The too fast, too frequent precipitation simulated in GCMs

Journal of Hydrometeorology, 2009

The Lagrangian Model (LMODEL) is a new multisensor satellite rainfall monitoring methodology based on the use of a conceptual cloud-development model that is driven by geostationary satellite imagery and is locally updated using microwave-based rainfall measurements from low earth-orbiting platforms. This paper describes the cloud development model and updating procedures; the companion paper presents model validation results. The model uses single-band thermal infrared geostationary satellite imagery to characterize cloud motion, growth, and dispersal at high spatial resolution (∼4 km). These inputs drive a simple, linear, semi-Lagrangian, conceptual cloud mass balance model, incorporating separate representations of convective and stratiform processes. The model is locally updated against microwave satellite data using a two-stage process that scales precipitable water fluxes into the model and then updates model states using a Kalman filter. Model calibration and updating employ ...

Journal of Geophysical Research: Atmospheres, 2017

The cloud-to-precipitation transition process in warm clouds simulated by state-of-the-art global climate models (GCMs), including both traditional climate models and a high-resolution model, is evaluated against A-Train satellite observations. The models and satellite observations are compared in the form of the statistics obtained from combined analysis of multiple-satellite observables that probe signatures of the cloud-to-precipitation transition process. One common problem identified among these models is the too-frequent occurrence of warm precipitation. The precipitation is found to form when the cloud particle size and the liquid water path (LWP) are both much smaller than those in observations. The too-efficient formation of precipitation is found to be compensated for by errors of cloud microphysical properties, such as underestimated cloud particle size and LWP, to an extent that varies among the models. However, this does not completely cancel the precipitation formation bias. Robust errors are also found in the evolution of cloud microphysical properties from nonprecipitating to drizzling and then to raining clouds in some GCMs, implying unrealistic interaction between precipitation and cloud water. Nevertheless, auspicious information is found for future improvement of warm precipitation representations: the adoption of more realistic autoconversion scheme in the high-resolution model improves the triggering of precipitation, and the introduction of a sophisticated subgrid variability scheme in a traditional model improves the simulated precipitation frequency over subtropical eastern ocean. However, deterioration in other warm precipitation characteristics is also found accompanying these improvements, implying the multisource nature of warm precipitation biases in GCMs. 1. Introduction Precipitation is of great hydrological and radiative importance in the climate system by its depletion of cloud water and its modification to cloud optical properties (Intergovernmental Panel on Climate Change, 2013; Pincus & Baker, 1994). Precipitation also responds strongly to atmospheric conditions such as aerosol perturbations and global warming (

2011

The objective of this project is to better understand cloud and precipitation processes on the Earth and to improve these processes in climate models by global cloud resolving approach. In FY2010, a 10-day long 3.5-km mesh global simulation of genesis process of Typhoon Fengshen was conducted. The results were analyzed in terms of multi-scale processes of tropical cyclogenesis and validated against the in-situ and satellite observations. A series of sensitivity experiments using 14 km mesh were executed to evaluate global statistics of simulated clouds. Based on the results, physical parameters were tuned to improve reproducibility of the cloud properties in long-term simulations. In order to understand basic mechanisms of tropical atmospheric variabilities with intraseasonal timescale, idealized experiments with aquaplanet setups were also performed. The results suggest the importance of zonal contrast of sea surface temperature forcing.

This study analyzes the diurnal cycle of precipitation simulated in a global cloud-resolving model (GCRM) named the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). A 30-day integration of NICAM successfully simulates the precipitation diurnal cycle associated with the land-sea breeze and the thermally induced topographic circulations as well as the horizontal propagation of diurnal cycle signals. The first harmonic of the diurnal cycle of precipitation in the 7-km run agrees well with that from satellite observations in its geographical distributions although its amplitude is slightly overestimated. The NICAM simulation revealed that the precipitation diurnal cycle over the Maritime Continent is strongly coupled with the land-sea breeze that controls the convergence/divergence pattern in the lower troposphere around the islands. The analysis also suggests that the cold pool often forms over the open ocean where the precipitation intensity is high, and the propagation of the cold pool events is related to the precipitation diurnal cycle as well as the land-sea breeze.

