Tropical Rainfall Measuring Mission Observations Research Articles

A Dimensionless Parameter for Predicting Convective Self‐Aggregation Onset in a Stochastic Reaction‐Diffusion Model of Tropical Radiative‐Convective Equilibrium

AbstractWe introduce a minimal stochastic lattice model for the column relative humidity (R) in the tropics, which incorporates convective moistening, horizontal transport and subsidence drying. The probability of convection occurring in a location increases with R, based on Tropical Rainfall Measuring Mission observations, providing a positive feedback that could lead to aggregation. We show that the simple model reproduces many aspects of full‐physics cloud resolving model experiments. Depending on model parameter settings and domain size and resolution choices, it can produce both random and aggregated equilibrium states. Clustering occurs more readily with larger domains and coarser resolutions, in agreement with full‐physics models. Using dimensional arguments and fits from empirical data, we derive a dimensionless parameter which we call the aggregation number, Nag, that predicts whether a specific model and experiment setup will result in an aggregated or random state. The parameter includes the moistening feedback strength, the horizontal moisture transport efficiency, the subsidence timescale, the domain size and spatial resolution. Using large ensembles of experiments, we show that the transition between random and aggregated states occurs at a critical value of Nag. We argue that Nag could help to understand the differences in aggregation states between full‐physics, cloud resolving models, which show little consensus about the robustness of self‐organized patterns, whose emergence appears to be sensitive to the model setup, physics and parameterizations.

Observed and predicted precipitation variability across Pakistan with special focus on winter and pre-monsoon precipitation.

This study utilises ground, satellite and model data to investigate the observed and future precipitation changes in Pakistan. Pakistan Meteorological Department's (PMD) monthly precipitation data set along with the Tropical Rainfall Measuring Mission (TRMM) monthly dataset TRMM_3B43 (0.25° × 0.25° resolution) and European Centre for Medium-Range Weather Forecasts's (ECMWF) monthly reanalysis product ERA5 have been used to evaluate rainfall trends over the climatic zones of Pakistan through Mann-Kendall test, Sen's slope estimator and innovative trend analysis for the time period 1978-2018. Community Climate System Model (CCSM4) projections have been employed to explore the projected changes in precipitation until 2099. Furthermore, TRMM and CCSM4 projections have been correlated and validated using root mean square error (RMSE) and mean bias error (MBE). There is a good correlation between TRMM and PMD ground observation at all stations of the country for all seasons, with correlation coefficient values ranging from 0.89 (November) to 0.97 (July and August). However, ERA5 monthly precipitation tends to overestimate rainfall in the winter months. The study shows a decreasing trend in winter precipitation in all zones of the country with a significant decrease over western mountains, i.e. zone C of the country. During 2008-2018, a sharp decrease in winter precipitation is observed as compared to the baseline value of 1978-2007 in all climatic zones. Rainy days have also shown a decrease in winter and pre-monsoon seasons. There seems to be a shift in precipitation from winter towards pre-monsoon season as pre-monsoon precipitation in the last 11years increased in all zones except for zone C. Coherently, there is a decrease in an area affected by winter precipitation and an increase in area for pre-monsoon precipitation. Future precipitation estimates from the CCSM4 model for RCP 4.5 and RCP 8.5 overestimate precipitation in most parts of the country for the first 9 observed years (2010-2018) and predict a rise in precipitation by 2099 which is more pronounced in the northern and western Pakistan while a decrease is predicted for the plains of the country, which might have negative consequences for agriculture.

Impact of WRF Parameterization Schemes on Track and Intensity of Extremely Severe Cyclonic Storm “Fani”

