Atmosphere Land System Research Articles

Estimation of Land Surface Temperature under Cloudy Skies Using Combined Diurnal Solar Radiation and Surface Temperature Evolution

Land surface temperature (LST) is a key parameter in the interaction of the land-atmosphere system. However, clouds affect the retrieval of LST data from thermal-infrared remote sensing data. Thus, it is important to determine a method for estimating LSTs at times when the sky is overcast. Based on a one-dimensional heat transfer equation and on the evolution of daily temperatures and net shortwave solar radiation (NSSR), a new method for estimating LSTs under cloudy skies (Tcloud) from diurnal NSSR and surface temperatures is proposed. Validation is performed against in situ measurements that were obtained at the ChangWu ecosystem experimental station in China. The results show that the root-mean-square error (RMSE) between the actual and estimated LSTs is as large as 1.23 K for cloudy data. A sensitivity analysis to the errors in the estimated LST under clear skies (Tclear) and in the estimated NSSR reveals that the RMSE of the obtained Tcloud is less than 1.5 K after adding a 0.5 K bias to the actual Tclear and 10 percent NSSR errors to the actual NSSR. Tcloud is estimated by the proposed method using Tclear and NSSR products of MSG-SEVIRI for southern Europe. The results indicate that the new algorithm is practical for retrieving the LST under cloudy sky conditions, although some uncertainty exists. Notably, the approach can only be used during the daytime due to the assumption of the variation in LST caused by variations in insolation. Further, if there are less than six Tclear observations on any given day, the method cannot be used.

Radiative–Convective Equilibrium over a Land Surface

Abstract Radiative–convective equilibrium (RCE) describes an idealized state of the atmosphere in which the vertical temperature profile is determined by a balance between radiative and convective fluxes. While RCE has been applied extensively over oceans, its application over the land surface has been limited. The present study explores the properties of RCE over land using an atmospheric single-column model (SCM) from the Laboratoire de Météorologie Dynamique–Zoom, version 5B (LMDZ5B) general circulation model coupled in temperature and moisture to a land surface model using a simplified bucket model with finite moisture capacity. Given the presence of a large-amplitude diurnal heat flux cycle, the resultant RCE exhibits multiple equilibria when conditions are neither strictly water nor energy limited. By varying top-of-atmosphere insolation (through changes in latitude), total system water content, and initial temperature conditions the sensitivity of the land RCE states is assessed, with particular emphasis on the role of clouds. Based on this analysis, it appears that a necessary condition for the model to exhibit multiple equilibria is the presence of low-level clouds coupled to the diurnal cycle of radiation. In addition the simulated surface precipitation rate varies nonmonotonically with latitude as a result of a tradeoff between in-cloud rain rate and subcloud rain reevaporation, thus underscoring the importance of subcloud layer processes and unsaturated downdrafts. It is shown that clouds, especially at low levels, are key elements of the internal variability of the coupled land–atmosphere system through their feedback on radiation.

Interfacing the Urban Land–Atmosphere System Through Coupled Urban Canopy and Atmospheric Models

We couple a single column model (SCM) to a cutting-edge single-layer urban canopy model (SLUCM) with realistic representation of urban hydrological processes. The land-surface transport of energy and moisture parametrized by the SLUCM provides lower boundary conditions to the overlying atmosphere. The coupled SLUCM–SCM model is tested against field measurements of sensible and latent heat fluxes in the surface layer, as well as vertical profiles of temperature and humidity in the mixed layer under convective conditions. The model is then used to simulate urban land–atmosphere interactions by changing urban geometry, surface albedo, vegetation fraction and aerodynamic roughness. Results show that changes of landscape characteristics have a significant impact on the growth of the boundary layer as well as on the distributions of temperature and humidity in the mixed layer. Overall, the proposed numerical framework provides a useful stand-alone modelling tool, with which the impact of urban land-surface conditions on the local hydrometeorology can be assessed via land–atmosphere interactions.

