E. N. Rajagopal

Comparison of TMPA-3B42 Versions 6 and 7 Precipitation Products with Gauge-Based Data over India for the Southwest Monsoon Period

AbstractThe upgraded version 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products is available to the user community. In this paper, two successive versions of the TMPA-3B42 research monitoring product, version 6 (V6) and V7, at the daily scale are evaluated over India during the southwest monsoon with gauge-based data for a 13-yr (1998–2010) period. Over typical monsoon rainfall zones, biases are improved by 5%–10% in V7 over the regions of higher rainfall like the west coast, northeastern, and central India. A similar reduced bias is seen in V7 over the rain-shadow region located in southeastern India. In terms of correlation, anomaly correlation, and RMSE, a marginal improvement is seen in V7. Additionally, in all-India summer monsoon rainfall amounts, mean, interannual values, and standard deviation show an overall improvement in V7. Different skill metrics over typical subregions within India show an improvement of the monsoon rainfall represe...

Improvements in medium range weather forecasting system of India

Medium range weather forecasts are being generated in real time using Global Data Assimilation Forecasting System (GDAFS) at NCMRWF since 1994. The system has been continuously upgraded in terms of data usage, assimilation and forecasting system. Recently this system was upgraded to a horizontal resolution of T574 (about 22 km) with 64 levels in vertical. The assimilation scheme of this upgraded system is based on the latest Grid Statistical Interpolation (GSI) scheme and it has the provision to use most of available meteorological and oceanographic satellite datasets besides conventional meteorological observations. The new system has an improved procedure for relocating tropical cyclone to its observed position with the correct intensity. All these modifications have resulted in improvement of skill of medium range forecasts by about 1 day.

All-sky radiance simulation of Megha-Tropiques SAPHIR microwave sensor using multiple scattering radiative transfer model for data assimilation applications

Incorporation of cloud- and precipitation-affected radiances from microwave satellite sensors in data assimilation system has a great potential in improving the accuracy of numerical model forecasts over the regions of high impact weather. By employing the multiple scattering radiative transfer model RTTOV-SCATT, all-sky radiance (clear sky and cloudy sky) simulation has been performed for six channel microwave SAPHIR (Sounder for Atmospheric Profiling of Humidity in the Inter-tropics by Radiometry) sensors of Megha-Tropiques (MT) satellite. To investigate the importance of cloud-affected radiance data in severe weather conditions, all-sky radiance simulation is carried out for the severe cyclonic storm ‘Hudhud’ formed over Bay of Bengal. Hydrometeors from NCMRWF unified model (NCUM) forecasts are used as input to the RTTOV model to simulate cloud-affected SAPHIR radiances. Horizontal and vertical distribution of all-sky simulated radiances agrees reasonably well with the SAPHIR observed radiances over cloudy regions during different stages of cyclone development. Simulated brightness temperatures of six SAPHIR channels indicate that the three dimensional humidity structure of tropical cyclone is well represented in all-sky computations. Improved correlation and reduced bias and root mean square error against SAPHIR observations are apparent. Probability distribution functions reveal that all-sky simulations are able to produce the cloud-affected lower brightness temperatures associated with cloudy regions. The density scatter plots infer that all-sky radiances are more consistent with observed radiances. Correlation between different types of hydrometeors and simulated brightness temperatures at respective atmospheric levels highlights the significance of inclusion of scattering effects from different hydrometeors in simulating the cloud-affected radiances in all-sky simulations. The results are promising and suggest that the inclusion of multiple scattering radiative transfer models into data assimilation system can simulate the cloud-affected microwave radiance data which provide detailed information on three dimensional humidity structure of the atmosphere in the presence of cloud hydrometeors.

Simulation of Tropical Cyclones over Bay of Bengal with NCMRWF Regional Unified Model

This study delineates the relative performance of the 12-km resolution NCMRWF regional Unified Model (NCUM-R) over the operational global NCUM (NCUM-G) model. Forecasts of four Bay of Bengal (BoB) landfalling tropical cyclones (TCs) using several different initial conditions (ICs) are used to compare the performance of two models. The position and intensity errors of the TCs are estimated with respect to the India Meteorological Department (IMD) and Joint Typhoon Warning Center (JTWC) best-track datasets and an inter-comparison study is also carried out between IMD and JTWC. The overall results suggest that the NCUM-R simulates the position and intensity of TCs more accurately compared to the NCUM-G. A majority of the TC tracks in the NCUM-G diverge more from the IMD track when compared to NCUM-R simulated tracks. It is also clearly noticed that both the models are more skillful in track prediction when initialized at intensity stages greater than “cyclone” category. However, the mean position errors at different forecast hours and landfall errors of TCs are reduced by approximately 31 and 47% in the NCUM-R simulations compared to NCUM-G simulations, respectively. The mean gain in skill of the NCUM-R in cross track (CT) and along track (AT) error is around 29 and 24% over NCUM-G, respectively. The intensity errors are less in the NCUM-R simulations. The mean rainfall skill scores are considerably improved in the NCUM-R simulations in day-1 and day-2 as compared to the NCUM-G simulations. It is noticed that the mean position errors of the TCs are approximately 8% lower when compared against the JTWC tracks than the IMD tracks. However, the intensity errors are higher against the JTWC than that of IMD most likely due to the averaging period of the wind speed.

