Evaluation of Upper Indus Near-Surface Climate Representation by WRF in the High Asia Refined Analysis

Abstract Data paucity is a severe barrier to the characterization of Himalayan near-surface climates. Regional climate modeling can help to fill this gap, but the resulting data products need critical evaluation before use. This study aims to extend the appraisal of one such dataset, the High Asia Refined Analysis (HAR). Focusing on the upper Indus basin (UIB), the climatologies of variables needed for process-based hydrological and cryospheric modeling are evaluated, leading to three main conclusions. First, precipitation in the 10-km HAR product shows reasonable correspondence with most in situ measurements. It is also generally consistent with observed runoff, while additionally reproducing the UIB’s strong vertical precipitation gradients. Second, the HAR shows seasonally varying bias patterns. A cold bias in temperature peaks in spring but reduces in summer, at which time the high bias in relative humidity diminishes. These patterns are concurrent with summer overestimation (underestimation) of incoming shortwave (longwave) radiation. Finally, these seasonally varying biases are partly related to deficiencies in cloud, snow, and albedo representations. In particular, insufficient cloud cover in summer leads to the overestimation of incoming shortwave radiation. This contributes to the reduced cold bias in summer by enhancing surface warming. A persistent high bias in albedo also plays a critical role, particularly by suppressing surface heating in spring. Improving representations of cloud, snow cover, and albedo, and thus their coupling with seasonal climate transitions, would therefore help build upon the considerable potential shown by the HAR to fill a vital data gap in this immensely important basin.

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An Evaluation of Surface Atmospheric Changes over the Arctic Ocean for 2000–09 Using Recent Reanalyses

Earth Interactions ◽

10.1175/ei-d-14-0012.1 ◽

2015 ◽

Vol 19 (2) ◽

pp. 1-18 ◽

Cited By ~ 1

Author(s):

Ayan H. Chaudhuri ◽

Rui M. Ponte

Keyword(s):

Arctic Ocean ◽

Extreme Event ◽

Longwave Radiation ◽

Remotely Sensed ◽

Surface Radiation ◽

Shortwave Radiation ◽

The Arctic ◽

Near Surface ◽

The Arctic Ocean ◽

Ice Retreat

Abstract The authors examine five recent reanalysis products [NCEP Climate Forecast System Reanalysis (CFSR), Modern-Era Retrospective Analysis for Research and Applications (MERRA), Japanese 25-year Reanalysis Project (JRA-25), Interim ECMWF Re-Analysis (ERA-Interim), and Arctic System Reanalysis (ASR)] for 1) trends in near-surface radiation fluxes, air temperature, and humidity, which are important indicators of changes within the Arctic Ocean and also influence sea ice and ocean conditions, and 2) fidelity of these atmospheric fields and effects for an extreme event: namely, the 2007 ice retreat. An analysis of trends over the Arctic for the past decade (2000–09) shows that reanalysis solutions have large spreads, particularly for downwelling shortwave radiation. In many cases, the differences in significant trends between the five reanalysis products are comparable to the estimated trend within a particular product. These discrepancies make it difficult to establish a consensus on likely changes occurring in the Arctic solely based on results from reanalyses fields. Regarding the 2007 ice retreat event, comparisons with remotely sensed estimates of downwelling radiation observations against these reanalysis products present an ambiguity. Remotely sensed observations from a study cited herewith suggest a large increase in downwelling summertime shortwave radiation and decrease in downwelling summertime longwave radiation from 2006 and 2007. On the contrary, the reanalysis products show only small gains in summertime shortwave radiation, if any; however, all the products show increases in downwelling longwave radiation. Thus, agreement within reanalysis fields needs to be further checked against observations to assess possible biases common to all products.

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Optimization of Noah and Noah_MP WRF Land Surface Schemes in Snow-Melting Conditions over Complex Terrain

Monthly Weather Review ◽

10.1175/mwr-d-16-0408.1 ◽

2017 ◽

Vol 145 (12) ◽

pp. 4727-4745 ◽

Cited By ~ 17

Author(s):

