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

2007 ◽  
Vol 8 (4) ◽  
pp. 642-664 ◽  
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.

Spurious Grid-Scale Precipitation in the North American Regional Reanalysis

2007 ◽  
Vol 135 (6) ◽  
pp. 2168-2184 ◽  
Author(s):  
Gregory L. West ◽  
W. James Steenburgh ◽  
William Y. Y. Cheng
Keyword(s):  
North American ◽  
Prediction Models ◽  
Weather Prediction ◽  
Regional Climate ◽  
Potential Temperature ◽  
Climate Data ◽  
The North ◽  
North American Regional Reanalysis ◽  
Upper Level ◽  
Regional Reanalysis

Abstract Spurious grid-scale precipitation (SGSP) occurs in many mesoscale numerical weather prediction models when the simulated atmosphere becomes convectively unstable and the convective parameterization fails to relieve the instability. Case studies presented in this paper illustrate that SGSP events are also found in the North American Regional Reanalysis (NARR) and are accompanied by excessive maxima in grid-scale precipitation, vertical velocity, moisture variables (e.g., relative humidity and precipitable water), mid- and upper-level equivalent potential temperature, and mid- and upper-level absolute vorticity. SGSP events in environments favorable for high-based convection can also feature low-level cold pools and sea level pressure maxima. Prior to 2003, retrospectively generated NARR analyses feature an average of approximately 370 SGSP events annually. Beginning in 2003, however, NARR analyses are generated in near–real time by the Regional Climate Data Assimilation System (R-CDAS), which is identical to the retrospective NARR analysis system except for the input precipitation and ice cover datasets. Analyses produced by the R-CDAS feature a substantially larger number of SGSP events with more than 4000 occurring in the original 2003 analyses. An oceanic precipitation data processing error, which resulted in a reprocessing of NARR analyses from 2003 to 2005, only partially explains this increase since the reprocessed analyses still produce approximately 2000 SGSP events annually. These results suggest that many NARR SGSP events are not produced by shortcomings in the underlying Eta Model, but by the specification of anomalous latent heating when there is a strong mismatch between modeled and assimilated precipitation. NARR users should ensure that they are using the reprocessed NARR analyses from 2003 to 2005 and consider the possible influence of SGSP on their findings, particularly after the transition to the R-CDAS.

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

2019 ◽  
Vol 20 (3) ◽  
pp. 467-487 ◽  
Author(s):  
David M. W. Pritchard ◽  
Nathan Forsythe ◽  
Hayley J. Fowler ◽  
Greg M. O’Donnell ◽  
Xiao-Feng Li
Keyword(s):  
Regional Climate ◽  
Critical Role ◽  
Critical Evaluation ◽  
Longwave Radiation ◽  
Indus Basin ◽  
Shortwave Radiation ◽  
Cold Bias ◽  
Near Surface ◽  
High Asia ◽  
High Bias

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.

The Sensitivity of Springtime Arctic Mixed-Phase Stratocumulus Clouds to Surface-Layer and Cloud-Top Inversion-Layer Moisture Sources

2014 ◽  
Vol 71 (2) ◽  
pp. 574-595 ◽  
Author(s):  
Amy Solomon ◽  
Matthew D. Shupe ◽  
Ola Persson ◽  
Hugh Morrison ◽  
Takanobu Yamaguchi ◽  
...  
Keyword(s):  
Surface Layer ◽  
Mixed Layer ◽  
Inversion Layer ◽  
Single Layer ◽  
Mixed Phase ◽  
Specific Humidity ◽  
Cloud System ◽  
Energy Budgets ◽  
Quasi Equilibrium ◽  
Near Surface

Abstract In this study, a series of idealized large-eddy simulations is used to understand the relative impact of cloud-top and subcloud-layer sources of moisture on the microphysical–radiative–dynamical feedbacks in an Arctic mixed-phase stratocumulus (AMPS) cloud system. This study focuses on a case derived from observations of a persistent single-layer AMPS cloud deck on 8 April 2008 during the Indirect and Semi-Direct Aerosol Campaign near Barrow, Alaska. Moisture and moist static energy budgets are used to examine the potential impact of ice in mixed-phase clouds, specific humidity inversions coincident with temperature inversions as a source of moisture for the cloud system, and the presence of cloud liquid water above the mixed-layer top. This study demonstrates that AMPS have remarkable insensitivity to changes in moisture source. When the overlying air is dried initially, radiative cooling and turbulent entrainment increase moisture import from the surface layer. When the surface layer is dried initially, the system evolves to a state with reduced mixed-layer water vapor and increased surface-layer moisture, reducing the loss of water through precipitation and entrainment of near-surface air. Only when moisture is reduced both above and below the mixed layer does the AMPS decay without reaching a quasi-equilibrium state. A fundamental finding of this study is that, with or without cloud ice and with or without a specific humidity inversion, the cloud layer eventually extends into the temperature inversion producing a precipitation flux as a source of water into the mixed layer.