Journal of Geophysical Research, 2010

New, definitive measures of precipitation frequency provided by CloudSat are used to assess the realism of global model precipitation. The character of liquid precipitation (defined as a combination of accumulation, frequency, and intensity) over the global oceans is significantly different from the character of liquid precipitation produced by global weather and climate models. Five different models are used in this comparison representing state-of-the-art weather prediction models, state-of-the-art climate models, and the emerging high-resolution global cloud "resolving" models. The differences between observed and modeled precipitation are larger than can be explained by observational retrieval errors or by the inherent sampling differences between observations and models. We show that the time integrated accumulations of precipitation produced by models closely match observations when globally composited. However, these models produce precipitation approximately twice as often as that observed and make rainfall far too lightly. This finding reinforces similar findings from other studies based on surface accumulated rainfall measurements. The implications of this dreary state of model depiction of the real world are discussed.

Water Science and Technology Library, 2008

Measuring precipitation from space is a long standing issue of meteorology and climatology. Since the launch of the first meteorological satellites in the 60s several visible/infrared/microwave techniques for "inferring", rather than "measuring" rainfall intensity from space were conceived, but seldom reached operational application. Algorithms have greatly evolved and now offer an acceptable quality level when products are averaged over suitable time and space scales. Daily, monthly and yearly products have become important inputs for climate studies, but their quality significantly lowers when the algorithms are applied to estimate instantaneous rainrates. The most recent methods go back to the basic physical principles of precipitation formation and evolution. The re-examination of the physical content of the algorithms is driven by new insights on precipitation formation mechanisms now available together with new observational tools from space and from the ground. New satellite missions, activities and efforts of international organizations are devoted to the generation of high resolution precipitation products for applications in meteorology, hydrology and climate.

SOLA, 2016

Resolution dependence was found in the simulated diurnal precipitation cycle over land in the tropics. We conducted a series of grid refinement experiments of the atmosphere from 14 km to 0.87 km using a global high-resolution model without any convection parameterizations. In the high-resolution experiment, the peak of the cycle was earlier and precipitation at the peak was higher. The characteristics of the simulated diurnal precipitation cycle changed at a grid spacing of around 2−3 km. The precipitation started to increase in the morning in the high-resolution experiments, suggesting that small-scale moist convection became active in the late morning. In the lower-resolution experiments, convection and precipitation began in the late afternoon. As well as the enhancement of moisture transport from the boundary layer to the middle troposphere, the rapid formation of rain can also be attributed to the difference in diurnal precipitation cycles between lower and higher resolution experiments.

Quarterly Journal of the Royal Meteorological Society, 2012

We investigate the sensitivity of simulated cloud properties and surface precipitation to assumptions regarding the size distributions of the precipitating hydrometeors in a one-moment bulk microphysics scheme. Three sensitivity experiments were applied to two composites of 15 convective and 15 frontal stratiform intense precipitation events observed in a coastal midlatitude region (Belgium), which were evaluated against satellite-retrieved cloud properties and radar-rain-gauge derived surface precipitation. It is found that the cloud optical thickness distribution was well captured by all experiments, although a significant underestimation of cloudiness occurred in the convective composite. The cloud-top-pressure distribution was improved most by more realistic snow size distributions (including a temperaturedependent intercept parameter and non-spherical snow for the calculation of the slope parameter), due to increased snow depositional growth at high altitudes. Surface precipitation was far less sensitive to whether graupel or hail was chosen as the rimed ice species, as compared to previous idealized experiments. This smaller difference in sensitivity could be explained by the stronger updraught velocities and higher freezing levels in the idealized experiments compared to typical coastal midlatitude environmental conditions. Citation: Van Weverberg K, van Lipzig NPM, Delobbe L, Vogelmann AM. 2012. The role of precipitation size distributions in km-scale NWP simulations of intense precipitation: evaluation of cloud properties and surface precipitation. Q.

