Land Atmosphere Coupling Research Articles

Effect of Teleconnected Land–Atmosphere Coupling on Northeast China Persistent Drought in Spring–Summer of 2017

Northeast China (NEC) suffered a severe drought that persisted from March to July of 2017 with profound impacts on agriculture and society, raising an urgent need to understand the mechanism for persistent droughts over midlatitudes. Previous drought mechanism studies focused on either large-scale teleconnections or local land–atmosphere coupling, while less attention was paid to their synergistic effects on drought persistence. Here we show that the 2017 NEC drought was triggered by a strong positive phase of the Arctic Oscillation in March, and maintained by the anticyclone over the area south to Lake Baikal (ASLB) through a quasi-stationary Rossby wave in April–July, accompanied by sinking motion and north wind anomaly. By using a land–atmosphere coupling index based on the persistence of positive feedbacks between the boundary layer and land surface, we find that the coupling states over NEC and ASLB shifted from a wet coupling in March to a persistently strengthened dry coupling in April–July. Over ASLB, the dry coupling and sinking motion increased surface sensible heat, decreased cloud cover, and weakened longwave absorption, resulting in a diabatic heating anomaly in the lower atmosphere and a diabatic cooling anomaly in the upper atmosphere. This anomalous vertical heating profile led to a negative anomaly of potential vorticity at low levels, indicating that the land–atmosphere coupling had a phase-lock effect on the Rossby wave train originating from upstream areas, and therefore maintained the NEC drought over downstream regions. Our study suggests that an upstream quasi-stationary wave pattern strengthened by land–atmosphere coupling should be considered in diagnosing persistent droughts, especially over northern midlatitudes.

Robust observations of land-to-atmosphere feedbacks using the information flows of FLUXNET

Feedbacks between atmospheric processes like precipitation and land surface fluxes including evapotranspiration are difficult to observe, but critical for understanding the role of the land surface in the Earth System. To quantify global surface-atmosphere feedbacks we use results of a process network (PN) applied to 251 eddy covariance sites from the LaThuile database to train a neural network across the global terrestrial surface. There is a strong land–atmosphere coupling between latent (LE) and sensible heat flux (H) and precipitation (P) during summer months in temperate regions, and between H and P during winter, whereas tropical rainforests show little coupling seasonality. Savanna, shrubland, and other semi-arid ecosystems exhibit strong responses in their coupling behavior based on water availability. Feedback couplings from surface fluxes to P peaks at aridity (P/potential evapotranspiration ETp) values near unity, whereas coupling with respect to clouds, inferred from reduced global radiation, increases as P/ETp approaches zero. Spatial patterns in feedback coupling strength are related to climatic zone and biome type. Information flow statistics highlight hotspots of (1) persistent land–atmosphere coupling in sub-Saharan Africa, (2) boreal summer coupling in the central and southwestern US, Brazil, and the Congo basin and (3) in the southern Andes, South Africa and Australia during austral summer. Our data-driven approach to quantifying land atmosphere coupling strength that leverages the global FLUXNET database and information flow statistics provides a basis for verification of feedback interactions in general circulation models and for predicting locations where land cover change will feedback to climate or weather.

The New Stand-Alone Surface Analysis at ECMWF: Implications for Land–Atmosphere DA Coupling

Abstract This article presents the “screen-level and surface analysis only” (SSA) system at the European Centre for Medium-Range Weather Forecasts (ECMWF). SSA is a simplification of the operational land–atmosphere weakly coupled data assimilation (WCDA). The goal of SSA is to provide 1) efficient research into land surface developments in NWP and 2) land reanalyses with land–atmosphere coupling. SSA maintains a coupled forecast model between assimilation cycles, but the atmospheric analysis is not performed; rather, it is forced from an archived analysis. Hence, SSA is much faster than WCDA, although it lacks feedback between the land and atmospheric analyses. A global sensitivity analysis was performed over one year to compare the WCDA and SSA systems. Prescribed proxy 2-m temperature/humidity screen-level observation errors were approximately doubled in the soil moisture data assimilation, thereby reducing the average size of the root-zone soil moisture analysis increments by about 60%. The systematic impact of these changes on the WCDA surface and near-surface atmospheric dynamics was effectively captured by SSA, although the short-term impact was underestimated. Importantly, the SSA forecast verification scores accurately reflected those of WCDA: atmospheric 1–10-day temperature/humidity forecasts were degraded in the tropics and lower midlatitudes up to about 700 hPa. The soil moisture analysis performance was not significantly impacted. These results endorse SSA as an NWP research tool and confirm the role of assimilating proxy screen-level observations in the soil moisture analysis to improve weather forecasts. Appropriate use and limitations of SSA are considered.

Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity

Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land-atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture-precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land-atmosphere feedbacks is projected to increase in the 21st century. Importantly, land-atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.

Separating the Impact of Individual Land Surface Properties on the Terrestrial Surface Energy Budget in both the Coupled and Uncoupled Land–Atmosphere System

AbstractChanges in the land surface can drive large responses in the atmosphere on local, regional, and global scales. Surface properties control the partitioning of energy within the surface energy budget to fluxes of shortwave and longwave radiation, sensible and latent heat, and ground heat storage. Changes in surface energy fluxes can impact the atmosphere across scales through changes in temperature, cloud cover, and large-scale atmospheric circulation. We test the sensitivity of the atmosphere to global changes in three land surface properties: albedo, evaporative resistance, and surface roughness. We show the impact of changing these surface properties differs drastically between simulations run with an offline land model, compared to coupled land–atmosphere simulations that allow for atmospheric feedbacks associated with land–atmosphere coupling. Atmospheric feedbacks play a critical role in defining the temperature response to changes in albedo and evaporative resistance, particularly in the extratropics. More than 50% of the surface temperature response to changing albedo comes from atmospheric feedbacks in over 80% of land areas. In some regions, cloud feedbacks in response to increased evaporative resistance result in nearly 1 K of additional surface warming. In contrast, the magnitude of surface temperature responses to changes in vegetation height are comparable between offline and coupled simulations. We improve our fundamental understanding of how and why changes in vegetation cover drive responses in the atmosphere, and develop understanding of the role of individual land surface properties in controlling climate across spatial scales—critical to understanding the effects of land-use change on Earth’s climate.

How Well Do Operational Numerical Weather Prediction Configurations Represent Hydrology?

Abstract Land surface models (LSMs) have traditionally been designed to focus on providing lower-boundary conditions to the atmosphere with less focus on hydrological processes. State-of-the-art application of LSMs includes a land data assimilation system (LDAS), which incorporates available land surface observations to provide an improved realism of surface conditions. While improved representations of the surface variables (such as soil moisture and snow depth) make LDAS an essential component of any numerical weather prediction (NWP) system, the related increments remove or add water, potentially having a negative impact on the simulated hydrological cycle by opening the water budget. This paper focuses on evaluating how well global NWP configurations are able to support hydrological applications, in addition to the traditional weather forecasting. River discharge simulations from two climatological reanalyses are compared: one “online” set, which includes land–atmosphere coupling and LDAS with an open water budget, and an “offline” set with a closed water budget and no LDAS. It was found that while the online version of the model largely improves temperature and snow depth conditions, it causes poorer representation of peak river flow, particularly in snowmelt-dominated areas in the high latitudes. Without addressing such issues there will never be confidence in using LSMs for hydrological forecasting applications across the globe. This type of analysis should be used to diagnose where improvements need to be made; considering the whole Earth system in the data assimilation and coupling developments is critical for moving toward the goal of holistic Earth system approaches.

Radiation and energy balance dynamics over a rapidly receding glacier in the central Himalaya

Driven by the strength in local land–atmosphere coupling, inter‐annual variability of larger‐scale atmospheric circulations primarily determines a glacier's response to warming in high Asia. In this study, micrometeorological measurements in conjunction with regional reanalysis data set were analysed to examine seasonal land–atmosphere coupling strength at a typical central Himalayan (CH) glacier where the influence of Indian summer monsoon (ISM) predominates relative to winter‐westerlies. Energy–water (E–W) exchange and coupling behaviour were studied for the Pindari glacier based on sub‐hourly measurements of radiative–convective flux, state parameters, and sub‐surface thermal profiles using cross‐correlations between various E–W balance components. Coupling was positive in summer and winter accumulation seasons. However, it remained strongest during ISM. Coupling reversed during seasonal transition phases concurrent with distinct seasonality in E–W components. Lead–lag relation between some variables showed strong association at diurnal‐scale (VPD–Rn; VPD–LE; Rn–G), whereas some persisted beyond months (Rn–LE; Bowen ratio–precipitation; surface–air temperature). Weak association of variation of latent heat flux (LE) and rainfall was found during ISM at local scale than at regional scale, but with a lag, which was more prominent at regional scale. These observations indicate a seasonally variable coupling between E–W balance components through response–feedback mechanisms. Cross‐correlations of daily mean values of energy fluxes and meteorological variables reveal that Rn and air temperature are the prime drivers of energy balance. Net radiative energy (Rn) dominates energy exchanges at the glacier–atmosphere interface (governed primarily by the variation in net shortwave radiation), contributed on average 62% of the melt energy. However, sub‐surface heat flux along with the turbulent fluxes was the energy sinks of 24 and 15%, respectively. This study would help understand and parameterize E–W exchange pathways for ISM dominated CH glaciers in coupled glacier–climate models.

