Geer, A. J., Lonitz, K., Weston, P., Kazumori, M., Okamoto, K., Zhu, Y., Liu, E. H., Collard, A., Bell, W., Migliorini, S., and Chambon, P.: All-sky satellite data assimilation at
operational weather forecasting centres, Q. J. Roy. Meteor. Soc., 144, 1191–1217, https://doi.org/10.1002/qj.3202, 2018.
GOES-R Algorithm Working Group and GOES-R Program Office: NOAA GOES-R Series Advanced Baseline Imager (ABI) Level 2 Cloud Top Pressure (CTP), [Data in May, June, and July of 2020 are used], NOAA National Centers for Environmental Information [data set], https://doi.org/10.7289/V5D50K85, 2018.
GPM Science Team: GPM DPR and GMI Combined Convective Stratiform Heating L3 1 month 0.5 degree
× 0.5 degree V06, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Earth Data [data set], https://doi.org/10.5067/GPM/DPRGMI/CSH/3B-MONTH/06, 2017a.
GPM Science Team: GPM DPR and GMI Combined Stratiform Heating L2 1.5 hours 5 km V06, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), Earth Data [data set], https://doi.org/10.5067/GPM/DPRGMI/CSH/2H/06, 2017b.
GPM Science Team: GPM DPR Spectral Latent Heating Profiles L3 1 month 0.5 degree
× 0.5 degree V07, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/DPR/SLH/3A-MONTH/07, 2022.
Gustafsson, N., Janjić, T., Schraff, C., Leuenberger, D., Weissmann, M.,
Reich, H., Brousseau, P., Montmerle, T., Wattrelot, E., Bučánek, A.,
and Mile, M.: Survey of data assimilation methods for convective-scale
numerical weather prediction at operational centres, Q. J. Roy. Meteorol. Soc., 144, 1218–1256,
https://doi.org/10.1002/qj.3179, 2018.
Hilburn, K. A., Ebert-Uphoff, I., and Miller, S. D.: Development and
interpretation of a neural-network-based synthetic radar reflectivity
estimator using GOES-R satellite observations, J. Appl. Meteorol. Climatol., 60, 3–21, https://doi.org/10.1175/JAMC-D-20-0084.1, 2021.
Houze Jr., R. A.: Stratiform precipitation in regions of convection: A
meteorological paradox?, B. Am. Meteorol. Soc., 78, 2179–2196, https://doi.org/10.1175/1520-0477(1997)078<2179:SPIROC>2.0.CO;2, 1997.
Huaman, L. and Schumacher, C.: Assessing the vertical latent heating
structure of the East Pacific ITCZ using the CloudSat CPR and TRMM
PR, J. Climate, 31, 2563–2577, https://doi.org/10.1175/JCLI-D-17-0590.1,
2018.
Huaman, L. and Takahashi, K.: The vertical structure of the eastern Pacific
ITCZs and associated circulation using the TRMM Precipitation Radar and in
situ data, Geophys. Res. Lett., 43, 8230–8239, https://doi.org/10.1002/2016GL068835,
2016.
Johnson, R. H.: Partitioning tropical heat and moisture budgets into cumulus
and mesoscale components: Implications for cumulus
parameterization, Mon. Weather Rev., 112, 1590–1601, https://doi.org/10.1175/1520-0493(1984)112<1590:PTHAMB>2.0.CO;2, 1984.
Kummerow, C., Barnes, W., Kozu, T., Shiue, J., and Simpson, J.: The tropical
rainfall measuring mission (TRMM) sensor package, J. Atmos. Ocean. Technol., 15, 809–817, https://doi.org/10.1175/1520-0426(1998)015<0809:TTRMMT>2.0.CO;2, 1998.
Lee, Y., Kummerow, C. D., and Zupanski, M.: A simplified method for the detection of convection using high-resolution imagery from GOES-16, Atmos. Meas. Tech., 14, 3755–3771, https://doi.org/10.5194/amt-14-3755-2021, 2021.