A method to estimate land surface temperature from Meteosat Second Generation data using multi-temporal data

Land surface temperature (LST) is key parameters in the interaction of land-atmosphere system. This paper proposed a method to inverse LST from multi-temporal thermal infrared remote sensing data based on the theory of split-window algorithm and diurnal temperature cycle model. The new method was validated by a diurnal brightness temperatures data sets corresponding to MSG2-SEVIRI, which was simulated by the atmospheric radiative transfer model MODTRAN 4 with several input parameters under clear sky, including near surface air temperature, atmospheric water, surface temperature and emissivity, and viewing angles, and result showed the root mean square error (RMSE) of LST reaches 1.2K for simulated data and most errors are within ± 2K with accurate parameters input. At the same time, comparison of LST estimated using the proposed method from MSG2-SEVIRI data with that from MOD11B1 V5 product displayed that the RMSE equals to 3.0K and most errors are distributed within ± 6K. But, the method is proposed under no cloudy condition and is tested only in mid-latitude and daytime; more validation should be made in different areas and atmospheric conditions.

The role of land-surface processes in modulating the Indian monsoon annual cycle

The annual cycle of solar radiation, together with the resulting land–ocean differential heating, is traditionally considered the dominant forcing controlling the northward progression of the Indian monsoon. This study makes use of a state-of-the-art atmospheric general circulation model in a realistic configuration to conduct “perpetual” experiments aimed at providing new insights into the role of land–atmosphere processes in modulating the annual cycle of precipitation over India. The simulations are carried out at three important stages of the monsoon cycle: March, May, and July. Insolation and SSTs are held fixed at their respective monthly mean values, thus eliminating any external seasonal forcing. In the perpetual May experiment both precipitation and circulation are able to considerably evolve only by regional internal land–atmosphere processes and the mediation of soil hydrology. A large-scale equilibrium state is reached after approximately 270 days, closely resembling mid-summer climatological conditions. As a result, despite the absence of external forcing, intense and widespread rains over India are able to develop in the May-like state. The interaction between soil moisture and circulation, modulated by surface heating over the northwestern semi-arid areas, determines a slow northwestward migration of the monsoon, a crucial feature for the existence of desert regions to the west. This also implies that the land–atmosphere system in May is far from being in equilibrium with the external forcing. The inland migration of the precipitation front comprises a succession of large-scale 35–50 day coupled oscillations between soil moisture, precipitation, and circulation. The oscillatory regime is self-sustained and entirely due to the internal dynamics of the system. In contrast to the May case, minor changes in the land–atmosphere system are found when the model is initialized in March and, more surprisingly, in July, the latter case further emphasizing the role of northwestern surface heating.

Impact of vegetation variability on potential predictability and skill of EC-Earth simulations

Climate models often use a simplified and static representation of vegetation characteristics to determine fluxes of energy, momentum and water vapour between surface and lower atmosphere. In order to analyse the impact of short term variability in vegetation phenology, we use remotely-sensed leaf area index and albedo products to examine the role of vegetation in the coupled land–atmosphere system. Perfect model experiments are carried out to determine the impact of realistic temporal variability of vegetation on potential predictability of evaporation and temperature, as well as model skill of EC-Earth simulations. The length of the simulation period is hereby limited by the availability of satellite products to 2000–2010. While a realistic representation of vegetation positively influences the simulation of evaporation and its potential predictability, a positive impact on 2 m temperature is of smaller magnitude, regionally confined and more pronounced in climatically extreme years.

Acceleration of Land Surface Model Development over a Decade of Glass

An overview of initiatives that are a part of the Global Land Atmosphere System Study (GLASS), which has ushered in an era in which land surface models (LSM) for numerical weather and climate prediction now incorporate complex vegetation responses, detailed hydrology, dynamic snowpack evolution, urban processes, and more, is presented. A critical goal of GLASS is to expand from the uncoupled point-based (PILPS) and globally based (GSWP) evaluations to include simulations that are fully coupled with the atmosphere. GLASS includes Global Soil Wetness Project Phase (GSWP) in which the earlier GSWP-2 datasets will be extended forward to the present, enabling scientific progress toward attribution of recent changes to various components of the climate system, including the terrestrial component.

A Simple, Minimal Parameter Model for Predicting the Influence of Changing Land Cover on the Land–Atmosphere System+

Abstract The impacts of changing land cover on the soil–vegetation–atmosphere system are numerous. With the fraction of land used for farming and grazing expected to increase, extensive alterations to land cover such as replacing forests with cropland will continue. Therefore, quantifying the impact of global land-cover scenarios on the biosphere is critical. The Predicting Ecosystem Goods and Services Using Scenarios boundary layer (PegBL) model is a new global soil–vegetation–boundary layer model designed to quantify these impacts and act as a complementary tool to computationally expensive general circulation models and large-eddy simulations. PegBL provides high spatial resolution and inexpensive first-order estimates of land-cover change on the surface energy balance and atmospheric boundary layer with limited input requirements. The model uses a climatological-data-driven land surface model that contains only the physics necessary to accurately reproduce observed seasonal cycles of fluxes and state variables for natural and agricultural ecosystems. A bulk boundary layer model was coupled to the land model to estimate the impacts of changing land cover on the lower atmosphere. The model most realistically simulated surface–atmosphere dynamics and impacts of land-cover change at tropical rain forest and northern boreal forest sites. Further, simple indices to measure the potential impact of land-cover change on boundary layer climate were defined and shown to be dependent on boundary layer dynamics and geographically similar to results from previous studies, which highlighted the impacts of land-cover change on the atmosphere in the tropics and boreal forest.

