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Improvements of Rain/No-Rain Classification Methods for Microwave Radiometer over Coasts by Dynamic Surface-Type ClassificationAbstract
The rain/no-rain classification for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) fails to detect rain over coasts, where the microwave footprint encompasses a mixture of radiometrically cold ocean and radiometrically warm land. A static land–ocean–coast mask is used to determine the surface type of each satellite footprint. The coast mask is conservatively wide to account for the largest footprints, preventing use of the more appropriate ocean or land algorithm for coastal regions.
The purpose of this paper is to develop a classification whereby the smallest region possible is defined as coast. In this endeavor, two major improvements are applied to the land–ocean–coast classification. First, the surface classification based on microwave footprints of the high frequency actually used in rain detection is employed. Second, the footprint area of the surface classification is established using an effective field-of-view size and scan geometry of the TMI. These improvements are applied to the Global Satellite Mapping of Precipitation TMI algorithm. The classification result is validated using the TRMM precipitation radar. The validation shows that these improvements lead to better rain detection in the coastal region.
Abstract
The rain/no-rain classification for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) fails to detect rain over coasts, where the microwave footprint encompasses a mixture of radiometrically cold ocean and radiometrically warm land. A static land–ocean–coast mask is used to determine the surface type of each satellite footprint. The coast mask is conservatively wide to account for the largest footprints, preventing use of the more appropriate ocean or land algorithm for coastal regions.
The purpose of this paper is to develop a classification whereby the smallest region possible is defined as coast. In this endeavor, two major improvements are applied to the land–ocean–coast classification. First, the surface classification based on microwave footprints of the high frequency actually used in rain detection is employed. Second, the footprint area of the surface classification is established using an effective field-of-view size and scan geometry of the TMI. These improvements are applied to the Global Satellite Mapping of Precipitation TMI algorithm. The classification result is validated using the TRMM precipitation radar. The validation shows that these improvements lead to better rain detection in the coastal region.
Abstract
Mechanisms responsible for westward generation of eastward-moving tropical convective bands in the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) are investigated using a two-dimensional numerical cloud model. Sequential generation of new convective bands to the west of an old eastward-moving convective band is successfully simulated in an environment of a convectively active day during TOGA COARE, characterized by west winds at low levels and strong easterlies aloft.
It is concluded that the westward generation of new convective bands is explained by a gravity wave mechanism. Two westward-propagating modes excited below the convective cells moving westward relative to the convective bands appear to play an important role. A slow-propagating mode (∼15 m s−1) excited by a shallow convective band is ducted in the troposphere under an unstable layer of small Richardson number containing its critical level. A fast-propagating mode (∼25 m s−1) excited by a deep convective band is ducted in the troposphere under the remaining region of the convective cell containing its critical level. These two modes propagate horizontally to the west and promote the growth of shallow convection into long-lived convective bands. A dry model with thermal forcing representing the convective cell showed that preferential excitation of westward-propagating waves below the convective cell is due to westward motion and ascension of the convective cell. A comparative simulation without the critical level confirms the proposed gravity wave mechanism.
Abstract
Mechanisms responsible for westward generation of eastward-moving tropical convective bands in the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) are investigated using a two-dimensional numerical cloud model. Sequential generation of new convective bands to the west of an old eastward-moving convective band is successfully simulated in an environment of a convectively active day during TOGA COARE, characterized by west winds at low levels and strong easterlies aloft.
It is concluded that the westward generation of new convective bands is explained by a gravity wave mechanism. Two westward-propagating modes excited below the convective cells moving westward relative to the convective bands appear to play an important role. A slow-propagating mode (∼15 m s−1) excited by a shallow convective band is ducted in the troposphere under an unstable layer of small Richardson number containing its critical level. A fast-propagating mode (∼25 m s−1) excited by a deep convective band is ducted in the troposphere under the remaining region of the convective cell containing its critical level. These two modes propagate horizontally to the west and promote the growth of shallow convection into long-lived convective bands. A dry model with thermal forcing representing the convective cell showed that preferential excitation of westward-propagating waves below the convective cell is due to westward motion and ascension of the convective cell. A comparative simulation without the critical level confirms the proposed gravity wave mechanism.
