Diurnal Temperature Cycle Research Articles

The Seasonal and Diurnal Cycles of Refractivity and Anomalous Propagation in the Sahelian Area from Microwave Radiometric Profiling

AbstractThe Sahelian zone of West Africa is a semiarid area where strong amplitude of the seasonal and diurnal cycles of water vapor and temperature is observed. One year of continuous observation of vertical profiles of water vapor and temperature gathered from Niamey, Niger, with a profiling microwave radiometer is used to analyze the climatology of refractivity and microwave propagation regimes in the low troposphere. Seasonal and diurnal cycles of refractivity and ground-based radar anomalous propagation are emphasized. It is shown that the combined effect of water vapor and temperature vertical gradients is responsible for strong seasonal and diurnal cycles of the ducting propagation regime. Statistics of propagation regimes are given. The probability density functions of the refractivity gradient are found lognormally distributed. Three months of C-band radar data simultaneous with the profiling microwave radiometer observations have also been collected. Relations between the vertical refractivity gradient and the ground-based radar anomalous propagation echoes (APE) are illustrated and discussed. APE spatial distributions are found strongly related to the main features of the orography and topography inside the radar-observed area. Contingency tests show that the probability for APE to be linked to ducting is higher than 95%. In addition, this paper suggests that observing the refractivity vertical profiles from a microwave radiometer profiler located close to a meteorological radar provides information on whether anomalous propagation has to be considered as a potential cause of spurious signal in the measured reflectivity field.

Enhanced Turbulence Associated with the Diurnal Jet in the Ocean Surface Boundary Layer

AbstractDetailed observations of the diurnal jet, a surface intensification of the wind-driven current associated with the diurnal cycle of sea surface temperature (SST), were obtained during August and September 2012 in the subtropical Atlantic. A diurnal increase in SST of 0.2° to 0.5°C was observed, which corresponded to a diurnal jet of 0.15 m s−1. The increase in near-surface stratification limits the vertical diffusion of the wind stress, which in turn increases the near-surface shear. While the stratification decreased the turbulent dissipation rate ε below the depth of the diurnal jet, there was an observed increase in ε within the diurnal jet. The diurnal jet was observed to increase the near-surface shear by a factor of 5, which coincided with enhanced values of ε. The diurnal evolution of the Richardson number, which is an indicator of shear instability, is less than 1, suggesting that shear instability may contribute to near-surface turbulence. While the increased stratification due to the diurnal heating limits the depth of the momentum flux due to the wind, shear instability provides an additional source of turbulence that interacts with the enhanced shear of the diurnal jet to increase ε within this shallow layer.

1041 Diurnal vaginal temperature cycles of Senepol and crossbred beef heifers with different hair coat types and colors under tropical conditions

1041 Diurnal vaginal temperature cycles of Senepol and crossbred beef heifers with different hair coat types and colors under tropical conditions

Disaggregation of remotely sensed land surface temperature: A new dynamic methodology

AbstractThe trade‐off between the spatial and temporal resolutions of satellite‐derived land surface temperature (LST) gives birth to disaggregation of LST (DLST). However, the concurrent enhancement of the spatiotemporal resolutions of LST remains difficult, and many studies disregard the conservation of thermal radiance between predisaggregated and postdisaggregated LSTs. Here we propose a new dynamic methodology to enhance concurrently the spatiotemporal resolutions of satellite‐derived LSTs. This methodology conducts DLST by the controlling parameters of the temperature cycle models, i.e., the diurnal temperature cycle (DTC) model and annual temperature cycle (ATC) model, rather than directly by the LST. To achieve the conservation of thermal radiance between predisaggregated and postdisaggregated LSTs, herein we incorporate a modulation procedure that adds temporal thermal details to coarse resolution LSTs rather than straightforwardly transforms fine‐resolution scaling factors into LSTs. Indirect validations at the same resolution show that the mean absolute error (MAE) between the predicted and reference LSTs is around 1.0 K during a DTC; the associated MAE is around 2.0 K during an ATC, but this relatively lower accuracy is due more to the uncertainty of the ATC model. The upscaling validations indicate that the MAE is around 1.0 K and the normalized mean absolute error is around 0.3. Comparisons between the DTC‐ and ATC‐based DLST illustrate that the former retains a higher accuracy, but the latter holds a higher flexibility on days when background low‐resolution LSTs are unavailable. This methodology alters the static DLST into a dynamic way, and it is able to provide temporally continuous fine‐resolution LSTs; it will also promote the design of DLST methods for the generation of high‐quality LSTs.

