Hyperresolution global land surface modeling: meeting a grand challenge for monitoring Earth's terrestrial water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 109 unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Spatio-temporal surface soil heat flux estimates from satellite data: results for the AMMA experiment at the Fakara (Niger) supersite

This paper describes a method that employs Earth Observation (EO) data to calculate spatiotemporal estimates of soil heat flux, G, using a physically-based method (the Analytical Method). The method involves a harmonic analysis of land surface temperature (LST) data. It also requires an estimate of near-surface soil thermal inertia; this property depends on soil textural composition and varies as a function of soil moisture content. The EO data needed to drive the model equations, and the ground-based data required to provide verification of the method, were obtained over the Fakara domain within the African Monsoon Multidisciplinary Analysis (AMMA) program. LST estimates (3 km × 3 km, one image 15 min−1) were derived from MSG-SEVIRI data. Soil moisture estimates were obtained from ENVISAT-ASAR data, while estimates of leaf area index, LAI, (to calculate the effect of the canopy on G, largely due to radiation extinction) were obtained from SPOT-HRV images. The variation of these variables over the Fakara domain, and implications for values of G derived from them, were discussed. Results showed that this method provides reliable large-scale spatiotemporal estimates of G. Variations in G could largely be explained by the variability in the model input variables. Furthermore, it was shown that this method is relatively insensitive to model parameters related to the vegetation or soil texture. However, the strong sensitivity of thermal inertia to soil moisture content at low values of relative saturation (<0.2) means that in arid or semi-arid climates accurate estimates of surface soil moisture content are of utmost importance, if reliable estimates of G are to be obtained. This method has the potential to improve large-scale evaporation estimates, to aid land surface model prediction and to advance research that aims to explain failure in energy balance closure of meteorological field studies.

The impact of a seasonally ice free Arctic Ocean on the temperature, precipitation and surface mass balance of Svalbard

The observed decline in summer sea ice extent since the 1970s is predicted to continue until the Arctic Ocean is seasonally ice free during the 21st Century. This will lead to a much perturbed Arctic climate with large changes in ocean surface energy flux. Svalbard, located on the present day sea ice edge, contains many low lying ice caps and glaciers and is expected to experience rapid warming over the 21st Century. The total sea level rise if all the land ice on Svalbard were to melt completely is 0.02 m. The purpose of this study is to quantify the impact of climate change on Svalbard’s surface mass balance (SMB) and to determine, in particular, what proportion of the projected changes in precipitation and SMB are a result of changes to the Arctic sea ice cover. To investigate this a regional climate model was forced with monthly mean climatologies of sea surface temperature (SST) and sea ice concentration for the periods 1961–1990 and 2061–2090 under two emission scenarios. In a novel forcing experiment, 20th Century SSTs and 21st Century sea ice were used to force one simulation to investigate the role of sea ice forcing. This experiment results in a 3.5 m water equivalent increase in Svalbard’s SMB compared to the present day. This is because over 50 % of the projected increase in winter precipitation over Svalbard under the A1B emissions scenario is due to an increase in lower atmosphere moisture content associated with evaporation from the ice free ocean. These results indicate that increases in precipitation due to sea ice decline may act to moderate mass loss from Svalbard’s glaciers due to future Arctic warming.

Incorporation of water vapour transfer in the JULES Land Surface Model: implications for key soil variables and land surface fluxes

This study focuses on the mechanisms underlying water and heat transfer in upper soil layers, and their effects on soil physical prognostic variables and the individual components of the energy balance. The skill of the JULES (Joint UK Land Environment Simulator) land surface model (LSM) to simulate key soil variables, such as soil moisture content and surface temperature, and fluxes such as evaporation, is investigated. The Richards equation for soil water transfer, as used in most LSMs, was updated by incorporating isothermal and thermal water vapour transfer. The model was tested for three sites representative of semi-arid and temperate arid climates: the Jornada site (New Mexico, USA), Griffith site (Australia) and Audubon site (Arizona, USA). Water vapour flux was found to contribute significantly to the water and heat transfer in the upper soil layers. This was mainly due to isothermal vapour diffusion; thermal vapour flux also played a role at the Jornada site just after rainfall events. Inclusion of water vapour flux had an effect on the diurnal evolution of evaporation, soil moisture content and surface temperature. The incorporation of additional processes, such as water vapour flux among others, into LSMs may improve the coupling between the upper soil layers and the atmosphere, which in turn could increase the reliability of weather and climate predictions.