Sensitivity of high-resolution Arctic regional climate model projections to different implementations of land surface processes

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between -1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: -2 hPa to 1.5 hPa, z: -15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models.

The role of soil ice in land-atmosphere coupling over the United States: A soil moisture–precipitation winter feedback mechanism

[1] We perform two 23 year simulations using a regional climate model coupled with the National Center for Atmospheric Research Community Land Model version 3.5 (RegCM-CLM) to investigate land-atmosphere coupling in the continental United States during the cold season (October–April) and the role of soil water phase. One simulation allows the land surface to interact freely (RunI) while the other simulation uses monthly climatological soil moisture (soil liquid plus soil ice) to represent an uncoupled land surface (RunC). A winter land-atmosphere coupling signal occurs slightly south of the freezing line, indicating that the freezing line could be regarded as a temporally varying transition zone similar to the dry-to-wet transition zone identified in prior studies during boreal summer. Warmer soil temperatures in RunI translate into additional available surface energy (sum of latent and sensible heat) producing locally elevated moist static energy in the atmosphere. Additionally, warmer temperatures and greater moist static energy increase both large-scale (6–30% increase, March) and convective precipitation (>100% increase, April). As a result of the increased liquid precipitation during transition months, soil liquid water increases thereby warming winter ground and air temperatures in the interactive run and enhancing the potential for subsequent liquid precipitation. While RunC includes more persistent soil ice than is likely present in the real land-atmosphere system, this precipitation-soil moisture feedback underscores the role of soil moisture phase and variability as an important surface parameter in the winter months.

Spectral Behaviour of a Coupled Land-Surface and Boundary-Layer System

The temporal spectral response of a coupled land-atmosphere system to daily forcing of net radiation at the land surface is investigated using the analytic approach. The original definition of the problem dates back to an early study by Lettau. The present study builds on the problem and introduces some important additions, with a focus on the propagation of heat flux and temperature waves in both the soil and the atmospheric boundary layer. The study highlights the dependence of the complex amplitude of surface temperature and heat fluxes on the different land-surface parameters, such as friction velocity, evaporative fraction, aerodynamic resistance and vegetation height. Finally, the dependency of surface state variables to the frequency of the forcing is analyzed.

Integrating anthropogenic heat flux with global climate models

Nearly all energy used for human purposes is dissipated as heat within Earth's land–atmosphere system. Thermal energy released from non‐renewable sources is therefore a climate forcing term. Averaged globally, this forcing is only +0.028 W m−2, but over the continental United States and western Europe, it is +0.39 and +0.68 W m−2, respectively. Here, present and future global inventories of anthropogenic heat flux (AHF) are developed, and parameterizations derived for seasonal and diurnal flux cycles. Equilibrium climate experiments show statistically‐significant continental‐scale surface warming (0.4–0.9°C) produced by one 2100 AHF scenario, but not by current or 2040 estimates. However, significant increases in annual‐mean temperature and planetary boundary layer (PBL) height occur over gridcells where present‐day AHF exceeds 3.0 W m−2. PBL expansion leads to a slight, but significant increase in atmospheric residence time of aerosols emitted from large‐AHF regions. Hence, AHF may influence regional climate projections and contemporary chemistry‐climate studies.

