scholarly journals Estimating radar precipitation in cold climates: the role of air temperature within a non-parametric framework

2018 ◽  
Vol 22 (12) ◽  
pp. 6533-6546 ◽  
Author(s):  
Kuganesan Sivasubramaniam ◽  
Ashish Sharma ◽  
Knut Alfredsen
Keyword(s):  
Predictive Model ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Precipitation Rate ◽  
Cold Climates ◽  
Near Surface ◽  
Air Temperatures ◽  
Precipitation Estimation ◽  
Precipitation Estimates ◽  
Non Parametric

Abstract. The use of ground-based precipitation measurements in radar precipitation estimation is well known in radar hydrology. However, the approach of using gauged precipitation and near-surface air temperature observations to improve radar precipitation estimates in cold climates is much less common. In cold climates, precipitation is in the form of snow, rain or a mixture of the two phases. Air temperature is intrinsic to the phase of the precipitation and could therefore be a possible covariate in the models used to ascertain radar precipitation estimates. In the present study, we investigate the use of air temperature within a non-parametric predictive framework to improve radar precipitation estimation for cold climates. A non-parametric predictive model is constructed with radar precipitation rate and air temperature as predictor variables and gauge precipitation as an observed response using a k nearest neighbour (k-nn) regression estimator. The relative importance of the two predictors is ascertained using an information theory-based weighting. Four years (2011–2015) of hourly radar precipitation rates from the Norwegian national radar network over the Oslo region, hourly gauged precipitation from 68 gauges and gridded observational air temperatures were used to formulate the predictive model, hence making our investigation possible. Gauged precipitation data were corrected for wind-induced under-catch before using them as true observed response. The predictive model with air temperature as an added covariate reduces root-mean-square error (RMSE) by up to 15 % compared to the model that uses radar precipitation rate as the sole predictor. More than 80 % of gauge locations in the study area showed improvement with the new method. Further, the associated impact of air temperature became insignificant at more than 85 % of gauge locations when the near-surface air temperature was warmer than 10 ∘C, which indicates that the partial dependence of precipitation on air temperature is most useful for colder temperatures.

scholarly journals Estimating Radar Precipitation in Cold Climates: The role of Air Temperature within a Nonparametric Framework

2018 ◽  
Author(s):  
Kuganesan Sivasubramaniam ◽  
Ashish Sharma ◽  
Knut Alfredsen
Keyword(s):  
Predictive Model ◽  
Air Temperature ◽  
Mean Squared Error ◽  
Radar Reflectivity ◽  
Precipitation Rate ◽  
Cold Climates ◽  
Radar Network ◽  
Precipitation Estimation ◽  
Partial Dependence

Abstract. In cold climates, the form of precipitation (snow or rain or a mixture of snow and rain) results in uncertainty in radar precipitation estimation. Estimation often proceeds without distinguishing the state of precipitation which is known to impact the radar reflectivity–precipitation relationship. In the present study, we investigate the use of air temperature within a nonparametric predictive framework to improve radar precipitation estimation for cold climates. Compared to radar reflectivity–gauge relationships, this approach uses gauge precipitation and air temperature observations to estimate radar precipitation. A nonparametric predictive model is constructed with radar precipitation rate and air temperature as predictor variables, and gauge precipitation as an observed response using a k-nearest neighbour (k-nn) regression estimator. The relative importance of the two predictors is ascertained using an information theory-based rationale. Four years (2011–2015) of hourly radar precipitation rate from the Norwegian national radar network over the Oslo region, hourly gauged precipitation from 68 gauges, and gridded observational air temperature were used to formulate the predictive model and hence make our investigation possible. Gauged precipitation data were corrected for wind induced catch error before using them as true observed response. The predictive model with air temperature as an added covariate reduces root mean squared error (RMSE) by up to 15 % compared to the model that uses radar precipitation rate as the sole predictor. More than 80 % of gauge locations in the study area showed improvement with the new method. Further, the associated impact of air temperature became insignificant at more than 85 % of gauge locations when the temperature was above 10 degrees Celsius, which indicates that the partial dependence of precipitation on air temperature is most important for colder climates alone.