Weather Research and Forecasting (WRF) model version 4.1.3 is configured in the present study to understand the impact of microphysical parameterization schemes on the track and intensity of extremely severe cyclonic storm (ESCS) “Fani” that occurred during 26 April to 4 May 2019 in the Bay of Bengal. The model is customized with six different microphysical parameterization schemes along with Kain–Fritsch cumulus for convection and the Yonsei University planetary boundary-layer scheme for computation of heat and moisture transport. The simulations are conducted at 27-km horizontal resolution with 41 levels in the vertical for 150 h (00UTC 28 April to 06UTC 4 May 2019). Model-simulated features such as the track, track error, minimum central sea-level pressure (MSLP), maximum sustained surface wind (MSW), and precipitation are validated against India Meteorological Department (IMD) and Tropical Rainfall Measuring Mission (TRMM) observation data. Although all the schemes predict track patterns similar to observation, the MP3 scheme shows the least track error even after landfall, and its track length is maximum in comparison with other schemes, albeit less than the observed track. The MP3 scheme exhibits a better track for “Fani,” followed by MP14. The lowest mean direct position error (along-track error) of 85 km (68.5 km) is noted for the MP3 scheme, followed by 112.5 km (82.3 km) for the MP8 scheme. Analysis of the MSLP and MSW using the t-test suggests that the MP2 scheme has better forecast ability, followed by MP6. Analysis of the quantitative/spatial matching of the rainfall forecasts and TRMM observations using the Method for Object-Based Diagnostic Evaluation (MODE) tool suggests that the MP8 (MP14) scheme is capable of simulating the rainfall beyond (up to) 48 h. Analysis of the zonal cross-section of horizontal and vertical winds shows that intense convection is well simulated by the MP2, MP3, and MP4 schemes during the change of intensity from cyclonic storm to severe cyclonic storm (SCS), by MP6 and MP14 from SCS to very severe cyclonic storm (VSCS) and from VSCS to ESCS, and by MP8 at ESCS level. All the schemes can capture the eyewall and simulate the westerly that allowed the system to move north-northeastwards. The synoptic flow at different pressure levels is reproduced by all the schemes. However, assessing the impact of the microphysics parameterizations on the synoptic flow of “Fani” at low resolution was difficult. Analysis of Qc and Qr indicates definite impacts of the microphysical parameterizations on the vertical structure of “Fani” in producing rainfall. The MP3 scheme exhibits a better cloud pattern up to upper troposphere level, followed by the MP2 scheme. Analysis of the latent heat flux predicted using the different microphysics schemes suggests that the latent heat flux release at VSCS intensity level or above contributes to further intensification of the TC, and this feature is very well simulated by the MP2 scheme.

Evaluating Precipitation Features and Rainfall Characteristics in a Multi-Scale Modeling Framework.

Cloud and precipitation systems are simulated with a multi‐scale modeling framework (MMF) and compared over the Tropics and Subtropics against the Tropical Rainfall Measuring Mission (TRMM) Radar‐defined Precipitation Features (RPFs) product. A methodology, in close analogy to the TRMM RPFs, is developed to produce simulated precipitation features (PFs) from the output of the embedded two‐dimensional (2D) cloud‐resolving models (CRMs) within an MMF. Despite the limitations of 2D CRMs, the simulated population distribution, horizontal and vertical structure of PFs, and the geographical location and local rainfall contribution of mesoscale convective systems (MCSs) are in good agreement with the TRMM observations. However, some model discrepancies are found and can be identified and quantified within the PF distributions. Using model biases in relative population and rainfall contributions, PFs can be characterized into four size categories: small, medium to large, very large, and extremely large. Four different major mechanisms might account for the model biases in each different category: (1) the two‐dimensionality of the CRMs, (2) a positive convection‐wind‐evaporation feedback loop, (3) an artificial dynamic constraint in a bounded CRM domain with cyclic boundaries, and (4) the limited CRM domain size. The second and fourth mechanisms tend to contribute to the excessive tropical precipitation biases commonly found in most MMFs, whereas the other mechanisms reduce rainfall contributions from small and very large PFs. MMF sensitivity experiments with various CRM domain sizes and grid spacings showed that larger domains (higher resolutions) tend to shift PF populations toward larger (smaller) sizes.

Combining Use of TRMM and Ground Observations of Annual Precipitations for Meteorological Drought Trends Monitoring in Morocco

The monitoring of drought statewide is a difficult issue especially when the national network of meteorological stations is sparse or do not cover the entire country. In this paper, rainfall satellite estimates derived from Tropical Rainfall Measuring Mission (TRMM) product have been used to evaluate the ability of remote sensing data to study the trends of annual precipitation in Morocco between 1998 and 2012. The standardized precipitation index, SPI, has been chosen to monitor meteorological drought in Morocco. Firstly, the accuracy of TRMM product to estimate annual rainfall was evaluated. Annual precipitations derived from 5113 daily TRMM data were compared to the corresponding rainfall measurements from 23 rain gauges. The results showed a general good linear relationship between TRMM and rain gauges data. When considering annual record, the Pearson correlation coefficient, R², was equal to 0.73 and the root mean square error, RMSE, was equal to 159.8mm/year. The correlation between rain gauge measurements and TRMM rainfall had been clearly improved when working with long-term annual average precipitation. The R² increased to 0.79 and the RMSE decreased to 115,2mm. Secondly, the Mann-kendall tau coefficient, the Theil Sen slope and the contextual Mann-Kendall significance were used to analyze the SPI trends over Morocco. This analysis showed that mainly two regions appeared to be subject of significant trends during the studied period: The extreme north eastern of Morocco manifests a positive SPI trends and is more and more subject of extreme rainfall while the extreme south of the country is suffering from a decrease of annual precipitation which could represent significant socio-economic risks in these areas.