Elena Tomasi ◽

Lorenzo Giovannini ◽

Dino Zardi ◽

Massimiliano de Franceschi

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Winter Season ◽

Wrf Model ◽

Longwave Radiation ◽

Shortwave Radiation ◽

Land Use Classification ◽

Near Surface ◽

Thermal Inversion ◽

Alpine Valley

The paper presents the results of high-resolution simulations performed with the WRF Model, coupled with two different land surface schemes, Noah and Noah_MP, with the aim of accurately reproducing winter season meteorological conditions in a typical Alpine valley. Accordingly, model results are compared against data collected during an intensive field campaign performed in the Adige Valley, in the eastern Italian Alps. In particular, the ability of the model in reproducing the time evolution of 2-m temperature and of incoming and outgoing shortwave and longwave radiation is examined. The validation of model results highlights that, in this context, WRF reproduces rather poorly near-surface temperature over snow-covered terrain, with an evident underestimation, during both daytime and nighttime. Furthermore it fails to capture specific atmospheric processes, such as the temporal evolution of the ground-based thermal inversion. The main cause of these errors lies in the miscalculation of the mean gridcell albedo, resulting in an inaccurate estimate of the reflected solar radiation calculated by both Noah and Noah_MP. Therefore, modifications to the initialization, to the land-use classification, and to both land surface models are performed to improve model results, by intervening in the calculation of the albedo, of the snow cover, and of the surface temperature. Qualitative and quantitative analyses show that, after these changes, a significant improvement in the comparability between model results and observations is achieved. In particular, outgoing shortwave radiation is lowered, 2-m temperature maxima increased accordingly, and ground-based thermal inversions are better captured.

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Influence of Precipitation Assimilation on a Regional Climate Model’s Surface Water and Energy Budgets

Journal of Hydrometeorology ◽

10.1175/jhm615.1 ◽

2007 ◽

Vol 8 (4) ◽

pp. 642-664 ◽

Cited By ~ 12

Author(s):

Ana M. B. Nunes ◽

John O. Roads

Keyword(s):

Surface Water ◽

Energy Budget ◽

Prediction Models ◽

Regional Climate ◽

Longwave Radiation ◽

Specific Humidity ◽

Climate Simulation ◽

Energy Budgets ◽

Near Surface ◽

Regional Reanalysis

Abstract Initialization of the moisture profiles has been used to overcome the imbalance between analysis schemes and prediction models that generates the so-called spinup problem seen in the hydrological fields. Here precipitation assimilation through moisture adjustment has been proposed as a technique to reduce this problem in regional climate simulations by adjusting the specific humidity according to 3-hourly North American Regional Reanalysis rain rates during two simulated years: 1988 and 1993. A control regional simulation provided the initial condition fields for both simulations. The precipitation assimilation simulation was then compared to the control regional climate simulation, reanalyses, and observations to determine whether assimilation of precipitation had a positive influence on modeled surface water and energy budget terms. In general, rainfall assimilation improved the regional model surface water and energy budget terms over the conterminous United States. Precipitation and runoff correlated better than the control and the global reanalysis fields to the regional reanalysis and available observations. Upward shortwave and downward short- and longwave radiation fluxes had regional seasonal cycles closer to the observed values than the control, and the near-surface temperature anomalies were also improved.

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An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves

Geoscientific Model Development ◽

10.5194/gmd-8-2285-2015 ◽

2015 ◽

Vol 8 (7) ◽

pp. 2285-2298 ◽

Cited By ~ 17

Author(s):

A. I. Stegehuis ◽

R. Vautard ◽

P. Ciais ◽

A. J. Teuling ◽

D. G. Miralles ◽

...

Keyword(s):

Heat Wave ◽

Land Surface ◽

Western Europe ◽

Climate Models ◽

Climate Model ◽

Heat Waves ◽

Regional Climate ◽

Shortwave Radiation ◽

Cold Bias ◽

The Impact

Abstract. Many climate models have difficulties in properly reproducing climate extremes, such as heat wave conditions. Here we use the Weather Research and Forecasting (WRF) regional climate model with a large combination of different atmospheric physics schemes, in combination with the NOAH land-surface scheme, with the goal of detecting the most sensitive physics and identifying those that appear most suitable for simulating the heat wave events of 2003 in western Europe and 2010 in Russia. In total, 55 out of 216 simulations combining different atmospheric physical schemes have a temperature bias smaller than 1 °C during the heat wave episodes, the majority of simulations showing a cold bias of on average 2–3 °C. Conversely, precipitation is mostly overestimated prior to heat waves, and shortwave radiation is slightly overestimated. Convection is found to be the most sensitive atmospheric physical process impacting simulated heat wave temperature across four different convection schemes in the simulation ensemble. Based on these comparisons, we design a reduced ensemble of five well performing and diverse scheme configurations, which may be used in the future to perform heat wave analysis and to investigate the impact of climate change during summer in Europe.

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Influence of the Laurentian Great Lakes on Regional Climate*

Journal of Climate ◽

10.1175/jcli-d-12-00140.1 ◽

2013 ◽

Vol 26 (3) ◽

pp. 789-804 ◽

Cited By ~ 74

Author(s):

Michael Notaro ◽

Kathleen Holman ◽

Azar Zarrin ◽

Elody Fluck ◽

Steve Vavrus ◽

...

