Study of Multi-Scale Cloud Processes Over the Tropical Western Pacific Using Cloud-Resolving Models Constrained by Satellite Data

Clouds in the tropical western Pacific are an integral part of the large scale environment. An improved understanding of the multi-scale structure of clouds and their interactions with the environment is critical to the ARM (Atmospheric Radiation Measurement) program for developing and evaluating cloud parameterizations, understanding the consequences of model biases, and providing a context for interpreting the observational data collected over the ARM Tropical Western Pacific (TWP) sites. Three-dimensional cloud resolving models (CRMs) are powerful tools for developing and evaluating cloud parameterizations. However, a significant challenge in using CRMs in the TWP is that the region lacks conventional data, so large uncertainty exists in defining the large-scale environment for clouds. This project links several aspects of the ARM program, from measurements to providing improved analyses, and from cloud-resolving modeling to climate-scale modeling and parameterization development, with the overall objective to improve the representations of clouds in climate models and to simulate and quantify resolved cloud effects on the large-scale environment. Our objectives will be achieved through a series of tasks focusing on the use of the Weather Research and Forecasting (WRF) model and ARM data. Our approach includes: -- Perform assimilation of COSMIC GPS radio occultation and other satellites products using the WRF Ensemble Kalman Filter assimilation system to represent the tropical large-scale environment at 36 km grid resolution. This high-resolution analysis can be used by the community to derive forcing products for single-column models or cloud-resolving models. -- Perform cloud-resolving simulations using WRF and its nesting capabilities, driven by the improved regional analysis and evaluate the simulations against ARM datasets such as from TWP-ICE to optimize the microphysics parameters for this region. A cirrus study (Mace and co-authors) already exists for TWP-ICE using satellite and ground-based observations. -- Perform numerical experiments using WRF to investigate how convection over tropical islands in the Maritime Continent interacts with large-scale circulation and affects convection in nearby regions. -- Evaluate and apply WRF as a testbed for GCM cloud parameterizations, utilizing the ability of WRF to run on multiple scales (from cloud resolving to global) to isolate resolution and physics issues from dynamical and model framework issues. Key products will be disseminated to the ARM and larger community through distribution of data archives, including model outputs from the data assimilation products and cloud resolving simulations, and publications

Procjena fizikalnih parametrizacija u WRF modelu prilikom simuliranja značajnih obilnih oborina nad područjem indijskog monsuna

In this paper the performance of Weather Research and Forecasting (WRF) model for simulation of heavy rainfall events in presence of monsoon depressions over the Indian monsoon region is investigated with different physics options. A number of experiments for forecasts up to 72 hours are performed with two nested domains at the resolution of 45 km and 15 km respectively. The study shows that WRF model is sensitive to the choice of convective scheme. Betts-Miller-Janjic (BMJ) cumulus scheme is found to produce better results compared to other cumulus schemes for the Indian monsoon region. The model is capable of capturing the movement of the monsoon depression with a lead time of 72 hours. The model is expected to be very useful for forecasting of rainfall and depression tracks in short range time scales over Indian monsoon region.U radu se ispituju performanse WRF modela pri simuliranju obilnih oborina na području indijskog monsuna u vrijeme monsunske depresije za različite odabire fizikalnih shema. Napravljen je veći broj prognostičkih eksperimenata u trajanju do 72 sata, s dvije ugniježđene domene s rezolucijama od 45 km i 15 km. Studija pokazuje da je WRF model osjetljiv na izbor konvektivne sheme. Za područje indijskog monsuna Betts-Miller-Janjic (BMJ) kumulusna shema daje bolje rezultate u odnosu na druge kumulusne sheme. Model je uspio uhvatiti pomicanje monsunske depresije u trajanju do 72 sata. Model može biti vrlo koristan za područje indijskog monsuna u kratkoročnim prognozama prognozu oborine i putanja monsunske depresije