Behaviour of predicted convective clouds and precipitation in the high resolution Unified Model over the Indian summer monsoon region

National Centre for Medium Range Weather Forecasting (NCMRWF) high resolution regional convective scale Unified Model (NCUM-R) with latest tropical science settings is used to evaluate vertical structure of cloud and precipitation over two prominent monsoon regions: Western Ghats (WG) and Monsoon Core Zone (MCZ). Model radar reflectivity generated using Cloud Feedback Model Inter-comparison Project (CFMIP) observation simulator package (COSP) along with CloudSat profiling radar reflectivity is sampled for an active synoptic situation based on a new method using Budykos index of turbulence (BT). Regime classification based on BT-precipitation relationship is more predominant during the active monsoon period when convective scale models resolution increases from 4 km to 1.5 km. Model predicted precipitation and vertical distribution of hydrometeors are found to be generally in agreement with Global Precipitation Measurement (GPM) products and BT based CloudSat observation respectively. Frequency of occurrence of radar reflectivity from model implies that the low level clouds below freezing level is underestimated compared to the observations over both regions. In addition, high level clouds in the model predictions are much lesser over WG than MCZ.

Effect of new radiance observations on numerical weather prediction models

The assimilation of any new observational dataset into a numerical weather prediction (NWP) system can affect the quality of the existing datasets, with respect to the model background (the short-term forecast). This, in turn, influences the use of the existing observations within the NWP system. Indeed, it is the standard practice of operational NWP centers to assess the quality of observations with respect to NWP model fields. Furthermore, the importance of using NWP fields to assess the data quality from microwave sensing instruments has already been shown.1–3 The influence of a new dataset—from the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) instrument—on existing NWP models therefore needs to be assessed. The SAPHIR instrument is a six-channel microwave humidity profiler on the Megha-Tropiques (MT) satellite. The six channels are close to the absorption band of water vapor (at about 183GHz) and thus provide a relatively narrow weighting function, from the surface to an altitude of 10km, for retrieving water vapor profiles in the cloud-free troposphere. The new radiance/brightness temperatures (TBs) from SAPHIR have recently been added to the UK Met Office’s Unified Model (UM) assimilation system, which is being used in operations at India’s National Centre for Medium Range Weather Forecasting (NCMRWF). In this work,4 we have performed a detailed investigation of the impact of incorporating SAPHIR radiance data into the UK Met Office’s UM (i.e., which is used for NWPs). This UM Figure 1. Innovations (differences between the observations and simulations) for the Sounder for Atmospheric Profiling of Humidity in the Intertropics by Radiometry (SAPHIR) channel 1. Results are shown with (blue curve) and without (black curve) bias correction.

Recent land use/land cover changes and their impact on the evolution and structure of thunderstorm in New Delhi

Current study investigates the impact of changes in land use/land cover (Lu/Lc) on thunderstorm, the short lived convective event occurred in New Delhi. We are trying to understand the impact of urban Lu/Lc changes on the structure and evolution of severe thunderstorm activities over a short time period. Lu/Lc data from IGBP are available for the period 1992-1993 and recent period 2012-2013 Lu/Lc data are from the ISRO AWiFS satellite sensor. We have used a cloud resolving model at 1.5 km resolution embedded within a coarser resolution global model at 17 km resolution. These configurations of models are based on UK Met Office Unified Model. Recent period Lu/Lc shows an increase in urban build up and increase in bare soil fraction over Delhi region. Our result shows that the Lu/LC change can impact the low level wind and thermodynamic structure of the storm.

Verification of Medium Range Probabilistic Rainfall Forecasts Over India

Forecasting rainfall in the tropics is a challenging task further hampered by the uncertainty in the numerical weather prediction models. Ensemble prediction systems (EPSs) provide an efficient way of handling the inherent uncertainty of these models. Verification of forecasts obtained from an EPS is a necessity, to build confidence in using these forecasts. This study deals with the verification of the probabilistic rainfall forecast obtained from the National Centre for Medium Range Weather Forecasting (NCMRWF) Global Ensemble Forecast system (NGEFS) for three monsoon seasons, i.e., JJAS 2012, 2013 and 2014. Verification is done based on the Brier Score (BS) and its components (reliability, resolution and uncertainty), Brier Skill Score (BSS), reliability diagram, relative operating characteristic (ROC) curve and area under the ROC (AROC) curve. Three observation data sets are used (namely, NMSG, CPC-RFE2.0 and TRMM) for verification of forecasts and the statistics are compared. BS values for verification of NGEFS forecasts using NMSG data are the lowest, indicating that the forecasts have a better match with these observations as compared to both TRMM and CPC-RFE2.0. This is further strengthened by lower reliability, higher resolution and BSS values for verification against this data set. The ROC curve shows that lower rainfall amounts have a higher hit rate, which implies that the model has better skill in predicting these rainfall amounts. The reliability plots show that the events with lower probabilities were under forecasted and those with higher probabilities were over forecasted. From the current study it can be concluded that even though NGEFS is a coarse resolution EPS, the probabilistic forecast has good skill. This in turn leads to an increased confidence in issuing operational probabilistic forecasts based on NGEFS.