Relationships between Land Surface and Near-Surface Atmospheric Variables in the NCEP North American Regional Reanalysis

2007 ◽  
Vol 8 (6) ◽  
pp. 1184-1203 ◽  
Author(s):  
Yan Luo ◽  
Ernesto H. Berbery ◽  
Kenneth E. Mitchell ◽  
Alan K. Betts
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
Land Surface ◽  
Cloud Cover ◽  
Near Surface ◽  
Positive Correlation ◽  
Precipitation Anomalies ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis ◽  
Atmospheric Variables

Abstract This study examines the recently released National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) products over diverse climate regimes to determine the regional relationships between soil moisture and near-surface atmospheric variables. NARR assimilates observed precipitation, as well as near-surface observations of humidity and wind, while seeking a balance of the surface water and energy budgets with a modern land surface model. The results of this study indicate that for most basins (of approximate size of 0.5–1.0 × 106 km2) the NARR surface water budgets have relatively small residuals (about 0.2 mm day−1), and slightly larger residuals (about 0.4 mm day−1) for basins with complex terrain like those in the western United States. Given that the NARR is an assimilation system (especially one that assimilates observed precipitation), the NARR does not include feedbacks between soil moisture and precipitation. Nonetheless, as a diagnostic tool anchored to observations, the NARR does show that the extent of positive correlation between anomalies of soil moisture and anomalies of precipitation in a given region depends on that region’s dryness. The existence of correlations among all variables is a necessary—but not sufficient—condition for land–atmosphere feedbacks to exist, as a region with no correlations would not be expected to have feedbacks. Likewise, a high degree of persistence of soil moisture anomalies in a given basin does not by itself guarantee a positive correlation between anomalies of soil moisture and precipitation. Land surface–atmosphere relationships at monthly time scales are identified by examining the associations between soil moisture and surface and boundary layer variables. Low soil moisture is consistently associated with increased net shortwave radiation and increased outgoing longwave radiation through the effects of less cloud cover and lower atmospheric humidity. No systematic association is revealed between soil moisture and total net surface radiation, as this relation varies substantially between different basins. Low soil moisture is positively correlated with increased sensible heat and lower latent heat (reflected in a smaller evaporative fraction), decreased low-cloud cover, and higher lifting condensation level. The relation between soil moisture anomalies and precipitation anomalies is found to be quite variable between the basins, depending on whether availability of surface water exceeds the available energy for evaporation, or vice versa. Wetter basins, like the Columbia and Ohio, display weak or no correlations between soil moisture anomalies and precipitation anomalies. On the other hand, transitional regions between wet and dry regions, like the central Great Plains, manifest a positive correlation between soil moisture anomalies and precipitation anomalies. These results further the understanding of previous predictability studies (in coupled land–atmosphere prediction models), which indicates that in order for precipitation anomalies to emerge in response to soil moisture anomalies in a given region, it is necessary that the region’s seasonal climate be neither too dry nor too wet.

scholarly journals MSWX: global 3-hourly 0.1° bias-corrected meteorological data including near real-time updates and forecast ensembles

2021 ◽  
pp. 1-55
Author(s):  
Hylke E. Beck ◽  
Albert I.J.M. van Dijk ◽  
Pablo R. Larraondo ◽  
Tim R. McVicar ◽  
Ming Pan ◽  
...  
Keyword(s):  
Real Time ◽  
Long Range ◽  
Air Temperature ◽  
Hydrological Modeling ◽  
Meteorological Data ◽  
Longwave Radiation ◽  
Cumulative Distribution ◽  
Specific Humidity ◽  
Near Surface ◽  
Medium Range