Keyword(s):

Great Lakes ◽

Air Temperature ◽

Climate Model ◽

Regional Climate ◽

Cloud Amount ◽

Surface Energy Budget ◽

Laurentian Great Lakes ◽

Theoretical Physics ◽

Shortwave Radiation ◽

Near Surface

Abstract The influence of the Laurentian Great Lakes on climate is assessed by comparing two decade-long simulations, with the lakes either included or excluded, using the Abdus Salam International Centre for Theoretical Physics Regional Climate Model, version 4. The Great Lakes dampen the variability in near-surface air temperature across the surrounding region while reducing the amplitude of the diurnal cycle and annual cycle of air temperature. The impacts of the Great Lakes on the regional surface energy budget include an increase (decrease) in turbulent fluxes during the cold (warm) season and an increase in surface downward shortwave radiation flux during summer due to diminished atmospheric moisture and convective cloud amount. Changes in the hydrologic budget due to the presence of the Great Lakes include increases in evaporation and precipitation during October–March and decreases during May–August, along with springtime reductions in snowmelt-related runoff. Circulation responses consist of a regionwide decrease in sea level pressure in autumn–winter and an increase in summer, with enhanced ascent and descent in the two seasons, respectively. The most pronounced simulated impact of the Great Lakes on synoptic systems traversing the basin is a weakening of cold-season anticyclones.

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Interhemispheric Variability of Earth’s Radiation

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-15-0106.1 ◽

2015 ◽

Vol 72 (12) ◽

pp. 4615-4628 ◽

Cited By ~ 2

Author(s):

Alexander Ruzmaikin ◽

Hartmut H. Aumann ◽

Jonathan H. Jiang

Keyword(s):

Time Scales ◽

Critical Role ◽

Heat Content ◽

Coupled Model ◽

Longwave Radiation ◽

Shortwave Radiation ◽

Hemispheric Differences ◽

Meridional Transport ◽

The Pacific ◽

Intercomparison Project

Abstract The variability of interhemispheric symmetry of Earth’s energy serves as an independent indicator of climate change. The analysis of updated data obtained from satellite measurements at the top of the atmosphere (TOA) shows that in accord with Earth’s orbital requirements the annually averaged incident solar radiation is the same in the Northern and Southern Hemispheres, the annual mean of the reflected shortwave radiation is almost north–south symmetric, and the annual mean of the outgoing longwave radiation is larger in the Northern Hemisphere by 1.4 W m−2. These mean radiations systematically differ from the mean radiations found from the numerical atmospheric models that participated in the Coupled Model Intercomparison Project phase 5 (CMIP5). The hemispheric differences of the TOA radiations vary on the annual and interannual time scales. The multidecadal variability in Earth’s north–south temperature difference reveals a similarity of trends in both hemispheres. The Atlantic meridional transport (in contrast to the Pacific meridional transport) is found to be coherent with the interhemispheric ocean heat content (OHC) difference on decadal and multidecadal time scales, indicating a critical role of the Atlantic in the interhemispheric energy balance change.

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Developing an algorithm to consider sub-grid topographic effects on surface radiation in a kilometre-scale regional climate model

10.5194/egusphere-egu21-5575 ◽

2021 ◽

Author(s):

Christian Steger ◽

Christoph Schär

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Longwave Radiation ◽

Surface Radiation ◽

Shortwave Radiation ◽

View Factor ◽

Radiation Correction ◽

Sky View Factor

In mountainous regions, atmospheric and surface conditions (like snow coverage) are strongly modulated by complex terrain. One relevant process is the topographic effect on incoming/outgoing surface short- and longwave radiation by surrounding terrain. Radiation in weather and climate models is typically represented by the two-stream approximation, which only allows for vertical radiation exchange and thus no lateral interaction with terrain. In reality, surface radiation can be modulated through various processes: the direct-beam part of the incoming shortwave radiation depends on local surface inclination and on shading from the neighbouring terrain. Incoming diffuse shortwave radiation is modified by partial sky-obstruction and terrain reflection. Outgoing longwave radiation is reduced by interception from neighbouring terrain.In this study, we develop a parameterisation which considers the above-mentioned processes on a sub-grid scale, and implement the scheme in the Regional Climate Model COSMO (Consortium for Small-scale Modeling). On the grid scale, such a parameterisation is already available and has been applied in the numerical weather prediction mode of COSMO. Applying this parameterisation in the climate mode of COSMO has revealed that biases like the over-/underestimation of snow cover duration at south-/north-facing slopes can be improved. However, the associated radiation correction appears to be too weak because only terrain effects on the resolved scales are considered. We therefore parameterise these effects on a sub-grid scale.The (current) surface radiation correction scheme requires consideration of topographic parameters like the elevation of the horizon and the sky-view factor. The computation of these parameters on the sub-grid scale is very expensive, because non-local information of a large high-resolution Digital Elevation Model (DEM) needs to be processed. We developed a new algorithm, which allows for horizon computations from a high-resolution DEM in a fast and flexible way. We furthermore found that existing sky-view factor algorithms might yield inaccurate results for locations with very steep terrain and subsequently developed an improved method. Output of these new algorithms will be used for the new sub-grid radiation parameterisation scheme.