A Modified Framework for Quantifying Land–Atmosphere Covariability during Hydrometeorological and Soil Wetness Extremes in Oklahoma

AbstractGlobal “hot spots” for land–atmosphere coupling have been identified through various modeling studies—both local and global in scope. One hot spot that is common to many of these analyses is the U.S. southern Great Plains (SGP). In this study, we perform a mesoscale analysis, enabled by the Oklahoma Mesonet, that bridges the spatial and temporal gaps between preceding local and global analyses of coupling. We focus primarily on east–west variations in seasonal coupling in the context of interannual variability over the period spanning 2000–15. Using North American Regional Reanalysis (NARR)-derived standardized anomalies of convective triggering potential (CTP) and the low-level humidity index (HI), we investigate changes in the covariance of soil moisture and the atmospheric low-level thermodynamic profile during seasonal hydrometeorological extremes. Daily CTP and HI z scores, dependent upon climatology at individual NARR grid points, were computed and compared to in situ soil moisture observations at the nearest mesonet station to provide nearly collocated annual composites over dry and wet soils. Extreme dry and wet year CTP and HI z-score distributions are shown to deviate significantly from climatology and therefore may constitute atmospheric precursors to extreme events. The most extreme rainfall years differ from climatology but also from one another, indicating variability in the strength of land–atmosphere coupling during these years. Overall, the covariance between soil moisture and CTP/HI is much greater during drought years, and coupling appears more consistent. For example, propagation of drought during 2011 occurred under antecedent CTP and HI conditions that were identified by this study as being conducive to positive dry feedbacks demonstrating potential utility of this framework in forecasting regional drought propagation.

Isolating the Observed Influence of Vegetation Variability on the Climate of La Plata River Basin

AbstractThis work aims to isolate and quantify the local and remote biogeophysical influences of slowly varying vegetation variability on the climate of La Plata basin (LPB) in the austral spring season (September–November) using observational records. Past studies have shown strong land–atmosphere coupling in LPB during this season. The analysis uses a 34-yr record (1981–2014) of the modified enhanced vegetation index (EVI2) from the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Vegetation Index and Phenology dataset and the third-generation normalized difference vegetation index (NDVI) from Global Inventory Modeling and Mapping Studies. The dominant patterns of vegetation index variability in space and time are assessed using empirical orthogonal function/principal component analysis over the LPB. The dominant mode in the austral spring is a vegetation dipole, with greening (browning) or positive (negative) vegetation index anomalies in the northeastern (southwestern) part of the basin. Using the stepwise generalized equilibrium feedback assessment (SGEFA), the effect of the vegetation variability on the atmosphere is then isolated. The dominant mode of LPB vegetation variability in austral spring is related to warmer temperatures in the southwest LPB and enhanced precipitation over the central and southern parts of the basin. A mechanism is proposed for the increase in latent heat flux and cooler temperatures in the northeastern LPB due to greening, and the increase in sensible heat flux, warmer temperatures, and decrease in surface pressure in southwestern LPB due to browning. The geostrophic response to this induced pressure gradient leads to anomalous northerly enhancement of moisture-laden winds, deeper penetration of moisture into LPB, and increased precipitation over the central and southern parts of the basin.

Decadal intensification of local thermal feedback of summer soil moisture over North China

Soil moisture (SM) feedback on climate variables especially temperature is an important aspect in land-atmosphere coupling. Based on the Global Land Data Assimilation System (GLDAS) V2.0 SM data and the gridded observational temperature data, we statistically analyze the thermal feedback of SM over North China (NC). The results show that SM exerts a decreasing trend under the background of evident warming over NC, inducing a decadal enhancement of SM feedbacks on the local temperature and extreme hot events. The SM feedback contributes 6% of the total air temperature variation during 1961–2012, while it reaches 36% after the regional warming during 1994–2012. Such SM affecting temperature is mainly reflected in its feedback on daily maximum temperature, which is also intensified during the warm period. The decadal intensification is also found in the feedback of SM on hot extremes. Further analyses show that the abnormal changes of the latent and sensible heat fluxes caused by the SM anomaly are the main reasons that affect the thermal conditions. Besides, the rising Bowen ratio indicates that upward thermal transfer on the land surface is enhanced in recent years, which suggests that the atmosphere is more sensible to the abnormal heating on the ground. This consequently translates into the decadal intensification of the local thermal feedback of SM in summer over NC.

