Surface-atmosphere Interactions Research Articles

Infrared and millimetre-wave scintillometry in the suburban environment – Part 2: Large-area sensible and latent heat fluxes

Abstract. A millimetre-wave scintillometer was paired with an infrared scintillometer, enabling estimation of large-area evapotranspiration across northern Swindon, a suburban area in the UK. Both sensible and latent heat fluxes can be obtained using this "two-wavelength" technique, as it is able to provide both temperature and humidity structure parameters, offering a major advantage over conventional single-wavelength scintillometry. The first paper of this two-part series presented the measurement theory and structure parameters. In this second paper, heat fluxes are obtained and analysed. These fluxes, estimated using two-wavelength scintillometry over an urban area, are the first of their kind. Source area modelling suggests the scintillometric fluxes are representative of 5–10 km2. For comparison, local-scale (0.05–0.5 km2) fluxes were measured by an eddy covariance station. Similar responses to seasonal changes are evident at the different scales but the energy partitioning varies between source areas. The response to moisture availability is explored using data from 2 consecutive years with contrasting rainfall patterns (2011–2012). This extensive data set offers insight into urban surface-atmosphere interactions and demonstrates the potential for two-wavelength scintillometry to deliver fluxes over mixed land cover, typically representative of an area 1–2 orders of magnitude greater than for eddy covariance measurements. Fluxes at this scale are extremely valuable for hydro-meteorological model evaluation and assessment of satellite data products.

An estimation of the land‐atmosphere coupling strength in South America using the Global Land Data Assimilation System

ABSTRACTThe aim of this study is to identify regions of strong land surface –atmosphere coupling for the austral summer over South America. To accomplish this, a statistical methodology is applied to estimate the interactions of soil moisture with evapotranspiration and precipitation derived from the Global Land Data Assimilation System (GLDAS) dataset. Possible impacts of El Niño Southern Oscillation (ENSO) on the coupling strength are also examined. Particular emphasis is set over two sub‐regions of interest: Southeastern South America (SESA) and the continental part of the South Atlantic Convergence Zone (SACZ). Positive and significant soil moisture–precipitation feedbacks are found over parts of SACZ and in the southern part of South America. Instead, significant negative feedback is found over SESA. The influence of ENSO over the soil moisture–precipitation coupling strength signal is evident over tropical regions. Plausible physical mechanisms involved in the land surface–atmosphere interactions, the influence of ENSO and that of precipitation persistence over extratropical regions on the results, are discussed. The implications of this analysis on monthly to seasonal forecast are also examined. Despite that this methodology cannot be used to establish a precise causal–effect relationship, this study gives a valuable first order approximation of land surface–atmosphere interactions over South America that complements pre‐existing work.

An ecosystem services perspective on brush management: research priorities for competing land‐use objectives

Summary The vegetation of semi‐arid and arid landscapes is often comprised of mixtures of herbaceous and woody vegetation. Since the early 1900s, shifts from herbaceous to woody plant dominance, termed woody plant encroachment and widely regarded as a state change, have occurred world‐wide. This shift presents challenges to the conservation of grassland and savanna ecosystems and to animal production in commercial ranching systems and pastoral societies. Dryland management focused on cattle and sheep grazing has historically attempted to reduce the abundance of encroaching woody vegetation (hereafter, ‘brush management’) with the intent of reversing declines in forage production, stream flow or groundwater recharge. Here, we assess the known and potential consequences of brush management actions, both positive and negative, on a broader suite of ecosystem services, the scientific challenges to quantifying these services and the trade‐offs among them. Our synthesis suggests that despite considerable investments accompanying the application of brush management practices, the recovery of key ecosystem services may be short‐lived or absent. However, in the absence of such interventions, those and other ecosystem services may be compromised, and the persistence of grassland and savanna ecosystem types and their endemic plants and animals threatened. Addressing the challenges posed by woody plant encroachment will require integrated management systems using diverse theoretical principles to design the type, timing and spatial arrangement of initial management actions and follow‐up treatments. These management activities will need to balance cultural traditions and preferences, socio‐economic constraints and potentially competing land‐use objectives. Synthesis. Our ability to predict ecosystem responses to management aimed at recovering ecosystem services where grasslands and savannas have been invaded by native or exotic woody plants is limited for many attributes (e.g. primary production, land surface–atmosphere interactions, biodiversity conservation) and inconsistent for others (e.g. forage production, herbaceous diversity, water quality/quantity, soil erosion, carbon sequestration). The ecological community is challenged with generating robust information about the response of ecosystem services and their interactions if we are to position land managers and policymakers to make objective, science‐based decisions regarding the many trade‐offs and competing objectives for the conservation and dynamic management of grasslands and savannas.