Quantification of Precipitation Asymmetries of Tropical Cyclones Using 16‐Year TRMM Observations

AbstractBoth low and higher wavenumber asymmetries of tropical cyclone (TC) precipitation are quantified from 16 years of Tropical Rainfall Measuring Mission (TRMM) microwave imager rainfall estimates using Fourier decomposition. The energy spectrum of rainfall perturbation and impacts of the storm motion and vertical wind shear to the rainfall asymmetry are analyzed. It is found that the wavenumber 1 perturbation only contributes 37% of the total perturbation energy of total TC precipitation, while over 70% of the total perturbation energy is from the sum of wavenumbers 1 through 6. Most of the total precipitation asymmetry is from the heavy precipitation, and contributions for light and moderate precipitation types are small. The maximum motion‐relative precipitation asymmetry is generally located down motion but shifts cyclonically after adding wavenumber 2–6 components to wavenumber 1. The asymmetry index of wavenumber 1 and 1–6 asymmetries relative to the vertical wind shear is about 2 to 3 times as large as that relative to the storm motion. The vertical wind shear is a more important factor than the storm motion in producing precipitation asymmetry, especially for the wavenumber 1. A dominant downshear left wavenumber‐1 asymmetry maximum is found regardless of the shear vector orientation to the TC motion, the magnitude of the shear value, and the speed of TC motion. However, the maximum asymmetry of wavenumber 1–6 asymmetry becomes downshear right for the subgroup with low shear, fast motion, and the shear vector left to the motion.

Tropical cloud and precipitation regimes as seen from near‐simultaneous TRMM, CloudSat, and CALIPSO observations and comparison with ISCCP

AbstractAlthough Tropical Rainfall Measuring Mission (TRMM) and CloudSat/CALIPSO fly in different orbits, they frequently cross each other so that for the period between 2006 and 2010, a total of 15,986 intersect lines occurred within 20 min of each other from 30°S to 30°N, providing a rare opportunity to study tropical cloud and precipitation regimes and their internal vertical structure from near‐simultaneous measurements by these active sensors. A k‐means cluster analysis of TRMM and CloudSat matchups identifies three tropical cloud and precipitation regimes: the first two regimes correspond to, respectively, organized deep convection with heavy rain and cirrus anvils with moderate rain; the third regime is a convectively suppressed regime that can be further divided into three subregimes, which correspond to, respectively, stratocumulus clouds with drizzle, cirrus overlying low clouds, and nonprecipitating cumulus. Inclusion of CALIPSO data adds to the dynamic range of cloud properties and identifies one more cluster; subcluster analysis further identifies a thin, midlevel cloud regime associated with tropical mountain ranges. The radar‐lidar cloud regimes are compared with the International Satellite Cloud Climatology Project (ISCCP) weather states (WSs) for the extended tropics. Focus is placed on the four convectively active WSs, namely, WS1–WS4. ISCCP WS1 and WS2 are found to be counterparts of Regime 1 and Regime 2 in radar‐lidar observations, respectively. ISCCP WS3 and WS4, which are mainly isolated convection and broken, detached cirrus, do not have a strong association with any individual radar and lidar regimes, a likely effect of the different sampling strategies between ISCCP and active sensors and patchy cloudiness of these WSs.

Brightness Temperature Simulation of Observed Precipitation Using a Three-Dimensional Radiative Transfer Model

AbstractThis study demonstrates the capabilities of a three-dimensional radiative transfer model coupled to a polarized microwave surface emissivity model. Simulations are performed at 10, 19, and 37 GHz for TMI and WindSat using three-dimensional fields of rain, snow, and graupel derived from Tropical Rainfall Measuring Mission observations of moderate Tropical Storm Asma in conjunction with atmospheric profiles and surface fields from ECMWF. Simulations are well behaved and compare well with measured brightness temperatures. Comparisons are made between simulations with a wind-roughened surface and simulations assuming a specular surface. This theoretical study, which is supported with WindSat retrievals, shows the frequencies and conditions under which surface emissions may be detected in the presence of rain.