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Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble

Geoscientific Model Development ◽

10.5194/gmd-8-603-2015 ◽

2015 ◽

Vol 8 (3) ◽

pp. 603-618 ◽

Cited By ~ 113

Author(s):

E. Katragkou ◽

M. García-Díez ◽

R. Vautard ◽

S. Sobolowski ◽

P. Zanis ◽

...

Keyword(s):

Cloud Cover ◽

Water Cycle ◽

Regional Climate ◽

Shortwave Radiation ◽

Cold Bias ◽

Total Cloud Cover ◽

Model Simulations ◽

Temperature And Precipitation ◽

Downward Shortwave Radiation ◽

Downward Radiation

Abstract. In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990–2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell–Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max −2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40–60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (−2.8 °C); this location suggests that land–atmosphere rather than cloud–radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain–Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15–30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.

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Testing longwave radiation parameterizations under clear and overcast skies at Storglaciären, Sweden

The Cryosphere ◽

10.5194/tc-3-75-2009 ◽

2009 ◽

Vol 3 (1) ◽

pp. 75-84 ◽

Cited By ~ 41

Author(s):

J. Sedlar ◽

R. Hock

Keyword(s):

Meteorological Data ◽

Water Vapor Pressure ◽

Longwave Radiation ◽

Cloud Fraction ◽

Shortwave Radiation ◽

Mean Bias Error ◽

Bias Error ◽

Near Surface ◽

Radiation Parameterizations ◽

Sky Conditions

Abstract. Energy balance based glacier melt models require accurate estimates of incoming longwave radiation but direct measurements are often not available. Multi-year near-surface meteorological data from Storglaciären, Northern Sweden, were used to evaluate commonly used longwave radiation parameterizations in a glacier environment under clear-sky and all-sky conditions. Parameterizations depending solely on air temperature performed worse than those which include water vapor pressure. All models tended to overestimate incoming longwave radiation during periods of low longwave radiation, while incoming longwave was underestimated when radiation was high. Under all-sky conditions root mean square error (RMSE) and mean bias error (MBE) were 17 to 20 W m−2 and −5 to 1 W m−2, respectively. Two attempts were made to circumvent the need of cloud cover data. First cloud fraction was parameterized as a function of the ratio, τ, of measured incoming shortwave radiation and calculated top of atmosphere radiation. Second, τ was related directly to the cloud factor (i.e. the increase in sky emissivity due to clouds). Despite large scatter between τ and both cloud fraction and the cloud factor, resulting calculations of hourly incoming longwave radiation for both approaches were only slightly more variable with RMSE roughly 3 W m−2 larger compared to using cloud observations as input. This is promising for longwave radiation modeling in areas where shortwave radiation data are available but cloud observations are not.

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Sensitivity of simulated temperature, precipitation, and global radiation to different WRF configurations over the Carpathian Basin for regional climate applications

Climate Dynamics ◽

10.1007/s00382-020-05416-x ◽

2020 ◽

Vol 55 (9-10) ◽

pp. 2849-2866

Author(s):

Ákos János Varga ◽

Hajnalka Breuer

Keyword(s):

Large Scale ◽

Regional Climate ◽

Global Radiation ◽

Wrf Model ◽

Carpathian Basin ◽

Shortwave Radiation ◽

Cold Bias ◽

Parameterization Schemes ◽

Downward Shortwave Radiation ◽

Basin Region

Abstract In this study, the Weather Research and Forecasting (WRF) model is used to produce short-term regional climate simulations with several configurations for the Carpathian Basin region. The goal is to evaluate the performance of the model and analyze its sensitivity to different physical and dynamical settings, and input data. Fifteen experiments were conducted with WRF at 10 km resolution for the year 2013. The simulations differ in terms of configuration options such as the parameterization schemes, the hydrostatic and non-hydrostatic dynamical cores, the initial and boundary conditions (ERA5 and ERA-Interim reanalyses), the number of vertical levels, and the length of the spin-up period. E-OBS dataset 2 m temperature, total precipitation, and global radiation are used for validation. Temperature underestimation reaches 4–7 °C for some experiments and can be reduced by certain physics scheme combinations. The cold bias in winter and spring is mainly caused by excessive snowfall and too persistent snow cover, as revealed by comparison with satellite-based observations and a test simulation without snow on the surface. Annual precipitation is overestimated by 0.6–3.8 mm day−1, with biases mainly accumulating in the period driven by large-scale weather processes. Downward shortwave radiation is underestimated all year except in the months dominated by locally forced phenomena (May to August) when a positive bias prevails. The incorporation of downward shortwave radiation to the validation variables increased the understanding of underlying problems with the parameterization schemes and highlighted false model error compensations.

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