AbstractWe present Multi-Source Weather (MSWX), a seamless global gridded near-surface meteorological product featuring a high 3-hourly 0.1° resolution, near real-time updates (~3-hour latency), and bias-corrected medium-range (up to 10 days) and long-range (up to 7 months) forecast ensembles. The product includes ten meteorological variables: precipitation, air temperature, daily minimum and maximum air temperature, surface pressure, relative and specific humidity, wind speed, and downward shortwave and longwave radiation. The historical part of the record starts January 1, 1979, and is based on ERA5 data bias-corrected and downscaled using high-resolution reference climatologies. The data extension to within ~3 hours of real-time is based on analysis data from GDAS. The 30-member medium-range forecast ensemble is based on GEFS and updated daily. Finally, the 51-member long-range forecast ensemble is based on SEAS5 and updated monthly. The near real-time and forecast data are statistically harmonized using running-mean and cumulative distribution function-matching approaches to obtain a seamless record covering 1979 to 7 months from now. MSWX presents new and unique opportunities for hydrological modeling, climate analysis, impact studies, and monitoring and forecasting of droughts, floods, and heatwaves (within the bounds of the caveats and limitations discussed herein). The product is available at www.gloh2o.org/mswx.

scholarly journals Atmospheric energy budget response to idealized aerosol perturbation in tropical cloud systems

2019 ◽  
Author(s):  
Guy Dagan ◽  
Philip Stier ◽  
Matthew Christensen ◽  
Guido Cioni ◽  
Daniel Klocke ◽  
...  
Keyword(s):  
Energy Budget ◽  
Sensible Heat Flux ◽  
Surface Air Temperature ◽  
Longwave Radiation ◽  
Cloud Droplet ◽  
Near Surface ◽  
Cloud Systems ◽  
Atmospheric Energy ◽  
Convective Clouds ◽  
Aerosol Effects

Abstract. The atmospheric energy budget is analysed in numerical simulations of tropical cloud systems. This is done in order to better understand the physical processes behind aerosol effects on the atmospheric energy budget. The simulations include both shallow convective clouds and deep convective tropical clouds over the Atlantic Ocean. Two different sets of simulations, at different dates (10–12/8/2016 and 16–18/8/2016), are being simulated with different dominant cloud modes (shallow or deep). For each case, the cloud droplet number concentrations (CDNC) is varied as a proxy for changes in aerosol concentrations. It is shown that the total column atmospheric radiative cooling is substantially reduced with CDNC in the deep-cloud dominated case (by ~ 10.0 W/m2), while a much smaller reduction (~ 1.6 W/m2) is shown in the shallow-cloud dominated case. This trend is caused by an increase in the ice and water vapor content at the upper troposphere that leads to a reduced outgoing longwave radiation. A decrease in sensible heat flux (driven by increase in the near surface air temperature) reduces the warming by ~ 1.4 W/m2 in both cases. It is also shown that the cloud fraction response behaves in opposite ways to an increase in CDNC, showing an increase in the deep-cloud dominated case and a decrease in the shallow-cloud dominated case. This demonstrates that under different environmental conditions the response to aerosol perturbation could be different.

Stratospheric and Tropospheric Flux Contributions to the Polar Cap Energy Budgets

2021 ◽  
pp. 1-49
Author(s):  
Christopher J. Cardinale ◽  
Brian E. J. Rose ◽  
Andrea L. Lang ◽  
Aaron Donohoe
Keyword(s):  
Energy Budget ◽  
Vertical Structure ◽  
Lower Troposphere ◽  
Longwave Radiation ◽  
Surface Energy Budget ◽  
The Arctic ◽  
Energy Budgets ◽  
Polar Regions ◽  
Static Energy ◽  
Arctic Surface

AbstractThe flux of moist static energy into the polar regions plays a key role in the energy budget and climate of the polar regions. While usually studied from a vertically integrated perspective (Fwall), this analysis examines its vertical structure, using the NASA-MERRA-2 reanalysis to compute climatological and anomalous fluxes of sensible, latent, and potential energy across 70°N and 65°S for the period 1980–2016. The vertical structure of the climatological flux is bimodal, with peaks in the mid- to lower-troposphere and mid- to upper-stratosphere. The near zero flux at the tropopause defines the boundary between stratospheric (Fstrat) and tropospheric (Ftrop) contributions to Fwall. Especially at 70°N, Fstrat is found to be important to the climatology and variability of Fwall, contributing 20.9 Wm−2 to Fwall (19% of Fwall) during the winter and explaining 23% of the variance of Fwall. During winter, an anomalous poleward increase in Fstrat preceding a sudden stratospheric warming is followed by an increase in outgoing longwave radiation anomalies, with little influence on the surface energy budget of the Arctic. Conversely, a majority of the energy input by an anomalous poleward increase in Ftrop goes toward warming the Arctic surface. Ftrop is found to be a better metric than Fwall for evaluating the influence of atmospheric circulations on the Arctic surface climate.