Sensitivity of ice-phase cloud microphysics in the NCAR WRF model

Two advanced bulk cloud microphysics schemes, namely, Thompson and Morrison schemes, are evaluated based on observations gathered from the Tropical Warm Pool International Cloud Experiment (TWP-ICE). Because of large uncertainties related to observational retrievals during the “wet” monsoon period (January 17-25, 2006), we have focused on the subsequent “dry” monsoon period (January 26 to February 2, 2006), when deep convections are absent. Compared with the 35-Ghz millimeter wavelength cloud radar (MMCR) and NASA satellite retrievals, all BCMSs tend to simulate more high-level cirrus clouds during the “dry” monsoon period. Therefore, sensitivity tests are carried out to evaluate the issues associated with the ice-phase cloud microphysical parameterizations. Three sensitive tests are carried out to investigate the sensitivity of 1) the maximum number of cloud ice concentration (referred to as the intercept parameter, IP), 2) prescribed size distributions (SD) of cloud ice (Thompson scheme only), and 3) the empirical functions of water and ice saturation threshold (ST). One suite of “convective resolving or cloud-permitting” (4.0 km) simulations of the TWP-ICE “dry” monsoon period illustrates the significant difference among simulated cirrus cloud fraction, cloud ice, snow, and graupel contents for both Thompson and Morrison schemes. These differences are further investigated in another suite of high-resolution “cloud-resolving” (1.5 km) simulations for five days within the TWP-ICE “dry” monsoon period. Based on “cloud-permitting” simulations, we found that Thompson scheme is not sensitive to gamma or exponential SD. Hence the following results are for the exponential SD only. Thompson scheme is more sensitive to ST than Morrison scheme, especially when the temperature drops below minus 40-60oC. Morrison scheme is more sensitive to IP than Thompson scheme. Based on “cloud-resolving” simulations, we found that the above sensitive dependencies on IP and ST for Thompson and Morrison schemes become diminished at high vertical and horizontal resolutions, which infers the importance of future generations of “cloud-resolving” models. Future work is inferred also with respects to other ice-phase cloud microphysical constraints, such as terminal velocities of ice/snow/graupel hydrometros and cloud ice nucleation processes, including explicit aerosol interactions

Procjena fizikalnih parametrizacija u WRF modelu prilikom simuliranja značajnih obilnih oborina nad područjem indijskog monsuna

In this paper the performance of Weather Research and Forecasting (WRF) model for simulation of heavy rainfall events in presence of monsoon depressions over the Indian monsoon region is investigated with different physics options. A number of experiments for forecasts up to 72 hours are performed with two nested domains at the resolution of 45 km and 15 km respectively. The study shows that WRF model is sensitive to the choice of convective scheme. Betts-Miller-Janjic (BMJ) cumulus scheme is found to produce better results compared to other cumulus schemes for the Indian monsoon region. The model is capable of capturing the movement of the monsoon depression with a lead time of 72 hours. The model is expected to be very useful for forecasting of rainfall and depression tracks in short range time scales over Indian monsoon region.U radu se ispituju performanse WRF modela pri simuliranju obilnih oborina na području indijskog monsuna u vrijeme monsunske depresije za različite odabire fizikalnih shema. Napravljen je veći broj prognostičkih eksperimenata u trajanju do 72 sata, s dvije ugniježđene domene s rezolucijama od 45 km i 15 km. Studija pokazuje da je WRF model osjetljiv na izbor konvektivne sheme. Za područje indijskog monsuna Betts-Miller-Janjic (BMJ) kumulusna shema daje bolje rezultate u odnosu na druge kumulusne sheme. Model je uspio uhvatiti pomicanje monsunske depresije u trajanju do 72 sata. Model može biti vrlo koristan za područje indijskog monsuna u kratkoročnim prognozama prognozu oborine i putanja monsunske depresije

The role of land surface processes on the mesoscale simulation of the July 26, 2005 heavy rain event over Mumbai, India

