MAPS Special Issue: Land Atmospheric Interactions

MAPS Special Issue: Land Atmospheric Interactions

Land-Surface Scheme Validation using the Oklahoma Atmospheric Surface-Layer Instrumentation System (OASIS) Program and Oklahoma Mesonet Data:

Preliminary Results

The Oklahoma Atmospheric Surface-layer Instrumentation System (OASIS) Program: Challenges and Preliminary Results of Using In-situ Data for Model Validation

of the ISBA Land-surface Scheme

J. A. Brotzge and D. Weber

Center for Analysis and Prediction of Storms, Norman, Oklahoma

1.  Introduction

This paper describes the initial use of Mesonet and OASIS data for use in verifying the Interactions Soil Biosphere Atmosphere (ISBA) land-surface model (LSM). Previous routine, real-time measurements of surface fluxes and soil moisture were limited to field projects with short, high-intensive observational periods. Field programs such as HAPEX-MOBILY (Andre et al. 1986), the First ISLSCP Field Experiment (FIFE; Sellers et al. 1988), and MONSOON 90 (Kustas et al. 1991) provided rich data sets for advancing knowledge of land-surface interactions. However, these field experiments were limited in size and scope, and did not allow for long-term (multi-seasonal) nor large-scale (regional to statewide) estimates of surface and ground parameters. Land surface model validation is not common for a number of reasons, one of which is that few observational programs have extended their scope into measuring surface and sub-surface conditions. The HAPEX (?????) project did contain a number of important measurement components including surface soil temperature moisture as well as vegetation type and coverage information and was used to verify a number of different models including the model used in this study. Jerry I couldn’t find my HAPEX paper so can you add some thing here that sums up what data they used… The notable difference with the present study is the completeness of the data collected in addition to the spatial and temporal extent of the new data set. As described within, the available data will allow researchers to scrutinize the numerical frameworks over a complete set of weather phenomena and improve the methods associated with land surfaces schemes. The current research efforts at the Center for Analysis and Prediction of Storms (CAPS) includes a rigorous validation of a number of physics components used by the Advanced Regional Prediction System (ARPS) described by Xue et.al. (2000a).

The Oklahoma Atmospheric Surface-layer Instrumentation System (OASIS; Brotzge et al., 1999) is a unique, statewide network sponsored by the National Science Foundation which collects, quality controls,, quality controls and archives radiation, surface fluxes, and soil data in real-time on a continuous basis. OASIS enhanced the existing observational capabilitescapabilitiescapabilities of the Oklahoma Mesonet to allow for continuous monitoring of the total surface energy budget. OASIS data have been collected and archived from 90 Mesonet sites statewide every 5 to 30 minutes since 1 January 2000. The primary objective of OASIS is to develop a long-term, large-scale data set of fine spatial and temporal resolution against which remote sensing algorithms and numerical models can be verified. This is the first such study to use data from OASIS for model verification.

The Advanced Regional Prediction System is a three-dimensional, nonhydrostatic mesoscale model developed by the CAPS at the University of Oklahoma. The ARPS is used as both a forecasting and research tool primarily but not limited to the prediction of convective storms. An accurate land-surface scheme for use in a mesoscale model is critical to forecasting cloud formation and convection. The land surface and soil package of ARPS (Xue et al., 2001b) includes the Interactions Soil Biosphere Atmosphere (ISBA) scheme described by Noilhan and Planton (1989) and Pleim and Xiu (1995). While the ISBA scheme has been extensively tested against atmospheric data (Jacquemin and Noilhan, 1990; Noilhan et al., 1991; Bougeault et al., 1991; Mahfouf et al., 1995; Noilhan and Mahfouf, 1996; Xiu and Pleim, 2001), the land surface model (LSM) has not been as thoroughly tested against soil observations. In addition, several recent improvements to ISBA (Noilhan and Planton, 1996; Xiu and Pleim, 2001) have not yet been included into the ARPS scheme.

This paper outlines the many challenges in developing, maintaining, and using in-situ data for model validation. Section 2 presents an overview of the Mesonet and OASIS data including the limitations and operational challenges with the collection and representativeness of in-situ data. Instrument limitations and failures, spatial representativeness, and inconsistent closure of the surface energy budget each contribute to measurement error and uncertainty. In addition, model sensitivity to initialization and surface heterogeneity makes model verification even more difficult. Each of these problems is discussed, and preliminary results from model validation of ARPS using OASIS and Mesonet data are provided in Section 3.

