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

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.

2020 ◽  
Vol 12 (22) ◽  
pp. 3691
Author(s):  
Breogán Gómez ◽  
Cristina L. Charlton-Pérez ◽  
Huw Lewis ◽  
Brett Candy

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.


2014 ◽  
Vol 27 (14) ◽  
pp. 5411-5421 ◽  
Author(s):  
Ayan H. Chaudhuri ◽  
Rui M. Ponte ◽  
An T. Nguyen

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.


2008 ◽  
Vol 21 (22) ◽  
pp. 5807-5819 ◽  
Author(s):  
Hengchun Ye

Abstract Potential benefits or disadvantages of increasing precipitation in high-latitude regions under a warming climate are dependent on how and in what form the precipitation occurs. Precipitation frequency and type are equally as important as quantity and intensity to understanding the seasonality of hydrological cycles and the health of the ecosystem in high-latitude regions. This study uses daily historical synoptic observation records during 1936–90 over the former USSR to reveal associations between the frequency of precipitation types (rainfall, snowfall, mixed solid and liquid, and wet days of all types) and surface air temperatures to determine potential changes in precipitation characteristics under a warming climate. Results from this particular study show that the frequency of precipitation of all types generally increases with air temperature during winter. However, both solid and liquid precipitation days predominantly decrease with air temperature during spring with a reduction in snowfall days being most significant. During autumn, snowfall days decrease while rainfall days increase resulting in overall decreases in wet days as air temperature increases. The data also reveal that, as snowfall days increase in relationship to increasing air temperatures, this increase may level out or even decrease as mean surface air temperature exceeds −8°C in winter. In spring and autumn, increasing rainfall days switch to decreasing when the mean surface air temperature goes above 6°C. The conclusion of this study is that changes in the frequency of precipitation types are highly dependent on the location’s air temperature and that threshold temperatures exist beyond which changes in an opposite direction occur.


2011 ◽  
Vol 11 (1) ◽  
pp. 39-52
Author(s):  
C. M. Hall ◽  
G. Hansen ◽  
F. Sigernes ◽  
K. M. Kuyeng Ruiz

Abstract. We present a seasonal climatology of tropopause altitude for 78° N 16° E derived from observations 2007–2010 by the SOUSY VHF radar on Svalbard. The spring minimum occurs one month later than that of surface air temperature and instead coincides with the maximum in ozone column density. This confirms similar studies based on radiosonde measurements in the arctic and demonstrates downward control by the stratosphere. If one is to exploit the potential of tropopause height as a metric for climate change at high latitude and elsewhere, it is imperative to observe and understand the processes which establish the tropopause – an understanding to which this study contributes.


2019 ◽  
Vol 53 (3-4) ◽  
pp. 1805-1821 ◽  
Author(s):  
Shangfeng Chen ◽  
Renguang Wu ◽  
Linye Song ◽  
Wen Chen

2019 ◽  
Vol 32 (24) ◽  
pp. 8537-8561 ◽  
Author(s):  
Jiao Chen ◽  
Aiguo Dai ◽  
Yaocun Zhang

Abstract Increases in atmospheric greenhouse gases will not only raise Earth’s temperature but may also change its variability and seasonal cycle. Here CMIP5 model data are analyzed to quantify these changes in surface air temperature (Tas) and investigate the underlying processes. The models capture well the mean Tas seasonal cycle and variability and their changes in reanalysis, which shows decreasing Tas seasonal amplitudes and variability over the Arctic and Southern Ocean from 1979 to 2017. Daily Tas variability and seasonal amplitude are projected to decrease in the twenty-first century at high latitudes (except for boreal summer when Tas variability increases) but increase at low latitudes. The day of the maximum or minimum Tas shows large delays over high-latitude oceans, while it changes little at low latitudes. These Tas changes at high latitudes are linked to the polar amplification of warming and sea ice loss, which cause larger warming in winter than summer due to extra heating from the ocean during the cold season. Reduced sea ice cover also decreases its ability to cause Tas variations, contributing to the decreased Tas variability at high latitudes. Over low–midlatitude oceans, larger increases in surface evaporation in winter than summer (due to strong winter winds, strengthened winter winds in the Southern Hemisphere, and increased winter surface humidity gradients over the Northern Hemisphere low latitudes), coupled with strong ocean mixing in winter, lead to smaller surface warming in winter than summer and thus increased seasonal amplitudes there. These changes result in narrower (wider) Tas distributions over the high (low) latitudes, which may have important implications for other related fields.


2015 ◽  
Vol 28 (15) ◽  
pp. 5908-5921 ◽  
Author(s):  
Cheng Qian ◽  
Xuebin Zhang

Abstract The annual cycle is the largest variability for many climate variables outside the tropics. Whether human activities have affected the annual cycle at the regional scale is unclear. In this study, long-term changes in the amplitude of surface air temperature annual cycle in the observations are compared with those simulated by the climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Different spatial domains ranging from hemispheric to subcontinental scales in mid- to high-latitude land areas for the period 1950–2005 are considered. Both the optimal fingerprinting and a nonoptimal detection and attribution technique are used. The results show that the space–time pattern of model-simulated responses to the combined effect of anthropogenic and natural forcings is consistent with the observed changes. In particular, models capture not only the decrease in the temperature seasonality in the northern high latitudes and East Asia, but also the increase in the Mediterranean region. A human influence on the weakening in the temperature seasonality in the Northern Hemisphere is detected, particularly in the high latitudes (50°–70°N) where the influence of the anthropogenic forcing can be separated from that of the natural forcing.


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