scholarly journals An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern United States: observational-based analysis of surface temperature

2016 ◽  
Vol 16 (10) ◽  
pp. 6475-6494 ◽  
Author(s):  
Jianglong Zhang ◽  
Jeffrey S. Reid ◽  
Matthew Christensen ◽  
Angela Benedetti
Keyword(s):  
United States ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cooling Efficiency ◽  
Surface Cooling ◽  
Near Surface ◽  
Smoke Aerosol ◽  
Weather Forecasts ◽  
Air Temperatures ◽  
Daily Changes

Abstract. A major continental-scale biomass burning smoke event from 28–30 June 2015, spanning central Canada through the eastern seaboard of the United States, resulted in unforecasted drops in daytime high surface temperatures on the order of 2–5  °C in the upper Midwest. This event, with strong smoke gradients and largely cloud-free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near-surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, τ) reached values above 5. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550) was found. A further analysis of European Centre for Medium-Range Weather Forecasts (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near-surface air temperature forecasts for up to 54 h as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near-surface air temperatures from ECMWF, NCEP, and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke-aerosol-induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near-surface air temperature forecasts. However, regions such as eastern China, eastern Russia, India, and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.

scholarly journals Suitability of a constant air temperature lapse rate over an Alpine glacier: testing the Greuell and Böhm model as an alternative

2013 ◽  
Vol 54 (63) ◽  
pp. 120-130 ◽  
Author(s):  
Lene Petersen ◽  
Francesca Pellicciotti ◽  
Inge Juszak ◽  
Marco Carenzo ◽  
Ben Brock
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Ambient Air ◽  
Lapse Rate ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Alpine Glacier ◽  
Temperature Lapse Rate ◽  
Boundary Layer Height ◽  
Air Temperatures

AbstractNear-surface air temperature, typically measured at a height of 2 m, is the most important control on the energy exchange and the melt rate at a snow or ice surface. It is distributed in a simplistic manner in most glacier melt models by using constant linear lapse rates, which poorly represent the actual spatial and temporal variability of air temperature. In this paper, we test a simple thermodynamic model proposed by Greuell and Böhm in 1998 as an alternative, using a new dataset of air temperature measurements from along the flowline of Haut Glacier d’Arolla, Switzerland. The unmodified model performs little better than assuming a constant linear lapse rate. When modified to allow the ratio of the boundary layer height to the bulk heat transfer coefficient to vary along the flowline, the model matches measured air temperatures better, and a further reduction of the root-mean-square error is obtained, although there is still considerable scope for improvement. The modified model is shown to perform best under conditions favourable to the development of katabatic winds – few clouds, positive ambient air temperature, limited influence of synoptic or valley winds and a long fetch – but its performance is poor under cloudy conditions.

scholarly journals Infrared Interferometric Measurements of the Near-Surface Air Temperature over the Oceans

2005 ◽  
Vol 22 (7) ◽  
pp. 1019-1032 ◽  
Author(s):  
P. J. Minnett ◽  
K. A. Maillet ◽  
J. A. Hanafin ◽  
B. J. Osborne
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Heat Island ◽  
Radiometric Measurement ◽  
Near Surface ◽  
Air Temperatures ◽  
Wide Range ◽  
Marine Air ◽  
The Tropical Pacific

Abstract The radiometric measurement of the marine air temperature using a Fourier transform infrared spectroradiometer is described. The measurements are taken by the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) that has been deployed on many research ships in a wide range of conditions. This approach is inherently more accurate than conventional techniques and can be used to determine some of the error characteristics of the standard measurements. Examples are given from several cruises ranging from the Arctic to the equatorial Pacific Oceans. It is shown that the diurnal heating signal in radiometric air temperatures in the tropical Pacific can typically reach an amplitude of ∼15% of that measured by conventional sensors. Conventional data have long been recognized as being contaminated by direct solar heating and heat island effects of the ships or buoys on which they are mounted, but here this effect is quantified by comparisons with radiometric measurements.

