Near-surface Humidity Research Articles

Investigation of Urban Air Temperature and Humidity Patterns during Extreme Heat Conditions Using Satellite-Derived Data

AbstractExtreme heat is a leading cause of weather-related human mortality. The urban heat island (UHI) can magnify heat exposure in metropolitan areas. This study investigates the ability of a new MODIS-retrieved near-surface air temperature and humidity dataset to depict urban heat patterns over metropolitan Chicago, Illinois, during June–August 2003–13 under clear-sky conditions. A self-organizing mapping (SOM) technique is used to cluster air temperature data into six predominant patterns. The hottest heat patterns from the SOM analysis are compared with the 11-summer median conditions using the urban heat island curve (UHIC). The UHIC shows the relationship between air temperature (and dewpoint temperature) and urban land-use fraction. It is found that during these hottest events 1) the air temperature and dewpoint temperature over the study area increase most during nighttime, by at least 4 K relative to the median conditions; 2) the urban–rural temperature/humidity gradient is decreased as a result of larger temperature and humidity increases over the areas with greater vegetation fraction than over those with greater urban fraction; and 3) heat patterns grow more rapidly leading up to the events, followed by a slower return to normal conditions afterward. This research provides an alternate way to investigate the spatiotemporal characteristics of the UHI, using a satellite remote sensing perspective on air temperature and humidity. The technique has potential to be applied to cities globally and provides a climatological perspective on extreme heat that complements the many case studies of individual events.

Evaluation of CMIP5 climate models in simulating 1979–2005 oceanic latent heat flux over the Pacific

The climatological mean state, seasonal variation and long-term upward trend of 1979–2005 latent heat flux (LHF) in historical runs of 14 coupled general circulation models from CMIP5 (Coupled Model Intercomparison Project Phase 5) are evaluated against OAFlux (Objectively Analyzed air–sea Fluxes) data. Inter-model diversity of these models in simulating the annual mean climatological LHF is discussed. Results show that the models can capture the climatological LHF fairly well, but the amplitudes are generally overestimated. Model-simulated seasonal variations of LHF match well with observations with overestimated amplitudes. The possible origins of these biases are wind speed biases in the CMIP5 models. Inter-model diversity analysis shows that the overall stronger or weaker LHF over the tropical and subtropical Pacific region, and the meridional variability of LHF, are the two most notable diversities of the CMIP5 models. Regression analysis indicates that the inter-model diversity may come from the diversity of simulated SST and near-surface atmospheric specific humidity. Comparing the observed long-term upward trend, the trends of LHF and wind speed are largely underestimated, while trends of SST and air specific humidity are grossly overestimated, which may be the origins of the model biases in reproducing the trend of LHF.

High-frequency variability of latent-heat flux in the South China Sea

Synoptic-scale disturbances of latent-heat flux in the South China Sea are examined using Xisha automatic weather station measurements and satellite-derived daily latent heat-flux datasets. The power spectra of observations suggest a synoptic feature with a pronounced energy peak at a period of 4–8 days, comparable with the timescales of the atmospheric synoptic variabilities in the region. The characteristics of the synoptic latent-heat flux variations in summer are remarkably different from those in winter. The amplitudes of significant synoptic oscillations are about 20 and 40 W·m−2 during summer and winter monsoons, respectively. An active monsoon is clearly correlated with positive and negative phases of the synoptic latent-heat flux oscillations in the South China Sea. Using a composite analysis, some fundamental features of the synoptic latent-heat flux variabilities were revealed. In summer, the synoptic-scale latent-heat flux fluctuations are highly correlated with wind speed. While the synoptic variations of winds were removed during summer, the latent-heat anomalies precede about 1 day. In winter, however, they are primarily associated with winds and near-surface air humidity. When the synoptic oscillations of near-surface air humidity are removed, the amplitude of the composite latent-heat flux is reduced by 70%.