The role of northern Arabian Sea surface temperature biases in CMIP5 model simulations and future projections of Indian summer monsoon rainfall

Many climate models have problems simulating Indian summer monsoon rainfall and its variability, resulting in considerable uncertainty in future projections. Problems may relate to many factors, such as local effects of the formulation of physical parametrisation schemes, while common model biases that develop elsewhere within the climate system may also be important. Here we examine the extent and impact of cold sea surface temperature (SST) biases developing in the northern Arabian Sea in the CMIP5 multi-model ensemble, where such SST biases are shown to be common. Such biases have previously been shown to reduce monsoon rainfall in the Met Office Unified Model (MetUM) by weakening moisture fluxes incident upon India. The Arabian Sea SST biases in CMIP5 models consistently develop in winter, via strengthening of the winter monsoon circulation, and persist into spring and summer. A clear relationship exists between Arabian Sea cold SST bias and weak monsoon rainfall in CMIP5 models, similar to effects in the MetUM. Part of this effect may also relate to other factors, such as forcing of the early monsoon by spring-time excessive equatorial precipitation. Atmosphere-only future time-slice experiments show that Arabian Sea cold SST biases have potential to weaken future monsoon rainfall increases by limiting moisture flux acceleration through non-linearity of the Clausius-Clapeyron relationship. Analysis of CMIP5 model future scenario simulations suggests that, while such effects are likely small compared to other sources of uncertainty, models with large Arabian Sea cold SST biases suppress the range of potential outcomes for changes to future early monsoon rainfall.

Heat and moisture budgets from airborne measurements and high-resolution model simulations

High-resolution simulations with a mesoscale model are performed to estimate heat and moisture budgets of a well-mixed boundary layer. The model budgets are validated against energy budgets obtained from airborne measurements over heterogeneous terrain in Western Germany. Time rate of change, vertical divergence, and horizontal advection for an atmospheric column of air are estimated. Results show that the time trend of specific humidity exhibits some deficiencies, while the potential temperature trend is matched accurately. Furthermore, the simulated turbulent surface fluxes of sensible and latent heat are comparable to the measured fluxes, leading to similar values of the vertical divergence. The analysis of different horizontal model resolutions exhibits improved surface fluxes with increased resolution, a fact attributed to a reduced aggregation effect. Scale-interaction effects could be identified: while time trends and advection are strongly influenced by mesoscale forcing, the turbulent surface fluxes are mainly controlled by microscale processes.

Localization of deep water formation: role of atmospheric moisture transport and geometrical constraints on ocean circulation

A series of coupled atmosphere–ocean–ice aquaplanet experiments is described in which topological constraints on ocean circulation are introduced to study the role of ocean circulation on the mean climate of the coupled system. It is imagined that the earth is completely covered by an ocean of uniform depth except for the presence or absence of narrow barriers that extend from the bottom of the ocean to the sea surface. The following four configurations are described: Aqua (no land), Ridge (one barrier extends from pole to pole), Drake (one barrier extends from the North Pole to 35°S), and DDrake (two such barriers are set 90° apart and join at the North Pole, separating the ocean into a large basin and a small basin, connected to the south). On moving from Aqua to Ridge to Drake to DDrake, the energy transports in the equilibrium solutions become increasingly “realistic,” culminating in DDrake, which has an uncanny resemblance to the present climate. Remarkably, the zonal-average climates of Drake and DDrake are strikingly similar, exhibiting almost identical heat and freshwater transports, and meridional overturning circulations. However, Drake and DDrake differ dramatically in their regional climates. The small and large basins of DDrake exhibit distinctive Atlantic-like and Pacific-like characteristics, respectively: the small basin is warmer, saltier, and denser at the surface than the large basin, and is the main site of deep water formation with a deep overturning circulation and strong northward ocean heat transport. A sensitivity experiment with DDrake demonstrates that the salinity contrast between the two basins, and hence the localization of deep convection, results from a deficit of precipitation, rather than an excess of evaporation, over the small basin. It is argued that the width of the small basin relative to the zonal fetch of atmospheric precipitation is the key to understanding this salinity contrast. Finally, it is argued that many gross features of the present climate are consequences of two topological asymmetries that have profound effects on ocean circulation: a meridional asymmetry (circumpolar flow in the Southern Hemisphere; blocked flow in the Northern Hemisphere) and a zonal asymmetry (a small basin and a large basin).

