Comparisons of satellites liquid water estimates to ECMWF and GMAO analyses, 20th century IPCC AR4 climate simulations, and GCM simulations

Li, Jui‐Lin F.; Waliser, Duane E.; Woods, Christopher P.; Teixeira, J.; Bacmeister, Julio T.; Chern, J.; Shen, Bo-Wen; Tompkins, Adrian M.; Tao, Wei‐Kuo; Köhler, Martin

doi:10.1029/2008gl035427

Cited by 62 publications

(70 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The variability of the LWP in the SP-CAM and GFDL AM appear slightly smaller than the satellite estimates. In contrast with the discussion by Li et al (2008), there is rough agreement between the GCMs and the satellite estimates of LWP in RICO-like conditions. This might suggest that the GCMs' representation of liquid water is more reliable in trade-wind regimes than for the planet as a whole, though there remains more than a factor of two in the spread of these GCMs within this regime.…”

Section: Zoom In On Rico Conditionscontrasting

confidence: 46%

See 1 more Smart Citation

Revealing differences in GCM representations of low clouds

2009

View full text Add to dashboard Cite

Aquaplanet configurations of four atmospheric general circulation models (GCMs) are compared with standard, Earth-like configurations and observations. The focus here is on tropical, low-level clouds, which have been identified as important for estimates of climate sensitivity. Investigating the distribution of the monthly mean vertical velocity and lower-tropospheric stability, the aquaplanets are seen to capture the core of the distribution of the more Earth-like configurations, whose distributions are, in turn, similar to that of reanalysis data. By conditionally sampling over these distributions, low-cloud regimes are defined, separating shallow cumulus convection from stratocumulus. Within each regime, the GCMs produce similar large-scale environments, yet disparate depictions of the clouds. Aquaplanets lack stratocumulus because of their zonally symmetric boundary conditions, but produce extensive trade-wind regions populated by shallow cumulus clouds just like those in the Earth-like setting. The analysis shows that aquaplanets can be compared with observations, just as well as the Earth-like configuration, with the added ability to focus on particular regimes without complications from geographical or temporal biases.

show abstract

Section: Zoom In On Rico Conditionscontrasting

confidence: 46%

“…As with the other quantities, the aquaplanets exhibit LWP values similar to the Earth-like configurations. The apparent disagreement among models-and among different observing systems-has also been noted recently by Li et al (2008).…”

Section: Trade-wind Versus Stratocumulusmentioning

confidence: 93%

Revealing differences in GCM representations of low clouds

2009

View full text Add to dashboard Cite

show abstract

“…where e WS = 2 m·s −1 , e TCWV = 0.9 mm, e TCLW = 1 mm and e SST = 0.50 K. The uncertainties on the WS, TCVW and TCLW are best estimates based upon published validation results (see e.g., [47,[55][56][57][58]). The SST uncertainty is derived from a comparison against Argo drifting buoys, using the MMD (see Section 3.3).…”

Section: Initial Oe Setupmentioning

confidence: 99%

Optimal Estimation of Sea Surface Temperature from AMSR-E

et al. 2018

View full text Add to dashboard Cite

The Optimal Estimation (OE) technique is developed within the European Space AgencyClimate Change Initiative (ESA-CCI) to retrieve subskin Sea Surface Temperature (SST) from AQUA's Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E). A comprehensive matchup database with drifting buoy observations is used to develop and test the OE setup. It is shown that it is essential to update the first guess atmospheric and oceanic state variables and to perform several iterations to reach an optimal retrieval. The optimal number of iterations is typically three to four in the current setup. In addition, updating the forward model, using a multivariate regression model is shown to improve the capability of the forward model to reproduce the observations. The average sensitivity of the OE retrieval is 0.5 and shows a latitudinal dependency with smaller sensitivity for cold waters and larger sensitivity for warmer waters. The OE SSTs are evaluated against drifting buoy measurements during 2010. The results show an average difference of 0.02 K with a standard deviation of 0.47 K when considering the 64% matchups, where the simulated and observed brightness temperatures are most consistent. The corresponding mean uncertainty is estimated to 0.48 K including the in situ and sampling uncertainties. An independent validation against Argo observations from 2009 to 2011 shows an average difference of 0.01 K, a standard deviation of 0.50 K and a mean uncertainty of 0.47 K, when considering the best 62% of retrievals. The satellite versus in situ discrepancies are highest in the dynamic oceanic regions due to the large satellite footprint size and the associated sampling effects. Uncertainty estimates are available for all retrievals and have been validated to be accurate. They can thus be used to obtain very good retrieval results. In general, the results from the OE retrieval are very encouraging and demonstrate that passive microwave observations provide a valuable alternative to infrared satellite observations for retrieving SST.

show abstract

“…As mentioned in the previous section, some of the above LWP derivations are contaminated by the presence of precipitation (Li et al, 2008). In particular, radar reflectivity is highly sensitive to drop size (∼D 6 where D is drop diameter) , thus making radar-derived LWP highly sensitive to the larger precipitation drops.…”

Section: Satellite Intercomparison Of Lwpmentioning

confidence: 99%

A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

et al. 2010

View full text Add to dashboard Cite

Abstract. Here, liquid water path (LWP), cloud fraction, cloud top height, and cloud base height retrieved by a suite of A-train satellite instruments (the CPR aboard CloudSat, CALIOP aboard CALIPSO, and MODIS aboard Aqua) are compared to ship observations from research cruises made in 2001 and 2003-2007 into the stratus/stratocumulus deck over the southeast Pacific Ocean. It is found that CloudSat radar-only LWP is generally too high over this region and the CloudSat/CALIPSO cloud bases are too low. This results in a relationship (LWP∼h 9 ) between CloudSat LWP and CALIPSO cloud thickness (h) that is very different from the adiabatic relationship (LWP∼h 2 ) from in situ observations. Such biases can be reduced if LWPs suspected to be contaminated by precipitation are eliminated, as determined by the maximum radar reflectivity Z max >−15 dBZ in the apparent lower half of the cloud, and if cloud bases are determined based upon the adiabatically-determined cloud thickness (h∼LWP 1/2 ). Furthermore, comparing results from a global model (CAM3.1) to ship observations reveals that, while the simulated LWP is quite reasonable, the model cloud is too thick and too low, allowing the model to have LWPs that are almost independent of h. This model can also obtain a reasonable diurnal cycle in LWP and cloud fraction at a location roughly in the centre of this region (20 • S, 85 • W) but has an opposite diurnal cycle to those observed aboard ship at a location closer to the coast (20 • S, 75 • W). The diurnal cycle at the latter location is slightly improved in the newest version of the model (CAM4). However, the simulated clouds remain too thick and too low, as cloud bases are usually at or near the surface.

show abstract

Comparisons of satellites liquid water estimates to ECMWF and GMAO analyses, 20th century IPCC AR4 climate simulations, and GCM simulations

Cited by 62 publications

References 8 publications

Revealing differences in GCM representations of low clouds

Revealing differences in GCM representations of low clouds

Optimal Estimation of Sea Surface Temperature from AMSR-E

A comparison of ship and satellite measurements of cloud properties with global climate model simulations in the southeast Pacific stratus deck

Contact Info

Product

Resources

About