Evaluation of simulated climatological diurnal temperature range in CMIP5 models from the perspective of planetary boundary layer turbulent mixing

This study examines the effects of modeled planetary boundary layer (PBL) mixing on the simulated temperature diurnal cycle climatology over land in 20 CMIP5 models with AMIP simulations. When compared with observations, the magnitude of diurnal temperature range (DTR) is systematically underestimated over almost all land areas due to a widespread warm bias of daily minimum temperature (Tmin) and mostly a cold bias of daily maximum temperature (Tmax). Analyses of the CMIP5 multi-model ensemble means suggest that the biases of the simulated PBL mixing could very likely contribute to the temperature biases. For the regions with the cold bias in Tmax, the daytime PBL mixing is generally underestimated. The consequent more dry air entrainment from the free atmosphere could help maintain the surface humidity gradient, and thus produce more surface evaporation and potentially lower the Tmax. The opposite situation holds true for the regions with the warm bias of Tmax. This mechanism could be particularly applicable to the regions with moderate and wet climate conditions where surface evaporation depends more on the surface humidity gradient, but less on the available soil moisture. For the widespread warm bias of Tmin, the widely-recognized overestimated PBL mixing at nighttime should play a dominant role by transferring more heat from the atmosphere to the near-surface to warm the Tmin. Further analyses using the high resolution CFMIP2 output also support the CMIP5 results about the connections of the biases between the simulated turbulent mixing and the temperature diurnal cycle. The large inter-model variations of the simulated temperature diurnal cycle primarily appear over the arid and semi-arid regions and boreal arctic regions where the model differences in the PBL turbulence mixing could make equally significant contributions to the inter-model variations of DTR, Tmax and Tmin compared to the model differences in surface radiative processes. These results highlight the importance and need for accurate descriptions of the PBL processes with respect to the turbulent mixing in order to improve the temperature diurnal cycle simulations in climate models.

Spatiotemporal Divergence of the Warming Hiatus over Land Based on Different Definitions of Mean Temperature.

Existing studies of the recent warming hiatus over land are primarily based on the average of daily minimum and maximum temperatures (T2). This study compared regional warming rates of mean temperature based on T2 and T24 calculated from hourly observations available from 1998 to 2013. Both T2 and T24 show that the warming hiatus over land is apparent in the mid-latitudes of North America and Eurasia, especially in cold seasons, which is closely associated with the negative North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) and cold air propagation by the Arctic-original northerly wind anomaly into mid-latitudes. However, the warming rates of T2 and T24 are significantly different at regional and seasonal scales because T2 only samples air temperature twice daily and cannot accurately reflect land-atmosphere and incoming radiation variations in the temperature diurnal cycle. The trend has a standard deviation of 0.43 °C/decade for T2 and 0.41 °C/decade for T24, and 0.38 °C/decade for their trend difference in 5° × 5° grids. The use of T2 amplifies the regional contrasts of the warming rate, i.e., the trend underestimation in the US and overestimation at high latitudes by T2.

