A challenging issue in the hydrologic and meteorologic fields is the spatial, temporal, and seasonal characteristics of precipitation and other meteorological variables (e.g. precipitation, wind, snow). METSTAT has a specialized niche to address these challenges using its expansive in-house database of archived climatological and meteorological data, state-of-the-science models/methods and over 20 years of experience to provide high quality datasets and analysis.
Precipitation/Rainfall frequency values provide a critically important resource for basic hydrologic design, thereby achieving regulatory compliance, public safety, optimization of water infrastructure design and water resource management programs. Rainfall-frequency values serve as a fundamental resource that allow the estimation of design rainfall events and ensuing floods to be made order to optimize planning and design of engineering projects. Projects of this nature are of great importance given the costs of lives and property associated with hydrologic structure failures that can be prevented given accurate rainfall-frequency statistics. Rainfall frequency estimates provide engineers and hydrologists the needed information to build safe and efficient hydraulic structures (e.g. culverts, bridges, dam spillways, stormwater/drainage systems). In general, the demand for improved rainfall statistics is driven by governments wishing to develop safe, efficient and cost-effective water retaining structures as well as risk-based analyses.
METSTAT utilizes the regional L-moment frequency analysis approach for computing precipitation frequency estimates, which is the state-of-the-science approach that few know how to conduct. METSTAT is uniquely qualified to carry out such projects.
Precipitation frequency estimates (e.g. 100-year 24-hour) are used as basic design criteria for a variety of hydraulic structures such as dams, roadway drainage, bridges and culverts. L-moments and frequency analysis utilize a dataset (annual maximum series or partial duration series) to estimate the characteristics of the underlying population by selecting and parameterizing a probability distribution (e.g. Gumbel, Log-Pearson, Generalized Extreme Value (GEV)).
Spatially distributed estimates of meteorological data are becoming increasingly important as inputs to spatially explicit meteorologic, hydrologic, regional, and global models. METSTAT has developed a proven, government-accepted and cost-effective spatial interpolation technique that utilizes a mean monthly/annual/seasonal precipitation to help interpolate between ungauged locations.
A large portion of precipitation frequency analysis and interpolation procedures are allocated to quality control (QC) methods. Potential errors associated with precipitation datasets are gauge under-catch, timing, data shifts, observer error, and metadata (latitude, longitude, elevation). All are essential for an accurate assessment of datasets. METSTAT uses a QC processes that examine the timing, magnitude, and interpolated values for the identification of erroneous data.
METSTAT has conducted frequency analyses for the following variables:
- Wind speed and gust
- Snow depth and load
- 3-, 6- and 12-hour dew point temperature