STATE OF THE CLIMATE IN 2009

More documents

Recommendations

Info

USING SI-TRACABLE GLOBAL POSITIONING SYSTEM RADIOOCCULATION MEASUREMENTS FOR CLIMATE MONITORING—S-P. Ho, Y.-H. Kuo, W. Schreiner, and X. ZhouGlobal Positioning System(GPS) Radio Occultation(RO) data are an importantcomponent of the evolvingglobal observing system (NRC2007; WMO 2007; GCOS2004). GPS-RO is the onlyself-calibrated observing techniquefrom space whereby itsfundamental measurement istraceable to the internationalsystem of units (SI) (SI traceability;Ohring 2007). GPSreceivers on low-Earth orbiting(LEO) satellites receivemeasurable radio frequencysignals transmitted from GPSsatellites; monitoring and corrections from a series ofatomic clocks allows the signal timing to be traced to theSI second with a high degree of accuracy. Significant advantagesof SI-traceable GPS-RO observations for climatemonitoring include: (i) no satellite-to-satellite bias (Hajjet al. 2004; Ho et al. 2009a); (ii) great precision (Antheset al. 2008; Foelsche et al. 2009; Ho et al. 2009a); and (iii)no synoptic sampling bias (cloud/precipitation effects).Raw RO observations and precise positions and velocitiesof GPS and LEO satellites, can be used to deriveatmospheric temperature and moisture profiles (Hajjet al. 2004; Kuo et al. 2004; Ho et al. 2009b). GPS-ROtemperature can be validated by comparing temperaturemeasurements from FORMOSAT-3/ COSMIC with highquality radiosonde measurements. With a uniform distributionof COSMIC RO data in time and space (~2500profiles per day, Fig. 2.22), more than 10 000 collocationsof Vaisala-RS92 radiosonde and COSMIC data within2 hours and 300 km exist (Fig. 2.23). The precision ofCOSMIC derived temperature profiles is estimated to bebetter than 0.05 K from 8 km to 30 km (Ho et al. 2009a);COSMIC temperature is very close to radiosondes from200 hPa to 20 hPa (around 12 km to 25 km). Because thequality of RO data does not vary with location and time,it is very useful for assessing systematic errors in differentradiosonde sensors (e.g., He et al. 2009; Kuo et al.2005; Elliott and Gaffen 1991; Luers and Eskridge 1998).Radiative temperature biases that vary during the day andnight can be identified for different radiosonde sensorFig. 2.22. Typical operational distribution of COSMIC GPS radio occultationsoundings (green dots) over a 24-hr period across the globe. Red dots are locationsof operational radiosonde stations.Fig. 2.23. Temperature comparisons between COS-MIC and radiosonde Vaisala-RS92 in 2007. Mean bias,absolute mean bias and mean standard deviation arecomputed from 200 hPa to 10 hPa. The red line is themean difference, the blue line is the standard deviation,and the dotted line is the sample number for RO andradiosonde pairs in that height (upper horizontal axis).S36 | juNE 2010
types when comparing with collocatedCOSMIC RO soundings (He et al. 2009).The upper troposphere and lowerstratosphere (UT/LS) is a critical regionfor understanding the radiativebalance of the climate system and climateprocesses. However, due to poorvertical resolution and/or fundamentalmeasurement uncertainty, most in situand satellite sounder measurements ofmeteorological parameters in this regionare not suitable for climate monitoring(Karl et al. 2006). The very high precisionand vertical resolution (from ~60m near the surface