scholarly journals A New Model to Downscale Urban and Rural Surface and Air Temperatures Evaluated in Shanghai, China

2018 ◽  
Vol 57 (10) ◽  
pp. 2267-2283 ◽  
Author(s):  
Dongwei Liu ◽  
C. S. B. Grimmond ◽  
Jianguo Tan ◽  
Xiangyu Ao ◽  
Jie Peng ◽  
...  
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Wave Radiation ◽  
Climate Services ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures

AbstractA simple model, the Surface Temperature and Near-Surface Air Temperature (at 2 m) Model (TsT2m), is developed to downscale numerical model output (such as from ECMWF) to obtain higher-temporal- and higher-spatial-resolution surface and near-surface air temperature. It is evaluated in Shanghai, China. Surface temperature (Ts) and near-surface air temperature (Ta) submodels account for variations in land cover and their different thermal properties, resulting in spatial variations of surface and air temperature. The net all-wave radiation parameterization (NARP) scheme is used to compute net wave radiation for the surface temperature submodel, the objective hysteresis model (OHM) is used to calculate the net storage heat fluxes, and the surface temperature is obtained by the force-restore method. The near-surface air temperature submodel considers the horizontal and vertical energy changes for a column of well-mixed air above the surface. Modeled surface temperatures reproduce the general pattern of MODIS images well, while providing more detailed patterns of the surface urban heat island. However, the simulated surface temperatures capture the warmer urban land cover and are 10.3°C warmer on average than those derived from the coarser MODIS data. For other land-cover types, values are more similar. Downscaled, higher-temporal- and higher-spatial-resolution air temperatures are compared to observations at 110 automatic weather stations across Shanghai. After downscaling with TsT2m, the average forecast accuracy of near-surface air temperature is improved by about 20%. The scheme developed has considerable potential for prediction and mitigation of urban climate conditions, particularly for weather and climate services related to heat stress.

scholarly journals An evaluation of the impact of aerosol particles on weather forecasts from a biomass burning aerosol event over the Midwestern US: Observational-based analysis of surface temperature

2016 ◽  
Author(s):  
Jianglong Zhang ◽  
Jeffrey S. Reid ◽  
Matthew Christensen ◽  
Angela Benedetti
Keyword(s):  
Air Temperature ◽  
Biomass Burning ◽  
Surface Air Temperature ◽  
Cooling Efficiency ◽  
Surface Cooling ◽  
Near Surface ◽  
Smoke Aerosol ◽  
Weather Forecasts ◽  
Air Temperatures ◽  
Daily Changes

Abstract. A major continental scale biomass burning smoke event from June 28–30, 2015, spanning central Canada through the eastern seaboard of the United States, resulted in un-forecasted drops in daytime high surface temperatures on the order of 2–5 °C in the Upper Mid-West. This event, with strong smoke gradients and largely cloud free conditions, provides a natural laboratory to study how aerosol radiative effects may influence numerical weather prediction (NWP) forecast outcomes. Here, we describe the nature of this smoke event and evaluate the differences in observed near surface air temperatures between Bismarck (clear) and Grand Forks (overcast smoke), to evaluate to what degree solar radiation forcing from a smoke plume introduces daytime surface cooling, and how this affects model bias in forecasts and analyses. For this event, mid-visible (550 nm) smoke aerosol optical thickness (AOT, τ) reached values above five. A direct surface cooling efficiency of −1.5 °C per unit AOT (at 550 nm, τ550) was found. A further analysis of European Center for Medium range Weather Forecasting (ECMWF), National Centers for Environmental Prediction (NCEP), United Kingdom Meteorological Office (UKMO) near surface air temperature forecasts for up to 52 hours as a function of Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target AOT data across more than 400 surface stations, also indicated the presence of the daytime aerosol direct cooling effect, but suggested a smaller aerosol direct surface cooling efficiency with magnitude on the order of −0.25 °C to −1.0 °C per unit τ550. In addition, using observations from the surface stations, uncertainties in near surface air temperatures from ECMWF, NCEP and UKMO model runs are estimated. This study further suggests that significant daily changes in τ550 above 1, at which the smoke aerosol induced direct surface cooling effect could be comparable in magnitude with model uncertainties, are rare events on a global scale. Thus, incorporating a more realistic smoke aerosol field into numerical models is currently less likely to significantly improve the accuracy of near surface air temperature forecasts. However, regions such as East China, East Russian, India and portions of the Saharan and Taklamakan deserts, where significant daily changes in AOTs are more frequent, are likely to benefit from including an accurate aerosol analysis into numerical weather forecasts.

