Observational Constraints on the Cloud Thermodynamic Phase in Midlatitude Storms

2006 ◽  
Vol 19 (20) ◽  
pp. 5273-5288 ◽  
Author(s):  
Catherine M. Naud ◽  
Anthony D. Del Genio ◽  
Mike Bauer

Abstract The conditions under which supercooled liquid water gradually gives way to ice in the mixed-phase regions of clouds are still poorly understood and may be an important source of cloud feedback uncertainty in general circulation model projections of long-term climate change. Two winters of cloud phase discrimination, cloud-top temperature, sea surface temperature, and precipitation from several satellite datasets (the NASA Terra and Aqua Moderate Resolution Imaging Spectroradiometer, and the Tropical Rainfall Measuring Mission) for the North Atlantic and Pacific Ocean basins are analyzed to better understand these processes. Reanalysis surface pressures and vertical velocities are used in combination with a synoptic storm-tracking algorithm to define storm tracks, create composite storm dynamical and cloud patterns, and examine changes in storm characteristics over their life cycles. Characteristically different storm cloud patterns exist in the Atlantic and Pacific and on the west and east sides of each ocean basin. This appears to be related to the different spatial patterns of sea surface temperature in the two ocean basins. Glaciation occurs at very warm temperatures in the high, thick, heavily precipitating clouds typical of frontal ascent regions, except where vertical velocities are strongest, similar to previous field experiments. Outside frontal regions, however, where clouds are shallower, supercooled water exists at lower cloud-top temperatures. This analysis is the first large-scale assessment of cloud phase and its relation to dynamics on climatologically representative time scales. It provides a potentially powerful benchmark for the design and evaluation of mixed-phase process parameterizations in general circulation models and suggests that assumptions made in some existing models may negatively bias their cloud feedback estimates.

2020 ◽  
Vol 24 (1) ◽  
pp. 269-291 ◽  
Author(s):  
Alfonso Senatore ◽  
Luca Furnari ◽  
Giuseppe Mendicino

Abstract. Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.


2008 ◽  
Vol 363 (1498) ◽  
pp. 1761-1766 ◽  
Author(s):  
Peter Good ◽  
Jason A Lowe ◽  
Mat Collins ◽  
Wilfran Moufouma-Okia

Future changes in meridional sea surface temperature (SST) gradients in the tropical Atlantic could influence Amazon dry-season precipitation by shifting the patterns of moisture convergence and vertical motion. Unlike for the El Niño-Southern Oscillation, there are no standard indices for quantifying this gradient. Here we describe a method for identifying the SST gradient that is most closely associated with June–August precipitation over the south Amazon. We use an ensemble of atmospheric general circulation model (AGCM) integrations forced by observed SST from 1949 to 2005. A large number of tropical Atlantic SST gradient indices are generated randomly and temporal correlations are examined between these indices and June–August precipitation averaged over the Amazon Basin south of the equator. The indices correlating most strongly with June–August southern Amazon precipitation form a cluster of near-meridional orientation centred near the equator. The location of the southern component of the gradient is particularly well defined in a region off the Brazilian tropical coast, consistent with known physical mechanisms. The chosen index appears to capture much of the Atlantic SST influence on simulated southern Amazon dry-season precipitation, and is significantly correlated with observed southern Amazon precipitation. We examine the index in 36 different coupled atmosphere–ocean model projections of climate change under a simple compound 1% increase in CO 2 . Within the large spread of responses, we find a relationship between the projected trend in the index and the Amazon dry-season precipitation trends. Furthermore, the magnitude of the trend relationship is consistent with the inter-annual variability relationship found in the AGCM simulations. This suggests that the index would be of use in quantifying uncertainties in climate change in the region.


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