Kaniska Mallick

Latent Heat Flux and Canopy Conductance Based on Penman-Monteith, Priestley-Taylor Equation, and Bouchet's Complementary Hypothesis

A novel method is presented to analytically resolve the terrestrial latent heat flux (lE) and conductances (boundary layer gB and surface gS) using net radiation (RN), ground heat flux (G), air temperature (Ta), and relative humidity (RH). This method consists of set of equations where the two unknown internal state variables (gB and gS) were expressed in terms of the known core variables, combining diffusion equations, the Penman‐Monteith equation, the Priestley‐Taylor equation, and Bouchet’s complementary hypothesis. Estimated lE is validated with the independent eddy covariance lE observations over Soil Moisture Experiment 2002 (SMEX-02); the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP) selected sites from FLUXNET and tropics eddy flux, representing four climate zones (tropics, subtropics, temperate, and cold); and multiple biomes. The authors find a RMSE of 23.8‐ 54.6 W m 22 for hourly lEover SMEX-02 and GCIP and 23.8‐29.0 W m 22 for monthlylEover the FLUXNET and tropics. Observational and modeled evidence in the reduction in annual evaporation (E) pattern on the order of 33% from 1999 to 2006 was found in central Amazonia. Retrieved gS responded to vapor pressure deficit, measured lE, and gross photosynthesis in a theoretically robust behavior. However, the current scheme [Penman‐Monteith‐Bouchet‐Lhomme (PMBL)] showed some overestimation of lE in limited soil moisture regimes. PMBL provides similar results when compared with another Priestley‐Taylor‐based lE estimation approach [Priestley‐Taylor‐Jet Propulsion Laboratory (PT-JPL)] but with the advantage of having the conductances analytically recovered.

Reintroducing radiometric surface temperature into the Penman‐Monteith formulation

Here we demonstrate a novel method to physically integrate radiometric surface temperature (TR) into the Penman-Monteith (PM) formulation for estimating the terrestrial sensible and latent heat fluxes (H and λE) in the framework of a modified Surface Temperature Initiated Closure (STIC). It combines TR data with standard energy balance closure models for deriving a hybrid scheme that does not require parameterization of the surface (or stomatal) and aerodynamic conductances (gS and gB). STIC is formed by the simultaneous solution of four state equations and it uses TR as an additional data source for retrieving the “near surface” moisture availability (M) and the Priestley-Taylor coefficient (α). The performance of STIC is tested using high-temporal resolution TR observations collected from different international surface energy flux experiments in conjunction with corresponding net radiation (RN), ground heat flux (G), air temperature (TA), and relative humidity (RH) measurements. A comparison of the STIC outputs with the eddy covariance measurements of λE and H revealed RMSDs of 7–16% and 40–74% in half-hourly λE and H estimates. These statistics were 5–13% and 10–44% in daily λE and H. The errors and uncertainties in both surface fluxes are comparable to the models that typically use land surface parameterizations for determining the unobserved components (gS and gB) of the surface energy balance models. However, the scheme is simpler, has the capabilities for generating spatially explicit surface energy fluxes and independent of submodels for boundary layer developments.

Global surface net-radiation at 5 km from MODIS Terra

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott’s index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W∙m−2 in boreal to 72.0 ± 4.1 W∙m−2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° × 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth’s Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10 W·m−2 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth’s surface.

On the net surface water exchange rate estimated from remote-sensing observation and reanalysis

This study compares the net surface water exchange rates, or surface precipitation (P) minus evapotranspiration (ET), and atmospheric water vapour sinks calculated from various observations and reanalyses, and investigates whether they are physically consistent. We use the observed precipitation from the Global Precipitation Climatology Project (GPCP) and the Tropical Rainfall Measuring Mission (TRMM) 3B43, ocean evaporation from Goddard Satellite-based Surface Turbulent Fluxes Version 2c (GSSTF2c), and land ET from the Moderate Resolution Imaging Spectroradiometer (MODIS) global ET project (MOD16) and PT-JPL products to calculate observed P minus observed ET. P–ET is also obtained from atmospheric water vapour sink calculated using Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit observation specific humidity observation and wind fields from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and ERA-interim, denoted as AIRSM and AIRSE, respectively. MERRA and ERA-interim water vapour budgets are also calculated for cross-comparison and consistency check. The period of study is between 2003 and 2006 based on the availability of all of the data sets. Averaged water vapour sinks from AIRS and reanalysis are consistent over the global ocean and are close to zero (range: 0.02–0.06 mm day−1), but range between 0.14 and 0.23 mm day−1 when land is included. Over ocean within 50oS--50oN, averaged observed P minus observed evaporation shows a much larger negative number than that obtained from AIRS and reanalysis. The differences mainly occur over subtropical oceans, especially in the southern hemisphere in summer and the northern hemisphere in winter. Over land, generally higher agreement between observed P minus observed ET and atmospheric water vapour sinks (calculated from AIRS and reanalysis) is found. However, large regional differences, often with strong seasonal dependence, are also observed over land. Estimates of atmospheric water vapour sinks are influenced by both winds and biases in water vapour data, especially over tropics and subtropical oceans, thereby calling for the need for further investigations and consistency checks of satellite-based and reanalysis water vapour, reanalysis winds, P observations, and surface evaporation estimates. In higher latitudes, atmospheric water vapour sinks calculated from AIRSM, AIRSE, MERRA, and ERA-interim are more consistent with each other.

Bridging Thermal Infrared Sensing and Physically‐Based Evapotranspiration Modeling: From Theoretical Implementation to Validation Across an Aridity Gradient in Australian Ecosystems

Thermal infrared sensing of evapotranspiration (E) through surface energy balance (SEB) models is challenging due to uncertainties in determining the aerodynamic conductance (gA) and due to inequalities between radiometric (TR) and aerodynamic temperatures (T0). We evaluated a novel analytical model, the Surface Temperature Initiated Closure (STIC1.2), that physically integrates TR observations into a combined Penman-Monteith Shuttleworth-Wallace (PM-SW) framework for directly estimating E, and overcoming the uncertainties associated with T0 and gA determination. An evaluation of STIC1.2 against high temporal frequency SEB flux measurements across an aridity gradient in Australia revealed a systematic error of 10–52% in E from mesic to arid ecosystem, and low systematic error in sensible heat fluxes (H) (12– 25%) in all ecosystems. Uncertainty in TR versus moisture availability relationship, stationarity assumption in surface emissivity, and SEB closure corrections in E were predominantly responsible for systematic E errors in arid and semi-arid ecosystems. A discrete correlation (r) of the model errors with observed soil moisture variance (r 5 0.33–0.43), evaporative index (r 5 0.77–0.90), and climatological dryness (r 5 0.60–0.77) explained a strong association between ecohydrological extremes and TR in determining the error structure of STIC1.2 predicted fluxes. Being independent of any leaf-scale biophysical parameterization, the model might be an important value addition in working group (WG2) of the Australian Energy and Water Exchange (OzEWEX) research initiative which focuses on observations to evaluate and compare biophysical models of energy and water cycle components. Plain Language Summary Evapotranspiration modeling and mapping in arid and semi-arid ecosystems are uncertain due to empirical approximation of surface and atmospheric conductances. Here we demonstrate the performance of a fully analytical model which is independent of any leaf-scale empirical parameterization of the conductances and can be potentially used for continental scale mapping of ecosystem water use as well as water stress using thermal remote sensing satellite data.

A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.