Regional Model Simulations of the 2008 Drought in Southern South America Using a Consistent Set of Land Surface Properties

AbstractThis work discusses the land surface–atmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model–Noah land surface model (WRF–Noah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes.The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system.

Land Surface Temperature Retrieval from MODIS Data by Integrating Regression Models and the Genetic Algorithm in an Arid Region

The land surface temperature (LST) is one of the most important parameters of surface-atmosphere interactions. Methods for retrieving LSTs from satellite remote sensing data are beneficial for modeling hydrological, ecological, agricultural and meteorological processes on Earth’s surface. Many split-window (SW) algorithms, which can be applied to satellite sensors with two adjacent thermal channels located in the atmospheric window between 10 μm and 12 μm, require auxiliary atmospheric parameters (e.g., water vapor content). In this research, the Heihe River basin, which is one of the most arid regions in China, is selected as the study area. The Moderate-resolution Imaging Spectroradiometer (MODIS) is selected as a test case. The Global Data Assimilation System (GDAS) atmospheric profiles of the study area are used to generate the training dataset through radiative transfer simulation. Significant correlations between the atmospheric upwelling radiance in MODIS channel 31 and the other three atmospheric parameters, including the transmittance in channel 31 and the transmittance and upwelling radiance in channel 32, are trained based on the simulation dataset and formulated with three regression models. Next, the genetic algorithm is used to estimate the LST. Validations of the RM-GA method are based on the simulation dataset generated from in situ measured radiosonde profiles and GDAS atmospheric profiles, the in situ measured LSTs, and a pair of daytime and nighttime MOD11A1 products in the study area. The results demonstrate that RM-GA has a good ability to estimate the LSTs directly from the MODIS data without any auxiliary atmospheric parameters. Although this research is for local application in the Heihe River basin, the findings and proposed method can easily be extended to other satellite sensors and regions with arid climates and high elevations.

Quantifying the influence of deep soil moisture on ecosystem albedo: The role of vegetation

As changes in precipitation dynamics continue to alter the water availability in dryland ecosystems, understanding the feedbacks between the vegetation and the hydrologic cycle and their influence on the climate system is critically important. We designed a field campaign to examine the influence of two-layer soil moisture control on bare and canopy albedo dynamics in a semiarid shrubland ecosystem. We conducted this campaign during 2011 and 2012 within the tower footprint of the Santa Rita Creosote Ameriflux site. Albedo field measurements fell into one of four Cases within a two-layer soil moisture framework based on permutations of whether the shallow and deep soil layers were wet or dry. Using these Cases, we identified differences in how shallow and deep soil moisture influence canopy and bare albedo. Then, by varying the number of canopy and bare patches within a gridded framework, we explore the influence of vegetation and soil moisture on ecosystem albedo. Our results highlight the importance of deep soil moisture in land surface-atmosphere interactions through its influence on aboveground vegetation characteristics. For instance, we show how green-up of the vegetation is triggered by deep soil moisture, and link deep soil moisture to a decrease in canopy albedo. Understanding relationships between vegetation and deep soil moisture will provide important insights into feedbacks between the hydrologic cycle and the climate system.

Multi-Scale Sensible Heat Fluxes in the Suburban Environment from Large-Aperture Scintillometry and Eddy Covariance

Sensible heat fluxes ( $$Q_{H}$$ ) are determined using scintillometry and eddy covariance over a suburban area. Two large-aperture scintillometers provide spatially integrated fluxes across path lengths of 2.8 and 5.5 km over Swindon, UK. The shorter scintillometer path spans newly built residential areas and has an approximate source area of 2–4 $$\text {km}^{2}$$ , whilst the long path extends from the rural outskirts to the town centre and has a source area of around 5–10 $$\text {km}^{2}$$ . These large-scale heat fluxes are compared with local-scale eddy-covariance measurements. Clear seasonal trends are revealed by the long duration of this dataset and variability in monthly $$Q_{H}$$ is related to the meteorological conditions. At shorter time scales the response of $$Q_{H}$$ to solar radiation often gives rise to close agreement between the measurements, but during times of rapidly changing cloud cover spatial differences in the net radiation ( $$Q^{*}$$ ) coincide with greater differences between heat fluxes. For clear days $$Q_{H}$$ lags $$Q^{*}$$ , thus the ratio of $$Q_{H}$$ to $$Q^{*}$$ increases throughout the day. In summer the observed energy partitioning is related to the vegetation fraction through use of a footprint model. The results demonstrate the value of scintillometry for integrating surface heterogeneity and offer improved understanding of the influence of anthropogenic materials on surface-atmosphere interactions.