LeMone, M. A. and Zipser, E. J.: Cumulonimbus vertical velocity events in
GATE. Part I: Diameter, intensity and mass flux, J. Atmos.
Sci., 37, 2444–2457,
https://doi.org/10.1175/1520-0469(1980)037<2444:CVVEIG>2.0.CO;2, 1980.
Levizzani, V., Kidd, C., Kirschbaum, D. B., Kummerow, C. D., Nakamura, K.,
and Turk, F. J: Satellite Precipitation Measurement, Vol. 1, Springer, 897–915, https://doi.org/10.1007/978-3-030-24568-9, 2020.
Liu, C., Shige, S., Takayabu, Y. N., and Zipser, E.: Latent heating
contribution from precipitation systems with different sizes, depths, and
intensities in the tropics, J. Climate, 28, 186–203, https://doi.org/10.1175/JCLI-D-14-00370.1, 2015.
Luo, Z. J., Jeyaratnam, J., Iwasaki, S., Takahashi, H., and Anderson, R.:
Convective vertical velocity and cloud internal vertical structure: An
A-Train perspective, Geophys. Res. Lett., 41, 723–729, https://doi.org/10.1002/2013GL058922, 2014.
Nelson, E. L., L'Ecuyer, T. S., Saleeby, S. M., Berg, W., Herbener, S. R., and
Van Den Heever, S. C.: Toward an algorithm for estimating latent heat release
in warm rain systems, J. Atmos. Ocean. Technol., 33, 1309–1329, https://doi.org/10.1175/JTECH-D-15-0205.1, 2016.
Nelson, E. L. and L'Ecuyer, T. S.: Global character of latent heat release in
oceanic warm rain systems, J. Geophys. Res.-Atmos., 123, 4797–4817, https://doi.org/10.1002/2017JD027844, 2018.
Peckham, S. E., Smirnova, T. G., Benjamin, S. G., Brown, J. M., and Kenyon, J. S.:
Implementation of a digital filter initialization in the WRF Model and its
application in the Rapid Refresh, Mon. Weather Rev., 144, 99–106, https://doi.org/10.1175/MWR-D-15-0219.1, 2016.
Roberts, N. M. and Lean, H. W.: Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events, Mon. Weather Rev., 136, 78–97, 2008.
Satoh, S., Noda, A., and Iguchi, T.: Retrieval of latent heating profiles
from TRMM radar data, in: Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Am. Meteorol. Soc, Vol. 6,
https://ams.confex.com/ams/30radar/techprogram/paper_21763.htm, last access: 21 July 2001.
Schumacher, C., Houze Jr., R. A., and Kraucunas, I.: The tropical dynamical
response to latent heating estimates derived from the TRMM precipitation
radar, J. Atmos. Sci., 61, 1341–1358, https://doi.org/10.1175/1520-0469(2004)061<1341:TTDRTL>2.0.CO;2, 2004.
Shige, S., Takayabu, Y. N., Tao, W. K., and Johnson, D. E.: Spectral retrieval
of latent heating profiles from TRMM PR data. Part I: Development of a
model-based algorithm, J. Appl. Meteorol., 43, 1095–1113, https://doi.org/10.1175/1520-0450(2004)043<1095:SROLHP>2.0.CO;2, 2004.
Shige, S., Takayabu, Y. N., Tao, W. K., and Shie, C. L.: Spectral retrieval of
latent heating profiles from TRMM PR data. Part II: Algorithm improvement
and heating estimates over tropical ocean regions, J. Appl. Meteorol. Climatol., 46, 1098–1124,
https://doi.org/10.1175/JAM2510.1, 2007.
Steiner, M., Houze Jr., R. A., and Yuter, S. E.: Climatological characterization
of three-dimensional storm structure from operational radar and rain gauge
data, J. Appl. Meteorol. Climatol., 34, 1978–2007, https://doi.org/10.1175/1520-0450(1995)034<1978:CCOTDS>2.0.CO;2, 1995.
