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Klein, Stephen A.

Publications and source records attributed to Klein, Stephen A..

9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels

Abstract. The cloud radiative kernel method is a popular approach to quantify cloud feedbacks and rapid cloud adjustments to increased CO2 concentrations and to partition contributions from changes in cloud amount, altitude, and optical depth. However, because this method relies on cloud property histograms derived from passive satellite sensors or produced by passive satellite simulators in models, changes in obscuration of lower-level clouds by upper-level clouds can cause apparent low-cloud feedbacks and adjustments, even in the absence of changes in lower-level cloud properties. Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. Given that the methodology for diagnosing cloud feedbacks and adjustments using cloud radiative kernels has evolved over several papers, and obscuration effects have only occasionally been considered in recent papers, this paper serves to establish recommended best practices and to provide a corresponding code base for community use.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Well Does the DOE Global Storm Resolving Model Simulate Clouds and Precipitation Over the Amazon?

This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Taking Climate Model Evaluation to the Next Level

Earth system models are complex and represent a large number of processes, resulting in a persistent spread across climate projections for a given future scenario. Owing to different model performances against observations and the lack of independence among models, there is now evidence that giving equal weight to each available model projection is suboptimal. This Perspective discusses newly developed tools that facilitate a more rapid and comprehensive evaluation of model simulations with observations, process-based emergent constraints that are a promising way to focus evaluation on the observations most relevant to climate projections, and advanced methods for model weighting. These approaches are needed to distil the most credible information on regional climate changes, impacts, and risks for stakeholders and policy-makers.

Eyring, Veronika↗
NASA NTRS2016

The Impact of ARM on Climate Modeling

Climate models are among humanity's most ambitious and elaborate creations. They are designed to simulate the interactions of the atmosphere, ocean, land surface, and cryosphere on time scales far beyond the limits of deterministic predictability, and including the effects of time-dependent external forcings. The processes involved include radiative transfer, fluid dynamics, microphysics, and some aspects of geochemistry, biology, and ecology. The models explicitly simulate processes on spatial scales ranging from the circumference of the Earth down to one hundred kilometers or smaller, and implicitly include the effects of processes on even smaller scales down to a micron or so. The atmospheric component of a climate model can be called an atmospheric global circulation model (AGCM). In an AGCM, calculations are done on a three-dimensional grid, which in some of today's climate models consists of several million grid cells. For each grid cell, about a dozen variables are time-stepped as the model integrates forward from its initial conditions. These so-called prognostic variables have special importance because they are the only things that a model remembers from one time step to the next; everything else is recreated on each time step by starting from the prognostic variables and the boundary conditions. The prognostic variables typically include information about the mass of dry air, the temperature, the wind components, water vapor, various condensed-water species, and at least a few chemical species such as ozone. A good way to understand how climate models work is to consider the lengthy and complex process used to develop one. Lets imagine that a new AGCM is to be created, starting from a blank piece of paper. The model may be intended for a particular class of applications, e.g., high-resolution simulations on time scales of a few decades. Before a single line of code is written, the conceptual foundation of the model must be designed through a creative envisioning that starts from the intended application and is based on current understanding of how the atmosphere works and the inventory of mathematical methods available.

atmospheric circulation↗
NASA NTRS2015

External Influences on Modeled and Observed Cloud Trends

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

clouds (meteorology)↗
NASA NTRS1993

The seasonal cycle of low stratiform clouds

The seasonal cycle of low stratiform clouds is studied using data from surface-based cloud climatologies. The impact of low clouds on the radiation budget is illustrated by comparison of data from the Earth Radiation Budget Experiment with the cloud climatologies. Ten regions of active stratocumulus convection are identified. These regions fall into four categories: subtropical marine, midlatitude marine, Arctic stratus, and Chinese stratus. With the exception of the Chinese region, all the regions with high amounts of stratus clouds are over the oceans. In all regions except the Arctic, the season of maximum stratus corresponds to the season of greatest lower-troposphere static stability. Interannual variations in stratus cloud amount also are related to changes in static stability. A linear analysis indicates that a 6 percent increase in stratus fractional area coverage is associated with each 1 C increase in static stability. Over midlatitude oceans, sky-obscuring fog is a large component of the summertime stratus amount. The amount of fog appears to be related to warm advection across sharp gradients of SST.

Klein, Stephen A.↗
NASA NTRS1993

Spurious changes in the ISCCP dataset

The International Satellite Cloud Climatology Project (ISCCP) data set for July 1983-December 1990 exhibits a long term decrease in mean cloud optical depth and mean cloudtop temperature which is large compared to the mean for this period. It is here suggested that this decrease is an artifact of incomplete normalization of the visible channel on successive polar orbiters employed as the ISCCP's calibration standard; more accurate calibration techniques are required for the establishment of long-term climate trends.

Klein, Stephen A.↗
NASA NTRS1991

The influence of dynamics on two-dimensional model results - Simulations of C-14 and stratospheric aircraft NO(x) injections

The influence of dynamics on model results is investigated via a 2D photochemical model. Three representations of atmospheric transport are tested in order to simulate total ozone and C-14 amounts after nuclear tests in the early 1960s. Three scenarios of NO(x) injections from a proposed fleet of stratospheric aircraft and their effects on ozone are simulated. The three dynamical formulations used are Dynamics A, a base dynamics used in previous work with this model; Dynamics B, a strong circulation dynamics discussed by Jackman et al. (1989); and Dynamics C, the dynamics used by Shia et al. (1989). The advective component of the stratosphere to the troposphere mass exchange rate is largest for Dynamics B (5.8 x 10 exp 17 kg/yr) and smallest for Dynamics C (1.4 x 10 exp 17 kg/yr), with the advective strat/trop exchange rate for Dynamics A (2.4 x 10 exp 17 kg/yr) being these two extremes. Ozone depletion from NO(x) injections of stratospheric aircraft showed a strong sensitivity to dynamics.

Jackman, Charles H.↗