Numerical simulations on influence of urban land cover expansion and anthropogenic heat release on urban meteorological environment in Pearl River Delta

Urbanization is an extreme way in which human being changes the land use/land cover of the earth surface, and anthropogenic heat release occurs at the same time. In this paper, the anthropogenic heat release parameterization scheme in the Weather Research and Forecasting model is modified to consider the spatial heterogeneity of the release; and the impacts of land use change and anthropogenic heat release on urban boundary layer structure in the Pearl River Delta, China, are studied with a series of numerical experiments. The results show that the anthropogenic heat release contributes nearly 75 % to the urban heat island intensity in our studied period. The impact of anthropogenic heat release on near-surface specific humidity is very weak, but that on relative humidity is apparent due to the near-surface air temperature change. The near-surface wind speed decreases after the local land use is changed to urban type due to the increased land surface roughness, but the anthropogenic heat release leads to increases of the low-level wind speed and decreases above in the urban boundary layer because the anthropogenic heat release reduces the boundary layer stability and enhances the vertical mixing.

Revisiting the Phoenix TECP data: Implications for regolith control of near-surface humidity on Mars

We analyze the recalibrated in situ humidity measurements by the Phoenix lander, which landed at 68.2°N, 234.3°E and operated from Ls 78° through Ls 148°, ∼152 sols. Vapor pressures demonstrate significant day–night variations with values ranging from 0.005Pa to 0.37Pa, an order of magnitude lower than previously reported, and evening derived enthalpies less than that for a purely ice deposition-driven process, suggesting other water vapor sinks may contribute to the near-surface humidity at the martian polar regions.

An Improved Near-Surface Specific Humidity and Air Temperature Climatology for the SSM/I Satellite Period

AbstractA near-surface specific humidity (Qa) and air temperature (Ta) climatology on daily and 0.25° grids was constructed by the objectively analyzed air–sea fluxes (OAFlux) project by objectively merging two recent satellite-derived high-resolution analyses, the OAFlux existing 1° analysis, and atmospheric reanalyses. The two satellite products include the multi-instrument microwave regression (MIMR) Qa and Ta analysis and the Goddard Satellite-Based Surface Turbulent Fluxes, version 3 (GSSTF3), Qa analysis. This study assesses the degree of improvement made by OAFlux using buoy time series measurements at 137 locations and a global empirical orthogonal function (EOF) analysis. There are a total of 130 855 collocated daily values for Qa and 283 012 collocated daily values for Ta in the buoy evaluation. It is found that OAFlux Qa has a mean difference close to 0 and a root-mean-square (RMS) difference of 0.73 g kg−1, and Ta has a mean difference of −0.03°C and an RMS difference of 0.45°C. OAFlux shows no major systematic bias with respect to buoy measurements over all buoy locations except for the vicinity of the Gulf Stream boundary current, where the RMS difference exceeds 1.8°C in Ta and 1.2 g kg−1 in Qa. The buoy evaluation indicates that OAFlux represents an improvement over MIMR and GSSTF3. The global EOF-based intercomparison analysis indicates that OAFlux has a similar spatial–temporal variability pattern with that of three atmospheric reanalyses including MERRA, NCEP-1, and ERA-Interim, but that it differs from GSSTF3 and the Climate Forecast System Reanalysis (CFSR).

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

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.

Multi-platform Observations Characterizing the Afternoon-to-Evening Transition of the Planetary Boundary Layer in Northern Alabama, USA

Observations from the University of Alabama in Huntsville campus and ground-based scanning radar for over 140 total spring, summer, and autumn cases are studied to contribute to the relative scarcity of long-term datasets documenting the afternoon-to-evening transition of the planetary boundary layer. A sunset relative frame of reference is employed, focusing on the period 3 h before to 2 h after astronomical sunset, and several findings are consistent with previous investigations. Fluctuating components of wind and temperature computed from nearly collocated surface, Doppler wind profiler, and vertically pointing Doppler lidar measurements show a consistent decline as turbulence intensity diminishes through the transition. When normalized by their initial values, a pattern emerges: temperature variances decline slowly at first then quite abruptly after about 90 min before sunset. After the temperature variances begin to wane, vertical velocity fluctuations decrease, and the rate of their decay increases as vigorous thermal structures diminish. The fastest decline of the horizontal wind variance occurs after an accelerated vertical wind variance decrease, and the horizontal wind fluctuations display the slowest rate of decrease among these quantities. Near-surface humidity measurements show increases in mean water vapour mixing ratio as a steady rise generally beginning about 80 min prior to sunset. Composites of mean lidar vertical motion show final convective-type towers of upward motion occur about an hour before sunset and are coherent through 800 m (all heights a.g.l.). Lidar vertical motion variance at 195 m decreases by more than an order of magnitude approaching sunset, then remains below 0.01 m\(^{2}\) s\(^{-2}\) for the rest of the studied time frame. Subtle, but steady, increases in both horizontal wind speed and radar-derived horizontal wind convergence above the surface layer (at 300 m) span the entire 5-h time frame. While the convergence results show a broad range, an increase in the mean is clear and found to be statistically significant. Implications for possible transition-effect enhancements to pre-existing low-level convergence areas are briefly noted.