The impact of assimilating MeghaTropiques SAPHIR radiances in the simulation of tropical cyclones over the Bay of Bengal using the WRF model

ABSTRACTThe present study aims to investigate the impact of assimilating SAPHIR (Sounder for Probing Vertical Profiles of Humidity) radiances in the simulation of tropical cyclones over the Indian region by the Weather Research and Forecasting (WRF) model. Three tropical cyclones which formed over the Bay of Bengal are chosen as the case studies. Since SAPHIR is a humidity microwave sensor, it is interesting to assess the impact of these observations in simulating cyclones which depend significantly on moist-convective processes. The study makes use of the three-dimensional variational (3DVar) assimilation technique of the WRF variational assimilation system. The results of the study indicate that the assimilation of SAPHIR radiances do have a positive impact on the simulation of tropical cyclones considered here. Two model simulations are performed – a control run (Ctrl) with only conventional and satellite wind observations assimilated, and a SAPH run (SAPH) where SAPHIR radiances are also assimilated in addition to conventional and satellite wind observations. Both these simulations are compared to each other and to observations from the India Meteorological Department (IMD), Joint Typhoon Warning Centre (JTWC), and Tropical Rainfall Measurement Mission (TRMM), as well as analysis fields from Global Forecast System (GFS) from the National Centres for Environmental Prediction (NCEP). Comparison of minimum sea level pressure and maximum wind speed simulated by the model with the IMD and JTWC observations shows that the SAPHIR assimilation has a moderate impact on the simulation of these features by the model. Track prediction of the model is also improved at initial forecast times, as evidenced by the reduced track errors in the model run with SAPHIR radiances assimilated. The warm core structure, as well as the relative vorticity structure of the cyclones, are also impacted in a moderate manner by the assimilation of SAPHIR radiances. The assimilation also positively impacted the rainfall simulation of the model. This is seen from the higher equitable threat score, lower false alarm ratio, and higher probability of detection estimated with respect to TRMM observations, in the SAPH run as compared to the Ctrl run.

Stochastic convective parameterization improving the simulation of tropical precipitation variability in the NCAR CAM5

AbstractThe Plant‐Craig (PC) stochastic convective parameterization scheme is implemented into the National Center for Atmospheric Research Community Atmosphere Model version 5 (CAM5) to couple with the Zhang‐McFarlane deterministic convection scheme. To evaluate its impact on tropical precipitation simulation, two experiments are conducted: one with the standard CAM5 and the other with the stochastic scheme incorporated. Results show that the PC stochastic parameterization decreases the frequency of weak precipitation and increases the frequency of strong precipitation, resulting in better agreement with observations. The most striking improvement is in the probability distribution function (PDF) of precipitation intensity, with the well‐known too‐much‐drizzle problem in CAM5 largely eliminated. In the global tropical belt, the precipitation intensity PDF from the simulation agrees remarkably well with that of Tropical Rainfall Measuring Mission observations. The stochastic scheme also yields a similar magnitude of intraseasonal variability of precipitation to observations and improves the simulation of the eastward propagating intraseasonal signals of precipitation and zonal wind.

Imprint of the ENSO on rainfall and latent heating variability over the Southern South China Sea from TRMM observations

Analyses of the Tropical Rainfall Measuring Mission (TRMM) datasets revealed a prominent interannual variation in the convective-stratiform rainfall and latent heating over the southern South China Sea (SCS) during the winter monsoon between 1998 and 2010. Although the height of maximum latent heating remained nearly constant at around 7 km in all of the years, the year-to-year changes in the magnitudes of maximum latent heating over the region were noticeable. The interannual variations of the convective- stratiform rainfall and latent heating over the southern SCS were highly anti-correlated with the Nino-3 index, with more (less) rainfall and latent heating during La Nina (El Nino) years. Analysis of the large-scale environment revealed that years of active rainfall and latent heating corresponded to years of large deep convergence and relative humidity at 600 hPa. The moisture budget diagnosis indicated that the interannual variation of humidity at 600 hPa was largely modulated by the vertical moisture advection. The year-to-year changes in rainfall over the southern SCS were mainly caused by the interannual variations of the dynamic component associated with anomalous upward motions in the middle troposphere, while the interannual variations of the thermodynamic component associated with changes in surface specific humidity played a minor role. Larger latent heating over the southern SCS during La Nina years may possibly further enhance the local Hadley circulation over the SCS in the wintertime.

