Showing papers by "William D. Collins published in 2017"

An independent assessment of anthropogenic attribution statements for recent extreme temperature and rainfall events

Abstract: The annual “State of the Climate” report, published in the Bulletin of the American Meteorological Society (BAMS), has included a supplement since 2011 composed of brief analyses of the human influence on recent major extreme weather events. There are now several dozen extreme weather events examined in these supplements, but these studies have all differed in their data sources as well as their approaches to defining the events, analyzing the events, and the consideration of the role of anthropogenic emissions. This study reexamines most of these events using a single analytical approach and a single set of climate model and observational data sources. In response to recent studies recommending the importance of using multiple methods for extreme weather event attribution, results are compared from these analyses to those reported in the BAMS supplements collectively, with the aim of characterizing the degree to which the lack of a common methodological framework may or may not influence overall ...

Diagnosing conditional anthropogenic contributions to heavy Colorado rainfall in September 2013

Abstract: The Colorado floods of September 2013 caused severe damage and fatalities, and resulted from prolonged heavy rainfall unusual for that time of year – both in its record-breaking amounts and associated weather systems. We investigate the possible role of anthropogenic climate change in this extreme event. The unusual hydrometeorology of the event, however, challenges standard frameworks for attributing extreme events to anthropogenic climate change, because they typically struggle to simulate and connect the large-scale meteorology associated with local weather processes. Therefore we instead employ a part dynamical modelling- part observational- based event attribution approach, which simulates regional Colorado rainfall conditional on boundary conditions prescribed from the observed synoptic-scale meteorology in September 2013 – and assumes these conditions would have been similar in the absence of anthropogenic forcing. Using this ‘conditional event attribution’ approach we find that our regional climate model simulations indicate that anthropogenic drivers increased the magnitude of heavy northeast Colorado rainfall for the wet week in September 2013 by 30%, with the occurrence probability of a week at least that wet increasing by at least a factor of 1.3. By comparing the convective and large-scale components of rainfall, we find that this increase resulted in part from the additional moisture-carrying capacity of a warmer atmosphere – allowing more intense local convective rainfall that induced a dynamical positive feedback in the existing larger scale moisture flow – and also in part from additional moisture transport associated with larger scale circulation change. Our approach precludes assessment of changes in the frequency of the observed synoptic meteorological conditions themselves, and thus does not assess the effect of anthropogenic climate drivers on the statistics of heavy Colorado rainfall events. However, tailoring analysis tools to diagnose particular aspects of localized extreme weather events, conditional on the observed large-scale meteorology, can prove useful for diagnosing the physical effects of anthropogenic climate change on severe weather events – especially given large uncertainties in assessments of anthropogenic driven changes in atmospheric circulation.

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Abstract: Significant feedbacks in energy, agriculture, land use and the carbon cycle are identified for the twenty-first century when climate impacts on land are factored into climate projections so as to allow for two-way interactions between human and Earth systems. Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration1. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing2,3. While historical data sets are available to inform past and current climate analyses4,5, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories6. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario7. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date1,8,9.

A New Paradigm for Diagnosing Contributions to Model Aerosol Forcing Error

Abstract: A new paradigm in benchmark absorption-scattering radiative transfer is presented that enables both the globally averaged and spatially resolved testing of climate model radiation parameterizations in order to uncover persistent sources of biases in the aerosol instantaneous radiative effect (IRE). A proof of concept is demonstrated with the Geophysical Fluid Dynamics Laboratory AM4 and Community Earth System Model 1.2.2 climate models. Instead of prescribing atmospheric conditions and aerosols, as in prior intercomparisons, native snapshots of the atmospheric state and aerosol optical properties from the participating models are used as inputs to an accurate radiation solver to uncover model-relevant biases. These diagnostic results show that the models' aerosol IRE bias is of the same magnitude as the persistent range cited (~1 W/m2) and also varies spatially and with intrinsic aerosol optical properties. The findings underscore the significance of native model error analysis and its dispositive ability to diagnose global biases, confirming its fundamental value for the Radiative Forcing Model Intercomparison Project.

Simultaneous characterization of mesoscale and convective-scale tropical rainfall extremes and their dynamical and thermodynamic modes of change

Abstract: The Superparameterized Community Atmosphere Model (SPCAM) is used to identify the dynamical and organizational properties of tropical extreme rainfall events on two scales. We compare the mesoscales resolved by General Circulation Models (GCMs) and the convective scales resolved by Cloud-Resolving Models (CRMs) to reassess and extend on previous results from GCMs and CRMs in radiative-convective equilibrium. We first show that the improved representation of subgridscale dynamics in SPCAM allows for a close agreement with the 7%/K Clausius-Clapeyron rate of increase in mesoscale extremes rainfall rates. Three contributions to changes in extremes are quantified and appear consistent in sign and relative magnitude with previous results. On mesoscales, the thermodynamic contribution (5.8%/K) and the contribution from mass flux increases (2%/K) enhance precipitation rates, while the upward displacement of the mass flux profile (-1.1%/K) offsets this increase. Convective-scale extremes behave similarly except that changes in mass flux are negligible due to a balance between greater numbers of strong updrafts and downdrafts and lesser numbers of weak updrafts. Extremes defined on these two scales behave as two independent sets of rainfall events, with different dynamics, geometries, and responses to climate change. In particular, the increases in mesoscale mass flux directly contribute to the intensification of mesoscale extreme rain, but do not seem to affect the increase in convective-scale rainfall intensities. These results motivate the need for better understanding the role of the large-scale forcing on the dynamical processes involved in the formation and intensification of heavy convective rainfall.

An intercomparison of GCM and RCM dynamical downscaling for characterizing the hydroclimatology of California and Nevada

Abstract: Dynamical downscaling is a widely used technique to properly capture regional surface heterogeneities that shape the local hydroclimatology. However, in the context of dynamical downscaling...

Spherical Harmonic Spectral Estimation on Arbitrary Grids

Abstract: This study explores the use of nonuniform fast spherical Fourier transforms on meteorological data that are arbitrarily distributed on the sphere The applicability of this methodology in the atmospheric sciences is demonstrated by estimating spectral coefficients for nontrivial subsets of reanalysis data on a uniformly spaced latitude–longitude grid, a global cloud resolving model on an icosahedral mesh with 3-km horizontal grid spacing, and for temperature anomalies from arbitrarily distributed weather stations over the United States A spectral correction technique is developed that can be used in conjunction with the inverse transform to yield data interpolated onto a uniformly spaced grid, with optional triangular truncation, at reduced computational cost compared to other variance conserving interpolation methods, such as kriging or natural spline interpolation The spectral correction yields information that can be used to deduce gridded observational biases not directly available from othe

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Abstract: © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing. While historical data sets are available to inform past and current climate analyses, assessments of future climate change have relied on projections of energy and land use from energy-economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low-mid-range forcing scenario. The feedbacks between climate-induced biospheric change and human system forcings to the climate system - demonstrated here - are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy-economic models to ESMs used to date.