Alteration of Hawaiian basalts under sulfur-rich conditions: Applications to understanding surface-atmosphere interactions on Mars and Venus

A suite of Hawaiian basalts that were variably altered in the presence of SO 2 -rich gases during the current summit eruptive episode at Halemaumau crater, Kilauea, were studied to determine their alteration phase assemblage and reactive pathways using electron microscopy, Mossbauer spectroscopy, and X-ray diffraction. The alteration conditions represent an acid fog environment. Alteration rinds on the basalts vary in thickness from tens of micrometers to the entirety of the rock and are composed of amorphous silica rims (85–95 wt% SiO 2 ) overlain by sulfates. Sulfate mineralogy consisted of gypsum, anhydrite, and natroalunite-jarosite. No phyllosilicates were observed in any alteration assemblages. Phenocrysts and glass were both observed to be extensively reacted during alteration. The Halemaumau samples may provide good analogs for basalt alteration on other rocky planetary bodies, i.e., Mars, Venus, and Mercury, where S is ubiquitous and low fluid/rock ratios are common.

Kuo‐Nan Liou Receives 2013 Roger Revelle Medal: Citation

The Revelle Medal is awarded for “outstanding contributions in atmospheric sciences, atmosphere‐ocean coupling, atmosphere‐land coupling, biogeochemical cycles, climate, or related aspects of the Earth system.” It also celebrates the man Roger Revelle, who through his broad interests, his awareness of global change, and his national and international service, was a true statesman of science. Dr. Kuo‐Nan Liou's accomplishments in research and leadership service are the perfect embodiment of this ideal. He made trailblazing contributions in radiation, the prime driver in the Earth's energy budget, and in cloud physics; both are fundamental to our understanding of climate dynamics and atmosphere‐surface interactions. Moreover, his leadership successively as chair of two departments and as director of two separate Institutes and his outreach initiatives in spearheading hydrologic‐atmospheric experimentation and in founding the Joint Institute for Regional Earth System Science and Engineering at UCLA reveal him to be a true leader in the image of Roger Revelle.

Cloud and boundary layer interactions over the Arctic sea ice in late summer

Abstract. Observations from the Arctic Summer Cloud Ocean Study (ASCOS), in the central Arctic sea-ice pack in late summer 2008, provide a detailed view of cloud–atmosphere–surface interactions and vertical mixing processes over the sea-ice environment. Measurements from a suite of ground-based remote sensors, near-surface meteorological and aerosol instruments, and profiles from radiosondes and a helicopter are combined to characterize a week-long period dominated by low-level, mixed-phase, stratocumulus clouds. Detailed case studies and statistical analyses are used to develop a conceptual model for the cloud and atmosphere structure and their interactions in this environment. Clouds were persistent during the period of study, having qualities that suggest they were sustained through a combination of advective influences and in-cloud processes, with little contribution from the surface. Radiative cooling near cloud top produced buoyancy-driven, turbulent eddies that contributed to cloud formation and created a cloud-driven mixed layer. The depth of this mixed layer was related to the amount of turbulence and condensed cloud water. Coupling of this cloud-driven mixed layer to the surface boundary layer was primarily determined by proximity. For 75% of the period of study, the primary stratocumulus cloud-driven mixed layer was decoupled from the surface and typically at a warmer potential temperature. Since the near-surface temperature was constrained by the ocean–ice mixture, warm temperatures aloft suggest that these air masses had not significantly interacted with the sea-ice surface. Instead, back-trajectory analyses suggest that these warm air masses advected into the central Arctic Basin from lower latitudes. Moisture and aerosol particles likely accompanied these air masses, providing necessary support for cloud formation. On the occasions when cloud–surface coupling did occur, back trajectories indicated that these air masses advected at low levels, while mixing processes kept the mixed layer in equilibrium with the near-surface environment. Rather than contributing buoyancy forcing for the mixed-layer dynamics, the surface instead simply appeared to respond to the mixed-layer processes aloft. Clouds in these cases often contained slightly higher condensed water amounts, potentially due to additional moisture sources from below.

