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Conference paper titled, Comparing microclimate weather conditions from the weather research and forecasting (WRF) model with typical meteorological year (TMY) data for building energy simulations accepted for Building Simulation 2025 Conference in Brisbane, Australia in Aug 2025.
We evaluated the performance of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) at-launch algorithm for monthly oceanic rain rate using two years (January 1998 - December 1999) of TMI data. The TMI at-launch algorithm is based on Wilheit et al.'s technique for estimating monthly oceanic rainfall that relies on histograms of multichannel microwave measurements. Comparisons with oceanic monthly rain rates derived from the Defense Meteorological Satellite Program (DMSP) F-13 and F-14 Special Sensor Microwave Imager (SSM/I) data show the average rain rates over the TRMM region (between 400S and 40N) are 3.0, 2.85 and 2.89 mm/day, respectively for F-13, F-14 and TMI. Based on the latest version of TB data (version 5), both rainrate and freezing height derived from TMI are similar to those from the F-13 and F-14 SSM/I data. However, regionally the differences are statistically significant at the 95% confidence. Three hourly monthly rainrates are also computed from 3-hourly TB histograms to examine the diurnal cycle of precipitation. Over most of the oceanic TRMM area, a distinct early morning rainfall peak is found. A harmonic analysis shows that the amplitude of the 12h harmonic is significant and comparable to that of the 24h harmonic.
A multi-layered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and TRMM Microwave Imager (TMI) measurements from the Tropical Rainfall Measuring Mission spacecraft between January and August 1998. Lookup tables of top-of-atmosphere 0.65- m reflectance are developed for ice-over-water cloud systems using radiative transfer calculations with various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible Infrared Solar-infrared Split-window Technique (VISST), which matches the VIRS IR, 3.9- m, and VIS data to the multilayer-cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42% and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values, and exceed those of single-layered layered clouds by 7% and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites and the standard deviations of the differences are similar to those for single-layered clouds. Examples of a method for applying the MCRS over land without microwave data yield similar differences with the surface retrievals. By combining the MCRS with other techniques that focus primarily on optically thin cirrus over low water clouds, it will be possible to more fully assess the IWP in all conditions over ocean except for precipitating systems.
This study attempts to apprise stakeholders about the accurate use of a typical meteorological year (TMY) data set for decision-making that could potentially speed up the acceptance and deployment of projects and reduce risks to financiers and developers. A TMY data set represents hourly concatenation of 12 typical meteorological months constructed using multiyear data sets. Typically, TMY data sets are constructed under horizonal irradiance conditions that are then used in photovoltaic (PV) performance models for available energy calculations in a location after transposing the data to represent a desired plane-of-array (POA) orientation. In this study, we attempt to show that a POA TMY generated with corresponding POA irradiance time-series information produces significantly different results than a POA TMY generated by transposing a TMY data set. In some months, the differences can be more than 3% for irradiance and energy yield. These results point to the need for generating TMY data sets using POA irradiance time series representing the orientation at which PV panels will be deployed.
Sensitivity studies are performed on the assimilation of TRMM (Tropical Rainfall Measurement Mission) Microwave Imager (TMI) derived rainfall data into a mesoscale model using a four-dimensional variational data assimilation (4DVAR) technique. A series of numerical experiments is conducted to evaluate the impact of TMI rainfall data on the numerical simulation of Hurricane Bonnie (1998). The results indicate that rainfall data assimilation is sensitive to the error characteristics of the data and the inclusion of physics in the adjoint and forward models. In addition, assimilating the rainfall data alone is helpful for producing a more realistic eye and rain bands in the hurricane but does not ensure improvements in hurricane intensity forecasts. Further study indicated that it is necessary to incorporate TMI rainfall data together with other types of data such as wind data into the model, in which case the inclusion of the rainfall data further improves the intensity forecast of the hurricane. This implies that proper constraints may be needed for rainfall assimilation.
The Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) observed the Earth in lower latitudes between 1997 - 2015. Its conical-scan radiometer has nine channels and measured microwave radiances between 10 and 89 GHz. These data provide information on atmospheric temperature, humidity, clouds, precipitation, as well as sea surface temperature. Radiance data from other microwave radiometers such as Special Sensor Microwave Imager (SSM/I) and Special Sensor Microwave Imager Sounder (SSMIS) onboard various Defense Meteorological Satellite Program (DMSP) satellites are assimilated in clear-sky conditions in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and its version 2 (MERRA-2) data sets at the Global Modeling and Assimilation Office (GMAO) at NASA Goddard Space Flight Center. The GMAO's Hybrid 4D-EnVar-based Atmospheric Data Assimilation System (ADAS) is enhanced with an all-sky microwave radiance data assimilation capability in the real-time GEOS-Forward Processing (FP) system. Currently, the FP system assimilates Global Precipitation Measurement (GPM) microwave imager (GMI) radiance data utilizing this all-sky capability, and is being extended to use more all-sky data from other microwave radiometers. In this presentation, we will focus on impacts of all-sky TMI radiance data on GEOS analyses of atmospheric moisture, precipitation and other fields, and discuss their applications for future GEOS reanalyses.