A quantitative assessment of precipitation associated with the ITCZ in the CMIP5 GCM simulations

According to the Intergovernmental Panel on Climate Change 5th Assessment Report, the broad-scale features of precipitation as simulated by Phase 5 of the Coupled Model Intercomparison Project (CMIP5) are in modest agreement with observations, however, large systematic errors are found in the Tropics. In this study, a new algorithm has been developed to define the North Pacific Intertropical Convergence Zone (ITCZ) through several metrics, including: the centerline position of the ITCZ, the width of the ITCZ, and the magnitude of precipitation along the defined ITCZ. These metrics provide a quantitative analysis of precipitation associated with the ITCZ over the equatorial northern Pacific. Results from 29 CMIP5 Atmospheric Model Intercomparison Project (AMIP) Global Circulation Model (GCM) runs are compared with Global Precipitation Climatology Project (GPCP) and Tropical Rainfall Measuring Mission (TRMM) observations. Similarities and differences between the GCM simulations and observations are analyzed with the intent of quantifying magnitude-, location-, and width-based biases within the GCMs. Comparisons show that most of the GCMs tend to simulate a stronger, wider ITCZ shifted slightly northward compared to the ITCZ in GPCP and TRMM observations. Comparisons of CMIP and AMIP simulated precipitation using like-models were found to be nearly equally distributed, with roughly half of GCMs showing an increase (decrease) in precipitation when coupled (decoupled) from their respective ocean model. Further study is warranted to understand these differences.

Radar Vertical Profile of Reflectivity Correction with TRMM Observations Using a Neural Network Approach

Abstract Complex terrain poses challenges to the ground-based radar quantitative precipitation estimation (QPE) because of partial or total blockages of radar beams in the lower tilts. Reflectivities from higher tilts are often used in the QPE under these circumstances and biases are then introduced due to vertical variations of reflectivity. The spaceborne Precipitation Radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite can provide good measurements of the vertical structure of reflectivity even in complex terrain, but the poor temporal resolution of TRMM PR data limits their usefulness in real-time QPE. This study proposes a novel vertical profile of reflectivity (VPR) correction approach to enhance ground radar–based QPEs in complex terrain by integrating the spaceborne radar observations. In the current study, climatological relationships between VPRs from an S-band Doppler weather radar located on the east coast of Taiwan and the TRMM PR are developed using an artificial neural network (ANN). When a lower tilt of the ground radar is blocked, higher-tilt reflectivity data are corrected with the trained ANN and then applied in the rainfall estimation. The proposed algorithm was evaluated with three typhoon precipitation events, and its preliminary performance was evaluated and analyzed.

Climatology of monsoon precipitation over the Tibetan Plateau from 13-year TRMM observations

Based on the 13-year data from the Tropical Rainfall Measuring Mission (TRMM) satellite during 2001–2013, the influencing geographical location of the Tibetan Plateau (Plateau) monsoon is determined. It is found that the domain of the Plateau monsoon is bounded by the latitude between 27° N and 37° N and the longitude between 60° E and 103° E. According to the annual relative precipitation, the Plateau monsoon can be divided into three sections: the Plateau winter monsoon (PWM) over Iran and Afghanistan, the Plateau summer monsoon (PSM) over the central Plateau, and the transiting zone of the Plateau monsoon (TPM) over the south, west, and east edges of the Plateau. In PWM and PSM, the monsoon climatology has a shorter rainy season with the mean annual rainfall of less than 800 mm. In TPM, it has a longer rainy season with the mean annual rainfall of more than 1800 mm. PWM experiences a single-peak monthly rainfall with the peak during January to March; PSM usually undergoes a multi-peak pattern with peaks in the warm season; TPM presents a double-peak pattern, with a strong peak in late spring to early summer and a secondary peak in autumn. The Plateau monsoon also characterizes an asymmetrical seasonal advance of the rain belt. In the east of the Plateau, the rain belt migrates in a south–north orientation under the impact of the tropical and subtropical systems’ oscillation. In the west of the Plateau, the rain belt advances in an east–west direction, which is mainly controlled by the regional Plateau monsoon.