Journal of Climate, 2007

The frequency distributions of surface rain rate are evaluated in the Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/Imager (SSM/I) satellite observations and the NOAA/GFDL global atmosphere model version 2 (AM2). Instantaneous satellite rain-rate observations averaged over the 2.5°latitude ϫ 2°longitude model grid are shown to be representative of the half-hour rain rate from single time steps simulated by the model. Rain-rate events exceeding 10 mm h Ϫ1 are observed by satellites in most regions, with 1 mm h Ϫ1 events occurring more than two orders of magnitude more frequently than 10 mm h Ϫ1 events. A model simulation using the relaxed Arakawa-Schubert (RAS) formulation of cumulus convection exhibits a strong bias toward many more light rain events compared to the observations and far too few heavy rain events. A simulation using an alternative convection scheme, which includes an explicit representation of mesoscale circulations and an alternative formulation of the closure, exhibits, among other differences, an order of magnitude more tropical rain events above the 5 mm h Ϫ1 rate compared to the RAS simulation. This simulation demonstrates that global atmospheric models can be made to produce heavy rain events, in some cases even exceeding the observed frequency of such events. Additional simulations reveal that the frequency distribution of the surface rain rate in the GCM is shaped by a variety of components within the convection parameterization, including the closure, convective triggers, the spectrum of convective and mesoscale clouds, and other parameters whose physical basis is currently only understood to a limited extent. Furthermore, these components interact nonlinearly such that the sensitivity of the rain-rate distribution to the formulation of one component may depend on the formulation of the others. Two simulations using different convection parameterizations are performed using perturbed sea surface temperatures as a surrogate for greenhouse gas-forced climate warming. Changes in the frequency of rain events greater than 2 mm h Ϫ1 associated with changing the convection scheme in the model are greater than the changes in the frequency of heavy rain events associated with a 2-K warming using either model. Thus, uncertainty persists with respect to simulating intensity distributions for precipitation and projecting their future changes. Improving the representation of the frequency distribution of rain rates will rely on refinements in the formulation of cumulus closure and the other components of convection schemes, and greater certainty in predictions of future changes in both total rainfall and in rain-rate distributions will require additional refinements in those parameterizations that determine the cloud and water vapor feedbacks.

Journal of Climate, 2003

Testing general circulation model parameterizations against observations is traditionally done by comparing simulated and observed, time-averaged quantities, such as monthly mean cloud cover, evaluated on a stationary grid. This approach ignores the dynamical aspects of clouds, such as their life cycle characteristics, spatial coverage, temporal duration, and internal variability. In this study, a complementary Lagrangian approach to the validation of modeled tropical cloudiness is explored. An automated cloud detection and tracking algorithm is used to observe and track overcast decks of cloud in a consecutive set of hourly Meteosat-5 images and the National Center for Atmospheric Research Community Climate Model version 3 (NCAR CCM3). The algorithm is applied to the deep convective cloud systems of the tropical Indian Ocean region during a 49-day period of the 1999 winter monsoon season. Observations of precipitation are taken from the Tropical Rainfall Measuring Mission (TRMM) satellite in addition to a Meteosat-5 infrared rainfall technique that is calibrated using the TRMM data.Clouds, defined as overcast decks, are observed spanning spatial scales from 25 km2 to greater than 107 km2, as well as temporal scales from 1 h to greater than 100 h. Semipermanent decks of anvil and cirrus cloud, with numerous regions of deep convection embedded within, dominate total cloud cover. Bridging between convective centers within the deck by cirrus clouds, particularly during the suppressed portion of the diurnal cycle of convection, may help to maintain the integrity of semipermanent overcast decks over long timescales. At scales greater than 106 km2 the size distribution of simulated clouds is biased such that the dominant scale of clouds is several million square kilometers larger than the dominant scale of observed clouds. Virtually all of the simulated precipitation occurs at rain rates lower than 2 mm h-1, while as much as 25% of observed precipitation occurs at rain rates higher than 2 mm h-1. Precipitation associated with deep convection in observed semipermanent cloud systems is organized into more localized mesoscale structures of adjacent convective cells attached to stratiform precipitation regions. A separate analysis of TRMM data by Wilcox and Ramanathan determined that such structures can exceed the size of grid cells in coarse-grid global models and have area-averaged rain rates up to and exceeding 2 mm h-1. These mesoscale convective systems are responsible for the extreme, episodic precipitation events that are not parameterized in the model. The simulated cloud systems gently precipitate throughout their duration and everywhere within their boundaries. The model lacks a process that acts to organize the convective cells within fewer grid cells, in addition to a representation of the observed stratiform precipitation structures. A modification to CCM3 is tested that is intended to account for the evaporation of upper-level precipitation in midlevel mesoscale downdrafts. The modification results in only a slight change in domain-averaged precipitation. However, it causes a significant shift in the distribution of precipitation toward higher rain rates that is more consistent with the distribution of TRMM observed rain rates. The modification demonstrates the sensitivity of the model to one important component of mesoscale organized convection.