Cloud tolerance of remote-sensing technologies to measure land surface temperature

Abstract. Conventional methods to estimate land surface temperature (LST) from space rely on the thermal infrared (TIR) spectral window and is limited to cloud-free scenes. To also provide LST estimates during periods with clouds, a new method was developed to estimate LST based on passive-microwave (MW) observations. The MW-LST product is informed by six polar-orbiting satellites to create a global record with up to eight observations per day for each 0.25° resolution grid box. For days with sufficient observations, a continuous diurnal temperature cycle (DTC) was fitted. The main characteristics of the DTC were scaled to match those of a geostationary TIR-LST product.This paper tests the cloud tolerance of the MW-LST product. In particular, we demonstrate its stable performance with respect to flux tower observation sites (four in Europe and nine in the United States), over a range of cloudiness conditions up to heavily overcast skies. The results show that TIR-based LST has slightly better performance than MW-LST for clear-sky observations but suffers an increasing negative bias as cloud cover increases. This negative bias is caused by incomplete masking of cloud-covered areas within the TIR scene that affects many applications of TIR-LST. In contrast, for MW-LST we find no direct impact of clouds on its accuracy and bias. MW-LST can therefore be used to improve TIR cloud screening. Moreover, the ability to provide LST estimates for cloud-covered surfaces can help expand current clear-sky-only satellite retrieval products to all-weather applications.

Homogenised daily lake surface water temperature data generated from multiple satellite sensors: A long-term case study of a large sub-Alpine lake.

Availability of remotely sensed multi-spectral images since the 1980’s, which cover three decades of voluminous data could help researchers to study the changing dynamics of bio-physical characteristics of land and water. In this study, we introduce a new methodology to develop homogenised Lake Surface Water Temperature (LSWT) from multiple polar orbiting satellites. Precisely, we developed homogenised 1 km daily LSWT maps covering the last 30 years (1986 to 2015) combining data from 13 satellites. We used a split-window technique to derive LSWT from brightness temperatures and a modified diurnal temperature cycle model to homogenise data which were acquired between 8:00 to 17:00 UTC. Gaps in the temporal LSWT data due to the presence of clouds were filled by applying Harmonic ANalysis of Time Series (HANTS). The satellite derived LSWT maps were validated based on long-term monthly in-situ bulk temperature measurements in Lake Garda, the largest lake in Italy. We found the satellite derived homogenised LSWT being significantly correlated to in-situ data. The new LSWT time series showed a significant annual rate of increase of 0.020 °C yr−1 (*P < 0.05), and of 0.036 °C yr−1 (***P < 0.001) during summer.

A practical algorithm for estimating surface soil moisture using combined optical and thermal infrared data

Surface soil moisture (SSM) is a critical variable for understanding the energy and water exchange between the land and atmosphere. A multi-linear model was recently developed to determine SSM using ellipse variables, namely, the center horizontal coordinate (x0), center vertical coordinate (y0), semi-major axis (a) and rotation angle (θ), derived from the elliptical relationship between diurnal cycles of land surface temperature (LST) and net surface shortwave radiation (NSSR). However, the multi-linear model has a major disadvantage. The model coefficients are calculated based on simulated data produced by a land surface model simulation that requires sufficient meteorological measurements. This study aims to determine the model coefficients directly using limited meteorological parameters rather than via the complicated simulation process, decreasing the dependence of the model coefficients on meteorological measurements. With the simulated data, a practical algorithm was developed to estimate SSM based on combined optical and thermal infrared data. The results suggest that the proposed approach can be used to determine the coefficients associated with all ellipse variables based on historical meteorological records, whereas the constant term varies daily and can only be determined using the daily maximum solar radiation in a prediction model. Simulated results from three FLUXNET sites over 30 cloud-free days revealed an average root mean square error (RMSE) of 0.042m3/m3 when historical meteorological records were used to synchronously determine the model coefficients. In addition, estimated SSM values exhibited generally moderate accuracies (coefficient of determination R2=0.395, RMSE=0.061m3/m3) compared to SSM measurements at the Yucheng Comprehensive Experimental Station.