Abstract
To understand how coastal precipitation is controlled by the low-level background wind, we performed comprehensive analysis using the 17-yr observations of the TRMM PR over the entire region of the tropics. We classified the data according to the direction (onshore or offshore) and strength of the cross-shore wind. Under weak winds, the contribution of the diurnal cycle to total precipitation is large, indicating that thermally forced precipitation with a symmetrical propagation pattern with opposite sign across the coastline is dominant. As the background wind strengthens, the contribution of the diurnal cycle reduces owing to the predominance of mechanical forcing; however, the effect of the diurnal cycle remains nonnegligible with an asymmetrical propagation pattern across the coastline. Using the linear theory of the sea–land-breeze circulation, we demonstrated that the difference in propagation is attributable to gravity waves excited by the land–ocean surface heating difference. Under weak winds, symmetrical diurnal phase propagation is caused by the two symmetrical modes of landward and seaward gravity waves. Under stronger background winds, in addition to the Doppler-shifted landward and seaward modes, waves propagating toward the upwind side in the flow-relative frame but with slow group velocity are advected to the downwind near the coastline, forming another mode that moves slowly in the downwind direction. The superposition of the three modes leads to asymmetrical propagation of precipitation with varying phase speed depending on the distance from the coastline.
Abstract
To understand how coastal precipitation is controlled by the low-level background wind, we performed comprehensive analysis using the 17-yr observations of the TRMM PR over the entire region of the tropics. We classified the data according to the direction (onshore or offshore) and strength of the cross-shore wind. Under weak winds, the contribution of the diurnal cycle to total precipitation is large, indicating that thermally forced precipitation with a symmetrical propagation pattern with opposite sign across the coastline is dominant. As the background wind strengthens, the contribution of the diurnal cycle reduces owing to the predominance of mechanical forcing; however, the effect of the diurnal cycle remains nonnegligible with an asymmetrical propagation pattern across the coastline. Using the linear theory of the sea–land-breeze circulation, we demonstrated that the difference in propagation is attributable to gravity waves excited by the land–ocean surface heating difference. Under weak winds, symmetrical diurnal phase propagation is caused by the two symmetrical modes of landward and seaward gravity waves. Under stronger background winds, in addition to the Doppler-shifted landward and seaward modes, waves propagating toward the upwind side in the flow-relative frame but with slow group velocity are advected to the downwind near the coastline, forming another mode that moves slowly in the downwind direction. The superposition of the three modes leads to asymmetrical propagation of precipitation with varying phase speed depending on the distance from the coastline.
Abstract
Over coastal mountain ranges of the Asian monsoon region, heavy orographic rainfall is frequently associated with low precipitation-top heights (PTHs). This leads to conspicuous underestimation of rainfall using microwave radiometer algorithms, which conventionally assume that heavy rainfall is associated with high PTHs. Although topographically forced upward motion is important for rainfall occurrence, it does not fully constrain precipitation profiles in this region. This paper focuses on the thermodynamic characteristics of the atmosphere that determine PTHs in tropical coastal mountains of Asia (Western Ghats, Arakan Yoma, Bilauktaung, Cardamom, Annam Range, and the Philippines).
PTHs of heavy orographic rainfall generally decrease with enhanced low- and midlevel relative humidity, especially during the summer monsoon. In contrast, PTHs over the Annam Range of the Indochina Peninsula increase with enhanced low-level and midlevel relative humidity during the transition from boreal summer to winter monsoon, demonstrating that convection depth is not simply a function of humidity. Instead, PTHs of heavy orographic rainfall decreased with increasing low-level stability for all monsoon regions considered in this study, as well as the Annam Range during the transition from boreal summer to winter monsoon. Therefore, low-level static stability, which inhibits cloud growth and promotes cloud detrainment, appears to be the most important parameter in determining PTHs of heavy rainfall in the Asian monsoon region.
Abstract
Over coastal mountain ranges of the Asian monsoon region, heavy orographic rainfall is frequently associated with low precipitation-top heights (PTHs). This leads to conspicuous underestimation of rainfall using microwave radiometer algorithms, which conventionally assume that heavy rainfall is associated with high PTHs. Although topographically forced upward motion is important for rainfall occurrence, it does not fully constrain precipitation profiles in this region. This paper focuses on the thermodynamic characteristics of the atmosphere that determine PTHs in tropical coastal mountains of Asia (Western Ghats, Arakan Yoma, Bilauktaung, Cardamom, Annam Range, and the Philippines).
