scholarly journals Retrieval of Model Grid-Scale Heat Capacity Using Geostationary Satellite Products. Part I: First Case-Study Application

2005 ◽  
Vol 44 (9) ◽  
pp. 1346-1360 ◽  
Author(s):  
Richard T. McNider ◽  
William M. Lapenta ◽  
Arastoo P. Biazar ◽  
Gary J. Jedlovec ◽  
Ronnie J. Suggs ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Heat Capacity ◽  
General Circulation ◽  
Mesoscale Model ◽  
Regional Scale ◽  
Model Performance ◽  
General Circulation Models ◽  
Surface Energy Budget ◽  
Scale Model ◽  
First Case

Abstract In weather forecast and general circulation models the behavior of the atmospheric boundary layer, especially the nocturnal boundary layer, can be critically dependent on the magnitude of the effective model grid-scale bulk heat capacity. Yet, this model parameter is uncertain both in its value and in its conceptual meaning for a model grid in heterogeneous conditions. Current methods for estimating the grid-scale heat capacity involve the areal/volume weighting of heat capacity (resistance) of various, often ill-defined, components. This can lead to errors in model performance in certain parameter spaces. Here, a technique is proposed and tested for recovering bulk heat capacity using time tendencies in satellite-retrieved surface skin temperature (SST). The technique builds upon sensitivity studies that show that surface temperature is most sensitive to thermal inertia in the early evening hours. The retrievals are made within the context of a surface energy budget in a regional-scale model [the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)]. The retrieved heat capacities are used in the forecast model, and it is shown that the model predictions of temperature are improved in the nighttime during the forecast periods.

scholarly journals Wet scavenging limits the detection of aerosol–cloud–precipitation interactions

2015 ◽  
Vol 15 (5) ◽  
pp. 6851-6886 ◽  
Author(s):  
E. Gryspeerdt ◽  
P. Stier ◽  
B. A. White ◽  
Z. Kipling
Keyword(s):  
Spatial Variability ◽  
General Circulation ◽  
Regional Scale ◽  
General Circulation Models ◽  
Satellite Observations ◽  
Scale Model ◽  
Convective Clouds ◽  
Aerosol Cloud ◽  
Wet Scavenging ◽  
Aerosol Properties

Abstract. Satellite studies of aerosol–cloud interactions usually make use of retrievals of both aerosol and cloud properties, but these retrievals are rarely spatially co-located. While it is possible to retrieve aerosol properties above clouds under certain circumstances, aerosol properties are usually only retrieved in cloud free scenes. Generally, the smaller spatial variability of aerosols compared to clouds reduces the importance of this sampling difference. However, as precipitation generates an increase in spatial variability, the imperfect co-location of aerosol and cloud property retrievals may lead to changes in observed aerosol–cloud–precipitation relationships in precipitating environments. In this work, we use a regional-scale model, satellite observations and reanalysis data to investigate how the non-coincidence of aerosol, cloud and precipitation retrievals affects correlations between them. We show that the difference in the aerosol optical depth (AOD)-precipitation relationship between general circulation models (GCMs) and satellite observations can be explained by the wet scavenging of aerosol. Using observations of the development of precipitation from cloud regimes, we show how the influence of wet scavenging can obscure possible aerosol influences on precipitation from convective clouds. This obscuring of aerosol–cloud–precipitation interactions by wet scavenging suggests that even if GCMs contained a perfect representation of aerosol influences on convective clouds, the difficulty of separating the "clear-sky" aerosol from the "all-sky" aerosol in GCMs may prevent them from reproducing the correlations seen in satellite data.

scholarly journals Wet scavenging limits the detection of aerosol effects on precipitation

2015 ◽  
Vol 15 (13) ◽  
pp. 7557-7570 ◽  
Author(s):  
E. Gryspeerdt ◽  
P. Stier ◽  
B. A. White ◽  
Z. Kipling
Keyword(s):  
Spatial Variability ◽  
General Circulation ◽  
Regional Scale ◽  
General Circulation Models ◽  
Satellite Observations ◽  
Scale Model ◽  
Convective Clouds ◽  
Aerosol Cloud ◽  
Wet Scavenging ◽  
Aerosol Properties

