scholarly journals A Comparison of Atmospheric Reanalysis Surface Products over the Ocean and Implications for Uncertainties in Air–Sea Boundary Forcing

2013 ◽  
Vol 26 (1) ◽  
pp. 153-170 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte ◽  
Gael Forget ◽  
Patrick Heimbach
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Small Time ◽  
Time Variable ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
Single Product ◽  
Common Reference ◽  
Meridional Winds ◽  
Variable Errors

Abstract This paper investigates the uncertainties related to atmospheric fields from reanalysis products used in forcing ocean models. Four reanalysis products, namely from 1) the interim ECMWF Re-Analysis (ERA-Interim), 2) version 2 of the Common Reference Ocean–Ice Experiments (CORE2), 3) the 25-Year Japanese Reanalysis Project (JRA-25), and 4) NCEP–NCAR, are evaluated against satellite-derived observations for eight different fields (zonal and meridional winds, precipitation, specific humidity, continental discharge, surface air temperature, and downwelling longwave and shortwave radiation fluxes). No single product is found to agree better in all fields with satellite-derived observations. Reanalysis products are mostly comparable to each other because of their similar physical assumptions and assimilation of common observations. Adjusted atmospheric fields from the Estimating the Circulation and Climate of the Ocean (ECCO) optimizations are also in agreement with other reanalysis products. Time-mean and time-variable errors are estimated separately and mapped globally in space, based on 14-day average fields to focus on monthly to interannual periods. Time-variable errors are larger in comparison to the signal than time-mean errors for most fields, thus justifying the need to separate them for studying uncertainties as well as formulating optimization procedures. Precipitation and wind stress fields show significant time-mean and time-variable errors whereas downwelling radiation, air temperature, and humidity fields show small time-mean errors but large time-variable errors, particularly in the tropics. Uncertainties based on evaluating multiple products presented here are considerably larger than uncertainties based on single product pairs.

scholarly journals A Comparison of Atmospheric Reanalysis Products for the Arctic Ocean and Implications for Uncertainties in Air–Sea Fluxes

2014 ◽  
Vol 27 (14) ◽  
pp. 5411-5421 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte ◽  
An T. Nguyen
Keyword(s):  
Arctic Ocean ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Specific Humidity ◽  
Shortwave Radiation ◽  
The Arctic ◽  
The Arctic Ocean ◽  
Temperature And Humidity ◽  
Meridional Winds ◽  
Similar Solutions

Abstract The uncertainties related to atmospheric fields in the Arctic Ocean from commonly used and recently available reanalysis products are investigated. Fields from the 1) ECMWF Interim Re-Analysis (ERA-Interim), 2) Common Ocean–Ice Reference Experiment version 2 (CORE2), 3) Japanese 25-yr Reanalysis Project (JRA-25), 4) NCEP–NCAR reanalysis, 5) NCEP Climate Forecast System Reanalysis (CFSR), and 6) Modern-Era Retrospective Analysis for Research and Applications (MERRA) are evaluated against satellite-derived and in situ observations for zonal and meridional winds, precipitation, specific humidity, surface air temperature, and downwelling longwave and shortwave radiation fluxes. Comparison to reference observations shows that for variables such as air temperature and humidity, all reanalysis products have similar solutions. However, other variables such as winds, precipitation, and radiation show large spreads. The magnitude of uncertainties in all fields is large when compared to the signal. Biases in Arctic cloud parameterizations and predicted temperature and humidity profiles in reanalyses as discussed in other studies are likely common sources of error that affect surface downwelling radiation, air temperature, humidity, and precipitation.

scholarly journals Spatiotemporal Characteristics of the Dominant Modes of Surface Air Temperature Interannual Variations over South China during the Spring-to-Summer Transition

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 65
Author(s):  
Fen Wang ◽  
Yaokun Li ◽  
Jianping Li
Keyword(s):  
Heat Flux ◽  
Air Temperature ◽  
South China ◽  
Surface Heat Flux ◽  
Surface Air Temperature ◽  
Surface Heat ◽  
Shortwave Radiation ◽  
Northerly Wind ◽  
The North ◽  
Land Surfaces