Continuous measurements of isotopic composition of water vapour on the East Antarctic Plateau

Abstract. Water stable isotopes in central Antarctic ice cores are critical to quantify past temperature changes. Accurate temperature reconstructions require one to understand the processes controlling surface snow isotopic composition. Isotopic fractionation processes occurring in the atmosphere and controlling snowfall isotopic composition are well understood theoretically and implemented in atmospheric models. However, post-deposition processes are poorly documented and understood. To quantitatively interpret the isotopic composition of water archived in ice cores, it is thus essential to study the continuum between surface water vapour, precipitation, surface snow and buried snow. Here, we target the isotopic composition of water vapour at Concordia Station, where the oldest EPICA Dome C ice cores have been retrieved. While snowfall and surface snow sampling is routinely performed, accurate measurements of surface water vapour are challenging in such cold and dry conditions. New developments in infrared spectroscopy enable now the measurement of isotopic composition in water vapour traces. Two infrared spectrometers have been deployed at Concordia, allowing continuous, in situ measurements for 1 month in December 2014–January 2015. Comparison of the results from infrared spectroscopy with laboratory measurements of discrete samples trapped using cryogenic sampling validates the relevance of the method to measure isotopic composition in dry conditions. We observe very large diurnal cycles in isotopic composition well correlated with temperature diurnal cycles. Identification of different behaviours of isotopic composition in the water vapour associated with turbulent or stratified regime indicates a strong impact of meteorological processes in local vapour/snow interaction. Even if the vapour isotopic composition seems to be, at least part of the time, at equilibrium with the local snow, the slope of δD against δ18O prevents us from identifying a unique origin leading to this isotopic composition.

Fitness implications of simulated climate change in three species of copper butterflies (Lepidoptera: Lycaenidae)

Ongoing climate change and especially the associated heat waves may pose a major challenge to biodiversity conservation. Although many ectotherms in temperate zones may benefit from current climate change, others will suffer. However, the specific biological features determining the response of a given species to climate change have remained largely unknown. In the present study, conducted in three copper butterfly species that likely differ in their vulnerability to climate change, we tested the responses to simulated heat waves using ecologically realistic diurnal temperature cycles. Surprisingly, we found little support for our hypothesis that the most vulnerable species will suffer most from simulated climate change. Although species differed significantly in their responses to treatments, such variation appears to be largely ruled by selection pressures associated with the specific developmental pathway. In general, simulated heat waves had little effect on fitness components including fat content and immune function. Consequently, all three species appear to be capable of dealing with projected changes during their larval and pupal development. Whether this also applies to other developmental stages, more extreme stress or indirect effects climate change remains to be seen. Identifying the critical factors determining the vulnerability of a species to climate change will remain an important task for future research.

Climatological diurnal variability in sea surface temperature characterized from drifting buoy data

AbstractDrifting buoy sea‐surface temperature (SST) records have been used to characterize the diurnal variability of ocean temperature at a depth of order 20 cm. We use measurements covering the period 1986–2012 from the International Comprehensive Ocean‐Atmosphere Data Set (ICOADS) version 2.5, which is a collection of marine surface observations that includes individual SST records from drifting buoys. Appropriately transformed, this dataset is well suited for estimation of the diurnal cycle, since many drifting buoys have high temporal coverage (many reports per day), and are globally distributed. For each drifter for each day, we compute the local‐time daily SST variation relative to the local‐time daily mean SST. Climatological estimates of subdaily SST variability are found by averaging across various strata of the data: in 10° latitudinal bands as well as globally; and stratified with respect to season, wind speed and cloud cover. A parameterization of the diurnal variability is fitted as a function of the variables used to stratify the data, and the coefficients for this fit are also provided with the data. Results are consistent with expectations based on the previous work: the diurnal temperature cycle peaks in early afternoon (circa 2 pm local time); there is an increase in amplitude and a decrease in seasonality towards the equator. Generally, the ocean at this depth cools on windy days and warms on calm days, so that a component of subdaily variability is the SST tendency on slower timescales. By not ‘closing’ the diurnal cycle when stratified by environmental conditions, this dataset differs from previously published diurnal‐cycle parameterizations. This thorough characterization of the SST diurnal cycle will assist in interpreting SST observations made at different local times of day for climatological purposes, and in testing and constraining models of the diurnal‐cycle and air‐sea interaction at high temporal resolution.