A record-breaking heavy rain event occurred over Mumbai, India on July 26th, 2005 with 24-h rainfall exceeding 944 mm. Operational weather forecast models failed to predict the intensity and amount of heavy rainfall. The objective of this study was to test the impact of the three different land surface models when coupled to the Weather Research Forecasting (WRF), and also to investigate the ability of the WRF model to simulate the Mumbai heavy rain event. Numerical experiments were designed using the WRF model, with three nested domains (30, 10, and 3.3 km grid spacing). Results confirmed that the simulated rainfall is sensitive to the grid spacing (with finer grids leading to higher rainfall). Results also suggest that simulated precipitation amounts are sensitive to the choice of cumulus parameterization (with Grell-Devenyi cumulus scheme performing relatively best). To reduce the confounding impact of cumulus parameterization in studying the impacts of land surface models, we evaluated results for the 3.3 km grid spacing domain with explicit convection. Simulations were performed from 12Z, July 25th to 00Z, July 27th with identical boundary conditions and model configurations for three different land surface models (the Slab, the Noah, and a modified version with photosynthesis module-the Noah-GEM). The model results were compared with observed rainfall, surface temperature, and operational soundings over three locations: Mumbai, Bangalore and Bhopal. Model results showed that: (i) The simulated rainfall was sensitive to the chosen land surface model. The rainfall spatial distributions, as well as their temporal characteristics, were different for each of the three WRF runs with different LSMs. (ii) In contrast to the findings over mid-latitudes, the relatively simpler Slab model had a relatively better performance than the modestly complex Noah and Noah-GEM LSMs. For example, the highest observed rainfall over Mumbai was 944 mm and the simulated amounts for Slab, Noah and Noah-GEM runs were 781 mm, 733 mm and 678 mm, respectively. (iii) Overall, the Slab model simulated a relatively cooler surface and a shallower boundary layer. Most significantly, the Slab model resulted in a convergence hotspot at both the 850 mb and 500 mb levels, which lead to high moisture accumulation and higher rainfall activity over Mumbai. Noah and Noah-GEM, on the other hand, resulted in a divergence zone over Mumbai and the Western Ghats leading to more widespread runs but relatively lower rainfall amounts over Mumbai. Additional synthetic experiments were performed to test the sensitivity of land use land cover, the model start time and run duration. Results indicated that the WRF model was able to reproduce several features of the Mumbai rain event, and that the land surface representations would have substantial impact on the heavy rain simulations. Future studies with more up to date land use land cover data, and regional calibration of the land surface model parameters, show the potential for improving the performance of the Noah-WRF over the Indian monsoon region

Orography-Induced Gravity Wave Drag Parameterization in the Global WRF: Implementation and Sensitivity to Shortwave Radiation Schemes

This paper describes the implementation of the orographic gravity wave drag (GWDO) processes induced by subgrid-scale orography in the global version of the Weather Research and Forecasting (WRF) model. The sensitivity of the model simulated climatology to the representation of shortwave radiation and the addition of the GWDO processes is investigated using the Kim-Arakawa GWDO parameterization and the Goddard, RRTMG (Rapid Radiative Transfer Model for GCMs), and Dudhia shortwave radiation schemes. This sensitivity study is a part of efforts of selecting the physics package that can be useful in applying the WRF model to global and seasonal configuration. The climatology is relatively well simulated by the global WRF; the zonal mean zonal wind and temperature structures are reasonably represented with the Kim-Arakawa GWDO scheme using the Goddard and RRTMG shortwave schemes. It is found that the impact of the shortwave radiation scheme on the modeled atmosphere is pronounced in the upper atmospheric circulations above the tropopause mainly due to the ozone heating. The scheme that excludes the ozone process suffers from a distinct cold bias in the stratosphere. Moreover, given the improper thermodynamic environment conditions by the shortwave scheme, the role of the GWDO process is found to be limited

Sensitivity of Present and Future Surface Temperatures to Precipitation Characteristics

A model simulation study shows that different diurnal cycles of precipitation are consistent with radically different present and future climate characteristics. In projected future climate scenarios, divergence in the time of day and type of precipitation had very divergent impacts on the radiation balance and consequently on surface temperatures. The relationship between the diurnal cycle of precipitation versus the present and future climate was examined using the GISS-MM5 (Goddard Institute for Space Studies Mesoscale Model 5) regional climate modeling system with 2 alternative moist convection schemes. June-August (JJA) mean surface temperatures of the 1990s, 2050s, and 2080s were simulated over the eastern US on a double nested 108/36 km domain, with the 36 km domain centered over the eastern US. In the 1990s, one model version simulated maxima in (convective) precipitation during the early morning, while the second model simulated the hour of precipitation maxima with considerable spatial variability (in better agreement with observations). In the futuristic climate scenarios, differences in the time of day of precipitation had very important impacts on the radiation balance at the surface. One version gave more precipitation at night and fewer clouds during the day, promoting higher surface temperatures. The alternative version created more precipitation during the day, consistent with diminished absorption of solar radiation at the surface and consequently lower surface temperatures. The results demonstrate the importance of improving cumulus parameterizations in regional mesoscale and global climate models and suggest that such improvements would lead to greater confidence in model projections of climate change