems and associated storm track activity [1,5].

The fractional contribution of each precipitation type to total precipitation occurrences (Figure 5b) reveals distinct latitudinal patterns that complement the occurrence distributions as shown in Figure 1. The convective type maintains ~20% up to ~30° latitude in both hemispheres before decreasing from mid-latitudes poleward. The stratiform type shows a local maximum near the ITCZ, slightly decreases up to ~20° latitude, then increases markedly to reach 50–60% from 40° poleward in both hemispheres. The mixed type fluctuates between 40% and 55% across the full latitudinal range. This distribution pattern highlights how precipitation mechanisms vary with latitude, with stratiform processes dominant at mid-latitudes. These results suggest a fundamental shift in precipitation processes, from tropical regions, where convective systems make a significant contribution alongside stratiform precipitation, to mid-latitude regions, where stratiform processes become increasingly dominant (e.g., [29,30]).

The mean summer precipitation intensity shows relatively symmetric patterns between hemispheres, with some asymmetry remaining only at higher latitudes for convective precipitation (Figure 5c). Convective precipitation shows the highest intensities, with maximum values occurring in the tropics (~3.4 mm/h in GMI, ~3.8 mm/h in DPR) and a secondary peak at ~40° latitude in both hemispheres. GMI measurements for convective precipitation are consistently 10–15% lower than DPR values across most latitudes. This mid-latitude maximum appears to be strongly associated with storm track activity along the eastern margins of continents in both hemispheres, as shown in Figure 4. These regions are characterized by enhanced baroclinic instability and frequent cyclone development. For stratiform precipitation, the GMI reports higher precipitation intensities than DPR, particularly in tropical regions (by approximately 15–25%). Interestingly, in the Southern Hemisphere around 30° S, GMI stratiform precipitation intensity actually exceeds that of convective precipitation. However, the difference between measurements becomes substantially smaller (typically 2–5%) at latitudes above 35°, indicating better measurement agreement away from the tropics. Mixed precipitation types generally remain below ~0.5 mm/h throughout all latitudes, showing the least variation across latitudinal bands.

The latitudinal distribution of total accumulated precipitation (Figure 5d) shows characteristic patterns that differ from the occurrence distributions (Figure 5a). Both GMI and DPR measurements reveal a tropical maximum near the ITCZ. For all precipitation types, the GMI consistently shows higher values than DPR across all latitudes, with the greatest differences appearing in tropical regions. Stratiform precipitation contributes the largest amount to total accumulated precipitation at each latitude, followed by convective and mixed types (Figure 5e). This dominant role of stratiform precipitation persists across all latitudes, though its relative importance increases poleward of 40°, where both convective and mixed precipitation become highly limited. The tropical regions exhibit higher accumulated precipitation in the NH than in the SH across all precipitation types, while mid-latitude regions show greater accumulation in the SH than in the NH, particularly in areas with extensive ocean coverage. Notably, the difference in total accumulation between the NH and SH at mid-latitudes has diminished significantly compared to the occurrence frequency distribution (Figure 5a), suggesting relatively lower rainfall intensity in the SH mid-latitudes, as confirmed by the mean precipitation intensity shown in Figure 5c.

Figure 5e presents the fractional contribution of each precipitation type to the total accumulation. Despite convective precipitation’s lower occurrence frequency, it contributes approximately 40% of the totals in tropical regions. At mid-latitudes, stratiform precipitation dominates, accounting for 60–90% of the totals. A significant transition occurs in both hemispheres, though at different latitude bands—between 30–45° N in the NH and between 30–40° S in the SH. During this transition, the convective fraction sharply decreases to a few percent, while the stratiform fraction increases substantially. GMI measurements indicate stratiform precipitation reaches approximately 80% around 50° N and 75% around 45° S, while DPR measurements show stratiform fractions approaching 90% in both hemispheres. The poleward shift of this transition zone in the NH compared to the SH is particularly noteworthy as it may reflect differences in continental configuration and associated circulation patterns.

When normalized by ocean area (100 × 100 km²) at each latitude (Figure 5f), the accumulated precipitation distribution effectively shows the relative precipitation production efficiency across different regions during the summer months. The tropical maximum remains prominent, with rainfall efficiency in the ITCZ region approximately three times higher than typical mid-latitude values. Unlike the total accumulated rainfall shown in Figure 5d, which shows gradual variations with latitude poleward of 30°, the normalized precipitation demonstrates a more distinct pattern: a pronounced maximum in the tropical region, followed by relatively uniform values extending to approximately 60° in both hemispheres. The normalized distribution also shows greater hemispheric symmetry compared to the non-normalized data in Figure 5d. This uniform precipitation efficiency across extratropical latitudes is maintained through a clear passing of the baton from convective to stratiform precipitation with increasing latitude.