Deciphering the role of solar-induced thermal stresses in rock weathering

A dearth of direct field observations limits our understanding of individual mechanical weathering processes and how they interact. In particular, the specific contributions of solar-induced thermal stresses to mechanical weathering are poorly characterized. Here, we present an 11 mo data set of cracking, using acoustic emissions (AEs), combined with measurements of rock temperature, strain and other environmental conditions, all recorded continuously for a granite boulder resting on the ground in open sun. We also present stresses derived from a numerical model of the temperature and stress fields in the boulder, idealized as a uniform elastic sphere experiencing simple solar temperature forcing. The thermal model is validated using this study’s data. Most observed cracking coincides with the timing of calculated maximum, insolation-driven, tensile thermal stresses. We also observe that most cracking occurs when storms, or other weather events, strongly perturb the rock surface temperature field at these times. We hypothesize that these weather-actuated thermal perturbations result in a complex thermal stress distribution that is superimposed on the background stresses arising from simple diurnal forcing; these additive stresses ultimately trigger measurable cracking. Measured locations of observed cracking and surface strain support this hypothesis in that they generally match model-predicted locations of maximum solar-induced tensile stresses. Also, recorded rock surface strain scales with diurnal temperature cycling and records progressive, cumulative extension (dilation), consistent with ongoing, thermal stress-driven subcritical crack growth in the boulder. Our results therefore suggest that (1) insolation-related thermal stresses by themselves are of sufficient magnitude to facilitate incremental subcritical crack growth that can subsequently be exploited by other chemical and physical processes and (2) simple insolation can impart an elevated tensile stress field that makes rock more susceptible to cracking triggered by added stress from other weathering mechanisms. Our observed cracking activity does not correlate simply with environmental conditions, including temperature extremes or the often-cited 2 °C/min thermal shock threshold. We propose that this lack of correlation is due to both the ever-varying ambient stress levels in any rock at Earth’s surface, as well as to the fact that ongoing subcritical crack growth itself will influence a rock’s stress field and strength. Because similar thermal cycling is universally experienced by subaerially exposed rock, this study elucidates specific mechanisms by which solar-induced thermal stresses may influence virtually all weathering processes.

Detecting and quantifying oil slick thickness by thermal remote sensing: A ground-based experiment

Abstract Thermal remote sensing has been used to detect oil slicks, yet estimation of slick thickness has largely remained unfeasible, mainly because the optimal detection time during a day, the minimum detectable thickness (MDT), and the relationship between the thermal response and thickness all remain largely unknown. Here, a ground-based experiment is used to address some of these uncertainties. The experiment measured the brightness temperatures (BTs) of oil slicks (with different known thicknesses) and oil-free water as a function of time of the day for both clear and turbid waters. The BT differences (BTDs) between oil slicks and oil-free water were further simulated using a diurnal temperature cycle (DTC) model. The results demonstrate that: (1) for an oil slick that is in thermal equilibrium with the water, the optimal time for thermal detection is around local noon (positive BTDs) with midnight (negative BTs) being the next best time; the periods shortly before sunrise and after sunset are not suitable for the thermal detection of oil slicks; (2) a better linear relationship between slick thickness and BTD is found during daytime than night-time and the type of background water also plays a role in this; and (3) assuming a detection limit of 0.3 °C for a thermal sensor, the MDT at noon is approximately 40 μm for both clear and turbid waters, while for other times of the day the MDT is higher (e.g., 75 and 150 μm for clear and turbid waters, respectively, at midnight). Detection limits for several existing satellite sensors and for other observation scenarios are also discussed.

Loss of a lake system in a megacity: The impact of urban expansion on seasonal meteorology in Mexico City

