Kirsten L. Findell

Modeled Impact of Anthropogenic Land Cover Change on Climate

Abstract Equilibrium experiments with the Geophysical Fluid Dynamics Laboratory’s climate model are used to investigate the impact of anthropogenic land cover change on climate. Regions of altered land cover include large portions of Europe, India, eastern China, and the eastern United States. Smaller areas of change are present in various tropical regions. This study focuses on the impacts of biophysical changes associated with the land cover change (albedo, root and stomatal properties, roughness length), which is almost exclusively a conversion from forest to grassland in the model; the effects of irrigation or other water management practices and the effects of atmospheric carbon dioxide changes associated with land cover conversion are not included in these experiments. The model suggests that observed land cover changes have little or no impact on globally averaged climatic variables (e.g., 2-m air temperature is 0.008 K warmer in a simulation with 1990 land cover compared to a simulation with poten...

Weak Simulated Extratropical Responses to Complete Tropical Deforestation

The Geophysical Fluid Dynamics Laboratory atmosphere–land model version 2 (AM2/LM2) coupled to a 50-m-thick slab ocean model has been used to investigate remote responses to tropical deforestation. Magnitudes and significance of differences between a control run and a deforested run are assessed through comparisons of 50-yr time series, accounting for autocorrelation and field significance. Complete conversion of the broadleaf evergreen forests of South America, central Africa, and the islands of Oceania to grasslands leads to highly significant local responses. In addition, a broad but mild warming is seen throughout the tropical troposphere (0.2°C between 700 and 150 mb), significant in northern spring and summer. However, the simulation results show very little statistically significant response beyond the Tropics. There are no significant differences in any hydroclimatic variables (e.g., precipitation, soil moisture, evaporation) in either the northern or the southern extratropics. Small but statistically significant local differences in some geopotential height and wind fields are present in the southeastern Pacific Ocean. Use of the same statistical tests on two 50-yr segments of the control run show that the small but significant extratropical differences between the deforested run and the control run are similar in magnitude and area to the differences between nonoverlapping segments of the control run. These simulations suggest that extratropical responses to complete tropical deforestation are unlikely to be distinguishable from natural climate variability.

An enhanced model of land water and energy for global hydrologic and earth-system studies

AbstractLM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and pro...

Regional and Global Impacts of Land Cover Change and Sea Surface Temperature Anomalies

The atmospheric and land components of the Geophysical Fluid Dynamics Laboratorys (GFDLs) Cli- mate Model version 2.1 (CM2.1) is used with climatological sea surface temperatures (SSTs) to investigate the relative climatic impacts of historical anthropogenic land cover change (LCC) and realistic SST anom- alies. The SST forcing anomalies used are analogous to signals induced by El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the background global warming trend. Coherent areas of LCC are represented throughout much of central and eastern Europe, northern India, southeastern China, and on either side of the ridge of the Appalachian Mountains in North America. Smaller areas of change are present in various tropical regions. The land cover changes in the model are almost exclusively a conversion of forests to grasslands. Model results show that, at the global scale, the physical impacts of LCC on temperature and rainfall are less important than large-scale SST anomalies, particularly those due to ENSO. However, in the regions where the land surface has been altered, the impact of LCC can be equally or more important than the SST forcing patterns in determining the seasonal cycle of the surface water and energy balance. Thus, this work provides a context for the impacts of LCC on climate: namely, strong regional-scale impacts that can sig- nificantly change globally averaged fields but that rarely propagate beyond the disturbed regions. This suggests that proper representation of land cover conditions is essential in the design of climate model experiments, particularly if results are to be used for regional-scale assessments of climate change impacts.

Impact of Soil Moisture–Atmosphere Interactions on Surface Temperature Distribution

AbstractUnderstanding how different physical processes can shape the probability distribution function (PDF) of surface temperature, in particular the tails of the distribution, is essential for the attribution and projection of future extreme temperature events. In this study, the contribution of soil moisture–atmosphere interactions to surface temperature PDFs is investigated. Soil moisture represents a key variable in the coupling of the land and atmosphere, since it controls the partitioning of available energy between sensible and latent heat flux at the surface. Consequently, soil moisture variability driven by the atmosphere may feed back onto the near-surface climate—in particular, temperature. In this study, two simulations of the current-generation Geophysical Fluid Dynamics Laboratory (GFDL) Earth System Model, with and without interactive soil moisture, are analyzed in order to assess how soil moisture dynamics impact the simulated climate. Comparison of these simulations shows that soil moist...

Precipitation Sensitivity to Surface Heat Fluxes over North America in Reanalysis and Model Data

A new methodology for assessing the impact of surface heat fluxes on precipitation is applied to data from the North American Regional Reanalysis (NARR) and to output from the Geophysical Fluid Dynamics Laboratory’s Atmospheric Model 2.1 (AM2.1). The method assesses the sensitivity of afternoon convective rainfall frequency and intensity to the late-morning partitioning of latent and sensible heating, quantified in terms of evaporative fraction (EF). Over North America, both NARR and AM2.1 indicate sensitivity of convective rainfall triggering to EF but no appreciable influence of EF on convective rainfall amounts. Functional relationships between the triggering feedback strength (TFS) metric and mean EF demonstrate the occurrence of stronger couplingfor meanEFintherangeof0.6to 0.8. To leadingorder, AM2.1exhibits spatial distributions and seasonality of the EF impact on triggering resembling those seen in NARR: rainfall probability increases with higher EF over the eastern United States and Mexico and peaks in Northern Hemisphere summer. Over those regions, the impact of EF variability on afternoon rainfall triggering in summer can explain up to 50% of seasonal rainfall variability. However, the AM2.1 metrics also exhibit some features not present in NARR, for example, strong coupling extending northwestward from the central Great Plains into Canada. Sources of disagreement may include model hydroclimatic biases that affect the mean patterns and variability of surface flux partitioning, withEF variability typically much lower in NARR. Finally, the authors also discuss the consistency of their results with other assessments of land‐precipitation coupling obtained from different methodologies.

