Scoping a field experiment: error diagnostics of TRMM precipitation radar estimates in complex terrain as a basis for IPHEx2014

Abstract

A diagnostic analysis of the space–time structure of error in quantitative precipitation estimates (QPEs) from the precipitation radar (PR) on the Tropical Rainfall Measurement Mission (TRMM) satellite is presented here in preparation for the Integrated Precipitation and Hydrology Experiment (IPHEx) in 2014. IPHEx is the first NASA ground-validation field campaign after the launch of the Global Precipitation Measurement (GPM) satellite. In anticipation of GPM, a science-grade high-density raingauge network was deployed at mid to high elevations in the southern Appalachian Mountains, USA, since 2007. This network allows for direct comparison between ground-based measurements from raingauges and satellite-based QPE (specifically, PR 2A25 Version 7 using 5 years of data 2008–2013). Case studies were conducted to characterize the vertical profiles of reflectivity and rain rate retrievals associated with large discrepancies with respect to ground measurements. The spatial and temporal distribution of detection errors (false alarm, FA; missed detection, MD) and magnitude errors (underestimation, UND; overestimation, OVR) for stratiform and convective precipitation are examined in detail toward elucidating the physical basis of retrieval error. The diagnostic error analysis reveals that detection errors are linked to persistent stratiform light rainfall in the southern Appalachians, which explains the high occurrence of FAs throughout the year, as well as the diurnal MD maximum at midday in the cold season (fall and winter) and especially in the inner region. Although UND dominates the error budget, underestimation of heavy rainfall conditions accounts for less than 20% of the total, consistent with regional hydrometeorology. The 2A25 V7 product underestimates low-level orographic enhancement of rainfall associated with fog, cap clouds and cloud to cloud feeder–seeder interactions over ridges, and overestimates light rainfall in the valleys by large amounts, though this behavior is strongly conditioned by the coarse spatial resolution (5 km) of the topography mask used to remove ground-clutter effects. Precipitation associated with small-scale systems (2) and isolated deep convection tends to be underestimated, which we attribute to non-uniform beam-filling effects due to spatial averaging of reflectivity at the PR resolution. Mixed precipitation events (i.e., cold fronts and snow showers) fall into OVR or FA categories, but these are also the types of events for which observations from standard ground-based raingauge networks are more likely subject to measurement uncertainty, that is raingauge underestimation errors due to undercatch and precipitation phase. Overall, the space–time structure of the errors shows strong links among precipitation, envelope orography, landform (ridge–valley contrasts), and a local hydrometeorological regime that is strongly modulated by the diurnal cycle, pointing to three major error causes that are inter-related: (1) representation of concurrent vertically and horizontally varying microphysics; (2) non-uniform beam filling (NUBF) effects and ambiguity in the detection of bright band position; and (3) spatial resolution and ground-clutter correction.