Investigating the role of multi-spectral and near surface temperature and humidity data to improve precipitation detection at high latitudes

Accurate estimation of global precipitation is critical for the study of the earth in a changing climate. It is generally understood that instantaneous retrieval of precipitation using microwave sensors is more accurate in the tropics and mid latitudes, but the retrievals become difficult and uncertain at higher latitude and over frozen land. In the lack of reliable microwave-based precipitation estimates at high latitudes, retrievals from a single infrared band are commonly used as an alternative to fill the missing gaps. The present study shows that multi-spectral infrared, near-surface air temperature, and near-surface humidity data can add useful information to that obtained from a single infrared band and can significantly improve delineating precipitating from non-precipitating scenes, especially at higher latitudes over land. The role of surface air temperature and humidity is found to be more effective at higher latitudes, but multispectral data is effective across all latitudes. The study is performed using 4years (2007–2010) of collocated multi-spectral data from the Moderate Resolution Imaging Spectroradiometer (MODIS), surface temperature and humidity data from the European Center for Medium Range Weather Forecast (ECMWF) analysis, and reference precipitation data from CloudSat, which can detect even very light precipitation within 80°S–80°N.

A comparison of SSM/I-derived global marine surface-specific humidity datasets

Satellite-based microwave sensors have, since the 1980s, provided a means to retrieve near-surface marine specific humidity (qa), accurate estimation of which is necessary for climate and air–sea interaction applications. Seven satellite measurement-derived monthly mean humidity datasets are compared with one another and with a dataset constructed from in situ measurements. The means, spatial and temporal structures of the datasets are shown to be markedly different, with a range of yearly, global mean qa of ∼1 g kg–1. Comparison of the datasets derived using the same satellite measurements of brightness temperature reveals differences in qa that depend on the source of satellite data; the processing and quality control applied to the data; and the algorithm used to derive qa from the satellite measurements of brightness temperature. Regional differences between satellite-derived qa due to the choice of input data, quality control and retrieval algorithm can all exceed the accuracy requirements for surface flux calculation of ∼0.3 g kg–1 and in some cases can be several g kg–1 in monthly means for some periods and regions.

Consistency of Estimated Global Water Cycle Variations over the Satellite Era

Abstract Motivated by the question of whether recent interannual to decadal climate variability and a possible “climate shift” may have affected the global water balance, we examine precipitation minus evaporation (P – E) variability integrated over the global oceans and global land for the period 1979–2010 from three points of view—remotely sensed retrievals and syntheses over the oceans, reanalysis vertically integrated moisture flux convergence (VMFC) over land, and land surface models (LSMs) forced with observations-based precipitation, radiation, and near-surface meteorology. Over land, reanalysis VMFC and P − evapotranspiration (ET) from observationally forced LSMs agree on interannual variations (e.g., El Niño/La Niña events); however, reanalyses exhibit upward VMFC trends 3–4 times larger than P − ET trends of the LSMs. Experiments with other reanalyses using reduced observations show that upward VMFC trends in the full reanalyses are due largely to observing system changes interacting with assimilation model physics. The much smaller P − ET trend in the LSMs appears due to changes in frequency and amplitude of warm events after the 1997/98 El Niño, a result consistent with coolness in the eastern tropical Pacific sea surface temperature (SST) after that date. When integrated over the global oceans, E and especially P variations show consistent signals of El Niño/La Niña events. However, at scales longer than interannual there is considerable uncertainty especially in E. This results from differences among datasets in near-surface atmospheric specific humidity and wind speed used in bulk aerodynamic retrievals. The P variations, all relying substantially on passive microwave retrievals over ocean, also have uncertainties in decadal variability, but to a smaller degree.