to ~1.5 km at 40km) of GPS-RO data makes them verysuitable to detect changes in UT/LS temperature (Hoet al. 2007), tropopause height, and the distribution ofdouble tropopauses (Randel et al. 2007). Because GPS-ROdata are not affected by on-orbit heating and cooling ofsatellite components, they are veryuseful for identifying the time/locationdependent biases of microwavesounders (Ho et al. 2009c), makingthem potentially useful as a climatebenchmark (Ho et al. 2009a) in additionto being well suited to detectclimate trends (Ho et al. 2009b;Ringer and Healy 2008).Using refractivity data and reasonablyindependent temperatureprofiles, highly precise COSMICwater vapor profiles can be derived.Comparisons of total-column watervapor (TCWV) from COSMIC withthose derived from ground-basedGPS (i.e., International Global NavigationSatellite Systems—IGS, Wanget al. 2007) show that the meanglobal difference between IGS andCOSMIC TCWV is about -0.2 mmwith a standard deviation of 2.7 mm(Fig. 2.24).Fig. 2.24. Global comparisons of TCWV between COSMIC andthose derived from ground-based GPS (i.e., IGS) for 2008.STATE OF THE CLIMATE IN 2009 juNE 2010 |S37
Page 8 and 9: Luo, Jing-Jia, Research Institute f
Page 10 and 11: Tedesco, Marco, Department Earth an
Page 12 and 13: 4. THE TROPICS.....................
Page 14 and 15: ABSTRACT—M. O. Baringer, D. S. Ar
Page 16 and 17: I. INTRODUCTION—M. O. Baringer an
Page 18 and 19: Table 1.1 The GCOS Essential Climat
Page 20 and 21: S18 | juNE 2010
Page 22 and 23: Stratospheric TemperatureCloudiness
Page 25: Source Datasets Sectionhttp://www.p
Page 28 and 29: HOW do WE KNOW THE WORLD HAS WARMED
Page 30 and 31: Fig. 2.6. As for Fig. 2.1 but for l
Page 32 and 33: Fig. 2.10. Change in TCWV from 2008
Page 34 and 35: Precipitation anomalies in 2009, ov
Page 36 and 37: Fig. 2.18. Seasonal SCE anomalies (
Page 40 and 41: 6) Lake levels—C. BirkettLake vol
Page 42 and 43: Fig. 2.30. (a) The daily AO index f
Page 45 and 46: (C) Carbon monoxide (CO)There has b
Page 47 and 48: Table 2.5. Mixing ratios, radiative
Page 50 and 51: the mid-1990s but has since levelle
Page 52 and 53: with all 42 glaciers observed retre
Page 54 and 55: of 0.1° and 5 days (Kaiser et al.
Page 56 and 57: Fig. 3.1. (a) Yearly mean SSTAs in
Page 58 and 59: (Fig. 3.3c). It is interesting that
Page 60 and 61: strong there, consistent with anoma
Page 62 and 63: cont'RECENT ADVANCES IN OUR UNDERST
Page 64 and 65: is to cause SST to rise if oceanic
Page 66 and 67: egions around the subtropical salin
Page 68 and 69: Fig 3.17. Principal empirical ortho
Page 70 and 71: Fig. 3.19. Daily estimates of the s
Page 72 and 73: Fig. 3.22. (top) The 2009 SSH anoma
Page 74 and 75: to update the CO 2climatology, ther
Page 76 and 77: µmol kg -1 or about half of the ac
Page 78 and 79: Fig. 3.31. (a) Average MODIS-Aqua C
Page 80 and 81: latitudes, chlorophyll and thermal
Page 83 and 84: Fig. 4.4. (a) Anomalous 850-hPa win
Page 85 and 86: (Fig. 4.6). These include four MJO
Page 87 and 88: Fig. 4.8. NOAA’s ACE index expres
Page 89 and 90:
Fig. 4.14. ASO 2009: Anomalous 200-
Page 91 and 92:
Fig. 4.17. The tracks of all TCs th
Page 93 and 94:
Several previous studies have shown
Page 95 and 96:
followed by TY Linfa and TS Nangka
Page 97 and 98:
The Philippines were severely affec
Page 99 and 100:
The historical SIO TC data is proba
