scholarly journals Evaluation of Cloud Liquid Water Path Trends Using a Multidecadal Record of Passive Microwave Observations

2017 ◽  
Vol 30 (15) ◽  
pp. 5871-5884 ◽  
Author(s):  
Andrew Manaster ◽  
Christopher W. O’Dell ◽  
Gregory Elsaesser

In this study, observed cloud liquid water path (LWP) trends from the Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP) dataset (1988–2014) are compared to trends computed from the temporally coincident records of 16 global climate models (GCMs) participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). For many regions, observed trend magnitudes are several times larger than the corresponding model mean trend magnitudes. Muted model mean trends are thought to be the result of cancellation effects arising from differing interannual variability characteristics and differences in model physics–dynamics. In most regions, the majority of modeled trends were statistically consistent with the observed trends. This was thought to be because of large estimated errors in both the observations and the models due to interannual variability. Over the southern oceans (south of 40°S latitude), general agreement between the observed trend and virtually all GCM trends is also found (about 1–2 g m−2 decade−1). Observed trends are also compared to those from the Atmospheric Model Intercomparison Project (AMIP). Like the CMIP5 models, the majority of modeled AMIP trends were statistically consistent with the observed trends. It was also found that, in regions where the AMIP model mean time series better captures observed interannual variability, it tends to better capture the magnitude of the observed trends.

2013 ◽  
Vol 26 (11) ◽  
pp. 3823-3845 ◽  
Author(s):  
Axel Lauer ◽  
Kevin Hamilton

Abstract Clouds are a key component of the climate system affecting radiative balances and the hydrological cycle. Previous studies from the Coupled Model Intercomparison Project phase 3 (CMIP3) showed quite large biases in the simulated cloud climatology affecting all GCMs as well as a remarkable degree of variation among the models that represented the state of the art circa 2005. Here the progress that has been made in recent years is measured by comparing mean cloud properties, interannual variability, and the climatological seasonal cycle from the CMIP5 models with satellite observations and with results from comparable CMIP3 experiments. The focus is on three climate-relevant cloud parameters: cloud amount, liquid water path, and cloud radiative forcing. The comparison shows that intermodel differences are still large in the Coupled Model Intercomparison Project phase 5 (CMIP5) simulations, and reveals some small improvements of particular cloud properties in some regions in the CMIP5 ensemble over CMIP3. In CMIP5 there is an improved agreement of the modeled interannual variability of liquid water path and of the modeled longwave cloud forcing over mid- and high-latitude oceans with observations. However, the differences in the simulated cloud climatology from CMIP3 and CMIP5 are generally small, and there is very little to no improvement apparent in the tropical and subtropical regions in CMIP5. Comparisons of the results from the coupled CMIP5 models with their atmosphere-only versions run with observed SSTs show remarkably similar biases in the simulated cloud climatologies. This suggests the treatments of subgrid-scale cloud and boundary layer processes are directly implicated in the poor performance of current GCMs in simulating realistic cloud fields.


2001 ◽  
Vol 106 (D13) ◽  
pp. 14485-14500 ◽  
Author(s):  
James C. Liljegren ◽  
Eugene E. Clothiaux ◽  
Gerald G. Mace ◽  
Seiji Kato ◽  
Xiquan Dong

2004 ◽  
Vol 17 (24) ◽  
pp. 4760-4782 ◽  
Author(s):  
Manajit Sengupta ◽  
Eugene E. Clothiaux ◽  
Thomas P. Ackerman

Abstract A 4-yr climatology (1997–2000) of warm boundary layer cloud properties is developed for the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) site. Parameters in the climatology include cloud liquid water path, cloud-base height, and surface solar flux. These parameters are retrieved from measurements produced by a dual-channel microwave radiometer, a millimeter-wave cloud radar, a micropulse lidar, a Belfort ceilometer, shortwave radiometers, and atmospheric temperature profiles amalgamated from multiple sources, including radiosondes. While no significant interannual differences are observed in the datasets, there are diurnal variations with nighttime liquid water paths consistently higher than daytime values. The summer months of June, July, and August have the lowest liquid water paths and the highest cloud-base heights. Model outputs of cloud liquid water paths from the European Centre for Medium-Range Weather Forecasts (ECMWF) model and the Eta Model for 104 model output location time series (MOLTS) stations in the environs of the SGP central facility are compared to observations. The ECMWF and MOLTS median liquid water paths are greater than 3 times the observed values. The MOLTS data show lower liquid water paths in summer, which is consistent with observations, while the ECMWF data exhibit the opposite tendency. A parameterization of normalized cloud forcing that requires only cloud liquid water path and solar zenith angle is developed from the observations. The parameterization, which has a correlation coefficient of 0.81 with the observations, provides estimates of surface solar flux that are comparable to values obtained from explicit radiative transfer calculations based on plane-parallel theory. This parameterization is used to estimate the impact on the surface solar flux of differences in the liquid water paths between models and observations. Overall, there is a low bias of 50% in modeled normalized cloud forcing resulting from the excess liquid water paths in the two models. Splitting the liquid water path into two components, cloud thickness and liquid water content, shows that the higher liquid water paths in the model outputs are primarily a result of higher liquid water contents, although cloud thickness may a play a role, especially for the ECMWF model results.


2008 ◽  
Vol 21 (8) ◽  
pp. 1721-1739 ◽  
Author(s):  
Christopher W. O’Dell ◽  
Frank J. Wentz ◽  
Ralf Bennartz

Abstract This work describes a new climatology of cloud liquid water path (LWP), termed the University of Wisconsin (UWisc) climatology, derived from 18 yr of satellite-based passive microwave observations over the global oceans. The climatology is based on a modern retrieval methodology applied consistently to the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer (AMSR) for Earth Observing System (EOS) (AMSR-E) microwave sensors on eight different satellite platforms, beginning in 1988 and continuing through 2005. It goes beyond previously published climatologies by explicitly solving for the diurnal cycle of cloud liquid water by providing statistical error estimates, and includes a detailed discussion of possible systematic errors. A novel methodology for constructing the climatology is used in which a mean monthly diurnal cycle as well as monthly means of the liquid water path are derived simultaneously from the data on a 1° grid; the methodology also produces statistical errors for these quantities, which decrease toward the end of the time record as the number of observations increases. The derived diurnal cycles are consistent with previous findings in the tropics, but are also derived for higher latitudes and contain more information than in previous studies. The new climatology exhibits differences with previous observationally based climatologies and is found to be more consistent with the 40-yr ECMWF Re-Analysis (ERA-40) than are the previous climatologies. Potential systematic errors of the order of 15%–30% or higher exist in the LWP climatology. A previously unexplored source of systematic error is caused by the assumption that all microwave-based retrievals of LWP must make regarding the partitioning of cloud water and rainwater, which cannot be determined using microwave observations alone. The potentially large systematic errors that result may hamper the usefulness of microwave-based climatologies of both cloud liquid water and especially rain rate, particularly in certain regions of the tropics and midlatitudes where the separation of rain from liquid cloud water is most critical.


Sign in / Sign up

Export Citation Format

Share Document