PTHs of heavy orographic rainfall generally decrease with enhanced low- and midlevel relative humidity, especially during the summer monsoon. In contrast, PTHs over the Annam Range of the Indochina Peninsula increase with enhanced low-level and midlevel relative humidity during the transition from boreal summer to winter monsoon, demonstrating that convection depth is not simply a function of humidity. Instead, PTHs of heavy orographic rainfall decreased with increasing low-level stability for all monsoon regions considered in this study, as well as the Annam Range during the transition from boreal summer to winter monsoon. Therefore, low-level static stability, which inhibits cloud growth and promotes cloud detrainment, appears to be the most important parameter in determining PTHs of heavy rainfall in the Asian monsoon region.
Abstract
Rainfall over the coastal regions of western India [Western Ghats (WG)] and Myanmar [Arakan Yoma (AY)], two regions experiencing the heaviest rainfall during the Asian summer monsoon, is examined using a Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) dataset spanning 16 years. Rainfall maxima are identified on the upslope of the WG and the coastline of AY, in contrast to the offshore locations observed in previous studies. Continuous rain with slight nocturnal and afternoon–evening maxima occurs over the upslope of the WG, while an afternoon peak over the upslope and a morning peak just off the coast are found in AY, resulting in different locations of the rainfall maxima for the WG (upslope) and AY (coastline). Large rainfall amounts with small diurnal amplitudes are observed over the WG and AY under strong environmental flow perpendicular to the coastal mountains, and vice versa. Composite analysis of the boreal summer intraseasonal oscillation (BSISO) shows that the rain anomaly over the WG slopes lags behind the northward-propagating major rainband. The cyclonic systems associated with the BSISO introduces a southwest wind anomaly behind the major rainband, enhancing the orographic rainfall over the WG, and resulting in the phase lag. This lag is not observed in the AY region where more closed cyclonic circulations occur. Diurnal variations in rainfall over the WG regions are smallest during the strongest BSISO rainfall anomaly phase.
Abstract
Rainfall over the coastal regions of western India [Western Ghats (WG)] and Myanmar [Arakan Yoma (AY)], two regions experiencing the heaviest rainfall during the Asian summer monsoon, is examined using a Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) dataset spanning 16 years. Rainfall maxima are identified on the upslope of the WG and the coastline of AY, in contrast to the offshore locations observed in previous studies. Continuous rain with slight nocturnal and afternoon–evening maxima occurs over the upslope of the WG, while an afternoon peak over the upslope and a morning peak just off the coast are found in AY, resulting in different locations of the rainfall maxima for the WG (upslope) and AY (coastline). Large rainfall amounts with small diurnal amplitudes are observed over the WG and AY under strong environmental flow perpendicular to the coastal mountains, and vice versa. Composite analysis of the boreal summer intraseasonal oscillation (BSISO) shows that the rain anomaly over the WG slopes lags behind the northward-propagating major rainband. The cyclonic systems associated with the BSISO introduces a southwest wind anomaly behind the major rainband, enhancing the orographic rainfall over the WG, and resulting in the phase lag. This lag is not observed in the AY region where more closed cyclonic circulations occur. Diurnal variations in rainfall over the WG regions are smallest during the strongest BSISO rainfall anomaly phase.
Abstract
The spectral latent heating (SLH) algorithm was developed to estimate apparent heat source (Q 1) profiles for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Parts I and II of this study. In this paper, the SLH algorithm is used to estimate apparent moisture sink (Q 2) profiles. The procedure of Q 2 retrieval is the same as that of heating retrieval except for using the Q 2 profile lookup tables derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) utilizing a cloud-resolving model (CRM). The Q 2 profiles were reconstructed from CRM-simulated parameters with the COARE table and then compared with CRM-simulated “true” Q 2 profiles, which were computed directly from the water vapor equation in the model. The consistency check indicates that discrepancies between the SLH-reconstructed and CRM-simulated profiles for Q 2, especially at low levels, are larger than those for Q 1 and are attributable to moistening for the nonprecipitating region that SLH cannot reconstruct. Nevertheless, the SLH-reconstructed total Q 2 profiles are in good agreement with the CRM-simulated ones. The SLH algorithm was applied to PR data, and the results were compared with Q 2 profiles derived from the budget study. Although discrepancies between the SLH-retrieved and sounding-based profiles for Q 2 for the South China Sea Monsoon Experiment (SCSMEX) are larger than those for heating, key features of the vertical profiles agree well. The SLH algorithm can also estimate differences of Q 2 between the western Pacific Ocean and the Atlantic Ocean, consistent with the results from the budget study.