An integrated high-resolution hydrometeorological modeling testbed using LIS and WRF

Interactions between the atmosphere and the land surface have considerable influences on weather and climate. Coupled land–atmosphere systems that can realistically represent these interactions are thus critical for improving our understanding of the atmosphere-biosphere exchanges of energy, water, and their associated feedbacks. NASA's Land Information System (LIS) is a high-resolution land data assimilation system that integrates advanced land surface models, high-resolution satellite and observational data, data assimilation techniques, and high performance computing tools. LIS has been coupled to the Weather Research and Forecasting (WRF) model, enabling a high-resolution land–atmosphere modeling system. Synthetic simulations using the coupled LIS–WRF system demonstrates the interoperable use of land surface models, high-resolution land surface data and other land surface modeling tools through LIS. Real case study simulations for a June 2002 International H2O Project (IHOP) day is conducted by executing LIS first in an uncoupled manner to generate high-resolution soil moisture and soil temperature initial conditions. During the case study period, the land surface (LIS) and the atmospheric (WRF) models are executed in a coupled manner using the LIS–WRF system. The results from the simulations illustrate the impact of accurate, high-resolution land surface conditions on improving the prediction of clouds and precipitation. Thus, the coupled LIS–WRF system provides a testbed to enable studies in improving our understanding and predictability of regional and global water and energy cycles.

Quantifying the Strength of Soil Moisture–Precipitation Coupling and Its Sensitivity to Changes in Surface Water Budget

Abstract This paper presents a new index to quantify the strength of soil moisture–precipitation coupling in AGCMs and explores how the soil moisture–precipitation coupling in Community Atmosphere Model version 3 (CAM3)–Community Land Model version 3 (CAM3–CLM3) responds to parameterization-induced surface water budget changes. Specifically, this study (a) compares the regions of strong coupling identified by the newly proposed index and the index currently used in the Global Land–Atmosphere Coupling Experiment (GLACE); (b) examines how the surface water budget changes influence the strength of soil moisture–precipitation coupling as measured by the two indexes, respectively; and (c) examines how these changes influence the memory of the coupled land–atmosphere system as measured by the correlation between soil moisture and subsequent precipitation. The new index and the GLACE index are consistent in identifying central North America and West Africa as major regions of strong coupling during June–August (JJA). However, in some areas of western Europe and of subtropical South America where the GLACE index is low, the new index suggests a modest significant coupling during JJA. In response to the surface water budget changes that presumably favor a stronger soil moisture–precipitation coupling, the new index increases, but the GLACE index decreases in a majority of the regions of modest-to-strong coupling, although both show some mixed response. Changes in the land–atmosphere system memory suggest an increase of coupling strength, consistent with results from the new index. The strong dependence of the GLACE index on the relative importance of atmospheric internal variability is identified as a potential cause for the differences between the two indexes. The two indexes emphasize different aspects of soil moisture–precipitation coupling, and one might be more suitable than the other depending on the purpose of individual studies.

Observed timescales of evapotranspiration response to soil moisture

The sensitivity of evapotranspiration (ET) to soil moisture storage plays an important role in the land‐atmosphere system. Yet little is known about its magnitude, or its dependence on vegetation, soil, and/or climate characteristics. Here we relate the sensitivity to the timescale of ET decay in absence of rainfall, and show that it can thus be derived from time series of ET alone. We analyze ET observations from 15 vegetated sites covering a range of climates conditions, yielding timescales of 15–35 days. Longer timescales (weaker ET sensitivity) are found in regions with seasonal droughts, or at sites with woody vegetation. We compare observed values with output of different land surface models (LSMs) from the Second Global Soil Wetness Project, revealing large inter‐model differences and significant differences with observations. Our methodology can lead to improved representation of soil moisture effects on ET in LSMs.

The Hydrologic Feedback Pathway for Land–Climate Coupling

Abstract The impact of improvements in land surface initialization and specification of observed rainfall in global climate model simulations of boreal summer are examined to determine how the changes propagate around the hydrologic cycle in the coupled land–atmosphere system. On the global scale, about 70% of any imparted signal in the hydrologic cycle is lost in the transition from atmosphere to land, and 70% of the remaining signal is lost from land to atmosphere. This means that globally, less than 10% of the signal of any change survives the complete circuit of the hydrologic cycle in this model. Regionally, there is a great deal of variability. Specification of observed precipitation to the land component of the climate model strongly communicates its signal to soil wetness in rainy regions, but predictive skill in evapotranspiration arises primarily in dry regions. A maximum in signal transmission to model precipitation exists in between, peaking where mean rainfall rates are 1.5–2 mm day−1. It appears that the nature of the climate system inherently limits to these regions the potential impact on prediction of improvements in the ability of models to simulate the water cycle. Land initial conditions impart a weaker signal on the system than replacement of precipitation, so a weaker response is realized in the system, focused mainly in dry regions.