The surface air temperature (SAT) interannual variability during the spring-to-summer transition over South China (SC) has been decomposed into two dominant modes by applying empirical orthogonal function (EOF) analysis. The first EOF mode (EOF1) is characterized by homogenous SAT anomalies over SC, whereas the second EOF mode (EOF2) features a dipole SAT anomaly pattern with opposite anomalies south and north of the Yangtze River. A regression analysis of surface heat flux and advection anomalies on the normalized principle component time series corresponding to EOF1 suggests that surface heat flux anomalies can explain SAT anomalies mainly by modulating cloud-shortwave radiation. Negative cloud anomalies result in positive downward shortwave radiation anomalies through the positive shortwave cloud radiation effect, which favor warm SAT anomalies over most of SC. For EOF2, the distribution of advection anomalies resembles the north–south dipole pattern of SAT anomalies. This suggests that wind-induced advection plays an important role in the SAT anomalies of EOF2. Negative SAT anomalies are favored by cold advection from northerly wind anomalies over land surfaces in high-latitude regions. Positive SAT anomalies are induced by warm advection from southerly wind anomalies over the ocean in low-latitude regions.

scholarly journals Numerical Simulations of Effects of Soil Moisture and Modification by Mountains over New Zealand in Summer

2011 ◽  
Vol 139 (2) ◽  
pp. 494-510 ◽  
Author(s):  
Yang Yang ◽  
Michael Uddstrom ◽  
Mike Revell ◽  
Phil Andrews ◽  
Hilary Oliver ◽  
...  
Keyword(s):  
Soil Moisture ◽  
New Zealand ◽  
Moisture Content ◽  
Air Temperature ◽  
Land Surface ◽  
Soil Moisture Content ◽  
Surface Air Temperature ◽  
Shortwave Radiation ◽  
Lower Sensitivity ◽  
The South

Abstract Historically most soil moisture–land surface impact studies have focused on continents because of the important forecasting and climate implications involved. For a relatively small isolated mountainous landmass in the ocean such as New Zealand, these impacts have received less attention. This paper addresses some of these issues for New Zealand through numerical experiments with a regional configuration of the Met Office Unified Model atmospheric model. Two pairs of idealized simulations with only contrasting dry or wet initial soil moisture over a 6-day period in January 2004 were conducted, with one pair using realistic terrain and the other pair flat terrain. For the mean of the 6 days, the differences in the simulated surface air temperature between the dry and moist cases were 3–5 K on the leeside slopes and 1–2 K on the windward slopes and the central leeside coastal region of the South Island in the afternoon. This quite nonuniform response in surface air temperature to a uniformly distributed soil moisture content and soil type is mainly attributed to modification of the effects of soil moisture by mountains through two different processes: 1) spatial variation in cloud coverage across the mountains ranges leading to more shortwave radiation at ground surface on the leeside slope than the windward slope, and 2) the presence of a dynamically and thermally induced onshore flow on the leeside coast bringing in air with a lower sensitivity to soil moisture. The response of local winds to soil moisture content is through direct or indirect effects. The direct effect is due to the thermal contrast between land and sea/land shown for the leeside solenoidal circulations, and the indirect effect is through the weakening of the upstream blocking of the South Island for dryer soils shown by the weakening and onshore shift of the upstream deceleration and forced ascent of incoming airflow.

scholarly journals Impact of stratospheric aerosol intervention geoengineering on surface air temperature in China: A surface energy budget perspective

2021 ◽  
Author(s):  
Zhaochen Liu ◽  
Xianmei Lang ◽  
Dabang Jiang
Keyword(s):  
Spatial Pattern ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Albedo ◽  
Surface Air Temperature ◽  
Stratospheric Aerosol ◽  
Surface Energy Budget ◽  
Shortwave Radiation ◽  
Surface Cooling ◽  
Temperature Changes

Abstract. Stratospheric aerosol intervention (SAI) geoengineering is a rapid, effective, and promising means to counteract anthropogenic global warming, but the climate response to SAI, with great regional disparities, remains uncertain. In this study, we use Geoengineering Model Intercomparison Project G4 experiment simulations from three models (HadGEM2-ES, MIROC-ESM, and MIROC-ESM-CHEM) that offset anthropogenic forcing under medium-low emissions (RCP4.5) by injecting a certain amount of SO2 into the stratosphere every year, to investigate the surface air temperature response to SAI geoengineering over China. It has been shown that the SAI leads to surface cooling over China over the last 40 years of injection simulation (2030–2069), which varies among models, regions and seasons. The spatial pattern of SAI-induced temperature changes over China is mainly due to net surface shortwave radiation changes. We find that changes in solar radiation modification strength, surface albedo, atmospheric water vapor and cloudiness affect surface shortwave radiation. In summer, the increased cloud cover in some regions reduces net surface shortwave radiation, causing strong surface cooling. In winter, both the strong cooling in all three models and the abnormal warming in MIROC-ESM are related to surface albedo changes. Our results suggest that cloud and land surface processes in models may dominate the spatial pattern of SAI-induced surface air temperature changes over China.