Abstract
The spectral latent heating (SLH) algorithm was developed to estimate apparent heat source (Q 1) profiles for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) in Parts I and II of this study. In this paper, the SLH algorithm is used to estimate apparent moisture sink (Q 2) profiles. The procedure of Q 2 retrieval is the same as that of heating retrieval except for using the Q 2 profile lookup tables derived from numerical simulations of tropical cloud systems from the Tropical Ocean and Global Atmosphere (TOGA) Coupled Ocean–Atmosphere Response Experiment (COARE) utilizing a cloud-resolving model (CRM). The Q 2 profiles were reconstructed from CRM-simulated parameters with the COARE table and then compared with CRM-simulated “true” Q 2 profiles, which were computed directly from the water vapor equation in the model. The consistency check indicates that discrepancies between the SLH-reconstructed and CRM-simulated profiles for Q 2, especially at low levels, are larger than those for Q 1 and are attributable to moistening for the nonprecipitating region that SLH cannot reconstruct. Nevertheless, the SLH-reconstructed total Q 2 profiles are in good agreement with the CRM-simulated ones. The SLH algorithm was applied to PR data, and the results were compared with Q 2 profiles derived from the budget study. Although discrepancies between the SLH-retrieved and sounding-based profiles for Q 2 for the South China Sea Monsoon Experiment (SCSMEX) are larger than those for heating, key features of the vertical profiles agree well. The SLH algorithm can also estimate differences of Q 2 between the western Pacific Ocean and the Atlantic Ocean, consistent with the results from the budget study.
Abstract
Latent heating (LH) from precipitation systems with different sizes, depths, and convective intensities is quantified with 15 years of LH retrievals from version 7 Precipitation Radar (PR) products of the Tropical Rainfall Measuring Mission (TRMM). Organized precipitation systems, such as mesoscale convective systems (MCSs; precipitation area > 2000 km2), contribute to 88% of the LH above 7 km over tropical land and 95% over tropical oceans. LH over tropical land is mainly from convective precipitation, and has one vertical mode with a peak from 4 to 7 km. There are two vertical modes of LH over tropical oceans. The shallow mode from about 1 to 4 km results from small, shallow, and weak precipitation systems, and partially from congestus clouds with radar echo top between 5 and 8 km. The deep mode from 5 to 9 km is mainly from stratiform precipitation in MCSs.
MCSs of different regions and seasons have different LH vertical structure mainly due to the different proportion of stratiform precipitation. MCSs over ocean have a larger fraction of stratiform precipitation and a top-heavy LH structure. MCSs over land have a higher percentage of convective versus stratiform precipitation, which results in a relatively lower-level peak in LH compared to MCSs over the ocean. MCSs during monsoons have properties of LH in between those typical land and oceanic MCSs.
Consistent with the diurnal variation of precipitation, tropical land has a stronger LH diurnal variation than tropical oceans with peak LH in the late afternoon. Over tropical oceans in the early morning, the shallow mode of LH peaks slightly earlier than the deep mode. There are almost no diurnal changes of MCSs LH over oceans. However, the small convective systems over land contribute a significant amount of LH at all vertical levels in the afternoon, when the contribution of MCSs is small.
Abstract
Latent heating (LH) from precipitation systems with different sizes, depths, and convective intensities is quantified with 15 years of LH retrievals from version 7 Precipitation Radar (PR) products of the Tropical Rainfall Measuring Mission (TRMM). Organized precipitation systems, such as mesoscale convective systems (MCSs; precipitation area > 2000 km2), contribute to 88% of the LH above 7 km over tropical land and 95% over tropical oceans. LH over tropical land is mainly from convective precipitation, and has one vertical mode with a peak from 4 to 7 km. There are two vertical modes of LH over tropical oceans. The shallow mode from about 1 to 4 km results from small, shallow, and weak precipitation systems, and partially from congestus clouds with radar echo top between 5 and 8 km. The deep mode from 5 to 9 km is mainly from stratiform precipitation in MCSs.
MCSs of different regions and seasons have different LH vertical structure mainly due to the different proportion of stratiform precipitation. MCSs over ocean have a larger fraction of stratiform precipitation and a top-heavy LH structure. MCSs over land have a higher percentage of convective versus stratiform precipitation, which results in a relatively lower-level peak in LH compared to MCSs over the ocean. MCSs during monsoons have properties of LH in between those typical land and oceanic MCSs.
Consistent with the diurnal variation of precipitation, tropical land has a stronger LH diurnal variation than tropical oceans with peak LH in the late afternoon. Over tropical oceans in the early morning, the shallow mode of LH peaks slightly earlier than the deep mode. There are almost no diurnal changes of MCSs LH over oceans. However, the small convective systems over land contribute a significant amount of LH at all vertical levels in the afternoon, when the contribution of MCSs is small.
