An investigation of the role of current and future remote sensing data systems in numerical meteorology

A flexible system for performing observing system simulation experiments which made contributions to meteorology across all elements of the observing system simulation experiment (OSSE) components was developed. Future work will seek better understanding of the links between satellite-measured radiation and radiative transfer in the clear, cloudy and precipitating atmosphere and investigate how that understanding might be applied to improve the depiction of the initial state and the treatment of physical processes in forecast models of the atmosphere

The Cooperative VAS Program with the Marshall Space Flight Center

Work was divided between the analysis/forecast model development and evaluation of the impact of satellite data in mesoscale numerical weather prediction (NWP), development of the Multispectral Atmospheric Mapping Sensor (MAMS), and other related research. The Cooperative Institute for Meteorological Satellite Studies (CIMSS) Synoptic Scale Model (SSM) has progressed from a relatively basic analysis/forecast system to a package which includes such features as nonlinear vertical mode initialization, comprehensive Planetary Boundary Layer (PBL) physics, and the core of a fully four-dimensional data assimilation package. The MAMS effort has produced a calibrated visible and infrared sensor that produces imager at high spatial resolution. The MAMS was developed in order to study small scale atmospheric moisture variability, to monitor and classify clouds, and to investigate the role of surface characteristics in the production of clouds, precipitation, and severe storms

An investigation of satellite sounding products for the remote sensing of the surface energy balance and soil moisture

Improved techniques for the remote sensing of the land surface energy balance (SEB) and soil moisture would greatly improve prediction of climate and weather as well as be of benefit to agriculture, hydrology and many associated fields. Most of the satellite remote sensing methods which were researched to date rely upon satellite-measured infrared surface temperatures or their time changes as a remote sensing signal. Optimistically, only four or five levels of information (wet to dry) in surface heating/evaporation are discernable by surface temperature methods and a good understanding of atmospheric conditions is necessary to bring them to this accuracy level. Skin temperature methods were researched as well as begun work on several new methods for the remote sensing of the SEB, some elements of which are applicable to current and retrospective data sources and some which will rely on instrumentation from the Earth Observing System (EOS) program in the 1990s

An investigation of current and future satellite and in-situ data for the remote sensing of the land surface energy balance

This final report from the University of Wisconsin-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) summarizes a research program designed to improve our knowledge of the water and energy balance of the land surface through the application of remote sensing and in-situ data sources. The remote sensing data source investigations to be detailed involve surface radiometric ('skin') temperatures and also high-spectral-resolution infrared radiance data from atmospheric sounding instruments projected to be available at the end of the decade, which have shown promising results for evaluating the land-surface water and energy budget. The in-situ data types to be discussed are measurements of the temporal changes of the height of the planetary boundary layer and measurements of air temperature within the planetary boundary layer. Physical models of the land surface, planetary boundary layer and free atmosphere have been used as important tools to interpret the in-situ and remote sensing signals of the surface energy balance. A prototype 'optimal' system for combining multiple data sources into a three-dimensional estimate of the surface energy balance was developed and first results from this system will be detailed. Potential new sources of data for this system and suggested continuation research will also be discussed

An investigation of the role of current and future remote sensing data systems in numerical meteorology

The goals of this research endeavor have been to develop a flexible and relatively complete framework for the investigation of current and future satellite data sources in numerical meteorology. In order to realistically model how satellite information might be used for these purposes, it is necessary that Observing System Simulation Experiments (OSSEs) be as complete as possible. It is therefore desirable that these experiments simulate in entirety the sequence of steps involved in bringing satellite information from the radiance level through product retrieval to a realistic analysis and forecast sequence. In this project we have worked to make this sequence realistic by synthesizing raw satellite data from surrogate atmospheres, deriving satellite products from these data and subsequently producing analyses and forecasts using the retrieved products. The accomplishments made in 1991 are presented. The emphasis was on examining atmospheric soundings and microphysical products which we expect to produce with the launch of the Advanced Microwave Sounding Unit (AMSU), slated for flight in mid 1994

Observation simulation experiments with regional prediction models

Research efforts in FY 1990 included studies employing regional scale numerical models as aids in evaluating potential contributions of specific satellite observing systems (current and future) to numerical prediction. One study involves Observing System Simulation Experiments (OSSEs) which mimic operational initialization/forecast cycles but incorporate simulated Advanced Microwave Sounding Unit (AMSU) radiances as input data. The objective of this and related studies is to anticipate the potential value of data from these satellite systems, and develop applications of remotely sensed data for the benefit of short range forecasts. Techniques are also being used that rely on numerical model-based synthetic satellite radiances to interpret the information content of various types of remotely sensed image and sounding products. With this approach, evolution of simulated channel radiance image features can be directly interpreted in terms of the atmospheric dynamical processes depicted by a model. Progress is being made in a study using the internal consistency of a regional prediction model to simplify the assessment of forced diabatic heating and moisture initialization in reducing model spinup times. Techniques for model initialization are being examined, with focus on implications for potential applications of remote microwave observations, including AMSU and Special Sensor Microwave Imager (SSM/I), in shortening model spinup time for regional prediction