Sensible heat flux records constrain projections of European warming

Rising atmospheric concentrations of greenhouse gases are adding more energy to the Earth system, but how that extra energy turns to heat—and where that heating takes place—depends in part on regional variations in how the atmosphere and the land surface interact. Based on a historically high susceptibility to natural climate variability, driven in part by such land surface–atmosphere interactions, researchers expect Europe to be more strongly affected by climate change than some other regions.

Progress and opportunities for monitoring greenhouse gases fluxes in Mexican ecosystems: the MexFlux network

Understanding ecosystem processes from a functional point of view is essential to study relationships among climate variability, biogeochemical cycles, and surface-atmosphere interactions. Increasingly during the last decades, the eddy covariance (EC) method has been applied in terrestrial, marine and urban ecosystems to quantify fluxes of greenhouse gases (e.g., CO2, H2O) and energy (e.g., sensible and latent heat). Networks of EC systems have been established in different regions and have provided scientific information that has been used for designing environmental and adaptation policies. In this context, this article outlines the conceptual and technical framework for the establishment of an EC regional network (i.e., MexFlux) to measure the surface-atmosphere exchange of heat and greenhouse gases in Mexico. The goal of the network is to improve our understanding of how climate variability and environmental change influence the dynamics of Mexican ecosystems. First, we discuss the relevance of CO2 and water vapor exchange between terrestrial ecosystems and the atmosphere. Second, we briefly describe the EC basis and present examples of measurements in terrestrial and urban ecosystems of Mexico. Finally, we describe the conceptual and operational goals at short-, medium-, and long-term scales for continuity of the MexFlux network.

Adjustment of A Simplified Satellite-Based Algorithm for Gross Primary Production Estimation Over Korea

Monitoring the global gross primary production (GPP) is relevant to understanding the global carbon cycle and evaluating the effects of interannual climate variation on food and fiber production. GPP, the flux of carbon into ecosystems via photosynthetic assimilation, is an important variable in the global carbon cycle and a key process in land surface–atmosphere interactions. The Moderate-resolution Imaging Spectroradiometer (MODIS) is one of the primary global monitoring sensors. MODIS GPP has some of the problems that have been proven in several studies. Therefore this study was to solve the regional mismatch that occurs when using the MODIS GPP global product over Korea. To solve this problem, we estimated each of the GPP component variables separately to improve the GPP estimates. We compared our GPP estimates with validation GPP data to assess their accuracy. For all sites, the correlation was close with high significance (R 2 = 0.8164, RMSE = 0.6126 g·C·m –2 ·d –1 , bias = –0.0271 g·C·m –2 ·d –1 ). We also compared our results to those of other models. The component variables tended to be either over- or under-estimated when compared to those in other studies over the Korean peninsula, although the estimated GPP was better. The results of this study will likely improve carbon cycle modeling by capturing finer patterns with an integrated method of remote sensing.

Leaf area index estimation in semiarid mixed grassland by considering both temporal and spatial variations

Leaf area index (LAI) estimation in a mixed grassland ecosystem is limited by temporal and spatial variations controlled by land surface heterogeneity and ecological parameters. Therefore, simply estimated LAI usually has difficulty in meeting the requirements of the land surface–atmosphere interaction models. We estimated LAI based on the relationship between LAI and normalized difference vegetation index (NDVI) by considering temporal and spatial variations. Spatial variations of both LAI and NDVI were investigated using the Morlet wavelet approach. Based on the ground reflectance data, LAI estimation can be greatly improved by taking temporal and spatial variations into account. The coefficient of determination (r 2 ) values of the LAI-NDVI equations were increased by 0.28, 0.51, and 0.44 in the early, maximum, and late growing seasons, respectively. LAI estimation from SPOT 4/5 and Landsat TM 5 images confirmed the applicability of the proposed estimation approach.

Annual survey of water vapor vertical distribution and water–aerosol coupling in the martian atmosphere observed by SPICAM/MEx solar occultations

