scholarly journals Evaluation of Asian summer precipitation in different configurations of a high-resolution general circulation model in a range of decision-relevant spatial scales

2021 ◽  
Vol 25 (12) ◽  
pp. 6381-6405
Author(s):  
Mark R. Muetzelfeldt ◽  
Reinhard Schiemann ◽  
Andrew G. Turner ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
...  

Abstract. High-resolution general circulation models (GCMs) can provide new insights into the simulated distribution of global precipitation. We evaluate how summer precipitation is represented over Asia in global simulations with a grid length of 14 km. Three simulations were performed: one with a convection parametrization, one with convection represented explicitly by the model's dynamics, and a hybrid simulation with only shallow and mid-level convection parametrized. We evaluate the mean simulated precipitation and the diurnal cycle of the amount, frequency, and intensity of the precipitation against satellite observations of precipitation from the Climate Prediction Center morphing method (CMORPH). We also compare the high-resolution simulations with coarser simulations that use parametrized convection. The simulated and observed precipitation is averaged over spatial scales defined by the hydrological catchment basins; these provide a natural spatial scale for performing decision-relevant analysis that is tied to the underlying regional physical geography. By selecting basins of different sizes, we evaluate the simulations as a function of the spatial scale. A new BAsin-Scale Model Assessment ToolkIt (BASMATI) is described, which facilitates this analysis. We find that there are strong wet biases (locally up to 72 mm d−1 at small spatial scales) in the mean precipitation over mountainous regions such as the Himalayas. The explicit convection simulation worsens existing wet and dry biases compared to the parametrized convection simulation. When the analysis is performed at different basin scales, the precipitation bias decreases as the spatial scales increase for all the simulations; the lowest-resolution simulation has the smallest root mean squared error compared to CMORPH. In the simulations, a positive mean precipitation bias over China is primarily found to be due to too frequent precipitation for the parametrized convection simulation and too intense precipitation for the explicit convection simulation. The simulated diurnal cycle of precipitation is strongly affected by the representation of convection: parametrized convection produces a peak in precipitation too close to midday over land, whereas explicit convection produces a peak that is closer to the late afternoon peak seen in observations. At increasing spatial scale, the representation of the diurnal cycle in the explicit and hybrid convection simulations improves when compared to CMORPH; this is not true for any of the parametrized simulations. Some of the strengths and weaknesses of simulated precipitation in a high-resolution GCM are found: the diurnal cycle is improved at all spatial scales with convection parametrization disabled, the interaction of the flow with orography exacerbates existing biases for mean precipitation in the high-resolution simulations, and parametrized simulations produce similar diurnal cycles regardless of their resolution. The need for tuning the high-resolution simulations is made clear. Our approach for evaluating simulated precipitation across a range of scales is widely applicable to other GCMs.

2021 ◽  
Author(s):  
Mark R. Muetzelfeldt ◽  
Reinhard Schiemann ◽  
Andrew G. Turner ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
...  