Identification of micro-scale anthropogenic CO2, heat and moisture sources – processing eddy covariance fluxes for a dense urban environment

Anthropogenic emissions of heat and exhaust gases play an important role in the atmospheric boundary layer, altering air quality, greenhouse gas concentrations and the transport of heat and moisture at various scales. This is particularly evident in urban areas where emission sources are integrated in the highly heterogeneous urban canopy layer and directly linked to human activities which exhibit significant temporal variability. It is common practice to use eddy covariance observations to estimate turbulent surface fluxes of latent heat, sensible heat and carbon dioxide, which can be attributed to a local scale source area. This study provides a method to assess the influence of micro-scale anthropogenic emissions on heat, moisture and carbon dioxide exchange in a highly urbanized environment for two sites in central London, UK. A new algorithm for the Identification of Micro-scale Anthropogenic Sources (IMAS) is presented, with two aims. Firstly, IMAS filters out the influence of micro-scale emissions and allows for the analysis of the turbulent fluxes representative of the local scale source area. Secondly, it is used to give a first order estimate of anthropogenic heat flux and carbon dioxide flux representative of the building scale. The algorithm is evaluated using directional and temporal analysis. The algorithm is then used at a second site which was not incorporated in its development. The spatial and temporal local scale patterns, as well as micro-scale fluxes, appear physically reasonable and can be incorporated in the analysis of long-term eddy covariance measurements at the sites in central London. In addition to the new IMAS-technique, further steps in quality control and quality assurance used for the flux processing are presented. The methods and results have implications for urban flux measurements in dense urbanised settings with significant sources of heat and greenhouse gases.

The surface urban energy and water balance scheme (SUEWS): evaluation in Los Angeles and Vancouver

An urban energy and water balance model is presented which uses a small number of commonly measured meteorological variables and information about the surface cover. Rates of evaporation-interception for a single layer with multiple surface types (paved, buildings, coniferous trees and/or shrubs, deciduous trees and/or shrubs, irrigated grass, non-irrigated grass and water) are calculated. Below each surface type, except water, there is a single soil layer. At each time step the moisture state of each surface is calculated. Horizontal water movements at the surface and in the soil are incorporated. Particular attention is given to the surface conductance used to model evaporation and its parameters. The model is tested against direct flux measurements carried out over a number of years in Vancouver, Canada and Los Angeles, USA. At all measurement sites the model is able to simulate the net all-wave radiation and turbulent sensible and latent heat well (RMSE = 25–47 W m−2, 30–64 and 20–56 W m−2, respectively). The model reproduces the diurnal cycle of the turbulent fluxes but typically underestimates latent heat flux and overestimates sensible heat flux in the day time. The model tracks measured surface wetness and simulates the variations in soil moisture content. It is able to respond correctly to short-term events as well as annual changes. The largest uncertainty relates to the determination of surface conductance. The model has the potential be used for multiple applications; for example, to predict effects of regulation on urban water use, landscaping and planning scenarios, or to assess climate mitigation strategies.

Improved evaporative flux partitioning and carbon flux in the land surface model JULES: impact on the simulation of land surface processes in temperate Europe

The primary role of land surface models embedded in climate models is to partition surface available energy into upwards, radiative, sensible and latent heat fluxes. Partitioning of evapotranspiration, ET, is of fundamental importance: as a major component of the total surface latent heat flux, ET affects the simulated surface water balance, and related energy balance, and consequently the feedbacks with the atmosphere. In this context it is also crucial to credibly represent the CO2 exchange between ecosystems and their environment. In this study, JULES, the land surface model used in UK weather and climate models, has been evaluated for temperate Europe. Compared to eddy covariance flux measurements, the CO2 uptake by the ecosystem is underestimated and the ET overestimated. In addition, the contribution to ET from soil and intercepted water evaporation far outweighs the contribution of plant transpiration. To alleviate these biases, adaptations have been implemented in JULES, based on key literature references. These adaptations have improved the simulation of the spatio-temporal variability of the fluxes and the accuracy of the simulated GPP and ET, including its partitioning. This resulted in a shift of the seasonal soil moisture cycle. These adaptations are expected to increase the fidelity of climate simulations over Europe. Finally, the extreme summer of 2003 was used as evaluation benchmark for the use of the model in climate change studies. The improved model captures the impact of the 2003 drought on the carbon assimilation and the water use efficiency of the plants. It, however, underestimates the 2003 GPP anomalies. The simulations showed that a reduction of evaporation from the interception and soil reservoirs, albeit not of transpiration, largely explained the good correlation between the carbon and the water fluxes anomalies that was observed during 2003. This demonstrates the importance of being able to discriminate the response of individual component of the ET flux to environmental forcing.