Abstract. Satellite studies of aerosol–cloud interactions usually make use of retrievals of both aerosol and cloud properties, but these retrievals are rarely spatially co-located. While it is possible to retrieve aerosol properties above clouds under certain circumstances, aerosol properties are usually only retrieved in cloud-free scenes. Generally, the smaller spatial variability of aerosols compared to clouds reduces the importance of this sampling difference. However, as precipitation generates an increase in spatial variability of aerosols, the imperfect co-location of aerosol and cloud property retrievals may lead to changes in observed aerosol–cloud–precipitation relationships in precipitating environments. In this work, we use a regional-scale model, satellite observations and reanalysis data to investigate how the non-coincidence of aerosol, cloud and precipitation retrievals affects correlations between them. We show that the difference in the aerosol optical depth (AOD)–precipitation relationship between general circulation models (GCMs) and satellite observations can be explained by the wet scavenging of aerosol. Using observations of the development of precipitation from cloud regimes, we show how the influence of wet scavenging can obscure possible aerosol influences on precipitation from convective clouds. This obscuring of aerosol–cloud–precipitation interactions by wet scavenging suggests that even if GCMs contained a perfect representation of aerosol influences on convective clouds, the difficulty of separating the "clear-sky" aerosol from the "all-sky" aerosol in GCMs may prevent them from reproducing the correlations seen in satellite data.

scholarly journals Investigation of Regional and Seasonal Variations in Marine Boundary Layer Cloud Properties from MODIS Observations

2008 ◽  
Vol 21 (19) ◽  
pp. 4955-4973 ◽  
Author(s):  
Michael P. Jensen ◽  
Andrew M. Vogelmann ◽  
William D. Collins ◽  
Guang J. Zhang ◽  
Edward P. Luke
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Test Bed ◽  
Liquid Water Path ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Peak Versus

Abstract To aid in understanding the role that marine boundary layer (MBL) clouds play in climate and assist in improving their representations in general circulation models (GCMs), their long-term microphysical and macroscale characteristics are quantified using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the National Aeronautics and Space Administration’s (NASA’s) Terra satellite. Six years of MODIS pixel-level cloud products are used from oceanic study regions off the west coasts of California, Peru, the Canary Islands, Angola, and Australia where these cloud types are common. Characterizations are given for their organization (macroscale structure), the associated microphysical properties, and the seasonal dependencies of their variations for scales consistent with the size of a GCM grid box (300 km × 300 km). MBL mesoscale structure is quantified using effective cloud diameter CD, which is introduced here as a simplified measure of bulk cloud organization; it is straightforward to compute and provides descriptive information beyond that offered by cloud fraction. The interrelationships of these characteristics are explored while considering the influences of the MBL state, such as the occurrence of drizzle. Several commonalities emerge for the five study regions. MBL clouds contain the best natural examples of plane-parallel clouds, but overcast clouds occur in only about 25% of the scenes, which emphasizes the importance of representing broken MBL cloud fields in climate models (that are subgrid scale). During the peak months of cloud occurrence, mesoscale organization (larger CD) increases such that the fractions of scenes characterized as “overcast” and “clumped” increase at the expense of the “scattered” scenes. Cloud liquid water path and visible optical depth usually trend strongly with CD, with the largest values occurring for scenes that are drizzling. However, considerable interregional differences exist in these trends, suggesting that different regression functionalities exist for each region. For peak versus off-peak months, the fraction of drizzling scenes (as a function of CD) are similar for California and Angola, which suggests that a single probability distribution function might be used for their drizzle occurrence in climate models. The patterns are strikingly opposite for Peru and Australia; thus, the contrasts among regions may offer a test bed for model simulations of MBL drizzle occurrence.

scholarly journals An automatic and effective parameter optimization method for model tuning

2015 ◽  
Vol 8 (11) ◽  
pp. 3579-3591 ◽  
Author(s):  
T. Zhang ◽  
L. Li ◽  
Y. Lin ◽  
W. Xue ◽  
F. Xie ◽  
...  
Keyword(s):  
Simplex Method ◽  
General Circulation ◽  
Model Development ◽  
Model Performance ◽  
Parameter Tuning ◽  
General Circulation Models ◽  
Development Stage ◽  
Optimum Combination ◽  
Downhill Simplex Method ◽  
Downhill Simplex

Abstract. Physical parameterizations in general circulation models (GCMs), having various uncertain parameters, greatly impact model performance and model climate sensitivity. Traditional manual and empirical tuning of these parameters is time-consuming and ineffective. In this study, a "three-step" methodology is proposed to automatically and effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. Different from the traditional optimization methods, two extra steps, one determining the model's sensitivity to the parameters and the other choosing the optimum initial value for those sensitive parameters, are introduced before the downhill simplex method. This new method reduces the number of parameters to be tuned and accelerates the convergence of the downhill simplex method. Atmospheric GCM simulation results show that the optimum combination of these parameters determined using this method is able to improve the model's overall performance by 9 %. The proposed methodology and software framework can be easily applied to other GCMs to speed up the model development process, especially regarding unavoidable comprehensive parameter tuning during the model development stage.