scholarly journals Surface Air Temperature and Humidity from Intersatellite-Calibrated HIRS Measurements in High Latitudes

2012 ◽  
Vol 29 (1) ◽  
pp. 3-13 ◽  
Author(s):  
Lei Shi ◽  
Ge Peng ◽  
John J. Bates
Keyword(s):  
Air Temperature ◽  
High Latitude ◽  
Surface Air Temperature ◽  
Ocean Surface ◽  
Specific Humidity ◽  
Large Set ◽  
High Latitudes ◽  
Neural Network Approach ◽  
Temperature And Humidity ◽  
Rms Errors

Abstract High-latitude ocean surface air temperature and humidity derived from intersatellite-calibrated High-Resolution Infrared Radiation Sounder (HIRS) measurements are examined. A neural network approach is used to develop retrieval algorithms. HIRS simultaneous nadir overpass observations from high latitudes are used to intercalibrate observations from different satellites. Investigation shows that if HIRS observations were not intercalibrated, then it could lead to intersatellite biases of 1°C in the air temperature and 1–2 g kg−1 in the specific humidity for high-latitude ocean surface retrievals. Using a full year of measurements from a high-latitude moored buoy site as ground truth, the instantaneous (matched within a half-hour) root-mean-square (RMS) errors of HIRS retrievals are 1.50°C for air temperature and 0.86 g kg−1 for specific humidity. Compared to a large set of operational moored and drifting buoys in both northern and southern oceans greater than 50° latitude, the retrieval instantaneous RMS errors are within 2.6°C for air temperature and 1.4 g kg−1 for specific humidity. Compared to 5 yr of International Maritime Meteorological Archive in situ data, the HIRS specific humidity retrievals show less than 0.5 g kg−1 of differences over the majority of northern high-latitude open oceans.

scholarly journals The Met Office Operational Soil Moisture Analysis System

2020 ◽  
Vol 12 (22) ◽  
pp. 3691
Author(s):  
Breogán Gómez ◽  
Cristina L. Charlton-Pérez ◽  
Huw Lewis ◽  
Brett Candy
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Air Temperature ◽  
Land Surface ◽  
River Flow ◽  
Surface Air Temperature ◽  
Specific Humidity ◽  
Surface Data ◽  
Temperature And Humidity ◽  
Soil Wetness

In this study, the current Met Office operational land surface data assimilation system used to produce soil moisture analyses is presented. The main aim of including Land Surface Data Assimilation (LSDA) in both the global and regional systems is to improve forecasts of surface air temperature and humidity. Results from trials assimilating pseudo-observations of 1.5 m air temperature and specific humidity and satellite-derived soil wetness (ASCAT) observations are analysed. The pre-processing of all the observations is described, including the definition and construction of the pseudo-observations. The benefits of using both observations together to produce improved forecasts of surface air temperature and humidity are outlined both in the winter and summer seasons. The benefits of using active LSDA are quantified by the root mean squared error, which is computed using both surface observations and European Centre for Medium-Range Weather Forecasts (ECMWF) analyses as truth. For the global model trials, results are presented separately for the Northern (NH) and Southern (SH) hemispheres. When compared against ground-truth, LSDA in winter NH appears neutral, but in the SH it is the assimilation of ASCAT that contributes to approximately a 2% improvement in temperatures at lead times beyond 48 h. In NH summer, the ASCAT soil wetness observations degrade the forecasts against observations by about 1%, but including the screen level pseudo-observations provides a compensating benefit. In contrast, in the SH, the positive effect comes from including the ASCAT soil wetness observations, and when both observations types are assimilated there is a compensating effect. Finally, we demonstrate substantial improvements to hydrological prediction when using land surface data assimilation in the regional model. Using the Nash-Sutcliffe Efficiency (NSE) metric as an aggregated measure of river flow simulation skill relative to observations, we find that NSE was improved at 106 of 143 UK river gauge locations considered after LSDA was introduced. The number of gauge comparisons where NSE exceeded 0.5 is also increased from 17 to 28 with LSDA.

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