scholarly journals Temperature Characteristics of Porous Portland Cement Concrete during the Hot Summer Session

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Liqun Hu ◽  
Yangyang Li ◽  
Xiaolong Zou ◽  
Shaowen Du ◽  
Zhuangzhuang Liu ◽  
...  
Keyword(s):  
Heat Flux ◽  
Portland Cement ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Total Output ◽  
Portland Cement Concrete ◽  
Cement Concrete ◽  
Near Surface ◽  
Air Temperatures ◽  
Summer Session

Pavement heats the near-surface air and affects the thermal comfort of the human body in hot summer. Because of a large amount of connected porosity of porous Portland cement concrete (PPCC), the thermal parameters of PPCC are much different from those of traditional Portland cement concrete (PCC). The temperature change characteristics of PPCC and the effects on surrounding environment are also different. A continuous 48-hour log of temperature of a PCC and five kinds of PPCC with different porosity were recorded in the open air in the hot summer. The air temperatures at different heights above concrete specimens were tested using self-made enclosed boxes to analyze the characteristics of near-surface air temperature. The output heat flux of different concrete specimens was calculated. The results show that the PPCC has higher temperature in the daytime and lower temperature in the nighttime and larger temperature gradient than the PCC. The air temperature above PPCC is lower than that of PCC after solar radiation going to zero at night. The total output heat flux of PPCC is slightly smaller in the daytime and significantly smaller at night than that of PCC. The results of tests and calculations indicate that PPCC contributes to the mitigation of heating effect of pavement on the near-surface air.

scholarly journals An Evaluation of HIRS Near-Surface Air Temperature Product in the Arctic with SHEBA Data

2016 ◽  
Vol 33 (3) ◽  
pp. 453-460 ◽  
Author(s):  
Ge Peng ◽  
Lei Shi ◽  
Steve T. Stegall ◽  
Jessica L. Matthews ◽  
Christopher W. Fairall
Keyword(s):  
Air Temperature ◽  
Heat Budget ◽  
Surface Air Temperature ◽  
Correlation Coefficients ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Near Surface ◽  
Brightness Temperatures ◽  
Uncertainty Sources ◽  
Air Temperatures

AbstractThe accuracy of cloud-screened 2-m air temperatures derived from the intersatellite-calibrated brightness temperatures based on the High Resolution Infrared Radiation Sounder (HIRS) measurements on board the National Oceanic and Atmospheric Administration (NOAA) Polar-Orbiting Operational Environmental Satellite (POES) series is evaluated by comparing HIRS air temperatures to 1-yr quality-controlled measurements collected during the Surface Heat Budget of the Arctic Ocean (SHEBA) project (October 1997–September 1998). The mean error between collocated HIRS and SHEBA 2-m air temperature is found to be on the order of 1°C, with a slight sensitivity to spatial and temporal radii for collocation. The HIRS temperatures capture well the temporal variability of SHEBA temperatures, with cross-correlation coefficients higher than 0.93, all significant at the 99.9% confidence level. More than 87% of SHEBA temperature variance can be explained by linear regression of collocated HIRS temperatures. The analysis found a strong dependency of mean temperature errors on cloud conditions observed during SHEBA, indicating that availability of an accurate cloud mask in the region is essential to further improve the quality of HIRS near-surface air temperature products. This evaluation establishes a baseline of accuracy of HIRS temperature retrievals, providing users with information on uncertainty sources and estimates. It is a first step toward development of a new long-term 2-m air temperature product in the Arctic that utilizes intersatellite-calibrated remote sensing data from the HIRS instrument.