A Numeric Study of Regional Climate Change Induced by Urban Expansion in the Pearl River Delta, China

AbstractThe Pearl River Delta region has experienced rapid urbanization and economic development during the past 20 years. To investigate the impacts of urbanization on regional climate, the Advanced Research core of the Weather Research and Forecasting (ARW-WRF) model is used to conduct a pair of 1-yr simulations with two different representations of urbanization. Results show that the reduction in vegetated and irrigated cropland due to urban expansion significantly modifies the near-surface temperature, humidity, wind speed, and regional precipitation, which are obtained based on the significance t test of the differences between two simulations with different urbanization representations at the 95% level. Urbanization causes the mean 2-m temperature over urbanized areas to increase in all seasons (from spring to winter: 1.7° ± 0.7°C, 1.4° ± 0.3°C, 1.3° ± 0.3°, and 0.9° ± 0.4°C, respectively) and the urban diurnal temperature range decreases in three seasons and increases in one (from spring to winter: −0.5° ± 0.3°C, +0.6° ± 0.3°C, −0.4° ± 0.2°C, and −0.8° ± 0.2°C, respectively). Urbanization reduces near-surface water vapor (1.5 g kg−1 in summer and 0.4 g kg−1 in winter), 10-m wind speed (37% independent of season), and annual total precipitation days (approximately 6–14 days). However, the total rainfall amount increases by approximately 30%, since the decrease in the number of days with light rain (8–12) is overcome by the increase in the number of days of heavy or extreme rain (3–6), suggesting that urbanization induces more heavy rain events over the urban areas. Overall, the effect of urbanization on regional climate in the Pearl River Delta is found to be significant and must be considered in any broader regional climate assessment.

Impact of Land Model Calibration on Coupled Land–Atmosphere Prediction

Abstract Land–atmosphere (LA) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. In this study, the authors examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled Weather Research and Forecasting Model (WRF) forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystems in NASA's Land Information System (LIS-OPT/LIS-UE). The impact of the calibration on the 1) spinup of the land surface used as initial conditions and 2) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. In addition, the sensitivity of this approach to the period of calibration (dry, wet, or average) is investigated. Results show that the offline calibration is successful in providing improved initial conditions and land surface physics for the coupled simulations and in turn leads to systematic improvements in land–PBL fluxes and near-surface temperature and humidity forecasts. Impacts are larger during dry regimes, but calibration during either primarily wet or dry periods leads to improvements in coupled simulations due to the reduction in land surface model bias. Overall, these results provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.

Quantifying Errors due to Frequency Changes and Target Location Uncertainty for Radar Refractivity Retrievals

Abstract Radar refractivity retrievals can capture near-surface humidity changes, but noisy phase changes of the ground clutter returns limit the accuracy for both klystron- and magnetron-based systems. Observations with a C-band (5.6 cm) magnetron weather radar indicate that the correction for phase changes introduced by local oscillator frequency changes leads to refractivity errors no larger than 0.25 N units: equivalent to a relative humidity change of only 0.25% at 20°C. Requested stable local oscillator (STALO) frequency changes were accurate to 0.002 ppm based on laboratory measurements. More serious are the random phase change errors introduced when targets are not at the range-gate center and there are changes in the transmitter frequency (ΔfTx) or the refractivity (ΔN). Observations at C band with a 2-μs pulse show an additional 66° of phase change noise for a ΔfTx of 190 kHz (34 ppm); this allows the effect due to ΔN to be predicted. Even at S band with klystron transmitters, significant phase change noise should occur when a large ΔN develops relative to the reference period [e.g., ~55° when ΔN = 60 for the Next Generation Weather Radar (NEXRAD) radars]. At shorter wavelengths (e.g., C and X band) and with magnetron transmitters in particular, refractivity retrievals relative to an earlier reference period are even more difficult, and operational retrievals may be restricted to changes over shorter (e.g., hourly) periods of time. Target location errors can be reduced by using a shorter pulse or identified by a new technique making alternate measurements at two closely spaced frequencies, which could even be achieved with a dual–pulse repetition frequency (PRF) operation of a magnetron transmitter.