The role of land and ocean evaporation on the variability of precipitation in the Yangtze River valley

Abstract. The Yangtze River valley (YRV) experiences large intraseasonal and interannual precipitation variability, which is mainly due to East Asian monsoon influence. The East Asian monsoon is caused by interaction of many processes in the coupled land–atmosphere–ocean system. To better understand YRV precipitation variability in this complex system, we have studied the precipitation moisture sources and their connection to YRV precipitation. We obtained the moisture sources by using the European Centre for Medium-Range Weather Forecasts' (ECMWF) ERA-Interim reanalysis dataset, the FLEXible PARTicle dispersion model (FLEXPART), and the WaterSip moisture source diagnostic. The variability of moisture sources reflects the variability of YRV precipitation. Intraseasonal variations of moisture sources include a shift of the most important source regions as the monsoon progresses. Interannual variability of the moisture sources shows that sources which are less important climatologically are closely connected to variations of the driest and wettest years. Our results show that land directly contributes 58 % of moisture for YRV precipitation during 1980–2016, whereas the ocean contributes 42 % in direct transport. While the importance of the ocean as a moisture source is often emphasized, our results underscore the importance of the process of continental recycling and the role of land moisture sources.

Regional grid refinement in an Earth system model: impacts on the simulated Greenland surface mass balance

Abstract. In this study, the resolution dependence of the simulated Greenland ice sheet surface mass balance (GrIS SMB) in the variable-resolution Community Earth System Model (VR-CESM) is investigated. Coupled atmosphere–land simulations are performed on two regionally refined grids over Greenland at 0.5∘ (∼55 km) and 0.25∘ (∼28 km), maintaining a quasi-uniform resolution of 1∘ (∼111 km) over the rest of the globe. On the refined grids, the SMB in the accumulation zone is significantly improved compared to airborne radar and in situ observations, with a general wetting (more snowfall) at the margins and a drying (less snowfall) in the interior GrIS. Total GrIS precipitation decreases with resolution, which is in line with best-available regional climate model results. In the ablation zone, CESM starts developing a positive SMB bias with increased resolution in some basins, notably in the east and the north. The mismatch in ablation is linked to changes in cloud cover in VR-CESM, and a reduced effectiveness of the elevation classes subgrid parametrization in CESM. Overall, our pilot study introduces VR-CESM as a new tool in the cryospheric sciences, which could be used to dynamically downscale SMB in scenario simulations and to force dynamical ice sheet models through the CESM coupling framework.

Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales

Abstract Land–atmosphere feedbacks occurring on daily to weekly time scales can magnify the intensity and duration of extreme weather events, such as droughts, heat waves, and convective storms. For such feedbacks to occur, the coupled land–atmosphere system must exhibit sufficient memory of soil moisture anomalies associated with the extreme event. The soil moisture autocorrelation e-folding time scale has been used previously to estimate soil moisture memory. However, the theoretical basis for this metric (i.e., that the land water budget is reasonably approximated by a red noise process) does not apply at finer spatial and temporal resolutions relevant to modern satellite observations and models. In this study, two memory time scale metrics are introduced that are relevant to modern satellite observations and models: the “long-term memory” τL and the “short-term memory” τS. Short- and long-term surface soil moisture (SSM) memory time scales are spatially anticorrelated at global scales in both a model and satellite observations, suggesting hot spots of land–atmosphere coupling will be located in different regions, depending on the time scale of the feedback. Furthermore, the spatial anticorrelation between τS and τL demonstrates the importance of characterizing these memory time scales separately, rather than mixing them as in previous studies.