scholarly journals Intercomparison of Surface Temperatures from AIRS, MERRA, and MERRA-2 with NOAA and GC-Net Weather Stations at Summit, Greenland

2018 ◽  
Vol 57 (5) ◽  
pp. 1231-1245 ◽  
Author(s):  
Thomas J. Hearty ◽  
Jae N. Lee ◽  
Dong L. Wu ◽  
Richard Cullather ◽  
John M. Blaisdell ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cold Season ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Weather Stations ◽  
The Difference ◽  
Temperature Inversions

AbstractThe surface skin and air temperatures reported by the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU-A), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and MERRA-2 at Summit, Greenland, are compared with near-surface air temperatures measured at National Oceanic and Atmospheric Administration (NOAA) and Greenland Climate Network (GC-Net) weather stations. The AIRS/AMSU-A surface skin temperature (TS) is best correlated with the NOAA 2-m air temperature (T2M) but tends to be colder than the station measurements. The difference may be the result of the frequent near-surface temperature inversions in the region. The AIRS/AMSU-A surface air temperature (SAT) is also correlated with the NOAA T2M but has a warm bias during the cold season and a larger standard error than the surface temperature. The extrapolation of the temperature profile to calculate the AIRS SAT may not be valid for the strongest inversions. The GC-Net temperature sensors are not held at fixed heights throughout the year; however, they are typically closer to the surface than the NOAA station sensors. Comparing the lapse rates at the two stations shows that it is larger closer to the surface. The difference between the AIRS/AMSU-A SAT and TS is sensitive to near-surface inversions and tends to measure stronger inversions than both stations. The AIRS/AMSU-A may be sampling a thicker layer than either station. The MERRA-2 surface and near-surface temperatures show improvements over MERRA but little sensitivity to near-surface temperature inversions.

scholarly journals Evaluation and Comparison of Noah and Pleim–Xiu Land Surface Models in MM5 Using GÖTE2001 Data: Spatial and Temporal Variations in Near-Surface Air Temperature

2007 ◽  
Vol 46 (10) ◽  
pp. 1587-1605 ◽  
Author(s):  
J-F. Miao ◽  
D. Chen ◽  
K. Borne
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Land Surface ◽  
Model Performance ◽  
Surface Air Temperature ◽  
Near Surface ◽  
Surface Models ◽  
Urban Heat ◽  
Soil Moisture Initialization ◽  
Evident Difference

Abstract In this study, the performance of two advanced land surface models (LSMs; Noah LSM and Pleim–Xiu LSM) coupled with the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), version 3.7.2, in simulating the near-surface air temperature in the greater Göteborg area in Sweden is evaluated and compared using the GÖTE2001 field campaign data. Further, the effects of different planetary boundary layer schemes [Eta and Medium-Range Forecast (MRF) PBLs] for Noah LSM and soil moisture initialization approaches for Pleim–Xiu LSM are investigated. The investigation focuses on the evaluation and comparison of diurnal cycle intensity and maximum and minimum temperatures, as well as the urban heat island during the daytime and nighttime under the clear-sky and cloudy/rainy weather conditions for different experimental schemes. The results indicate that 1) there is an evident difference between Noah LSM and Pleim–Xiu LSM in simulating the near-surface air temperature, especially in the modeled urban heat island; 2) there is no evident difference in the model performance between the Eta PBL and MRF PBL coupled with the Noah LSM; and 3) soil moisture initialization is of crucial importance for model performance in the Pleim–Xiu LSM. In addition, owing to the recent release of MM5, version 3.7.3, some experiments done with version 3.7.2 were repeated to reveal the effects of the modifications in the Noah LSM and Pleim–Xiu LSM. The modification to longwave radiation parameterizations in Noah LSM significantly improves model performance while the adjustment of emissivity, one of the vegetation properties, affects Pleim–Xiu LSM performance to a larger extent. The study suggests that improvements both in Noah LSM physics and in Pleim–Xiu LSM initialization of soil moisture and parameterization of vegetation properties are important.

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