A technique for estimating monthly oceanic rainfall rate using multi-channel microwave measurements has been developed. This technique is applied to the Special Sensor Microwave Imager (SSM/I) data since 1987 to infer monthly rainfall for the Global Precipitation Climatology Project (GPCP). A modified version of this algorithm is now being applied to the TRMM Microwave Imager (TMI) data. There are three prominent features of this algorithm. First, the knowledge of the form of the rainfall intensity probability density function used to augment the measurements. Second, utilizing a linear combination of the 19.35 and 22.235 GHz channels to deemphasize the effect of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35 and 22.23 5 GHz brightness temperature histograms, TMI data with better spatial resolution and 24 hour sampling (vs. sun-synchronized sampling, which is limited to two narrow intervals of local solar time for DMSP satellites) prompt us to study the similarity and difference between these two rainfall estimates. One year of rainfall data (January to December 1998) are used in this study. The mean differences of these two rain estimates are typically less than 15%. Statistical tests are administrated to evaluate the differences between rainfall estimates from SSM/I and TMI data. Differences between TMI and SSM/I rain estimates are discussed in the context of radiative transfer calculations and rainfall estimate algorithm.
Joint observations from the TRMM mission are used to examine the contribution which lightning observations can make towards estimation of vertical structure and rainfall from passive microwave data. Passive microwave (TMI) observations are binned into distinct vertical structure categories based on cluster analysis of radar (PR) vertical profiles and convective/stratiform (C/S) classifiers. TMI rain estimates are high-biased relative to radar for stratiform and mixed convective/stratiform vertical structures and low-biased relative to radar for convective structures. Significant ambiguity exists in the TMI brightness temperature space between midlevel stratiform and convective profile types which are primary contributors to tropical rainfall. The ambiguity is worst for convective profile types with radar echo tops within and just above the mixed-phase region. The ability of TMI data (including all low and high frequency polarized brightness temperatures; 19V, 19H, 21V, 37V, 37H, 85V, 85H) to predict vertical structure is assessed. The incremental benefit of including TMI convective/stratiform (C/S) classifiers (both 85 GHz polarization and 19, 37 and 85 GHz texture-based) and LZS lightning observations is then considered. The use of all parameters (brightness temperatures, TMI C/S classifiers, lightning data, predicted vertical structure) to reduce TMI/PR rainfall estimate scatter is demonstrated. For both vertical structure and rainfall estimation, inclusion of C/S classifiers and lightning observations provide statistical skill improvements but do not completely alleviate critical midlevel profile C/S ambiguity and related rain estimate errors.
A typical meteorological year (TMY) data set essentially represents an hourly compilation of median months constructed using multi-year datasets. Although TMY data sets are generated from irradiance data in the horizontal plane, they are used in photovoltaic (PV) modeling for systems inclined to various angles. This paper demonstrates that a POA TMY (plane of array TMY) generated by selecting median months from a multi-year POA irradiance timeseries dataset produces significantly different results than a POA TMY generated by transposing a TMY dataset constructed from horizontal data. In some months the differences can be more than 3%. These results point to the need for generating TMY's using POA irradiance timeseries representing the orientation at which PV panels will be deployed.
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The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) will be updated to a final version within the next year. These updates are based on increased knowledge in recent years of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI version updates. This paper discusses four aspects of the TMI data product that will be improved: spacecraft attitude, calibration and quality control, along-scan bias corrections, and sensor pointing accuracy. These updates will be incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI.
It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves and to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and over various smaller longitude bands by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged IR brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5deg by 2.5deg box covered by IR brightness temperatures less than 210 K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130degW-95degW) were observed in that band to have a flash rate of 56.4 flashes/day, a coverage by brightness temperatures less than 210 K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g/kg, and a 300-hPa omega value of -0.04 Pascals/s in the trough phase compared to the non-developing wave trough values of 22.1 flashes/day, a coverage by brightness temperatures less than 210 K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g/kg, and a 300-hPa omega value of -0.01 Pascals/s.
It has been hypothesized that deep, intense convective-scale "hot" towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., "electrically-hot towers") present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5degN-20degN and 130degW-20degE in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves. In addition, information from the NHC reports was used to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To assess the evolution of convection associated with the AEWs as they propagated across our analysis domain, the full 130degW-20degE domain was divided into five longitude bands, and waves were analyzed for each band. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and each longitude band by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation.