scholarly journals The MAGS Water and Energy Budget Study

2008 ◽  
Vol 9 (1) ◽  
pp. 96-115 ◽  
Author(s):  
K. K. Szeto ◽  
H. Tran ◽  
M. D. MacKay ◽  
R. Crawford ◽  
R. E. Stewart
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Regional Analysis ◽  
Moisture Flux ◽  
Northern Region ◽  
Energy Budgets ◽  
Weather Forecasts ◽  
Energy Cycle ◽  
Regional Reanalysis ◽  
Environmental Prediction

Abstract This study represents the first attempt at developing a comprehensive climatology of atmospheric and surface water and energy budgets for the Mackenzie River basin (MRB). Different observed, remotely sensed, (re)analyzed, and modeled datasets were used to obtain independent estimates of the budgets. In particular, assimilated datasets, including the National Centers for Environmental Prediction Global Reanalysis 2 (NCEP-R2), the global 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-40), the NCEP North American Regional Reanalysis (NARR), and the Canadian Meteorological Centre (CMC) operational regional analysis as well as results from the Canadian Regional Climate Model (CRCM) simulations, are used in the study. Apart from the development of state-of-the-art budget estimates for the MRB, the relative merits of current models, data assimilation systems, and global blended datasets in representing aspects of the water and energy cycle of this northern and data-sparse region were also assessed. In addition, the levels of uncertainty in assessing the budgets as well as their sources are discussed. The regional water budget for the MRB is closed within 10% of the observed runoff by using the moisture flux convergence from ERA-40, NARR, CMC, or CRCM. While these are noted improvements over previous water closure assessments for the region, magnitudes of the residuals in balancing the budgets are often comparable to the budget terms themselves in all the model and analysis datasets, and the spreads of budget estimates from the different datasets are also typically large, suggesting that substantial improvements to the models and observations are needed before the assessments of water and energy budgets for this northern region can be vastly improved.

scholarly journals A Comparison of Intra-Annual and Long-Term Trend Scaling of Extreme Precipitation with Temperature in a Large-Ensemble Regional Climate Simulation

2020 ◽  
Vol 33 (21) ◽  
pp. 9233-9245
Author(s):  
Qiaohong Sun ◽  
Francis Zwiers ◽  
Xuebin Zhang ◽  
Guilong Li
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Data Availability ◽  
Climate Simulation ◽  
Large Ensemble ◽  
Near Surface ◽  
High Background

AbstractLong-term changes in extreme daily and subdaily precipitation simulated by climate models are often compared with corresponding temperature changes to estimate the sensitivity of extreme precipitation to warming. Such “trend scaling” rates are difficult to estimate from observations, however, because of limited data availability and high background variability. Intra-annual temperature scaling (here called binning scaling), which relates extreme precipitation to temperature at or near the time of occurrence, has been suggested as a possible substitute for trend scaling. We use a large ensemble simulation of the Canadian regional climate model (CanRCM4) to assess this possibility, considering both daily near-surface air temperature and daily dewpoint temperature as scaling variables. We find that binning curves that are based on precipitation data for the whole year generally look like the composite of binning curves for winter and summer, with the lower temperature portion similar to winter and the higher temperature portion similar to summer, indicating that binning curves reflect seasonal changes in the relationship between temperature and extreme precipitation. The magnitude and spatial pattern of binning and trend scaling rates are also quantitatively different, with little spatial correlation between them, regardless of precipitation duration or choice of temperature variable. The evidence therefore suggests that binning scaling with temperature is not a reliable predictor for future changes in precipitation extremes in the climate simulated by CanRCM4. Nevertheless, external forcing does have a discernable influence on binning curves, which are seen to shift upward and to the right in some regions, consistent with a general increase in extreme precipitation.

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