The vertical distribution of water vapor is a very important diagnostic to determine the physical and chemical processes that drive the martian water cycle. Yet, very few direct measurements have been performed so far, and our knowledge of the H2O vertical distribution on Mars relies on General Circulation Models (GCMs). The study presented here follows for the first time the evolution of water vapor profile during a martian year. 120 profiles, obtained by the SPICAM spectrometer onboard Mars Express with the solar occultations technique, are retrieved. They cover the northern spring-summer season and the southern spring of Mars Year (MY) 29. The seasonal evolution of H2O mixing ratio vertical distribution reveals its strong dynamism, especially during southern spring. There are significant discrepancies with the predictions of the General Circulation Model developed at the Laboratoire de Météorologie Dynamique (LMD-GCM). The LMD-GCM underestimates the water vapor content in the middle atmosphere. The measured profiles also exhibit often abrupt temporal variations and a greater variety of shapes, with the frequent presence of detached layers. We believe that the model underestimates the strength of the coupling between water vapor and aerosols, whose slant optical depth profile is obtained by SPICAM simultaneously with H2O. The SPICAM measurements can be grouped according to the mutual behavior of the two profiles. Individual features are often related too. The presence of water supersaturation and of correlated aerosol–water detached layers highlights the role of water ice clouds as a favorable location for the dust–water coupling. The water vapor vertical distribution is more reactive than expected to regional perturbations, which can propagate rapidly through the atmosphere, create abrupt water vapor and aerosol upsurges and influence the large-scale vertical evolution of these two constituents. This phenomenon has been observed thrice during MY29. The martian annual water cycle revealed by the SPICAM profiles exhibits a different behavior with respect to nadir observations. This result suggests a generally weak connection between the upper atmosphere and the lower atmospheric layers, to whom the nadir measurements are most sensitive and that are not resolved by SPICAM occultations, and hints at a significant influence of surface-atmosphere interactions on the water cycle.

What controls the error structure in evapotranspiration models?

Evapotranspiration models allow climate modelers to describe surface–atmosphere interactions, ecologists to understand the impact that global temperature change and increased radiation budgets will have on ecosystems, and farmers to decide how much irrigation to give their crops. Physically based algorithms for estimating evapotranspiration must manage a trade-off between physical realism and the difficulty of parameterizing key inputs, namely resistance factors associated with water vapor transport through the canopy and turbulent transport of water vapor from the canopy to ambient air. In this study we calculate predicted evapotranspiration at 42 AmeriFlux sites using two types of dedicated evapotranspiration models—one using physical resistances from the Penman–Monteith equation (Monteith, 1965) (Mu et al., 2007, 2011) and another based on the Priestley–Taylor (1972) equation, substituting functional constraints for resistances (Fisher et al., 2008). We analyze the structure of the residual series with respect to various meteorological and biophysical inputs, specifically Jarvis and McNaughton's (1986) decoupling coefficient, Ω, which is designed to represent the degree of control that plant stomata versus atmospheric demand and net radiation exercise over transpiration. We find that vegetation indices, magnitude of daytime fluxes, and bulk canopy resistance (rc)—which largely drives Ω—are strong predictors of patterns in model bias for all flux products. Though our analysis suggests a consistently negative relationship between Ω and mean predicted error for all evapotranspiration models, we found that vegetation indices and flux magnitudes were the most significant drivers of model error. Before addressing error associated with canopy resistance and Ω, refinements to existing models should focus on correcting biases with respect to flux magnitudes and canopy indices. We suggest a dual-model approach for backsolving rc (rather than estimating it from lookup tables and canopy indices), and increased attention to water availability, which largely drives stomatal opening and closure.

Global modelling of the early martian climate under a denser CO2 atmosphere: Water cycle and ice evolution

We discuss 3D global simulations of the early martian climate that we have performed assuming a faint young Sun and denser CO2 atmosphere. We include a self-consistent representation of the water cycle, with atmosphere–surface interactions, atmospheric transport, and the radiative effects of CO2 and H2O gas and clouds taken into account. We find that for atmospheric pressures greater than a fraction of a bar, the adiabatic cooling effect causes temperatures in the southern highland valley network regions to fall significantly below the global average. Long-term climate evolution simulations indicate that in these circumstances, water ice is transported to the highlands from low-lying regions for a wide range of orbital obliquities, regardless of the extent of the Tharsis bulge. In addition, an extended water ice cap forms on the southern pole, approximately corresponding to the location of the Noachian/Hesperian era Dorsa Argentea Formation. Even for a multiple-bar CO2 atmosphere, conditions are too cold to allow long-term surface liquid water. Limited melting occurs on warm summer days in some locations, but only for surface albedo and thermal inertia conditions that may be unrealistic for water ice. Nonetheless, meteorite impacts and volcanism could potentially cause intense episodic melting under such conditions. Because ice migration to higher altitudes is a robust mechanism for recharging highland water sources after such events, we suggest that this globally sub-zero, ‘icy highlands’ scenario for the late Noachian climate may be sufficient to explain most of the fluvial geology without the need to invoke additional long-term warming mechanisms or an early warm, wet Mars.