Improving land-surface parameterization schemes using stable water isotopes: Introducing the ‘iPILPS’ initiative

iPILPS, isotopes in the Project for the Intercomparison of Land-surface Parameterization Schemes (PILPS), is a new stage in one of the longest running atmospheric/climate model intercomparison projects (MIPs). Its goal is to provide a rigorous framework within which isotopic simulations of the continental surface can be inter-compared, evaluated, validated and/or improved. Operating under the auspices of the Global Energy and Water Cycle Experiment's (GEWEX) Land–Atmosphere System Study, PILPS is an off-line intercomparison and improvement framework offered for land-surface schemes used in weather forecast, climate and Earth System models. This paper describes the motivation for iPILPS, emphasising the energy and water budget difficulties of current land-surface schemes (LSSs) and underlining the need for new tools with which to probe “correctness” of evapotranspiration parameterization. It also explains and describes the likely beneficial outcomes anticipated from including isotopes in land-surface parameterization evaluation. These are the potential to: improve parameterization of surface energy partition by current LSSs; add information leading to refinement of basin-wide water modelling; reduce the range in simulated carbon uptake in the whole biomass and its subcomponents; and fingerprint sources and sinks involved in specific processes allowing evaluation of LSSs and, hopefully, their validation.

THE SPATIAL AND TEMPORAL CHANGES OF PAN EVAPORATION FROM 1971 TO 2000 IN THE YELLOW RIVER BASIN

Evaporation is a critical process in the material and energy cycle of land-atmosphere system. The Yellow River basin (YRB) experienced severe water shortage in the past several decades. The spatial and temporal characteristics of pan evaporation (PE) and their changes are of vital importance to the understanding of the hydrological process and water resources in the YRB.In this paper, the temporal and spatial changes of PE in the YRB from 1971 to 2000 were examined in detail. The major findings are as the follows:(1) there was an increasing trend in the YRB for PE starting from the late of 1980's although the general trend of global PE change was decrease;(2) the PE decreased in most areas of the YRB in spring and summer, but most parts increased in autumn and winter. At the mean time there exist areas, like the Fenhe River basin, where PE increased in all the seasons; and (3) sunshine hours decrease and wind speed decrease were the major causes for PE decrease from 1971 to 2000 and sunshine increase led to PE increase from the late of 1980's.

A Role of the Soil Enthalpy in Land Memory*

Abstract Recent studies have identified a connection between the summer monsoon rainfall in the southwest United States and anomalies of the antecedent winter precipitation and snowpack in the northwest United States. This connection shows a seasonal-scale predictability of the precipitation and indicates a seasonal predictability of the land–atmosphere system (the “land memory”) in the western United States. Although some efforts have been devoted to understanding this predictability, the physical processes constituting it remain unexplained. In this empirical study, a potential source, the soil enthalpy, and its role in land memory are examined for the recent epoch of a strong land memory (1961–90). The rationale is that the soil enthalpy variation has magnitudes comparable to the atmospheric enthalpy changes at various time scales, and the soil enthalpy anomaly in the top 20–50-cm soil column can persist for 2–3 months. As shown by the major results of this study, a persistent negative anomaly of the s...

Groundwater influences on soil moisture and surface evaporation

Soil hydrological processes play an important role in land-atmosphere system. In most climate models, these processes are described by soil moisture variations in the first 2 m of soil resulting from precipitation, evaporation, and transpiration. Groundwater effects on soil moisture variations and surface evaporation are either neglected or not explicitly treated. Although groundwater may have a small effect on soil moisture in areas with a deep groundwater table, groundwater can act as a soil water source and have substantial effects in areas where the water table is near or within a model's soil column. How groundwater affects soil moisture, its vertical distribution, as well as the surface water flux are the issues addressed in this study. A soil hydrological model was developed to include groundwater effects by allowing water exchange between the unsaturated zone and groundwater. The model uses a vertically varying saturation hydraulic conductivity, and is evaluated using observations at one station in the Nebraska Sand Hills. Model results show its ability to describe the roles of groundwater in maintaining the observed soil moisture, especially in deep layers. In addition, comparisons show that the soil moisture content in the first meter of the soil column from the model with groundwater is 21% greater than that from a model without groundwater. High soil moisture content in the root zone results in increased evapotranspiration (ET). The average ET in three periods from 1998 to 2000 is 7–21% higher when groundwater is considered in the model. Because of the groundwater effects, spatial variations in the groundwater table can create an additional spatial variability of soil moisture and surface water flux. This additional variability could be important in development of storms in regions whose domain has a large portion with high groundwater table.