It has been hypothesized that deep, intense convective-scale hot towers may aid the process of tropical cyclogenesis and intensification through dynamic and thermodynamic feedbacks on the larger meso-to-synoptic scale circulation. In this study, we make use of NCEP Reanalysis data and Tropical Rainfall Measurement Mission (TRMM) lightning imaging sensor (LIS), precipitation radar (PR), and microwave imager (TMI) data to investigate the role that widespread and/or intense lightning-producing convection (i.e., electrically-hot towers) present in African easterly waves (AEWs) may play in tropical cyclogenesis over the Atlantic, Caribbean, and East Pacific regions. NCEP Reanalysis 700 hPa meridional winds for the months of June to November for the years 2001-2009 were analyzed for the domain of 5 deg. N-20 deg. N and 130 deg. W-20 deg. E in order to partition individual AEWs into northerly, southerly, trough, and ridge phases. Subsequently, information from National Hurricane Center (NHC) storm reports was used to divide the waves into developing and non-developing waves. In addition, information from the NHC reports was used to further divide the developing waves into those waves that spawned storms that only developed to tropical storm strength and those that spawned storms that reached hurricane strength. The developing waves were also divided by the region in which they developed. To assess the evolution of convection associated with the AEWs as they propagated across our analysis domain, the full 130 deg. W-20 deg. E domain was divided into five longitude bands, and waves were analyzed for each band. To help determine the gross nature of the smaller convective scale, composites were created of all developing and non-developing waves as a function of AEW wave phase over the full analysis domain and each longitude band by compositing TRMM PR, TMI, LIS, and IR brightness temperature data extracted from the NASA global-merged infrared brightness temperature dataset. Finally, similar composites were created using various NCEP variables to assess the nature of the larger scale environment and circulation. Results suggest a clear distinction between developing and non-developing waves as developing waves near their region of development in terms of the intensity of convection (indicated by lightning flash rate), coverage of cold cloudiness (indicated by the percentage of a 2.5 deg. by 2.5 deg. box covered by IR brightness temperatures less than 240 deg. K and 210 deg. K), and large-scale variables, such as midlevel moisture and upper-level upward motion. For example, waves that developed in the East Pacific longitude band (i.e., 130 deg. W 95 deg. W) were observed in that band to have a flash rate of 56.4 flashes per day, a coverage by brightness temperatures less than 240 deg. K equal to 15.9%, a coverage by brightness temperatures less than 210 deg. K equal to 2.2%, a 700-hPa specific humidity anomaly of 0.4 g per kilogram, and a 300-hPa omega value of -0.04 Pascals per second in the trough phase compared to the non-developing wave trough values of 22.1 flashes per day, a coverage by brightness temperatures less than 240 deg. K equal to 8.1%, a coverage by brightness temperatures less than 210 deg. K equal to 0.9%, a 700-hPa specific humidity anomaly of -0.3 g per kilogram, and a 300-hPa omega value of -0.01 Pascals per second. Further analysis is being conducted to determine if the aforementioned behavior is observed for developing waves farther from their region of development and to determine any significant differences between waves that spawned storms that reached tropical storm strength and those that spawned storms that reached hurricane strength.
A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.
The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR-based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.
This paper presents the development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics during summer 2001. The technique is calibrated separately over land and ocean, making ingenious use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The low sampling rate of TRMM PR imposes limitations on calibrating IR- based techniques; however, our research shows that PR observations can be applied to improve IR-based techniques significantly by selecting adequate calibration areas and calibration length. The diurnal cycle of rainfall, as well as the division between convective and ~ t i f m rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the latter being important for the calculation of vertical profiles of latent heating.
The development of a satellite infrared (IR) technique for estimating convective and stratiform rainfall and its application in studying the diurnal variability of rainfall on a global scale is presented. The Convective-Stratiform Technique (CST), calibrated by coincident, physically retrieved rain rates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), is applied over the global tropics. The technique makes use of the IR data from the TRMM Visible/Infrared Scanner (VIRS) before application to global geosynchronous satellite data. The calibrated CST technique has the advantages of high spatial resolution (4 km), filtering of non-raining cirrus clouds, and the stratification of the rainfall into its convective and stratiform components, the last being important for the calculation of vertical profiles of latent heating. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall will be presented. The technique is validated using available data sets and compared to other global rainfall products such as Global Precipitation Climatology Project (GPCP) IR product, calibrated with TRMM Microwave Imager (TMI) data. Results from five years of PR data will show the global-tropical partitioning of convective and stratiform rainfall.