IMPACT OF EL NIÑO AND LA NIÑA ON SOIL MOISTURE- PRECIPITATION FEEDBACK OF INDIAN MONSOON OVER CENTRAL INDIA

Abstract. The processes across an interface between land surface and the atmosphere over central India have a strong impact on the Indian summer monsoon climate, particularly during extreme years. The soil moisture-climate interactions, i.e. impacts on temperature and precipitation for years of excess (1999,2010) and deficit (1987,2009) rainfall over central India are being analyzed. For this study, two land surface parameterization schemes the Biosphere Atmosphere Transfer scheme (BATS) and the Community Land Model (CLM) were coupled using the regional climate model RegCM4.0. Soil moisture-temperature coupling and soil moisture-precipitation feedbacks are important land surface atmosphere interactions in context of climate change scenario. As feedbacks between land and atmosphere are hard to measure directly, correlation between temperature and evapotranspiration is the diagnostic used for assessing soil moisture-evapotranspiration-temperature coupling strength and simple statistic called "normalized feedback parameter" λNC of soil moisture and precipitation is used to access the strength of soil moisture precipitation feedback at a regional scale. The soil moisture – atmosphere coupling strength in BATS scheme coupled with RegCM4.0 is more than the coupling strength in the CLM scheme enabled with RegCM4.0. From our study it is validated that central India is the region in the Indian monsoon domain where profound soil moisture-climate interactions take place at a regional scale.

Evaluation of a Dynamic Agroecosystem Model (Agro-IBIS) for Soybean in Southern Brazil

Abstract With the growing demands for food and biofuel, new technologies and crop management systems are being used to increase productivity and minimize land-use impacts. In this context, estimates of productivity and the impacts of agriculture management practices are becoming increasingly important. Numerical models that describe the soil–surface–atmosphere interactions for natural and agricultural ecosystems are important tools to explore the impacts of these agronomical technologies and their environmental impacts. However, these models need to be validated by considering the different soil and environmental conditions before they can be widely applied. The process-based terrestrial agricultural version of the Integrated Biosphere Simulator (IBIS) model (Agro-IBIS) has only been calibrated and validated for North American sites. Here, the authors validate the Agro-IBIS results for an experimental soybean site in southern Brazil. At this site, soybean was grown under two different management systems: no tillage (NT) and conventional tillage (CT). The model results were evaluated against micrometeorological, soil condition, and biomass observations made during the soybean growing season. The leaf area index (LAI) was underestimated, approaching the values obtained in the CT crop system, with higher error in the leaf senescence period. The model shows higher skill for daily averages and the diurnal cycle of the energy balance components in the period of high LAI. The soil temperature and moisture were robustly simulated, although the latter is best correlated with the observations made at the CT field. The ecosystem respiration is highly underestimated, causing an overestimation of the cumulative net ecosystem exchange (NEE), particularly at the end of the crop cycle.

Infrared Continental Surface Emissivity Spectra and Skin Temperature Retrieved from IASI Observations over the Tropics

AbstractLand surface temperature and emissivity spectra are essential variables for improving models of the earth surface–atmosphere interaction or retrievals of atmospheric variables such as thermodynamic profiles, chemical composition, cloud and aerosol characteristics, and so on. In most cases, emissivity spectral variations are not correctly taken into account in climate models, leading to potentially significant errors in the estimation of surface energy fluxes and temperature. Satellite infrared observations offer the dual opportunity of accurately estimating these properties of land surfaces as well as allowing a global coverage in space and time. Here, high-spectral-resolution observations from the Infrared Atmospheric Sounder Interferometer (IASI) over the tropics (30°N–30°S), covering the period July 2007–March 2011, are interpreted in terms of 1° × 1° monthly mean surface skin temperature and emissivity spectra from 3.7 to 14 μm at a resolution of 0.05 μm. The standard deviation estimated for the surface temperature is about 1.3 K. For the surface emissivity, it varies from about 1%–1.5% for the 10.5–14- and 5.5–8-μm windows to about 4% around 4 μm. Results from comparisons with products such as Moderate Resolution Imaging Spectroradiometer (MODIS) low-resolution emissivity and surface temperature or ECMWF forecast data (temperature only) are presented and discussed. Comparisons with emissivity derived from the Airborne Research Interferometer Evaluation System (ARIES) radiances collected during an aircraft campaign over Oman and made at the scale of the IASI field of view offer valuable data for the validation of the IASI retrievals.