Differences in tropical high clouds among reanalyses: origins and radiative impacts

Abstract

Abstract. We examine differences among reanalysis high-cloud products in the tropics, assess the impacts of these differences on radiation budgets at the top of the atmosphere and within the tropical upper troposphere and lower stratosphere (UTLS), and discuss their possible origins in the context of the reanalysis models. We focus on the ERA5 (fifth-generation European Centre for Medium-range Weather Forecasts – ECMWF – reanalysis), ERA-Interim (ECMWF Interim Reanalysis), JRA-55 (Japanese 55-year Reanalysis), MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, Version 2), and CFSR/CFSv2 (Climate Forecast System Reanalysis/Climate Forecast System Version 2) reanalyses. As a general rule, JRA-55 produces the smallest tropical high-cloud fractions and cloud water contents among the reanalyses, while MERRA-2 produces the largest. Accordingly, long-wave cloud radiative effects are relatively weak in JRA-55 and relatively strong in MERRA-2. Only MERRA-2 and ERA5 among the reanalyses produce tropical-mean values of outgoing long-wave radiation (OLR) close to those observed, but ERA5 tends to underestimate cloud effects, while MERRA-2 tends to overestimate variability. ERA5 also produces distributions of long-wave, short-wave, and total cloud radiative effects at the top of the atmosphere that are very consistent with those observed. The other reanalyses all exhibit substantial biases in at least one of these metrics, although compensation between the long-wave and short-wave effects helps to constrain biases in the total cloud radiative effect for most reanalyses. The vertical distribution of cloud water content emerges as a key difference between ERA-Interim and other reanalyses. Whereas ERA-Interim shows a monotonic decrease of cloud water content with increasing height, the other reanalyses all produce distinct anvil layers. The latter is in better agreement with observations and yields very different profiles of radiative heating in the UTLS. For example, whereas the altitude of the level of zero net radiative heating tends to be lower in convective regions than in the rest of the tropics in ERA-Interim, the opposite is true for the other four reanalyses. Differences in cloud water content also help to explain systematic differences in radiative heating in the tropical lower stratosphere among the reanalyses. We discuss several ways in which aspects of the cloud and convection schemes impact the tropical environment. Discrepancies in the vertical profiles of temperature and specific humidity in convective regions are particularly noteworthy, as these variables are directly constrained by data assimilation, are widely used, and feed back to convective behaviour through their relationships with thermodynamic stability.

Atmospheric tropical modes are important drivers of Sahelian springtime heatwaves

“…OLR in ERA5 is taken as the negative of the net top-of-atmosphere (TOA) thermal radiation. Wang et al (2017), Tall et al (2019), Wright et al (2020) and Hersbach et al (2020) assessed radiative fluxes in different products and found that ERA5 shows TOA fluxes (including OLR) that are very consistent with the observed. Using observed OLR data such as the daily interpolated data from the NOAA (Liebmann and Smith 1996) does not significantly alter the results obtained with ERA5 (not shown), making it suitable for the present study.…”

Inter-annual, seasonal and diurnal features of the cloud liquid water path over the land surface and various water bodies in Northern Europe as obtained from the satellite observations by the SEVIRI instrument in 2011–2017

“…It is interesting and important to compare the obtained statistical characteristics of the LWP land-sea gradient with the data provided by reanalyses. Wright et al (2020) note that, though cloud fields in reanalyses are essentially model products, many variables, which influence the cloud fields, are altered during the assimilation process. Therefore, detecting differences between the LWP gradient values obtained in experiments and provided by reanalyses can be valuable for identification of possible problems in reanalyses and for future model development.…”

Prediction skill of Sahelian heatwaves out to subseasonal lead times and importance of atmospheric tropical modes of variability

“…Furthermore, Gleixner et al (2020) showed that in ERA5, near-surface temperatures are less climatologically biased, and their interannual variability better represented than in ERA-Interim across Africa, including in the Sahel band. Similarly, Wang et al (2017), Tall et al (2019), Wright et al (2020) and Hersbach et al (2020) proved that ERA5 represents relatively well the observed OLR over the tropical domain, confirming its suitability as reference dataset for the analysis of tropical modes. The Berkeley Earth Surface Temperatures (BEST; Muller et al 2014;Rohde et al 2016) dataset is used as a second reference dataset to provide an independent evaluation of thermal indices (given that ERA5 is created using the same model as ENS-ext).…”