3.3. Statistics of Rain Intensity

While previous sections examined the spatial distributions and geographical characteristics of precipitation parameters, this section presents a quantitative statistical analysis of five years of collocated GMI and DPR observations across global oceans, revealing their measurement characteristics for different precipitation types (

Table 1. Statistical comparison of precipitation intensity between GMI and DPR measurements for different precipitation types.

Precipitation Type	Convective	Stratiform	Mixed	All
mean/STD of GMI RR (mm/h)	2.77/5.42	1.84/2.74	0.44/0.56	1.27/2.61
mean/STD of DPR RR (mm/h)	3.18/8.42	1.63/3.32	0.21/0.42	1.12/3.57
RMSE(GMI-DPR)	5.65	2.24	0.60	2.35
mean difference (GMI-DPR) (mm/h)	−0.41	0.21	0.23	0.15
mean abs difference|GMI-DPR|(mm/h)	1.83	0.85	0.38	0.72
correlation	0.75	0.75	0.41	0.76
occurrence fraction (%)	10.4	42.0	47.6	100
total rainfall fraction for GMI (%)	22.7	60.8	16.5	100
total rainfall fraction for DPR (%)	29.6	61.4	9.0	100

). For convective precipitation, which accounts for 10.4% of occurrences but contributes 22.7% (GMI) to 29.6% (DPR) of total precipitation, the GMI systematically underestimates by 13.8% compared to DPR (2.77 mm/h vs. 3.18 mm/h). This underestimation appears in the global distribution maps as shown in Figure 4, with negative GMI-DPR differences concentrated in the eastern Pacific ITCZ and along the eastern coasts of mid-latitude continents in both hemispheres. The significantly higher standard deviations for convective precipitation (5.42 mm/h for the GMI versus 8.42 mm/h for DPR) and larger RMSE (5.65 mm/h) demonstrate that overall DPR has enhanced capability in measuring extreme precipitation events compared to stratiform and mixed precipitation.

Conversely, for stratiform precipitation, which represents 42.0% of occurrences and contributes 60.8% (GMI) to 61.4% (DPR) of total precipitation, the GMI shows overestimation (1.84 mm/h) compared to DPR (1.63 mm/h), with a difference of 12.1%. The standard deviations (2.74 mm/h for the GMI and 3.32 mm/h for DPR) and lower RMSE (2.24 mm/h) reflect the moderate characteristics compared to convective precipitation type. This overestimation pattern is clearly visible in the spatial distribution of GMI-DPR differences for stratiform precipitation as shown in Figure 4d, with positive values (yellow to red colors) spread widely across tropical, subtropical, and most mid-latitude areas. This overestimation can be attributed to fundamental detection characteristics of both instruments. Bringi et al. (2021) [41] demonstrated that in stratiform rain, where smaller drops predominate, the ratio of specific attenuation (k) to reflectivity (Z) increases. Since GMI (passive microwave) measurements are more sensitive to attenuation processes, while DPR (active radar) measures reflectivity, this physical relationship explains why the GMI is likely to retrieve higher rainfall rates than DPR in stratiform precipitation environments. This pattern aligns with observations by Turk et al. (2021) [42], who noted that the GMI and DPR offer complementary capabilities in precipitation detection, with the GMI potentially providing enhanced sensitivity to light precipitation that predominates in stratiform systems. According to Schumacher and Houze (2003) [30], who analyzed TRMM PR data (1998–2000) focused on tropical regions (20° N–20° S), stratiform precipitation accounts for 73% of rain-covered areas and 40% of total rainfall, with maximum fractions of ~60% in the eastern/central Pacific ITCZ. This current study, using GMI and DPR measurements with an additional mixed classification category and different spatial resolution, shows comparable stratiform rainfall contribution (~60%) in ITCZ regions while showing lower fractions in subtropical high-pressure regions. When considering the additional contribution from the mixed precipitation type, the combined fraction becomes similar to or even higher than the maximum stratiform fractions (~60%) reported by Schumacher and Houze (2003) [30]. Despite methodological differences, both studies confirm that tropical oceanic environments also efficiently produce stratiform precipitation through warm, moist boundary layers and near-moist adiabatic stratification.

Mixed precipitation types, while occurring most frequently (47.6%), show large differences in their contribution to total precipitation between the two instruments: 16.5% for the GMI and 9.0% for DPR. The large difference and the low correlation between GMI and DPR measurements (0.41) likely reflects uncertainties in detecting very light rain.