The goals of this work are twofold. First, the limitations of the OASIS data set must be documented prior to its use as verification against model output. The second objective of this work is to update and test the ISBA scheme within ARPS against the field observations provided by OASIS. More specifically, this study aims to validate and improve the modeling of soil and skin surface temperature and moisture within the ISBA scheme.

This paper outlines the many challenges in developing, maintaining, and using in-situ data for model validation. Instrument limitations and failures, spatial representativeness, and inconsistent closure of the surface energy budget each contribute to measurement error and uncertainty. In addition, model sensitivity to initialization and surface heterogeneity makes model verification even more difficult. Each of these problems is discussed, and preliminary results from model validation of ARPS using OASIS data are provided.

2.  Mesonet and OASIS Data Overview

The Oklahoma Mesonet (Brock et al., 1995) provides the infrastructure upon which the OASIS is built. Approximately 90 Mesonet sites have been enhanced to allow net radiation, ground and sensible heat fluxes to be estimated directly (Fig. 1). Latent heat flux is estimated as the residual of the surface energy budget. Skin temperature and soil moisture also are measured directly at the 90 sites. Ten of the 90 OASIS sites, termedcalled “super sites”, have additional sonic anemometry and 4-component net radiometers, which allow more accurate and precise measurements of net radiation and sensible and latent heat fluxes. The ten super sites are equipped with redundant instrumentation and multiple methods of measurement to allow for improved quality control of the data. A super site has been selected in each of Oklahoma’s nine climatic zones, to provide a diverse yet simultaneous set of observations from across the state.A comprehensive data set was compiled for this study from one year of OASIS data archived and collected from a single OASIS super site located at Norman, Oklahoma (NORM). NORM (Lat. 35 15’ 20”; Lon. 97 29’ 0” ) is characterized by flat terrain (~ 0.0° slope), and short grasses. Standard atmospheric Mesonet and OASIS flux data were collected every 5 minutes; soil data were collected every 30 minutes. Atmospheric data included air temperature, relative humidity, atmospheric pressure, rainfall, and wind speed and direction. Surface parameters included incoming and outgoing shortwave and longwave radiation, sensible and latent heat fluxes, ground heat flux, skin temperature, and soil moisture and soil temperatures at 5, 25, 60, and 75 cm depths. Snowfall depths were included into the data set as estimated at a nearby National Weather Service (NWS) office (approximately 3.03 km distant). Vertical soundings from 00 and 12 UTC from the NWS were archived and collected as well. Vegetation data were obtained from bi-weekly NDVI values from which the appropriate 1 km x 1 km pixel was extracted to coincide with the site location. These estimates were interpolated to daily values. Soil information for the Norman site was provided by the Oklahoma Climatological Survey.

For this study validation of the ISBA scheme, ARPS was tested in a one-dimensional mode; model output was directly compared against the observed data.

2.1 Instrumentation and measurement procedures

The measurement methods used by OASIS are summarized in Table 1. A detailed description of the sensors is found in Brotzge (2000). What follows is a brief summary of the assumptions and unique problems associated with each measurement method. This review is used foremost to develop an approximate error estimate associated with the data set. Second, problems in measurement are important to be understood in context when used for comparison against modeled data. As discussed by Noilhan et al. (1991), model results most likely will not exactly reproduce the surface observations, either because of nonrepresentativeness of the measurements or model deficiencies. Thus, a correct interpretation of the observations and modeled data require a complete understanding of both observational and modeling deficiencies.

2.1.1 Net radiation

Shuttleworth (1991) describes net radiation as one of the most difficult parameters to measure accurately. For this reason, net and four4-component radiometers were installed at the OASIS super sites. The net radiometer used by OASIS is the NR-Lite, a recently developed sensor, which is relatively low-cost, is nearly maintenance-free and does not require the use of polyethylene domes which can degrade over time. However, the simplicity of the design permits greater sensitivity to operational errors. Brotzge and Duchon (2000) identified several limitations of the sensor. These problems include poor initial calibration, and a degradation of performance during high winds and low sun angles, and during precipitation.

The four-component radiometer, the CNR1, comprises four separate sensors housed in a single unit, allowing incoming and outgoing shortwave and longwave radiation to be directly observed. A heating element, embedded within the body of the sensor, is activated during certain weather periods to minimize the effects of dew, frost or precipitation. The sensor is much more expensive than the NR-Lite but does not incur the operational problems associated with wind or precipitation. Both radiation sensors are mounted at a height of 2 m.