Performance of convection schemes on the simulation of summer monsoon features over the South Asia CORDEX domain using RegCM‐4.3

ABSTRACTAn endeavour is made to investigate the performance of convective parameterization schemes on the simulation of South Asian summer monsoon features through a regional climate model (RegCM). For this purpose, RegCM version 4.3 developed by International Center for Theoretical Physics (ICTP) is used for the simulation experiments in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework over the South Asia domain. Four convective schemes, namely, Emanuel, Grell, Tiedtke and a mixed scheme (Emanuel over land and Grell over the ocean) are evaluated in RegCM4.3 at 45 km horizontal resolution. The simulated results of precipitation, temperature and wind fields are systematically evaluated respectively with Tropical Rainfall Measurement Mission (TRMM), Climate Research Unit (CRU) and ECMWF re‐analysis (ERA) Interim datasets. The results reveal that the response of a mixed convective scheme is better in simulating precipitation and temperature realistically over the Indian subcontinent and is in close agreement with the TRMM observations, compared with the three other schemes. The circulation features are also properly represented with the mixed convection scheme. Furthermore, the annual cycle of precipitation and temperature averaged over the Indian region are well estimated in the mixed scheme, compared with the CRU observations. The northward propagation of monsoon intra‐seasonal oscillations in extreme monsoon seasons is simulated reasonably in a mixed convection scheme as compared with three other schemes. The inter‐annual variability of area averaged JJAS precipitation over the Indian region is simulated well by the model for the combination of Emanuel over land and Grell over the ocean. Grell scheme overestimates the JJAS precipitation, whereas Emanual and Tiedtke schemes underestimate it.

A Systematic Relationship between the Representations of Convectively Coupled Equatorial Wave Activity and the Madden–Julian Oscillation in Climate Model Simulations

Abstract The relationship between a model’s performance in simulating the Madden–Julian oscillation (MJO) and convectively coupled equatorial wave (CCEW) activity during wintertime is examined by analyzing precipitation from 26 general circulation models (GCMs) participating in the MJO Task Force/Global Energy and Water Cycle Experiment (GEWEX) Atmospheric System Study (GASS) MJO model intercomparison project as well as observations based on the Tropical Rainfall Measuring Mission (TRMM). A model’s performance in simulating the MJO is determined by how faithfully it reproduces the eastward propagation of the large-scale intraseasonal variability (ISV) compared to TRMM observations. Results suggest that models that simulate a better MJO tend to 1) have higher fractional variances for various high-frequency wave modes (Kelvin, mixed Rossby–gravity, and westward and eastward inertio-gravity waves), which are defined by the ratios of wave variances of specific wave modes to the “total” variance, and 2) exhibit stronger CCEW variances in association with the eastward-propagating ISV precipitation anomalies for these high-frequency wave modes. The former result is illustrative of an alleviation in the good MJO models of the widely reported GCM deficiency in simulating the correct distribution of variance in tropical convection [i.e., typically too weak (strong) variance in the high- (low-) frequency spectrum of the precipitation]. The latter suggests better coherence and stronger interactions between these aforementioned high-frequency CCEWs and the ISV envelope in good MJO models. Both factors likely contribute to the improved simulation of the MJO in a GCM.

Process-Oriented Diagnosis of East Pacific Warm Pool Intraseasonal Variability

Abstract June–October east Pacific warm pool intraseasonal variability (ISV) is assessed in eight atmospheric general circulation simulations. Complex empirical orthogonal function analysis is used to document the leading mode of 30–90-day precipitation variability in the models and Tropical Rainfall Measuring Mission observations. The models exhibit a large spread in amplitude of the leading mode about the observed amplitude. Little relationship is demonstrated between the amplitude of the leading mode and the ability of models to simulate observed north-northeastward propagation. Several process-oriented diagnostics are explored that attempt to distinguish why some models produce superior ISV. A diagnostic based on the difference in 500–850-hPa averaged relative humidity between the top 5% and the bottom 10% of precipitation events exhibits a significant correlation with leading mode amplitude. Diagnostics based on the vertically integrated moist entropy budget also demonstrate success at discriminating models with strong and weak variability. In particular, the vertical component of gross moist stability exhibits a correlation with amplitude of −0.9, suggesting that models in which convection and associated divergent circulations are less efficient at discharging moisture from the column are better able to sustain strong ISV. Several other diagnostics are tested that show no significant relationship with leading mode amplitude, including the warm pool mean surface zonal wind, the strength of surface flux feedbacks, and 500–850-hPa averaged relative humidity for the top 1% of rainfall events. Vertical zonal wind shear and 850-hPa zonal wind do not appear to be good predictors of model success at simulating the observed northward propagation pattern.