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land–Atmosphere Coupling

Abstract The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from “off the shelf” products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high-resolution land surface model and in situ soil moisture estimates. Case studies are analyzed using the local land–atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land versus atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

A case‐study of land–atmosphere coupling during monsoon onset in northern India

AbstractThis article presents a land–atmosphere case‐study for a single day during monsoon onset, incorporating data from a research aircraft, satellite products and model outputs. The unique aircraft observations reveal temperature and humidity contrasts of up to 5 K and 4 g/kg in the planetary boundary layer induced by spatial variations in soil moisture. Both antecedent rain and irrigation were found to be drivers of this atmospheric variability. There is also evidence of soil moisture‐induced mesoscale circulations above some surfaces. This is the first time such responses have been observed in situ over India. Soil moisture‐driven temperature anomalies are larger than those found in previous observational studies in the African Sahel. Moreover, irrigation in the region is extensive, unlike in the Sahel, and has a similar atmospheric effect to antecedent rainfall. This implies that historical changes in irrigation practices are likely to have had an important influence on mesoscale processes within the Indian monsoon. We also examine evidence linking soil moisture and cloud formation. Above wetter soils we observed a suppression of shallow cloud, whilst the initiation of deep convection occurred mostly in areas affected by wet–dry soil moisture boundaries. To investigate the impact of soil moisture heterogeneity on large‐scale wind flow, three model depictions of the day are assessed: the European Centre for Medium‐Range Weather Forecasts ERA‐Interim and ERA5 reanalyses, and a high‐resolution (1.5 km) simulation generated using the Indian National Centre for Medium Range Weather Forecasting regional convection‐permitting Unified Model. We find evidence indicating surface flux uncertainties in the models lead to ∼3.5 hPa anomalies in the monsoon trough. This does affect the simulation of monsoon circulation and rainfall. Better representation of mesoscale land–atmosphere coupling is likely to improve the depiction of convection within weather and climate models over India.

Implementation of the Land Surface Processes into a Vector Vorticity Equation Model (VVM) to Study its Impact on Afternoon Thunderstorms over Complex Topography in Taiwan

In this study, we aim to evaluate the impact of fast land-atmosphere interactions on the afternoon thunderstorm in Taiwan through high-resolution meteorological simulations. For this purpose, the Noah land surface model (LSM) is implemented into the vector vorticity equation cloud-resolving model (VVM) with corresponding realistic land surface data of Taiwan into the coupling system, called TaiwanVVM. Two idealized experiments are conducted by giving the same surface forcing but one with direct land-atmosphere coupling from Noah LSM (called Coupled experiment) and the other with prescribed surface fluxes (called Prescribed experiment). Our results show that the fast land-atmosphere interaction over complex topography has a significant influence on rainfall intensity, especially in the heavy precipitating region where the interaction is strong. Without direct coupling between the land surface and the atmosphere in the Prescribed experiment, the diurnal intensity is suppressed by 50% over whole Taiwan and 70% for East Taiwan. Our findings demonstrate that the intensity of the afternoon thunderstorm is sensitive to fast land-atmosphere interactions by modifying local circulation in the mountainous region of Taiwan.

Evaluation of Drydown Processes in Global Land Surface and Hydrological Models Using Flux Tower Evapotranspiration

A key aspect of the land surface response to the atmosphere is how quickly it dries after a rainfall event. It is key because it will determine the intensity and speed of the propagation of drought and also affects the atmospheric state through changes in the surface heat exchanges. Here, we test the theory that this response can be studied as an inherent property of the land surface that is unchanging over time unless the above- and below-ground structures change. This is important as a drydown metric can be used to evaluate a landscape and its response to atmospheric drivers in models used in coupled land–atmosphere mode when the forcing is often not commensurate with the actual atmosphere. We explore whether the speed of drying of a land unit can be quantified and how this can be used to evaluate models. We use the most direct observation of drying: the rate of change of evapotranspiration after a rainfall event using eddy-covariance observations, or commonly referred to as flux tower data. We analyse the data and find that the drydown timescale is characteristic of different land cover types, then we use that to evaluate a suite of global hydrological and land surface models. We show that, at the site level, the data suggest that evapotranspiration decay timescales are longer for trees than for grasslands. The studied model’s accuracy to capture the site drydown timescales depends on the specific model, the site, and the vegetation cover representation. A more robust metric is obtained by grouping the modeled data by vegetation type and, using this, we find that land surface models capture the characteristic timescale difference between trees and grasslands, found using flux data, better than large-scale hydrological models. We thus conclude that the drydown metric has value in understanding land–atmosphere interactions and model evaluation.