Validation of Satellite-Derived Daily Latent Heat Flux over the South China Sea, Compared with Observations and Five Products

Abstract This study describes the development of the South China Sea (SCS) daily satellite-derived latent heat flux (SCSSLH) for the period of 1998–2011 at 0.25° × 0.25° resolution using data mainly from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI). Flux-related variables of daily TMI data smoothed with 3-day running mean were finally chosen because of the best fit with the 1727 high-quality observations from seven moored stations and 24 ship surveys. Near-surface air specific humidity was computed using the global relationship based on satellite precipitable water. Verification against 1016 high-resolution radiosonde profiles from 1998 to 2012 and the time series from the Xisha automatic weather station during 2008–10 indicate that this satellite-derived air specific humidity can reasonably capture observed mean condition and temporal variability. They are therefore used to derive SCSSLH based on the Coupled Ocean–Atmosphere Response Experiment version 3.0 (COARE 3.0) algorithm. Compared with five other latent heat flux products—the Goddard Satellite-Based Surface Turbulent Fluxes version 2 (GSSTF2), the objectively analyzed air–sea heat fluxes (OAFlux), the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data version 3 (HOAPS3), the National Centers for Environmental Prediction/Department of Energy Global Reanalysis 2 (NCEP-2), and the European Centre for Medium-Range Weather Forecasts (ECMWF)—the daily SCSSLH shows the highest spatial resolution and realistic values in the SCS, with an exception along the northern continental shelf. More importantly, the other five products seem to overestimate the latent heat flux systematically. The flux representation in this study comes not only with a better flux algorithm but also with the improved estimates of bulk variables based on in situ measurements, which further highlights the unique role of high-quality meteorological measurements and atmospheric weather stations in evaluating the air–sea interaction in the SCS.

A Modeling Study of Irrigation Effects on Surface Fluxes and Land–Air–Cloud Interactions in the Southern Great Plains

AbstractIn this study, the authors incorporate an operational-like irrigation scheme into the Noah land surface model as part of the Weather Research and Forecasting Model (WRF). A series of simulations, with and without irrigation, is conducted over the Southern Great Plains (SGP) for an extremely dry (2006) and wet (2007) year. The results show that including irrigation reduces model bias in soil moisture and surface latent heat (LH) and sensible heat (SH) fluxes, especially during a dry year. Irrigation adds additional water to the surface, leading to changes in the planetary boundary layer. The increase in soil moisture leads to increases in the surface evapotranspiration and near-surface specific humidity but decreases in the SH and surface temperature. Those changes are local and occur during daytime. There is an irrigation-induced decrease in both the lifting condensation level (ZLCL) and mixed-layer depth. The decrease in ZLCL is larger than the decrease in mixed-layer depth, suggesting an increasing probability of shallow clouds. The simulated changes in precipitation induced by irrigation are highly variable in space, and the average precipitation over the SGP region only slightly increases. A high correlation is found among soil moisture, SH, and ZLCL. Larger values of soil moisture in the irrigated simulation due to irrigation in late spring and summer persist into the early fall, suggesting that irrigation-induced soil memory could last a few weeks to months. The results demonstrate the importance of irrigation parameterization for climate studies and improve the process-level understanding on the role of human activity in modulating land–air–cloud interactions.

Time Scales of the Trade Wind Boundary Layer Adjustment

Abstract The adjustment of the trade wind atmospheric boundary layer to an abrupt sea surface warming is investigated using a large-eddy simulation (LES) and two simple bulk models: a mixed-layer model (MLM), and a model based on the mixing-line hypothesis (XLM). The near-surface temperature adjusts in a few hours, faster than can be expected from the characteristic time scales associated with the physical processes at play. The near-surface humidity adjusts more slowly, with a time scale of about a day, and it exhibits an initial decrease before increasing to its equilibrium value. An analysis of the MLM suggests that the initial tendency of humidity and temperature results from the difference in Bowen ratios between the equilibrium and the perturbation. An analysis of the three linear modes of the XLM shows that the fastest-decaying mode adjusts the subcloud-layer buoyancy, with a constructive interaction of all of the physical processes. The second-fastest-decaying mode is an adjustment of the boundary layer thermodynamical structure and the slowest mode adjusts the boundary layer depth. Approximate analytical expressions of the time scales characterizing these linear modes are derived both for the MLM and the XLM. The MLM exhibits no scale separation between the fastest and second-fastest time scales and a scale separation between these and the slowest time scale only in the case of a shallow well-mixed boundary layer. The XLM exhibits a scale separation between the buoyancy adjustment of the subcloud layer and the overall thermodynamic adjustment, while conserving the scale separation with the slower adjustment of the boundary layer depth.