AbstractThe Mexico City Metropolitan Area (MCMA) has undergone significant urban expansion in a closed basin that once supported a large lacustrine system. While urbanization has been mentioned as a factor in observed meteorological trends, a systematic study of the effects of land use‐land cover change (LULCC) on seasonal meteorology is lacking. In this study, we utilize the Weather Research and Forecasting (WRF) system to determine the spatiotemporal changes in near‐surface air temperature, precipitation, and boundary layer conditions induced by the modern‐day urban landscape relative to presettlement conditions. We capture the MCMA extent through an improved Landsat‐based multicategory urban classification and therefore account for intraurban spatial heterogeneity and further conduct additional experiments to examine the sensitivity to anthropogenic heating within WRF. We find that accounting for these factors produced the best simulations of thermal conditions, with RMSE values less than 1.5°C at all measurement stations, and an improved diurnal cycle of air temperature and precipitation. We then assessed the impacts of LULCC in the MCMA, finding that thermal changes were largest during daytime hours, with temperature increasing, on average, by more than 4°C. Furthermore, we utilize these simulations to mechanistically link the built environment‐induced increase in air temperature to simulated increases in rainfall during the evening hours. To our knowledge, this study provides the first dynamical and thermodynamical evidence to support the rainfall enhancements documented through observations in the MCMA and link it quantitatively to the warming effects associated with urbanization. These results have important implications for understanding the meteorological conditions leading to widespread urban flooding in the MCMA.

The impact of clouds, land use and snow cover on climate in the Canadian Prairies

Abstract. This study uses 55 years of hourly observations of air temperature, relative humidity, daily precipitation, snow cover and cloud cover from 15 climate stations across the Canadian Prairies to analyze biosphere-atmosphere interactions. We will provide examples of the coupling between climate, snow cover, clouds, and land use. Snow cover acts as a fast climate switch. With the first snow fall, air temperature falls by 10 °C, and a similar increase in temperature occurs with snow melt. Climatologically, days with snow cover are 10 °C cooler than days with no snow cover in Alberta. However the interannual variability has a larger range, so that for every 10 % decrease in days with snow cover, the mean October to April climate is warmer by 1.4 to 1.5 °C. Snow cover also transforms the coupling between clouds and the diurnal cycle of air temperature from a boundary layer regime dominated by shortwave cloud forcing in the warm season to one dominated by longwave cloud forcing with snow cover. Changing agricultural land use in the past thirty years, specifically the reduction of summer fallowing, has cooled and moistened the growing season climate and increased summer precipitation. These hourly climate data provide a solid observational basis for understanding land surface coupling, which can be used to improve the representation of clouds and land-surface processes in atmospheric models.

Impact of atmospheric convectively coupled equatorial Kelvin waves on upper ocean variability

AbstractConvectively coupled Kelvin waves (CCKWs) are atmospheric weather systems that propagate eastward along the equatorial wave guide with phase speeds between 11 and 14 m s−1. They are an important constituent of the convective envelope of the Madden‐Julian oscillation (MJO), for which ocean‐atmosphere interactions play a vital role. Hence, ocean‐atmosphere interactions within CCKWs may be important for MJO development and prediction and for tropical climate, in general. Although the atmospheric structure of CCKWs has been well studied, their impact on the underlying ocean is unknown. In this paper, the ocean‐atmosphere interactions in CCKWs are investigated by a case study from November 2011 during the CINDY/DYNAMO field experiment, using in situ oceanographic measurements from an ocean glider. The analysis is then extended to a 15 year period using precipitation data from the Tropical Rainfall Measuring Mission and surface fluxes from the TropFlux analysis. A methodology is developed to calculate trajectories of CCKWs. CCKW events are strongly controlled by the MJO, with twice as many CCKWs observed during the convectively active phase of the MJO compared to the suppressed phase. Coherent ocean‐atmosphere interaction is observed during the passage of a CCKW, which lasts approximately 4 days at any given longitude. Surface wind speed and latent heat flux are enhanced, leading to a transient suppression of the diurnal cycle of sea surface temperature (SST) and a sustained decrease in bulk SST of 0.1°C. Given that a typical composite mean MJO SST anomaly is of the order of 0.3°C, and more than one CCKW can occur during the active phase of a single MJO event, the oceanographic impact of CCKWs is of major importance to the MJO cycle.

