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The surface of the Arctic Ocean in summer is a mix of sea ice and water in both leads and melt ponds. Here we use data collected at multiple sites during the year-long experiment to study the Surface Heat Budget of the Arctic Ocean (SHEBA) to develop a bulk turbulent flux algorithm for predicting the surface fluxes of momentum and sensible and latent heat over the Arctic Ocean during summer from readily measured or modelled quantities. The distinctive aerodynamic feature of summer sea ice is that the leads and melt ponds create vertical ice faces that the wind can push against; momentum transfer to the surface is thus enhanced through form drag. In effect, summer sea ice behaves aerodynamically like the marginal ice zone, which is another surface that consists of sea ice and water. In our bulk flux algorithm, we therefore combine our SHEBA measurements of the neutral-stability drag coefficient at a reference height of 10 m, C DN10 , with similar measurements from marginal ice zones that have been reported in the literature to create a unified parametrization for C DN10 for summer sea ice and for any marginal ice zone. This parametrization predicts C DN10 from a second-order polynomial in ice concentration. Our bulk flux algorithm also includes expressions for the roughness lengths for temperature and humidity, introduces new profile stratification corrections for stable stratification, and effectively eliminates the singularities that often occur in iterative flux algorithms for very light winds. In summary, this new algorithm seems capable of estimating the friction velocity u

The Persistent Cold-Air Pool Study (PCAPS) was conducted in Utah's Salt Lake valley from 1 December 2010 to 7 February 2011. The field campaign's primary goal was to improve understanding of the physical processes governing the evolution of multiday cold-air pools (CAPs) that are common in mountain basins during the winter. Meteorological instrumentation deployed throughout the Salt Lake valley provided observations of the processes contributing to the formation, maintenance, and destruction of 10 persistent CAP episodes. The close proximity of PCAPS field sites to residences and the University of Utah campus allowed many undergraduate and graduate students to participate in the study. Ongoing research, supported by the National Science Foundation, is using the PCAPS dataset to examine CAP evolution. Preliminary analyses reveal that variations in CAP thermodynamic structure are attributable to a multitude of physical processes affecting local static stability: for example, synoptic-scale processes impact changes in temperatures and cloudiness aloft while variations in boundary layer forcing modulate the lower levels of CAPs. During episodes of strong winds, complex interactions between the synoptic and mesoscale f lows, local thermodynamic structure, and terrain lead to both partial and complete removal of CAPs. In addition, the strength and duration of CAP events affect the local concentrations of pollutants such as PM2.5.

This paper describes important characteristics of an uncoupled high-resolution land data assimilation system (HRLDAS) and presents a systematic evaluation of 18-month-long HRLDAS numerical experiments, conducted in two nested domains (with 12-and 4-km grid spacing) for the period from 1 January 2001 to 30 June 2002, in the context of the International H 2 O Project (IHOP_2002). HRLDAS was developed at the National Center for Atmospheric Research (NCAR) to initialize land-state variables of the coupled Weather Research and Forecasting (WRF)-land surface model (LSM) for high-resolution applications. Both uncoupled HRDLAS and coupled WRF are executed on the same grid, sharing the same LSM, land use, soil texture, terrain height, time-varying vegetation fields, and LSM parameters to ensure the same soil moisture climatological description between the two modeling systems so that HRLDAS soil state variables can be used to initialize WRF-LSM without conversion and interpolation. If HRLDAS is initialized with soil conditions previously spun up from other models, it requires roughly 8-10 months for HRLDAS to reach quasi equilibrium and is highly dependent on soil texture. However, the HRLDAS surface heat fluxes can reach quasi-equilibrium state within 3 months for most soil texture categories. Atmospheric forcing conditions used to drive HRLDAS were evaluated against Oklahoma Mesonet data, and the response of HRLDAS to typical errors in each atmospheric forcing variable was examined. HRLDAS-simulated finescale (4 km) soil moisture, temperature, and surface heat fluxes agreed well with the Oklahoma Mesonet and IHOP_2002 field data. One case study shows high correlation between HRLDAS evaporation and the low-level water vapor field derived from radar analysis.

The flux footprint is the contribution, per unit emission, of each element of a surface area source to the vertical scalar flux measured at height z,; it is equal to the vertical flux from a unit surface point source. The dependence of the flux footprint on crosswind location is shown to be identical to the crosswind concentration distribution for a unit surface point source; an analytic dispersion model is used to estimate the crosswind-integrated flux footprint. Based on the analytic dispersion model, a normalized crosswind-integrated footprint is proposed that principally depends on the single variable Z/Z,,, , where Z is a measure of vertical dispersion from a surface source. The explicit dependence of the crosswind-integrated flux footprint on downwind distance, thermal stability and surface roughness is contained in the dependence of Z on these variables. By also calculating the flux footprint with a Lagrangian stochastic dispersion model, it is shown that the normalized flux footprint is insensitive to the analytic model assumption of a self-similar vertical concentration profile.