scholarly journals A double ITCZ phenomenology of wind errors in the equatorial Atlantic in seasonal forecasts with ECMWF models

2019 ◽  
Vol 19 (17) ◽  
pp. 11383-11399
Author(s):  
Jonathan K. P. Shonk ◽  
Teferi D. Demissie ◽  
Thomas Toniazzo
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Marine Boundary Layer ◽  
General Circulation Models ◽  
Equatorial Atlantic ◽  
Seasonal Forecasts ◽  
Coupled Models ◽  
Trade Winds ◽  
Double Itcz ◽  
Rapid Transition

Abstract. Modern coupled general circulation models produce systematic biases in the tropical Atlantic that hamper the reliability of long-range predictions. This study focuses on a common springtime westerly wind bias in the equatorial Atlantic in seasonal hindcasts from two coupled models – ECMWF System 4 and EC-Earth v2.3 – and in hindcasts also based on System 4, but with prescribed sea-surface temperatures. The development of the equatorial westerly bias in early April is marked by a rapid transition from a wintertime easterly, cold tongue bias to a springtime westerly bias regime that displays a marked double intertropical convergence zone (ITCZ). The transition is a seasonal feature of the model climatology (independent of initialisation date) and is associated with a seasonal increase in rainfall where a second branch of the ITCZ is produced south of the Equator. Excess off-equatorial convergence redirects the trade winds away from the Equator. Based on arguments of temporal coincidence, the results of our analysis contrast with those from previous work, and alleged causes hereto identified as the likely cause of the equatorial westerly bias in other models must be discarded. Quite in general, we find no evidence of remote influences on the development of the springtime equatorial bias in the Atlantic in the IFS-based models. Limited evidence however is presented that supports the hypothesis of an incorrect representation of the meridional equatorward flow in the marine boundary layer of the southern Atlantic as a contributing factor. Erroneous dynamical constraints on the flow upstream of the Equator may generate convergence and associated rainfall south of the Equator. This directs attention to the representation of the properties of the subtropical boundary layer as a potential source for the double ITCZ bias.

scholarly journals Weak Land–Atmosphere Coupling Strength in HadAM3: The Role of Soil Moisture Variability

2005 ◽  
Vol 6 (5) ◽  
pp. 670-680 ◽  
Author(s):  
David M. Lawrence ◽  
Julia M. Slingo
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Coupling Strength ◽  
General Circulation ◽  
General Circulation Models ◽  
Soil Conditions ◽  
Wide Range ◽  
The Impact ◽  
Soil Moisture Variability ◽  
Moisture Variability

Abstract A recent model intercomparison, the Global Land–Atmosphere Coupling Experiment (GLACE), showed that there is a wide range of land–atmosphere coupling strengths, or the degree that soil moisture affects the generation of precipitation, amongst current atmospheric general circulation models (AGCMs). Coupling strength in the Hadley Centre atmosphere model (HadAM3) is among the weakest of all AGCMs considered in GLACE. Reasons for the weak HadAM3 coupling strength are sought here. In particular, the impact of pervasive saturated soil conditions and low soil moisture variability on coupling strength is assessed. It is found that when the soil model is modified to reduce the occurrence of soil moisture saturation and to encourage soil moisture variability, the soil moisture–precipitation feedback remains weak, even though the relationship between soil moisture and evaporation is strengthened. Composites of the diurnal cycle, constructed relative to soil moisture, indicate that the model can simulate key differences in boundary layer development over wet versus dry soils. In particular, the influence of wet or dry soil on the diurnal cycles of Bowen ratio, boundary layer height, and total heat flux are largely consistent with the observed influence of soil moisture on these properties. However, despite what appears to be successful simulation of these key aspects of the indirect soil moisture–precipitation feedback, the model does not capture observed differences for wet and dry soils in the daily accumulation of boundary layer moist static energy, a crucial feature of the feedback mechanism.