Abstract. High-resolution general circulation models (GCMs) can provide new insights into the simulated distribution of global precipitation. We evaluate how summer precipitation is represented over Asia in global simulations with a grid length of 14 km. Three simulations were performed: one with a convection parametrization, one with convection represented explicitly by the model's dynamics, and a hybrid simulation with only shallow and mid-level convection parametrized. We evaluate the mean simulated precipitation and the diurnal cycle of the amount, frequency and intensity of the precipitation against satellite observations of precipitation from the Climate Prediction Center morphing method (CMORPH). We also compare the high-resolution simulations with coarser simulations that use parametrized convection. The simulated and observed precipitation is averaged over spatial scales defined by the hydrological catchment basins; these provide a natural spatial scale for performing decision-relevant analysis that is tied to the underlying regional physical geography. By selecting basins of different sizes, we evaluate the simulations as a function of the spatial scale. A new BAsin-Scale Model Assessment ToolkIt (BASMATI) is described, which facilitates this analysis. We find that there are strong wet biases (locally up to 72 mm day−1 at small spatial scales) in the mean precipitation over mountainous regions such as the Himalayas. The explicit convection simulation worsens existing wet and dry biases compared to the parametrized convection simulation. When the analysis is performed at different basin scales, the precipitation bias decreases as the spatial scales increase for all simulations; the lowest-resolution simulation has the smallest root mean squared error compared to CMORPH. In the simulations, a positive mean precipitation bias over China is primarily found to be due to too frequent precipitation for the parametrized convection simulation, and too intense precipitation for the explicit convection simulation. The simulated diurnal cycle of precipitation is strongly affected by the representation of convection: parametrized convection produces a peak in precipitation too close to midday over land, whereas explicit convection produces a peak that is closer to the late afternoon peak seen in observations. At increasing spatial scale, the representation of the diurnal cycle in the explicit and hybrid convection simulations improves when compared to CMORPH; this is not true for any of the parametrized simulations. Some of the strengths and weaknesses of simulated precipitation in a high-resolution GCM are found: the diurnal cycle is improved at all spatial scales with convection parametrization disabled; the interaction of the flow with orography exacerbates existing biases for mean precipitation in the high-resolution simulations; and parametrized simulations produce similar diurnal cycles regardless of their resolution. The need for tuning the high-resolution simulations is made clear. Our approach for evaluating simulated precipitation across a range of scales is widely applicable to other GCMs.


Author(s):  
Ricardo Scrosati

This study investigated the synchrony of frond dynamics among patches of the intertidal seaweed Mazzaella parksii (=M. cornucopiae; Rhodophyta: Gigartinales) at local spatial scale. At Prasiola Point (Pacific coast of Canada), the mean synchrony of the seasonal changes in frond density among seven permanent, 100-cm2 quadrats was significant (mean Pearson's r=0·73, with 0·65–0·81 as 95% confidence limits) between 1993 and 1995. This indicates that predicting seasonal trends for non-monitored patches at local spatial scale can be done relatively well based on observations on a limited number of quadrats. The identification of the spatial scales at which seaweed populations covary synchronously will permit minimizing sampling effort while retaining the ability to make valid predictions for non-monitored sites.


2017 ◽  
Vol 56 (9) ◽  
pp. 2561-2575 ◽  
Author(s):  
Aitor Atencia ◽  
Isztar Zawadzki ◽  
Marc Berenguer

AbstractThe most widely used technique for nowcasting of quantitative precipitation in operational and research centers is the Lagrangian extrapolation of the latest radar observations. However, this technique has a limited forecast skill because of the assumption made on its formulation, such as the fact that the motion vectors do not change and, even more important for convective events, neglect any growth or decay in the precipitation field. In this work, the McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) errors have been computed for 10 yr of radar composite data over the continental United States. The study of these errors shows systematic bias depending on the time of day. This effect is related to the solar cycle, whose heating energy results in an increase in the average rainfall in the afternoon. This external forcing interacts with the atmospheric system, creating local initiation and dissipation of convection depending on orography, land use, cloud coverage, etc. The signal of the diurnal cycle in MAPLE precipitation forecast has been studied in different locations and spatial scales as a function of lead time in order to recognize where, when, and for which spatial scales the signal is significant. This information has been used in the development of a scaling correction scheme where the mean errors due to the diurnal cycle are adjusted. The results show that the developed methodology improves the forecast for the spatial scales and locations where the diurnal cycle signal is significant.