A Probabilistic Bulk Model of Coupled Mixed Layer and Convection. Part II: Shallow Convection Case

The probabilistic bulk convection model (PBCM) developed in a companion paper is here extended to shallow nonprecipitating convection. The PBCM unifies the clear-sky and shallow convection boundary layer regimes by obtaining mixed-layer growth, cloud fraction, and convective inhibition from a single parameterization based on physical principles. The evolution of the shallow convection PBCM is based on the statistical distribution of the surface thermodynamic state of convective plumes. The entrainment velocity of the mixed layer is related to the mass flux of the updrafts overshooting the dry inversion capping the mixed layer. The updrafts overcoming the convective inhibition generate active cloudbase mass flux, which is the boundary condition for the shallow cumulus scheme. The subcloud-layer entrainment velocity is directly coupled to the cloud-base mass flux through the distribution of vertical velocity and fractional cover of the updrafts. Comparisons of the PBCM against large-eddy simulations from the Barbados Oceanographic and MeteorologicalExperiment (BOMEX) andfromthe SouthernGreat PlainsAtmospheric RadiationMeasurement Program (ARM) facility demonstrate good agreement in terms of thermodynamic structure, cloud-base mass flux, and cloud top. The equilibrium between the cloud-base mass flux and rate of growth of the mixed layer determines the equilibrium convective inhibition and cloud cover. This process is an important new insight on the coupling between the mixed-layer and cumulus dynamics. Given its relative simplicity and transparency, the PBCM represents a powerful tool for developing process-based understanding and intuition about the physical processes involved in boundary layer–convection interactions, as well as a test bed for diagnosing and validating shallow convection parameterizations.

Impact of common sea surface temperature anomalies on global drought and pluvial frequency.

Abstract Climate model simulations run as part of the Climate Variability and Predictability (CLIVAR) Drought Working Group initiative were analyzed to determine the impact of three patterns of sea surface temperature (SST) anomalies on drought and pluvial frequency and intensity around the world. The three SST forcing patterns include a global pattern similar to the background warming trend, a pattern in the Pacific, and a pattern in the Atlantic. Five different global atmospheric models were forced by fixed SSTs to test the impact of these SST anomalies on droughts and pluvials relative to a climatologically forced control run. The five models generally yield similar results in the locations of drought and pluvial frequency changes throughout the annual cycle in response to each given SST pattern. In all of the simulations, areas with an increase in the mean drought (pluvial) conditions tend to also show an increase in the frequency of drought (pluvial) events. Additionally, areas with more frequent ext...

An Idealized Prototype for Large-Scale Land–Atmosphere Coupling

AbstractA process-based, semianalytic prototype model for understanding large-scale land–atmosphere coupling is developed here. The metric for quantifying the coupling is the sensitivity of precipitation P to soil moisture W, . For a range of prototype parameters typical of conditions found over tropical or summertime continents, the sensitivity measure exhibits a broad minimum at intermediate soil moisture values. This minimum is attributed to a trade-off between evaporation (or evapotranspiration) E and large-scale moisture convergence across the range of soil moisture states. For water-limited, low soil moisture conditions, is dominated by evaporative sensitivity , reflecting high potential evaporation Ep arising from relatively warm surface conditions and a moisture-deficient atmospheric column under dry surface conditions. By contrast, under high soil moisture (or energy limited) conditions, becomes slightly negative as Ep decreases. However, because convergence and precipitation increase strongly wi...

A Probabilistic Bulk Model of Coupled Mixed Layer and Convection. Part I: Clear-Sky Case

A new bulk model of the convective boundary layer, the probabilistic bulk convection model (PBCM), is presented. Unlike prior bulk approaches that have modeled the mixed-layer-top buoyancy flux as a constant fractionofthesurfacebuoyancyflux,PBCMimplementsanewmixed-layer-topentrainmentclosurebasedon the mass flux of updrafts overshooting the inversion. This mass flux is related to the variability of the surface state (potential temperature u and specific humidity q) of an ensemble of updraft plumes. The authors evaluatethemodelagainstobservedclear-skyweakandstronginversioncasesandshowthatPBCMperforms well. The height, state, and timing of the boundary layer growth are accurately reproduced. Sensitivitystudies are performed highlighting the role of the main parameters (surface variances, lateral entrainment). The model is weakly sensitive to the exact specification of the variability at the surface and is most sensitive to the lateral entrainment of environmental air into the rising plumes. Apart from allowing time-dependent top-ofthe-boundary-layer entrainment rates expressed in terms of surface properties, which can be observed in situ, PBCM naturally takes into account the transition to the shallow convection regime, as described in a companion paper. Thus, PBCM represents an important step toward a unified framework bridging parameterizations of mixed-layer entrainment velocity in both clear-sky and moist convective boundary layers.