R. van der Velde

Quantification of land-atmosphere exchanges of water, energy and carbon dioxide in space and time over the heterogeneous Barrax site

To advance our understanding of land–atmosphere exchanges of water, energy and carbon dioxide (CO2) in space and time over heterogeneous land surfaces, two intensive field campaigns were carried out at the Barrax agricultural test site in Spain during 12–21 July 2004 (SPARC 2004) and 8–14 July 2005 (SEN2FLEX 2005) involving multiple field, satellite and airborne instruments for characterizing the state of the atmosphere, the vegetation and the soil from the visible to the microwave range of the spectrum. Part of the experimental area is a core site of area 25 km2, within which numerous crops are grown, on both irrigated and dry land, alongside fields of bare soil. The campaigns were carried out in the framework of the Earth Observation Envelope Programme of the European Space Agency (ESA) with the aim of supporting geophysical algorithm development, calibration/validation and the simulation of future spaceborne Earth Observation missions. Both campaigns were also contributions to the EU 6FP EAGLE Project. The emphasis of this contribution is on the in situ measurements of land–atmosphere exchanges of water, energy and CO2 as well as the thermal dynamic states of the atmosphere, the soil and the vegetation. Preliminary analysis and interpretation of the measurements are presented. These two data sets are open to the scientific community for collaborative investigations.

Assessment of Roughness Length Schemes Implemented within the Noah Land Surface Model for High-Altitude Regions

Current land surface models still have difficulties with producing reliable surface heat fluxes and skin temperature (Tsfc) estimates for high-altitude regions, which may be addressed via adequate parameterization of the roughness lengths for momentum (z0m) and heat (z0h) transfer. In this study, the performance of various z0h and z0m schemes developed for the Noah land surface model is assessed for a high-altitude site (3430 m) on the northeastern part of the Tibetan Plateau. Based on the in situ surface heat fluxes and profile measurements of wind and temperature, monthly variations of z0m and diurnal variations of z0h are derived through application of the Monin–Obukhov similarity theory. These derived values together with the measured heat fluxes are utilized to assess the performance of those z0m and z0h schemes for different seasons. The analyses show that the z0m dynamics are related to vegetation dynamics and soil water freeze–thaw state, which are reproduced satisfactorily with current z0m schemes. Further, it is demonstrated that the heat flux simulations are very sensitive to the diurnal variations of z0h. The newly developed z0h schemes all capture, at least over the sparse vegetated surfaces during the winter season, the observed diurnal variability much better than the original one. It should, however, be noted that for the dense vegetated surfaces during the spring and monsoon seasons, not all newly developed schemes perform consistently better than the original one. With the most promising schemes, the Noah simulated sensible heat flux, latent heat flux, Tsfc, and soil temperature improved for the monsoon season by about 29%, 79%, 75%, and 81%, respectively. In addition, the impact of Tsfc calculation and energy balance closure associated with measurement uncertainties on the above findings are discussed, and the selection of the appropriate z0h scheme for applications is addressed.

Analysis of long-term terrestrial water storage variations in Yangtze River basin

In this study, we analyze 32 yr of terrestrial water storage (TWS) data obtained from the Interim Reanalysis Data (ERA-Interim) and Noah model from the Global Land Data Assimilation System (GLDAS-Noah) for the period 1979 to 2010. The accuracy of these datasets is validated using 26 yr (1979–2004) of runoff data from the Yichang gauging station and comparing them with 32 yr of independent precipitation data obtained from the Global Precipitation Climatology Centre Full Data Reanalysis Version 6 (GPCC) and NOAA’s PRECipitation REConstruction over Land (PREC/L). Spatial and temporal analysis of the TWS data shows that TWS in the Yangtze River basin has decreased significantly since the year 1998. The driest period in the basin occurred between 2005 and 2010, and particularly in the middle and lower Yangtze reaches. The TWS figures changed abruptly to persistently high negative anomalies in the middle and lower Yangtze reaches in 2004. The year 2006 is identified as major inflection point, at which the system starts exhibiting a persistent decrease in TWS. Comparing these TWS trends with independent precipitation datasets shows that the recent decrease in TWS can be attributed mainly to a decrease in the amount of precipitation. Our findings are based on observations and modeling datasets and confirm previous results based on gauging station datasets.