The Effect of Phase-Correlated Returns and Spatial Smoothing on the Accuracy of Radar Refractivity Retrievals

Abstract Radar refractivity retrievals have the potential to accurately capture near-surface humidity fields from the phase change of ground clutter returns. In practice, phase changes are very noisy and the required smoothing will diminish large radial phase change gradients, leading to severe underestimates of large refractivity changes (ΔN). To mitigate this, the mean refractivity change over the field (〈ΔN〉field) must be subtracted prior to smoothing. However, both observations and simulations indicate that highly correlated returns (e.g., when single targets straddle neighboring gates) result in underestimates of 〈ΔN〉field when pulse-pair processing is used. This may contribute to reported differences of up to 30 N units between surface observations and retrievals. This effect can be avoided if 〈ΔN〉field is estimated using a linear least squares fit to azimuthally averaged phase changes. Nevertheless, subsequent smoothing of the phase changes will still tend to diminish the all-important spatial perturbations in retrieved refractivity relative to 〈ΔN〉field; an iterative estimation approach may be required. The uncertainty in the target location within the range gate leads to additional phase noise proportional to ΔN, pulse length, and radar frequency. The use of short pulse lengths is recommended, not only to reduce this noise but to increase both the maximum detectable refractivity change and the number of suitable targets. Retrievals of refractivity fields must allow for large ΔN relative to an earlier reference field. This should be achievable for short pulses at S band, but phase noise due to target motion may prevent this at C band, while at X band even the retrieval of ΔN over shorter periods may at times be impossible.

Impact of a satellite-derived leaf area index monthly climatology in a global numerical weather prediction model

The leaf area index (LAI), defined as the one-sided green leaf area per unit ground area, is used in many numerical weather prediction (NWP) models as an indicator of the vegetation development state, which is of paramount importance to characterize land evaporation, photosynthesis, and carbon-uptake processes. LAI is often simply represented by lookup tables, dependent on the vegetation type and seasons. However, global LAI datasets derived from remote sensing observations have more recently become available. These products are based on sensors such as the Advanced Very High Resolution Radiometer (AVHRR) or the Moderate Resolution Imaging Spectroradiometer (MODIS), onboard polar orbiting satellites that can cover the entire globe within typically 3 days and with a spatial resolution of the order of 1 km. We examine the meteorological impact of satellite-derived LAI products on near-surface air temperature and humidity, which comes both from the stomatal transpiration of leaves and from the intercepted water on the surface of leaves, re-evaporating into the atmosphere. Two distinct monthly LAI climatology datasets derived respectively from AVHRR and MODIS sensors are tested. A set of forecasts and data assimilation experiments with the integrated forecasting system of the European Centre for Medium-range Weather Forecasts is performed with the monthly LAI climatology datasets as opposed to a vegetation-dependent constant LAI. The monthly LAI is shown to improve the forecasts of near-surface (screen-level) air temperature and relative humidity through its effect on evapotranspiration, with the largest impact obtained over needleleaf forests, crops, and grassland. At longer time-scales, the introduction of the monthly LAI is shown to have a positive impact on the model climate particularly during the boreal spring, where the LAI climatology has a large seasonal cycle.

The seasonal variability of an air-sea heat flux in the northern South China Sea

The seasonal variabilities of a latent-heat flux (LHF), a sensible-heat flux (SHF) and net surface heat flux are examined in the northern South China Sea (NSCS), including their spatial characteristics, using the in situ data collected by ship from 2006 to 2007. The spatial distribution of LHF in the NSCS is mostly controlled by wind in summer and autumn owing to the lower vertical gradient of air humidity, but is influenced by both wind and near-surface air humidity vertical gradient in spring and winter. The largest area-averaged LHF is in autumn, with the value of 197.25 W/m(2), followed by that in winter; the third and the forth are in summer and spring, respectively. The net heat flux is positive in spring and summer, so the NSCS absorbs heat; and the solar shortwave radiation plays the most important role in the surface heat budget. In autumn and winter, the net heat flux is negative in most of the observation region, so the NSCS loses heat; and the LHF plays the most important role in the surface heat budget. The net heating is mainly a result of the offsetting between heating due to the shortwave radiation and cooling due to the LHF and the upward (outgoing) long wave radiation, since the role of SHF is negligible. The ratio of the magnitudes of the three terms (shortwave radiation to LHF to long-wave radiation) averaged over the entire year is roughly 3:2:1, and the role of SHF is the smallest.