The importance of moisture distribution for the growth and energetics of mid-latitude systems

A primitive equation model is used to study the sensitivity of baroclinic wave life cycles to the initial latitude-height distribution of humidity. Diabatic heating is parametrized only as a consequence of condensation in regions of large-scale ascent. Experiments are performed in which the initial relative humidity is a simple function of model level, and in some cases latitude bands are specified which are initially relatively dry. It is found that the presence of moisture can either increase or decrease the peak eddy kinetic energy of the developing wave, depending on the initial moisture distribution. A relative abundance of moisture at mid-latitudes tends to weaken the wave, while a relative abundance at low latitudes tends to strengthen it. This sensitivity exists because competing processes are at work. These processes are described in terms of energy box diagnostics. The most realistic case lies on the cusp of this sensitivity. Further physical parametrizations are then added, including surface fluxes and upright moist convection. These have the effect of increasing wave amplitude, but the sensitivity to initial conditions of relative humidity remains. Finally, 'control' and 'doubled CO2' life cycles are performed, with initial conditions taken from the time-mean zonal-mean output of equilibrium GCM experiments. The attenuation of the wave resulting from reduced baroclinicity is more pronounced than any effect due to changes in initial moisture.

Importance of initial state and atmospheric conditions for urban land surface models' performance

Urban land surface models (LSM) are commonly evaluated for short periods (a few weeks to months) because of limited observational data. This makes it difficult to distinguish the impact of initial conditions on model performance or to consider the response of a model to a range of possible atmospheric conditions. Drawing on results from the first urban LSM comparison, these two issues are considered. Assessment shows that the initial soil moisture has a substantial impact on the performance. Models initialised with soils that are too dry are not able to adjust their surface sensible and latent heat fluxes to realistic values until there is sufficient rainfall. Models initialised with too wet soils are not able to restrict their evaporation appropriately for periods in excess of a year. This has implications for short term evaluation studies and implies the need for soil moisture measurements to improve data assimilation and model initialisation. In contrast, initial conditions influencing the thermal storage have a much shorter adjustment timescale compared to soil moisture. Most models partition too much of the radiative energy at the surface into the sensible heat flux at the probable expense of the net storage heat flux.

Land surface feedbacks and palaeomonsoons in northern Africa

We ran a sequence of climate model experiments for 6000 years ago, with land-surface conditions based on a realistic map of palaeovegetation, lakes and wetlands, to quantify the effects of land-surface feedbacks in the Saharan region. Vegetation-induced albedo and moisture flux changes produced year-round warming, forced the monsoon to 17°–25°N two months earlier, and shifted the precipitation belt ≈300 km northwards compared to the effects of orbital forcing alone. The addition of lakes and wetlands produced localised changes in evaporation and precipitation, but caused no further extension of the monsoon belt. Diagnostic analyses with biome and continental hydrology models showed that the combined land-surface feedbacks, although substantial, could neither maintain grassland as far north as observed (≈26°N) nor maintain Lake “MegaChad” (330,000 km²).

ERA-Interim/Land: a global land surface reanalysis data set

ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

Modeling plant transpiration under limited soil water: comparison of different plant and soil hydraulic parameterizations and preliminary implications for their use in land surface models

Accurate estimates of how soil water stress affects plant transpiration are crucial for reliable land surface model (LSM) predictions. Current LSMs generally use a water stress factor, β, dependent on soil moisture content, θ, that ranges linearly between β = 1 for unstressed vegetation and β = 0 when wilting point is reached. This paper explores the feasibility of replacing the current approach with equations that use soil water potential as their independent variable, or with a set of equations that involve hydraulic and chemical signaling, thereby ensuring feedbacks between the entire soil–root–xylem–leaf system. A comparison with the original linear θ-based water stress parameterization, and with its improved curvi-linear version, was conducted. Assessment of model suitability was focused on their ability to simulate the correct (as derived from experimental data) curve shape of relative transpiration versus fraction of transpirable soil water. We used model sensitivity analyses under progressive soil drying conditions, employing two commonly used approaches to calculate water retention and hydraulic conductivity curves. Furthermore, for each of these hydraulic parameterizations we used two different parameter sets, for 3 soil texture types; a total of 12 soil hydraulic permutations. Results showed that the resulting transpiration reduction functions (TRFs) varied considerably among the models. The fact that soil hydraulic conductivity played a major role in the model that involved hydraulic and chemical signaling led to unrealistic values of β, and hence TRF, for many soil hydraulic parameter sets. However, this model is much better equipped to simulate the behavior of different plant species. Based on these findings, we only recommend implementation of this approach into LSMs if great care with choice of soil hydraulic parameters is taken