2020 ◽  
Vol 35 (4) ◽  
pp. 1427-1445
Author(s):  
Ewan Short

AbstractForecasters working for Australia’s Bureau of Meteorology (BoM) produce a 7-day forecast in two key steps: first they choose a model guidance dataset to base the forecast on, and then they use graphical software to manually edit these data. Two types of edits are commonly made to the wind fields that aim to improve how the influences of boundary layer mixing and land–sea-breeze processes are represented in the forecast. In this study the diurnally varying component of the BoM’s official wind forecast is compared with that of station observations and unedited model guidance datasets. Coastal locations across Australia over June, July, and August 2018 are considered, with data aggregated over three spatial scales. The edited forecast produces a lower mean absolute error than model guidance at the coarsest spatial scale (over 50 000 km2), and achieves lower seasonal biases over all spatial scales. However, the edited forecast only reduces errors or biases at particular times and locations, and rarely produces lower errors or biases than all model guidance products simultaneously. To better understand physical reasons for biases in the mean diurnal wind cycles, modified ellipses are fitted to the seasonally averaged diurnal wind temporal hodographs. Biases in the official forecast diurnal cycle vary with location for multiple reasons, including biases in the directions that sea breezes approach coastlines, amplitude biases, and disagreement in the relative contribution of sea-breeze and boundary layer mixing processes to the mean diurnal cycle.


2019 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson

Abstract. We present multi-seasonal simulations representative of present-day and future thermodynamic environments using the global Model for Prediction Across Scales-Atmosphere (MPAS) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select ten simulation years with varying phases of El Niño-Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analysed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most of Northern Hemispheric basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemispheric phenomena, and, more generally, the utility of MPAS for studying climate change at spatial scales generally unachievable in GCMs.


2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.


2017 ◽  
Vol 47 (11) ◽  
pp. 2691-2710 ◽  
Author(s):  
Shun Ohishi ◽  
Tomoki Tozuka ◽  
Meghan F. Cronin

AbstractDetailed mechanisms for frontogenesis/frontolysis of the sea surface temperature (SST) front in the Agulhas Return Current (ARC) region are investigated using outputs from a high-resolution coupled general circulation model. The SST front is maintained throughout the year through an approximate balance between frontolysis by surface heat flux and frontogenesis by horizontal advection. Although a southward (northward) cross-isotherm flow on the northern (southern) side of the front is weaker than a strong eastward along-isotherm current in the frontal region, this cross-isotherm confluent flow advects warmer (cooler) temperature toward the SST front north (south) of the front and acts as the dominant frontogenesis mechanism. In addition, stronger (weaker) frontogenesis in austral summer (winter) is attributed to the stronger (weaker) cross-isotherm confluence, which may be linked to seasonal variations of the Agulhas Current, ARC, and Antarctic Circumpolar Current. On the other hand, the contribution from entrainment is relatively small, because frontolysis by larger (smaller) entrainment velocity on the northern (southern) side opposes frontogenesis by less (more) effective cooling associated with a thicker (thinner) mixed layer and smaller (larger) temperature difference between the mixed layer and entrained water in the northern (southern) region. To gain further insight into the time-mean cross-isotherm confluent flow in the frontal region, the vorticity balance is examined. It is shown that anticyclonic (cyclonic) vorticity advection north (south) of the front by the mean cross-isotherm confluence is in balance with the sum of cyclonic (anticyclonic) vorticity advection by the mean along-isotherm flow and cross-isotherm eddy–mean interaction.


2007 ◽  
Vol 31 (2) ◽  
pp. 179-197 ◽  
Author(s):  
J.-C. Otto ◽  
K. Kleinod ◽  
O. König ◽  
M. Krautblatter ◽  
M. Nyenhuis ◽  
...  

The analysis and interpretation of remote sensing data facilitates investigation of land surface complexity on large spatial scales. We introduce here a geometrically high-resolution data set provided by the airborne High Resolution Stereo Camera (HRSC-A). The sensor records digital multispectral and panchromatic stereo bands from which a very high-resolution ground elevation model can be produced. After introducing the basic principles of the HRSC technique and data, applications of HRSC data within the multidisciplinary Research Training Group 437 are presented. Applications include geomorphologic mapping, geomorphometric analysis, mapping of surficial grain-size distribution, rock glacier kinematic analysis, vegetation monitoring and three-dimensional landform visualization. A final evaluation of the HRSC data based on three years of multipurpose usage concludes this presentation. A combination of image and elevation data opens up various possibilities for visualization and three-dimensional analysis of the land surface, especially in geomorphology. Additionally, the multispectral imagery of the HRSC data has potential for land cover mapping and vegetation monitoring. We consider HRSC data a valuable source of high-resolution terrain information with high applicability in physical geography and earth system science.


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