Ageing of Australian DNAN Based Melt‐Cast Insensitive Explosives

Abstract2,4‐Dinitroanisole (DNAN) is a new melt‐cast matrix ingredient that replaces traditional TNT in TNT‐based melt‐cast explosives. Aside from sensitiveness improvements, the use of DNAN allows for the continued operation of existing melt‐cast facilities (for example the Australian Munitions plants located at Mulwala and Benalla) without the need for major plant modifications. Researchers at Defence Science and Technology Group (DST Group) have developed several DNAN based formulations that have been extensively characterized. In an effort to better understand the ageing properties of these formulations, an accelerated ageing program was undertaken. Testing was conducted under two different ageing conditions; the first test condition was conducted at a constant 60 °C with ambient humidity and the second test condition was the A2 diurnal cycle (representative of hot dry climates). Analysis of the formulation density, sensitiveness, mechanical and thermal properties was made at three‐month intervals for a period of 12 months and results compared with conventional explosives similarly aged. For all DNAN‐based formulations there was negligible change in impact, friction, electrostatic discharge, and thermal testing over time. These results highlight the ability of the ARX formulations to diurnal temperature cycling and to hold favorable sensitiveness properties to various stimuli.

An assessment of the Polar Weather Research and Forecasting (WRF) model representation of near‐surface meteorological variables over West Antarctica

AbstractDespite the recent significant climatic changes observed over West Antarctica, which include large warming in central West Antarctica and accelerated ice loss, adequate validation of regional simulations of meteorological variables are rare for this region. To address this gap, results from a recent version of the Polar Weather Research and Forecasting model (Polar WRF) covering West Antarctica at a high horizontal resolution of 5 km were validated against near‐surface meteorological observations. The model employed physics options that included the Mellor‐Yamada‐Nakanishi‐Niino boundary layer scheme, the WRF Single Moment 5‐Class cloud microphysics scheme, the new version of the rapid radiative transfer model for both shortwave and longwave radiation, and the Noah land surface model. Our evaluation finds this model to be a useful tool for realistically capturing the near‐surface meteorological conditions. It showed high skill in simulating surface pressure (correlation ≥0.97), good skill for wind speed with better correlation at inland sites (0.7–0.8) compared to coastal sites (0.3–0.6), generally good representation of strong wind events, and good skill for temperature in winter (correlation ≥0.8). The main shortcomings of this configuration of Polar WRF are an occasional failure to properly represent transient cyclones and their influence on coastal winds, an amplified diurnal temperature cycle in summer, and a general tendency to underestimate the wind speed at inland sites in summer. Additional sensitivity studies were performed to quantify the impact of the choice of boundary layer scheme and surface boundary conditions. It is shown that the model is most sensitive to the choice of boundary layer scheme, with the representation of the temperature diurnal cycle in summer significantly improved by selecting the Mellor‐Yamada‐Janjic boundary layer scheme. By contrast, the model results showed little sensitivity to whether the horizontal resolution was 5 or 15 km.

Regional Soil Moisture Biases and Their Influence on WRF Model Temperature Forecasts over the Intermountain West

Abstract Operational Weather Research and Forecasting (WRF) Model forecasts run over Dugway Proving Ground (DPG) in northwest Utah, produced by the U.S. Army Test and Evaluation Command Four-Dimensional Weather System (4DWX), underpredict the amplitude of the diurnal temperature cycle during September and October. Mean afternoon [2000 UTC (1300 LST)] and early morning [1100 UTC (0400 LST)] 2-m temperature bias errors evaluated against 195 surface stations using 6- and 12-h forecasts are –1.37° and 1.66°C, respectively. Bias errors relative to soundings and 4DWX-DPG analyses illustrate that the afternoon cold bias extends from the surface to above the top of the planetary boundary layer, whereas the early morning warm bias develops in the lowest model levels and is confined to valleys and basins. These biases are largest during mostly clear conditions and are caused primarily by a regional overestimation of near-surface soil moisture in operational land surface analyses, which do not currently assimilate in situ soil moisture observations. Bias correction of these soil moisture analyses using data from 42 North American Soil Moisture Database stations throughout the Intermountain West reduces both the afternoon and early morning bias errors and improves forecasts of upper-level temperature and stability. These results illustrate that the assimilation of in situ and remotely sensed soil moisture observations, including those from the recently launched NASA Soil Moisture Active Passive (SMAP) mission, have the potential to greatly improve land surface analyses and near-surface temperature forecasts over arid regions.