Tao, W. K., Lang, S., Simpson, J., and Adler, R.: Retrieval Algorithms for
Estimating the Vertical Profiles of Latent Heat Release Their Applications
for TRMM, J. Meteorol. Soc. Jap. Ser. II, 71, 685–700, https://doi.org/10.2151/jmsj1965.71.6_685, 1993.
Tao, W. K., Smith, E. A., Adler, R. F., Haddad, Z. S., Hou, A. Y., Iguchi, T.,
Kakar, R., Krishnamurti, T. N., Kummerow, C. D., Lang, S., and Meneghini, R.:
Retrieval of latent heating from TRMM measurements, B. Am. Meteorol. Soc., 87, 1555–1572,
https://doi.org/10.1175/BAMS-87-11-1555, 2006.
Tao, W. K., Takayabu, Y. N., Lang, S., Shige, S., Olson, W., Hou, A.,
Skofronick-Jackson, G., Jiang, X., Zhang, C., Lau, W., and Krishnamurti, T.:
TRMM latent heating retrieval: Applications and comparisons with field
campaigns and large-scale analyses, Meteorol. Monogr., 56, 2.1–2.34, https://doi.org/10.1175/AMSMONOGRAPHS-D-15-0013.1, 2016.
Tao, W. K., Iguchi, T., and Lang, S.: Expanding the Goddard CSH algorithm for
GPM: New extratropical retrievals, J. Appl. Meteorol. Climatol., 58, 921–946, https://doi.org/10.1175/JAMC-D-18-0215.1, 2019.
Weygandt, S. S. and Benjamin, S.: Radar reflectivity-based initialization of
precipitation systems using a diabatic digital filter within the Rapid
Update Cycle, 22nd Conf. on Weather Analysis and Forecasting/18th
Conf. on Numerical Weather Prediction, Park City, Am. Meteor Soc., 1B.7.
26 June 2007.
Wu, J., Del Genio, A. D., Yao, M. S., and Wolf, A. B.: WRF and GISS SCM
simulations of convective updraft properties during TWP-ICE, J. Geophys. Res.-Atmos., 114, D4,
https://doi.org/10.1029/2008JD010851, 2009.
Xu, K. M. and Randall, D. A.: Updraft and downdraft statistics of simulated
tropical and midlatitude cumulus convection, J. Atmos. Sci. 58, 1630–1649, https://doi.org/10.1175/1520-0469(2001)058<1630:UADSOS>2.0.CO;2, 2001.
Yanai, M., Esbensen, S., and Chu, J. H.: Determination of bulk properties of
tropical cloud clusters from large-scale heat and moisture budgets, J. Atmos. Sci., 30,
611–627, https://doi.org/10.1175/1520-0469(1973)030<0611:DOBPOT>2.0.CO;2, 1973.
Yang, S. and Smith, E. A.: Moisture budget analysis of TOGA COARE area using
SSM/I-retrieved latent heating and large-scale Q 2 estimates, J. Atmos. Ocean. Technol., 16,
633–655, https://doi.org/10.1175/1520-0426(1999)016<0633:MBAOTC>2.0.CO;2, 1999.
Zhang, C., Ling, J., Hagos, S., Tao, W. K., Lang, S., Takayabu, Y. N., Shige,
S., Katsumata, M., Olson, W. S., and L'Ecuyer, T.: MJO signals in latent
heating: Results from TRMM retrievals, J. Atmos. Sci., 67, 3488–3508, https://doi.org/10.1175/2010JAS3398.1, 2010.
Zipser, E. J. and Lutz, K. R.: The vertical profile of radar reflectivity of
convective cells: A strong indicator of storm intensity and lightning
probability?, Mon. Weather Rev., 122, 1751–1759, https://doi.org/10.1175/1520-0493(1994)122<1751:TVPORR>2.0.CO;2, 1994.