Evaluation of TIGGE ensemble predictions of Northern Hemisphere summer precipitation during 2008–2012

The ensemble mean quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) from six operational global ensemble prediction systems (EPSs) in The Observing System Research and Predictability Experiment Interactive Grand Global Ensemble (TIGGE) data set are evaluated against the Tropical Rainfall Measuring Mission observations using a series of area-weighted verification metrics during June to August 2008–2012 in the Northern Hemisphere (NH) midlatitude and tropics. Results indicate that generally the European Centre for Medium-Range Weather Forecasts performs best while the Canadian Meteorological Centre (CMC) is relatively good for short-range QPFs and PQPFs at light precipitation thresholds. The overall forecast skill is better in the NH midlatitude than in the NH tropics. QPFs and PQPFs from China Meteorological Administration (CMA) have very little discrimination ability of different observed rain events in the NH tropics. The day +1 QPFs from Japan Meteorological Agency have remarkably large moist biases in the NH tropics, which leads to the discontinuity of forecast performance with the lead times. Performance changes due to the major EPS upgrades during the five summers are also examined using the forecasts from CMA as the reference to eliminate the interannual variation. After the EPS upgrade, CMC improves the PQPF skill at light precipitation threshold while its excessively enlarged ensemble spread increases the overall QPF and PQPF errors.

ECMWF and GFS model forecast verification during DYNAMO: Multiscale variability in MJO initiation over the equatorial Indian Ocean

AbstractImproving understanding and prediction of the initiation of the Madden‐Julian Oscillation (MJO) over the equatorial Indian Ocean (IO) was a main objective of the Dynamics of the MJO (DYNAMO) field campaign. This study evaluates the European Centre for Medium‐Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction Global Forecast System (GFS) operational global model forecasts of MJO‐2 in DYNAMO (November–December 2011). The model rainfall and 850 hPa zonal winds are compared with the Tropical Rainfall Measurement Mission (TRMM) rainfall and operational analysis in the equatorial IO. The ECMWF forecasts of the total equatorial rainfall were more consistent with TRMM observations. The GFS did not accurately predict the onset of equatorial convection beyond 5 day lead time. Instead, the GFS rainfall was mainly off the Equator in the Intertropical Convergence Zone (ITCZ). The GFS did not capture synoptic scale systems that bring in dry air intrusions from the subtropics and disrupt convection in the ITCZ which is favorable for equatorial convection associated with the MJO initiation. DYNAMO observations suggest that multiscale interactions among convection, synoptic systems, and the MJO large‐scale circulations were important for the initiation of MJO‐2. The model forecasts and analysis of 850 hPa zonal wind are decomposed into mesoscale, synoptic, and large‐scale flows. Results show that (1) both models have good initial conditions and 1–2 day forecasts and (2) the ECMWF has significantly better skill than the GFS in terms of forecasting equatorial convection, synoptic systems, and the large‐scale MJO circulation at 5–15 day lead times.

Correction of Radar QPE Errors for Nonuniform VPRs in Mesoscale Convective Systems Using TRMM Observations

Abstract Mesoscale convective systems (MCSs) contain both regions of convective and stratiform precipitation, and a bright band (BB) is often found in the stratiform region. Inflated reflectivity intensities in the BB often cause positive biases in radar quantitative precipitation estimation (QPE). A vertical profile of reflectivity (VPR) correction is necessary to reduce such biases. However, existing VPR correction methods for ground-based radars often perform poorly for MCSs owing to their coarse resolution and poor coverage in the vertical direction, especially at far ranges. Spaceborne radars such as the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), on the other hand, can provide high resolution VPRs. The current study explores a new approach of incorporating the TRMM VPRs into the VPR correction for the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar QPE. High-resolution VPRs derived from the Ku-band TRMM PR data are converted into equivalent S-band VPRs using an empirical technique. The equivalent S-band TRMM VPRs are resampled according to the WSR-88D beam resolution, and the resampled (apparent) VPRs are then used to correct for BB effects in the WSR-88D QPE when the ground radar VPR cannot accurately capture the BB bottom. The new scheme was tested on six MCSs from different regions in the United States and it was shown to provide effective mitigation of the radar QPE errors due to BB contamination.