Augmentations to the Noah Model Physics for Application to the Yellow River Source Area. Part II: Turbulent Heat Fluxes and Soil Heat Transport

This is the second part of a study on the assessment of the Noah land surface model (LSM) in simulating surface water and energy budgets in the high-elevation source region of the Yellow River. Here, there is a focusonturbulentheatfluxesandheattransportthroughthesoilcolumnduringthemonsoonseason,whereas the first part of this study deals with the soil water flow. Four augmentations are studied for mitigating the overestimation of turbulent heat flux and underestimation of soil temperature measurements: 1) the muting effect of vegetation on the thermal heat conductivity kh is removed from the transport of heat from the first to thesecondsoil layer,2)theexponential decayfactorbveg imposedonkh iscalculatedusingthe ratiooftheleaf area index (LAI) over the green vegetation fraction (GVF), 3) Zilitinkevich’s empirical coefficient Czil for turbulent heat transport is computed as a function of the momentum roughness length z0,m, and 4) the impact of organic matter is considered in the parameterization of the thermal heat properties. Although usage of organic matter for calculating kh improves the correspondence between the estimates and laboratory measurements of heat conductivities, it is shown to have a relatively small impact on the Noah LSM performance even for large organic matter contents. In contrast, the removal of the muting effect of vegetation on kh and the parameterizationofbveg greatlyenhancesthe soiltemperature profilesimulations,whereasturbulentheat flux and surface temperature computations mostly benefit from the modified Czil formulation. Further, the nighttime surface temperature overestimation is resolved from a coupled land‐atmosphere perspective.

Assimilation of satellite observed snow albedo in a land surface model

This study assesses the impact of assimilating satellite-observed snow albedo on the Noah land surface model (LSM)-simulated fluxes and snow properties. A direct insertion technique is developed to assimilate snow albedo into Noah and is applied to three intensive study areas in North Park (Colorado) that are part of the 2002/03 Cold Land Processes Field Experiment (CLPX). The assimilated snow albedo products are 1) the standard Moderate Resolution Imaging Spectrometer (MODIS) product (MOD10A1) and 2) retrievals from MODIS observations with the recently developed Pattern-Based Semiempirical (PASS) approach. The performance of the Noah simulations, with and without assimilation, is evaluated using the in situ measurements of snow albedo, upward shortwave radiation, and snow depth. The results show that simulations with albedo assimilation agree better with the measurements. However, because of the limited impact of snow albedo updates after subsequent snowfall, the mean (or seasonal) error statistics decrease significantly for only two of the three CLPX sites. Though the simulated snow depth and duration for the snow season benefit from the assimilation, the greatest improvements are found in the simulated upward shortwave radiation, with root mean squared errors reduced by about 30%. As such, this study demonstrates that assimilation of satellite-observed snow albedo can improve LSM simulations, which may positively affect the representation of hydrological and surface energy budget processes in runoff and numerical weather prediction models.

Development and validation of the SMAP enhanced passive soil moisture product

Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 m3/m3 at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 m3/m3. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.

Assessment of version 4 of the SMAP passive soil moisture standard product

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core cal/val sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.

L-band H polarized microwave emission during the corn growth cycle

L-band radiometry is recognized as a technique with a significant potential for providing spatial and temporal soil moisture variations [1, 2]. As a result, satellite missions dedicated to global soil moisture monitoring have been proposed. A 2D-interferometric L-band radiometer has recently been launched onboard the European SMOS (Soil moisture and Ocean Salinity) satellite, [3], and the NASA is in preparation of a similar suite of microwave instruments as a part of the Aquarius and SMAP (Soil Moisture Active/Passive missions, [4] which have anticipated launch dates in 2011 and 2014, respectively. The reliability of soil moisture products derived from these microwave observations will depend, at least in part, on the effectiveness of accounting for vegetation and surface roughness impacts.

Passive L-band H polarized microwave emission during the corn growth cycle

From a combined active/passive microwave remote sensing campaign conducted in 2002, hourly L-band H polarized TB (Brightness temperature) measurements are available for five episodes distributed over the corn growth cycle. In this study, fitting the τ-ω model to the TB measurements shows that the empirical parameter b, defining the optical depth or canopy opacity (τ), and its dependence towards the incidence and azimuth angles both change during the growth cycle. The b found for the early growth stage is about three times larger than expected based on the literature, while near peak biomass and at senescence its value is about half. Moreover, the soil moisture dependence of the roughness and crop row orientation are found to be important uncertainties in the TB simulations. The latter effect is particularly significant at senescence.

A Vegetation Correction Methodology Applied for Soil Moisture Retrieval from C-Band Radar Observations

This research presents a methodology to correct backscatter (sigmadeg) observations for vegetation effects. The proposed methodology is based on the concept that the ratio between the surface scattering over the total amount of scattering (sigmadeg_surface/sigmadeg_soil) is affected only by the vegetation and can be described as a function of the vegetation water content. The data set used in this study was collected at USDAs Optimizing Production Inputs for Economic and Environmental Enhancement (OPE³) experimental site in Beltsville, Maryland (USA) over a corn growth cycle in 2002 and includes C-band (4.75 GHz) HH- and VV-polarized observations acquired at incidence angles of 15, 35 and 55 degrees. During this period the corn crops reached peak biomass of 6.6 kg m^-2 and a soil moisture range varying from 0.02 to 0.26 cm³cm^-3. The results show that through application of the proposed vegetation correction methodology the soil moisture retrieval accuracy can be improved from 0.033 to 0.032 cm³cm^-3, 0.049 to 0.033 cm³cm^-3, and 0.079 to 0.047 cm³cm^-3 at incidence angles of 15, 35 and 55 degrees, respectively.