Assimilation of SAPHIR radiance: impact on hyperspectral radiances in 4D-VAR

Assimilation of a new observation dataset in an NWP system may affect the quality of an existing observation data set against the model background (short forecast), which in-turn influence the use of an existing observation in the NWP system. Effect of the use of one data set on the use of another data set can be quantified as positive, negative or neutral. Impact of the addition of new dataset is defined as positive if the number of assimilated observations of an existing type of observation increases, and bias and standard deviation decreases compared to the control (without the new dataset) experiment. Recently a new dataset, Megha Tropiques SAPHIR radiances, which provides atmospheric humidity information, is added in the Unified Model 4D-VAR assimilation system. In this paper we discuss the impact of SAPHIR on the assimilation of hyper-spectral radiances like AIRS, IASI and CrIS. Though SAPHIR is a Microwave instrument, its impact can be clearly seen in the use of hyper-spectral radiances in the 4D-VAR data assimilation systems in addition to other Microwave and InfraRed observation. SAPHIR assimilation decreased the standard deviation of the spectral channels of wave number from 650 -1600 cm-1 in all the three hyperspectral radiances. Similar impact on the hyperspectral radiances can be seen due to the assimilation of other Microwave radiances like from AMSR2 and SSMIS Imager.

Performance of NCMRWF Model TC Track Forecasts During 2013

There are two tropical cyclone (TC) seasons over the North Indian Ocean (NIO), (including the Bay of Bengal (BOB) and the Arabian Sea (AS)), i.e. during the pre-monsoon months (April–early June) and the post-monsoon months (October–December) (Mohanty et al., Mar Geod 33:294–314, 2010). Further the Indian subcontinent happens to be one of the world’s highly vulnerable areas since the coastal population density is very high leading to an extensive damage to life and property. Therefore, forecasting of TC track and landfall location is critical for early warnings and mitigation of disaster. Track forecast errors over the NIO though improved significantly in recent years (Mohapatra et al., J Earth Syst Sci 122:589–601, 2013, J Earth Syst Sci 124:861–874. doi: 10.1007/s12040-015-0581-x, 2015) are still high relative to those over the Atlantic and Pacific Oceans. With advancements in computational power, development of better NWP models (both global and regional), the forecasting capability of meteorologists have greatly increased. Several meteorological centers like NCEP, UKMet office, ECMWF, JMA, JTWC etc give a real time forecast of TC tracks from their global NWP models (deterministic as well as Ensemble Prediction Systems (EPS)) (Hamill et al. Mon Weather Rev 139:3243–3247, 2011; Froude et al. Mon Weather Rev 135:2545–2567, 2007; Buckingham et al. Weather Forecast 25:1736–1754, 2010; Heming et al. Meteorol Appl 2:171–184, 1995; Heming and Radford Mon Weather Rev 126:1323–1331, 1998). TC track prediction from an ensemble forecasting system besides providing a track from each ensemble member also provides the strike probability (Weber Mon Weather Rev 133:1840–1852, 2005). For the TCs of NIO, Mohapatra et al. (J Earth Syst Sci 122:589–601, 2013, J Earth Syst Sci 124:861–874. doi: 10.1007/s12040-015-0581-x, 2015) provided a detailed verification of the official forecast tracks and its improvements in the recent past. This study provides a detailed verification of the NCMRWF NWP model forecasts of 2013 TC cases. Some of the earlier studies (Ashrit et al. Improved track and intensity predictions using TC bogusing and regional assimilation. In: Mohanty UC, Mohapatra M, Singh OP, Bandyopadhyay BK, Rathore LS (eds) Monitoring and prediction of TCs in the Indian ocean and climate change, Springer, Dordrecht, p 246–254, 2014; Chourasia et al. Mausam 64:135–148, 2013 and Mohandas and Ashrit Nat hazard 73:213–235, 2014) focused on the NCMRWF model TC forecasts and the impact of bogusing, assimilation and cumulus parameterisation etc. The present study is focused on the real time operational forecasts provided to India Meteorological Department (IMD). During May–December 2013, there were five TCs observed in the Bay of Bengal namely: Viyaru (May10–17), Phailin (October 4–14), Helen (November 19–23), Lehar (November 19–28) and Madi (December 6–13). This report summarises the performance of the real time prediction of these TC tracks by the NCMRWF Global Forecast Systems.