Page 101 and 102:
Fig. 4.26. Global anomalies of TCHP
Page 103 and 104:
degree resolution NASA TRMM rainfal
Page 105 and 106:
F i g. 4.32 . TRMM (a) mean and (b)
Page 107 and 108:
THE forgotten sub-BASIN—THE centr
Page 109 and 110:
5. THE ARCTIC—J. Richter-Menge, E
Page 111 and 112:
and North America (south of 55° la
Page 113 and 114:
Fig. 5.8. 2007-09 Atlantic water la
Page 115 and 116:
d. Sea ice cover—D. Perovich, R.
Page 117 and 118:
e. Land1) Vegetation—D. A. Walker
Page 119 and 120:
Fig. 5.18. Total annual river disch
Page 121 and 122:
negative SCD anomalies were evident
Page 123 and 124:
with records beginning in 1873, the
Page 125 and 126:
(QuikSCAT, 2000-09) microwave remot
Page 127 and 128:
6. ANTARCTICAa. Overview—R. L. Fo
Page 129 and 130:
(SCAR) report ‘Antarctic Climate
Page 131 and 132:
these stations in April, August, an
Page 133 and 134:
e. 2008-2009 Seasonal melt extent a
Page 135 and 136:
positive ice-season duration anomal
Page 137 and 138:
7. REGIONAL CLIMATESa. Introduction
Page 139 and 140:
first half of the year (January-Jun
Page 141 and 142:
its second wettest such period. Sev
Page 143 and 144:
California began the year with mode
Page 145 and 146:
The first drought occurred in March
Page 147 and 148:
Fig. 7.8. (a) Annual mean temperatu
Page 149 and 150:
Fig. 7.11. (a) Annual mean temperat
Page 151 and 152:
EXTREME rainfall and the flood of t
Page 153 and 154:
Fig. 7.14. Composite for standardiz
Page 155 and 156:
Fig. 7.17. Daily maximum temperatur
Page 157 and 158:
(ii) PrecipitationDecember to Febru
Page 159 and 160:
For Zimbabwe, the rainfall season,
Page 161 and 162:
Fig. 7.28. Annual mean temperature
Page 163 and 164:
Fig. 7.31. Seasonal anomalies (1961
Page 165 and 166:
(1706-2009), and new national recor
Page 167 and 168:
cold in southern and central Finlan
Page 169 and 170:
EXCEPTIONAL storm strikes northern
Page 171 and 172:
7.32b). April was particularly mild
Page 173 and 174:
to -44 о С) persisted in southern
Page 175 and 176:
Fig. 7.39. Weather conditions in De
Page 177 and 178:
on the 1971-2000 climatology) for a
Page 179 and 180:
excess rainfall, while 11 subdivisi
Page 181 and 182:
4) Southwest Asia(i) Iraq—M. Roge
Page 183 and 184:
Wales. The warmth was particularly
Page 185 and 186:
The most significant severe thunder
Page 187 and 188:
mm thick, which fell on parts of No
Page 189 and 190:
and Vanua Levu islands (Fiji) as a
Page 191 and 192:
Table 7.5. Maximum temperature anom
Page 193 and 194:
8. SEASONAL SUMMARIES—Mike Halper
Page 195 and 196:
Fig. 8.5. Jun-Aug 2009 (top) surfac
Page 197 and 198:
ACKNOWLEDGMENTSIn addition to the m
Page 199 and 200:
CFCCFC-11CFC-12CH 4Chl satCIIFENClC
Page 201 and 202:
OAFlux Objectively Analyzed Air-Sea
Page 203 and 204:
Ashok, K., S. K. Behera, S. A. Rao,
Page 205 and 206:
Cangialosi, J. P., and L. A. Avila,
Page 207 and 208:
Francis, J. A., W. Chan, D. J. Leat
Page 209 and 210:
Hudson, J. M. G., and G. H. R. Henr
Page 211 and 212:
Landsea, C. W., and W. M. Gray, 199
Page 213 and 214:
Meinen, C. S., M. O. Baringer, and
Page 215 and 216:
Ramaswamy, V., M. D. Schwarzkopf, W
Page 217 and 218:
——, ——, T. C. Peterson, and
Page 219 and 220:
Wang, L., C. Derksen, and R. Brown,
Page 224:
Monthly average temperature anomali
show all

STATE OF THE CLIMATE IN 2009

Create successful ePaper yourself

Delete template?

Save as template?