For all precipitation types combined, the GMI measures higher precipitation intensity than DPR (1.27 mm/h versus 1.12 mm/h, a difference of 12.6% relative to their mean value). The overall correlation coefficient of 0.76 represents the relationship between GMI and DPR measurements across precipitation types, indicating good general agreement. The mean absolute difference of 0.72 mm/h, however, is relatively large compared to the mean precipitation rates, suggesting that while the two measurements capture similar precipitation patterns, they often differ significantly in magnitude at specific locations. This systematic difference (12.6%) between the GMI and DPR is comparable with regional uncertainties found by Adler et al. (2012) [33], who analyzed differences between various satellite products across all seasons and surface types (land and ocean). Their comprehensive assessment underscores the importance of considering measurement uncertainty when interpreting precipitation patterns, particularly in higher-latitude oceanic regions.

4. Conclusions

This study has examined the characteristics of collocated GMI and DPR precipitation measurements through comprehensive analysis of five years of summer season observations. The analysis reveals several key findings regarding precipitation distribution characteristics observed by both instruments and systematic differences between these instruments.

Regarding precipitation distribution characteristics, first, both instruments show good agreement in capturing spatial patterns of global precipitation, consistently identifying major precipitation features such as the ITCZ, SPCZ, monsoon regions, and dry zones associated with subtropical high pressure systems. Second, a fundamental transition in precipitation characteristics primarily occurs between 30° and 40°, marking a shift from tropical to mid-latitude regimes. This boundary is characterized by a sharp decrease in convective contribution, while stratiform processes become predominant. Third, tropical regions (below ~30°) produce intense convective precipitation that contributes approximately 40% of total precipitation despite lower frequency, while latitudes beyond 30° show a progressive shift toward stratiform-dominated regimes, characterized by more frequent but less intense precipitation events that account for 60–90% of total precipitation in mid-latitudes. These mid-latitude regions produce significantly less precipitation volume per unit area compared to tropical regions. The tropical regions near the ITCZ generate approximately three times more precipitation per unit area, highlighting the exceptional efficiency of tropical convective systems. Fourth, unlike the surrounding tropical regions, the STHP regions (15–35° N/S) exhibit a distinctive precipitation regime, particularly in the eastern Pacific, where we observe relatively higher convective fractions with minimal stratiform precipitation but substantial mixed-type precipitation. This pattern suggests that precipitation in these thermodynamically stable and subsidence-dominated environments is likely to form as isolated convective systems rather than organized MCSs, which would normally produce extensive stratiform precipitation regions.

Regarding differences between instruments, first, systematic differences exist between these instruments that vary by precipitation type. The GMI underestimates convective precipitation intensity by 13.8% (2.77 mm/h vs. DPR’s 3.18 mm/h) but overestimates stratiform precipitation by 12.1% (1.84 mm/h vs. 1.63 mm/h). Mixed precipitation, occurring most frequently (47.6% of cases), shows the largest discrepancy in contribution to total precipitation between instruments (16.5% for the GMI vs. 9.0% for DPR), with the lowest correlation (0.41) between measurements. While convective precipitation represents only 10.4% of occurrences, it contributes 22.7% (GMI) to 29.6% (DPR) of total precipitation. In contrast, stratiform precipitation accounts for 42.0% of occurrences and contributes 60.8–61.4% of total precipitation, demonstrating its dominant role in the global water cycle, especially in mid-latitude regions. Second, these differences follow similar patterns to previous comparisons between the TMI and PR [25], though the magnitude of differences for convective precipitation has significantly decreased (from −62% to −13.8%), while the overall difference has increased (from 2.6% to 12.1%), reflecting remaining challenges in stratiform precipitation measurement. Third, the geographical variation of GMI-DPR differences shows a see-saw pattern across latitude bands with a transition around 30–40°: GMI-DPR differences exhibit opposite signs between tropical/subtropical and mid-latitude regions for the convective type while showing a reverse pattern for the stratiform precipitation type (Figure 2). These distinct geographical patterns ultimately stem from the combination of the precipitation type-dependent measurement characteristics of each instrument and latitudinal distribution of prevailing precipitation regimes.

This study provides important insights into systematic differences between active and passive microwave precipitation estimates and their implications for satellite-based retrievals. These dual-sensor observations help improve the quantification of uncertainty in precipitation retrievals. Moreover, the findings suggest that such differences likely propagate into merged products like IMERG, which rely heavily on passive microwave algorithms such as GPROF, highlighting the need for precipitation-type-specific parameterizations in retrieval frameworks. While this study focuses on summer seasons over oceanic regions, future work should explore other seasons, longer periods, and land surfaces to better understand the underlying physical causes of these differences.