Data from the NR-Lite and CNR1 were collected and archived from all of 2000 at the ten super sites (Brotzge, 2000). Comparisons between the co-located sensors revealed minimal differences between them (< 5%). Multiple sensors at a site proved to be valuable in identifying a failed sensor or poor data.

2.1.2 Ground heat flux

A combination approach (Tanner 1960) is used to estimate the total ground heat flux and . The combination approach includes separate estimates for the ground flux and storage terms:

where l [W (m K)-1] is the thermal conductivity, dT [K] is the temperature difference across the plate, dz [m] is the plate thickness, C [J (m3 K)-1] is the soil heat capacity, dz2 [m] is the depth of the soil layer, and dT/dt is the temporal rate of change in the integrated soil temperature between 0 and 5 cm (Fritschen and Gay, 1979). Two Platinum Resistance Temperature Detectors (PRTDs) and two heat flux plates are installed at each of the 90 sites at a depth of 5 cm. An average of the 2 PRTDs is used to estimate dT/dt; likewise the mean of the two flux plates are used to estimate the first term. The soil heat capacity is estimated at each site as a function of the measured volume fraction of minerals, organic material, and soil moisture. For more details, see Brotzge (2000).

Massman (1993) identified several assumptions used in estimating ground heat flux. The specific heat capacity of the soil must be assumed constant in depth and in time, and horizontal heat flow is neglected. The thermal conductivity of the ground flux plate must match that of the soil (Fritschen and Gay, 1979). Because the conductivity of the plates generally do not match that of the soil, Fritschen and Simpson (1989) developed a correction for the soil thermal conductivity as a function of plate conductivity, size, and shape, which has been applied to this data set. Finally, the flux plates themselves may impede the vertical flow of heat and moisture within the soil (Tanner, 1960; van Loon et al., 1998). Air gaps between the soil and plates also can lead to significant measurement errors (Fritschen and Gay, 1979).

Significant errors are more likely to occur from large variability in ground flux properties and surface heterogeneity than from instrument error. The effects of heterogeneity are described in greater detail in section 2.2.14.1, however, significant variability has been observed in soil moisture and soil properties within a relatively small (20 x 20 m2) area (Basara, 2001). A comparison study conducted by Brotzge (2000) revealed differences of nearly 100 Wm-2 between two sets of co-located ground flux measurements. These two sets of measurements were located approximately 100 m apart. Thus, while instrument errors generally are limited to less than 5%, errors due to surface heterogeneity can lead to much greater uncertainty. Using the mean from two heat flux plates and the mean from two PRTDs reduces the error in ground heat flux from spatial heterogeneity. However, the exact magnitude of the error remains unknown.

2.1.3 Sensible and latent heat fluxes

The ten super sites also have been equipped with sonic anemometry to directly measure the sensible heat flux, in part to verify the gradient method used by the standard sites. The sonic anemometer is installed at a height of 4.5 m and is mounted to the west of the tower. Data from the sensor cannot be used during or immediately following precipitation. Foken and Wichura (1996) have listed a host of sensor configuration and meteorological problems that can occur when using an eddy correlation technique. For this study, sonic measurements have been corrected for moisture dependence (Schotanus et al., 1983; Stull, 1988) and for tilting of the sensor (T. Horst, personal communication 1999).

Each of the 90 standard OASIS sites is equipped with similar cup anemometers and thermistors to monitor vertical gradients in wind and temperature. The vertical gradients of heat and momentum are applied to Monin-Obukhov similarity theory to derive an estimate of sensible heat flux (Brotzge and Crawford, 2000). Brotzge and Crawford identified three major difficulties in estimating gradient fluxes using the Mesonet infrastructure. First, the method is extremely sensitive to instrument errors. Second, the temperature sensors are only naturally aspirated, meaning that during high solar radiation, low wind conditions, radiational heating of the sensors creates a bias in temperature measurements. Third, nearby trees and topography create subtle fetch problems, thus biasing flux estimates. McAloon et al. (2000) and McAloon (2001) have found that the gradient technique is much more reliable during unstable and neutral conditions, and have identified those Mesonet sites where fetch is not a problem. Furthermore, McAloon (2001) has found a significant sensitivity (> 100 Wm-2) to the theoretical constants used.