Application of Cluster Analysis to Climate Model Performance Metrics

2011 ◽  
Vol 50 (8) ◽  
pp. 1666-1675 ◽  
Author(s):  
Satoru Yokoi ◽  
Yukari N. Takayabu ◽  
Kazuaki Nishii ◽  
Hisashi Nakamura ◽  
Hirokazu Endo ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
General Circulation ◽  
Performance Metrics ◽  
Climate Model ◽  
Model Performance ◽  
General Circulation Models ◽  
Clustering Methods ◽  
Dynamic Constraints ◽  
Overall Performance

AbstractThe overall performance of general circulation models is often investigated on the basis of the synthesis of a number of scalar performance metrics of individual models that measure the reproducibility of diverse aspects of the climate. Because of physical and dynamic constraints governing the climate, a model’s performance in simulating a certain aspect of the climate is sometimes related closely to that in simulating another aspect, which results in significant intermodel correlation between performance metrics. Numerous metrics and intermodel correlations may cause a problem in understanding the evaluation and synthesizing the metrics. One possible way to alleviate this problem is to group the correlated metrics beforehand. This study attempts to use simple cluster analysis to group 43 performance metrics. Two clustering methods, the K-means and the Ward methods, yield considerably similar clustering results, and several aspects of the results are found to be physically and dynamically reasonable. Furthermore, the intermodel correlation between the cluster averages is considerably lower than that between the metrics. These results suggest that the cluster analysis is helpful in obtaining the appropriate grouping. Applications of the clustering results are also discussed.

scholarly journals A Numerical Study of Early Summer Regional Climate and Weather over LSA-East. Part I: Model Implementation and Verification

2003 ◽  
Vol 131 (8) ◽  
pp. 1895-1909 ◽  
Author(s):  
Da-Lin Zhang ◽  
Wei-Zhong Zheng ◽  
Yong-Kang Xue
Keyword(s):  
General Circulation ◽  
Mesoscale Model ◽  
Numerical Study ◽  
Regional Climate ◽  
General Circulation Models ◽  
Shortwave Radiation ◽  
Surface Boundary ◽  
Diurnal Changes ◽  
Low Level ◽  
Weather Events

Abstract The Pennsylvania State University–NCAR Mesoscale Model (MM5) and a simplified simple biosphere (SSiB) scheme are modified and then coupled to study various regional climate and weather problems. These modifications include correcting the moisture and cloud hydrometeor fields to ensure the mass conservation; incorporating the effects of dissipative heating to ensure total energy conservation; decoupling soil and vegetation types in specifying various surface parameters; and eliminating the shortwave radiation reaching the surface at points where deep convection occurs. A 30-day integration of June 1998 over the Midwest states was used to examine the model's capability in capturing the observed wet regional climate and the passage of several mesoscale weather events. It is found that the coupled model reproduces the distribution and magnitude of monthly accumulated precipitation, the time series of area-integrated precipitation, surface pressures, and diurnal changes in surface temperatures, low-level winds and precipitation, as well as the evolution of precipitation systems across the central United States. In particular, the model reproduces well many daily weather events, including the distribution and intensity of low-level temperature and pressure perturbations and precipitation, even up to a month. The results suggest that the daily temperature, clouds, and precipitation events from the weekly to monthly scales, as well as their associated regional climate phenomena, could be reasonably simulated if the surface, boundary layer, radiation, and convective processes are realistically parameterized, and the large-scale forcing could be reasonably provided by general circulation models.

The Simulation of Moisture Processes in Climate Models and Climate Sensitivity

2005 ◽  
Vol 18 (13) ◽  
pp. 2172-2193 ◽  
Author(s):  
Haijun Hu ◽  
Robert J. Oglesby ◽  
Susan Marshall
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Atmospheric Moisture ◽  
Model Sensitivity ◽  
Surface Warming ◽  
Wide Range ◽  
Modeling Techniques ◽  
Moisture Performance

Abstract General circulation models (GCMs) designed for projecting climatic change have exhibited a wide range of sensitivity. Therefore, projected surface warming with increasing CO2 varies considerably depending on which model is used. Despite notable advances in computing power and modeling techniques that have occurred over the past decade, uncertainties of model sensitivity have not been reduced accordingly. The sensitivity issue is investigated by examining two GCMs of very different modeling techniques and sensitivity, with attention focused on how moisture processes are treated in these models, how moisture simulations are affected by these processes, and how well these simulations compare to the observed and analyzed moisture field. Both GCMs predict increases of atmospheric moisture with doubled CO2, but the increment predicted by one model is substantially higher (approximately twice) than that predicted by the other. This same difference is seen in responses of the boundary layer diffusive moistening rate. Calculations with a radiative–convective model indicate that the differences in predicted equilibrium atmospheric moisture, including both column amount and vertical distribution, have contributed to the largest differences in model sensitivity between the two models. We argue that in order for climate models to be credible for prediction purposes, they must possess credible skills of simulating surface and boundary layer processes, which likely holds the key to overall moisture performance, its response to external forcing, and in turn to model sensitivity.

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