Soil Moisture Variability Intensifies and Prolongs Eastern Amazon Temperature and Carbon Cycle Response to El Niño–Southern Oscillation

El Niño–Southern Oscillation (ENSO) is an important driver of climate and carbon cycle variability in the Amazon. Sea surface temperature (SST) anomalies in the equatorial Pacific drive teleconnections with temperature directly through changes in atmospheric circulation. These circulation changes also impact precipitation and, consequently, soil moisture, enabling additional indirect effects on temperature through land–atmosphere coupling. To separate the direct influence of ENSO SST anomalies from the indirect effects of soil moisture, a mechanism-denial experiment was performed to decouple their variability in the Energy Exascale Earth System Model (E3SM) forced with observed SSTs from 1982 to 2016. Soil moisture variability was found to amplify and extend the effects of SST forcing on eastern Amazon temperature and carbon fluxes in E3SM. During the wet season, the direct, circulation-driven effect of ENSO SST anomalies dominated temperature and carbon cycle variability throughout the Amazon. During the following dry season, after ENSO SST anomalies had dissipated, soil moisture variability became the dominant driver in the east, explaining 67%–82% of the temperature difference between El Niño and La Niña years, and 85%–91% of the difference in carbon fluxes. These results highlight the need to consider the interdependence between temperature and hydrology when attributing the relative contributions of these factors to interannual variability in the terrestrial carbon cycle. Specifically, when offline models are forced with observations or reanalysis, the contribution of temperature may be overestimated when its own variability is modulated by hydrology via land–atmosphere coupling.

The Sensitivity of Land-Atmosphere Coupling to Modern Agriculture in the Northern Midlatitudes.

Modern agricultural land cover and management are important as regional climate forcings. Previous work has shown that land cover change can significantly impact key climate variables, including turbulent fluxes, precipitation, and surface temperature. However, fewer studies have investigated how intensive crop management can impact background climate conditions, such as the strength of land-atmosphere coupling and evaporative regime. We conduct sensitivity experiments using a state-of-the-art climate model with modified vegetation characteristics to represent modern crop cover and management, using observed crop-specific leaf area indexes and calendars. We quantify changes in land-atmosphere interactions and climate over intensively cultivated regions situated at transitions between moisture- and energy-limited conditions. Results show that modern intensive agriculture has significant and geographically varying impacts on regional evaporative regimes and background climate conditions. Over the northern Great Plains, modern crop intensity increases the model simulated precipitation and soil moisture, weakening hydrologic coupling by increasing surface water availability and reducing moisture limits on evapotranspiration. In the U.S. Midwest, higher growing season evapotranspiration, coupled with winter and spring rainfall declines, reduces regional soil moisture, while crop albedo changes also reduce net surface radiation. This results overall in reduced dependency of regional surface temperature on latent heat fluxes. In central Asia, a combination of reduced net surface energy and enhanced pre-growing season precipitation amplify the energy-limited evaporative regime. These results highlight the need for improved representations of agriculture in global climate models to better account for regional climate impacts and interactions with other anthropogenic forcings.

Multiple Equilibria in a Land–Atmosphere Coupled System

Many low-order modeling studies indicate that there may be multiple equilibria in the atmosphere induced by thermal and topographic forcings. However, most work uses uncoupled atmospheric model and just focuses on the multiple equilibria with distinct wave amplitude, i.e., the high- and low-index equilibria. Here, a low-order coupled land–atmosphere model is used to study the multiple equilibria with both distinct wave phase and wave amplitude. The model combines a two-layer quasi-geostrophic channel model and an energy balance model. Highly truncated spectral expansions are used and the results show that there may be two stable equilibria with distinct wave phase relative to the topography: one (the other) has a lower layer streamfunction that is nearly in (out of) phase with the topography, i.e., the lower layer ridges (troughs) are over the mountains, called ridge-type (trough-type) equilibria. The wave phase of equilibrium state depends on the direction of lower layer zonal wind and horizontal scale of the topography. The multiple wave phase equilibria associated with ridge- and trough-types originate from the orographic instability of the Hadley circulation, which is a pitch-fork bifurcation. Compared with the uncoupled model, the land–atmosphere coupled system produces more stable atmospheric flow and more ridge-type equilibrium states, particularly, these effects are primarily attributed to the longwave radiation fluxes. The upper layer streamfunctions of both ridge- and trough-type equilibria are also characterized by either a high- or low-index flow pattern. However, the multiple wave phase equilibria associated with ridge- and trough-types are more prominent than multiple wave amplitude equilibria associated with high- and low-index types in this study.