An Investigation of Current and Future Data Systems in Numerical Meteorology

The Advanced Microwave Sounding Unit (AMSU) and the Microwave Humidity Sounder (MHS) constitute the advanced microwave sounding system to be flown on the EOS-PM platform. Similar instruments (the AMSU-A corresponding to the AMSU and the AMSU-B corresponding to the MHS) are scheduled to become operational on the NOAA polar orbiting satellites beginning with NOAA-K. The unique characteristics of the AMSU-MHS instruments, as compared to the capabilities of their infrared and microwave predecessors, introduce new opportunities, and challenges, for operational retrievals of atmospheric structure. Not only will these new data improve present capabilities for the retrieval of atmospheric profiles of temperature and moisture, but they will provide the only opportunity for successfully retrieving atmospheric temperature and humidity profiles in the presence of modest amounts of cloud and precipitation. A complementary opportunity is presented by the potential of the AMSU-MHS to obtain information about the structure of clouds and precipitation. The data sets obtained will contribute to the current knowledge of global water and energy budgets, and provide critical information on the horizontal and vertical distribution of tropospheric water vapor, the spatial and temporal distribution of rain, and the relationship of cloud formation and dissipation to atmospheric dynamics and thermodynamics

Estimating Near Real-Time Hourly Evapotranspiration Using Numerical Weather Prediction Model Output and GOES Remote Sensing Data in Iowa

This study evaluates the applicability of numerical weather prediction output supplemented with remote sensing data for near real-time operational estimation of hourly evapotranspiration (ET). Rapid Refresh (RAP) and High-Resolution Rapid Refresh (HRRR) systems were selected to provide forcing data for a Penman-Monteith model to calculate the Actual Evapotranspiration (AET) over Iowa. To investigate how the satellite-based remotely sensed net radiation ( R n ) estimates might potentially improve AET estimates, Geostationary Operational Environmental Satellite derived R n (GOES- R n ) data were incorporated into each dataset for comparison with the RAP and HRRR R n -based AET evaluations. The authors formulated a total of four AET models—RAP, HRRR, RAP-GOES, HRRR-GOES, and validated the respective ET estimates against two eddy covariance tower measurements from central Iowa. The implementation of HRRR-GOES for AET estimates showed the best results among the four models. The HRRR-GOES model improved statistical results, yielding a correlation coefficient of 0.8, a root mean square error (mm hr−1) of 0.08, and a mean bias (mm hr−1) of 0.02 while the HRRR only model results were 0.64, 0.09, and 0.04, respectively. Despite limited in situ observational data to fully test a proposed AET estimation, the HRRR-GOES model clearly showed potential utility as a tool to predict AET at a regional scale with high spatio-temporal resolution

Solar radiation, longwave radiation and emergent wetland evapotranspiration estimates from satellite data in Florida, USA

Routine estimates of daily incoming solar radiation from the GOES-8 satellite were compared to locally measured values in Florida. Longwave radiation estimates corrected using GOES-derived cloud amount and cloud top temperature products improved net radiation estimates as compared to a clear sky longwave approach. The Penman-Monteith, Turc, Hargreaves and Makkink models were applied using GOES-derived estimates of solar radiation and net radiation to predict daily evapotranspiration and were compared to evapotranspiration measured with an eddy-correlation system in an emergent wetland experimental site in north-central Florida under unstressed conditions. While the Penman-Monteith model provided the best estimates of evapotranspiration (R 2 = 0.92), the empirical Makkink method demonstrated nearly comparable agreement (R 2 = 0.90) using only the GOES solar radiation and measured temperature. The results show that it is possible to generate spatially distributed daily potential evapotranspiration estimates using GOES-derived solar radiation and net radiation with limited additional surface measurements

GOES surface insolation to estimate wetlands evapotranspiration

Incoming solar radiation derived from GOES-8 satellite observations, in combination with local meteorological measurements, were used to model evapotranspiration from a wetland. The wetland experiment was conducted in the Paynes Prairie Preserve, North Central Florida during a growing season characterized by significant convective activity. The satellite solar radiation measurements generally agreed with pyranometer data gathered at the site. The satellite net radiation estimates were in good agreement with the 30-min averages of measured net radiometer data. Satellite derived net radiation estimates were used in the Penman–Monteith and Priestley–Taylor models to calculate evapotranspiration. The calculated instantaneous evaporative fluxes were in good agreement with 30-min average ground-based eddy correlation system measurements. The daily averages of modeled evapotranspiration were in very good agreement (r2=0.90) with reference eddy flux measurements