Abstract
The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate–high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.5° horizontal resolution, the occurrence of conditional rain rates over 100 mm day−1 is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations.
An improved convective–stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.
Abstract
The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate–high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.5° horizontal resolution, the occurrence of conditional rain rates over 100 mm day−1 is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations.
An improved convective–stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.
Abstract
Three-dimensional distributions of the apparent heat source (Q 1) − radiative heating (QR ) estimated from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) utilizing the spectral latent heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated Q 1 − QR averaged over the tropical oceans is estimated as ∼72.6 J s−1 (∼2.51 mm day−1) and that over tropical land is ∼73.7 J s−1 (∼2.55 mm day−1) for 30°N–30°S. It is shown that nondrizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems: deep systems and congestus. A rough estimate of the shallow-heating contribution against the total heating is about 46.7% for the average tropical oceans, which is substantially larger than the 23.7% over tropical land.
Although cumulus congestus heating linearly correlates with SST, deep-mode heating is dynamically bounded by large-scale subsidence. It is notable that a substantial amount of rain, as large as 2.38 mm day−1 on average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that, even in the region with SSTs warmer than 28°C, large-scale subsidence effectively suppresses the deep convection, with the remaining heating by congestus clouds.
The results support that the entrainment of mid–lower-tropospheric dry air, which accompanies the large-scale subsidence, is the major factor suppressing the deep convection. Therefore, a representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and the resultant large-scale circulation.
Abstract
Three-dimensional distributions of the apparent heat source (Q 1) − radiative heating (QR ) estimated from Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) utilizing the spectral latent heating (SLH) algorithm are analyzed. Mass-weighted and vertically integrated Q 1 − QR averaged over the tropical oceans is estimated as ∼72.6 J s−1 (∼2.51 mm day−1) and that over tropical land is ∼73.7 J s−1 (∼2.55 mm day−1) for 30°N–30°S. It is shown that nondrizzle precipitation over tropical and subtropical oceans consists of two dominant modes of rainfall systems: deep systems and congestus. A rough estimate of the shallow-heating contribution against the total heating is about 46.7% for the average tropical oceans, which is substantially larger than the 23.7% over tropical land.
Although cumulus congestus heating linearly correlates with SST, deep-mode heating is dynamically bounded by large-scale subsidence. It is notable that a substantial amount of rain, as large as 2.38 mm day−1 on average, is brought from congestus clouds under the large-scale subsiding circulation. It is also notable that, even in the region with SSTs warmer than 28°C, large-scale subsidence effectively suppresses the deep convection, with the remaining heating by congestus clouds.
The results support that the entrainment of mid–lower-tropospheric dry air, which accompanies the large-scale subsidence, is the major factor suppressing the deep convection. Therefore, a representation of the realistic entrainment is very important for proper reproduction of precipitation distribution and the resultant large-scale circulation.
Abstract
Heavy rainfall associated with shallow orographic rainfall systems has been underestimated by passive microwave radiometer algorithms owing to weak ice scattering signatures. The authors improve the performance of estimates made using a passive microwave radiometer algorithm, the Global Satellite Mapping of Precipitation (GSMaP) algorithm, from data obtained by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) for orographic heavy rainfall. An orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. Rainfall estimates made using the revised GSMaP algorithm are in better agreement with estimates from data obtained by the radar on the TRMM satellite and by gauge-calibrated ground radars than are estimates made using the original GSMaP algorithm.
Abstract
Heavy rainfall associated with shallow orographic rainfall systems has been underestimated by passive microwave radiometer algorithms owing to weak ice scattering signatures. The authors improve the performance of estimates made using a passive microwave radiometer algorithm, the Global Satellite Mapping of Precipitation (GSMaP) algorithm, from data obtained by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) for orographic heavy rainfall. An orographic/nonorographic rainfall classification scheme is developed on the basis of orographically forced upward vertical motion and the convergence of surface moisture flux estimated from ancillary data. Lookup tables derived from orographic precipitation profiles are used to estimate rainfall for an orographic rainfall pixel, whereas those derived from original precipitation profiles are used to estimate rainfall for a nonorographic rainfall pixel. Rainfall estimates made using the revised GSMaP algorithm are in better agreement with estimates from data obtained by the radar on the TRMM satellite and by gauge-calibrated ground radars than are estimates made using the original GSMaP algorithm.
